WO2022042778A2 - Ultrasound elastography system for use as a diagnostic support tool for persons with muscle spasticity, and corresponding operating method - Google Patents
Ultrasound elastography system for use as a diagnostic support tool for persons with muscle spasticity, and corresponding operating method Download PDFInfo
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- WO2022042778A2 WO2022042778A2 PCT/CO2021/000010 CO2021000010W WO2022042778A2 WO 2022042778 A2 WO2022042778 A2 WO 2022042778A2 CO 2021000010 W CO2021000010 W CO 2021000010W WO 2022042778 A2 WO2022042778 A2 WO 2022042778A2
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Classifications
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/52—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/5215—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of medical diagnostic data
- A61B8/5223—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of medical diagnostic data for extracting a diagnostic or physiological parameter from medical diagnostic data
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/48—Diagnostic techniques
- A61B8/485—Diagnostic techniques involving measuring strain or elastic properties
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/52—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/5215—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of medical diagnostic data
- A61B8/5238—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of medical diagnostic data for combining image data of patient, e.g. merging several images from different acquisition modes into one image
- A61B8/5246—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of medical diagnostic data for combining image data of patient, e.g. merging several images from different acquisition modes into one image combining images from the same or different imaging techniques, e.g. color Doppler and B-mode
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/52—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/5292—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves using additional data, e.g. patient information, image labeling, acquisition parameters
Definitions
- the present invention consists of an ultrasonic elastography system, as a support tool for the evaluation of muscular spasticity, and its method of operation, which comprises a set of physical components, hardware, as well as a logical component that includes a computational interface. , configured to identify and differentiate muscle tissue, and infer the degree of spasticity of patients undergoing rehabilitation processes through parametric ultrasonography images.
- the system includes a linear ultrasound probe, fixed by means of a bracelet on the surface of the muscle area to be evaluated, with the prior application of an ultrasound gel; while the logical component includes an RF signal acquisition module, a two-dimensional image generation module and a Color map module (elastogram).
- This technological solution allows the recognition of muscle spasticity in "quasi real" time, through parametric ultrasound images, which quantify, in a color map superimposed on the conventional ultrasound image, the rate of deformation reached by the muscle fibers, muscle tone and estimation of the speed of a region of fiber contraction.
- the invention meets the need, in the physiotherapy and rehabilitation environment, to technicalize and automate, in a quantitative way, the clinical evaluation of patients affected by spasticity, constituting a technological support tool and thus facilitating parameterization in the opinion among specialists. evaluators of said pathology, by providing an objective measurement based on the reading of high-frequency acoustic signals and identification through parametric ultrasonography images quantified in a color mapz .
- the present invention is related to the field of current necessities of life and medical sciences; specifically devices, instruments and measures aimed at establishing an evaluation by means of radiation, ultrasonic waves, the movement of a whole body or parts thereof.
- Muscle spasticity is a neurological disorder characterized by increased muscle rigidity, as well as the alteration of involuntary contractions of a muscle group against its own stretching, causing the deterioration of voluntary movements and resulting in periods of affectation in body posture. , gait disturbances, communication disorders, difficulties in performing self-hygiene, sleep disturbances and the impact on self-esteem among others. Worldwide, it is estimated that approximately 12 million people are affected by muscle spasticity.
- spasticity is very important to provide a comprehensive treatment, which helps to minimize the pathophysiological effects at the spinal and muscular level, motor function, painful spasms and fixed osteoarticular contractures, among others.
- ultrasonic elastography equipment can be found in the state of the art, but they are specially designed to identify liver fibrosis, or perform breast elastography, but none of them have been configured with protocols or algorithms developed to detect muscle spasticity in human beings. alive.
- patent US2020054275A1 which consists of a system comprising a first detection unit, attached to a proximal part of a human body with a joint as a reference, to measure an acceleration of the proximal part or an angular velocity from the proximal part; a second detection unit, attached to a distal end portion of the human body, for measuring an acceleration of the distal end portion or an angular velocity of the distal end portion; a processing unit to determine an angle of the joint between the part proximal and distal end portion based on the measured acceleration or measured angular velocity and determining a spasticity time point at which resistance to movement of the distal end portion is received and a display configured to display spasticity information.
- spasticity assessment which will be used to measure spasticity based on joint angle and spasticity time.
- this invention is an electro-mechanical device, where there is no capture of high-frequency acoustic signals and the evaluation is not carried out through images.
- the invention US2017181689A1 discloses a method and system for measuring muscle tone, in which the muscle tone measurement system comprises a detection end and a processing end, and where the processing end is electrically connected to the sensing end and coupled with a mobile computing device, so that the sensing end is capable of detecting the force that is applied to the first part of the limb and a number of physical values of a movement, and the processing end be able to detect an ambient temperature and a number of physical values of a movement.
- the mobile calculation device is adapted to generate a spasticity level value according to an angle value and a speed value corresponding to a movement of the joint, the calculation device has two weighting matrices trained by using a machine learning method, where the machine learning method is an artificial neural network or a support vector machine.
- the machine learning method is an artificial neural network or a support vector machine.
- it is an electro-mechanical device, where there is no capture of high-frequency acoustic signals and the evaluation is not carried out through images.
- patent US2016317066A1 refers to a portable device that can quantify spasticity;
- the device is designed to fit different limb sizes and includes an accelerometer and force sensing resistor for quantitative data.
- the device further includes a data acquisition module where the collected data can be processed and sent to an output device.
- the invention relates to an optimal diagnostic tool to quantify spasticity in a clinical setting by measuring the three factors necessary to assess spasticity: the range of motion of the spastic limb, the speed of movement, and the force of resistance when twisting around a joint at a relatively constant speed.
- This invention does not implement the collection and reading of high-frequency acoustic signals by means of ultrasonic probes, nor does it identify the deformation rate reached by the muscle fibers, the muscle tone and the speed of fiber contraction by means of parametric ultrasonography images. , and because it does not allow the generation of two-dimensional images and the development of a color map.
- Patent CN105266806A refers to a spasticity evaluation system and device, but it is based on the myotatic reflex threshold value and the resistance variable.
- the device comprises a sensing head, a surface electromyogram, a computer, and a display screen.
- the sensing head integrates pressure, angle, speed, acceleration sensors and is connected with the computer via data line or Bluetooth.
- the surface electromyogram records the electromyographic signals of the muscles measured through surface electrodes.
- a computer analyzes the resistance variable of the extremities, the speed of the stretching activity and the acceleration generated during a stretching activity and records the joint angle of activation of the myotatic reflex, the program performs some equations and establishes the evaluation threshold.
- Patent W02010121353A1 has also been identified in the state of the art, which reveals a portable device for the quantitative measurement of spasticity in an articulated limb, which comprises a measurement module with an articulation angle sensor, the articulation sensor comprises two adjustable sections with a distal end and a proximal end that attaches to a central hinge, comprise a mechanism for securing one side of the joint to a first section and another side of the joint to a second section.
- angular rate sensor articulated measures the angular velocity of the first longitudinal section with respect to the second longitudinal section: and a muscle activity sensor for measuring the electrical activity of the muscle.
- This device also includes a control module with a processor that receives articulation angle and angular velocity data and is programmed to determine a spasticity value.
- This device includes a fixed orthosis that does not receive and process acoustic or ultrasonic signals that allow the pattern found to be plotted.
- Patent US9265451 B2 also discloses a system and a method for the quantitative measurement of spasticity in a patient and does so particularly by stretch reflex measurements, which are quantitatively indicative of spasticity. They can be obtained by recording an electromyography (EMG) signal while the limb is moving at a variety of angular velocities. Each movement of the limb from an initial to a final position does not need to be performed at a constant speed, and therefore the method advantageously allows the clinician to perform the test at the bedside by eliminating the need for cumbersome mechanical components to move the limb. extremity while providing quantitative measurements.
- EMG electromyography
- the system comprises a joint angle sensor capable of detecting angular movement in the limb, an angular velocity determinant, an EMG detector to measure stretch reflex activity, a spasticity evaluator module to process the angle and velocity data recorded. at the onset of stretch reflex activity.
- Patent US20091 18649A1 for its part, provides an apparatus for evaluating a hypertonic condition such as spasticity in a limb.
- the device includes an accelerometer, a gyroscope and a pressure sensor.
- a base is provided on the apparatus on which the accelerometer, gyroscope and pressure sensor are mounted.
- the apparatus further includes a data communication device adapted to transmit data signals from said accelerometer, said gyroscope and said pressure sensor. The data transmitted from the The device can be processed locally during therapy or rehabilitation sessions to provide the examiner or patient with real-time status information.
- the apparatus comprises an apparatus for simulating movement of a limb having a hypertonic condition.
- the apparatus includes an electric motor adapted to be driven by a voltage control, the parameters for programming the simulator being obtained from a previously fed database.
- patent US2020196902A1 protects a method for measuring spasticity that includes: obtaining detection signals corresponding to a movement of the limb through at least one sensor over a period of time; transform the detection signals into a two-dimensional image; and inputting the two-dimensional image into a conventional neural network to generate a spasticity determination result, the calculation circuit generates the two-dimensional image according to an equation.
- this invention does not identify, through qualified ultrasonography parametric images in a color map, the deformation rate reached by the muscle fibers, the muscle tone and the speed of fiber contraction; it does not implement an ultrasonic probe to measure the reading of high-frequency acoustic signals to directly feed a computational interface, but rather captures the signals by means of sensors.
- Figure 1 Schematic view of the ultrasonic elastography system as a support tool for the diagnosis of muscle spasticity.
- FIG. 1A Image of radiofrequency signals acquired
- Figure 3 Two-dimensional image constructed from radiofrequency signals. Where you can see: (1). Epidermis. (two). Muscle fascia. (3). Biceps. (4). Brachial fascia. (5). Brachial. (6). Humerus.
- Figure 4 Image of a Color Map (Elastogram) superimposed on the two-dimensional image.
- Figure 8 View of the contrast options in the image in the “ultrasound” section.
- Figure 10 View of an example of axial elastogram
- Figure 1 1 View of an example of a lateral elastogram
- the invention presented consists of an ultrasonic elastography system, as a diagnostic support tool in people with muscular spasticity that allows the identification and differentiation of spastic muscle tissue in "quasi real" time, through parametric ultrasonography images, which quantify in a color map superimposed on a conventional ultrasound image, the rate of strain achieved by muscle fibers, muscle tone, and the estimation of the speed of a region of fiber contraction.
- This system is characterized in that it comprises a linear ultrasound probe (100), a bracelet (200), which couples and holds the linear ultrasound probe (100) on the muscle area to be evaluated; an ultrasound gel (300) applied to the surface of the muscle area to be evaluated; and a logical interface, executed from a laptop (400), through which the reading of the high-frequency acoustic signals is performed, obtained by the linear ultrasound probe (100), to establish a quantification of the degree of rigidity muscle (muscle tone), and infer the degree of spasticity of patients in rehabilitation processes.
- the logical interface executed from a laptop (400) includes an RF signal acquisition module (410), a two-dimensional image generation module (420) and a virtual color map module (elastogram) (430) .
