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. 2024 Mar 2;12(1):34–39. doi: 10.1159/000538044

Table 1.

The use of NIRS-IVUS for predicting subsequent cardiovascular event

Publication Aim Design Sample size Primary endpoint Results
Culprit
 Goldstein et al. [11] 2011 To determine whether intracoronary NIRS-IVUS can identify plaques that are likely to cause periprocedural MI in patients undergoing elective PCI Cohort 62 Rate of periprocedural MI 50% (high LCBI) versus 4.2% (low LCBI) (p = 0.0002)
 Lim et al. [19] 2022 To identify association between LCBI and decreased TIMI flow in patients undergoing PCI Cohort 636 Association between a decreased TIMI flow and LCBI Odds ratio of high LCBI for decreased TIMI flow (2.59, 95% CI 1.33–5.04; p = 0.005)
Non-culprit
 Waksman et al. [21] 2019 Assessing the ability of NIRS-IVUS imaging to detect vulnerable patients and vulnerable plaques Cohort 1,271 Association between maxLCBI4mm and non-culprit major adverse cardiovascular events Hazard ratio of high LCBI for NC-MACE (1.89, 95% CI 1.26–2.83; p = 0.0021)
 Stone et al. [22] 2020 Pilot randomized trial of PCI treatment of vulnerable plaques to inform a future large-scale pivotal study RCT 182 IVUS-derived minimum lumen area BVS versus GDMT alone
Target lesion failure MLA: 6.9±2.6 mm2 versus 3.0±1.0 mm2; p < 0.0001
TLF: 4.3% versus 10.7%; p = 0.12
 Erlinge et al. [23] 2021 To validate the use of NIRS-IVUS for identification of non-obstructive lipid-rich plaques that are prone to cause future cardiac events Cohort 898 (3,629 vessel) Composite endpoint including cardiac death, myocardial infarction, unstable angina, or progressive angina arising from untreated non-culprit lesions Hazard ratio of high LCBI for NC-MACE (2.27, 95% CI 1.25–4.13; p = 0.0071)
 Biccirè et al. [24] 2023 To analyze the proportions, determinants, and prognostic implications of triple regression (atheroma volume reduction, lipid content reduction, and increase in fibrous cap) RCT 265 The composite endpoint of death, myocardial infarction, and ischemia-driven revascularization Triple regression for composite endpoints (yes vs. no; 8.3% vs. 18.2%; p = 0.04)