Non-contrast Cardiac CT Images Dataset with Coronary Artery Calcium Scoring
The database investigated the association between cardiac fat volume and coronary artery disease (CAD). This dataset includes 14,127 non-contrast computed tomography (CT) slices of 120 patients diagnosed with CAD using an assessment of coronary artery calcium scoring by a cardiovascular specialist and radiologist, with 43 patients having coronary artery disease and the rest of the patients in the healthy individuals' group. Findings of Coronary artery calcium (CAC) in cardiac CT have been demonstrated to be a reliable and strong marker of coronary artery atherosclerosis. CAC represents one-fifth of the total plaque burden, indicating a high linear correlation with the second root of total pathologic plaque levels (r = 0.90; p <0.001). CAC may be a more sensitive and specific determinant of CAD risk than conventional CAD risk factors, which may indicate over- and under-diagnosis in arterial atherosclerosis. CAC scanning is a non-contrast-enhanced image acquisition technique that is performed while holding a breath. The weighted sum of CAC is defined by areas in the coronary artery with Hounsfield unit values greater than 130 including three or more adjacent pixels. Standard CAC classifications based on studies generally agree that CAC values of 0 to 10 indicate no calcified plaque, and values of 11 to 100, 101 to 400, and more than 400 indicate mild, moderate, and severe CAC levels, respectively. Between June 2017 and January 2019, this dataset was randomly collected from Parsian CT angiography medical center in shahid Madani hospital, Tabriz. As a statement, the Ethics Committee of Tabriz University of Medical Sciences approved this study (approval ID: IR.TBZMED.REC.1398.122).
Tabriz University of Medical Sciences