- the linear ultrasound probe (100) consists of a probe for medical use, preferably portable, that builds two-dimensional image arrays, with a dynamic depth range of 0.1 to 10 cm, has a width of band that includes 5MHz to 10 MHz and meets the following minimum specifications:
- the ultrasound gel (300) consists of a viscous solution, preferably composed of water and propylene glycol, and is the acoustic coupling medium between the ultrasound probe and the patient's skin. Eliminates air pockets between the transducer and the skin that can obstruct the passage of high-frequency mechanical waves to the analysis tissue.
- the bracelet (200) consists of an accessory that has a special design and configuration that acts as a support means for the probe, depending on its shape. Contains elastic bands, attached to a plastic buckle to attach to the biceps brachii. In other embodiments, the shape of the bracelet varies to adjust to the area or surface on which the signals are taken.
- the laptop has a capacity of at least ⁇ 5-5200U, and a Processor of at least 2.2 GHz, 3 MB. This so that it can correctly execute the logical interface; where said interface includes:
- An RF signal acquisition module (410), as can be seen in FIG. 2. Developed from Visual Studio with tools for the collection of radio frequency signals (RF) in time intervals and number of specific signals.
- SDK is the application programming interface or API (from the English application programming interface) created to allow the use of a certain programming language, in addition, to include sophisticated hardware in order to communicate with a certain embedded system.
- the most common software development tools include support for bug detection such as an integrated development environment (IDE) and other utilities.
- SDKs often have example code and supporting technotes or other supporting documentation to help clarify certain points in the primary reference material.
- IDE integrated development environment
- SDKs often have example code and supporting technotes or other supporting documentation to help clarify certain points in the primary reference material.
- radiofrequency signals will be stored in a .csv file automatically according to the number of data established during a certain period.
- the operator In order to take the mechanical signals in the radiofrequency range, through an ultrasonic probe, and access the collection of radiofrequency signals, the operator must start scanning the signals from the Visual Studio platform from which the acquired records will be directed to a destination file established by the software.
- the execution of the module begins in the first class called ⁇ RF>, which carries an association or sequence to the second step called ⁇ Scan 2D>, where the user chooses the ⁇ Play> option to start the scanning and acquisition of radio signals.
- radiofrequency which inherits processes from the ⁇ Scan 2D> class (Class where the signal acquisition time and number of data to be processed are processed).
- the user is free to choose the ⁇ Freeze> option whenever he considers that the operation of the procedure should stop.
- the generation process begins when an electrical pulse is applied to the piezoelectric crystal electrodes of the transducer. A vibration is produced and the ultrasonic beam is transmitted, which is subsequently transmitted and reflected by the tissues. When the energy returns to the emitter (transducer) vibrations are produced in the crystal which will become electric current and later, when amplified, they will be transformed into images.
- the operator To access the generation of the acoustic elastogram, the operator must select the reference signal (Signal and Image in Extension), which will be associated with the displaced signal (Signal and Image in Flexion), as can be seen in Fig. FIG. 2A
- FIG 3 a view of the construction of two-dimensional images from the radiofrequency signals acquired from the musculoskeletal tissue is shown, where it can be seen: (1). Epidermis. (two). Muscle fascia. (3). Biceps. (4). Brachial fascia. (5). Brachial. (6). Humerus.
- a Color Map module (Elastoarama) (430): Developed with algorithmic processes for the development of a color map (elastogram on the two-dimensional image), which through a displacement estimation method and using dynamic programming has the capacity to overcome discontinuities on the elastography image; that is, this algorithm provides true displacements on the elastogram.
- FIG 4. Shows a color map (Elastogram) superimposed on the two-dimensional image.
- the exhaustive block search is represented by the sum of absolute differences (SAD) function, used to determine the difference between two signals A.
- SAD absolute differences
- g(i) and g'(i+d) represent the initial and deformed RF data respectively.
- dmin ⁇ d ⁇ dmax are the displacements of the matrix represented in i.
- the grayscale elastogram on musculoskeletal tissue is shown, performing the elastography algorithm in two dimensions, where it is determined that despite the cost function to reduce the discontinuity on the signal matrix, this processing ends with an error of 10 % on the resulting elastogram.
- the ultrasound probe delivers a file in comma-separated values or CSV format and it is necessary to transform them to obtain the image.
- the color map (elastogram) module (430) allows comparing two ultrasounds that are captured at the maximum moments of flexion and extension of the muscle and generates a gradient with which a relative elastogram is made. Finally, it overlays the obtained elastogram and the ultrasound image.
- the system generates the report combining the evaluated data with their respective processed elastograms in text document format.
- the proposed architecture also allows viewing and storing acoustic images for the creation of repositories, which allow training, testing and validating classification algorithms.
- the images Once the images are converted to raw format, they are adapted by the Image Processing module, which performs the following operations: Logarithmic scaling, Dynamic equalization of the range of the images, Filtering and Scaling of the image.
- FIG. 5 shows the interface designed for system operation. As can be seen in said figure, it consists of several sections (tabs) through which the various modules that make up the system are executed.
- the first tab of the interface allows the capture of the information of the patient or evaluated in two separate blocks: “Personal information” and “Test information”.
- All this information is optional and can be used for evolutionary monitoring purposes or for the registration of the report generated by the system. It shows the screen with the form for capturing the evaluated information.
- the valued information is separated into two blocks: Personal Information and Test Information.
- the second block is mandatory.
- the interface allows you to record the following specific information:
- the “Exit” button allows the closing of the application while the “Next” button has the equivalent effect of pressing on the title of the next tab in the application: opening the “Ultrasound” tab in this case.
- FIG. 6 shows the view of the second tab of the interface, called “ultrasound", from which the signal acquisition module is executed and its purpose is to load the files in ".csv” format from the initial moments and end of the radiofrequency signals (generally maximum flexion and extension of the muscle).
- the upload process triggers the processing of the file for conversion to grayscale ultrasound images.
- the “.csv” format is the numerical data coming from the RF signals, made up of a matrix arrangement from which the two-dimensional image is built.
- Imadjust is a function of the system that saturates 1% of the highest and lowest value of all pixels in the image to increase contrast.
- FIG. 8 Shows a view of the contrast options on the image in the “ultrasound” section.
- the procedure must be carried out in the same way for the two ultrasound images corresponding to the initial and final moments.
- the “Exit” button allows the closing of the application; the “Back” button allows you to return to the first tab; and the “Next” button has the equivalent effect of clicking on the title of the third tab of the application: open the “Elastography and measurements” tab.
- buttons 9 and 10 allow elastograms to be generated in the axial and sagittal planes from the gradient calculated for each plane between the ultrasound images of the two evaluation moments, as shown in Figures 9 and 10.
- the “Exit” button allows the closing of the application; the “Back” button allows you to return to the first tab; and the “Next” button, has the equivalent effect of clicking on the title of the third tab of the application: opening the “Overlay” tab.
- FIG. 1 1 shows a view of an example "Superimposition", in which the action of superimposing the elastogram obtained with the image of the final moment is executed, in order to identify and relate the effort and muscular deformation in a caulitative way.
- the section includes four different overlay schemes:
- Alpha blending in which images are scaled in size and dimension n and then added together at equal weights. Difference, where the images are scaled in size and dimension n and then subtracted from each other.
- Pseudocolor where a homogeneous mask is applied to both images in order to highlight the "empty spaces" by extrapolation of maximums and minimums.
- the system determines the results, presenting a descriptive statistical analysis that represents the percentage of variation of pixels and a box diagram that shows the values of pixels on the same region for each evaluated limb of the patients. with spasticity.
- Figure 13 shows an example of the presentation of results with the statistical distribution based on the coefficient of variation.
- the arm with spastic hemiplegia presents a large percentage minority; indicating a lower coefficient of variation due to the low variability of pixels in the region of interest with respect to the arm without any alteration of muscle tone, which has a higher percentage, that is, a higher coefficient of variation.
- This stage includes loading, in the "Ultrasound” section, the data in .CVS format of the ultrasound signals in flexion and in extension taken by the linear probe (100); where once the signals are loaded they are converted into images and their contrast can be adjusted according to three parameters: imadjust, Histeq and Adapthisteq. c.) Generation of elastograms:
- This stage includes generating, in the “Elastography and Measurements” section, the elastograms in the axial and sagittal planes from the gradient calculated for each plane between the ultrasound images of the two evaluation moments. d.) elastogram overlay:
- This stage includes superimposing, in the "Overlay” section, the elastogram obtained with the image of the final moment, and identifying and relating the effort and muscular deformation in a caulitative manner; where said step includes the four different overlapping schemes previously explained. d) Presentation of results.
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Abstract
The invention relates to an ultrasound elastography system for use as a diagnostic support tool for persons with muscle spasticity, and to the corresponding operating method, characterised in that it comprises a linear ultrasound probe, a bracelet for connecting and securing the linear ultrasound probe to the muscle area to be evaluated, ultrasound gel applied to the surface of the muscle area to be evaluated, and a logical interface, run from a laptop computer, which is used to read high-frequency acoustic signals obtained by the linear ultrasound probe, in order to quantify the degree of muscle stiffness (muscle tone), and deduce the degree of spasticity in patients undergoing rehabilitation. According to the invention, the logical interface, run from a laptop, includes an RF signal acquisition module, a two-dimensional image generation module, and a virtual colour map module (elastogram).
Description
SISTEMA DE ELASTOGRAFÍA ULTRASÓNICA COMO HERRAMIENTA DE APOYO DIAGNÓSTICO EN PERSONAS CON ESPASTICIDAD MUSCULAR, Y SU MÉTODO DE OPERACIÓN. ULTRASONIC ELASTOGRAPHY SYSTEM AS A DIAGNOSTIC SUPPORT TOOL IN PEOPLE WITH MUSCULAR SPASTICITY, AND ITS METHOD OF OPERATION.
DESCRIPCIÓNDESCRIPTION
OBJETO DE LA INVENCIÓN (DESCRIPCIÓN BREVE) OBJECT OF THE INVENTION (BRIEF DESCRIPTION)
La presenta invención consiste en un sistema de elastografía ultrasónica, como herramienta de apoyo a la evaluación de la espasticidad muscular, y su método de operación, que comprende un conjunto de componentes físicos, hardware, así como de un componente lógico que incluye una interfaz computacional, configurados para identificar y diferenciar el tejido muscular, e inferir el grado de espasticidad de pacientes en procesos de rehabilitación a través de imágenes paraméthcas de ultrasonografía. El sistema incluye una sonda lineal de ultrasonido, fijado mediante un brazalete sobre la superficie de la zona muscular a ser evaluada, con la aplicación previa de un gel ecográfico; mientras que el componente lógico incluye un módulo de adquisición de señales RF, un módulo de generación de imágenes bidimensionales y un módulo de mapa de Colores (elastograma). The present invention consists of an ultrasonic elastography system, as a support tool for the evaluation of muscular spasticity, and its method of operation, which comprises a set of physical components, hardware, as well as a logical component that includes a computational interface. , configured to identify and differentiate muscle tissue, and infer the degree of spasticity of patients undergoing rehabilitation processes through parametric ultrasonography images. The system includes a linear ultrasound probe, fixed by means of a bracelet on the surface of the muscle area to be evaluated, with the prior application of an ultrasound gel; while the logical component includes an RF signal acquisition module, a two-dimensional image generation module and a Color map module (elastogram).
