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    • 专利摘要:
    The method for quantifying the presence of fats in a region of the heart (10) comprising: • an acquisition of an image of at least one cavity (25, 26, VG, VD) of the heart (10) and a wall (20, 21, 21 '); A selection of at least one pixel (27) of a core section (10) having a pixel density (Dv) included in a first range of values (G1); • a selection growth of at least one pixel (27) to define an extended area (27) 3D delimited by the cavity; A homogeneous dilation operation of the extended 3D zone making it possible to define an expanded volume (27 '); An extraction operation of a peripheral region (20 ') resulting from the subtraction between the expanded volume (27) and the extended 3D zone (27'); A quantization of the number of pixels of a second range of values (G2) within the peripheral region.
    公开号:FR3020700A1
    申请号:FR1453941
    申请日:2014-04-30
    公开日:2015-11-06
    发明作者:Hubert Cochet；Pierre Jais
    申请人:Institut National de la Sante et de la Recherche Medicale INSERM；Centre Hospitalier Universitaire de Bordeaux；Universite de Bordeaux；
    IPC主号:
    专利说明:

    [0001] METHOD FOR QUANTIFYING THE PRESENCE OF FAT IN A HEART REGION
    [0002] FIELD The field of the invention relates to methods for quantifying the presence of fibro-adipose tissue in a region of the heart, particularly in the thickness of the myocardial wall. The method of the invention also relates to systems for processing digital images obtained by scanning and for performing operations to achieve such quantification and, in addition, to generate a mapping of regions comprising fibro-adipose masses.
    [0003] STATE OF THE ART The current imaging methods make it possible to evaluate visually from images obtained from CT or MRI acquisitions the presence of fibro-adipose tissue in the region of the heart, particularly at the surface of the wall. myocardium of the right ventricle. On the other hand, the current methods do not make it possible to obtain a quantification of fibro-adipose masses and a mapping of the distribution of these masses on the surface of the wall of the heart and in the thickness of the wall. SUMMARY OF THE INVENTION The invention aims to overcome the aforementioned drawbacks. An object of the invention relates to a method for a quantification of the presence of fats in a region of the heart. The method comprises: an acquisition of a three-dimensional image of at least one cavity of the core and a wall delimiting said cavity; a selection of at least one pixel of the cavity defining a seed; a growth of the seed step by step until reaching an area of a pixel density below a predefined threshold, the growth of the seed leading to the definition of a delimited extended zone whose pixel density included in a first range of values, the 3D image obtained by growth being called "extended 3D zone"; an expansion operation of the extended 3D zone for defining an expanded volume comprising at least a part of the thickness of the wall of the cavity in question; an extraction operation of a peripheral region resulting from the subtraction of the volume from the extended 3D zone to the expanded volume; A quantization of the number of pixels of a second range of values of the extracted peripheral region. An advantage of such a method is to quantify a proportion of fat masses in the wall to perform analyzes. Thus it is also possible to map the wall of the heart. This method has many applications in particular in guiding an intervention on the heart, in identifying a type of muscle wall of the heart of a patient, in the prognosis of an attitude of the heart or in the diagnosis of a pathology of the heart. Finally, this method makes it possible to model certain specific densities of a core so as to establish statistics of a given population for example to establish a data repository. According to one embodiment, the acquisition of a three-dimensional image of the core is carried out by means of a scanner, the density of the pixels of the image being expressed in the Hounsfield unit. According to one embodiment, the method for a quantification of the presence of fats in a region of the heart comprises: a definition of at least one boundary of the three-dimensional image of the considered cavity of the heart; the growth of the seed taking place until it meets at least one border or zone with a pixel density lower than the predefined threshold.
    [0004] According to one embodiment, the boundary makes it possible to separate the portion of the acquired image comprising the cavity considered from an orifice opening into said cavity whose pixel density is in the first range of values. An advantage of defining a boundary (s), for example forming a plane, is that it makes it possible to limit the growth zone to a given volume. As a result, the definition of boundary (s) forming planes makes it possible to limit the calculations during the growth operation to the region extending into an orifice. Thus, the density of the pixels near the orifice or in the orifice are not compared with a predefined threshold, which limits the calculation operations. Indeed, the region extending into the orifices of the cavity, acquired at the same time as the image, does not comprise a wall in which it is desired to calculate pixel densities of the second range of values, for example corresponding to masses. fat. According to one embodiment, the growth of the seed takes place in three dimensions from a selection of pixels on a cutting plane of the cavity. According to one embodiment, the growth of the seed takes place in two dimensions on each sectional plane of the cavity, the "extended 3D zone" being reconstituted by the set of "extended 2D zones". An advantage of the growth operation from an automatic or manual selection of pixels in the cavity is that it quickly makes it possible to obtain the 3D contour of the cavity. An advantage of doing so is to benefit from a homogeneity of the pixel density of the cavity 25 to facilitate growth step by step. Indeed, such a growth operation performed from a selection of pixels of the wall would be more difficult to achieve since the wall can potentially include a large disparity of pixel density. Such an operation would lead potentially to clutter errors of the region formed by the wall 30 taking into account, for example, the presence of grease having a different pixel density that is sought precisely to be isolated by means of the method of the invention. According to one embodiment, the predefined threshold is defined with respect to a determination of a reference pixel density calculated from a measurement in the acquired image, said acquired image comprising the cavity and at least one of the walls. of said cavity. According to one embodiment, the reference density is calculated from a measurement made on the pixels of the cavity, the reference density corresponding to a low limit of the first range of pixel density values. According to one embodiment, the reference density is calculated from a measurement made on pixels of a wall defining a region of interest, the reference density corresponding to a high limit of a third range of values. pixel density of the region of interest. According to one embodiment, the reference pixel density is calculated in a range of values between the first range of values and the third range of values so as to better discriminate the membership of a pixel to one of these ranges of values. According to one embodiment, the measurement of the reference density is chosen from a predefined value corresponding to a typical profile of a core. An advantage of a calculation of a reference density is to allow an extension of the seed up to the internal limit of the cavity, called the endocardium, without "biting" on pixels of the wall. This solution makes it possible to isolate the entire region of the wall to count pixels having a certain density of pixels. As a result, the measurements on the wall have a good accuracy and take into account the entire thickness of the wall. Finally, this allows a simple operation of comparing a pixel density during the growth operation by ensuring good discrimination between the pixels of the wall and those of the cavity. According to one embodiment, the dilation operation is repeated a plurality of times to generate a plurality of dilated 3D images, the successive expansions being determined such that each new dilated 3D image comprises the previous dilated 3D image. In one embodiment, a 3D layer of a peripheral region of the extended 3D image is extracted by subtracting a Nth dilated image from the extended 3D image to the Nth expanded image of the extended 3D image.
