CARDIAN: a novel computational approach for real-time end-diastolic frame detection in intravascular ultrasound using bidirectional attention networks.

Introduction: Changes in coronary artery luminal dimensions during the cardiac cycle can impact the accurate quantification of volumetric analyses in intravascular ultrasound (IVUS) image studies. Accurate ED-frame detection is pivotal for guiding interventional decisions, optimizing therapeutic interventions, and ensuring standardized volumetric analysis in research studies. Images acquired at different phases of the cardiac cycle may also lead to inaccurate quantification of atheroma volume due to the longitudinal motion of the catheter in relation to the vessel.

Machine learning for atherosclerotic tissue component classification in combined near-infrared spectroscopy intravascular ultrasound imaging: Validation against histology.

Background And Aims: Accurate classification of plaque composition is essential for treatment planning. Intravascular ultrasound (IVUS) has limited efficacy in assessing tissue types, while near-infrared spectroscopy (NIRS) provides complementary information to IVUS but lacks depth information. The aim of this study is to train and assess the efficacy of a machine learning classifier for plaque component classification that relies on IVUS echogenicity and NIRS-signal, using histology as reference standard.

Detection of lipid-core plaques by intracoronary near-infrared spectroscopy identifies high risk of periprocedural myocardial infarction.

Background: Percutaneous coronary intervention (PCI) is associated with periprocedural myocardial infarction (MI) in 3% to 15% of cases (depending on the definition used). In many cases, these MIs result from distal embolization of lipid-core plaque (LCP) constituents. Prospective identification of LCP with catheter-based near-infrared spectroscopy (NIRS) may predict an increased risk of periprocedural MI and facilitate development of preventive measures.

In vivo validation of a catheter-based near-infrared spectroscopy system for detection of lipid core coronary plaques: initial results of the SPECTACL study.

Objectives: To determine whether catheter-based near-infrared spectroscopy (NIRS) signals obtained with a novel catheter-based system from coronaries of patients are similar to those from autopsy specimens and to assess initial safety of NIRS device.

Background: An intravascular NIRS system for detection of lipid core-containing plaques (LCP) has been validated in human coronary autopsy specimens. The SPECTACL (SPECTroscopic Assessment of Coronary Lipid) trial was a parallel first-in-human multicenter study designed to demonstrate the applicability of the LCP detection algorithm in living patients.

Increased radiation dose to overweight and obese patients from radiographic examinations.

Purpose: To estimate the increase in effective radiation dose from diagnostic x-rays for overweight and obese adult patients, as compared with the effective dose for lean reference phantoms.

Materials And Methods: Relative effective radiation doses (E/E(0)) for the acquisition of chest and abdominal radiographs were calculated by using Monte Carlo computer simulations of effective doses delivered to adult phantoms with (E) and without (E(0)) subcutaneous adipose tissue added to the torso for five fat distributions. Total (anterior plus posterior) fat thicknesses ranged from 0 to 38 cm.

Sustained involvement of a frontal-parietal network for spatial response selection with practice of a spatial choice-reaction task.

With practice, performance on a task typically becomes faster, more accurate, and less prone to interference from competing tasks. Some theories of this performance change suggest it reflects a qualitative reorganization of the cognitive processing required for successful task performance. Other theories suggest this change in performance reflects a more quantitative change in the amount of processing required to perform the task.