Esta solución tecnológica permite el reconocimiento de la espasticidad muscular en tiempo “cuasi real”, a través de imágenes paramétricas de ultrasonografía, que cuantifican, en un mapa de colores superpuesto en la imagen ecográfica convencional, la tasa de deformación alcanzada por las fibras musculares, el tono muscular y la estimación de la velocidad de una región de contracción de fibras. La invención atiende la necesidad, en el entorno fisioterapéutico y de rehabilitación, de tecnificar y automatizar, de manera cuantitativa, la evaluación clínica de pacientes afectados por espasticidad, constituyéndose en una herramienta tecnológica de apoyo y facilitando así una parametrización en el dictamen entre los especialistas evaluadores de dicha patología, al proporcionar una medición objetiva basada en la lectura de señales acústicas de alta frecuencia y la identificación a través de imágenes paramétricas de ultrasonografía cuantificadas en un mapa de coloresz .
SECTOR TÉCNICO DE LA INVENCIÓN This technological solution allows the recognition of muscle spasticity in "quasi real" time, through parametric ultrasound images, which quantify, in a color map superimposed on the conventional ultrasound image, the rate of deformation reached by the muscle fibers, muscle tone and estimation of the speed of a region of fiber contraction. The invention meets the need, in the physiotherapy and rehabilitation environment, to technicalize and automate, in a quantitative way, the clinical evaluation of patients affected by spasticity, constituting a technological support tool and thus facilitating parameterization in the opinion among specialists. evaluators of said pathology, by providing an objective measurement based on the reading of high-frequency acoustic signals and identification through parametric ultrasonography images quantified in a color mapz . TECHNICAL FIELD OF THE INVENTION
La presente invención está relacionada con el campo de necesidades corrientes de la vida y las ciencias médicas; específicamente aparatos, instrumentos y medidas encaminadas a establecer una evaluación por medio de radiaciones, ondas ultrasónicas el movimiento de un cuerpo entero o de partes del mismo. The present invention is related to the field of current necessities of life and medical sciences; specifically devices, instruments and measures aimed at establishing an evaluation by means of radiation, ultrasonic waves, the movement of a whole body or parts thereof.
ESTADO DE LA TÉCNICA ANTERIOR O ANTECEDENTES DE LA INVENCIÓN PRIOR STATE OF THE ART OR BACKGROUND OF THE INVENTION
La espasticidad muscular es un trastorno neurológico caracterizado por el incremento de la rigidez muscular, así como la alteración de contracciones involuntarias de un grupo muscular frente a su propio estiramiento, provocando el deterioro de los movimientos voluntarios y derivando en periodos de afectación en la postura corporal, alteraciones de la marcha, trastornos en la comunicación, dificultades para realizar la auto higiene, alteraciones del sueño y la repercusión en la autoestima entre otras. Se estima que, a nivel mundial, aproximadamente 12 millones de personas se ven afectadas a causa de la espasticidad muscular. Muscle spasticity is a neurological disorder characterized by increased muscle rigidity, as well as the alteration of involuntary contractions of a muscle group against its own stretching, causing the deterioration of voluntary movements and resulting in periods of affectation in body posture. , gait disturbances, communication disorders, difficulties in performing self-hygiene, sleep disturbances and the impact on self-esteem among others. Worldwide, it is estimated that approximately 12 million people are affected by muscle spasticity.
La valoración clínica la espasticidad es muy importante para suministrar un tratamiento integral, que contribuya a minimizar los efectos fisiopatológicos a nivel espinal y muscular, la función motora, los espasmos dolorosos y las contracturas fijas osteoarticulares entre otras. The clinical assessment of spasticity is very important to provide a comprehensive treatment, which helps to minimize the pathophysiological effects at the spinal and muscular level, motor function, painful spasms and fixed osteoarticular contractures, among others.
Actualmente, una de las herramientas de apoyo a la valoración clínica del grado de espasticidad muscular, es la escala de “ashworth modificada”, la cual es ampliamente utilizada; sin embargo su fiabilidad es ampliamente cuestionada debido al grado de subjetividad (dependiente del observador), por la carencia de normativas estándar para su aplicación y por sus limitaciones en el monitoreo continuo y la medición de los efectos en el proceso de rehabilitación de pacientes con espasticidad.
En este sentido, la mayoría de las herramientas disponibles en el estado de la técnica, para la evaluación de la espasticidad muscular, se basan en la subjetividad del profesional que realiza la observación de dicho trastorno; otros sistemas disponibles en el mercado se basan en electromiografía (EMG), y la gran mayoría requieren que el profesional realice movimientos en la extremidad del paciente a diferentes velocidades para adquirir el valor de la espasticidad, y algunos otros poseen motores o dispositivos para simular el movimiento en la extremidad con espasticidad, pero ninguno de los productos o equipos realiza una medición basada en la lectura de señales acústicas de alta frecuencia y la identificación a través de imágenes paramétricas de ultrasonografía cuantificadas en un mapa de colores. Currently, one of the support tools for the clinical assessment of the degree of muscle spasticity is the "modified Ashworth" scale, which is widely used; however, its reliability is widely questioned due to the degree of subjectivity (depending on the observer), the lack of standard regulations for its application and its limitations in continuous monitoring and measurement of the effects in the rehabilitation process of patients with spasticity. . In this sense, most of the tools available in the state of the art, for the evaluation of muscular spasticity, are based on the subjectivity of the professional who observes said disorder; other systems available on the market are based on electromyography (EMG), and the vast majority require the professional to perform movements on the patient's limb at different speeds to acquire the value of spasticity, and some others have motors or devices to simulate the movement in the limb with spasticity, but none of the products or equipment performs a measurement based on the reading of high-frequency acoustic signals and identification through parametric ultrasonography images quantified on a color map.
Adicionalmente, diversos equipos de elastografía ultrasónica pueden encontrarse en el estado de la técnica, pero los mismos son diseñados especialmente para identificar fibrosis hepática, o realizar elastografía mamaria pero ninguno de ellos ha sido configurado con protocolos o algoritmos desarrollados para detectar la espasticidad muscular en seres vivos. Additionally, various ultrasonic elastography equipment can be found in the state of the art, but they are specially designed to identify liver fibrosis, or perform breast elastography, but none of them have been configured with protocols or algorithms developed to detect muscle spasticity in human beings. alive.
De los diversos sistemas o equipos desarrollados para realizar la evaluación de la espasticidad muscular ninguno implementa un sistema de lectura de señales acústicas de alta frecuencia, ni identifican a través de imágenes paramétricas de ultrasonografía cuantificadas en un mapa de colores, la tasa de deformación alcanzada por las fibras musculares, el tono muscular y la velocidad de contracción de fibras. Of the various systems or equipment developed to assess muscle spasticity, none implement a system for reading high-frequency acoustic signals, nor do they identify, through parametric ultrasonography images quantified on a color map, the rate of deformation reached by muscle fibers, muscle tone and fiber contraction speed.
Un ejemplo de lo anteriormente descrito es la patente US2020054275A1 que consiste en un sistema que comprende una primera unidad de detección, unida a una parte proximal de un cuerpo humano con una articulación como referencia, para medir una aceleración de la parte proximal o una velocidad angular de la parte proximal; una segunda unidad de detección, unida a una parte del extremo distal del cuerpo humano, para medir una aceleración de la parte del extremo distal o la velocidad angular de la parte del extremo distal; una unidad de procesamiento para determinar un ángulo de la articulación entre la parte
proximal y la parte del extremo distal sobre la base de la aceleración medida o la velocidad angular medida y determinar un punto de tiempo de espasticidad en el que se recibe la resistencia al movimiento de la parte del extremo distal y una pantalla configurada para mostrar información de evaluación de la espasticidad, que se utilizará para medir la espasticidad en función del ángulo de la articulación y el tiempo de espasticidad. Básicamente esta invención es un dispositivo electro-mecánico, donde no hay captación de señales acústicas de alta frecuencia y la evaluación no se realiza a través de imágenes An example of what is described above is patent US2020054275A1, which consists of a system comprising a first detection unit, attached to a proximal part of a human body with a joint as a reference, to measure an acceleration of the proximal part or an angular velocity from the proximal part; a second detection unit, attached to a distal end portion of the human body, for measuring an acceleration of the distal end portion or an angular velocity of the distal end portion; a processing unit to determine an angle of the joint between the part proximal and distal end portion based on the measured acceleration or measured angular velocity and determining a spasticity time point at which resistance to movement of the distal end portion is received and a display configured to display spasticity information. spasticity assessment, which will be used to measure spasticity based on joint angle and spasticity time. Basically this invention is an electro-mechanical device, where there is no capture of high-frequency acoustic signals and the evaluation is not carried out through images.
En este mismo sentido, la invención US2017181689A1 revela un método y sistema para medir el tono muscular, en el que el sistema de medición del tono muscular comprende un extremo de detección y un extremo de procesamiento, y donde el extremo de procesamiento está conectado eléctricamente al extremo de detección y acoplado con un dispositivo de cálculo móvil, de modo que el extremo de detección sea capaz de detectar la fuerza que se aplica a la primera parte de la extremidad y una cantidad de valores físicos de un movimiento, y el extremo de procesamiento sea capaz de detectar una temperatura ambiente y una cantidad de valores físicos de un movimiento. El dispositivo de cálculo móvil está adaptado para generar un valor de nivel de espasticidad de acuerdo con un valor de ángulo y un valor de velocidad correspondiente a un movimiento de la articulación, el dispositivo de cálculo cuenta con dos matrices de ponderación entrenadas mediante el uso de un método de aprendizaje automático, donde el método de aprendizaje automático es una red neuronal artificial o una máquina de vectores de soporte. Al igual que la anterior invención, se trata de un dispositivo electro-mecánico, donde no hay captación de señales acústicas de alta frecuencia y la evaluación no se realiza a través de imágenes. In this same sense, the invention US2017181689A1 discloses a method and system for measuring muscle tone, in which the muscle tone measurement system comprises a detection end and a processing end, and where the processing end is electrically connected to the sensing end and coupled with a mobile computing device, so that the sensing end is capable of detecting the force that is applied to the first part of the limb and a number of physical values of a movement, and the processing end be able to detect an ambient temperature and a number of physical values of a movement. The mobile calculation device is adapted to generate a spasticity level value according to an angle value and a speed value corresponding to a movement of the joint, the calculation device has two weighting matrices trained by using a machine learning method, where the machine learning method is an artificial neural network or a support vector machine. Like the previous invention, it is an electro-mechanical device, where there is no capture of high-frequency acoustic signals and the evaluation is not carried out through images.