    [0005] One advantage of this layer-by-layer extraction solution is that the wall is cut thinly to isolate certain pixel densities from a layer. The layer-by-layer treatment of the wall allows a better segmentation of the region defining the wall, in particular to limit the operation of counting the pixels of a density given to the epicardium without exceeding it. According to one embodiment, a quantization operation comprises counting the number of pixels of a density comprised in the second range of values in an extracted 3D layer or a 3D peripheral region. An advantage of this operation is that it makes it possible to calculate the proportion of certain pixel density corresponding, for example, to fat masses. Indeed, the regions having fat masses in the wall can be isolated by calculating the density of 15 pixels in a certain range of value in the wall. This is possible because the pixel density of the fat has values different from the densities of the muscle pixels. According to one embodiment, a thresholding operation of the pixel densities of the peripheral 3D region comprises a distribution according to a plurality of ranges of values of different proportions of pixel densities. According to one embodiment, a generation of a 3D mapping of the wall of the cavity comprises the representation of the pixels of a density comprised in the second range of values with a predefined colorimetric coding. An advantage of this embodiment is to allow an operator to visualize the wall of the heart for example to prepare an intervention. According to one embodiment, a generation of a 3D mapping of the wall of the cavity comprises a subdivision of the second range of values into a plurality of sub-ranges of values corresponding to different proportions of pixel densities with a predefined color coding 35 assigned to each subdivision.
    [0006] An advantage of this embodiment is to allow to visualize different regions of the wall with different colors on a screen according to the level of fat present in the regions. The use of a segmented colorimetric coding allows a better appreciation of the areas impacted by the presence of fats. Advantageously, the dilation operation comprises a uniform extension of the wall of the three-dimensional volume of the 3D zone. This extension can be defined preferentially over a distance of between 1 mm and 12 mm. A value of 3 mm is particularly advantageous for quantifying the presence of fats in the wall of the right ventricle. Advantageously, the reference density is determined from a selection of pixels in a wall separating the right ventricle from the left ventricle. According to an exemplary embodiment, the first range of values is between 200 and 400 UH. The third range of values is between -100 and 100 HU. The second range of values is between -30 and -10 HU. Advantageously, when different dilations are configured to obtain a plurality of 3D images, each new dilated 3D image comprises a uniform layer having a thickness of at least one pixel in addition to the previous dilated 3D image.
    [0007] Advantageously, according to an exemplary embodiment, the heart cavity is the right ventricle and the valvular planes are the tricuspid and pulmonary planes. Advantageously, the terminals of the second range of values are defined to identify greasy masses in the wall.
    [0008] Another object of the invention relates to a system for visualizing an imaging of an organ for visualizing fat masses, implementing the method of the invention. The system of the invention comprises: a display device allowing: to display a section of a three-dimensional image acquired by a scanner; o to display a three-dimensional image whose mapping generated by the method of the invention; a selector: o at least one pixel to define a reference density and, o at least one pixel to generate an extended 3D zone obtained by growing step by step; a tool for drawing a line defining at least one valve plane; an interface: o to set the expansion distance d or a dilation proportion; o to extract a three-dimensional oversize from the volume coming from the extended 3D zone and dilated 3D zone; calculating means for: counting the number of pixels of the three-dimensional excess thickness having a density within a predefined value range; o Perform all calculations to process operations on 3D images, including expansion, extension, extraction. BRIEF DESCRIPTION OF THE FIGURES Other features and advantages of the invention will become apparent upon reading the following detailed description, with reference to the appended figures, which illustrate: FIG. 1: a view of a core and regions forming cavities and walls; FIG. 2A: a section of a three-dimensional image of the heart captured by a scanner with the definition of a valve plane according to the method of the invention; Figure 2B: a selection of an area to be extended according to the method of the invention in a 2D or 3D region of the image obtained from a heart chamber, here representing the right ventricle; FIG. 2C: a growth of a zone according to the method of the invention in a 2D or 3D region of the image obtained from a heart chamber representing here the right ventricle; FIG. 2D: the generation of an extended 2D or 3D zone defined in particular by the internal edge of the wall defining the cavity according to the method of the invention; FIGS. 3A, 3B: a generation of a dilated extended 2D or 3D zone comprising the cavity and the wall according to the method of the invention; FIG. 3C: the generation of a 2D or 3D peripheral zone defining the analyzed wall, obtained by subtracting the zone defining the cavity according to the method of the invention; FIG. 4A: a thresholding on a histogram making it possible to define the pixels of the image containing fibro-adipose tissue, and thus to quantify the content of fibro-adipose tissue contained in the wall and to map the distribution according to the method of the invention; Fig. 4B: an example of a range of values in which the reference pixel density can be calculated; Figure 5: The main steps of the process of the invention. DESCRIPTION Figure 1 shows a human heart. FIG. 1 shows, within the heart 10: a left ventricle, noted VG, a right ventricle, denoted VD, a right atrium, denoted OD, and a left atrium, denoted OG. In the following description, we call "cavity" a circulating blood volume contained in the heart and limited by cardiac walls. There are 4 cavities in the heart: a left ventricle VG, a right ventricle VD, a right atrium OD and a left atrium OG. The cavities accommodate a flow of blood that passes between the different arteries, veins and valves connecting certain volumes between them. By way of example, the tricuspid valve 16 is shown between the right ventricle VD ^ ^ ^ ^ ^ 15 and the right atrium OD, the mitral valve 15 is also shown between the left atrium OG and the left ventricle VG. In addition, the aorta 14 is shown arising in the left ventricle VG and the pulmonary artery 13 is shown arising in the right ventricle VD.
