Anatomical vs Physiological Lesion Characteristics in Prediction of Acute Coronary Syndrome

  • Seokhun Yang
  • , Jae Wook Chung
  • , Sang Hyeon Park
  • , Jinlong Zhang
  • , Keehwan Lee
  • , Doyeon Hwang
  • , Kyu Sun Lee
  • , Sang Hoon Na
  • , Joon Hyung Doh
  • , Chang Wook Nam
  • , Tae Hyun Kim
  • , Eun Seok Shin
  • , Eun Ju Chun
  • , Su Yeon Choi
  • , Hyun Kuk Kim
  • , Young Joon Hong
  • , Hun Jun Park
  • , Song Yi Kim
  • , Mirza Husic
  • , Jess Lambrechtsen
  • Jesper M. Jensen, Bjarne L. Nørgaard, Daniele Andreini, Pal Maurovich-Horvat, Bela Merkely, Martin Penicka, Bernard de Bruyne, Abdul Ihdayhid, Brian Ko, Georgios Tzimas, Jonathon Leipsic, Javier Sanz, Mark G. Rabbat, Farhan Katchi, Moneal Shah, Nobuhiro Tanaka, Ryo Nakazato, Taku Asano, Mitsuyasu Terashima, Hiroaki Takashima, Tetsuya Amano, Yoshihiro Sobue, Hitoshi Matsuo, Hiromasa Otake, Takashi Kubo, Masahiro Takahata, Takashi Akasaka, Teruhito Kido, Teruhito Mochizuki, Hiroyoshi Yokoi, Taichi Okonogi, Tomohiro Kawasaki, Koichi Nakao, Tomohiro Sakamoto, Taishi Yonetsu, Tsunekazu Kakuta, Yohei Yamauchi, Charles A. Taylor, Jeroen J. Bax, Leslee J. Shaw, Peter H. Stone, Jagat Narula, Bon Kwon Koo

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Background Acute coronary syndrome (ACS) arises from a complex interplay among luminal narrowing, plaque morphology, and hemodynamic environment. Objectives The authors aimed to compare the effectiveness of anatomy- and physiology-based ACS risk assessment. Methods In this international, multicenter, internal case-control study, 351 ACS patients who underwent coronary computed tomography angiography (CCTA) 1 month to 3 years before the event were analyzed. Lesions were classified as culprit or nonculprit based on invasive coronary angiography at the time of ACS. Core lab CCTA analyses assessed lesion-specific characteristics: stenosis severity, adverse plaque characteristics (APC) (low-attenuation plaque, positive remodeling, spotty calcification, napkin-ring sign), plaque burden at minimum lumen area, and changes in CCTA-derived fractional flow reserve (ΔFFRCT). Diagnostic performance in identifying culprit lesions was compared. Results Among 2,451 lesions, 363 (14.8%) became ACS culprits, with a median interval of 375 [95.0-644.5] days. All anatomical and simulated physiological characteristics were independently associated with culprit lesions (all P < 0.001). In identifying ACS culprit lesions, plaque burden ≥70% showed the highest sensitivity of 90.6% (87.2%-93.2%) and ΔFFRCT ≥0.10 had the highest specificity of 88.3% (86.9%-89.6%) %. Predictability was similar between ΔFFRCT and the combined degree of stenosis, the number of APCs, and plaque burden (area under the curve 0.805 [0.782-0.829] vs 0.802 [0.777-0.826]; P = 0.748), with additive discrimination towards each other. Conclusions Luminal narrowing, plaque quality and quantity, and local hemodynamics were independent predictors of ACS, offering specificity in physiology and sensitivity in anatomy. A comprehensive assessment of them further refined the risk prediction for future ACS.

Original languageEnglish
Pages (from-to)2833-2845
Number of pages13
JournalJACC: Cardiovascular Interventions
Volume18
Issue number23
DOIs
Publication statusPublished - 08-12-2025
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Cardiology and Cardiovascular Medicine

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