Patent Publication Number: US-2018049718-A1

Title: Ultrasonic diagnosis of cardiac performance by single degree of freedom chamber segmentation

Description:
This invention relates to medical diagnostic ultrasound systems and, in particular, to the use of single degree of freedom cardiac chamber segmentation. 
     Ultrasonic imaging is routinely used to diagnose cardiac performance by measurement of parameters such as ejection fraction and cardiac output. Such measurements require the volume of blood in a heart chamber at various phases of the heart cycle to be delineated in two or three dimensional images of a heart chamber. Typically measurements of the volume of cardiac chambers, such as the left ventricle, have been generated by users hand tracing the endocardial boundary of the chamber. Such tracings are subject to significant variability due to differences in the criteria different users utilize in determining where to locate the tracing. Automatic methods have been developed to attempt to automate this boundary tracing, such as the automated border tracing methodology described in U.S. Pat. No. 6,491,636 (Chenal et al.) In this technique, anatomical landmarks of a chamber are located, including the mitral valve plane corners and the apex of the heart chamber. One of a plurality of standard, expert-validated endocardial shapes are then fit to these landmarks. The automatically drawn border can then be manually adjusted by rubberbanding, by which the user moves control points on the border to adjust its final position over the endocardium. This processing is done for images taken at the end systole and end diastole heart phases. The two borders can be compared or subtracted to estimate ejection fraction or cardiac output. For example, US 2009/0136109 discloses to produce a myocardium thickness volume by comparing the identified endocardial border (which defines an inner surface of the myocardium) and the identified epicardial border (which defines an outer surface of the myocardium). The myocardium thickness volume of US 2009/0136109 is hollow, with the hollow space inside being the volume of the heart chamber. Similar approach is described in EP 2434454 A2, wherein a volume of the left ventricle (LV) is computed based on the detected LV boundaries. The system of EP 2434454 A2 uses various machine learning for locating and tracking the cardiac wall. These training techniques based on the training data set, which uses a database of known cases collected for machine learning. Ejection fraction can be estimated by well-established methods such as an automated Simpson&#39;s algorithm (rule of disks), to measure the fraction of the chamber volume ejected with each contraction of the heart. 
     But automated image analysis methods do not always produce heart chamber delineations that are acceptable to all users. This lack of success is due in large part to the inability of the automatic methods to consistently locate the border where any given user believes the border should be placed. Much of this poor performance is due to variations between different users on what are the anatomical landmarks which specify where the true border lies. 
     It is an object of the present invention to provide users with a simple automated tool for delineating the location of an acceptable heart chamber border. It is a further object that such delineations be standardized, and capable of comparison and the production of repeatable results among different users. Such results summarize the approach of one clinician into a single value that can be understood and communicated to other clinicians who have the same tool. 
     In accordance with the principles of the present invention, a diagnostic ultrasound system and method are described which diagnose cardiac performance. Images of a chamber of the heart are acquired and an image is segmented to delineate an inner and an outer boundary of the myocardium, or alternatively several (3+) boundaries of the myocardium. Preferably this is done with an automated image analysis processor such as one using heart model data. A user control is provided which enables a user to define the user&#39;s preferred chamber border location in relation to one, both, or several of the segmentation boundaries. The user control provides a single value, a single degree of freedom, which the user varies to locate the true chamber border, such as a percentage of the distance relative to the segmented boundaries. The single value can be shared with other users of the same tool, enabling other users to obtain the same results with other images, and hence a standardization of cardiac chamber border identification. 
    
    
     
       In the drawings: 
         FIG. 1  illustrates in block diagram form an ultrasonic diagnostic imaging system constructed in accordance with the principles of the present invention. 
         FIG. 2  is a block diagram illustrating border detection details of the QLQB processor of  FIG. 1  in accordance with the principles of the present invention. 
         FIGS. 3 a  and 3 b    illustrate landmarks of the left ventricle which are useful for border detection. 
