Nowadays, vulnerable coronary plaque detection from coronary computed tomography angiography (CCTA) is suboptimal, although being crucial for preventing major adverse cardiac events. Moreover, despite the suggestion of various vulnerability biomarkers, encompassing image and biomechanical factors, accurate patient stratification remains elusive, and a comprehensive approach integrating multiple markers is lacking. To this aim, this study introduces an innovative approach for assessing vulnerable coronary arteries and patients by integrating radiomics and biomechanical markers through machine learning methods. The study included 40 patients (7 high-risk and 33 low-risk) who underwent both CCTA and coronary optical coherence tomography (OCT). The dataset comprised 49 arteries (with 167 plaques), 7 of which (with 28 plaques) identified as vulnerable by OCT. Following image preprocessing and segmentation, CCTA-based radiomic features were extracted and a finite element analysis was performed to compute the biomechanical features. A novel machine learning pipeline was implemented to stratify coronary arteries and patients. For each stratification task, three independent predictive models were developed: a radiomic, a biomechanical and a combined radiomic-biomechanical model. Both k-nearest neighbors (KNN) and decision tree (DT) classifiers were considered. The best radiomic model (KNN) detected all 7 vulnerable arteries and patients and was associated with a balanced accuracy of 0.86 (sensitivity=1, specificity=0.71) for the artery model and of 0.83 (sensitivity=1, specificity=0.67) for the patient model. The best biomechanical model (DT) detected 6 over 7 vulnerable arteries and patients and remarkably increased the specificity, resulting in a balanced accuracy of 0.89 (sensitivity=0.86, specificity=0.93) for the artery model and of 0.88 (sensitivity=0.86, specificity=0.91) for the patient model. Notably, the combined approach optimized the performance, with an increase in the balance accuracy up to 0.94 for the artery model and up to 0.92 for the patient model, being associated with sensitivity=1 and high specificity (0.88 and 0.85 for artery and patient models, respectively). This investigation highlights the promise of radio-mechanical coronary artery phenotyping for patient stratification. If confirmed from larger studies, our approach enables a more personalized management of the disease, with the early identification of high-risk individuals and the reduction of unnecessary interventions for low-risk individuals.

Mitral annular calcification is a chronic and degenerative process of the fibrous base of the mitral valve. Surgical management of mitral valve dysfunction with severe annular calcification remains technically demanding and, to date, the preferred approach is still a standard full sternotomy. We aimed to analyze and report our experience with mitral valve surgery addressing annular calcification via the minimally invasive approach through a right mini-thoracotomy. Data of patients with mitral valve disease and underlying annular calcification undergoing minimally invasive surgery from 2018 to 2022 were prospectively collected and retrospectively analyzed. The severity of mitral annular calcification was categorized with an angio-computerized tomography scan analysis as mild, moderate or severe according to calcium thickness, calcium distribution, and trigone and leaflet involvement using the Mitral Annular Calcification Computerized Tomography-score. During the study period, 27 patients with mitral valve disease and associated mitral annular calcification were enrolled. The most common etiology was advanced Barlow’s disease, which was encountered in 18 cases (67%). Mitral valve replacement was performed in 21 patients (78%). No intraoperative death, atrioventricular disruption, or circumflex coronary artery injury occurred. Conversion to sternotomy was necessary in a single case. Residual moderate periprosthetic leak requiring early reoperation and permanent heart block mandating permanent pacemaker implantation were reported in one and in three patients, respectively. No cases of stroke were reported. Two patients died, accounting for a 7.4% perioperative mortality. At a median follow-up of 9 months, one patient had residual moderate mitral regurgitation, whereas two patients required short-term reoperation and prosthetic valve (re)replacement. Minimally invasive mitral valve surgery via right mini-thoracotomy should be considered an and effective approach to be indicated also in patients with mild-to-severe mitral annular calcification. Routine angio-computerized tomography scan during work-up is a mandatory step to stratify the anatomical extension and severity of the mitral annular calcification.

Background The role of planned angiographic control (PAC) over a conservative management driven by symptoms and ischaemia following percutaneous coronary intervention (PCI) of the unprotected left main (ULM) with second-generation drug-eluting stents remains controversial. PAC may timely detect intrastent restenosis, but it is still unclear if this translated into improved prognosis. Methods and analysis PULSE is a prospective, multicentre, open-label, randomised controlled trial. Consecutive patients treated with PCI on ULM will be included, and after the index revascularisation patients will be randomised to PAC strategy performed with CT coronary after 6 months versus a conservative symptoms and ischaemia-driven follow-up management. Follow-up will be for at least 18 months from randomisation. Major adverse cardiovascular events at 18 months (a composite endpoint including death, cardiovascular death, myocardial infarction (MI) (excluding periprocedural MI), unstable angina, stent thrombosis) will be the primary efficacy outcome. Secondary outcomes will include any unplanned target lesion revascularisation (TLR) and TLR driven by PAC. Safety endpoints embrace worsening of renal failure and bleeding events. A sample size of 550 patients (275 per group) is required to have a 80% chance of detecting, as significant at the 5% level, a 7.5% relative reduction in the primary outcome. Trial registration number NCT04144881