Classifications

• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/43—Detecting, measuring or recording for evaluating the reproductive systems
  • A61B5/4375—Detecting, measuring or recording for evaluating the reproductive systems for evaluating the male reproductive system
  • A61B5/4381—Prostate evaluation or disorder diagnosis
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/74—Details of notification to user or communication with user or patient ; user input means
  • A61B5/742—Details of notification to user or communication with user or patient ; user input means using visual displays
  • A61B5/743—Displaying an image simultaneously with additional graphical information, e.g. symbols, charts, function plots
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
  • A61B5/7221—Determining signal validity, reliability or quality
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/74—Details of notification to user or communication with user or patient ; user input means
  • A61B5/742—Details of notification to user or communication with user or patient ; user input means using visual displays
  • A61B5/7425—Displaying combinations of multiple images regardless of image source, e.g. displaying a reference anatomical image with a live image
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/74—Details of notification to user or communication with user or patient ; user input means
  • A61B5/7475—User input or interface means, e.g. keyboard, pointing device, joystick
  • A61B5/748—Selection of a region of interest, e.g. using a graphics tablet
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T11/00—2D [Two Dimensional] image generation
  • G06T11/001—Texturing; Colouring; Generation of texture or colour
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T19/00—Manipulating 3D models or images for computer graphics
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR 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
  • G06—COMPUTING; CALCULATING OR 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
  • G06T2207/10088—Magnetic resonance imaging [MRI]
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR 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
  • G06T2207/10104—Positron emission tomography [PET]
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T2207/00—Indexing scheme for image analysis or image enhancement
  • G06T2207/20—Special algorithmic details
  • G06T2207/20076—Probabilistic image processing
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR 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
  • G06T2207/30081—Prostate
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T2210/00—Indexing scheme for image generation or computer graphics
  • G06T2210/41—Medical

Definitions

• the invention relates to a device for visualizing an internal organ of a patient as well as an associated visualization method.
• the standard act for the detection of prostate cancer is to perform biopsies in the prostate.
• the diseased tissues with prostate cancer are not distinguished, in general, from healthy tissue in conventional ultrasound-type medical images.
• Magnetic resonance imaging (MRI) or positron emission tomography (PET) is more sensitive and more specific to pathology and can sometimes identify suspicious lesions.
• biopsies can traditionally be done by a transrectal approach or a transperineal approach.
• Transrectal biopsies are traditionally performed on an outpatient basis with local anesthesia, with the session then lasting less than one hour. But it is also possible to consider transrectal biopsies under general anesthesia.
• the patient is lying supine (flank with knees raised to the abdomen) or in a gynecological position. Once the patient is installed, the urologist inserts an endorectal probe through the patient's rectum, with a needle guide attached to the probe to perform prostate punctures through the rectum.
• transperineal biopsies are performed under general anesthesia.
• the patient is in a gynecological position.
• an endorectal probe is inserted into the patient's rectum to observe the prostate under ultrasound.
• a puncture guide is placed in front of the perineum of the patient (in front of the rectum and behind the genitals) to guide the puncture needle which will then pass through the perineal skin to reach the prostate.
• the clinician performs multiple biopsies distributed according to a systematic protocol throughout the prostate and / or a small number of biopsies concentrated on suspicious volumes detected upstream for example in MRI images.
• Document US 2009/093715 thus proposes a method for developing a biopsy schedule in the prostate.
• Document US 2010/0172559 proposes a method for facilitating the visualization of the prostate during a biopsy schedule.
• the clinician receives a report indicating the level of severity of each sample. Sometimes the report also indicates what level of severity is reached in a particular anatomical area or the entire organ. In case of proven illness, the results can help the clinician to characterize the disease and to define the best possible management of the patient.
• TNM stage which consists of a classification with three criteria defining the tumoral state, the state of the regional ganglia and distant metastases.
• prostate cancer can be classified into four different stages such as:
• Gleason grade visual tissue analysis (microscopic), which consists of a grade of cancer in five groups where aggression increases when moving to a grade 5 group.
• the clinician decides on the basis of the report or reports received (indicating with which level of severity each sample is reached and / or which zones seen during an imaging examination are suspect), taking into account the most appropriate load for the patient (considering the best benefit-risk ratio and the best possible quality of life for the patient). For example, it may decide to perform just periodic surveillance (also known as active surveillance) of the course of the disease or, on the contrary, decide on a treatment (qualification stage).
