Pet data driven cardiac quiescent period extraction

Abstract

Provided is a data driven approach for identifying the motion-free (or quiescent) period for imaging the heart. This timing information is not readily available from a conventional electrocardiogram (ECG) trace. The method identifies the motion-free period on a beat-by-beat basis.

Description

PET DATA DRIVEN CARDIAC QUIESCENT PERIOD EXTRACTIONFIELD

[0001] The present disclosure relates generally to the field of nuclear imaging systems and, more particularly, to a novel method for imaging a heart.BACKGROUND

[0002] Referring to FIGs. 1A-1B, FIG. 1A shows an external electrocardiogram (ECG) and Left Ventricle volume plots in one heartbeat cycle at rest; and FIG. IB shows ECG and Left Ventricle volume plots in one heartbeat cycle at stress. When the subject is at rest, the diastolic phase is typically longer than the systolic phase, whereas, when the subject is at stress the reverse may apply since the diastolic phase is shortened more than the systolic phase. The duration of systole is relatively constant during rest and stress conditions, whereas the diastolic period shortens significantly during cardiac stress. LV in FIGs. 1A and IB denote Left Ventricle. The P wave, Q wave, R wave, S wave, T wave, and U wave portions of the ECG cycle are noted in FIGs. 1A and IB. The quiescent period of the heart is identified by the double-headed arrow.

[0003] Imaging the contractile phase of a heart is typically performed by gating the acquisition or reconstruction with reference to an ECG device. Conventional ECG-gating simply divides each heartbeat into a predetermined number of equal phases. In some cases, it may be desirable to image the heart during the quiescent phase when the myocardium is relatively stationary (mid-to-late diastole) with the resulting image thus being less prone to motion artifacts. The existing cardiac imaging methods based on PET imaging, however, do not provide a useful method for obtaining PET image of a heart during its quiescent period. Some recent efforts in the industry have demonstrated the ability to discern the heartbeat directly from PET data utilizing center-of-mass approach. However, such method results in a signal that is relatively crude because center-of-mass approach largely captures the apical-basal motion of the heart. Much of the signal for such surrogate trace of the cardiac motion is masked by the symmetry of the shape and contractility of the heart. This is because the short axis of the heart comprises a torus and contractility is relatively uniform, so the center-of-mass does not change much during the cardiac cycle.

[0004] Thus, an improved means of producing PET scan image of a heart during its quiescent period is desired.SUMMARY

[0005] The present disclosure provides a data-driven approach for identifying the motion-free (quiescent) period of a heart for imaging the heart.

[0006] The method of the present disclosure can include: (a) conducting a PET scan of a patient and generating a listmode PET scan data that includes the patient’s heart; (b) extracting histo-image data at a high temporal resolution; (c) using a bounding box extracted from reconstructed PET scan data that was segmented for a ventricle of the patient’s heart, cropping the histo-image data to isolate the histo-image data of the ventricle of the patient’s heart; (d) identifying cardiac anatomical coordinates; (e) extracting time course of projections along cardiac axes (can be radial and / or longitudinal; (f) extracting normalized time courses of projections (radial and / or longitudinal) along cardiac axes; and (g) defining a threshold value to determine the heart’s quiescent period.

[0007] According to some other embodiments, the method of the present disclosure applied to obtaining quiescent image of a cardiac valve can comprise: (a) conducting a PET scan of a patient and generating a listmode PET scan data that includes the patient’s heart; (b) extracting histo-image data at a high temporal resolution; (c) using a bounding box extracted from reconstructed PET scan data that was segmented for the cardiac valve of the patient’s heart, cropping the histo-image data to isolate the histo-image data of a cardiac valve of the patient’s heart; (d) identifying cardiac anatomical coordinates; (e) extracting time course of projections along longitudinal cardiac axes; (f) extracting normalized time course of the projections along longitudinal cardiac axes; and (g) defining a threshold value to determine the heart’s quiescent period.

