Publications

This study aimed to compare computed tomography-derived fractional flow reserve (CT-FFR) values with graft patency and to establish the cut-off value of CT-FFR for predicting competitive graft flow after coronary artery bypass grafting (CABG). In 74 patients who underwent CABG, CT-FFR showed a high diagnostic accuracy (AUC = 0.977) with a cut-off value of 0.774 for predicting competitive graft flow. CT-FFR can provide useful information for predicting functional coronary artery stenosis and maintaining long-term graft patency.

This study validated the diagnostic performance of on-site automatic coronary computed tomography angiography-derived fractional flow reserve (CT-FFR) using a commercially available workstation. It involved 319 coronary artery disease (CAD) patients, showing a diagnostic accuracy of 80.6%, sensitivity of 88.1%, and specificity of 75.6% for predicting FFR ≤0.80. CT-FFR demonstrated superior diagnostic accuracy and discriminant ability compared to coronary computed tomography angiography (CCTA) for identifying hemodynamically significant lesions.

This study compares the performance of a deep learning-based location-adaptive threshold method (DL-LATM) software for coronary artery segmentation using coronary computed tomography angiography (CCTA) against other commercially available software. The study utilizes intravascular ultrasound (IVUS) data as the gold standard. The DL-LATM software demonstrated the highest accuracy in detecting lumen or plaque volume in stenotic regions, suggesting its potential as a supportive tool in diagnosing coronary artery disease (CAD).

This study evaluates the accuracy of a deep learning-based automated algorithm for coronary artery calcium (CAC) quantification based on enhanced ECG-gated coronary CT angiography (CCTA) with dedicated coronary calcium scoring CT (CSCT) as the reference. The algorithm showed high agreement with CSCT results, demonstrating excellent performance in volume and Agatston scores with a failure rate of 1.3%. The results support the use of this automated system for efficient CAC quantification and cardiovascular risk classification without additional radiation exposure.

Background: Field potential (FP) signals from human induced pluripotent stem cell-derived cardiomyocyte (hiPSC-CM) spheroid which are used for drug safety tests in the preclinical stage are different from action potential (AP) signals and require working knowledge of the multi-electrode array (MEA) system. In this study, we developed in silico three-dimensional (3-D) models of hiPSC-CM spheroids for the simulation of field potential measurement. We compared our model simulation results against in vitro experimental data under the effect of drugs E-4031 and nifedipine.

Cardiac resynchronization therapy (CRT) is an effective treatment option for patients with heart failure (HF) and left ventricular (LV) dyssynchrony. However, the problem of some patients not responding to CRT remains unresolved. This study aimed to propose a novel in silico method for CRT simulation.