Classifications

• • G—PHYSICS
  • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
  • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
  • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
  • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
  • A61B6/50—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body parts; specially adapted for specific clinical applications
  • A61B6/504—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body parts; specially adapted for specific clinical applications for diagnosis of blood vessels, e.g. by angiography
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
  • A61B6/50—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body parts; specially adapted for specific clinical applications
  • A61B6/507—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body parts; specially adapted for specific clinical applications for determination of haemodynamic parameters, e.g. perfusion CT
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
  • A61B6/52—Devices using data or image processing specially adapted for radiation diagnosis
  • A61B6/5211—Devices using data or image processing specially adapted for radiation diagnosis involving processing of medical diagnostic data
  • A61B6/5217—Devices using data or image processing specially adapted for radiation diagnosis involving processing of medical diagnostic data extracting a diagnostic or physiological parameter from medical diagnostic data
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T7/00—Image analysis
  • G06T7/0002—Inspection of images, e.g. flaw detection
  • G06T7/0012—Biomedical image inspection
• • G—PHYSICS
  • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
  • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
  • G16H30/00—ICT specially adapted for the handling or processing of medical images
  • G16H30/20—ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
  • A61B6/02—Arrangements for diagnosis sequentially in different planes; Stereoscopic radiation diagnosis
  • A61B6/03—Computed tomography [CT]
  • A61B6/032—Transmission computed tomography [CT]
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T12/00—Tomographic reconstruction from projections
  • G06T12/30—Image post-processing, e.g. metal artefact correction
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T2207/00—Indexing scheme for image analysis or image enhancement
  • G06T2207/10—Image acquisition modality
  • G06T2207/10072—Tomographic images
  • G06T2207/10081—Computed x-ray tomography [CT]
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T2207/00—Indexing scheme for image analysis or image enhancement
  • G06T2207/30—Subject of image; Context of image processing
  • G06T2207/30004—Biomedical image processing
  • G06T2207/30048—Heart; Cardiac
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T2207/00—Indexing scheme for image analysis or image enhancement
  • G06T2207/30—Subject of image; Context of image processing
  • G06T2207/30004—Biomedical image processing
  • G06T2207/30061—Lung
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T2207/00—Indexing scheme for image analysis or image enhancement
  • G06T2207/30—Subject of image; Context of image processing
  • G06T2207/30004—Biomedical image processing
  • G06T2207/30101—Blood vessel; Artery; Vein; Vascular

Definitions

• the present invention is concerned with the radiological detection of chronic thromboembolic pulmonary hypertension (CTEPH).
• CTEPH chronic thromboembolic pulmonary hypertension
• the invention relates to a method, a computer system and a computer program product for the automated detection of indications of the presence of CTEPH in a human.
• Chronic thromboembolic pulmonary hypertension is a special form of pulmonary hypertension (PH, pulmonary hypertension). It is characterized by the influx of thrombi into the pulmonary arteries. These clog and constrict the vessels in whole or in part and can transform connective tissue. In rare cases, pulmonary hypertension develops with poor prognosis.
• CTEPH chronic myeloea
• the symptoms of CTEPH are nonspecific. Dyspnoea and fatigue may occur in the early stages. The duration of the first symptoms of the diagnosis is on average 14 months, with some patients already in an advanced stage of the disease. This underlines the need for accurate and timely diagnostics.
• CTEPH chronic pulmonary hypertension
• the gold standard for diagnosing or excluding CTEPH is ventilation / perfusion scintigraphy.
• the negative predictive value of perfusion scintigraphy is close to 100, which means that a proper perfusion distribution excludes a CTEPH with almost certainty.
• the problem is that CTEPH is comparatively rare. The rarity and the complex diagnostics and differential diagnostics lead to CTEPH being underdiagnosed.