De otra parte la patente US2016317066A1 se refiere a un dispositivo portátil que puede cuantificar la espasticidad; el dispositivo está diseñado para adaptarse a diferentes tamaños de extremidades e incluye un acelerómetro y una resistencia de detección de fuerza para obtener datos cuantitativos. El dispositivo incluye además un módulo de adquisición de datos donde los datos recopilados se pueden procesar y enviar a un dispositivo de salida. La invención se refiere a
una herramienta de diagnóstico óptima para cuantificar la espasticidad en un entorno clínico midiendo los tres factores necesarios para evaluar la espasticidad: el rango de movimiento de la extremidad espástica, la velocidad de movimiento y la fuerza de resistencia cuando se gira alrededor de una articulación a una velocidad relativamente constante. En esta invención no se implementa la colecta y lectura de señales acústicas de alta frecuencia, mediante sondas ultrasónicas, ni identifica la tasa de deformación alcanzada por las fibras musculares, el tono muscular y la velocidad de contracción de fibras por medio de imágenes paramétricas de ultrasonografía, y por no permite generar imágenes bidimensionales y el desarrollo de un mapa de colores. On the other hand, patent US2016317066A1 refers to a portable device that can quantify spasticity; The device is designed to fit different limb sizes and includes an accelerometer and force sensing resistor for quantitative data. The device further includes a data acquisition module where the collected data can be processed and sent to an output device. The invention relates to an optimal diagnostic tool to quantify spasticity in a clinical setting by measuring the three factors necessary to assess spasticity: the range of motion of the spastic limb, the speed of movement, and the force of resistance when twisting around a joint at a relatively constant speed. This invention does not implement the collection and reading of high-frequency acoustic signals by means of ultrasonic probes, nor does it identify the deformation rate reached by the muscle fibers, the muscle tone and the speed of fiber contraction by means of parametric ultrasonography images. , and because it does not allow the generation of two-dimensional images and the development of a color map.
La patente CN105266806A se refiere a un sistema y dispositivo de evaluación de la espasticidad, pero está basado en el valor umbral del reflejo miotático y la variable de resistencia. El dispositivo comprende un cabezal de detección, un electromiograma de superficie, una computadora y una pantalla de visualización. El cabezal de detección integra sensores de presión, ángulo, velocidad, aceleración y está conectado con la computadora a través de una línea de datos o Bluetooth. El electromiograma de superficie registra las señales electromiográficas de los músculos medidos a través de electrodos de superficie. Una computadora analiza la variable de resistencia de las extremidades, la velocidad de la actividad de estiramiento y la aceleración generada durante una actividad de estiramiento y registra el ángulo articular de activación del reflejo miotático, el programa realiza unas ecuaciones y establece el umbral del evaluación. Patent CN105266806A refers to a spasticity evaluation system and device, but it is based on the myotatic reflex threshold value and the resistance variable. The device comprises a sensing head, a surface electromyogram, a computer, and a display screen. The sensing head integrates pressure, angle, speed, acceleration sensors and is connected with the computer via data line or Bluetooth. The surface electromyogram records the electromyographic signals of the muscles measured through surface electrodes. A computer analyzes the resistance variable of the extremities, the speed of the stretching activity and the acceleration generated during a stretching activity and records the joint angle of activation of the myotatic reflex, the program performs some equations and establishes the evaluation threshold.
También se ha identificado en el estado de la técnica la patente W02010121353A1 , que revela un dispositivo portátil para la medición cuantitativa de la espasticidad en una extremidad articulada, que comprende un módulo de medición con un sensor de ángulo de articulación, el sensor de articulación comprende dos secciones que se pueden ajustar con un extremo distal y un extremo proximal que se une a una bisagra central, comprenden un mecanismo para asegurar un lado de la articulación a una primera sección y otro lado de la articulación a una segunda sección. El sensor de velocidad angular
articulado mide la velocidad angular de la primera sección longitudinal con respecto a la segunda sección longitudinal: y un sensor de actividad muscular para medir la actividad eléctrica del músculo. Patent W02010121353A1 has also been identified in the state of the art, which reveals a portable device for the quantitative measurement of spasticity in an articulated limb, which comprises a measurement module with an articulation angle sensor, the articulation sensor comprises two adjustable sections with a distal end and a proximal end that attaches to a central hinge, comprise a mechanism for securing one side of the joint to a first section and another side of the joint to a second section. angular rate sensor articulated measures the angular velocity of the first longitudinal section with respect to the second longitudinal section: and a muscle activity sensor for measuring the electrical activity of the muscle.
Comprende también módulo de control con un procesador que recibe datos de ángulo de articulación y velocidad angular y está programado para determinar un valor de espasticidad. Este disposivtivo incluye una órtesis fija que no recibe y procesa señales acústicas o ultrasónicas que permitan graficar el patrón encontrado. It also includes a control module with a processor that receives articulation angle and angular velocity data and is programmed to determine a spasticity value. This device includes a fixed orthosis that does not receive and process acoustic or ultrasonic signals that allow the pattern found to be plotted.
La patente US9265451 B2 también divulga un sistema y un método para la medición cuantitativa de la espasticidad en un paciente y lo hace particularmente mediante las mediciones del reflejo de estiramiento, que son cuantitativamente indicativas de espasticidad. Se pueden obtener registrando una señal de electromiografía (EMG) mientras la extremidad se mueve a una variedad de velocidades angulares. Cada movimiento de la extremidad desde una posición inicial a una final no necesita realizarse a una velocidad constante y, por lo tanto, el método permite ventajosamente al médico realizar la prueba al lado de la cama al eliminar la necesidad de componentes mecánicos engorrosos para mover la extremidad mientras proporciona mediciones cuantitativas. El sistema comprende, un sensor de ángulo articular capaz de detectar movimiento angular en la extremidad, un determinante de velocidad angular, un detector EMG para medir la actividad del reflejo de estiramiento, un módulo evaluador de espasticidad para procesar el ángulo y datos de velocidad registrados al inicio de la actividad del reflejo de estiramiento. Patent US9265451 B2 also discloses a system and a method for the quantitative measurement of spasticity in a patient and does so particularly by stretch reflex measurements, which are quantitatively indicative of spasticity. They can be obtained by recording an electromyography (EMG) signal while the limb is moving at a variety of angular velocities. Each movement of the limb from an initial to a final position does not need to be performed at a constant speed, and therefore the method advantageously allows the clinician to perform the test at the bedside by eliminating the need for cumbersome mechanical components to move the limb. extremity while providing quantitative measurements. The system comprises a joint angle sensor capable of detecting angular movement in the limb, an angular velocity determinant, an EMG detector to measure stretch reflex activity, a spasticity evaluator module to process the angle and velocity data recorded. at the onset of stretch reflex activity.
La patente US20091 18649A1 por su parte, proporciona un aparato para evaluar una condición hipertónica tal como espasticidad en una extremidad. El aparato incluye un acelerómetro, un giroscopio y un sensor de presión. En el aparato se proporciona una base en la que se montan el acelerómetro, el giroscopio y el sensor de presión. El aparato incluye además un dispositivo de comunicación de datos adaptado para transmitir señales de datos desde dicho acelerómetro, dicho giroscopio y dicho sensor de presión. Los datos transmitidos desde el
aparato se pueden procesar localmente durante las sesiones de terapia o rehabilitación para proporcionar al examinador o al paciente información en tiempo real sobre el estado. Patent US20091 18649A1 for its part, provides an apparatus for evaluating a hypertonic condition such as spasticity in a limb. The device includes an accelerometer, a gyroscope and a pressure sensor. A base is provided on the apparatus on which the accelerometer, gyroscope and pressure sensor are mounted. The apparatus further includes a data communication device adapted to transmit data signals from said accelerometer, said gyroscope and said pressure sensor. The data transmitted from the The device can be processed locally during therapy or rehabilitation sessions to provide the examiner or patient with real-time status information.
Comprende un aparato para simular el movimiento de una extremidad que tiene una condición hipertónica. El aparato según este aspecto incluye un motor eléctrico adaptado para ser accionado por un control de voltaje, los parámetros para programar el simulador se obtienen de una base de datos alimentada anteriormente. It comprises an apparatus for simulating movement of a limb having a hypertonic condition. The apparatus according to this aspect includes an electric motor adapted to be driven by a voltage control, the parameters for programming the simulator being obtained from a previously fed database.
Finalmente la patente US2020196902A1 protege un método para medir la espasticidad que incluye: obtener señales de detección correspondientes a un movimiento de la extremidad a través de al menos un sensor durante un período de tiempo; transformar las señales de detección en una imagen bidlmensional; e ingresar la imagen bidlmensional en una red neuronal convencional para generar un resultado de determinación de espasticidad, el circuito de cálculo genera la imagen bidlmensional de acuerdo con una ecuación. Sin embargo ésta invención No identifica a través de imágenes paramétricas de ultrasonografía cualificadas en un mapa de colores, la tasa de deformación alcanzada por las fibras musculares, el tono muscular y la velocidad de contracción de fibras; no implementa una sonda ultrasónica para medir la lectura de señales acústicas de alta frecuencia para alimentar directamente una interfaz computacional, sino que capta las señales por medio de sensores. Finally, patent US2020196902A1 protects a method for measuring spasticity that includes: obtaining detection signals corresponding to a movement of the limb through at least one sensor over a period of time; transform the detection signals into a two-dimensional image; and inputting the two-dimensional image into a conventional neural network to generate a spasticity determination result, the calculation circuit generates the two-dimensional image according to an equation. However, this invention does not identify, through qualified ultrasonography parametric images in a color map, the deformation rate reached by the muscle fibers, the muscle tone and the speed of fiber contraction; it does not implement an ultrasonic probe to measure the reading of high-frequency acoustic signals to directly feed a computational interface, but rather captures the signals by means of sensors.
Considerando lo anterior se requiere desarrollar una solución que atienda la necesidad en el entorno fisioterapéutico y de rehabilitación para tecnificar y automatizar de manera cuantitativa y objetiva, la evaluación clínica de pacientes afectados por espasticidad. Considering the above, it is necessary to develop a solution that meets the need in the physiotherapy and rehabilitation environment to technify and automate in a quantitative and objective way, the clinical evaluation of patients affected by spasticity.
Principalmente se necesita proveer soluciones alternativas para de tecnificación en el proceso de valoración del grado de espasticidad (incremento de la rigidez muscular) para facilitar la evaluación clínica y determinar los cambios estructurales del musculo, la deformación alcanzada por las fibras musculares después de aplicar estímulos externo y las velocidades de contracción muscular,
que actualmente son fundamentados en métodos no instrumentales (subjetivos) y algunos métodos invasivos (electromiografía).
Mainly, it is necessary to provide alternative solutions for technification in the process of assessing the degree of spasticity (increased muscle stiffness) to facilitate clinical evaluation and determine the structural changes of the muscle, the deformation reached by the muscle fibers after applying external stimuli and speeds of muscle contraction, which are currently based on non-instrumental (subjective) methods and some invasive methods (electromyography).
DESCRIPCIÓN DE LAS FIGURAS DESCRIPTION OF THE FIGURES
Figura 1. Vista esquemática del sistema de elastografía ultrasónica como herramienta de apoyo al diagnóstico de la espasticidad muscular. Figure 1. Schematic view of the ultrasonic elastography system as a support tool for the diagnosis of muscle spasticity.
