Yoshihiro Sobue

OBJECTIVES: Automated artificial intelligence (AI)-based assessment of atherosclerosis burden applied to coronary computed tomography angiography (CCTA) can optimize image processing times, standardize interpretation, and minimize inter-observer variability. We investigated the diagnostic utility of AI-based CCTA quantification (AI-QCT) of coronary atherosclerosis in coronary segments co-registered with intravascular ultrasound (IVUS) of diseased and non-diseased segments. MATERIALS AND METHODS: Patients who underwent CCTA and IVUS in the INVICTUS registry (ClinicalTrials.gov: NCT04066062) were enrolled. Images were analyzed by independent core laboratories blinded to each modality's findings. Vessel external elastic membrane (EEM), lumen, plaque volumes, plaque burden, and percent atheroma volume (PAV) were quantified in whole co-registered segments and subsegments containing non-calcified and low-attenuation plaques. A calcium index was calculated for the whole co-registered segment. RESULTS: A total of 108 vessels from 85 patients were included. Pearson's correlation demonstrated strong associations between AI-QCT and IVUS in quantifying the EEM volume (r = 0.899), lumen volume (r = 0.943), and plaque volume (r = 0.833), length-normalized PAV (r = 0.851), and calcium index (r = 0.960) in the whole-segment analysis. Strong correlations were seen for vessel, lumen, and plaque volumes in non-calcified (Pearson's coefficient: 0.95, 0.97, and 0.83, respectively) and low-attenuation (Pearson's coefficient: 0.90, 0.86, and 0.86, respectively) plaque segments. The minimum lumen area was 0.61 ± 1.18 mm2 (95% CI, -0.83 to -0.38) smaller by AI-QCT than IVUS, with a similar lumen area stenosis (mean difference, 1.26 ± 24.17; 95% CI, -3.37 to 5.90). CONCLUSIONS: AI-QCT quantification of atherosclerosis burden showed high correlations and close agreement with IVUS in whole-segment and segments with non-calcified and low-attenuation plaques. KEY POINTS: Question Coronary atheroma burden is a powerful predictor of cardiovascular events. Can AI-based coronary CT angiography (CCTA) accurately quantify atherosclerotic burden across the full disease spectrum when compared with intravascular ultrasound (IVUS)? Findings AI-based CCTA quantification (AI-QCT) showed strong correlations with IVUS for plaque volume, burden, and calcium across whole coronary segments, including non-calcified and low-attenuation plaques. Clinical relevance AI-QCT provides rapid, automatic, and accurate atherosclerosis quantification without reader-dependent variability, enabling standardized cardiovascular risk assessment, treatment monitoring, and therapeutic decision-making across all disease severity spectrum in routine clinical practice.

BACKGROUND: The relevant time frame for predicting future acute coronary syndrome (ACS) based on coronary lesion characteristics remains uncertain. OBJECTIVES: The aim of this study was to investigate the association of lesion characteristics with test-to-event time and their prognostic impact on ACS. METHODS: The EMERALD II (Exploring the Mechanism of Plaque Rupture in Acute Coronary Syndrome Using Coronary CT Angiography and Computational Fluid Dynamics II) study analyzed 351 patients who underwent coronary computed tomography angiography (CTA) and experienced ACS between 1 month and 3 years of follow-up. Lesions identified on coronary CTA were classified as culprit (n = 363) or nonculprit (n = 2,088) on the basis of invasive coronary angiography findings at the time of ACS. Core laboratory coronary CTA analyses assessed 4 domains: degree of stenosis, plaque burden, number of adverse plaque characteristics (APC) (low-attenuation plaque, positive remodeling, spotty calcification, and napkin-ring sign), and changes in coronary CTA-derived fractional flow reserve across the lesion (ΔFFRCT). Patients were categorized into short (<1 year), mid (1-2 years), and long (2-3 years) test-to-event time groups. RESULTS: Patient characteristics, including cardiovascular risk factors, did not differ across short, mid, and long test-to-event groups (P > 0.05 for all), and the proportion of ACS culprit lesions was similar (P = 0.552). Among culprit lesions, shorter test-to-event time was associated with higher luminal stenosis, plaque burden, and ΔFFRCT (P for trend < 0.001 for all). The predictability for ACS culprit lesions based on the combined 4 characteristics tended to decrease over time and significantly reduced beyond 2 years (AUC: 0.851 vs 0.741; P = 0.006). In predicting ACS risk within test-to-event time <2 years using obstructive lesions (stenosis ≥ 50%), APC ≥2, plaque burden ≥70%, and ΔFFRCT ≥0.10, the risk was elevated compared to the average proportion of lesions becoming ACS culprit (12.1%) in the following subsets: lesions with 4 characteristics (proportion of lesions becoming ACS culprit: 49.3%; P < 0.001), lesions with 3 characteristics (obstructive lesions with plaque burden ≥70% and either ΔFFRCT ≥0.10 [proportion of lesions becoming ACS culprit: 33.0%; P < 0.001] or APC ≥2 [proportion of lesions becoming ACS culprit: 31.2%; P < 0.001]), and lesions with 2 characteristics (plaque burden ≥70% and ΔFFRCT ≥0.10; proportion of lesions becoming ACS culprit: 21.5%; P = 0.016). CONCLUSIONS: Increased luminal stenosis, plaque burden, and ΔFFRCT were associated with shorter test-to-ACS event time. The prognostic impact of lumen, plaque, and local hemodynamic characteristics was most relevant to ACS risk within a 2-year period, with higher risk observed when specific combinations of them were present. (Exploring the Mechanism of Plaque Rupture in Acute Coronary Syndrome Using Coronary CT Angiography and Computational Fluid Dynamics II [EMERALD II] Study; NCT03591328).

OBJECTIVE: This study highlights a case in which we performed a complex percutaneous coronary intervention on a 60-mm chronic total occlusion lesion with a remarkably low radiation dose by using the SPOT region of interest (SPOT ROI) function available on the Alphenix Evolve Edition X-ray system (Canon Medical Systems). KEY STEPS: Fluoroscopy was conducted exclusively using SPOT ROI from the start of guiding catheter engagement. The wire successfully traversed the chronic total occlusion lesion with SPOT ROI. Despite a fluoroscopy time of 71 min, the total radiation dose was kept at 990 mGy, remaining <1 Gy. POTENTIAL PITFALLS: The SPOT ROI function is only available on the Alphenix Evolve Edition X-ray system and cannot be used with other X-ray equipment. TAKE-HOME MESSAGE: This case suggests that SPOT ROI can be leveraged to safely reduce radiation during complex percutaneous coronary intervention.