LV systolic point-cloud model to quantify accuracy of CT derived regional strain

Manohar, Ashish; Colvert, Gabrielle M.; Schluchter, Andrew; Contijoch, Francisco; McVeigh, Elliot R.

doi:10.1117/12.2512635

Cited by 2 publications

(1 citation statement)

References 25 publications

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“…In this paper, we describe the development of an anthropomorphically accurate LV mesh phantom with defined correspondences between endocardial points as a function of time across the cardiac cycle 33 . The phantom is derived from a high-resolution CT scan of a human LV and displacements were applied to each point to create analytical end systolic poses exhibiting physiologically accurate endocardial strains.…”

Section: Introductionmentioning

confidence: 99%

Anthropomorphic left ventricular mesh phantom: a framework to investigate the accuracy of SQUEEZ using Coherent Point Drift for the detection of regional wall motion abnormalities

et al. 2019

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Section: Introductionmentioning

confidence: 99%

Anthropomorphic left ventricular mesh phantom: a framework to investigate the accuracy of SQUEEZ using Coherent Point Drift for the detection of regional wall motion abnormalities

et al. 2019

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Anthropomorphic left ventricular mesh phantom: a framework to investigate the accuracy of SQUEEZ using Coherent Point Drift for the detection of regional wall motion abnormalities

Manohar

Colvert

Schluchter

et al. 2019

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We present an anthropomorphically accurate left ventricular (LV) phantom derived from human CT data to serve as the ground truth for the optimization and the spatial resolution quantification of a CT-derived regional strain metric (SQUEEZ) for the detection of regional wall motion abnormalities. Displacements were applied to the mesh points of a clinically derived end-diastolic LV mesh to create analytical end-systolic poses with physiologically accurate endocardial strains. Normal function as well as regional dysfunction of four sizes (1, 2/3, 1/2, and 1/3 AHA (American Heart Association) segments as core diameter), each exhibiting hypokinesia (70% reduction in strain) and subtle hypokinesia (40% reduction in strain), were simulated. Regional shortening (RSCT) estimates were obtained by registering the end-diastolic mesh to each simulated end-systolic mesh condition using a non-rigid registration algorithm. Ground-truth models of normal function and of hypokinesia were used to identify the optimal parameters in the registration algorithm, and to measure the accuracy of detecting regional dysfunction of varying sizes and severities. For normal LV function, RSCT values in all 16 AHA segments were accurate to within ±5%. For cases with regional dysfunction, the errors in RSCT around the dysfunctional region increased with decreasing size of dysfunctional tissue.The current gold-standard for the non-invasive assessment of regional LV function is cardiovascular magnetic resonance (CMR) tagging 7-10 . However, CMR requires extended breath holds, acquisition over multiple heart beats, and manual contouring 7,11 . The growing number of patients with metallic medical device implants further limits the clinical use of CMR.Recent advances in x-ray computed tomography (CT) have made possible the acquisition of an entire 3D volume of the heart from a single table position in ~140 ms, which implies a series of functional images spanning the full cardiac cycle can be obtained within a single heartbeat [12][13][14][15][16] .Additionally, the spatial resolution (0.4 x 0.4 x 0.6 mm 3 nominal voxel size) allows for the detection and tracking of the fine endocardial texture comprising trabeculae carneae and papillary muscles 17 . The drawback of CT is patient exposure to ionizing radiation; however, due to recent advancements in CT technology, especially in the last 5 years, the average dose received by a patient from a functional cardiac CT scan is ~3 mSv, which is the average dose received from natural sources in a year 18 . SQUEEZ 17 is a new method introduced to measure regional endocardial strain from 4DCT images acquired with routine clinical protocols. SQUEEZ exploits the high fidelity of x-ray CT to track features of the endocardium, which are used by a non-rigid point set registration technique 19 to derive displacements of points on the endocardium across the cardiac cycle. This displacement estimate is used to obtain information on the regional strain of the endocardium. SQUEEZ has shown to be capable of differentiating ...

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LV systolic point-cloud model to quantify accuracy of CT derived regional strain

Cited by 2 publications

References 25 publications

Anthropomorphic left ventricular mesh phantom: a framework to investigate the accuracy of SQUEEZ using Coherent Point Drift for the detection of regional wall motion abnormalities

Anthropomorphic left ventricular mesh phantom: a framework to investigate the accuracy of SQUEEZ using Coherent Point Drift for the detection of regional wall motion abnormalities

Anthropomorphic left ventricular mesh phantom: a framework to investigate the accuracy of SQUEEZ using Coherent Point Drift for the detection of regional wall motion abnormalities

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