학술논문
Abstract 13674: Optimal Hounsfield Threshold for Lipid-Rich Plaque by Artificial Intelligence-Enabled Quantitative CT Using Near-Infrared Spectroscopy
Document Type
Academic Journal
Author
Omori, Hiroyuki; Matsuo, Hitoshi; Earls, James; Sobue, Yoshihiro; Fujimoto, Shinichiro; Nozaki, Yui; Nakazawa, Gaku; Takahashi, Kuniaki; Osawa, Kazuhiro; Okubo, Ryo; Kaneko, Umihiko; Sato, Hideyuki; Kajiya, Takashi; Miyoshi, Toru; Ichikawa, Keishi; Abe, Mitsunori; Kitagawa, Toshiro; Ikenaga, Hiroki; Saji, Mike; Iguchi, Nobuo; Ijichi, Takeshi; Mikamo, Hiroshi; Kurata, Akira; Moroi, Masao; iijima, raisuke; Crabtree, Tami; Min, James K; Nakanishi, Rine
Source
Circulation. Nov 08, 2022 146(Suppl_1 Suppl 1):A13674-A13674
Subject
Language
English
ISSN
0009-7322
Abstract
Introduction: By near-infrared spectroscopy (NIRS), plaques with 4-mm maximum lipid-core burden index (maxLCBI4mm) ≥ 400 are lipid-rich plaque. By CCTA, the optimal Hounsfield threshold (HU) for lipid-rich plaques defined by presence of low-density non-calcified plaque (LD-NCP) is still unclear.Hypothesis: Artificial intelligence-enabled quantitative CT (AI-QCT) will enable identification of HU for lipid-rich plaques when compared to NIRS reference standard.Methods: 128 atherosclerotic plaques from 47 patients were enrolled prospectively. MaxLCBI4mm (cutoff was defined as 400) and LD-NCP derived from AI-QCT (Cleerly LABS, Denver CO) were compared. LD-NCP using 3 different thresholds (<30, <50, and <70 HU) were analyzed by sensitivity, specificity, positive and negative predictive value, accuracy, and area Under the Curve (AUC).Results: Amongst 128 atherosclerotic plaques evaluated, 26 (20.3%) met NIRS criteria for lipid rich plaque (maxLCBI4mm ≥400). The volume of LD-NCP was measure using three different thresholds, <30, <50, and <70 HU as well as criteria of PR > 1.1 and LD-NCP volume >1.8 mm (LD-NCP volume threshold identified from AUC). This yielded a sensitivity, specificity, positive and negative predictive value, accuracy, and AUC of 92%, 88%, 67%, 98%, 89%, and 0.944 at <30HU, 96%, 79%, 53%,99% 82%, 0.921 at <50HU, and 96% 72%, 46%, 99%, 77%, and 0.907 respectively at <70HU (30 vs. 50 HU: p=0.008; 30 vs. 70HU: p=0.002 (Figure 1).Conclusions: A <30 HU threshold for definition of LD-NCP on AI-QCT correlates optimally with NIRS proven lipid-rich plaques.