• a first subject of the present invention is a method for detecting evidence of the presence of CTEPH in a human comprising the following steps:
• Another object of the present invention is a computer system for detecting evidence for the presence of CTEPH in a human, comprising - means for automatically receiving or retrieving one or more computed tomographic images of the human thorax
• a further subject of the present invention is a computer program product comprising a data carrier on which a computer program is stored, which can be loaded into the main memory of a computer system and there causes the computer system to carry out the following steps: receiving or retrieving one or more computed tomography images of the computer Thorax of the human
• the present invention is directed to the automated image analysis of computed tomographic images of the human thorax.
• Computed Tomography is an X-ray technique that displays the human body in cross-sectional images. Compared to a conventional radiograph, where usually only rough structures and bones are recognizable, soft tissue with low contrast differences is recorded in CT images in detail.
• An X-ray tube generates a so-called X-ray fan beam, which penetrates the body and is attenuated to different degrees within the body by the various structures, such as organs and bones.
• the reception detectors with respect to the X-ray emitter receive the different strength signals and forward them to a computer which composes layer images of the body from the received data.
• Computed tomography images can be viewed in 2D or 3D.
• a contrast agent may be injected into a vein prior to the production of CT images.
• Computed tomography is a commonly used method in the diagnosis of heart and lung diseases.
• the CT images are preferably multidetector CT images.
• Multidetector CT is the latest generation of computed tomography scanners available since 1998 in clinical radiology.
• the multi-detector CT is widely available and characterized by high, almost isotropic resolution (size of the pixels 0.5-1 mm in each spatial direction), which is a consideration of the CT Recordings in any room levels allowed.
• the examination time ranges between 1 and 10 seconds, so that even with dyspnoea or lack of cooperation of the patients nearly artifact-free images arise.
• a key criterion of the present invention is automation.
• CTEPH is a rare disease that is underdiagnosed. Overlooking this condition can have fatal consequences for the patient. Therefore, according to the present invention, computer tomographic images of the thorax are automatically analyzed for evidence of the presence of CTEPH. "Automated" means that no human intervention is required. According to the invention, therefore, a computer program is installed on a computer system which has access to computed tomography images of the thorax, runs as a background process, and automatically analyzes the images for indications of the presence of CTEPH.
• a background process is a process that does not interact directly with the user, acting asynchronously with the user interface.
• a CT scan is usually a data set with which the structures of the human thorax can be represented three-dimensionally.
• a CT scan usually represents the human thorax at the time the CT scan is taken.
• Multiple CT scans can represent the lung area of the human at different times; By means of these multiple CT images temporal changes in the tissue structures can thus be detected and thus, for example, a course of the disease can be investigated.
• the multiple CT scans are CT scans that represent different areas of the thorax.
• CT images present in one or more databases are retrieved and analyzed for the presence of indicia for CTEPH. This can happen, for example, at regular intervals. It is conceivable, for example, to carry out a search in the databases in which CT recordings are usually stored, for new CT recordings at regular intervals, for example every day or every week, and to retrieve the new CT recordings for image analysis. However, fetching can also be irregular. Retrieval can also be triggered by an event, for example, by saving a new CT scan. Preferably, the retrieval of new CT recordings is automated.
• a CT image produced by the human thorax is immediately and automatically subjected to an image analysis according to the invention after it has been generated.
• a computer system aligned to produce a corresponding CT scan may be configured to supply the CT scan to the image analysis of the present invention.
• the components that perform the image analysis receive the CT scan.
• an automated analysis of the CT scan takes place.
• the analysis is performed by an image recognition software.
• the image recognition software is configured to examine the CT image for the presence of specific (characteristic) features.
• CT images of people who suffer from CTEPH often show characteristic features that people without CTEPH do not have. According to the invention, the CT images are examined for the presence of these characteristic features.
• a characteristic feature that can be identified in the analyzes mentioned is the ratio of the volumes and / or the diameters of the right ventricle and the left ventricle (RV / LV ratio) (see, for example, Gonzales G et al., PLoS ONE 10 (5). : eO 127797). A value of 0.9 and more in the RV / LV diameter ratio is an indication for the presence of CTEPH.
