Regional Cerebral Atrophy Contributes to Personalized Survival Prediction in Amyotrophic Lateral Sclerosis: A Multicentre, Machine Learning, Deformation-Based Morphometry Study

IF 7.7 1区医学 Q1 CLINICAL NEUROLOGY Annals of Neurology Pub Date : 2025-02-22 DOI:10.1002/ana.27196

Isabelle Lajoie, Canadian ALS Neuroimaging Consortium (CALSNIC), Sanjay Kalra, Mahsa Dadar

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Abstract

Objective

Accurate personalized survival prediction in amyotrophic lateral sclerosis is essential for effective patient care planning. This study investigates whether grey and white matter changes measured by magnetic resonance imaging can improve individual survival predictions.

Methods

We analyzed data from 178 patients with amyotrophic lateral sclerosis and 166 healthy controls in the Canadian Amyotrophic Lateral Sclerosis Neuroimaging Consortium study. A voxel-wise linear mixed-effects model assessed disease-related and survival-related atrophy detected through deformation-based morphometry, controlling for age, sex, and scanner variations. Additional linear mixed-effects models explored associations between regional imaging and clinical measurements, and their associations with time to the composite outcome of death, tracheostomy, or permanent assisted ventilation. We evaluated whether incorporating imaging features alongside clinical data could improve the performance of an individual survival distribution model.

Results

Deformation-based morphometry uncovered distinct voxel-wise atrophy patterns linked to disease progression and survival, with many of these regional atrophies significantly associated with clinical manifestations of the disease. By integrating regional imaging features with clinical data, we observed a substantial enhancement in the performance of survival models across key metrics. Our analysis identified specific brain regions, such as the corpus callosum, rostral middle frontal gyrus, and thalamus, where atrophy predicted an increased risk of mortality.

Interpretation

This study suggests that brain atrophy patterns measured by deformation-based morphometry provide valuable insights beyond clinical assessments for prognosis. It offers a more comprehensive approach to prognosis and highlights brain regions involved in disease progression and survival, potentially leading to a better understanding of amyotrophic lateral sclerosis. ANN NEUROL 2025;97:1144–1157

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区域性脑萎缩有助于肌萎缩侧索硬化症的个性化生存预测：一项多中心、机器学习、基于变形的形态测量学研究。

目的：对肌萎缩侧索硬化症患者进行准确的个性化生存预测是制定有效的患者护理计划的必要条件。这项研究调查了磁共振成像测量的灰质和白质变化是否可以提高个体生存预测。方法：我们分析了加拿大肌萎缩性侧索硬化症神经影像学联盟研究中178例肌萎缩性侧索硬化症患者和166名健康对照者的数据。体素线性混合效应模型评估了通过基于变形的形态测量检测到的与疾病相关和与生存相关的萎缩，控制了年龄、性别和扫描仪的变化。其他线性混合效应模型探讨了区域成像和临床测量之间的关系，以及它们与死亡、气管切开术或永久辅助通气等复合结果的时间关系。我们评估了将影像学特征与临床数据结合是否可以改善个体生存分布模型的性能。结果：基于变形的形态测量揭示了与疾病进展和生存相关的不同体素萎缩模式，其中许多区域萎缩与疾病的临床表现显著相关。通过将区域成像特征与临床数据相结合，我们观察到生存模型在关键指标上的表现有了实质性的提高。我们的分析确定了特定的大脑区域，如胼胝体、吻侧额中回和丘脑，在这些区域萎缩预示着死亡风险的增加。解释：这项研究表明，通过基于变形的形态测量法测量脑萎缩模式，为临床预后评估提供了有价值的见解。它提供了一种更全面的预后方法，并突出了与疾病进展和生存有关的大脑区域，可能有助于更好地了解肌萎缩性侧索硬化症。Ann neurol 2025。

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来源期刊

Annals of Neurology 医学-临床神经学

CiteScore

18.00

自引率

1.80%

发文量

270

审稿时长

3-8 weeks

期刊介绍： Annals of Neurology publishes original articles with potential for high impact in understanding the pathogenesis, clinical and laboratory features, diagnosis, treatment, outcomes and science underlying diseases of the human nervous system. Articles should ideally be of broad interest to the academic neurological community rather than solely to subspecialists in a particular field. Studies involving experimental model system, including those in cell and organ cultures and animals, of direct translational relevance to the understanding of neurological disease are also encouraged.