• just periodic surveillance also known as active surveillance
• the next step is for the clinician to estimate the anatomical volume (s) reached by the disease and subsequently to delineate one or more treatment volumes (stage). delimitation).
• This step of delimiting the volume of treatment constitutes a major difficulty for the clinician because, for biopsies, only sampling sites were examined. In addition, even if the clinician also has other medical imaging information, the suspicious areas identified on these medical images often correspond only roughly to the volume actually reached by the disease.
• the clinician is restricted to represent mentally the general state of the prostate and the patient to identify areas that he considers healthy and those he considers suspicious and thus determine a volume of treatment.
• the present applicant already proposes a mapping system for visualizing the prostate in three dimensions as well as the locations where the various samples were taken from the prostate. It is also possible to display, in the same frame as the previous information, the suspect volumes detected by other medical examinations such as for example MRI imaging.
• Such a mapping system is for example illustrated in FIG.
• An object of the invention is to provide a display device of an internal organ of a patient to limit a risk of under-treatment or over-treatment of said internal organ.
• An object of the invention is also to provide a corresponding visualization method.
• the invention relates to a device for visualizing an internal organ of a patient comprising a computer and a screen connected to the computer for displaying at least one image of the internal organ.
• the computer is arranged to determine from at least one medical examination previously carried out on the internal organ, at least one zone of confidence and / or at least one affected zone, including at least partially one or several portions of the internal organ where samples and / or encompassing at least partially one or more areas previously identified as suspect during medical imaging, the determination being based on:
• the clinician thus has an image of the internal organ integrating an affected area and / or a zone of confidence taking into account the information acquired during the medical examination (the medical examination can be samples or medical imaging as radiological medical imaging, MRI, PET ).
• the displayed image is therefore not limited, for example, to the representation of the various samples and / or simply to a medical image itself (for example of the MRI type) but to the surrounding tissues of the different samples or a marked area. as suspicious during the medical examination.
• the medical examination being dedicated to the internal organ considered, and preferably dedicated to a localized study and internal to the organ, allows to personalize the zone of confidence and / or reached to each patient which allows the clinician to better estimate for example the appropriate treatment.
• zone of confidence means an area of the healthy internal organ without trace of disease
• affected area means an area of the internal organ at least partially already affected by the disease
• the computer is arranged to project a three-dimensional image of the internal organ on the screen.
• the computer is arranged to project two-dimensional cutting images of the internal member.
• the computer is arranged to cause the display on the image of the internal member of at least a portion of the internal member that has been punctured during sampling.
• the zone of confidence and / or impairment completely encompasses said portion.
• the zone of confidence and / or the zone reached is displayed on the screen with a color gradient as a function of the distance with respect to the associated sampled portion and / or the criticality of the surface. the ladie possibly detected in said portion.
• the zone of confidence and the zone reached are not displayed in the same color.
• the computer is configured to cause the display on the image of the internal member of at least one area of the internal member to preserve.
• the computer is further configured to partition the internal organ in elements and to display the partition formed by these different elements on the image of the internal organ.
• the zone of confidence and / or the zone reached is formed by one or more elements.
• the computer is configured to cause the display on the image of the internal body of at least one information in connection with the confidence zone and / or the affected area.
• the computer is configured to be able to display a general sick part encompassing at least a portion of the different zones reached.
• the computer is configured so as to partition the internal organ into different elements and to display the partition formed by these different elements on the image of the internal organ, the computer being further configured so as to display a diseased general part including at least one element of the partition comprising one or more affected areas.
• the computer is configured so that the general ill part also includes at least one element of the partition in contact with the partition element comprising one or more affected areas.
• the computer is configured to export the displayed image to an external device.
• the computer is arranged to define the zone reached and / or confidence also using a measurement error of the device that participated in the medical examination previously performed on the internal organ.
• the invention also relates to a method of visualizing an internal organ of a patient using a device as previously described comprising the step determine the zone (s) of confidence and / or zones reached and display the zone or zones.
