Incremental value of physiological indices to predict high-risk plaques detected by NIRS-IVUS

Identification of vulnerable plaques is important for reducing future cardiovascular events. This study aimed to investigate optimal modalities other than intravascular imaging in evaluating vulnerable plaques. We prospectively evaluated 105 non-culprit coronary lesions by CCTA imaging and near-infrared spectroscopy-intravascular ultrasound in 32 patients with acute coronary syndrome. Angiographically-derived ΔQFR and ΔFFR<sub>CT</sub> were measured as the difference in QFR and FFR<sub>CT</sub> across the stenosis. A receiver operating characteristic curve analysis was performed to determine the optimal cutoff values of angiographically- and CCTA-derived plaque features for a maxLCBI<sub>4mm</sub> ≥ 400. The best cutoff values for ΔQFR and ΔFFR<sub>CT</sub> to predict a maxLCBI<sub>4mm</sub> ≥ 400 were 0.05 and 0.06, respectively. ΔQFR and ΔFFR<sub>CT</sub> values and percent diameter stenosis on QCA or CCTA were associated with a maxLCBI<sub>4mm</sub> ≥ 400 (both P < 0.05). The combination of ΔFFR<sub>CT</sub> ≥ 0.06 and plaque density predicted a maxLCBI<sub>4mm</sub> ≥ 400 with 89.4% sensitivity and 84.5% specificity (area under the curve, 0.90; P < 0.0001). There was no significant difference in area under the curve values between ΔQFR and plaque density + ΔFFR<sub>CT</sub> ≥ 0.06 (0.92 vs. 0.90, P = 0.50). In the diagnosis of vulnerable plaques in acute coronary syndrome, the combination of ΔFFR<sub>CT</sub> and plaque density shows a diagnostic capability similar to that of ΔQFR in non-culprit lesions.

Authors

Institutions

Publication Details

Journal
Cardiovascular Intervention and Therapeutics
Published
2025-03-12
DOI
https://doi.org/10.1007/s12928-025-01116-7
Citations
2
Primary Topic
Cardiac Imaging and Diagnostics
Type
article
Field-Weighted Citation Impact
2.72
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Incremental value of physiological indices to predict high-risk plaques detected by NIRS-IVUS

Keishiro Sugimoto, Kazuyoshi Kakehi, Hiroki Matsuzoe, Kosuke Fujita et al.
2 citations
Cardiovascular Intervention and Therapeutics
Cardiac Imaging and Diagnostics
2.72
article

Incremental value of physiological indices to predict high-risk plaques detected by NIRS-IVUS

Keishiro Sugimoto, Kazuyoshi Kakehi, Hiroki Matsuzoe, Kosuke Fujita, Gaku Nakazawa, Kyohei Onishi, Yohei Funauchi, Koichiro Matsumura, Takayuki Kawamura, Masafumi Ueno, Nobuhiro Yamada
article en
2 citations

Abstract

Identification of vulnerable plaques is important for reducing future cardiovascular events. This study aimed to investigate optimal modalities other than intravascular imaging in evaluating vulnerable plaques. We prospectively evaluated 105 non-culprit coronary lesions by CCTA imaging and near-infrared spectroscopy-intravascular ultrasound in 32 patients with acute coronary syndrome. Angiographically-derived ΔQFR and ΔFFR<sub>CT</sub> were measured as the difference in QFR and FFR<sub>CT</sub> across the stenosis. A receiver operating characteristic curve analysis was performed to determine the optimal cutoff values of angiographically- and CCTA-derived plaque features for a maxLCBI<sub>4mm</sub> ≥ 400. The best cutoff values for ΔQFR and ΔFFR<sub>CT</sub> to predict a maxLCBI<sub>4mm</sub> ≥ 400 were 0.05 and 0.06, respectively. ΔQFR and ΔFFR<sub>CT</sub> values and percent diameter stenosis on QCA or CCTA were associated with a maxLCBI<sub>4mm</sub> ≥ 400 (both P < 0.05). The combination of ΔFFR<sub>CT</sub> ≥ 0.06 and plaque density predicted a maxLCBI<sub>4mm</sub> ≥ 400 with 89.4% sensitivity and 84.5% specificity (area under the curve, 0.90; P < 0.0001). There was no significant difference in area under the curve values between ΔQFR and plaque density + ΔFFR<sub>CT</sub> ≥ 0.06 (0.92 vs. 0.90, P = 0.50). In the diagnosis of vulnerable plaques in acute coronary syndrome, the combination of ΔFFR<sub>CT</sub> and plaque density shows a diagnostic capability similar to that of ΔQFR in non-culprit lesions.

Cardiovascular Intervention and TherapeuticsVol. 40(3)
Kindai University (JP)
Openalex Percentile: Top 12%
Cardiac Imaging and Diagnostics
2.72
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.