         FIGS. 4 a , 4 b  and 4 c    illustrate expert-derived endocardial border shapes used for automated border detection. 
         FIGS. 5 a  and 5 b    illustrates the delineation of epicardial and endocardial borders in images of the left ventricle. 
         FIG. 6  is a flowchart of the operation of a deformable heart model to find heart borders in accordance with the present invention. 
         FIGS. 7 a  and 7 b    are cardiac images of the left ventricle at end diastole and end systole in which the endocardial boundary and the interface between the trabeculaeted myocardium and the compacted myocardium have been traced. 
         FIGS. 8 a  and 8 b    illustrate the end systole ultrasound image of  FIG. 7 b    in which a user-defined border has been located at 0% and 100% of the distance between the two heart boundaries delineated in  FIG. 7   b.    
         FIG. 8 c    illustrates a cardiac image with a user-defined border is located at 40% of the distance toward the compacted myocardium interface from the endocardial tracing. 
         FIG. 8 d    illustrates a single degree of freedom user control in accordance with the embodiments of the present invention, wherein the user-defined border is located relative to several boundaries of the myocardium. 
         FIG. 9  illustrates user-defined heart chambers from biplane images which are being volumetrically measured using the rule of disks. 
         FIG. 10  illustrates a user-defined heart chamber wire frame model from a 3D ultrasound image preparatory to volumetric measurement. 
     
    
    
     Referring first to  FIG. 1  an ultrasonic diagnostic imaging system  10  constructed in accordance with the principles of the present invention is shown in block diagram form. An ultrasonic probe  12  includes an array  14  of ultrasonic transducers that transmit and receive ultrasonic pulses. The array may be a one dimensional linear or curved array for two dimensional imaging, or may be a two dimensional matrix of transducer elements for electronic beam steering in three dimensions. The ultrasonic transducers in the array  14  transmit ultrasonic energy and receive echoes returned in response to this transmission. A transmit frequency control circuit  20  controls the transmission of ultrasonic energy at a desired frequency or band of frequencies through a transmit/receive (“T/R”) switch  22  coupled to the ultrasonic transducers in the array  14 . The times at which the transducer array is activated to transmit signals may be synchronized to an internal system clock (not shown), or may be synchronized to a bodily function such as the heart cycle, for which a heart cycle waveform is provided by an ECG device  26 . When the heartbeat is at the desired phase of its cycle as determined by the waveform provided by ECG device  26 , the probe is commanded to acquire an ultrasonic image. This enables acquisition at the end diastole and end systole heart phases, for instance. The frequency and bandwidth of the ultrasonic energy generated by the transmit frequency control circuit  20  is controlled by a control signal f tr  generated by a central controller  28 . 
     Echoes from the transmitted ultrasonic energy are received by the transducers in the array  14 , which generate echo signals that are coupled through the T/R switch  22  and digitized by analog to digital (“A/D”) converters  30  when the system uses a digital beamformer. Analog beamformers may also be used. The A/D converters  30  sample the received echo signals at a sampling frequency controlled by a signal f s  generated by the central controller  28 . The desired sampling rate dictated by sampling theory is at least twice the highest frequency of the received passband, and might be on the order of 30-40 MHz. Sampling rates higher than the minimum requirement are also desirable. 
     The echo signal samples from the individual transducers in the array  14  are delayed and summed by a beamformer  32  to form coherent echo signals. For 3D imaging with a two dimensional array, it is preferable to partition the beamformer between a microbeamformer located in the probe and the main beamformer in the system mainframe as described in U.S. Pat. No. 6,013,032 (Savord) and U.S. Pat. No. 6,375,617 (Fraser). The digital coherent echo signals are then filtered by a digital filter  34 . In the illustrated ultrasound system, the transmit frequency and the receiver frequency are individually controlled so that the beamformer  32  is free to receive a band of frequencies which is different from that of the transmitted band such as a harmonic frequency band. The digital filter  34  bandpass filters the signals, and can also shift the frequency band to a lower or baseband frequency range. The digital filter can be a filter of the type disclosed in U.S. Pat. No. 5,833,613, for example. Filtered echo signals from tissue are coupled from the digital filter  34  to a B mode processor  36  for conventional B mode image processing. 