[0008] The present disclosure also provides an imaging system utilizing the methods disclosed herein.BRIEF DESCRIPTION OF THE DRAWINGS

[0009] The features of the embodiments described herein will be more fully disclosed in the following detailed description, which is to be considered together with the accompanying drawings wherein like numbers refer to like parts.

[0010] FIG. 1 A shows ECG and left ventricle volume plots in one heartbeat cycle at rest condition showing the systolic and diastolic phases.

[0011] FIG. IB shows ECG and left ventricle volume plots in one heartbeat cycle at stress condition showing the systolic and diastolic phases.

[0012] FIG. 2 is a flowchart depicting a method of the present disclosure.

[0013] FIG. 3A is an illustration of radial projections through the left ventricle wall in enddiastole.

[0014] FIG. 3B is an illustration of radial projections through the left ventricle wall in endsystole.

[0015] FIG. 4A represents image intensity along each radial projection illustrated in FIG. 3A as a function of polar angle.

[0016] FIG. 4B represents image intensity along each radial projection illustrated in FIG. 3B as a function of polar angle.

[0017] FIG. 5 is a plot of normalized image intensity as a function of the cardiac cycle.

[0018] FIG, 6 is an illustration of longitudinal projections through a valve (e.g. aortic valve) in a ventricle of a heart.

[0019] FIG. 7 is an illustration of an imaging system according to an embodiment of the present disclosure.DETAILED DESCRIPTION

[0020] This description of the exemplary embodiments is intended to be read in connection with the accompanying drawings, which are to be considered part of the entire written description. The drawing figures are not necessarily to scale and certain features may be shown exaggerated in scale or in somewhat schematic form in the interest of clarity and conciseness. Inthe description, relative terms such as “horizontal,” “vertical,” “up,” “down,” “top” and “bottom” as well as derivatives thereof (e.g., “horizontally,” “downwardly,” “upwardly,” etc.) should be construed to refer to the orientation as then described or as shown in the drawing figure under discussion. These relative terms are for convenience of description and normally are not intended to require a particular orientation. Terms including “inwardly” versus “outwardly,” “longitudinal” versus “lateral” and the like are to be interpreted relative to one another or relative to an axis of elongation, or an axis or center of rotation, as appropriate. Terms concerning attachments, coupling and the like, such as “connected” and “interconnected,” refer to a relationship wherein structures are secured or attached to one another either directly or indirectly through intervening structures, as well as both movable or rigid attachments or relationships, unless expressly described otherwise. The term “operatively connected” is such an attachment, coupling or connection that allows the pertinent structures to operate as intended by virtue of that relationship.

[0021] Provided is a data-driven approach for identifying the quiescent period of a heart from PET scan data so that the PET scan data that corresponds to the quiescent period of the heart can be selectively used for reconstructing images of the heart. The resulting PET scan images of the heart are minimally affected by contractile motion of the heart.

[0022] The data driven measure of contractility of heart is akin to a ventricular volume curve and offers details about the quiescent period which is not evident in conventional ECG trace. For ECG, the action potentials during contraction of the left ventricle, for example, comprise the main signal for gating and there are no suitable ECG signatures to demarcate the quiescent period. On the other hand, the data driven signal would be based solely on cardiac motion where quiescent period should be more evident. All counts obtained during the quiescent phase of each separate heartbeat can be included for the reconstruction of a single motion-frozen cardiac image. The inventive technology disclosed here can also be employed in PET scans where ECG- gating is not typically performed.

[0023] Provided in FIG. 2 is a flowchart 100 that illustrates the imaging method according to some embodiments of the present disclosure.

[0024] The concepts of the disclosed invention will be described using imaging of the left ventricle of a heart as an example but one of ordinary skill in the art would understand that thedisclosed method can be applied to imaging of different parts of a heart. For example, the inventive method can be applied to defining the quiescent period for the right ventricle, the left atrium, the right atrium.

[0025] Furthermore, the disclosed method can be applied to defining the quiescent period for the valves in a heart. The details of how the disclosed method can be applied to the valves will be discussed during the discussions below for the left ventricle example.