• FIG. 1 represents a mapping system of the prior art
• FIG. 2 schematically illustrates a display device according to a first embodiment of the invention
• FIG. 3 schematically illustrates the image displayed by the display device represented in FIG. 2,
• FIG. 4 schematically illustrates the image displayed by the display device shown in FIG. 2 once a clinician has manipulated the cursors at his disposal
• FIG. 5 schematically illustrates the image displayed by a display device according to a second embodiment of the invention
• FIG. 6 schematically illustrates the image displayed by a display device according to a third embodiment of the invention.
• the display device according to the first embodiment of the invention is here intended to be applied to the visualization of a prostate of a patient.
• the visualization device can be applied to other internal organs of the patient such as the liver, a kidney, a uterus ...
• the device here comprises a computer 1 integrating a computer 2 and a screen 3 connected to the computer to display an image of the prostate 4.
• the device comprises several human-machine interfaces namely here the keyboard 5 and the mouse 6 of the computer.
• the computer 2 is arranged to project a three-dimensional image of the prostate 4 on the screen 3.
• the three-dimensional image of the prostate 4 is cut into a plurality of images of the prostate section. two dimensions, the clinician can request the display via the man-machine interfaces 5, 6 of the three-dimensional image or one of the two-dimensional images.
• the computer 2 is arranged so that the screen 3 simultaneously displays the images of the prostate 4 a line 7 provided with a cursor 8: by moving the cursor 8 on this line 7, for example using In the mouse 6, the clinician causes the passage from the display of a two-dimensional image to another two-dimensional image.
• the slider 8 is vertical and arranged so that the more the clinician lowers the cursor 8 down, the more the two-dimensional image displayed represents a lower part of the prostate 4 and vice versa.
• the computer 2 is arranged to cause the display on the different images of the prostate 4 of the various portions 9 (only one of which is referenced here) of the prostate 4 which have been punctured during previous samples taken on the prostate for a study of said Specimens.
• the computer 2 is furthermore arranged to display the different portions 9 in different colors depending on whether the result of the analysis of each sample is positive or negative. For example portions 9 where a disease has been detected are displayed in dark red and portions where disease has not been detected are displayed in dark green.
• the computer is arranged to display the different portions 9 in different colors depending on whether the result of the analysis of each sample is positive or negative and according to the level of criticality (severity of the detected disease and / or propensity of said disease to develop ie possible disease progression) in the sample concerned and / or surrounding. For example portions 9 where a disease has not been detected are displayed in the same dark green color and the portions where a disease has been detected are red more or less dark depending on the level of criticality.
• the computer 2 is here also arranged to determine from said sampling zones of confidence 10 (only a part of which is referenced here) in three dimensions and affected areas 11 in three dimensions of the prostate and to display on the different images said zones.
• the zones of confidence 10 and the affected zones 11 are here defined so as to respectively encompass one of the portions of the prostate previously punctured and for which no disease has been detected (for confidence zones 10) and one of the portions of the prostate previously punctured and for which a disease has been detected (for affected areas 11).
• the zones of confidence 10 and the zones affected 11 are here defined so as to be centered around the sampled portion corresponding, fully encompassing the portion concerned.
• the affected areas 11 and / or the confidence zones 10 are defined so that their dimensions vary with the level of criticality detected in the associated sample and / or in the neighboring sample or samples.
• the computer 2 is further arranged to display the confidence zones 10 and the affected areas 11 in different colors.
• the computer 2 respects for this purpose the color code associated with portions 9 having been punctured.
• the zones of confidence 10 are thus here in green and the zones affected 11 in red.
• the computer 2 is here shaped to display the zones of confidence 10 and the zones reached 11 according to a color gradient as a function of the distance with respect to the associated sampled portion 9 as well as the criticality of the disease possibly detected in said portion 9.
• the confidence zones 10 are in a darker green than the associated sampled portion 9 and in a green less and less dark as one moves away from said portion 9.
• the affected areas 11 are in a red color as well. dark than the corresponding 9 removed portion in case of very high cancer risk (for example in the case of TNM stage T4 N0 MO or in case of Gleason G8 or in case of "high risk" on a classification of Amico) and affected areas 11 are in a less dark red than the associated 9 removed portion and in a less and less dark red as one away from said portion 9 in the other cases of classification of the detected disease.