    [0009] To better understand the following description, the valve orifices, aortic or venous opening or leaving each circulating blood volume of the heart are called "orifices". The method of the invention comprises a step comprising the acquisition of a 3D image of the heart or a region of the heart. Preferably, the acquired image comprises at least one cavity such as the right ventricle VD or the left ventricle VG or one of the atria OD, OG and the wall surrounding said cavity. This wall includes a muscle called myocardium, and extends from an internal boundary called "endocardium" to an outer limit called "epicardium". Figure 2A shows a sectional view of a 3D image of a heart acquired by means of a scanner. Different zones appear including: a zone delimiting the cavity of the right ventricle VD; a zone 20 delimiting the wall of the right ventricle VD; a zone 26 delimiting the cavity of the left ventricle VG; a zone 21 delimiting the wall of the left ventricle VG; - An area 21 'delimiting the wall between the two left and right ventricles, called the septum.
    [0010] The walls 20, 21 and 21 'are a single muscular wall surrounding the different cavities. The various notations 20, 21 and 21 'make it possible to differentiate an area of the wall 21' located between two cavities, such as, for example, the VD and VG, of a wall 20 or 21 separating a cavity from another organ or from the medium in which the heart is present.
    [0011] The zones represented in two dimensions delimiting regions of a sectional image are derived from zones of an image acquired in 3 dimensions. Thus, for example, the 3D zone is noted: the three-dimensional zone reconstituted from the set of 2D zones of each section plane. Thus, zone 25 will be denoted indifferently: a zone 2D denoting the section of a 3D image of the right ventricle VD which is represented in FIG. 2A; a 3D zone denoting the volume of the 3D image of the right ventricle VD resulting from the set of 2D sectional images of said zone. The method of the invention therefore comprises the acquisition of a 3D image preferably obtained by scanner. This acquisition step is denoted ACQ in FIG. 5. The image acquisition method is a tomodensitometry also called "scanning". These techniques are also identified as CT-scan or CAT-scan and rely on the measurement of X-ray absorption by the tissues of an organ. The digitization of the images makes it possible to reconstruct the 2D and 3D image of the anatomical structures of the observed region.
    [0012] The computer assigns each pixel of the image a gray scale value proportional to the X-ray attenuation by the corresponding body volume. The measured parameter is an attenuation coefficient that is commonly called "density". This density is specific to the imaged fabric. It is expressed in Hounsfield units (UH) and is distributed on a scale ranging from -1000UH for air at + 1000UH for cortical dense bone, through -50UH for adipose tissue and 0 for water. Within the heart, the density obtained by scanner differs between the wall and the cavity. Within the wall, fibro-adipose densities are different from normal muscle densities.
    [0013] The digitized 3D image can be acquired and saved by a computer that includes calculation means and a screen for viewing the generated 3D image. The 3D generated image comprises a volumetric distribution of pixels whose pixel density can be measured in particular by selecting a given pixel or a given area. For example, it is possible to calculate the mean and dispersion of the density values, i.e. the standard deviation, within a selected pixel group in the imaging plane or volume. Such a pixel selection is called a "region of interest". The method of the invention comprises a step for defining at least one plane defining at least one processing boundary of the 3D images considered in the subsequent steps of the method. This or these plan (s) are named (s) plan (s) valvular (s) in the following description s. This step is denoted PLAN VALV in FIG. 5. A valve plane makes it possible to define a closed cavity from the point of view of the continuity of the blood flow circulating in the circulating blood volume defining the cavity. Depending on the cavities considered, different entry and exit sites are present so as to allow continuity of the circulating blood flow. In Figure 1, we see the input and output sites of the following core cavities: Cavity OD: 15 o input = cell veins; o output = tricuspid valve; ^ RV cavity: o inlet = tricuspid valve; o outlet = pulmonary valve; OG cavity: o entry = pulmonary veins; o output = mitral valve; ^ VG cavity: o inlet = mitral valve; 25 o outlet = aortic valve. FIG. 2A shows a valve plane 11 for separating the zone 25 into a first zone 250 and a second zone 251. The second zone 251 communicates from a point of view of the 3D image with a region corresponding to the artery. pulmonary 13 which comes out right ventricle VD. The definition of the valvular plane 11 makes it possible, from an image processing point of view, to dissociate the pulmonary artery 13 and the right ventricle VD by generating a plane boundary 11. As a result, it becomes possible through the definition of such a valve plan to apply image processing of the volume 250 by analyzing the similarity of the pixel densities while considering a closed volume. FIG. 1 represents a second valvular plane 12 which makes it possible to separate the right ventricle VD from the right atrium OD at the level of the tricuspid valve 16. The definition of these valvular planes makes it possible to define a closed 3D region for the image processing and subsequent operations that will be performed by the method of the invention. In theory, it is preferable to define as many valvular planes to as orifices present in the cavity considered. However, the definition of a cavity can make it possible to define a boundary separating a cavity from several orifices if the latter are co-located in a nearby region. According to an alternative embodiment, a boundary 11 or 12 may be defined as a curved surface or a set of planes. Fig. 2A shows a valve plane 11 defining an upper boundary of the right ventricle VD. A second valve plane such as the plane 12 can also be defined in this figure. An operator may also choose another cut image in which the orifices will be visible to best define the defined region. Thus, each valve plane can be defined on the same sectional image or on different sectional images of the 3D image acquired from the cavity. This step can be performed by an operator action from a tool of a graphics palette in which the image is editable. The operator draws a line manually, the line represented on the screen generates a section plane on the 3D image along the axis not shown in the image. Finally, according to a particular embodiment, the method of the invention makes it possible to generate a default plan that can be validated or modified by an operator. According to another embodiment, when the anatomy of a cavity considered is known in advance, for example if it is a human heart, then the valvular planes can be generated according to the proportions of the patient. image of the acquired heart and according to a detected orientation angle of the acquired image. A pattern recognition method may be used to: automatically identify and locate the inputs / outputs of the cavity and; Automatically generate planes, including the orientation and the position in the space, making it possible to separate the cavity considered from the input (s) and output (s). In all cases, a means of editing or modifying the valve plan generated by default can be offered to an operator who can adjust the orientation and / or positioning of the latter. When the cavity is the LV left ventricle, the right atrium OD or the left atrium OG, the method of the invention comprises a definition of at least one valve plane for closing the cavity of an orifice.