[0026] Referring back to the flowchart 100, the disclosed method includes processes identified in sections A and section B of the flowchart 100. The processes identified in section A are carried out using reconstructed image data from PET, CT, or MR scan. The processes identified in section B are carried out on raw PET scan data (i.e. listmode data) of the heart. The output from the processes in section A are utilized by some of the processes in section B that will ultimately result in identifying the quiescent period of the heart and then selecting the histo- image data of the heart that only correspond to the quiescent period.

[0027] In section A of the flowchart 100, starting with the reconstructed PET, CT, or MR scan image 110 that includes a subject’s heart, the reconstructed image of the area of interest in the heart (the left ventricle in this example) is segmented, see step 111. Then, a bounding box defining the area around the area of interest (e.g. left ventricle) is extracted, see step 112, from the segmented reconstructed image. Next, an appropriate cardiac anatomical coordinate system is identified for the area of interest. For this left ventricle example, an array of radial (and / or longitudinal) cardiac vectors rnis extracted for the left ventricle, see step 113. For radial cardiac vectors, polar coordinates would be defined for the area of interest (the left ventricle in this example). As discussed below, for imaging a cardiac valve, more appropriate cardiac anatomical coordinate may be primarily longitudinal cardiac vectors. See the stylized illustrations in FIGs. 3A and 3B showing an array of radial cardiac vectors rnsuperimposed over a sectional view of the left ventricle for end-diastole and end-systole, respectively. In other words, the views shown in FIGs. 3A and 3B are slices taken through the long cardiac axis (i.e. longitudinal axis) of the left ventricle. At end-diastole, the myocardium 10 is in relaxed state and thus is thinner than the myocardium 10 at the end-systole.

[0028] In section B of the flowchart 100, starting with the raw PET scan data (listmode data) of the heart 120, histo-image data is extracted at a high temporal resolution, see step 130. Thehigh time of flight (TOF) performance of modem digital PET scanners enables direct generation of histo-images by accumulating event positions in the center of the TOF windows. These histo- images are non-quantitative but can be generated very quickly without performing a conventional reconstruction.

[0029] Next, because the motion of the heart can include respiratory and / or bulk motion of the patient, an optional pre-processing of the histo-image data can be performed to remove any respiratory and / or bulk motion of the patient, see step 135. This ensures that only motion components associated with cardiac contractility remain.

[0030] Next, using the bounding box that was extracted in step 112 in section A, the histo- image data is cropped to isolate the histo-image data of the left ventricle of the scanned heart, see step 140.

[0031] Next, using the array of radial cardiac vectors rnthat was identified and extracted in step 113 in section A, time course of radial projections is extracted, see step 150. The term “time course” here refers to a temporal series of events. See the plots of polar angle vs. projection image intensity for end-diastole and end-systole in FIGs. 4A and 4B, respectively. FIGs. 4A and 4B each represents image intensity along each radial projection as a function of the polar angle 4> at a given moment in time. Thus, at end-diastole, one plot like the one shown in FIG. 4A is generated for each slice taken through the long cardiac axis of the left ventricle at a given moment in time. Similarly, at end-systole, one plot like the one shown in FIG. 4B is generated for each slide taken through the long cardiac axis of the left ventricle at a given moment in time. The number of slices taken through the long cardiac axis can be optimized to provide meaningful data with minimum calculation time burden.

[0032] Next, normalized time course of the projections along the cardiac axes are extracted, see step 160. This produces the plot of derived projection image intensity position vs. cardiac cycle plot in FIG. 5. In other words, the plot in FIG. 5 is a plot of the integral of the time course of the radial projections over all slices taken through the long cardiac axis of the left ventricle. This plot is a surrogate for ventricular volume.