• the computer 2 is further configured to cause the display of one or more areas of the prostate to preserve, as far as possible, any treatment on the different images of the prostate.
• the different images of the prostate 4 here comprise a representation of the urethra, as an area to be preserved 12.
• the zones to be preserved 12 are here represented in a different color than the zones of confidence 10 and reached 11 as well as the associated portions 9. For example the areas to be preserved 12 are displayed in blue.
• the rest of the images of the prostate 4 is shown in a different color than the zones of confidence 10 and the affected areas 11, the associated portions 9 and the areas to be preserved 12 or else is not colored.
• the clinician provides calculator 2 with the results of the samples taken (for example, the classifications of the various samples on the Gleason, d'Amico or TNM grades). It should be noted that the clinician can modify these results (or provide additional data to complete these results) based on experience and / or results from other medical examinations such as medical imaging.
• the device thus offers the clinician flexibility in generating the displayed images.
• the clinician typically enters this data of the samples and / or these additional data using the keyboard 5 and the mouse 6.
• the computer 2 determines the different volumes forming the zone of confidence 10 or zone 11 around the portions where the biopsies have been performed.
• the calculator defines the volume around a portion 9 where a biopsy has been performed by multiplying the volume of said portion 9 by a predetermined fixed percentage and by a variable factor calculated according to the criticality (severity detected disease and / or propensity of said disease to develop) of a disease detected on said sample (and optionally also on neighboring samples).
• a computer configured so that for each zone of confidence the computer 2 defines the volume around a portion 9 where a biopsy has been performed by multiplying the volume of said portion 9 by a predetermined fixed percentage and by a variable factor calculated based, for example, on the criticality of a disease detected on neighboring samples.
• calculator 2 also determines the different volumes forming areas to preserve 12 for example using anatomical models.
• the computer determines the display colors of the various portions 9 punctured and 10 confidence zones, reached 11 and preserve 12.
• the computer 2 is also configured to manage the overlap between the zones of confidence and healthy when two samples are close.
• the affected zone 11 prevails and completely replaces the associated confidence zone.
• the dimensions of the affected zone 11 will therefore be larger than that of the associated confidence zone 10.
• the colors of the affected zone 11 will replace those of the zone of confidence 10.
• the computer 2 causes the images of the prostate 4 to be displayed in three dimensions with the insertion of the confidence zones 10, the affected zones 11 and the zones to be preserved 12 on said images according to the color code supra.
• the clinician can furthermore control, via the human-machine interfaces, a modification:
• the clinician is thus allowed to adapt the displayed images so that they are as representative as possible of reality, benefiting from the experience of the clinician who may also have access to other data such as radiological medical images.
• the volume around a portion 9 where a sample has been taken is defined in a predetermined manner by the computer 2 while being adjustable by the clinician himself.
• the computer 2 is further configured to be able to display a general ill portion 14 encompassing the different areas affected 11.
• the calculator 2 thus makes it possible to display the boundaries between the parts considered to be sick of the prostate, which makes it possible to assist the clinician even more in his work.
• the computer 2 is further arranged to display the general portion 14 in a colored manner.
• the calculator 2 respects for this purpose the color code associated with portions that have been punctured and for which a disease has been detected.
• the general sick part 14 is here in red.
• the computer 2 is here shaped to display the general patient part 14 according to a color gradient as a function of the distance separating the different areas affected 11 and the criticality level of the disease detected in the associated portions.
• the general patient part 14 is in a deep red between the affected areas 11 comprising at least one affected area 11 associated with a sample noted with a very high risk of cancer (for example in the case of TNM stage T4 NO MO or in the case of grade Gleason G8 or in case of "high risk" on a classification of Amico) and the general sick part 14 is in a less dark red for the rest of the general sick part 14.
• a very high risk of cancer for example in the case of TNM stage T4 NO MO or in the case of grade Gleason G8 or in case of "high risk" on a classification of Amico
• the dimensions and / or the color code of the general patient part 14 can be modified by the clinician via the human-machine interfaces.
• the computer 2 is arranged so that the screen 3 simultaneously displays the images of the prostate 4 a second line 20 provided with a second cursor 21: by moving the second cursor 21 on the second line 20, for example with the aid of the mouse 6, the clinician causes the progressive enlargement of the general part 14 from a display without a general ill part 14 ⁇ corresponding to FIG. 3) up to the maximum dimensions defined by the calculator 2.
