Combining IVUS + OCT Data, Biomechanical Models and Machine Learning Method for Accurate Coronary Plaque Morphology Quantification and Cap Thickness and Stress/Strain Index Predictions.

Assessment and prediction of vulnerable plaque progression and rupture risk are of utmost importance for diagnosis, management and treatment of cardiovascular diseases and possible prevention of acute cardiovascular events such as heart attack and stroke. However, accurate assessment of plaque vulnerability assessment and prediction of its future changes require accurate plaque cap thickness, tissue component and structure quantifications and mechanical stress/strain calculations. Multi-modality intravascular ultrasound (IVUS), optical coherence tomography (OCT) and angiography image data with follow-up were acquired from ten patients to obtain accurate and reliable plaque morphology for model construction.

Predicting Coronary Stenosis Progression Using Plaque Fatigue From IVUS-Based Thin-Slice Models: A Machine Learning Random Forest Approach.

Coronary stenosis due to atherosclerosis restricts blood flow. Stenosis progression would lead to increased clinical risk such as heart attack. Although many risk factors were found to contribute to atherosclerosis progression, factors associated with fatigue is underemphasized.

Image-based biomechanical modeling for coronary atherosclerotic plaque progression and vulnerability prediction.

Atherosclerotic plaque progression and rupture play an important role in cardiovascular disease development and the final drastic events such as heart attack and stroke. Medical imaging and image-based computational modeling methods advanced considerably in recent years to quantify plaque morphology and biomechanical conditions and gain a better understanding of plaque evolution and rupture process. This article first briefly reviewed clinical imaging techniques for coronary thin-cap fibroatheroma (TCFA) plaques used in image-based computational modeling.

Using Optical Coherence Tomography and Intravascular Ultrasound Imaging to Quantify Coronary Plaque Cap Stress/Strain and Progression: A Follow-Up Study Using 3D Thin-Layer Models.

Accurate plaque cap thickness quantification and cap stress/strain calculations are of fundamental importance for vulnerable plaque research. To overcome uncertainties due to intravascular ultrasound (IVUS) resolution limitation, IVUS and optical coherence tomography (OCT) coronary plaque image data were combined together to obtain accurate and reliable cap thickness data, stress/strain calculations, and reliable plaque progression predictions. IVUS, OCT, and angiography baseline and follow-up data were collected from nine patients (mean age: 69; m: 5) at Cardiovascular Research Foundation with informed consent obtained.

Very late vasomotor responses and gene expression with bioresorbable scaffolds and metallic drug-eluting stents.

Objectives: To investigate the long-term vasomotor response and inflammatory changes in Absorb bioresorbable vascular scaffold (BVS) and metallic drug-eluting stent (DES) implanted artery.

Background: Clinical evidence has demonstrated that compared to DES, BVS is associated with higher rates of target lesion failure. However, it is not known whether the higher event rates observed with BVS are related to endothelial dysfunction or inflammation associated with polymer degradation.