[0033] A moment will be taken here to consider how the disclosed method can be applied to taking image of cardiac valves instead of a ventricle. When applied to the valves, such as the aortic valve, the array of cardiac vectors representing the motion of the valves used for extractingtime course projections would be longitudinal vectors rather than radial vectors because the direction of the motion of the valves with respect to the direction of the motion of the myocardium of the ventricles is substantially orthogonal. This is illustrated in FIG. 6. FIG. 6 shows a cardiac valves 15 in a ventricle V. The array of vectors Lnrepresent the motion of the valves 15 and the array of vectors rnrepresent the contractile motion of the ventricle’s myocardium 10. The vectors Lnare substantially in longitudinal direction along the longitudinal axis of the ventricle V while the vectors rnare substantially in radial direction with respect to the longitudinal axis of the ventricle V.

[0034] Next, a threshold value T is defined to determine the boundaries for the quiescent period. The threshold value T is a free parameter that can be optimized to maximize the amount of signal that will be kept as being in the quiescent period of the heartbeat while not over defining the length of the quiescent period to minimize the amount of signal from the non- quiescent period from being defined as being in the quiescent period.

[0035] As shown in FIG. 5, the threshold value T defines the time points ti and ti that define the quiescent period. Thus, the period between ti and ti in the middle of the cardiac cycle shown in FIG. 5 is the non-quiescent period and the histo-image signals from that portion of the cardiac cycle would be discarded and only the histo-image signals from the quiescent period would be used for generating the final reconstructed image of the heart. For example, the threshold value T can be set as some % of the histo-image signal for a heartbeat.

[0036] In the processes outlined in the flowchart 100 of FIG. 2, the processes 150, 160, 170, and 180 in section B would be repeated for each heartbeat. In other words, the processes 150, 160, 170, and 180 is performed for the histo-image data set that corresponds to each heartbeat.

[0037] The resulting plot shown in FIG. 5 is a surrogate trace of the cardiac cycle derived directly from PET histo-images.

[0038] Still referring to FIG. 2, in some embodiments, the method of the present disclosure can comprise:(a) conducting a PET scan of a patient and generating a listmode PET scan data that includes the patient’s heart, see box 120;(b) extracting histo-image data at a high temporal resolution, see box 130;(c) using a bounding box extracted from reconstructed PET scan data that wassegmented for a ventricle of the patient’s heart, cropping the histo-image data to isolate the histo- image data of the ventricle of the patient’s heart, see box 140;(d) identifying cardiac anatomical coordinates, see box 113;(e) extracting time course of projections along cardiac axes (can be radial and / or longitudinal, see box 150;(f) extracting normalized time courses of projections (radial and / or longitudinal) along cardiac axes, see box 160; and(g) defining a threshold value to determine the heart’s quiescent period, see box 170.

[0039] In some embodiments, the method further comprises selecting only the histo-image data corresponding to the quiescent period, see box 180.

[0040] As discussed above, in some embodiments, step (d) comprises defining an array of radial and / or longitudinal cardiac vectors that was extracted from reconstructed PET, CT, or MR scan data that was segmented for left ventricle of the patient’s heart.

[0041] Often, histo-image data can be very noisy. Thus, in some embodiments, step (b) can include applying known denoising process. In some embodiments, such denoising process can be a neural network to denoise and enhance the quality of the histo-image data. In some embodiments, the neural network can be one that was trained with paired histo-images and fully reconstructed images.

[0042] According to some other embodiments, the inventive method described above using the left ventricle as an example is equally applicable to right ventricle.

[0043] According to some other embodiments, the inventive method described above using the left ventricle as an example is equally applicable to cardiac valves. The method of the present disclosure applied to obtaining quiescent image of a cardiac valve can comprise:(a) conducting a PET scan of a patient and generating a listmode PET scan data that includes the patient’s heart;(b) extracting histo-image data at a high temporal resolution;(c) using a bounding box extracted from reconstructed PET scan data that was segmented for the cardiac valve of the patient’s heart, cropping the histo-image data to isolate the histo-image data of a cardiac valve of the patient’s heart;(d) identifying cardiac anatomical coordinates;(e) extracting time course of projections along longitudinal cardiac axes;(f) extracting normalized time course of the projections along longitudinal cardiac axes; and(g) defining a threshold value to determine the heart’s quiescent period.