Figura 2. Imagen módulo de adquisición de señales RF. Figure 2. RF signal acquisition module image.
Figura 2A. Imagen de señales de radiofrecuencia adquiridas Figure 2A. Image of radiofrequency signals acquired
Figura 3. Imagen bidimensional construida a partir de las señales de radiofrecuencia. Donde se aprecia: (1 ). Epidermis. (2). Fascia Muscular. (3). Bíceps. (4). Fascia Braquial. (5). Braquial. (6). Humero. Figure 3. Two-dimensional image constructed from radiofrequency signals. Where you can see: (1). Epidermis. (two). Muscle fascia. (3). Biceps. (4). Brachial fascia. (5). Brachial. (6). Humerus.
Figura 4. Imagen de un Mapa de colores (Elastograma) superpuesto sobre la imagen bidimensional. Figure 4. Image of a Color Map (Elastogram) superimposed on the two-dimensional image.
Figura 5. Imagen de la interfaz para la operación del sistema, específicamente la sección “información del valorado.” Figure 5. Image of the interface for system operation, specifically the “valued information” section.
Figura 6. Imagen de e la interfaz para la operación del sistema, específicamente la sección “ultrasonido.” Figure 6. Image of the interface for system operation, specifically the “ultrasound” section.
Figura 7. Imagen del proceso de Carga de archivos .CSV en la sección “ultrasonido.” Figure 7. Image of the .CSV file upload process in the “ultrasound” section.
Figura 8. Vista de las opciones de contraste en la imagen en la sección “ultrasonido.” Figure 8. View of the contrast options in the image in the “ultrasound” section.
Figura 9. Imagen de e la interfaz para la operación del sistema, específicamente la sección Elastografía y Mediciones” Figure 9. Image of the interface for system operation, specifically the Elastography and Measurements section
Figura 10. Vista de un ejemplo de elastograma axial Figure 10. View of an example of axial elastogram
Figura 1 1 . Vista de un ejemplo de elastograma lateral Figure 1 1 . View of an example of a lateral elastogram
Figura 12. Vista de un ejemplo de superposición de elastograma. Mezcla Alfa Figure 12. View of an example of elastogram overlay. Alpha Blend
Figura 13. Vista de ejemplo de presentación de resultados.
DESCRIPCIÓN DETALLADA DE LA INVENCIÓN Figure 13. Example view of results presentation. DETAILED DESCRIPTION OF THE INVENTION
La invención presentada consiste en un consiste en un sistema de elastografía ultrasónica, como herramienta de apoyo diagnóstico en personas con espasticidad muscular que permite identificar y diferenciar el tejido muscular espástico en tiempo “cuasi real”, a través de imágenes paramétricas de ultrasonografía, que cuantifican en un mapa de colores superpuesto en una imagen ecográfica convencional, la tasa de deformación alcanzada por las fibras musculares, el tono muscular y la estimación de la velocidad de una región de contracción de fibras. The invention presented consists of an ultrasonic elastography system, as a diagnostic support tool in people with muscular spasticity that allows the identification and differentiation of spastic muscle tissue in "quasi real" time, through parametric ultrasonography images, which quantify in a color map superimposed on a conventional ultrasound image, the rate of strain achieved by muscle fibers, muscle tone, and the estimation of the speed of a region of fiber contraction.
Este sistema, como se puede apreciar en la FIG. 1 , se caracteriza porque comprende una sonda lineal de ultrasonido (100), un brazalete (200), que acopla y sujeta la sonda lineal de ultrasonido (100) sobre la zona muscular a ser evaluada; un gel ecográfico (300) aplicado en la superficie de la zona muscular a ser evaluada; y una interfaz lógica, ejecutada desde un computador portátil (400), a través de la cual se realiza la lectura de las señales acústicas de alta frecuencia, obtenidas por la sonda lineal de ultrasonido (100), para establecer una cuantificación del grado de rigidez muscular (tono muscular), e inferir el grado de espasticidad de pacientes en procesos de rehabilitación. Donde la interfaz lógica, ejecutada desde un computador portátil (400), incluye un módulo de adquisición de señales RF (410), un módulo de generación de imágenes bidimensionales (420) y un módulo virtual de mapa de colores (elastograma) (430). This system, as can be seen in FIG. 1, is characterized in that it comprises a linear ultrasound probe (100), a bracelet (200), which couples and holds the linear ultrasound probe (100) on the muscle area to be evaluated; an ultrasound gel (300) applied to the surface of the muscle area to be evaluated; and a logical interface, executed from a laptop (400), through which the reading of the high-frequency acoustic signals is performed, obtained by the linear ultrasound probe (100), to establish a quantification of the degree of rigidity muscle (muscle tone), and infer the degree of spasticity of patients in rehabilitation processes. Where the logical interface, executed from a laptop (400), includes an RF signal acquisition module (410), a two-dimensional image generation module (420) and a virtual color map module (elastogram) (430) .
En una realización preferida de la invención, la sonda lineal de ultrasonido (100) consiste en una sonda de uso médico, preferiblemente portátil, que construye matrices de imágenes bidimensionales, con un rango de profundidad dinámico de 0.1 a 10 cm, posee un ancho de banda que comprende los 5MHz hasta los 10 MHz y cumple con las siguientes especificaciones mínimas:
In a preferred embodiment of the invention, the linear ultrasound probe (100) consists of a probe for medical use, preferably portable, that builds two-dimensional image arrays, with a dynamic depth range of 0.1 to 10 cm, has a width of band that includes 5MHz to 10 MHz and meets the following minimum specifications:
Tabla 1. Especificaciones mínimas requeridas de la sonda sonda lineal de ultrasonido (100). Table 1. Minimum required specifications of the linear ultrasound probe (100).
El gel ecográfico (300) consiste en una solución viscosa, preferiblemente compuesta por agua y propilenglicol, y es el medio de acoplamiento acústico entre la sonda ultrasónica y la piel del paciente. Elimina bolsas de aire entre el transductor y la piel que pueden obstruir el paso de las ondas mecánicas de alta frecuencia hacia el tejido de análisis. The ultrasound gel (300) consists of a viscous solution, preferably composed of water and propylene glycol, and is the acoustic coupling medium between the ultrasound probe and the patient's skin. Eliminates air pockets between the transducer and the skin that can obstruct the passage of high-frequency mechanical waves to the analysis tissue.
En esta realización, el brazalete (200) consiste en un accesorio que cuenta con un diseño y configuración especial que actúa como medio de soporte de la sonda, en función de la forma. Contiene bandas elásticas, unidas a una hebilla de plástico para sujetarse al bíceps braquial. En otras realizaciones la forma del brazalete varía para ajustarse a la zona o superficie sobre la cual se realiza la toma de señales.
Continuando con la descripción de las piezas que conforman la realización preferida de la invención, el computador portátil cuenta con una capacidad de al menos ¡5-5200U, y un Procesador de al menos 2.2 GHz, 3 MB. Esto para que pueda ejecutar correctamente la interfaz lógica; en donde dicha interfaz incluye: In this embodiment, the bracelet (200) consists of an accessory that has a special design and configuration that acts as a support means for the probe, depending on its shape. Contains elastic bands, attached to a plastic buckle to attach to the biceps brachii. In other embodiments, the shape of the bracelet varies to adjust to the area or surface on which the signals are taken. Continuing with the description of the parts that make up the preferred embodiment of the invention, the laptop has a capacity of at least ¡5-5200U, and a Processor of at least 2.2 GHz, 3 MB. This so that it can correctly execute the logical interface; where said interface includes:
Un módulo de adquisición de señales RF (410), como se puede apreciar en la FIG. 2. desarrollado desde Visual Studio con herramientas para la colecta de señales de radiofrecuencia (RF) en intervalos de tiempo y numero de señales específicas. An RF signal acquisition module (410), as can be seen in FIG. 2. Developed from Visual Studio with tools for the collection of radio frequency signals (RF) in time intervals and number of specific signals.
SDK es La interfaz de programación de aplicaciones o API (del inglés application programing interface) creada para permitir el uso de cierto lenguaje de programación, además, incluir hardware sofisticado con el fin de comunicarse con un determinado sistema embebido. SDK is the application programming interface or API (from the English application programming interface) created to allow the use of a certain programming language, in addition, to include sophisticated hardware in order to communicate with a certain embedded system.
Las herramientas de desarrollo de software más comunes incluyen soporte hacia la detección de errores de programación como un entorno de desarrollo integrado (IDE, por sus siglas en inglés) y otras utilidades. Los SDK frecuentemente tienen códigos de ejemplo y notas técnicas de soporte u otra documentación de apoyo para ayudar a clarificar ciertos puntos del material de referencia primario. Mediante esta plataforma software se logra capturar una imagen o señal RF de cualquier segmento corporal, es necesario detallar que el código abierto de este software fue modificado por los autores de la invención, con el objetivo de no solo lograr capturar una imagen sino capturar una secuencia de señales RF en un determinado lapso de tiempo (Durante el movimiento de extensión-flexión del miembro con espasticidad). The most common software development tools include support for bug detection such as an integrated development environment (IDE) and other utilities. SDKs often have example code and supporting technotes or other supporting documentation to help clarify certain points in the primary reference material. Through this software platform it is possible to capture an image or RF signal of any body segment, it is necessary to detail that the open code of this software was modified by the authors of the invention, with the aim of not only capturing an image but capturing a sequence of RF signals in a given period of time (During the extension-flexion movement of the limb with spasticity).
De tal forma que estas señales de radiofrecuencia quedaran almacenas en un archivo .csv de manera automática de acuerdo al número de datos establecidos durante un periodo determinado. In such a way that these radiofrequency signals will be stored in a .csv file automatically according to the number of data established during a certain period.
Con el fin de realizar la toma de las señales mecánicas en el rango de radiofrecuencia, a través de una sonda ultrasónica, y acceder a la colecta de
señales de radiofrecuencia, el operador debe inicializar escaneo de las señales desde la plataforma Visual Studio desde el cual direccionara los registros adquiridas a un archivo de destino establecido por el software. In order to take the mechanical signals in the radiofrequency range, through an ultrasonic probe, and access the collection of radiofrequency signals, the operator must start scanning the signals from the Visual Studio platform from which the acquired records will be directed to a destination file established by the software.
Este es el punto más importante del sistema, ya que, una buena captura de las señales significa la obtención de buenos resultados cuantitativos. This is the most important point of the system, since a good capture of the signals means obtaining good quantitative results.
La ejecución del módulo da inicio en la primera clase llamada <RF>, la cual lleva una asociación o secuencia hacia el segundo paso llamado <Scan 2D>, donde el usuario escoge la opción <Play> para empezar el escaneo y adquisición de señales de radiofrecuencia, la cual hereda procesos de la clase <Scan 2D> (Clase donde se procesa el tiempo de adquisición de la señal y número de datos a procesar). The execution of the module begins in the first class called <RF>, which carries an association or sequence to the second step called <Scan 2D>, where the user chooses the <Play> option to start the scanning and acquisition of radio signals. radiofrequency, which inherits processes from the <Scan 2D> class (Class where the signal acquisition time and number of data to be processed are processed).