     Filtered echo signals of a contrast agent, such as microbubbles, are coupled to a contrast signal processor  38 . Contrast agents are often used to more clearly delineate the endocardial wall in relation to contrast agent in the blood pool of the heart chamber, or to perform perfusion studies of the microvasculature of the myocardium as described in U.S. Pat. No. 6,692,438 for example. The contrast signal processor  38  preferably separates echoes returned from harmonic contrast agents by the pulse inversion technique, in which echoes resulting from the transmission of multiple differently modulated pulses to an image location are combined to cancel fundamental signal components and enhance harmonic signal components. A preferred pulse inversion technique is described in U.S. Pat. No. 6,186,950, for instance. 
     The filtered echo signals from the digital filter  34  are also coupled to a Doppler processor  40  for conventional Doppler processing to produce velocity and power Doppler signals. The output signals from these processors may be displayed as planar images, and are also coupled to a 3D image processor  42  for the rendering of three dimensional images, which are stored in a 3D image memory  44 . Three dimensional rendering may be performed as described in U.S. Pat. No. 5,720,291, and in U.S. Pat. Nos. 5,474,073 and 5,485,842, all of which are incorporated herein by reference. 
     The signals from the contrast signal processor  38 , the B mode processor  36  and the Doppler processor  40 , and the three dimensional image signals from the 3D image memory  44  are coupled to a Cineloop® memory  48 , which stores image data for each of a large number of ultrasonic images. The image data are preferably stored in the Cineloop memory  48  in sets, with each set of image data corresponding to an image obtained at a respective time. The image data in a group can be used to display a parametric image showing tissue perfusion at a respective time during the heartbeat. The groups of image data stored in the Cineloop memory  48  may also be stored in a permanent memory device such as a disk drive or digital video recorder for later analysis. In this embodiment the images are also coupled to a QLAB processor  50 , where the images are analyzed to automatically delineate borders of the heart, enabling a user to then position a border as the user believes most accurately indicates the true border of a chamber of the heart. The QLAB processor also makes quantified measurements of various aspects of the anatomy in the image and delineates tissue boundaries and borders by automated border tracing as described in US patent publication no. 2005/0075567 and PCT publication no. 2005/054898. The data and images produced by the QLAB processor are displayed on a display  52 . 
       FIG. 2  illustrates further details of the operation of the QLAB processor to delineate a user-defined heart chamber border in accordance with the principles of the present invention. A cardiac ultrasound image is provided by a source of cardiac image data  60 , which may be the Cineloop memory  48 , the 3D image memory  44 , or one of image processors  36 ,  38 , or  40  of  FIG. 1 . The cardiac image is forwarded to an automatic border detection (ABD) processor  62 . The ABD processor may be a fully automatic or a semi-automatic (user-assisted) image processor which delineates a border of a chamber in a heart image, several of which are described below. In a typical semi-automatic ABD system, the user designates a first landmark in the cardiac image with a pointing device such as a mouse or a trackball, usually located on the ultrasound system control panel  70  or with a workstation keyboard, which manipulates a cursor over the image. In the example of  FIG. 3 a   , for instance, the first landmark designated is the medial mitral annulus (MMA) at the bottom of the left ventricle (LV) in the illustrated view. When the user clicks on the MMA in the image, a graphic marker appears such as the white control point indicated by the number “ 1 ” in the drawing. The user then designates a second landmark, in this example, the lateral mitral annulus (LMA), which is marked with the second white control point indicated by the number “ 2 ” in  FIG. 3 b   . A line produced by the ABD processor then automatically connects the two control points, which in the case of this longitudinal view of the left ventricle indicates the mitral valve plane. The user then moves the pointer to the endocardial apex, which is the uppermost point within the left ventricular cavity. As the user moves the pointer to this third landmark in the image, a template shape of the left ventricular endocardial cavity dynamically follows the cursor, distorting and stretching as the user-manipulated pointer seeks the apex of the LV chamber, as shown in  FIG. 5 a   . This template, shown as a white line in  FIG. 5 a   , is anchored by the first and second control points  1  and  2  and passes through the third control point, which is positioned at the apex when the user clicks the pointer at the apex, positioning the third control point  3 . Typical LV chamber border templates are shown in  FIGS. 4 a , 4 b , and 4 c   . These templates are determined from many expert tracings of the LV endocardial boundary