    [0014] The method of the invention comprises a step of selecting a reference pixel density. According to a first embodiment, this step preferably comprises a selection of pixels of a wall of the cavity. In this case, the reference pixel density is calculated to define a high pixel density limit of a region of interest defined in the wall. According to a second embodiment, the selection of a reference density can be chosen by a selection of pixels of the cavity. In this second mode, the reference pixel density defines a low limit of a pixel growth tolerance range as detailed hereinafter. According to a third embodiment, the reference pixel density is calculated between a range of pixel density values of the cavity and a range of pixel density values of the wall so as to discriminate the pixels of each of the regions. Finally, according to a fourth embodiment, the selection of a reference density can be performed by default as a function of the prior knowledge of the respective densities of the cavity and the wall in a given population. This pixel density defines a reference pixel density Dref. This step is denoted Dref in FIG. 5. The selection of a reference pixel density makes it possible, in particular, to parameterize a subsequent step of the method, in particular the growth step. According to the first embodiment of the selection of a reference density, this step of the method of the invention comprises the definition of a region of interest 22 drawn for example in the wall 21 '. This wall is called a myocardial wall. The definition of a region of interest 22 makes it possible to measure the mean and the standard deviation of the density of the pixels of this region, expressed in UH unit, that is to say in Hounsfield units. The region of interest 22 comprises at least one pixel. The objective of defining a region of interest 22 in the wall is to define a range of pixel density values whose reference pixel density Dref is calculated to define an upper limit of that range. The reference pixel density Dref serves as a reference in the step-by-step growth operation. During this growth operation, each pixel density considered in the growth operation is compared with the reference pixel density. The region of interest 22 may be defined on a 2D sectional image or may be defined in 3D to average the pixel density on a volume. According to a preferred embodiment, the region of interest 22 is defined in the inter ventricular region separating the right ventricle VD from the left ventricle VG. The wall 21 'offers a pixel density which makes it possible to define a good reference for subsequently carrying out a growth step without delimiting error of the extended zone. Another zone such as zone 20 or zone 21 may also be used alternatively to define a region of interest making it possible to fix a reference density Dref. This area is particularly well suited to serve as a reference for determining a reference pixel density Dref. According to another embodiment, it is possible to define a reference pixel density Dref not via a measurement in the image but according to a priori knowledge on the density of the wall in a given population. In this case, a default value can be generated based on a predefined setting. According to one embodiment, an operator selects a region of interest 22 manually, that is to say for example by means of a tool of a digital graphic palette or a mouse with regard to the image that appears on a screen. A region of interest 22 is thus defined in FIG. 2A. The display of the region of interest 22 in real time makes it possible to offer an operator a visual control, in particular to avoid taking pixels from cavities 25 or 26 respectively corresponding to the right ventricle VD and the left ventricle VG. According to another embodiment, an image processing software makes it possible to perform a shape recognition of a 2D or 3D image in order to recognize, for example, the right ventricle VD and the left ventricle VG in order to define a region of simple interest 22 in the wall 21 '. An automatic generated simple form can be a circle on the section view or a sphere on the 3D image.
    [0015] The method of the invention comprises a step comprising selecting at least one pixel 27 or a region 27 comprising a plurality of pixels. This pixel or region 27 defines a seed that will define an area that increases in volume to result in an extended 2D or 3D area filling the cavity. The cavity 250 comprises a pixel density greater than the density of the wall 21 '. This difference in density is explained by the nature of the tissues of the myocardium and that of the blood circulating in the cavity 250. In order to obtain a 2D or 3D region filling the cavity, the method of the invention makes it possible to start from a pixel or region selected within the cavity to extend gradually a zone enlarging according to a given criterion. This expansion step is denoted EXT ZONE in FIG. 5. One criterion may be to extend the region step by step to all the pixels whose density is greater than the reference density Dref.
    [0016] In the first embodiment corresponding to the calculation of a reference density in the wall, a threshold of density 3 standard deviations above the average measured in the wall can be chosen so that the region extends to the entire cavity but is limited to the inner side of the wall, that is to say the endocardium. The reference pixel density can therefore be chosen as the value corresponding to the above-average standard deviation density threshold measured in the region of interest 22 of the wall 21 '. In this case, the reference pixel density defines a high limit of the range of pixel density values defined around a mean density of a region of interest 22 of the wall.
