Plaque Characteristics Derived from Intravascular Optical Coherence Tomography That Predict Cardiovascular Death

被引:0
作者
Lee, Juhwan [1 ]
Gharaibeh, Yazan [2 ]
Zimin, Vladislav N. [3 ]
Kim, Justin N. [1 ]
Hassani, Neda S. [4 ]
Dallan, Luis A. P. [4 ]
Pereira, Gabriel T. R. [4 ]
Makhlouf, Mohamed H. E. [4 ]
Hoori, Ammar [1 ]
Wilson, David L. [1 ,5 ]
机构
[1] Case Western Reserve Univ, Dept Biomed Engn, Cleveland, OH 44106 USA
[2] Hashemite Univ, Fac Engn, Dept Biomed Engn, Zarqa 13133, Jordan
[3] Brookdale Univ Hosp Med Ctr, 1 Brookdale Plaza, Brooklyn, NY 11212 USA
[4] Univ Hosp Cleveland Med Ctr, Harrington Heart & Vasc Inst, Cleveland, OH 44106 USA
[5] Case Western Reserve Univ, Dept Radiol, Cleveland, OH 44106 USA
来源
BIOENGINEERING-BASEL | 2024年 / 11卷 / 08期
关键词
intravascular optical coherence tomography; cardiovascular death; plaque characteristics; fibrous cap surface area; OCTOPUS;
D O I
10.3390/bioengineering11080843
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
This study aimed to investigate whether plaque characteristics derived from intravascular optical coherence tomography (IVOCT) could predict a long-term cardiovascular (CV) death. This study was a single-center, retrospective study on 104 patients who had undergone IVOCT-guided percutaneous coronary intervention. Plaque characterization was performed using Optical Coherence TOmography PlaqUe and Stent (OCTOPUS) software developed by our group. A total of 31 plaque features, including lesion length, lumen, calcium, fibrous cap (FC), and vulnerable plaque features (e.g., microchannel), were computed from the baseline IVOCT images. The discriminatory power for predicting CV death was determined using univariate/multivariate logistic regressions. Of 104 patients, CV death was identified in 24 patients (23.1%). Univariate logistic regression revealed that lesion length, calcium angle, calcium thickness, FC angle, FC area, and FC surface area were significantly associated with CV death (p < 0.05). In the multivariate logistic analysis, only the FC surface area (OR 2.38, CI 0.98-5.83, p < 0.05) was identified as a significant determinant for CV death, highlighting the importance of the 3D lesion analysis. The AUC of FC surface area for predicting CV death was 0.851 (95% CI 0.800-0.927, p < 0.05). Patients with CV death had distinct plaque characteristics (i.e., large FC surface area) in IVOCT. Studies such as this one might someday lead to recommendations for pharmaceutical and interventional approaches.
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