• the second slider 21 is vertical and arranged so that the more the clinician lowers the second slider 21 down, the larger the dimensions of the general part 14 and vice versa.
• the clinician is thus allowed to adapt the general ill portion so that the displayed images are as representative as possible of reality, benefiting from the experience of the clinician who may also have access to other data such as radiological medical images. This allows the clinician to better integrate the volume to be treated. It can thus be seen that the images displayed are personalized to each patient, whether or not the clinician intervenes on the images once these have been generated by the computer 2.
• the computer 2 is configured to allow the export of the images displayed and made using the computer to an external device.
• a device is for example a processing device or any other device requiring information contained in said images.
• the computer 2 uses a standard exchange model to transfer the images, for example, although not exclusively, an exchange model meeting the DICOM standard (for Digital Imaging and Communications in Medicine). ).
• the predictive power of the sample follows a normal distribution as a function of the distance to the sample.
• the law of decreasing the reliability of the information as a function of the distance to the sample is thus modeled with a Gaussian function.
• ⁇ Set of a reference volume considered, ⁇ 6 R 3 (Three-dimensional space of real numbers), ⁇ is a measurable space;
• Biopsy carrot that is to say samples of index n, n 6 N (the set of natural numbers);
• Sub-volume of ⁇ (graphical representation) corresponding to the carrot and corresponding also to a portion taken 9;
• ⁇ volume of representation corresponds to any volume belonging to Q and defines as zones of confidence, zones affected
• a geometrical shape representing the volume around the core C n with respect to the zones of confidence and the zones affected is also chosen.
• a cylinder is chosen here.
• the parameters ⁇ and ⁇ are determined here from the results of the biopsy (and possibly the results of other medical examinations such as visual scores attributed to suspicious areas identified during medical imaging or other results. or scores) so that these parameters are thus specific to each patient.
• the zones of confidence and the areas affected are determined not only from the analysis of the samples taken but also from a statistical approach of the presence of healthy or unhealthy tissues around the samples taken (by intermediate here of the Gaussian function giving a density of probability).
• these parameters are independent for each core C n considered.
• the definitions of said Gaussian parameters thus make it possible to assign several types of Gaussian function f, thus several types of probabilities, to the different cores. Take the example of a cancer detected in some carrots with a very high Amico score (high propensity to expand): the clinician can then choose to apply a very strong standard deviation for the cores concerned.
• This distance d is for example a distance Euclidean.
• the distance d is then preferably taken perpendicular to the cylindrical core C n .
• the probability used is to keep the local maximum for each point of the discrete space used (pixel, metric unit, cell) for the areas of trust as for affected areas.
• a denotes a threshold value, predetermined and modifiable by the clinician ae [0; 1 [. This value is given empirically or perhaps deduced from histological information intersected with the inputs of the algorithm (cylinder size, probability, Gaussian function). If a is chosen equal to 0, only volume B is considered for the subset belonging to A and B.
• the second embodiment of the invention is identical to the first embodiment of the invention, with the difference that the computer 2 is further configured to partition the prostate into different elements. referenced here) and to display the partition formed by these different elements 15 on the images of the prostate 4.
• the prostate is partitioned in a "patient-specific" manner automatically.
• the prostate is for example partitioned into twelve elements.
• the elements are for example in the form of triangles or quadrangles but the partition can be done in any other way for example via segment planes, ellipsoids, functions ...
• the clinician can furthermore control via the man-machine interfaces a modification of the partitioning of the prostate.
• the screen information 17 including indications on each of the elements 15 of the partition such as the number of the element and the volume of this element (this information is not shown here) in Figure 5 only for one element).
• an indication of the severity of the disease detected within this element is displayed, for example "Gleason 5 + 4 (B11)”. and 4 + 3 (B13) "as well as” Probability cancer: very strong "(according to D'Amico's classification).
• the computer 2 is furthermore configured to calculate and display a general ill portion 14 encompassing at least the different affected areas 11 and formed by one or more elements 15 of the partition.
• the calculator 2 thus makes it possible to display the boundary of the portion considered to be sick of the prostate, which makes it possible to assist the clinician even more in his work.
