Deep learning model for low-dose CT late iodine enhancement imaging and extracellular volume quantification.

Objectives: To develop and validate deep learning (DL)-models that denoise late iodine enhancement (LIE) images and enable accurate extracellular volume (ECV) quantification.

Methods: This study retrospectively included patients with chest discomfort who underwent CT myocardial perfusion + CT angiography + LIE from two hospitals. Two DL models, residual dense network (RDN) and conditional generative adversarial network (cGAN), were developed and validated.

Advancements in imaging of intracranial atherosclerotic disease: beyond the arterial lumen to the vessel wall.

Intracranial atherosclerotic disease (ICAD) significantly increases the risk of ischemic stroke. It involves the accumulation of plaque within arterial walls and narrowing or blockage of blood vessel lumens. Accurate imaging is crucial for the diagnosis and management of ICAD at both acute and chronic stages.

Prognostic implications of pre-transcatheter aortic valve replacement computed tomography-derived coronary plaque characteristics and stenosis severity.

Objectives: The study aimed to investigate the prognostic value of pre-transcatheter aortic valve replacement (TAVR) computed tomography angiography (CTA) in assessing physiological stenosis severity (CTA-derived fractional flow reserve (CT-FFR)) and high-risk plaque characteristics (HRPC).

Materials And Methods: Among TAVR patients who underwent pre-procedure CTA, the presence and number of HRPCs (minimum lumen area of < 4 mm, plaque burden ≥ 70%, low-attenuating plaques, positive remodeling, napkin-ring sign, or spotty calcification) as well as CT-FFR were assessed. The risk of vessel-oriented composite outcome (VOCO, a composite of vessel-related ischemia-driven revascularization, vessel-related myocardial infarction, or cardiac death) was compared according to the number of HRPC and CT-FFR categories.

Financial and clinical outcomes of CT myocardial perfusion imaging and coronary CT angiography-guided versus coronary CT angiography-guided strategy.

Objectives: To compare the financial and clinical outcomes of CT myocardial perfusion imaging (CT-MPI) + coronary CT angiography (CCTA)-guided versus CCTA-guided strategy in patients suspected of chronic coronary syndrome (CCS).

Materials And Methods: This study retrospectively included consecutive patients suspected of CCS and referred for CT-MPI+CCTA-guided and CCTA-guided treatment. The details of medical costs within 3 months after index imaging, including downstream invasive procedures, hospitalization, and medications, were recorded.

CT-derived fractional flow reserve for prediction of major adverse cardiovascular events in diabetic patients.

Objectives: To investigate the prognostic value of computed tomography fractional flow reserve (CT-FFR) in patients with diabetes and to establish a risk stratification model for major adverse cardiac event (MACE).

Methods: Diabetic patients with intermediate pre-test probability of coronary artery disease were prospectively enrolled. All patients were referred for coronary computed tomography angiography and followed up for at least 2 years.

Computed Tomography Radiomics Model Predicts Procedure Success of Coronary Chronic Total Occlusions.

Background: Coronary computed tomography (CT) angiography imaging is useful for the preprocedural evaluation of chronic total occlusion (CTO). However, the predictive value of CT radiomics model for successful percutaneous coronary intervention (PCI) has not been studied. We aimed to develop and validate a CT radiomics model for predicting PCI success of CTOs.

Deep Learning Segmentation and Reconstruction for CT of Chronic Total Coronary Occlusion.

Background CT imaging of chronic total occlusion (CTO) is useful in guiding revascularization, but manual reconstruction and quantification are time consuming. Purpose To develop and validate a deep learning (DL) model for automated CTO reconstruction. Materials and Methods In this retrospective study, a DL model for automated CTO segmentation and reconstruction was developed using coronary CT angiography images from a training set of 6066 patients (582 with CTO, 5484 without CTO) and a validation set of 1962 patients (208 with CTO, 1754 without CTO).

Radiomics features of pericoronary adipose tissue improve CT-FFR performance in predicting hemodynamically significant coronary artery stenosis.

Objectives: To evaluate the value of radiomics-based model of pericoronary adipose tissue (PCAT) combined with CT fractional flow reserve (CT-FFR) in predicting hemodynamically significant coronary stenosis.

Methods: Patients with suspected or known coronary artery disease, who had coronary computed tomography angiography (CCTA), invasive coronary angiography (ICA), and FFR within 1 month, were retrospectively included. Radiomics features of lesion-based PCAT were extracted.

A Novel Computed Tomography-Based Imaging Approach for Etiology Evaluation in Patients With Acute Coronary Syndrome and Non-obstructive Coronary Angiography.

This study sought to investigate the diagnostic value of dynamic CT myocardial perfusion imaging (CT-MPI) combined with coronary CT angiography (CCTA) in acute coronary syndrome (ACS) patients without obstructive coronary angiography. Consecutive ACS patients with normal or non-obstructive coronary angiography findings who had cardiac magnetic resonance (CMR) contraindications or inability to cooperate with CMR examinations were prospectively enrolled and referred for dynamic CT-MPI + CCTA + late iodine enhancement (LIE). ACS etiology was determined according to combined assessment of coronary vasculature by CCTA, quantified myocardial blood flow (MBF) and presence of LIE.