[0044] In some embodiments, the method of obtaining quiescent image of a cardiac valve can further comprise (h) selecting only the histo-image data corresponding to the quiescent period for image reconstruction.

[0045] In some embodiments, the cardiac valve can be an aortic valve, a pulmonary valve, a tricuspid valve, or a mitral valve.

[0046] In some embodiments, the step (d) comprises defining an array of longitudinal cardiac vectors that was extracted from reconstructed PET, CT, or MR scan data that was segmented for the ventricle of the patient’s heart.

[0047] In some embodiments, the step (b) comprises using a neural network to enhance the quality of the histo-image data.

[0048] In some embodiments, the neural network was trained with paired histo-images and fully reconstructed images.

[0049] The present disclosure also provides an imaging system 200 utilizing the method outlined in the flowchart 100. Such imaging system 200 can comprise: a PET scanner 230 that scans a heart in a subject to generate image data of the heart; a memory 252, provided in a controller 250, having instructions stored thereon; and a processor 253, provided in the controller 250, configured to read the instructions to:(a) conduct a PET scan of a patient and generating a listmode PET scan data that includes the patient’s heart, see box 120 of flowchart 100;(b) extracting histo-image data at a high temporal resolution, box 130 of flowchart 100;(c) cropping the histo-image data to isolate the histo-image data of a ventricle of the patient’s heart, see box 140 of flowchart 100;(d) identifying cardiac anatomical coordinates;(e) extracting time course projections along cardiac axes (can be radial and / or lonogitudinal), see box 150 of flowchart 100;(f) extracting normalized time course of all projections (radial and / or longitudinal) along cardiac axes, see box 160 of flowchart 100; and(g) threshold to define quiescent period, see box 170 of flowchart 100.

[0050] In some embodiments of the imaging system 200, the instructions further comprises instructions for the processor 253 to select only the histo-image data corresponding to the quiescent period, see box 180 of the flowchart 100. Such imaging system 200 would also include some basic components such as the patient handling unit 210 and patient tunnel 220.

[0051] The following is a list of non-limiting illustrative embodiments disclosed herein:

[0052] Illustrative embodiment 1. A method comprising: (a) conducting a PET scan of a patient and generating a listmode PET scan data that includes the patient’s heart; (b) extracting histo-image data at a high temporal resolution; (c) using a bounding box extracted from reconstructed PET scan data that was segmented for a ventricle of the patient’s heart, cropping the histo-image data to isolate the histo-image data of the ventricle of the patient’s heart; (d) identifying cardiac anatomical coordinates; (e) extracting time course of projections along cardiac axes; (f) extracting normalized time courses of the projections along cardiac axes; and (g) define a threshold value to determine the heart’s quiescent period.

[0053] Illustrative embodiment 2. The method of illustrative embodiment 1, further comprising (h) selecting only the histo-image data corresponding to the quiescent period for image reconstruction.

[0054] Illustrative embodiment 3. The method according to any one of the preceding illustrative embodiments, where the ventricle is a left ventricle.

[0055] Illustrative embodiment 4. The method according to any one of the preceding illustrative embodiments 1 and 2, where the ventricle is a right ventricle.

[0056] Illustrative embodiment 5. The method according to one of the preceding illustrative embodiments, where the step (d) comprises defining an array of radial and / or longitudinalcardiac vectors that was extracted from reconstructed PET, CT, or MR scan data that was segmented for the ventricle of the patient’s heart.

[0057] Illustrative embodiment 6. The method according to one of the preceding illustrative embodiments, where the step (b) comprises using a neural network to enhance the quality of the histo-image data.

[0058] Illustrative embodiment 7. The method according to the illustrative embodiment 6, where the neural network was trained with paired histo-images and fully reconstructed images.

[0059] Illustrative embodiment 8. The method according to one of the preceding illustrative embodiments, where the histo-image data is pre-processed to remove respiratory, bulk, and other motion components with temporal requencies lower than those defining cardiac contractility.

