Cen Steven, Gebregziabher Mulugeta, Moazami Saeed, Azevedo Christina, Pelletier Daniel
University of Southern California.
Medical University of South Carolina.
Res Sq. 2023 May 2:rs.3.rs-2833532. doi: 10.21203/rs.3.rs-2833532/v1.
Digital Twin (DT) is a novel concept that may bring a paradigm shift for precision medicine. In this study we demonstrate a DT application for estimating the age of onset of disease-specific brain atrophy in individuals with multiple sclerosis (MS) using brain MRI. We first augmented longitudinal data from a well-fitted spline model derived from a large cross-sectional normal aging data. Then we compared different mixed spline models through both simulated and real-life data and identified the mixed spline model with the best fit. Using the appropriate covariate structure selected from 52 different candidate structures, we augmented the thalamic atrophy trajectory over the lifespan for each individual MS patient and a corresponding hypothetical twin with normal aging. Theoretically, the age at which the brain atrophy trajectory of an MS patient deviates from the trajectory of their hypothetical healthy twin can be considered as the onset of progressive brain tissue loss. With a 10-fold cross validation procedure through 1000 bootstrapping samples, we found the onset age of progressive brain tissue loss was, on average, 5-6 years prior to clinical symptom onset. Our novel approach also discovered two clear patterns of patient clusters: earlier onset vs. simultaneous onset of brain atrophy.
数字孪生（DT）是一个可能会给精准医学带来范式转变的新颖概念。在本研究中，我们展示了一种数字孪生应用，即使用脑部磁共振成像（MRI）来估计多发性硬化症（MS）患者特定疾病脑萎缩的发病年龄。我们首先扩充了来自一个从大量横断面正常衰老数据得出的拟合良好的样条模型的纵向数据。然后，我们通过模拟数据和实际数据比较了不同的混合样条模型，并确定了拟合最佳的混合样条模型。利用从52种不同候选结构中选择的合适协变量结构，我们为每位MS患者及其相应的正常衰老的假设孪生个体扩充了整个生命周期内的丘脑萎缩轨迹。从理论上讲，MS患者的脑萎缩轨迹偏离其假设健康孪生个体轨迹的年龄可被视为进行性脑组织损失的发病年龄。通过对1000个自抽样样本进行10折交叉验证程序，我们发现进行性脑组织损失的发病年龄平均比临床症状出现提前5至6年。我们的新方法还发现了两种明显的患者聚类模式：脑萎缩的早发型与同时发型。