    [0017] The extension of the zone 27 can be done uniformly in all the directions 28 of the 3D volume or the 2D plane corresponding to the zone 250. The method of the invention makes it possible to carry out this step of extending the zone 27 to a predefined density threshold is met. The pixel density threshold is set out of the pixel density tolerance that allows for step-by-step growth. When a pixel adjacent to the zone 27 comprises a density less than the predefined pixel density threshold, that is to say to the reference density, then the growth is stopped and the pixel encountered is not integrated into the growth zone 27. When the zone 27 increases to meet pixels adjacent to a wall 20 or 21 ', the growth operation ends. As a result, the growth of the zone 27 takes place until it meets the walls surrounding the cavity 250 which have a density lower than the density of the pixels of the cavity 25 or 250 and in particular lower than the density of reference pixels. defining the predefined pixel density threshold.
    [0018] According to the second embodiment of the step of selecting the reference density Dref, the method comprises selecting a reference density Dref of the cavity 27 and selecting a range of pixel growth tolerance.
    [0019] According to this embodiment, the step of growing the seed step by step can be performed by comparing the densities of adjacent pixels and their membership in a predefined range of values known as growth tolerance. This range of values is calculated from a measurement of the mean and the standard deviation of the densities within the cavity. It is possible to calculate a tolerance range by a percentage of the average density of the region initially chosen (for example +/- 30% of the average), or in a preferred embodiment by a deviation from the mean measured in standard deviation. (for example, average +/- 3 standard deviations). The density of the starting region within cavity 27 is therefore used to define the tolerance range. For example, if the pixel density of the starting region is 275 and the standard deviation of 25, the tolerance value range can be defined for example according to +/- 3 standard deviations from to the average, which makes it possible to define a range of values of [200, 350]. If a pixel adjacent to the zone 27 does not belong to this range, then the growth stops at this neighboring pixel in this direction of propagation. When a reference density of pixels Dref is chosen within the cavity, only a minimum threshold may be chosen because the values of the density of the pixels of the wall are smaller than that of the cavity. Thus, taking again the preceding example, a condition can be expressed in this way: as long as the density of pixels encountered step by step is greater than 200 HU, then the growth continues. The maximum limit 350 HU is optional. According to one embodiment, the criterion can be to extend the region 27 to the pixels adjacent to said region 27 if their density is within an interval close to the density of the pixels of the region 27. Thus the pixels of the seed can serve to calculate a reference pixel density. A tolerance threshold may be defined for analyzing the density of a neighboring pixel so as to generate, step by step, an extension of the zone 27 as shown in FIG. 2C. in the latter case, the second embodiment makes it possible to calculate a reference pixel density of the cavity as a low limit of a selection of pixels of the seed when the latter represents a region of interest having more than one pixel . Thus, the reference pixel density makes it possible to define the tolerance threshold.
    [0020] The predefined density threshold may be set in a range of values corresponding to the minimum pixel densities of the cavity 25. For example, it may be a percentage of a noted average density of a cavity. If the pixel density of the cavity is between 200 and 400 UH, then a wide threshold of 150 can be defined. By way of comparison, the pixel density of the acquired image, for example in the zone 21 ', is between 20 and 100 HU. Using an exemplary threshold of 150 HU, the zone 27 will extend to meet the boundary of the wall 20, 21 '. When a contrast agent is used in the blood circulating in the cavity 25, the pixel density of the image obtained from the cavity 25 or 3020 700 -18 250 can be raised and therefore the reference density Dref of the cavity can The range of associated growth tolerance values can also be raised in relation to the value of the reference density of the cavity Dref. According to a third embodiment which will be better understood on reading FIG. 4B, the reference density Dref is calculated so as to offer a comparison value making it possible to discriminate each pixel analyzed during the growth operation with respect to FIG. two ranges of values respectively associated with the cavity and the wall. FIG. 4B shows the pixel density distribution 46 in the wall 21 'and the pixel density distribution 45 in the cavity 25. Each of the distributions 45, 46, in this example, has the appearance of a Gaussian curve. but which can be different according to the envisaged cases: profile of the patient, type of contrast agent, pretreatment of the acquired images, etc. The two curves overlap in a zone 47 in which the definition of a density of pixels Dref makes it possible to discriminate each of the pixels of the two regions with the best precision. This embodiment corresponds to a combination of the first embodiment and the second embodiment. According to the fourth embodiment of the selection of a reference density Dref, the prior knowledge of a ratio between the density of pixels of the cavity 25 and the wall 20 or 21 'makes it possible to deduce a rule of growth of the region 27 according to the density of the pixels encountered step by step. An advantage of defining at least one valve plane that has been previously defined and plotted according to the method of the invention is that it makes it possible to define a stop boundary to the growth process of zone 27 without as far as the density of the neighboring pixels encountered is less than the predefined threshold. This boundary prevents the growth process from spreading into the orifices such as that of the pulmonary artery 13 or that of the tricuspid valve 16. The extension zone 27 can marry the internal volume formed by the intersection of the cavity 25 and the volume delimited by the valve plane 11 and including the seed 27. FIG. 2D represents such a volume generated from the growth of the zone 27. An advantage of the growth gradually in-between the pixels respecting a substantially close density tolerance and the definition of a predefined threshold limiting the propagation of growth is that the zone 27 stops clearly at the inner fabric of the wall 20, 21 ', it is to say the endocardium. This operation makes it possible to delimit the cavity and the wall with great precision, given the differences in pixel densities of these two 3D zones. The final growth region is therefore limited to a cavity, and extends within this cavity to the inner wall (endocardium), and to the orifices. According to a particular embodiment, the invention allows quantification on several cavities or on the whole heart. The number of cavities explored will depend on the selection of valvular input and output planes. Between these 2 planes 1 or more cavities can be analyzed.
