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28 February 2020 Improved accuracy and precision of calcium mass score using deconvolution and partial volume correction
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Abstract
There are multiple quantitative methods for assessing coronary calcifications with CT including Agatston, mass score, and volume score. Several studies have shown mass score in mg-calcium to be the most reproducible. Since we are interested in tracking changes in individual calcifications over time as a new biomarker of vascular disease, we have analyzed ways to further improve reproducibility. The conventional way to calculate calcium mass score is to sum all voxels above 130- HU and convert to mass score using a calibration constant. This does not account for blurring in CT system. To improve coronary calcification measurements, we used Richardson-Lucy deconvolution with a measured 2D and 3D impulse response (Philips IQon) and/or partial volume correction processing. At 120 kVp, we imaged a phantom with calcium inserts and calcified cadaver hearts at three rotational orientations at high (0.4883-mm, 0.67-mm-thick) and normal clinical (0.4883-mm, 2.5-mm-thick) resolution. For each calcification in clinical resolution images, in the order of partial volume correction, 2D deconvolution, and 3D deconvolution processing, averaged percentage difference to the actual value of the QRM phantom calcification inserts evaluation are 0.07,0.13 and 0.22, improves as for non-processed clinical evaluation is -0.41. Similarly, in cadaver hearts, accuracy for averaged percentage difference compared to high resolution results are -0.21, 0.29 and 0.09 respectively, improves as the clinical evaluation is -0.51. In all cases, precision across rotation angle improves as coefficient of variation are 0.09, 0.10 and 0.11 respectively in the same processing order, slightly improves compare to clinical evaluation 0.13.
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Yingnan Song, Brendan L. Eck, Jacob Levi, and David L. Wilson "Improved accuracy and precision of calcium mass score using deconvolution and partial volume correction", Proc. SPIE 11317, Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging, 1131729 (28 February 2020); https://doi.org/10.1117/12.2549832
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