• Another characteristic feature is the degree of curvature of the septum between the heart chambers (see, eg, DA Moses et al., Quantification of the curvature and shape of the interventricular septum; Magnetic Resonance in Medicine, Vol. 52 (1), 2004, 154- 163 and F.
• Typical vascular features include the lack of contrast media in the distal vessel sections in total obstruction or the formation of rope ladder thrombi, nets, stenoses, and partial obstructions.
• CTEPH-specific parenchymal features include scarring, mosaic perfusion, frosted glass exercises, and bronchial anomalies. The scars are due to infarcts due to the closure of pulmonary vessels, which are usually located in the lower segments.
• Mosaic perfusion consists of regions of varying density through regions of irregular hypo- and hyper-perfused areas caused by embolic occlusions, vascular remodeling of the distal vessels, and compensatory mechanisms. Hypoperfused areas are to be observed especially distally of the closed vessels, since in these areas the blood flow and thus the concentration of the contrast agent are reduced.
• Hyperdense areas are usually visible in areas that are now hyperperfused due to the redistribution and impress as a frosted glass opacity.
• the latter and other characteristic features are described in the literature (see, eg, JE Leifheit, characterization of patients with chronic thromboembolic pulmonary hypertension compared to polmonary hypertension of other WHO classifications using dual energy computed tomography, inaugural discard to achieve the degree of Doctor of Medicine Justus Liebig University Giessen, 2017).
• the identification of the characteristic features is preferably carried out by classical pattern recognition methods.
• methods of machine learning are also conceivable (artificial neural networks, deep learning and the like).
• the number of available CT scans of people who have CTEPH is (still) comparatively small, so that the machine learning methods could possibly cause problems with the small amount of available data for training.
• information may be stored in a database on the corresponding CT scan or on the person from whom the CT scan was generated, indicating that CTEPH-specific features are present in the CT scan CT scan have been identified.
• a calculation of a probability for the presence of CTEPH is carried out on the basis of the determined characteristic features.
• a value of 100% indicates that the patient is suffering from CTEPH; a value of 0% indicates that CTEPH can be excluded.
• the one or more CT scans be examined for the presence of a number of characteristic features.
• the individual features with a Factor so that features more indicative of CTEPH score higher in the probability function than features that are more non-specific.
• the degree of a feature is determined; the degree indicating the severity of the presence of CTEPH. The higher the degree, the more apparent the feature is and the higher the probability of CTEPH being present.
• one or more decision trees or regression trees are passed through; it may be that a trait only indicates CTEPH in combination with another trait. Further methods and combinations of methods for determining the probability are conceivable.
• the threshold may be, for example, between 20% and 70%. Preferably it is above 20% and below 51%.
• the transmission of a message then follows that the person should be subjected to further diagnostics in order to confirm or safely exclude CTEPH.
• This message may, for example, be directed to the person from whom the corresponding CT scan originated. It may also be directed to its doctor or hospital staff or to another person in contact with the person with evidence of CTEPH.
• the message can be a text message (email, SMS, etc.) or a voice message.
• FIG. 1 shows by way of example an embodiment for the implementation of the system according to the invention.
• FIG. 1 shows a CT system 1, which is designed as a dual-focus detector system. It has a first x-ray tube 2 with an opposite detector and a second x-ray tube 4 with another opposing detector 5. Both focus / detector systems 2, 3 and 4, 5 are arranged in a gantry housing 6 on a gantry rotating about a system axis 9 and not shown here.
• the patient 7 is located on a longitudinally displaceable patient bed 8. Before scanning the patient 7, a contrast agent is applied to the patient 7 by means of a contrast agent injector 12 to improve the contrast of a CT image reconstructed from the detector output data.
• control and processing unit 10 has a memory 11 in which in addition to the measured detector output data and computer programs Prgl-Prgn are stored, which are executed in operation and essentially take over the control of the system and the evaluation of the data.
