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15 March 2019 Novel measurement of LV twist using 4DCT: quantifying accuracy as a function of image noise
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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
Conference Presentation
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gabrielle M. Colvert, Ashish Manohar, Brendan Colvert, Andrew Schluchter, Francisco Contijoch, and Elliot McVeigh "Novel measurement of LV twist using 4DCT: quantifying accuracy as a function of image noise", Proc. SPIE 10953, Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging, 109531K (15 March 2019);

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