基于 FLAIR MRI 的局部纹理生物标志物对阿尔茨海默病和血管性疾病的分类。
Alzheimer's and vascular disease classification using regional texture biomarkers in FLAIR MRI.
机构信息
Electrical, Computer and Biomedical Engineering Department, Toronto Metropolitan University, 350 Victoria St., Toronto, ON M5B 2K3, Canada; Institute for Biomedical Engineering, Science Tech (iBEST), A Partnership Between St. Michael's Hospital and Toronto Metropolitan University, 209 Victoria St., Toronto, ON M5B 1T8, Canada.
Institute of Medical Science, University of Toronto, 1 King's College Circle, Toronto, ON M5S 1A8, Canada; Keenan Research Center for Biomedical Science, St. Michael's Hospital, Unity Health Network, 30 Bond St., Toronto, ON M5B 1W8, Canada; Department of Psychiatry, Faculty of Medicine, University of Toronto, 250 College Street, Toronto, ON M5T 1R8, Canada.
出版信息
Neuroimage Clin. 2023;38:103385. doi: 10.1016/j.nicl.2023.103385. Epub 2023 Mar 24.
Interactions between subcortical vascular disease and dementia due to Alzheimer's disease (AD) are unclear, and clinical overlap between the diseases makes diagnosis challenging. Existing studies have shown regional microstructural changes specific to each disease, and that textures in fluid-attenuated inversion recovery (FLAIR) MRI images may characterize abnormalities in tissue microstructure. This work aims to investigate regional FLAIR biomarkers that can differentiate dementia cohorts with and without subcortical vascular disease. FLAIR and diffusion MRI (dMRI) volumes were obtained in 65 mild cognitive impairment (MCI), 21 AD, 44 subcortical vascular MCI (scVMCI), 22 Mixed etiology, and 48 healthy elderly patients. FLAIR texture and intensity biomarkers were extracted from the normal appearing brain matter (NABM), WML penumbra, blood supply territory (BST), and white matter tract regions of each patient. All FLAIR biomarkers were correlated to dMRI metrics in each region and global WML load, and biomarker means between groups were compared using ANOVA. Binary classifications were performed using Random Forest classifiers to investigate the predictive nature of the regional biomarkers, and SHAP feature analysis was performed to further investigate optimal regions of interest for differentiating disease groups. The regional FLAIR biomarkers were strongly correlated to MD, while all biomarker regions but white matter tracts were strongly correlated to WML burden. Classification between Mixed disease and healthy, AD, and scVMCI patients yielded accuracies of 97%, 81%, and 72% respectively using WM tract biomarkers. Classification between scVMCI and healthy, MCI, and AD patients yielded accuracies of 89%, 84%, and 79% respectively using penumbra biomarkers. Only the classification between AD and healthy patients had optimal results using NABM biomarkers. This work presents novel regional FLAIR biomarkers that may quantify white matter degeneration related to subcortical vascular disease, and which indicate that investigating degeneration in specific regions may be more important than assessing global WML burden in vascular disease groups.
皮质下血管病与阿尔茨海默病（AD）所致痴呆之间的相互作用尚不清楚，且两种疾病的临床表现存在重叠，这使得诊断具有挑战性。现有研究表明，每种疾病都有特定的局部微观结构变化，且液体衰减反转恢复（FLAIR）磁共振成像（MRI）图像的纹理特征可能可以描述组织微观结构的异常。本研究旨在探讨可区分皮质下血管性痴呆与非皮质下血管性痴呆患者的局部 FLAIR 生物标志物。对 65 例轻度认知障碍（MCI）、21 例 AD、44 例皮质下血管性 MCI（scVMCI）、22 例混合病因和 48 例健康老年人患者进行了 FLAIR 和弥散 MRI（dMRI）容积测量。从每位患者的正常脑实质（NABM）、WM 半影区、血供区（BST）和白质束区提取 FLAIR 纹理和强度生物标志物。将所有 FLAIR 生物标志物与各区域和全脑白质病变（WML）负荷的 dMRI 指标相关联，并使用方差分析比较组间生物标志物均值。使用随机森林分类器进行二分类，以研究局部生物标志物的预测性质，并进行 SHAP 特征分析，以进一步研究区分疾病组的最佳感兴趣区域。局部 FLAIR 生物标志物与 MD 呈强相关，而所有生物标志物区域（除白质束外）与 WML 负荷均呈强相关。使用白质束生物标志物，混合性疾病与健康、AD 和 scVMCI 患者之间的分类准确率分别为 97%、81%和 72%。使用半影区生物标志物，scVMCI 与健康、MCI 和 AD 患者之间的分类准确率分别为 89%、84%和 79%。仅使用 NABM 生物标志物，AD 与健康患者之间的分类结果最佳。本研究提出了新的局部 FLAIR 生物标志物，这些标志物可能可以量化与皮质下血管疾病相关的白质变性，并表明在血管性疾病组中，研究特定区域的变性可能比评估全脑 WML 负荷更为重要。
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