AI DErived Plaque Quantification: CCTA and AI-QCPA for Determining Effective CAD Management
New and updated registry entries spanned AI cardiac imaging, a supplement trial, metabolic and oncology studies, and an AI review of diabetes self-management.
TL;DR
- ClinicalTrials.gov entries in the collection include a trial of AI-derived plaque quantification from CCTA imaging for coronary artery disease management.
- Other registry entries cover Urolithin A supplementation and glucose metabolism in adults 55 and older, and proton therapy for small cell lung cancer.
- A PubMed scoping review covers AI-driven digital tools for diabetes self-management in children.
The registry feed carried a study titled "AI DErived Plaque Quantification: CCTA and AI-QCPA for Determining Effective CAD Management," grouping an imaging-derived biomarker with a management decision in coronary artery disease. A separate entry evaluates intensity-modulated proton therapy for small cell lung cancer. [1] [5]
Interventional and supplement studies fill out the pipeline. One randomized, triple-masked controlled trial examines the effects of Urolithin A supplementation on glucose metabolism in healthy adults aged 55 and older; another entry tests ultrasound-guided needle percutaneous electrolysis with therapeutic exercise in femoroacetabular impingement syndrome. [2] [4]
A PubMed scoping review takes a different angle, surveying AI-driven digital tools for diabetes self-management in children. Registry entries describe planned or ongoing work, so they are not results. [3]
Why it matters
Trial registrations are an early signal of where a field is heading before results exist. This snapshot shows AI moving into routine imaging decisions while conventional device, supplement and radiotherapy studies continue.
Editor's note
Registry entries are study descriptions, not outcomes; titles are reported as registered and no results or effect sizes are asserted.