in many patients. The template  80  of  FIG. 4 a    is an elongated template typical of many normal patients. The template  82  of  FIG. 4 b    is more bulbous in shape, characteristic of many patients with congestive heart failure. The template  84  is yet a third possibility, a more teardrop shape. The template which best fits the three anatomical landmarks identified by the user is selected by the ABD processor  62  and distorted to fit the three user-defined landmarks. When positioned and fitted to the landmarks, the endocardial cavity template  80 ,  82 , or  84  provides an approximate tracing of the endocardium of the LV, as shown in  FIG. 5 a   . In the example of  FIG. 5 a    a black line which bisects the left ventricle follows the pointer as it approaches and designates the apex. This black line is anchored between the center of the line indicating the mitral valve plane and the left ventricular apex, essentially indicating a center line between the center of the mitral valve and the apex of the cavity. 
     Once the ABD processor  62  has found the endocardial lining of the LV, it then attempts to find the epicardial boundary. This is illustrated in  FIG. 5 b   , where the user has moved the cursor and clicked on the apex  4  of the outside of the dark myocardium in the image. The images of  FIG. 5  are contrast-enhanced harmonic images in which the chamber of the LV has been flooded with a contrast agent but the agent has not yet fully perfused the myocardium, which is why the LV chamber appears very bright against the darker surrounding myocardium in this image. When the user clicks on the epicardial apex, the ABD processor, as before, selects an outer or epicardial template similar to the templates of  FIG. 4  and fits it to the epicardium as illustrated in  FIG. 5 b   . The cardiac image now has both its endocardial boundary (line connecting  1 ,  3  and  2  markers), the blood pool-myocardium interface, and its epicardial boundary (line connecting  1 ,  4  and  2  markers), the outmost surface of the heart, delineated in the image by tracings produced by a graphics generator  66 . 
     Instead of semi-automatic operation requiring user interaction, the ABD processor may delineate the border of the LV fully automatically as described in the aforementioned U.S. Pat. No. 6,491,636. As explained therein, an image processor can be configured to find the mitral valve corners and apex automatically, then fit a template to the automatically-located landmarks. However, a preferred technique for automatically delineating the myocardial borders is with a heart model, as illustrated in  FIG. 6 . A heart model is a spatially-defined mathematical description of the tissue structure of a typical heart which can be fitted to the heart as it appears in a diagnostic image, thereby defining the specific anatomy of the imaged heart. The process of  FIG. 6  begins with the acquisition of a cardiac image at  90 . The position of the heart is then localized in the cardiac image by processing the image data with a generalized Hough transform at  92 . At this point the pose of the heart has not been defined, so misalignments in translation, rotation and scaling of the heart in the image data are corrected by use of a single similarity transformation for the whole heart model at  94 . Next at  96 , the model is deformed and affine transformations are assigned to specific regions of the heart. Constraints on the deformation are then relaxed by allowing the heart model to deform with respect to the piecewise affine transformation at  98 , and the shape-constrained deformable model is resized and deformed so that each part of the model fits the actual patient anatomy as shown in the image at the captured phase of the heart cycle. The model is thus accurately adapted to the organ boundaries shown in the cardiac image, thereby defining the boundaries including the endocardial lining, the interface between the trabeculaeted myocardium and the compacted myocardium, and the epicardial border. In a preferred implementation of such a heart model, the interface between the trabeculaeted myocardium and the compacted myocardium is found first, as this typically appears as a well-defined gradient between a brightly illuminated region and a region of moderate illumination in an ultrasound image. The endocardial boundary is generally less well-defined in a heart model due to the desire to be able to find the variable location of the less well-defined endothelial lining as it appears in an ultrasound image. Unlike the contrast-enhanced cardiac images of  FIGS. 5 a  and 5 b   , an unenhanced ultrasound image will generally exhibit a relatively sharp intensity gradient between the relatively high intensity echo tissue surrounding the myocardium and the medium intensity of the myocardium, and a relatively lesser gradient between the myocardium and the low intensity of the chamber&#39;s blood pool. This mandates in favor of discriminating the outer myocardial border first, then the inner endocardial boundary when diagnosing images acquired in the absence of a contrast agent. When the coordinates of a boundary have been found, they are communicated to the graphics generator  66 , which generates the traces that overlie the image in the calculated positions. 