    [0021] The method of the invention comprises a step in which the 3D extended area, denoted 27 in FIG. 3A, is dilated in its volume by a given proportion. This step is denoted DILAT in FIG. 5. The dilation of the zone 27 can be expressed as a percentage of the total volume or by an expansion distance denoted "d". The expansion distance d corresponds to the same expansion distance d of the volume in all directions 28 given that the expansion is homogeneous over the entire surface of the volume 27 which is dilated. The expansion operation corresponds to a homothety of each section plane of the surface 27. This expansion can be done in 2D, that is to say in the direction of the sectional plane on each of the sectional planes of the volume, but the preferred embodiment consists in making this expansion in 3D, that is to say in the direction perpendicular to the surface of the extended area 3D, denoted 27 in FIG. 3A. This direction perpendicular to the surface of the 3D volume may not be located in the plane of section.
    [0022] According to one embodiment, the zone 27 is dilated with an expansion distance of 1 to 12 mm. For example, a distance of 2 or 3 mm may be applied to the cavity delimited by the zone 27 when it comes to the human right ventricle VD. This distance is particularly adapted to the wall delimiting the right ventricle VD since it corresponds to the minimum thickness of the wall in the healthy subject. An advantage of matching the value of the expansion distance d to the wall thickness is that only the volume of the wall can be treated in subsequent steps of the process. This thickness therefore makes it possible to limit the analysis to the contours of the wall without the grease on the outer surface of the wall being counted. This has a significant advantage since the greasy masses located outside the wall can influence the quantification of fat masses inside the wall and that thanks to the method of the invention they are not taken into account. . However, it is possible to take into account in subsequent steps of the method the greasy masses located outside the wall 20, in particular on its outer surface thereof by choosing an expansion distance greater than 3 mm. The volume 27 thus expanded results in the definition of a volume 27 ', the excess thickness 20' is shown in Figure 3B. The volume 27 'thus comprises, by the effect of expansion, the volume 27 and all or part of the wall 20 of the right ventricle VD. Depending on the cavity considered, the expansion distance of the 3D volume obtained by the extension of the zone 27 can be adapted. For example, when the cavity is the LV left ventricle, the expansion distance d can be defined substantially close to 10 mm since the thickness of the wall of the left ventricle VG is substantially equal to this distance. According to another embodiment, several successive dilations can be applied to explore the presence of fibro-adipose tissue within the different layers in the thickness of the wall.
    [0023] The method of the invention comprises a step for extracting the 3D volume corresponding to the extra thickness generated by the expansion operation. This step is denoted EXTRACT in FIG. 5. To carry out this step, the method comprises the subtraction of the volume 27 from the expanded volume 27 '.
    [0024] FIG. 3C represents a sectional view of the portion 20 'corresponding to the extra thickness of the volume 27' obtained thanks to the subtraction operation of the two previous volumes 27 'and 27. Moreover, the method of the invention makes it possible to Optionally, define an area of interest 30 for diverting only part of the 3D image obtained after expansion. This area of interest 30 makes it possible to generate only a part of the volume that can be analyzed subsequently by the method of the invention. Typically, in the example of the dilation of the volume corresponding to a portion of the right ventricle VD, the delimitation 30 makes it possible to extract the excess thickness 20 'corresponding to the external border of the right ventricle VD and not to treat the border between the ventricle right VD and LV left ventricle. The method of the invention then comprises a step of quantizing the pixel densities of the volumetric region 20 '. This step is noted QUANTIFICATION in Figure 5. This step includes reading the image 20 ', processing each pixel of this region and recording each pixel density. Pixels of a predefined value range may be counted in the volume extracted in step EXTRACT. It is then possible to represent this quantization in the form of a histogram 40, such as that represented in FIG. 4. The representation in the form of a histogram can be generated by the step designated by HIST in FIG. of this histogram are counted the number of pixels, denoted Np, of the same pixel density, the pixel density, denoted Dp (UH), being represented as abscissa. The unit of pixel density is the unit of Hounsfield UH. When reading the histogram 40, it is possible to count the number of pixels, for example between -30 and -10 HU, and to deduce a rate of presence of such pixels in the wall of the right ventricle. For the purpose of a better interpretation of FIG. 4, the limit 41 is represented so as to identify the proportion of pixels whose density is less than -10 HU. The upper limit of the histogram for pixels with a density less than -10 is represented by the curve 42. According to one embodiment, the quantization takes into account all the pixels below a threshold, for example -10 HU on the As an example given in FIG. 4. According to another embodiment, several thresholds may be applied in order to quantify several fat masses of different densities, for example from -150 to -50 UH, and from -50 UH to -10 UH. According to one embodiment, the method of the invention comprises a mapping step for representing in superposition of the cavity in question, the excess thickness 20 'with a given colorimetric coding. This step is represented by the CARTO block in FIG. 5. The mapping step makes it possible to visualize the distribution of the pixels corresponding for example to greasy masses. For this, each pixel comprises a 3D position in the image and a pixel density. The assignment of a color of a pixel is carried out as soon as its density is within a given range of values, for example [-10, -30].
    [0025] The volume 20 ', thus generated and shown on a display such as a computer screen, can be viewed by an operator. Means for controlling the position and orientation of the image 20 'can be used so as to rotate in the space of the volume 20' to study the surface and the presence of fat in the myocardial wall.
    [0026] The image generated in 3D can be integrated into a visualization platform to provide an interventional surgeon or cardiologist with the means to control an intervention on a heart. Figure 5 shows the different steps of the process of the invention. It is specified that the PLAN VALV steps and the Dref steps are not performed according to an imposed execution order when they require manual operations by an operator. The latter can indifferently first define the valvular planes or first choose the reference density.
