Romano Michael F, Zhou Xiao, Balachandra Akshara R, Jadick Michalina F, Qiu Shangran, Nijhawan Diya A, Joshi Prajakta S, Mohammad Shariq, Lee Peter H, Smith Maximilian J, Paul Aaron B, Mian Asim Z, Small Juan E, Chin Sang P, Au Rhoda, Kolachalama Vijaya B
Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA.
Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA.
iScience. 2023 Aug 2;26(9):107522. doi: 10.1016/j.isci.2023.107522. eCollection 2023 Sep 15.
Quantifying the risk of progression to Alzheimer's disease (AD) could help identify persons who could benefit from early interventions. We used data from the Alzheimer's Disease Neuroimaging Initiative (ADNI, n = 544, discovery cohort) and the National Alzheimer's Coordinating Center (NACC, n = 508, validation cohort), subdividing individuals with mild cognitive impairment (MCI) into risk groups based on cerebrospinal fluid amyloid-β levels and identifying differential gray matter patterns. We then created models that fused neural networks with survival analysis, trained using non-parcellated T1-weighted brain MRIs from ADNI data, to predict the trajectories of MCI to AD conversion within the NACC cohort (integrated Brier score: 0.192 [discovery], and 0.108 [validation]). Using modern interpretability techniques, we verified that regions important for model prediction are classically associated with AD. We confirmed AD diagnosis labels using postmortem data. We conclude that our framework provides a strategy for risk-based stratification of individuals with MCI and for identifying regions key for disease prognosis.
量化发展为阿尔茨海默病（AD）的风险有助于识别可能从早期干预中获益的人群。我们使用了来自阿尔茨海默病神经影像倡议（ADNI，n = 544，发现队列）和国家阿尔茨海默病协调中心（NACC，n = 508，验证队列）的数据，根据脑脊液淀粉样β水平将轻度认知障碍（MCI）个体细分为风险组，并识别不同的灰质模式。然后，我们创建了将神经网络与生存分析相结合的模型，使用来自ADNI数据的未分割T1加权脑MRI进行训练，以预测NACC队列中MCI向AD转化的轨迹（综合Brier评分：0.192[发现队列]和0.108[验证队列]）。使用现代可解释性技术，我们验证了对模型预测重要的区域与AD经典相关。我们使用尸检数据确认了AD诊断标签。我们得出结论，我们的框架为基于风险的MCI个体分层以及识别疾病预后的关键区域提供了一种策略。