       FIG. 7  shows two ultrasound images, one with both boundaries of the myocardium outlined at end diastole ( FIG. 7 a   ), and the second with both myocardial boundaries traced at end systole ( FIG. 7 b   ). The compacted myocardial boundary is traced in black and the endocardial boundary is traced in white in these images. With both boundaries thus drawn, the user controls a chamber border delineator  64  with a user control on control panel  70  to indicate a location between the two tracings where the user believes the true chamber border is located. In one implementation the user operates a single variable control by which the user can position the true endocardial border at a location which is displaced a selected percentage of the distance between the previously drawn endocardial boundary and the previously drawn interface between the trabeculaeted myocardium and the compacted myocardium.  FIG. 8 a    illustrates the end systole image of  FIG. 7 b    when the single variable control is set at 0%, and  FIG. 8 b    illustrates the same image with the user control set at 100%, in which case the white line border is located at the outside of the myocardium. The visual tracing of the user-defined border is also produced by the graphics generator  66  in the system of  FIG. 1  for overlay over the ultrasound image. The user-set border is positioned at the called-for location as measured orthogonal to the endocardial tracing and at the called-for percentage of the distance between the two boundaries. In these examples the two myocardial boundary tracings are not shown for ease of illustration, which is one possible implementation, although the automatically drawn tracings could also be shown if desired. 
       FIG. 8 c    illustrates a situation in which the user has adjusted the user-positioned border (shown as a white line) so that it is 40% of the distance toward the compacted myocardium interface from the endocardial tracing. This is done by moving a slider  100  left or right in its slot  102 . As the slider is manipulated by the user, the user-controlled border tracing  110  moves back and forth between the two boundaries of the myocardium. In the example of  FIG. 8 c    the slider  100  is shown as a softkey control on the display screen which is manipulated by a mouse or other user interface control, although the slide could alternatively be a physical slider, knob or switch, or a trackball on a conventional ultrasound system control panel. The user control can also be implemented as a rocker control, toggle buttons, list box, or a numerical entry box. If the user has a preferred percentage for most cases, this can be saved as a default value. In the example of  FIG. 8 c    the numerical percentage is displayed on the screen and changes as the slider  100  is moved. Also shown in  FIG. 8 d    in an enlarged view  104  of a portion of the identified myocardial boundaries. The user clicks on a point of the myocardium of the image to the left, and that portion of the myocardium appears in the enlarged view  104 , with the user-manipulated border  110  shown between the myocardial boundaries  106  (outer boundary) and  108  (inner boundary). As the user manipulates the slider  100 , the border  110  moves between the two system-drawn boundaries  106  and  108 . 