El usuario es libre de elegir la opción <Freeze> al momento que el considere que la operación del procedimiento debe parar. The user is free to choose the <Freeze> option whenever he considers that the operation of the procedure should stop.
Un módulo de generación de imágenes bidimensionales (420): Desarrollado en Matlab, ejecuta procesos algorítmicos para la construcción y creación de imágenes bidimensionales a partir de las señales RF adquiridas previamente. A two-dimensional image generation module (420): Developed in Matlab, it executes algorithmic processes for the construction and creation of two-dimensional images from the previously acquired RF signals.
Mediante matrices de elementos fotográficos es posible formar las imágenes ecográficas; en el caso de las imágenes en escala de grises la visualización es posible gracias a los ecos que son los encargados de volver al transductor como píxeles. By means of arrays of photographic elements it is possible to form the ultrasound images; In the case of grayscale images, visualization is possible thanks to the echoes that are responsible for returning to the transducer as pixels.
El proceso de generación empieza cuando se aplica un pulso eléctrico a los electrodos de cristal piezoeléctrico del transductor. Se produce una vibración y se transmite el haz ultrasónico, el cual posteriormente es transmitido y reflejado por los tejidos. Cuando la energía vuelve al emisor (transductor) se producen vibraciones en el cristal las cuales se convertirán en corriente eléctrica y posteriormente al ser amplificadas se transformarán en imágenes.
Para acceder a realizar la generación de elastograma acústico, el operador debe efectuar la selección de la señal de referencia (Señal e Imagen en Extensión), la cual será asociada con la señal desplazada (Señal e Imagen en Flexión), como se aprecia en la FIG. 2A The generation process begins when an electrical pulse is applied to the piezoelectric crystal electrodes of the transducer. A vibration is produced and the ultrasonic beam is transmitted, which is subsequently transmitted and reflected by the tissues. When the energy returns to the emitter (transducer) vibrations are produced in the crystal which will become electric current and later, when amplified, they will be transformed into images. To access the generation of the acoustic elastogram, the operator must select the reference signal (Signal and Image in Extension), which will be associated with the displaced signal (Signal and Image in Flexion), as can be seen in Fig. FIG. 2A
En la FIG 3, se muestra una vista de la construcción de imágenes bidimensionales a partir de las señales de radiofrecuencia adquiridas desde el tejido musculo-esquelético, donde se aprecia: (1 ). Epidermis. (2). Fascia Muscular. (3). Bíceps. (4). Fascia Braquial. (5). Braquial. (6). Humero. In FIG 3, a view of the construction of two-dimensional images from the radiofrequency signals acquired from the musculoskeletal tissue is shown, where it can be seen: (1). Epidermis. (two). Muscle fascia. (3). Biceps. (4). Brachial fascia. (5). Brachial. (6). Humerus.
A partir de esta información se implementan las líneas de código desarrolladas, algoritmos basados en transformadas y envolventes matemáticas para obtener imágenes bidimensionales. From this information, the developed lines of code, algorithms based on transforms and mathematical envelopes are implemented to obtain two-dimensional images.
Un módulo de Mapa de Colores (Elastoarama) (430): Desarrollado con procesos algorítmicos para el desarrollo de un mapa de colores (elastograma sobre la imagen bidimensional), que mediante un método de estimación de desplazamientos y haciendo uso de programación dinámica tiene la capacidad de superar discontinuidades sobre la imagen de elastografía; es decir, este algoritmo proporciona desplazamientos verdaderos sobre el elastograma. A Color Map module (Elastoarama) (430): Developed with algorithmic processes for the development of a color map (elastogram on the two-dimensional image), which through a displacement estimation method and using dynamic programming has the capacity to overcome discontinuities on the elastography image; that is, this algorithm provides true displacements on the elastogram.
La FIG 4. Muestra un mapa de colores (Elastograma) superpuesto sobre la imagen bidimensional. FIG 4. Shows a color map (Elastogram) superimposed on the two-dimensional image.
Se representa la búsqueda exhaustiva por bloques mediante la función de suma de diferencias absolutas(SAD), usada para determinar la diferencia entre dos señales A. En donde g (i) y g’(i+d) representan los datos RF iniciales y deformados respectivamente. Este proceso se representa mediante la siguiente ecuación The exhaustive block search is represented by the sum of absolute differences (SAD) function, used to determine the difference between two signals A. Where g(i) and g'(i+d) represent the initial and deformed RF data respectively. This process is represented by the following equation
Δ= \g(i) - g'(i + d)\ Δ= \g(i) - g'(i + d)\
Donde dmin ≤ d ≤ dmax son los desplazamientos la matriz representada en i.
Se muestra el elastograma a escalas de grises sobre tejido musculo-esquelético efectuando el algoritmo de elastografía en dos dimensiones en donde se determina que a pesar de la función de costos para disminuir la discontinuidad sobre la matriz de señales este procesamiento termina con un error del 10% sobre el elastograma resultante. Where dmin ≤ d ≤ dmax are the displacements of the matrix represented in i. The grayscale elastogram on musculoskeletal tissue is shown, performing the elastography algorithm in two dimensions, where it is determined that despite the cost function to reduce the discontinuity on the signal matrix, this processing ends with an error of 10 % on the resulting elastogram.
De lo establecido anteriormente, con el objetivo de optimizar el sistema de elastografía ultrasónica como herramienta de apoyo al diagnóstico de la espasticidad muscular, la sonda de ultrasonido entrega un archivo en formato de valores separados por coma ó CSV y es necesario transformarlos para obtener la imagen de ultrasonido en el plano sagital o lateral. From the above, in order to optimize the ultrasonic elastography system as a tool to support the diagnosis of muscle spasticity, the ultrasound probe delivers a file in comma-separated values or CSV format and it is necessary to transform them to obtain the image. ultrasound in the sagittal or lateral plane.
El módulo de mapa de colores (elastograma) (430) permite comparar dos ultrasonidos que se capturan en los momentos máximos de flexión y extensión del músculo y genera un gradiente con el que se elabora un elastograma relativo. Finalmente sobrepone el elastograma obtenido y la imagen del ultrasonido. The color map (elastogram) module (430) allows comparing two ultrasounds that are captured at the maximum moments of flexion and extension of the muscle and generates a gradient with which a relative elastogram is made. Finally, it overlays the obtained elastogram and the ultrasound image.
El sistema genera el reporte combinando los datos del evaluado con sus respectivos elastogramas procesados en formato de documento de texto. The system generates the report combining the evaluated data with their respective processed elastograms in text document format.
Para el desarrollo del algoritmo que refleja el mapa de colores (elastograma) se tomaron como referentes artículos y algoritmos de código abierto basados en un método de procesamiento dinámico y regularización de patrones, los cuales fueron adaptados y modificados para el sistema de elastografía ejecutado por los creadores de la invención. For the development of the algorithm that reflects the color map (elastogram), articles and open source algorithms based on a method of dynamic processing and pattern regularization were taken as references, which were adapted and modified for the elastography system executed by the researchers. creators of the invention.
La arquitectura propuesta también permite visualizar y almacenar imágenes acústicas para la elaboración de repositorios, los cuales permiten entrenar, probar y validar algoritmos de clasificación. Una vez las imágenes son convertidas a formato raw, ellas son adecuadas por el módulo de Procesamiento de imágenes, este realiza las siguientes operaciones: Escalado logarítmico,
Ecualización dinámica del rango de las imágenes, Filtrado y Escalamiento de la imagen. The proposed architecture also allows viewing and storing acoustic images for the creation of repositories, which allow training, testing and validating classification algorithms. Once the images are converted to raw format, they are adapted by the Image Processing module, which performs the following operations: Logarithmic scaling, Dynamic equalization of the range of the images, Filtering and Scaling of the image.
La FIG. 5 muestra la interfaz diseñada para la operación del sistema. Como se puede apreciar en dicha figura, consta de varias secciones (pestañas) por medio de las cuales se ejecutan los diversos módulos que conforman el sistema. FIG. 5 shows the interface designed for system operation. As can be seen in said figure, it consists of several sections (tabs) through which the various modules that make up the system are executed.
La primera pestaña de la interfaz, denominada “información del valorado”, permite la captura de la información del paciente o evaluado en dos bloques separados: “Información personal” e “Información de la prueba”. The first tab of the interface, called "valued information", allows the capture of the information of the patient or evaluated in two separate blocks: "Personal information" and "Test information".
Toda esta información es opcional y puede ser empleada con fines de seguimiento evolutivo o para el registro del reporte que genera el sistema. La muestra la pantalla con el formulario para la captura de información del evaluado. All this information is optional and can be used for evolutionary monitoring purposes or for the registration of the report generated by the system. It shows the screen with the form for capturing the evaluated information.
La información del valorado está separada en dos bloques: Información personal e Información de la prueba. Para validez de estudios investigativos el segundo bloque es de diligenciamiento obligatorio. The valued information is separated into two blocks: Personal Information and Test Information. For the validity of investigative studies, the second block is mandatory.
La interfaz permite registrar la siguiente información específica: The interface allows you to record the following specific information:
- Nombres y apellidos - Names and surnames
- Tipo de documento - Document type
- Número de documento - Document number
- Fecha de nacimiento - Date of birth
- Género - Gender
- Teléfono - Telephone
- Género - Gender
- País - Country
- Departamento/Estado - Department/State
- Fecha de valoración - Valuation date
- Tipo de valoración - Valuation type
- Temperatura
HR (Humedad Relativa) - temperature RH (Relative Humidity)
HSNM (Altura sobre el nivel del mar) HSNM (Height above sea level)
El botón “Salir” permite el cierre de la aplicación mientras que el botón “Siguiente”, tiene el efecto equivalente a presionar sobre el título de la siguiente pestaña de la aplicación: abrir la pestaña “Ultrasonido” en este caso. The “Exit” button allows the closing of the application while the “Next” button has the equivalent effect of pressing on the title of the next tab in the application: opening the “Ultrasound” tab in this case.
LA FIG. 6, muestra la vista de la segunda pestaña de la interfaz, denominada “ultrasonido”, a partir de la cual se ejecuta el módulo de adquisición de señales y tiene como propósito la carga de los archivos en formato “.csv” de los momentos inicial y final de las señales de radiofrecuencia (generalmente flexión y extensión máxima del músculo). El proceso de carga desencadena el procesamiento del archivo para su conversión en imágenes de ultrasonido en escala de grises. FIG. 6 shows the view of the second tab of the interface, called "ultrasound", from which the signal acquisition module is executed and its purpose is to load the files in ".csv" format from the initial moments and end of the radiofrequency signals (generally maximum flexion and extension of the muscle). The upload process triggers the processing of the file for conversion to grayscale ultrasound images.
El formato “.csv” son los datos números provenientes de las señales RF, compuesto por un arreglo matricial a partir de los cuales se construye la imagen bidimensional. The “.csv” format is the numerical data coming from the RF signals, made up of a matrix arrangement from which the two-dimensional image is built.