    [0027] According to a variant of the process of the invention, the expansion operation can be carried out step by step by dilation of a pixel of the previously enlarged volume 27. The volume 27 can then be subtracted from the volume 27 'thus expanded to obtain a layer with a width of one pixel to which mapping can be applied. The operation can be repeated step by step on a plurality of superimposed layers corresponding to an excess thickness of a desired distance, for example 3 mm. This method makes it possible to represent each layer with a specific colorimetric coding which allows a 3D visualization with a high accuracy of reading in particular of the penetration rate of the fat in the thickness of the myocardial wall. According to another variant of the method of the invention, a colorimetric coding may be defined for pixel density segments of a predefined range of values. For example, considering a range of pixel density values of interest between -10 and -50 UH, 4 segments can be defined by the following ranges: [-10, -20], [-20, -30], [-30, -40], [-40, -50]. Each segment may comprise a colorimetric coding assigned to represent the density variations in the representation of the volume 20 'displayed. The method of the invention may optionally include a step prior to the acquisition of 3D images which comprises the diffusion of a contrast agent in the cavity. This contrast agent makes it possible to obtain densities of pixels of the different parts of the heart that are very different, which improves the contrast, for example between an area corresponding to the cavity in question and a zone corresponding to the myocardium. The contrast agent may be, for example, a water-soluble iodine agent. It can be injected by the venous or arterial route or injected by an infusion when the heart is explanted. The method of the invention is realized for example by means of a computer which is configured to acquire an image of a scanner. Software to represent the image on the screen can be used. The steps of the method can be executed by a software component specially designed for this purpose and which is implemented in an existing software or in a software dedicated to these processes. The computer of the computer can be used in order to perform all the image processing steps, namely in particular the zone extension, expansion and extraction operations of a peripheral 3D volume such as the volume 20 '. . According to a first embodiment, the method is applied to images of a heart of a man or a woman, the scanner being made in the region of the body concerned. According to another embodiment, the method is applied to images acquired from an animal heart. According to another embodiment, the method is applied to an isolated heart, for example explanted of the human body. It can be for example perfused. The method of the invention can be used for the diagnosis of arrhythmogenic dysplasia of the right ventricle, a pathology of the myocardium responsible for fatty infiltration of the wall. The method can also be used in patients whose diagnosis of arrhythmogenic dysplasia is already known, in order not to establish the diagnosis, but to quantify the extent of the disease to evaluate a prognosis, such as the risk of arrhythmia or heart failure. Such quantification can be applied repeatedly in the same patient in order to follow the spontaneous evolution of the disease, or to follow the effect of a possible treatment. The method can also be used to detect and quantify myocardial infarction sequelae, which are also associated with decreased muscle density in CT images.
    [0028] In addition to the detection of infarction sequelae, quantification could be used to evaluate a pejorative prognosis related to the size of the infarct, such as the risk of developing arrhythmia or heart failure. Finally, the method could also be applied to the detection and quantification of fat within the atrial wall. The method could again find diagnostic and prognostic applications, particularly in patients with atrial arrhythmia such as atrial fibrillation. Beyond the detection and quantification of fat, and its applications to the diagnosis and prognosis of pathologies, the method 30 of the invention allows a 3D mapping of fatty regions within the heart. It can therefore be applied to therapeutic guidance, particularly in the areas of ablation and cardiac stimulation. It is now possible to locate the intracardiac probes and catheters in space during the interventions, and the integration of 3D data within these localization systems has already been shown to be feasible and useful - 25 - assistance with intra-cardiac navigation and targeting of therapies. The ability to visualize fatty areas within the heart muscle can therefore guide the ablation and stimulation procedures. The pathologies concerned are disorders of rhythm and conduction in patients suffering from arrhythmogenic dysplasia of the right ventricle, in patients with myocardial scars (infarction, myocarditis, surgical scars), or in patients suffering from atrial fibrillation.
    权利要求:
    Claims (18)
    [0001]
    REVENDICATIONS1. A method for quantifying the presence of fats in a region of the heart (10) comprising: - an acquisition (ACQ) of a three-dimensional image of at least one cavity (25, 26, VG, VD, OG, OD) of the heart (10) and a wall (20, 21, 21 ') delimiting said cavity (25, 26, VG, VD, OG, OD); to - a selection of at least one pixel (27) of the cavity (25, 26, VD, VG, OD, OG) defining a seed (27); - a growth (EXT ZONE) of the seed (27) step by step until reaching an area of a pixel density (Dp) below a predefined threshold, the growth of the seed 15 (27) leading to the defining a delimited extended area (27) including the pixel density in a first range of values (Gi), the 3D image obtained by growth being referred to as the "extended 3D area" (27); a dilation operation (DILAT) of the extended 3D zone 20 making it possible to define an expanded volume (27 ') comprising at least a part of the thickness of the wall (20) of the cavity (25, 26, VD, VG , OD, OG) considered; an extraction operation (EXTRACT) of a peripheral region (20 ') resulting from the subtraction of the volume from the extended 3D zone (27) to the expanded volume (27') and; a quantization (QUANTIFICATION) of the number of pixels of a second range of values (G2) of the extracted peripheral region. 30
    [0002]
    2. Method for a quantification of the presence of greases according to claim 1, characterized in that the acquisition of a three-dimensional image of the core is carried out by means of a scanner, the density of the pixels of the image being expressed in FIG. Hounsfield unit. 35- 27 -
    [0003]
    3. Method for a quantification of the presence of fats in a region of the heart (10) according to any one of claims 1 to 2, characterized in that it comprises: - a definition of at least one boundary (PV, 11 , 12) of the three-dimensional image of the considered cavity of the heart (VG, VD, OG, OD); the growth (EXT ZONE) of the seed (27) taking place until meeting at least one boundary (PV, 11, 12) or an area of a pixel density lower than the predefined threshold.
    [0004]
    4. Method for a quantification of the presence of greases according to claim 3, characterized in that the boundary (PV, 11, 12) makes it possible to separate the part of the acquired image comprising the cavity (25) considered from an opening opening in said cavity (25) whose pixel density is in the first range of values (G1).
    [0005]
    5. Method for a quantification of the presence of fats according to any one of claims 1 to 4, characterized in that the growth (EXT ZONE) of the seed (27) is carried out in three dimensions from a selection of pixels on a section plane (25) of the cavity.