• the general patient portion 14 is for example determined based on a statistical approach to the presence of healthy or unhealthy tissues around the affected areas 11, the statistical approach being based here on the result of the samples of the different portions of the prostate.
• the general ill part 14 is formed of all the elements 15 of the partition having a face in common with an element 15 of the partition comprising an affected zone 11 associated with a sample noted with a very high cancer risk (for example in case of TNM T4 N0 MO stage or in case of Gleason G8 grade or in case of "high risk" on a classification of Amico) as well as by the element 15 concerned.
• the general sick part 14 can thus encompass areas yet displayed as trusted because of its elemental structure 15.
• the clinician can furthermore control, via the human-machine interfaces, a modification of the dimensions of the general part 14.
• the computer 2 is further arranged to display the general part ill respecting the color code associated with the portions having been punctured.
• the general sick part 14 is thus represented in red.
• the computer 2 is here shaped to display the general patient portion 14 according to a color gradient as a function of the distance separating the different zones and the criticality level of the disease detected in the associated portions.
• the general patient portion 14 is in a deep red at the level of its element 15 comprising an affected zone 11 associated with a sample noted with a very high risk of cancer (for example in the case of a TNM T4 NO MO stage or in the case of a grade Gleason G8 or in case of "high risk" on a classification of Amico) and the general part sick 14 is in a less dark red for the rest of the general sick part 14.
• a very high risk of cancer for example in the case of a TNM T4 NO MO stage or in the case of a grade Gleason G8 or in case of "high risk" on a classification of Amico
• the computer 2 is also configured to display on the images of the prostate 4 an area detected as suspect 16 during a previous medical examination other than the samples for example during an MRI or during an imaging PET (positron emission tomography). Only the edges of the zone detected as suspect 16 are typically displayed for example in dashed lines.
• the images displayed are personalized to each patient, whether or not the clinician intervenes on the images once these have been generated by the computer 2.
• the computer 2 is configured to allow the export of the images displayed and made using the computer to an external device.
• a device is for example a processing device or any other device requiring information contained in said images.
• the computer 2 has here resorted to a standard exchange model for transferring the images, for example, although not exclusively, a DICOM exchange model (for Digital Imaging and Communications in Medicine).
• a DICOM exchange model for Digital Imaging and Communications in Medicine
• the third embodiment of the invention is identical to the first embodiment of the invention, with the difference that the medical examination previously performed on the prostate is medical imaging (for example MRI or PET).
• medical imaging for example MRI or PET.
• the computer 2 is thus arranged to cause the display on the different images of the prostate 4 of one (or more) suspect zone 22 detected during medical imaging. In this case, only one suspect zone has been detected.
• This suspect zone is for example represented using semi-automatic contour detection algorithms with a possible manual adjustment.
• the computer 2 is further arranged to display the suspect zone 2 colored.
• the colored area is for example dark red.
• the computer 2 is here also arranged to determine from said suspect zone 22, an affected area 11 in three dimensions of the prostate and to display on the different images said affected area 11.
• the affected area 11 is here defined so as to encompass the suspect zone 22.
• the affected zone 11 is here defined so as to be centered around the suspect zone 22.
• the suspect zone 22 can be defined from the analysis of the score previously given to the suspect zone 22 (as for example using the PI-RADS or LIKERT scale) as well as a statistical approach. the presence of healthy or unhealthy tissue around said suspect zone (for example via a Gaussian function giving a probability density with a fixed percentage and a variable percentage as in the first embodiment).
• the computer 2 is further arranged to display the affected area in a colored manner.
• the computer 2 respects the color code associated with the suspect zone 22.
• the affected zone 11 is thus in red.
• the computer 2 is shaped to display the affected area 11 according to a color gradient as a function of the distance vis-à-vis the associated suspect zone 22.
• the computer 2 is further configured to cause the display of one or more areas of the prostate to preserve, as far as possible, any treatment on different images of the prostate 4.
• different images of the prostate 4 here comprise a representation of the urethra as an area to be preserved 12.
• the zones to be preserved 12 are here represented in a different color than the affected zone 11 as well as the suspect zone 22.
• the zones to be preserved 12 are displayed in blue.
• the rest of the images of the prostate 4 is shown in a different color than the affected area 11, the suspect area 22 and the areas to preserve 12 or is not colored.
