Lee Juhwan, Gharaibeh Yazan, Zimin Vladislav N, Kim Justin N, Hassani Neda S, Dallan Luis A P, Pereira Gabriel T R, Makhlouf Mohamed H E, Hoori Ammar, Wilson David L
Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, USA.
Department of Biomedical Engineering, Faculty of Engineering, The Hashemite University, Zarqa 13133, Jordan.
Bioengineering (Basel). 2024 Aug 19;11(8):843. doi: 10.3390/bioengineering11080843.
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 ( < 0.05). In the multivariate logistic analysis, only the FC surface area (OR 2.38, CI 0.98-5.83, < 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, < 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.
本研究旨在探讨血管内光学相干断层扫描(IVOCT)得出的斑块特征是否能够预测长期心血管(CV)死亡。本研究是一项针对104例接受IVOCT引导下经皮冠状动脉介入治疗患者的单中心回顾性研究。使用我们团队开发的光学相干断层扫描斑块与支架(OCTOPUS)软件进行斑块特征分析。从基线IVOCT图像中计算出总共31个斑块特征,包括病变长度、管腔、钙化、纤维帽(FC)以及易损斑块特征(如微通道)。使用单变量/多变量逻辑回归确定预测CV死亡的判别能力。在104例患者中,有24例(23.1%)发生CV死亡。单变量逻辑回归显示,病变长度、钙化角度、钙化厚度、FC角度、FC面积和FC表面积与CV死亡显著相关(<0.05)。在多变量逻辑分析中,只有FC表面积(OR 2.38,CI 0.98 - 5.83,<0.05)被确定为CV死亡的显著决定因素,突出了三维病变分析的重要性。FC表面积预测CV死亡的AUC为0.851(95%CI 0.800 - 0.927,<0.05)。发生CV死亡的患者在IVOCT中有明显的斑块特征(即大FC表面积)。这样的研究可能有朝一日会为药物和介入治疗方法带来建议。