Tzirakis Konstantinos, Kamarianakis Yiannis, Metaxa Eleni, Kontopodis Nikolaos, Ioannou Christos V, Papaharilaou Yannis
Institute of Applied and Computational Mathematics, Foundation for Research and Technology, 100 Nikolaou Plastira str, Vassilika Vouton, 700 13, Heraklion, Crete, Greece.
School of Mathematical and Statistical Sciences, Arizona State University, Tempe, AZ, USA.
Med Biol Eng Comput. 2017 Aug;55(8):1493-1506. doi: 10.1007/s11517-016-1610-x. Epub 2017 Jan 2.
Longitudinal studies of vascular diseases often need to establish correspondence between follow-up images, as the diseased regions may change shape over time. In addition, spatial data structures should be taken into account in the statistical analyses to avoid inferential errors. This study investigates the association between hemodynamics and thrombus growth in abdominal aortic aneurysms (AAAs) while emphasizing on the abovementioned methodological issues. Six AAA surfaces and their follow-ups were three-dimensionally reconstructed from computed-tomography images. AAA surfaces were mapped onto a rectangular grid which allowed identification of corresponding regions between follow-ups. Local thrombus thickness was measured at initial and follow-up surfaces and computational fluid dynamic simulations provided time-average wall shear stress (TAWSS), oscillatory shear index (OSI), and relative residence time. Six Bayesian regression models, which account for spatially correlated measurements, were employed to explore associations between hemodynamics and thrombus growth. Results suggest that spatial regression models based on TAWSS and OSI offer superior predictive performance for thrombus growth relative to alternative specifications. Ignoring the spatial data structure may lead to improper assessment with regard to predictor significance.
血管疾病的纵向研究通常需要在随访图像之间建立对应关系，因为病变区域的形状可能会随时间变化。此外，在统计分析中应考虑空间数据结构，以避免推理错误。本研究调查腹主动脉瘤（AAA）中血流动力学与血栓生长之间的关联，同时强调上述方法学问题。从计算机断层扫描图像中三维重建了六个AAA表面及其随访情况。将AAA表面映射到矩形网格上，这使得能够识别随访之间的对应区域。在初始表面和随访表面测量局部血栓厚度，并通过计算流体动力学模拟提供时间平均壁面切应力（TAWSS）、振荡切变指数（OSI）和相对停留时间。采用六个考虑空间相关测量的贝叶斯回归模型来探索血流动力学与血栓生长之间的关联。结果表明，相对于其他规格，基于TAWSS和OSI的空间回归模型对血栓生长具有更好的预测性能。忽略空间数据结构可能会导致对预测变量显著性的评估不当。