Para cargar cada uno de los archivos entregados por la sonda es necesario presionar el botón “Cargar CSV” en el extremo superior de cada uno de los contenedores de imagen de la ventana como se muestra en la FIG. 7. To load each of the files delivered by the probe, it is necessary to press the “Load CSV” button at the top of each of the image containers in the window, as shown in FIG. 7.
Una vez cargado el archivo, es posible ajustar el contraste de la imagen de acuerdo a tres parámetros: Once the file is loaded, it is possible to adjust the contrast of the image according to three parameters:
1. Imadjust, es una función propia del sistema que satura el 1 % del mayor y menor valor de todos los pixeles de la imagen para incrementar el contraste.1. Imadjust, is a function of the system that saturates 1% of the highest and lowest value of all pixels in the image to increase contrast.
2. Histeq, que realiza la mejora del contraste a través de una ecualización del histograma de la imagen. 2. Histeq, which performs contrast enhancement through image histogram equalization.
3. Adapthisteq, que realiza la mejora del contraste a través de un histograma adaptativo de contraste limitado.
La FIG. 8. enseña una vista de las opciones de contraste en la imagen en la sección “ultrasonido.” 3. Adapthisteq, which performs contrast enhancement through a contrast-limited adaptive histogram. FIG. 8. Shows a view of the contrast options on the image in the “ultrasound” section.
El procedimiento debe realizarse de la misma manera para las dos imágenes de los ultrasonidos correspondientes a los momentos inicial y final. The procedure must be carried out in the same way for the two ultrasound images corresponding to the initial and final moments.
El botón “Salir” permite el cierre de la aplicación; el botón “Atrás” permite regresar a la primera pestaña; y el botón “Siguiente”, tiene el efecto equivalente a presionar sobre el título de la tercera pestaña de la aplicación: abrir la pestaña “Elastografía y mediciones”. The “Exit” button allows the closing of the application; the “Back” button allows you to return to the first tab; and the “Next” button has the equivalent effect of clicking on the title of the third tab of the application: open the “Elastography and measurements” tab.
La siguiente sección de la interfaz, es la denominada “Elastografía y Mediciones” como se puede apreciar en la FIG 9. The next section of the interface is called "Elastography and Measurements" as can be seen in FIG 9.
En esta pestaña, los botones “desplazamiento axial” y “deformación lateral”, permiten generar los elastogramas en los planos axial y sagital a partir del gradiente calculado para cada plano entre las imágenes de ultrasonido de los dos momentos de la evaluación como se muestra en las Figuras 9 y 10. In this tab, the “axial displacement” and “lateral deformation” buttons allow elastograms to be generated in the axial and sagittal planes from the gradient calculated for each plane between the ultrasound images of the two evaluation moments, as shown in Figures 9 and 10.
El botón “Salir” permite el cierre de la aplicación; el botón “Atrás” permite regresar a la primera pestaña; y el botón “Siguiente”, tiene el efecto equivalente a presionar sobre el título de la tercera pestaña de la aplicación: abrir la pestaña “Superposición”. The “Exit” button allows the closing of the application; the “Back” button allows you to return to the first tab; and the “Next” button, has the equivalent effect of clicking on the title of the third tab of the application: opening the “Overlay” tab.
Finalmente, la FIG. 1 1 muestra una vista de lun ejemplo “Superposición”, en la que se ejecuta la acción de sobreponer el elastograma obtenido con la imagen del momento final, a fin de identificar y relacionar el esfuerzo y la deformación muscular de manera caulitativa. Para ello, la sección incluye cuatro esquemas diferentes de sobreposición: Finally, FIG. 1 1 shows a view of an example "Superimposition", in which the action of superimposing the elastogram obtained with the image of the final moment is executed, in order to identify and relate the effort and muscular deformation in a caulitative way. To do this, the section includes four different overlay schemes:
-. Mezcla alfa, en la que las imágenes se escalan en tamaño y dimensión n para luego sumarse en pesos ¡guales.
Diferencia, donde las imágenes se escalan en tamaño y dimensión n para luego restarse la una de la otra. -. Alpha blending, in which images are scaled in size and dimension n and then added together at equal weights. Difference, where the images are scaled in size and dimension n and then subtracted from each other.
Pseudocolor, donde se aplica una máscara homogénea a ambas imágenes con el fin de resaltar los “espacios vacíos” por extrapolación de máximos y mínimos. Pseudocolor, where a homogeneous mask is applied to both images in order to highlight the "empty spaces" by extrapolation of maximums and minimums.
-. Tablero de ajedrez, donde las dos imágenes no se sobreponen, sino que se intercalan en espacios cuadrados continuos. -. Checkerboard, where the two images do not overlap, but are interspersed in continuous square spaces.
Posterior a la obtención de los elastogramas, el sistema determinan los resultados, presentando un análisis de estadística descriptiva que representa el porcentaje de variación de pixeles y un diagrama de cajas que demuestra los valores de pixeles sobre una misma región para cada extremidad evaluada de los pacientes con espasticidad. After obtaining the elastograms, the system determines the results, presenting a descriptive statistical analysis that represents the percentage of variation of pixels and a box diagram that shows the values of pixels on the same region for each evaluated limb of the patients. with spasticity.
En la Figura 13. se observa un ejemplo de presentación de resultados con la distribución estadística en función del coeficiente de variación, según los datos estadísticos el brazo con hemiplejía espástica, presenta una gran minoría de porcentaje; indicando menor coeficiente de variación debido a la escasa variabilidad de pixeles en la región de interés con respecto al brazo sin ninguna alteración del tono muscular, el cual presenta mayor porcentaje es decir mayor coeficiente de variación. Figure 13 shows an example of the presentation of results with the statistical distribution based on the coefficient of variation. According to the statistical data, the arm with spastic hemiplegia presents a large percentage minority; indicating a lower coefficient of variation due to the low variability of pixels in the region of interest with respect to the arm without any alteration of muscle tone, which has a higher percentage, that is, a higher coefficient of variation.
Finalmente se realiza un recuento del método de operación del sistema; el cual comprende los pasos: a.) registro de la información del valorado: Finally, a recount of the method of operation of the system is made; which includes the steps: a.) registration of the valued information:
Al momento de ingresar a la interfaz, se debe registrar la información correspondiente al usuario, en la sección “información del valorado” con los siguientes datos:
- Nombres y apellidos At the time of entering the interface, the information corresponding to the user must be registered, in the "valued information" section with the following data: - Names and surnames
Tipo de documento Document type
Número de documento Document number
Fecha de nacimiento Date of birth
Género Gender
Teléfono Telephone
Género Gender
País Country
Departamento/Estado Department/State
Fecha de valoración Valuation date
Tipo de valoración Valuation Type
Temperatura Temperature
HR (Humedad Relativa) RH (Relative Humidity)
HSNM (Altura sobre el nivel del mar). HSNM (Height above sea level).
Una vez ingresados los datos se selecciona el botón siguiente y se procede con la carga de datos. b.) carga de datos: Once the data has been entered, the next button is selected and the data is loaded. b.) data load:
Esta etapa incluye cargar, en la sección “Ultrasonido”, los datos en formato .CVS de las señales de ultrasonido en flexión y en extensión tomadas por la sonda lineal (100); donde una vez cargadas las señales son convertidas en imágenes y su contraste puede ser ajustado de acuerdo a tres parámetros: imadjust, Histeq y Adapthisteq. c.) Generación de elastogramas: This stage includes loading, in the "Ultrasound" section, the data in .CVS format of the ultrasound signals in flexion and in extension taken by the linear probe (100); where once the signals are loaded they are converted into images and their contrast can be adjusted according to three parameters: imadjust, Histeq and Adapthisteq. c.) Generation of elastograms:
Esta etapa incluye generar, en la sección “Elastografía y Mediciones”, los elastogramas en los planos axial y sagital a partir del gradiente calculado para cada plano entre las imágenes de ultrasonido de los dos momentos de la evaluación.
d.) superposición de elastogramas: This stage includes generating, in the “Elastography and Measurements” section, the elastograms in the axial and sagittal planes from the gradient calculated for each plane between the ultrasound images of the two evaluation moments. d.) elastogram overlay:
Esta etapa incluye sobreponer, en la sección “Superposición”, el elastograma obtenido con la imagen del momento final, e identificar y relacionar el esfuerzo y la deformación muscular de manera caulitativa; donde dicho paso incluye los cuatro esquemas diferentes de sobreposición explicados previamente. d) Presentación de resultados. This stage includes superimposing, in the "Overlay" section, the elastogram obtained with the image of the final moment, and identifying and relating the effort and muscular deformation in a caulitative manner; where said step includes the four different overlapping schemes previously explained. d) Presentation of results.
Consideraciones finales: Es pertinente reiterar que el sistema de elastografía ultrasónica, como herramienta de apoyo diagnóstico en personas con espasticidad muscular, posee las siguientes ventajas características: Final considerations: It is pertinent to reiterate that the ultrasonic elastography system, as a diagnostic support tool in people with muscular spasticity, has the following characteristic advantages:
Adaptación: Debido a la integración de código fuente en algunos sistemas operativos como Visual Basic, se puede modificar el sistema con gran rapidez y efectividad, para que este se adapte a las condiciones de valoración fisiopatológica de la persona evaluada. Adaptation: Due to the integration of source code in some operating systems such as Visual Basic, the system can be modified very quickly and effectively, so that it adapts to the pathophysiological assessment conditions of the person evaluated.
Transporte: Teniendo en cuenta su diseño, peso y sus características físicas de fácil ensamble este sistema puede ser transportado por una sola persona bajo diversas condiciones ergonómicas. Transport: Taking into account its design, weight and physical characteristics of easy assembly, this system can be transported by a single person under various ergonomic conditions.
Velocidad diagnostica: Por su configuración técnica, este sistema genera de forma ligera, aproximaciones sobre un determinado grado de rigidez muscular asociándolo con un tipo de espasticidad muscular.
Diagnostic speed: Due to its technical configuration, this system slightly generates approximations of a certain degree of muscle stiffness, associating it with a type of muscle spasticity.
Claims
1 . Sistema de elastografía ultrasónica, como herramienta de apoyo diagnóstico en personas con espasticidad muscular, caracterizado porque comprende una sonda lineal de ultrasonido (100), un brazalete (200), que acopla y sujeta la sonda lineal de ultrasonido (100) sobre la zona muscular a ser evaluada; un gel ecográfico (300) esparcido en la superficie de la zona muscular a ser evaluada; y una interfaz lógica, ejecutada desde un computador portátil (400), a través de la cual se realiza la lectura de las señales acústicas de alta frecuencia, obtenidas por la sonda lineal de ultrasonido (100), para establecer una cuantificación del grado de rigidez muscular e inferir el grado de espasticidad de pacientes; donde la interfaz lógica, ejecutada desde un computador portátil (400), incluye un módulo de adquisición de señales RF (410), un módulo de generación de imágenes bidimensionales (420) y un módulo de mapa de colores (elastograma) (430). 1 . Ultrasonic elastography system, as a diagnostic support tool in people with muscular spasticity, characterized in that it comprises a linear ultrasound probe (100), a bracelet (200), which couples and holds the linear ultrasound probe (100) on the muscle area to be evaluated; an ultrasound gel (300) spread on the surface of the muscle area to be evaluated; and a logical interface, executed from a laptop (400), through which the reading of the high-frequency acoustic signals is performed, obtained by the linear ultrasound probe (100), to establish a quantification of the degree of rigidity muscle and infer the degree of spasticity of patients; where the logical interface, executed from a laptop (400), includes an RF signal acquisition module (410), a two-dimensional image generation module (420) and a color map module (elastogram) (430).