[0060] Illustrative embodiment 9. An imaging system comprising a PET scanner that scans a heart in a subject to generate image data of the heart; a memory having instructions stored thereon; and a processor configured to read the instructions to: (a) conduct a PET scan of a patient and generating a listmode PET scan data that includes the patient’s heart; (b) extracting histo-image data at a high temporal resolution; (c) using a bounding box extracted from reconstructed PET scan data that was segmented for a ventricle of the patient’s heart, cropping the histo-image data to isolate the histo-image data of the ventricle of the patient’s heart; (d) identifying cardiac anatomical coordinates; (e) extracting time course of projections along cardiac axes; (f) extracting normalized time course of the projections along cardiac axes; and (g) define a threshold value to determine the heart’s quiescent period.

[0061] Illustrative embodiment 10. The imaging system of illustrative embodiment 9, where the instructions further comprises instructions for the processor to select only the histo-image data corresponding to the quiescent period.

[0062] Illustrative embodiment 11. The imaging system of any one of the preceding illustrative embodiments 9 to 10, where the ventricle is a left ventricle.

[0063] Illustrative embodiment 12. The imaging system of any one of the preceding illustrative embodiments 9 to 10, where the ventricle is a right ventricle.

[0064] Illustrative embodiment 13. The imaging system of any one of the preceding illustrative embodiments 9 to 12, where the step (d) comprises defining an array of radial cardiac vectors that was extracted from reconstructed PET, CT, or MR scan data that was segmented for the ventricle of the patient’s heart.

[0065] Illustrative embodiment 14. The imaging system of any one of the preceding illustrative embodiments 9 to 13, where the step (b) comprises using a neural network to enhance the quality of the histo-image data.

[0066] Illustrative embodiment 15. The imaging system of illustrative embodiment 14, where the neural network was trained with paired histo-images and fully reconstructed images.

[0067] Illustrative embodiment 16. The imaging system of illustrative embodiment 9, where the histo-image data is pre-processed to remove respiratory, bulk, and other motion components with temporal requencies lower than those defining cardiac contractility.

[0068] Illustrative embodiment 17. A method comprising: (a) conducting a PET scan of a patient and generating a listmode PET scan data that includes the patient’s heart; (b) extracting histo-image data at a high temporal resolution; (c) using a bounding box extracted from reconstructed PET scan data that was segmented for the cardiac valve of the patient’s heart, cropping the histo-image data to isolate the histo-image data of a cardiac valve of the patient’s heart; (d) identifying cardiac anatomical coordinates; (e) extracting time course of projections along longitudinal axes; (f) extracting normalized time course of the projections along longitudinal axes; and (g) define a threshold value to determine the heart’s quiescent period.

[0069] Illustrative embodiment 18. The method of illustrative embodiment 17, further comprising (h) selecting only the histo-image data corresponding to the quiescent period for image reconstruction.

[0070] Illustrative embodiment 19. The method of any one of the preceding illustrative embodiments 17 and 18, where the cardiac valve is an aortic valve, a pulmonary valve, a tricuspid valve, or a mitral valve.

[0071] Illustrative embodiment 20. The method of any one of the preceding illustrative embodiments 17 to 19, where the step (d) comprises defining an array of longitudinal cardiac vectors that was extracted from reconstructed PET, CT, or MR scan data that was segmented for the cardiac valve of the patient’s heart.

[0072] Illustrative embodiment 21. The method of any one of the preceding illustrative embodiments 17 to 20, where the step (b) comprises using a neural network to enhance the quality of the histo-image data.

[0073] Illustrative embodiment 22. The method of the preceding illustrative embodiment 21, where the neural network was trained with paired histo-images and fully reconstructed images.

[0074] It will be understood that the foregoing description is of exemplary embodiments of this invention, and that the invention is not limited to the specific forms shown. Modifications may be made in the design and arrangement of the elements without departing from the scope of the invention.

