CT-derived ECV thresholds reduced screening rates for ATTR-CM in severe AS from 84.5% to 25.1%, maintaining high sensitivity and improving patient selection precision.
Does CT-derived ECV optimize patient selection for ATTR-CM diagnostic work-up in patients with severe aortic stenosis?
CT-derived ECV can serve as an objective gatekeeper to streamline patient selection for ATTR-CM screening in severe aortic stenosis, potentially reducing unnecessary testing compared to clinical criteria alone.
Tasa de eventos absoluta: 0% vs 0%
Abstract Background Transthyretin cardiac amyloidosis (ATTR-CM) is increasingly recognized in patients with severe aortic stenosis (AS), particularly elderly individuals undergoing transcatheter aortic valve implantation (TAVI). It may affect up to 1 in 8 patients over 65 years with severe AS. The 2021 ESC position statement by Garcia-Pavia et al. recommends screening patients aged ≥65 years with severe AS and left ventricular hypertrophy, though uptake remains low—partly due to uncertainty in selecting appropriate candidates. Extracellular volume (ECV) quantification by cardiac CT has emerged as a reproducible, objective tool to support screening. Incorporated into standard pre-TAVI protocols via delayed acquisitions, it enables myocardial tissue characterization without workflow disruption. Scully et al. validated CT-derived ECV thresholds with high sensitivity and negative predictive value (NPV) for excluding cardiac uptake on scintigraphy: ECV 29.2%: NPV 100% for Perugini ≥1 ECV 31.4%: NPV 98% for Perugini ≥1 ECV 33.4%: NPV 100% for Perugini 2–3 These thresholds support ECV’s potential role as a gatekeeper for more targeted screening. Purpose To assess the implementation of guideline-based ATTR-CM screening in severe AS and evaluate whether CT-derived ECV can optimize patient selection for diagnostic work-up. Methods We included 207 patients with severe AS who underwent pre-procedural CT between March 2024 and March 2025. A 5-minute delayed dual-energy acquisition enabled ECV quantification via iodine density mapping. ECV was measured in basal, mid, and apical short-axis slices; the mean of basal and mid segments was used, in line with prior validation studies. Results Among 207 patients, 175 (84.5%) met clinical criteria for ATTR-CM screening, but only 8 (3.9%) were effectively screened. Of these, three were awaiting DPD scintigraphy and five had negative diagnostic work-ups. Notably, over half of the screened patients had ECV 29.2%, despite fulfilling clinical criteria. The median ECV was 30.25% (IQR 27.6–33.4). Applying established thresholds: 58.9% had ECV 29.2% 38.6% had ECV 31.4% 25.1% had ECV 33.4% Thus, ECV-based triage could reduce screening rates from 84.5% to a range between 58.9% and 25.1%, depending on the selected threshold—without compromising sensitivity, and improving precision in patient selection. No significant differences in age, sex, or BMI were observed across ECV strata, reinforcing its added value over conventional clinical parameters. Conclusion Despite increasing awareness, real-world screening for ATTR-CM in severe AS remains rare. CT-derived ECV serves as a valuable gatekeeper, offering an objective and practical approach to streamline patient selection, reduce unnecessary testing, and enhance adherence to structured screening pathways. External validation is warranted.
Lôbo et al. (Thu,) reported a other. CT-derived ECV thresholds reduced screening rates for ATTR-CM in severe AS from 84.5% to 25.1%, maintaining high sensitivity and improving patient selection precision.