• the computer program according to the invention runs as a background process on the control and processing unit 10. It analyzes the sectional images or volume data for the presence of CTEPH indicia. In the event that CTEPH indicia are identified, and a calculated probability for the presence of CTEPH is above a defined threshold value, the computer program according to the invention displays a message on the screen of the control and processing unit 10 informing the radiologist that that there is a suspicion of CTEPH.
• Fig. 2 shows schematically a further embodiment for the implementation of the system according to the invention.
• the CT system 1 is connected to the control and processing unit 10 via the connection 14-1.
• the control and computation unit 10 controls the CT system 1 and evaluates the detector data and reconstructs the CT display as slice images or volume data.
• the sectional images and volume data are stored in a database 12 to which the control and computation unit 10 is connected via the connection 14-2. It is also conceivable that the database is a component of the control and processing unit 10.
• Database 12 may also be accessed by computer system 13 via connection 14-3.
• On the computer system 13 runs the computer program according to the invention. It is configured to record the CT scans of the human thorax stored in the database 12 for evidence of CTEPH analyzed. In the event that no clues are identified, a corresponding information on the CT recordings is stored.
• the computer program installed and running on the computer system 13 is configured to calculate a likelihood of the presence of CTEPH based on the detected features indicative of CTEPH. If this probability is above a defined threshold, the computer program generates a message that CTEPH may be present.
• the computer program installed and running on the computer system 13 may be configured to display the notification of the presence of CTEPH indicia on a screen forming part of the computer system 13. It is also conceivable that the computer program is configured to transmit a notification for the presence of CTEPH indicia via the connection 14-4 to the control and processing unit 10, via which the message is then displayed, eg on a screen becomes.
• the computer system 10 obtains the information as to whether CTEPH indicia exists directly from the database 12. It is also conceivable that the computer program is configured to transmit a notification for the presence of CTEPH indicia via the connection 14-5 to another computer system 15, where the message is then displayed, eg via a screen. It is also conceivable that the computer system 15 obtains the information as to whether CTEPH indicia exists via the connection 14-6 from the database 12.
• the dashed components in Fig. 2 are optional.
• the links 14-1, 14-2, 14-3, 14-4, 14-5, and 14-6 may be wired, fiber-optic, and / or wireless (eg, wireless) links.
• FIG 3 shows schematically an embodiment of the computer system 100 according to the invention.
• the computer system 100 is connected to a database 12, on which computer tomographic images of the thorax of a person are stored. It is also conceivable that the database 12 is a component of the computer system 100.
• the computer system 100 includes a receiving unit 110 with which the computer tomographic recordings can be received or called.
• the Computer system 100 comprises a control and computation unit 120, with which the computed tomography images can be analyzed and with which features can be identified in the computed tomography images that indicate the presence of CTEPH.
• the computer system 100 comprises a computing and testing unit 130, with which a probability for the presence of CTEPH can be calculated and with which it can be checked whether the probability is above a defined threshold value.
• the computing and testing unit 130 may be part of the control and processing unit 120.
• the computer system 100 comprises an output unit 140, with which a message about the result of the analysis can be displayed to a human or transmitted to a human.
• a method for detecting evidence of the presence of CTEPH in a human comprising the following steps:
• a computer system for detecting indicia of the presence of CTEPH in a human comprising - means for receiving or retrieving one or more computed tomographic images of the human thorax
• a computer program product comprising a data carrier on which a computer program is stored, which can be loaded into the main memory of a computer system and there causes the computer system to carry out the following steps:

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• 2018
  • 2018-04-26 EP EP18720250.2A patent/EP3619631A1/de not_active Withdrawn
  • 2018-04-26 US US16/609,138 patent/US20200237331A1/en not_active Abandoned
  • 2018-04-26 WO PCT/EP2018/060732 patent/WO2018202541A1/de not_active Ceased
  • 2018-04-26 JP JP2019560392A patent/JP2020518396A/ja active Pending
  • 2018-04-26 CN CN201880029130.4A patent/CN110574070A/zh active Pending
  • 2018-04-26 CA CA3061988A patent/CA3061988A1/en active Pending

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