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Background: Severe coronary artery calcification is associated with stent underexpansion and subsequent stent failure., Aims: We aimed to identify optical coherence tomography (OCT)-derived predictors of absolute (minimal stent area [MSA]) and relative stent expansion in calcified lesions., Methods: This retrospective cohort study included patients who underwent percutaneous coronary intervention (PCI) with OCT assessment before and after stent implantation between May 2008 and April 2022. Pre-PCI OCT was used to assess calcium burden and post-PCI OCT was used to assess absolute and relative stent expansion., Results: A total of 361 lesions in 336 patients were analyzed. Target lesion calcification (defined as OCT-detected maximum calcium angle ≥ 30°) was present in 242 (67.0%) lesions. Following PCI, median MSA was 5.37 mm 2 in calcified lesions and 6.24 mm 2 in noncalcified lesions (p < 0.001). Median stent expansion was 78% in calcified lesions and 83% in noncalcified lesions (p = 0.325). In the subset of calcified lesions, average stent diameter, preprocedural minimal lumen area, and total calcium length were independent predictors of MSA in multivariable analysis (mean difference 2.69 mm 2 /mm 2 , 0.52 mm 2 /mm, and -0.28 mm 2 /5 mm, respectively, all p < 0.001). Total stent length was the only independent predictor of relative stent expansion (mean difference -0.465% per mm, p < 0.001). Calcium angle, thickness, and the presence of nodular calcification were not significantly associated with MSA or stent expansion in multivariable analyses., Conclusion: Calcium length appeared to be the most important OCT-derived predictor of MSA, whereas stent expansion was mainly determined by total stent length., (© 2023 The Authors. Catheterization and Cardiovascular Interventions published by Wiley Periodicals LLC.)

Lesion calcification is frequently encountered during percutaneous coronary intervention and has been directly linked to procedural complications and future cardiac events. Intravascular lithotripsy is a novel balloon-based modality that does not rely on barotrauma or debulking, but converts electrical energy into mechanical energy creating sonic pressure waves that selectively disrupt calcium. The present review provides an overview of its mechanism of action, the available evidence on its safety and efficacy and indications for use., Competing Interests: Declaration of Competing Interest Joost Daemen received institutional grant/research support from Astra Zeneca, Abbott Vascular, Boston Scientific, ACIST Medical Systems, Medtronic, Pie Medical, and ReCor Medical. The remaining authors have nothing to disclose., (Copyright © 2022. Published by Elsevier Inc.)

Background: Coronary calcification has been linked to cardiovascular events. We developed and validated an algorithm to automatically quantify coronary calcifications on intravascular ultrasound (IVUS). We aimed to assess the prognostic value of an IVUS-calcium score (ICS) on patient-oriented composite endpoint (POCE)., Methods: We included patients that underwent coronary angiography plus pre-procedural IVUS imaging. The ICS was calculated per patient. The primary endpoint was a composite of all-cause mortality, stroke, myocardial infarction, and revascularization (POCE)., Results: In a cohort of 408 patients, median ICS was 85. Both an ICS ≥ 85 and a 100 unit increase in ICS increased the risk of POCE at 6-year follow-up (adjusted hazard ratio (aHR) 1.51, 95%CI 1.05-2.17, p value = 0.026, and aHR 1.21, 95%CI 1.04-1.41, p value = 0.014, respectively)., Conclusions: The ICS, calculated by a validated automated algorithm derived from routine IVUS pullbacks, was strongly associated with the long-term risk of POCE., (© 2021. The Author(s).)

Coronary calcification represents a challenge in the treatment of coronary artery disease by stent placement. It negatively affects stent expansion and has been related to future adverse cardiac events. Intravascular ultrasound (IVUS) is known for its high sensitivity in detecting coronary calcification. At present, automated quantification of calcium as detected by IVUS is not available. For this reason, we developed and validated an optimized framework for accurate automated detection and quantification of calcified plaque in coronary atherosclerosis as seen by IVUS. Calcified lesions were detected by training a supported vector classifier per IVUS A-line on manually annotated IVUS images, followed by post-processing using regional information. We applied our framework to 35 IVUS pullbacks from each of the three commonly used IVUS systems. Cross-validation accuracy for each system was >0.9, and the testing accuracy was 0.87, 0.89 and 0.89 for the three systems. Using the detection result, we propose an IVUS calcium score, based on the fraction of calcium-positive A-lines in a pullback segment, to quantify the extent of calcified plaque. The high accuracy of the proposed classifier suggests that it may provide a robust and accurate tool to assess the presence and amount of coronary calcification and, thus, may play a role in image-guided coronary interventions., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)