Department of Biostatistics, Brown University, Providence, RI 02903, USA.
Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA.
Biostatistics. 2022 Jan 13;23(1):83-100. doi: 10.1093/biostatistics/kxaa016.
Our main goal is to study and quantify the evolution of multiple sclerosis lesions observed longitudinally over many years in multi-sequence structural magnetic resonance imaging (sMRI). To achieve that, we propose a class of functional models for capturing the temporal dynamics and spatial distribution of the voxel-specific intensity trajectories in all sMRI sequences. To accommodate the hierarchical data structure (observations nested within voxels, which are nested within lesions, which, in turn, are nested within study participants), we use structured functional principal component analysis. We propose and evaluate the finite sample properties of hypothesis tests of therapeutic intervention effects on lesion evolution while accounting for the multilevel structure of the data. Using this novel testing strategy, we found statistically significant differences in lesion evolution between treatment groups.
我们的主要目标是研究和量化在多年的多序列结构磁共振成像（sMRI）中观察到的多发性硬化病变的演变。为此，我们提出了一类功能模型，用于捕捉所有 sMRI 序列中体素特定强度轨迹的时间动态和空间分布。为了适应分层数据结构（观察值嵌套在体素内，体素嵌套在病变内，病变又嵌套在研究参与者内），我们使用结构功能主成分分析。我们提出并评估了在考虑数据多层次结构的情况下，治疗干预对病变演变影响的假设检验的有限样本性质。使用这种新的测试策略，我们发现治疗组之间的病变演变存在统计学上的显著差异。
