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Novel measurement of LV twist using 4DCT: quantifying accuracy as a function of image noise
Author(s): Gabrielle M. Colvert; Ashish Manohar; Brendan Colvert; Andrew Schluchter; Francisco Contijoch; Elliot McVeigh
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Paper Abstract

Large trials have demonstrated the prognostic value of quantifying left ventricular (LV) twist because of its crucial role in the coupling of systolic and diastolic cardiac function. Current methods for measuring LV twist evaluate rotation in a 2D plane, chosen prospectively, and the data is acquired over multiple heartbeats. In this paper, a new method for assessing 3D endocardial LV twist from single-heartbeat, ECG-gated, 4DCT volumes is proposed. In this study, the ability of the novel LV twist algorithm to accurately measure rotation in a mathematical phantom with known deformation is evaluated. The mathematical phantom was then 3D-printed to determine the accuracy of the rotation measurement from CT images in the presence of varying levels of noise. Lastly, as a proof-of-concept, LV twist was measured in human hearts across the cardiac cycle to determine whether reasonable estimates of endocardial rotation could be obtained from 4DCT studies of standard clinical quality. In both the mathematical and 3D-printed phantoms (for CNR≥9.3), the measured LV twist was highly correlated (r2≥ 0.98, p<0.001) with the known ground truth rotation function. In the healthy controls, the mean endocardial LV twist was found to be 25.3° ± 6.5° and occurred within 30-36% of the R-R interval. From these results, it is clear that 3D rotational information and LV twist can be obtained from ECG-gated 4DCT volumes. The accuracy of LV twist in clinical data requires validation via a gold standard, such as MRI-tagging

Paper Details

Date Published: 15 March 2019
PDF: 10 pages
Proc. SPIE 10953, Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging, 109531K (15 March 2019); doi: 10.1117/12.2512532
Show Author Affiliations
Gabrielle M. Colvert, Univ. of California, San Diego (United States)
Ashish Manohar, Univ. of California, San Diego (United States)
Brendan Colvert, Univ. of California, San Diego (United States)
Andrew Schluchter, Univ. of California, San Diego (United States)
Francisco Contijoch, Univ. of California, San Diego (United States)
Elliot McVeigh, Univ. of California, San Diego (United States)


Published in SPIE Proceedings Vol. 10953:
Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging
Barjor Gimi; Andrzej Krol, Editor(s)

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