2. Sistema de elastografía ultrasónica, como herramienta de apoyo diagnóstico en personas con espasticidad muscular, según la reivindicación 1 , caracterizado porque el módulo de adquisición de señales (410) se activa al inicializar el escaneo de las señales desde la plataforma Visual Studio, desde donde se direccionan los registros adquiridos a un archivo de destino establecido por el módulo; y donde la ejecución de dicho módulo da inicio en la primera clase llamada <RF>, la cual lleva una asociación o secuencia hacia el segundo paso llamado <Scan 2D>, en el cual el usuario escoge la opción <Play> para empezar el escaneo y adquisición de señales de radiofrecuencia, la cual hereda procesos de la clase <Scan 2D>. 2. Ultrasonic elastography system, as a diagnostic support tool in people with muscular spasticity, according to claim 1, characterized in that the signal acquisition module (410) is activated when the scanning of the signals is initialized from the Visual Studio platform, from where the acquired records are directed to a destination file established by the module; and where the execution of said module starts in the first class called <RF>, which carries an association or sequence towards the second step called <Scan 2D>, in which the user chooses the option <Play> to start the scan and acquisition of radiofrequency signals, which inherits processes from the <Scan 2D> class.
3. Sistema de elastografía ultrasónica, como herramienta de apoyo diagnóstico en personas con espasticidad muscular, según la reivindicación 1 , caracterizado porque el módulo de adquisición de señales (410) incluye herramientas para la colecta de señales de radiofrecuencia (RF) en intervalos de tiempo y numero de señales específicas, donde estas señales de radiofrecuencia son almacenadas en un archivo .csv de manera automática, según el número de datos establecidos durante un periodo determinado.
3. Ultrasonic elastography system, as a diagnostic support tool for people with muscular spasticity, according to claim 1, characterized in that the signal acquisition module (410) includes tools for collecting radiofrequency (RF) signals at time intervals and number of specific signals, where these radiofrequency signals are stored in a .csv file automatically, according to the number of data established during a certain period.
4. Sistema de elastografía ultrasónica, como herramienta de apoyo diagnóstico en personas con espasticidad muscular, según la reivindicación 1 , caracterizado porque el módulo de generación de imágenes bidimensionales (420) ejecuta procesos algorítmicos para la construcción y creación de imágenes bidimensionales a partir de las señales RF adquiridas previamente. 4. Ultrasonic elastography system, as a diagnostic support tool in people with muscular spasticity, according to claim 1, characterized in that the two-dimensional image generation module (420) executes algorithmic processes for the construction and creation of two-dimensional images from the previously acquired RF signals.
5. Sistema de elastografía ultrasónica, como herramienta de apoyo diagnóstico en personas con espasticidad muscular, según la reivindicación 1 y 5, caracterizado porque el módulo de mapa de colores (elastograma) (430) incluye un protocolo de estimación de desplazamientos y, mediante programación dinámica, compara dos ultrasonidos que se capturan en los momentos máximos de flexión y extensión del músculo, generando un gradiente con el que se elabora un elastograma relativo, para luego sobreponer el elastograma obtenido y la imagen del ultrasonido. 5. Ultrasonic elastography system, as a diagnostic support tool for people with muscular spasticity, according to claims 1 and 5, characterized in that the color map module (elastogram) (430) includes a displacement estimation protocol and, by programming dynamic, compares two ultrasounds that are captured at the maximum moments of flexion and extension of the muscle, generating a gradient with which a relative elastogram is elaborated, to then superimpose the obtained elastogram and the ultrasound image.
6. Sistema de elastografía ultrasónica, como herramienta de apoyo diagnóstico en personas con espasticidad muscular, según la reivindicación 1 , caracterizado porque la interfaz lógica incluye las secciones: “información del valorado”; “Ultrasonido”; “Elastografía y Mediciones”; y “Superposición.” 6. Ultrasonic elastography system, as a diagnostic support tool in people with muscular spasticity, according to claim 1, characterized in that the logical interface includes the sections: "valued information"; "Ultrasound"; “Elastography and Measurements”; and “Overlay.”
7. Sistema de elastografía ultrasónica de la Reivindicación 1 , caracterizado porque la interfaz incluye los botones “Salir”, “Siguiente” y “Atrás”, donde el botón “Salir” permite el cierre de la aplicación, mientras que el botón “Siguiente” tiene el efecto equivalente a presionar sobre el título de la siguiente pestaña de la interfaz; y el botón “Atrás” permite regresar a la pestaña previa. 7. Ultrasonic elastography system of Claim 1, characterized in that the interface includes the "Exit", "Next" and "Back" buttons, where the "Exit" button allows closing the application, while the "Next" button it has the equivalent effect of clicking on the title of the next interface tab; and the “Back” button allows you to return to the previous tab.
8. Método de operación del Sistema Sistema de elastografía ultrasónica de la Reivindicación 1 y 6, caracterizado porque incluye los pasos de: a.) registro de la información del valorado, b.) carga de datos, c.) generación de elastogramas c.) superposición de elastogramas y; d) Presentación de resultados. 8. Method of operation of the Ultrasonic Elastography System System of Claim 1 and 6, characterized in that it includes the steps of: a.) registration of the valued information, b.) data loading, c.) generation of elastograms c. ) elastogram overlay and; d) Presentation of results.
9. Método de operación del Sistema Sistema de elastografía ultrasónica según la Reivindicación 8, caracterizado porque el registro de la información del
valorado, incluye registrar la información correspondiente al usuario, en la sección “información del valorado” con los siguientes datos: 9. System operation method Ultrasonic elastography system according to Claim 8, characterized in that the registration of the information of the valued, includes registering the information corresponding to the user, in the "valued information" section with the following data:
- Nombres y apellidos - Names and surnames
Tipo de documento Document type
Número de documento Document number
Fecha de nacimiento Date of birth
Género Gender
Teléfono Telephone
Género Gender
País Country
Departamento/Estado Department/State
Fecha de valoración Valuation date
Tipo de valoración Valuation Type
Temperatura Temperature
HR (Humedad Relativa) RH (Relative Humidity)
HSNM (Altura sobre el nivel del mar). HSNM (Height above sea level).
10. Método de operación del Sistema Sistema de elastografía ultrasónica según la Reivindicación 8, caracterizado porque la carga de datos, incluye cargar, en la sección “Ultrasonido”, los datos en formato .CVS de las señales de ultrasonido en flexión y en extensión tomadas por la sonda lineal (100); donde una vez cargadas las señales son convertidas en imágenes y su contraste puede ser ajustado de acuerdo a tres parámetros: imadjust, Histeq y Adapthisteq. 10. Method of operation of the Ultrasonic Elastography System System according to Claim 8, characterized in that the data loading includes loading, in the "Ultrasound" section, the data in .CVS format of the ultrasound signals in flexion and in extension taken by the linear probe (100); where once the signals are loaded they are converted into images and their contrast can be adjusted according to three parameters: imadjust, Histeq and Adapthisteq.
11. Método de operación del Sistema Sistema de elastografía ultrasónica según la Reivindicación 8, caracterizado porque la generación de elastogramas incluye generar, en la sección “Elastografía y Mediciones”, los elastogramas en los planos axial y sagital a partir del gradiente calculado para cada plano entre las imágenes de ultrasonido de los dos momentos de la evaluación. 11. System operation method Ultrasonic elastography system according to Claim 8, characterized in that the generation of elastograms includes generating, in the "Elastography and Measurements" section, the elastograms in the axial and sagittal planes from the gradient calculated for each plane between the ultrasound images of the two evaluation moments.
12. Método de operación del Sistema Sistema de elastografía ultrasónica según la Reivindicación 8, caracterizado porque la superposición de elastogramas incluye sobreponer, en la sección “Superposición”, el elastograma obtenido con
la imagen del momento final, e identificar y relacionar el esfuerzo y la deformación muscular de manera caulitativa; donde dicho paso incluye cuatro esquemas diferentes de sobreposición: Mezcla alfa, en la que las imágenes se escalan en tamaño y dimensión n para luego sumarse en pesos ¡guales. 12. System operation method Ultrasonic elastography system according to Claim 8, characterized in that the superimposition of elastograms includes superimposing, in the "Superposition" section, the elastogram obtained with the image of the final moment, and identify and relate the effort and the muscular deformation in a caulitative way; where said step includes four different overlay schemes: Alpha blending, in which the images are scaled in size and dimension n and then added in equal weights.
Diferencia, donde las imágenes se escalan en tamaño y dimensión n para luego restarse la una de la otra. Difference, where the images are scaled in size and dimension n and then subtracted from each other.
-. Pseudocolor, donde se aplica una máscara homogénea a ambas imágenes con el fin de resaltar los “espacios vacíos” por extrapolación de máximos y mínimos. -. Tablero de ajedrez, donde las dos imágenes no se sobreponen, sino que se intercalan en espacios cuadrados continuos.
-. Pseudocolor, where a homogeneous mask is applied to both images in order to highlight the "empty spaces" by extrapolation of maximums and minimums. -. Checkerboard, where the two images do not overlap, but are interspersed in continuous square spaces.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/CO2021/000010 WO2022042778A2 (en) | 2021-10-01 | 2021-10-01 | Ultrasound elastography system for use as a diagnostic support tool for persons with muscle spasticity, and corresponding operating method |
| CONC2022/0003093A CO2022003093A2 (en) | 2021-10-01 | 2022-03-17 | Ultrasonic elastography system as a diagnostic support tool in people with muscle spasticity, and its method of operation |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/CO2021/000010 WO2022042778A2 (en) | 2021-10-01 | 2021-10-01 | Ultrasound elastography system for use as a diagnostic support tool for persons with muscle spasticity, and corresponding operating method |
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| WO2022042778A2 true WO2022042778A2 (en) | 2022-03-03 |
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| CN205107748U (en) * | 2015-11-16 | 2016-03-30 | 樊留博 | A fixing device that is used for muscle supersound elasticity formation of image check -out set |
| JP2019514652A (en) * | 2016-04-27 | 2019-06-06 | ニュクス テクノロジーズ インコーポレイテッドＮｅｕｘ Ｔｅｃｈｎｏｌｏｇｉｅｓ， Ｉｎｃ． | Electrotherapy treatment |
| WO2020234438A1 (en) * | 2019-05-23 | 2020-11-26 | Koninklijke Philips N.V. | Muscle imaging system |
| CN112674791B (en) * | 2020-11-30 | 2023-08-29 | 深圳大学 | Optimization method and system for muscle ultrasonic elastography |
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