     The user-manipulated border  110  can also be positioned using a range of more than 100% as shown in the enlarged view  104 ′. The user-defined position A ( 110 ′A) is positioned beyond the compacted myocardium boundary  106 ′ and expressed in the range of more than 100%, while the user-defined position C ( 110 ′C) is positioned within the endocardial tracing  108 ′ and expressed in negative percentage range. The user-defined position B ( 110 ′B) positioned in between the endocardial and compacted myocardium boundaries can be expressed in the range in between 0% and 100%. 
     Alternatively, for user convenience the user-manipulated (defined) border can be moved with respect to three outlines as illustrated in  FIG. 8 d    (lower to the right view  104 ′): the compacted myocardium boundary  106 ′and endocardial boundary  108 ′, which correspond to the same percentage 100% and 0% respectively as in the previous example; and an additional boundary  109 ′ corresponding to the percentage value of 200%, wherein the additional boundary  109 ′ is located at the epicardial boundary. In the illustrated example, the slider  100  is adjusted at the value of 150% corresponding to the user-defined border  110 ′ position in between the compacted myocardium boundary  106 ′ and the epicardial boundary  109 ′. The alternative of the third boundary is addressing the fact that there is another boundary beyond the compacted myocardium boundary ( 106 ′), which is the epicardial boundary (denoted in this example as the additional boundary), said epicardial boundary may be also characterized by a noticeable and detectable gradient in the ultrasound image, which could be used to constrain the single degree of freedom slider. This epicardial boundary can be also identified by the border image processor. The slider is a single degree of freedom control. The user sets the position of the border  110  all around the chamber simply by setting the single value controlled by the slider. The value can be communicated to other users, who can obtain the same results by use of the same single numerical value. 
       FIGS. 9 and 10  illustrate how user-defined heart chamber borders of the present invention can be used to measure parameters such as cardiac output and ejection fraction. In the perspective view of  FIG. 9  two user-defined borders  210  and  212  of simultaneously acquired biplane images of the LV are shown on a base  220  which represents the mitral valve plane. The apex marker of the two borders is shown at  230 . In this example the image planes of the two biplane image borders are orthogonal to each other. The volume within the two borders  210  and  212  is mathematically divided into spaced planes  222  which are parallel to the base plane  220 . These planes intersect the left side of border  210  as shown at a,a and intersect the right side of border  210  as shown at c,c. The planes intersect the near side of tracing  212  as shown at b,b. 
     An ellipse is mathematically fit to the four intersection points a,b,c,d of each plane  222  as shown in  FIG. 9 . While curves or splines other than ellipses can be used, including arcs and irregular shapes, an ellipse provides the advantage that Simpson&#39;s formula has been clinically validated when practiced with ellipses. The volume of the disks defined by the planes  222  and the ellipses can be calculated by the rule of disks to estimate the volume of the LV. 
       FIG. 10  shows a wire frame model constructed of a user-defined border of a three dimensional heart chamber image. The horizontal sections  232 ,  234 ,  236  of the wire frame are border lines which intersect vertical border sections  210 ,  212  at intersection points a, b, c, and d. The horizontal sections are parallel to the mitral valve plane base  220 . The volume within the wire frame can be determined by a modified rule of disks computation or other volumetric estimation technique. When a volume computed as shown in  FIG. 9 or 10  for an end systole phase image is subtracted from a volume calculated for an end diastole image and divided by the same, the result is an ejection fraction estimation. 
     Other variations of the above will readily occur to those skilled in the art. Instead of a percentage quantification, the user-defined border can be positioned an incremental distance from a manual or automatically traced boundary. The slider can be calibrated in distance so that the position of a user-defined border is a user-determined number of millimeters offset from a reference boundary, for instance. Rather than use two traced boundaries, the user-defined border can be located in reference to a single boundary tracing, or can be at an interpolated offset from more than two boundaries. The user-defined border can also be positioned using a range of more than 100%; it can be positioned within the endocardial tracing or beyond the epicardial or compacted myocardium boundary.