    [0006]
    6. Method for a quantification of the presence of greases according to any one of claims 1 to 4, characterized in that the growth (EXT ZONE) of the seed (27) is carried out in two dimensions on each cutting plane of the cavity (25), the "extended 3D area" (27) being reconstructed by the set of "extended 2D areas".
    [0007]
    7. Method for a quantification of presence of greases according to any one of claims 1 to 6, characterized in that the predefined threshold is defined with respect to a determination of a reference pixel density (Dref) calculated from a measurement in the acquired image, said acquired image comprising the cavity (25) and at least one of the walls (20, 21, 21 ') of said cavity.
    [0008]
    8. Method for a quantification of presence of greases according to claim 7, characterized in that the reference density (Dref) is calculated from a measurement made on pixels of the cavity (25), the reference density ( Dref) corresponding to a low limit of the first range (G1) of pixel density values.
    [0009]
    9. Method for a quantification of the presence of greases according to claim 7, characterized in that the reference density (Dref) is calculated from a measurement made on pixels of a wall (20, 21, 21 '). defining a region of interest (22), the reference density (Dref) corresponding to a high limit of a third range of pixel density values (G3) of the region of interest (22).
    [0010]
    10. Method for a quantification of the presence of greases according to claims 8 and 9, characterized in that the reference pixel density (Dref) is calculated in a range of values between the first range (G1) of values and the third range of values (G3) so as to better discriminate the membership of a pixel to one of these ranges of values (Gi, G3).
    [0011]
    11. Method for a quantification of presence of greases according to claim 7, characterized in that the measurement of the reference density (Dref) is chosen from a predefined value corresponding to a typical profile of a core.
    [0012]
    12. Method for a quantification of presence of greases according to any one of claims 1 to 11, characterized in that the dilation operation (DILAT) is repeated a plurality of times so as to generate a plurality of dilated 3D images , the successive expansions being determined so that each new dilated 3D image comprises the previous dilated 3D image.
    [0013]
    13. Method for a quantification of grease presence according to claim 12, characterized in that a 3D layer of a peripheral region of the extended 3D image is extracted by subtracting an N-1 th dilated image. from the extended 3D image (27) to the Nth expanded image of the extended 3D image (27).
    [0014]
    14. Method for a quantification of presence of greases according to any one of claims 1 to 13, characterized in that a quantization operation (QUANTIFICATION) comprises the counting of the number of pixels of a density included in the second range of values (G2) in an extracted 3D layer or a 3D peripheral region.
    [0015]
    The method for a quantification of grease presence according to claim 14, characterized in that a thresholding operation of the pixel densities (HIST) of the peripheral 3D region (20 ') comprises a distribution (40) according to a plurality of ranges of values of different proportions of pixel densities (Dp).
    [0016]
    16. Method for a quantification of the presence of greases according to claim 14, characterized in that a generation of a 3D mapping of the wall of the cavity (25, 26, VD, VG, OD, OG) comprises the representation of pixels of a density in the second range of values (G2) with a predefined color coding.
    [0017]
    17. Method for a quantification of the presence of greases according to claim 15, characterized in that a generation of a 3D mapping of the wall of the cavity (25, 26, VD, VG, OD, OG) comprises a subdivision of the second range of values (G2) in a plurality of sub-ranges of values (SGi, iE [1, N]) corresponding to different pixel density ratios (Dp) with a predefined color coding assigned to each subdivision (SGi, iE [1,
    [0018]
    18. System for visualizing an imaging of an organ allowing the visualization of fat masses, implementing the method of the invention according to steps 1 to 17, characterized in that it comprises: a display allowing: 30 - o to display a section of a three-dimensional image acquired by a scanner; o to display a three-dimensional image whose mapping generated by the method of the invention; a selector: o at least one pixel to define a reference density and, o at least one pixel to generate an extended 3D zone obtained by growing step by step; a tool for drawing a line defining at least one valve plane; an interface: o to set the expansion distance d or a dilation proportion; o to extract a three-dimensional oversize from the volume coming from the extended 3D zone and dilated 3D zone; calculating means for: counting the number of pixels of the three-dimensional excess thickness having a density within a predefined value range; o Perform all calculations to process operations on 3D images, including expansion, extension, extraction. 25 ^ ^ ^ 15
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    同族专利:
    公开号 | 公开日
    JP2017514648A|2017-06-08|
    US10275878B2|2019-04-30|
    AU2015254675A1|2016-11-17|
    EP3138077B1|2021-08-18|
    AU2015254675B2|2019-12-12|
    JP6505827B2|2019-04-24|
    WO2015165978A1|2015-11-05|
    FR3020700B1|2016-05-13|
    EP3138077A1|2017-03-08|
    US20170061617A1|2017-03-02|
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    优先权:
    申请号 | 申请日 | 专利标题
    FR1453941A|FR3020700B1|2014-04-30|2014-04-30|METHOD FOR QUANTIFYING THE PRESENCE OF FAT IN A HEART REGION|FR1453941A| FR3020700B1|2014-04-30|2014-04-30|METHOD FOR QUANTIFYING THE PRESENCE OF FAT IN A HEART REGION|
    EP15721636.7A| EP3138077B1|2014-04-30|2015-04-29|Method for quantifying the presence of fats in a region of the heart|
    US15/307,643| US10275878B2|2014-04-30|2015-04-29|Method for the quantification of the presence of fats in a region of the heart|
    JP2017508758A| JP6505827B2|2014-04-30|2015-04-29|Method for quantification of the presence of fat in the area of the heart|
    AU2015254675A| AU2015254675B2|2014-04-30|2015-04-29|Method for quantifying the presence of fats in a region of the heart|
    PCT/EP2015/059362| WO2015165978A1|2014-04-30|2015-04-29|Method for quantifying the presence of fats in a region of the heart|
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