Claims

What is claimed is:

1. A method comprising:(a) conducting a PET scan of a patient and generating a listmode PET scan data that includes the patient’s heart;(b) extracting histo-image data at a high temporal resolution;(c) using a bounding box extracted from reconstructed PET scan data that was segmented for a ventricle of the patient’s heart, cropping the histo-image data to isolate the histo-image data of the ventricle of the patient’s heart;(d) identifying cardiac anatomical coordinates;(e) extracting time course of projections along cardiac axes;(f) extracting normalized time courses of the projections along cardiac axes; and(g) define a threshold value to determine the heart’s quiescent period.

2. The method of claim 1, further comprising (h) selecting only the histo-image data corresponding to the quiescent period for image reconstruction.

3. The method of claim 1, wherein the ventricle is a left ventricle.

4. The method of claim 1, wherein the ventricle is a right ventricle.

5. The method of claim 4, wherein the step (d) comprises defining an array of radial and / or longitudinal cardiac vectors that was extracted from reconstructed PET, CT, or MR scan data that was segmented for the ventricle of the patient’s heart.

6. The method of claim 1, wherein the step (b) comprises using a neural network to enhance the quality of the histo-image data.

7. The method of claim 6, wherein the neural network was trained with paired histo-images and fully reconstructed images.

8. The method of claim 1, wherein the histo-image data is pre-processed to remove respiratory, bulk, and other motion components with temporal frequencies lower than those defining cardiac contractility.

9. An imaging system comprising: a PET scanner that scans a heart in a subject to generate image data of the heart;a memory having instructions stored thereon; and a processor configured to read the instructions to:(a) conduct a PET scan of a patient and generating a listmode PET scan data that includes the patient’s heart;(b) extracting histo-image data at a high temporal resolution;(c) using a bounding box extracted from reconstructed PET scan data that was segmented for a ventricle of the patient’s heart, cropping the histo-image data to isolate the histo- image data of the ventricle of the patient’s heart;(d) identifying cardiac anatomical coordinates;(e) extracting time course of projections along cardiac axes;(f) extracting normalized time course of the projections along cardiac axes; and(g) define a threshold value to determine the heart’s quiescent period.

10. The imaging system of claim 9, wherein the instructions further comprises instructions for the processor to select only the histo-image data corresponding to the quiescent period.

11. The imaging system of claim 9, wherein the ventricle is a left ventricle.

12. The imaging system of claim 9, wherein the ventricle is a right ventricle.

13. The imaging system of claim 9, wherein the step (d) comprises defining an array of radial cardiac vectors that was extracted from reconstructed PET, CT, or MR scan data that was segmented for the ventricle of the patient’s heart.

14. The imaging system of claim 9, wherein the step (b) comprises using a neural network to enhance the quality of the histo-image data.

15. The imaging system of claim 14, wherein the neural network was trained with paired histo-images and fully reconstructed images.

16. The imaging system of claim 9, wherein the histo-image data is pre-processed to remove respiratory, bulk, and other motion components with temporal frequencies lower than those defining cardiac contractility.

17. A method comprising:(a) conducting a PET scan of a patient and generating a listmode PET scan data that includes the patient’s heart;(b) extracting histo-image data at a high temporal resolution;(c) using a bounding box extracted from reconstructed PET scan data that was segmented for the cardiac valve of the patient’s heart, cropping the histo-image data to isolate the histo- image data of a cardiac valve of the patient’s heart;(d) identifying cardiac anatomical coordinates;(e) extracting time course of projections along longitudinal axes;(f) extracting normalized time course of the projections along longitudinal axes; and(g) define a threshold value to determine the heart’s quiescent period.

18. The method of claim 17, further comprising (h) selecting only the histo-image data corresponding to the quiescent period for image reconstruction.

19. The method of claim 17, wherein the cardiac valve is an aortic valve, a pulmonary valve, a tricuspid valve, or a mitral valve.

20. The method of claim 17, wherein the step (d) comprises defining an array of longitudinal cardiac vectors that was extracted from reconstructed PET, CT, or MR scan data that was segmented for the cardiac valve of the patient’s heart.

21. The method of claim 17, wherein the step (b) comprises using a neural network to enhance the quality of the histo-image data.

22. The method of claim 21, wherein the neural network was trained with paired histo- images and fully reconstructed images.

Images