• the clinician can furthermore control, via the human-machine interfaces, a modification:
• the clinician is thus allowed to adapt the displayed images so that they are as representative as possible of reality by benefiting from the experience of the clinician who may also have access to other data such as sampling data for example.
• the computer 2 is arranged to display on the screen information 17 giving an indication of the name and the volume of area to be preserved (for example "1 cm 3 urethra") or the volume of the suspect zone and a probability of cancer of said zone (for example "8 cm 3 , Probability cancer: strong").
• the images displayed are personalized to each patient, whether or not the clinician intervenes on the images once these have been generated by the computer 2.
• the computer 2 is configured to allow the export of the images displayed and made using the computer to an external device.
• a device is for example a processing device or any other device requiring information contained in said images.
• the computer 2 has here resorted to a standard exchange model for transferring the images, for example, although not exclusively, a DICOM exchange model (for Digital Imaging and Communications in Medicine).
• a DICOM exchange model for Digital Imaging and Communications in Medicine
• the device may include a different number of man-machine interfaces.
• the man-machine interface (s) may be different from what has been cited and be for example a touch screen, a control unit comprising buttons, a stylus ...
• the computer makes it possible to display both a three-dimensional image of the internal member and two-dimensional sectional planes of the internal member
• the computer can be arranged to project only the three-dimensional image or the two-dimensional sectional planes of the internal organ (then forming a global three-dimensional study of the internal organ) or may project only one or several section plans in two dimensions.
• the three-dimensional image is cut into a plurality of two-dimensional prostate cutting images along a sectional plane normal to the cranial / caudal axis
• the three-dimensional image can be cut into two-dimensional planes along other cutting axes such as the anterior / posterior axis or the transverse axis.
• the computer will be able to display both the three-dimensional image of the internal member and the three series of two-dimensional sectional planes of the internal member defined along the three aforementioned axes.
• the calculator will then be able to display a different cursor associated with each series of cutting planes so that a clinician can move independently in each series of section planes.
• zones and / or general parts are always displayed together, it will also be possible to display only the zones (in part or in whole) and / or general parts. For example, a clinician will be able to select via the human-machine interface what he wants to see in the image.
• the computer can be configured to display different information on the image.
• each zone affected and / or trusted and / or protected can be numbered.
• Metric indications may be assigned to one, several or all zones. It will be possible to insert information on the level of criticality (severity of the detected disease and / or propensity of said disease to be developed) of diseases detected at the level of the sampled portions and / or at the level of the zone considered.
• Clinical information on the image may be added, such as inserting a representation of areas palpated by the clinician, suspicious areas identified by other examinations than the biopsy.
• Areas of trust and / or impairment may be defined from the results of the analyzes and / or by a statistical approach, for example based on clinical studies, statistical distribution maps, distribution models (thus making it possible to partition an organ into different elements and to associate one or more elements with a zone of confidence and / or a zone reached) and / or optimal distribution models (allowing in addition to associating the adjacent elements, with elements already associated with a zone reached , at the said affected area), probabilities of disease as a function of the position in the internal organ of suspicious zones or sick specimens, of statistical functions ...
• the statistical approach is personalized to each patient because it is based on at least a portion of the internal organ where at least one sample has been taken and / or the area previously identified as suspect u medical imaging course, to define areas of trust and / or impairment.
• the zones trusted and / or affected can be directly formed by one or more elements of partitioning.
• the clinician may modify the volumes or the areas of the zones of confidence and / or zones affected and / or areas to be preserved and / or general parts vis-à-vis what has been calculated and displayed by the device. This will further tailor the calculations to the patient's own case based on the clinician's experience.
• the clinician may request via a human-machine interface that the elements having a common surface with said elements are also raised so as to increase the size of the affected areas and / or confidence and / or one or more general parts.
• the zones of confidence, the affected areas and the general part of the patient are represented in a color gradient
• other types of representation for example binary (either colored or non-colored) can be envisaged. or a transparency gradient (more or less opaque zones depending on the level of criticality of the detected disease).
• the general parts can be displayed differently for example in the form of a partition by displaying the edges of the partition elements and / or the faces of said elements.
• the zones of confidence and / or reached and / or confidence can be displayed differently eg as a partition by displaying the edges of the elements of the partition and / or the faces of said elements.
