0000000000247579
AUTHOR
Giulia Sollami
Aortic valve and vascular calcium score in pre-TAVI CT: correlation with early post-procedural complications
Abstract Purpose The aim of our study was to evaluate the prevalence of early complications after Transcatheter Aortic Valve Implantation (TAVI) and their correlation with the Calcium Score (CS) of the aortic valve, aorta and ilio-femoral arteries derived from pre-procedural computed tomography (CT). Materials and methods We retrospectively reviewed 226 patients (100 males, mean age 79.4 ± 6.7 years) undergoing 64-slice CT for pre-TAVI evaluation from January 2018 to April 2021. The population was divided into CS quartiles. Results Overall, 173 patients underwent TAVI procedure, of whom 61% presented paravalvular leak after the procedure, 28% presented bleeding or vascular complications, 25…
Technical development in cardiac CT: current standards and future improvements—a narrative review
Non-invasive depiction of coronary arteries has been a great challenge for imaging specialists since the introduction of computed tomography (CT). Technological development together with improvements in spatial, temporal, and contrast resolution, progressively allowed implementation of the current clinical role of the CT assessment of coronary arteries. Several technological evolutions including hardware and software solutions of CT scanners have been developed to improve spatial and temporal resolution. The main challenges of cardiac computed tomography (CCT) are currently plaque characterization, functional assessment of stenosis and radiation dose reduction. In this review, we will discu…
CT Radiomic Features and Clinical Biomarkers for Predicting Coronary Artery Disease
AbstractThis study was aimed to investigate the predictive value of the radiomics features extracted from pericoronaric adipose tissue — around the anterior interventricular artery (IVA) — to assess the condition of coronary arteries compared with the use of clinical characteristics alone (i.e., risk factors). Clinical and radiomic data of 118 patients were retrospectively analyzed. In total, 93 radiomics features were extracted for each ROI around the IVA, and 13 clinical features were used to build different machine learning models finalized to predict the impairment (or otherwise) of coronary arteries. Pericoronaric radiomic features improved prediction above the use of risk factors alon…