Objectives This study sought to examine the utility of multimodality intravascular imaging and of the endothelial shear stress (ESS) distribution to predict atherosclerotic evolution. Background There is robust evidence that intravascular ultrasound (IVUS)-derived plaque characteristics and ESS distribution can predict, with however limited accuracy, atherosclerotic evolution; nevertheless, it is yet unclear whether multimodality imaging and ESS mapping enable more accurate prediction of coronary plaque progression. Methods A total of 44 patients admitted with a myocardial infarction that had successful revascularization and 3-vessel IVUS and optical coherence tomography (OCT) imaging at baseline and 13-month follow-up were included in the study. The IVUS data acquired at baseline in the nonculprit vessels were fused with x-ray angiography to reconstruct coronary anatomy and in the obtained models blood flow simulation was performed and the ESS was estimated. The baseline plaque characteristics and ESS distribution were used to identify predictors of disease progression: defined as a lumen reduction and an increase in plaque burden at follow-up. Results Seventy-three vessels were included in the final analysis. Baseline ESS and the IVUS-derived but not the OCT-derived plaque characteristics were independently associated with a decrease in lumen area and an increase in plaque burden. Low ESS (odds ratio: 0.45; 95% confidence interval: 0.28 to 0.71; p < 0.001) and plaque burden (odds ratio: 0.73; 95% confidence interval: 0.54 to 0.97; p = 0.030) were the only independent predictors of disease progression at follow-up. The accuracy of the IVUS-derived plaque characteristics in predicting disease progression did not improve when ESS (AUC: 0.824 vs. 0.847; p = 0.127) or when OCT variables and ESS (AUC: 0.842; p = 0.611) were added into the model. Conclusions ESS and OCT-derived variables did not improve the efficacy of IVUS in predicting disease progression. Further research is required to investigate whether multimodality imaging combined with ESS mapping will allow more reliable vulnerable plaque detection. (Comparison of Biomatrix Versus Gazelle in ST-Elevation Myocardial Infarction \[STEMI\] \[COMFORTABLE\]; [NCT00962416][1]) [1]: https://clinicaltrials.gov/ct2/show/NCT00962416

中文翻译：

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实用的多模态血管内成像和局部血流动力学力预测动脉粥样硬化疾病进展

目的本研究旨在检查多模态血管内成像和内皮切应力（ESS）分布在预测动脉粥样硬化演变中的作用。背景技术有强有力的证据表明，血管内超声（IVUS）引起的斑块特征和ESS分布可以预测动脉粥样硬化的发展，但准确性有限。然而，尚不清楚多模态成像和ESS映射是否能够更准确地预测冠状动脉斑块的进展。方法研究共纳入44例在基线和13个月随访中成功进行了血运重建，3血管IVUS和光学相干断层扫描（OCT）成像的心肌梗死患者。将在非罪犯血管中基线获得的IVUS数据与X射线血管造影术相融合，以重建冠状动脉解剖结构，并在获得的模型中进行血流模拟并估算ESS。基线斑块特征和ESS分布用于确定疾病进展的预测指标：定义为随访时管腔减少和斑块负担增加。结果最终分析中包括73艘船。基线ESS和IVUS衍生的斑块特征与OCT衍生的斑块特征无关，它们与管腔面积的减少和斑块负担的增加独立相关。低ESS（优势比：0.45; 95％置信区间：0.28至0.71; p <0.001）和菌斑负担（优势比：0.73; 95％置信区间：0.54至0.97; p = 0）。030）是随访中疾病进展的唯一独立预测因子。当将ESS（AUC：0.824 vs. 0.847; p = 0.127）或将OCT变量和ESS（AUC：0.842; p = 0.611）添加到模型中时，IVUS衍生斑块特征在预测疾病进展中的准确性并没有提高。结论ESS和OCT衍生的变量不能提高IVUS预测疾病进展的功效。需要进一步研究以调查多模态成像与ESS映射相结合是否将允许更可靠的易损斑块检测。（ST抬高型心肌梗死\ [STEMI \] \ [COMFORTABLE \]中生物基质与瞪羚的比较； [NCT00962416] [1]）[1]：https：//clinicaltrials.gov/ct2/show/NCT00962416 当将ESS（AUC：0.824 vs. 0.847; p = 0.127）或将OCT变量和ESS（AUC：0.842; p = 0.611）添加到模型中时，IVUS衍生斑块特征在预测疾病进展中的准确性并没有提高。结论ESS和OCT衍生的变量不能提高IVUS预测疾病进展的功效。需要进一步研究以调查多模态成像与ESS映射相结合是否将允许更可靠的易损斑块检测。（ST抬高型心肌梗死\ [STEMI \] \ [COMFORTABLE \]中生物基质与瞪羚的比较； [NCT00962416] [1]）[1]：https：//clinicaltrials.gov/ct2/show/NCT00962416 当将ESS（AUC：0.824 vs. 0.847; p = 0.127）或将OCT变量和ESS（AUC：0.842; p = 0.611）添加到模型中时，IVUS衍生斑块特征在预测疾病进展中的准确性并没有提高。结论ESS和OCT衍生的变量不能提高IVUS预测疾病进展的功效。需要进一步研究以调查多模态成像与ESS映射相结合是否将允许更可靠的易损斑块检测。（ST抬高型心肌梗死\ [STEMI \] \ [COMFORTABLE \]中生物基质与瞪羚的比较； [NCT00962416] [1]）[1]：https：//clinicaltrials.gov/ct2/show/NCT00962416 结论ESS和OCT衍生的变量不能提高IVUS预测疾病进展的功效。需要进一步研究以调查多模态成像与ESS映射相结合是否将允许更可靠的易损斑块检测。（ST抬高型心肌梗死\ [STEMI \] \ [COMFORTABLE \]中生物基质与瞪羚的比较； [NCT00962416] [1]）[1]：https：//clinicaltrials.gov/ct2/show/NCT00962416 结论ESS和OCT衍生的变量不能提高IVUS预测疾病进展的功效。需要进一步研究以调查多模态成像与ESS映射相结合是否将允许更可靠的易损斑块检测。（ST抬高型心肌梗死\ [STEMI \] \ [COMFORTABLE \]中生物基质与瞪羚的比较； [NCT00962416] [1]）[1]：https：//clinicaltrials.gov/ct2/show/NCT00962416