• we have chosen a normal law we can choose any other type of law to define the areas of confidence and / or reached. It will also be possible to choose different types of laws depending on the zones to be defined. For example, the applicable laws may be exponential, logarithmic or even linear.
• the zones affected and / or confidence can be defined according to the measurement error that can make the device and / or device that participated in the medical examination previously performed on the internal organ .
• the medical examination is medical imaging
• the device that allowed this imaging will generate an image with an error and we will detect a suspicious area with an error on its location, error that will be reported in the calculations to determine a affected area.
• the test is a biopsy
• l r where the biopsy will be displayed on an image can be shifted to where the biopsy was actually really done. In this way, if a carrot of biopsy contained cancerous cells, said cells could come from an area actually shifted by 1 millimeter vis-à-vis the area displayed on the screen as being supposed to be that of the biopsy .
• the computer of the device may be configured to automatically take into account the errors of the device itself and / or of the apparatus which allowed the preliminary medical examination (biopsy and / or medical imaging) in its calculation of the area reached and / or confidence.
• the error will generally depend on the type of imaging used and / or the type of registration (for example elastic or rigid) used (for biopsy as for medical imaging, in fact during a biopsy keeps an imaging in order to be able to study where the biopsy is performed in the internal organ).
• the computer will be configured to accumulate if desired the various errors in its calculation of the area reached and / or confidence (it may indeed be cumulative errors for example in the case of a multiple registration).
• the device can thus be configured to recover in a database the errors associated with each type of imaging and each type of registration and calculate the zones of confidence and / or reach once, for example, the practitioner will have indicated the type of imaging and the type of registration used.
• the error will be considered to be + or - a millimeter or + or - 2 millimeters, for an MRI type of imaging to be + or - 5 millimeters, for an ultrasound-type imaging to be of + or - 1 millimeter ...
• the errors may be different depending on the measurement axes of the device and / or the device that participated in the medical examination previously performed on the internal organ.
• the medical examination is an imagery MRI-type medical device
• the device that allowed this imaging will generate an image with a different error on one of its three axes vis-à-vis its other two axes since the resolution on one of its axes will typically be 3 millimeters while it will be 0.7 millimeters on the other two axes.
• the distance "d" chosen in the algorithm is a Euclidean distance
• one can choose other types of distances such as for example a mean distance to the sample or the distance from Chebyshev.
• the Chebyshev distance can be used to define a distance at the cellular level. From here, one could also use the concept of Moore's neighborhood used in cell biology by defining a Moore neighborhood of order N to each cell or cluster of cells considered a carrot ' C n .
• each core has been considered as a single element, a core C n can be subsampled into a set of k "pieces" of core defined as The algorithm will then be applied to the elements
• the device of the first embodiment may be shaped to cause the display of information as in the second embodiment and in the third embodiment.
• this information may for example include an indication of the criticality of the disease detected within each sample, indications on the volume of samplings, indications on the volume of the zones affected, of confidence, to preserve, on a suspect zone ...
• the device of the first embodiment could be configured to display on the images an area detected as suspect during a previous medical examination as in the second embodiment.
• first embodiment or the second embodiment with the third embodiment, that is to say, display on the images both zones of confidence and / or those related to samples taken and to both affected areas related to an area identified as suspicious during a previous examination of medical imaging.
• This will advantageously benefit from the complementarity of information between medical examinations of the biopsy type and medical examinations of the medical imaging type.
• the third embodiment with several suspect zones represented (and the corresponding affected areas)
• it will be possible, as in the first embodiment or the second embodiment, to have the device configured to define and display a general ill part framing the different suspicious areas (and modifiable by the clinician).
• the partitioning of the internal organ into different elements can be applied to any described embodiment.

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• 2016
  • 2016-12-08 FR FR1662141A patent/FR3059885B1/fr active Active
• 2017
  • 2017-12-07 US US16/466,550 patent/US11026639B2/en active Active
  • 2017-12-07 EP EP17816640.1A patent/EP3551041A1/de active Pending
  • 2017-12-07 CN CN201780075976.7A patent/CN110049715B/zh active Active
  • 2017-12-07 WO PCT/EP2017/081838 patent/WO2018104458A1/fr unknown
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