用隐式神经表示提升MRI分辨率，更准分割阿尔茨海默病关键脑区。
Achieving detailed medial temporal lobe segmentation with upsampled isotropic training from implicit neural representation
- 用隐式神经表示融合T1w与T2w图像，生成各向同性高分辨训练数据。
- 在独立测试中，各向同性模型对轻度认知障碍者与正常人区分效果更强（效应量更大）。
- 无需额外标注，就能提升脑区形态测量的稳定性和可靠性，适合追踪阿尔茨海默病进展。
磁共振成像（MRI）生物标志物对阿尔茨海默病（AD）的诊断、监测和治疗至关重要。AD中的神经纤维缠结病理与神经退行性变密切相关，其在大脑中的传播常始于内侧颞叶（MTL）亚区。精确分割MTL亚区有助于提取疾病进展的细粒度生物标志物。通常使用T2加权（T2w）MRI扫描成像MTL，但受限于磁共振物理特性与采集约束，这类图像高度各向异性，难以可靠建模几何结构并提取如皮层厚度等形态学指标。本研究采用隐式神经表示方法，将各向同性的T1w与各向异性的T2w MRI结合，上采样专家标注的MTL亚区图谱，构建多模态、高分辨率的各向同性训练数据集，并用于nnU-Net框架的自动分割。在独立测试集中，基于该各向同性模型提取的形态学指标比基于各向异性数据训练的模型具有更强的效应量，能更好区分轻度认知障碍（MCI）患者与认知正常个体。重测分析显示，该模型提取的形态学指标稳定性更高。本研究证明，无需额外图谱标注，即可显著提升MRI衍生的MTL亚区生物标志物的可靠性，从而更准确量化和追踪AD病理与脑萎缩之间的关系，助力疾病进程监测。
原文摘要 · Abstract (English)
Imaging biomarkers in magnetic resonance imaging (MRI) are important tools for diagnosing, tracking and treating Alzheimer's disease (AD). Neurofibrillary tau pathology in AD is closely linked to neurodegeneration and generally follows a pattern of spread in the brain, with early stages involving subregions of the medial temporal lobe (MTL). Accurate segmentation of MTL subregions is needed to extract granular biomarkers of AD progression. MTL subregions are often imaged using T2-weighted (T2w) MRI scans that are highly anisotropic due to constraints of MRI physics and image acquisition, making it difficult to reliably model MTL subregions geometrically and extract morphological measures, such as thickness. In this study, we used an implicit neural representation method to combine isotropic T1-weighted (T1w) and anisotropic T2w MRI to upsample an atlas set of expert-annotated MTL subregions, establishing a multi-modality, high-resolution training set of isotropic data for automatic segmentation with the nnU-Net framework. In an independent test set, the morphological measures extracted using this isotropic model showed stronger effect sizes than models trained on anisotropic in distinguishing participants with mild cognitive impairment (MCI) and cognitively unimpaired individuals. In test-retest analysis, morphological measures extracted using the isotropic model had greater stability. This study demonstrates improved reliability of MRI-derived MTL subregion biomarkers without additional atlas annotation effort, which may more accurately quantify and track the relationship between AD pathology and brain atrophy for monitoring disease progression.
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