Volume 16, Issue 4 (July & August 2025)
BCN 2025, 16(4): 787-804 |
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Pahlevani V, Eskanadri F, Almasi-Dooghaee M, Hajizadeh E. Structural MRI Biomarkers Related to Cognitive Recovery and Resistance to Recovery Using the Penalized Mixture Cure Model. BCN 2025; 16 (4) :787-804
URL: http://bcn.iums.ac.ir/article-1-3121-en.html
URL: http://bcn.iums.ac.ir/article-1-3121-en.html
1- Department of Biostatistics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran.
2- Department of Statistics, Faculty of Statistics Mathematics and Computer, Allameh Tabataba’i University, Tehran, Iran.
3- Department of Neurology, School of Medicine, Iran University of Medical Sciences, Tehran, Iran.
2- Department of Statistics, Faculty of Statistics Mathematics and Computer, Allameh Tabataba’i University, Tehran, Iran.
3- Department of Neurology, School of Medicine, Iran University of Medical Sciences, Tehran, Iran.
Abstract:
Introduction: Cognitive trajectories in individuals with a baseline clinical dementia rating (CDR) score of 0.5 vary widely, ranging from recovery (stable reverse migration) to resistance to recovery. Identifying predictors of these trajectories is essential for targeted interventions. This study aimed to investigate baseline structural magnetic resonance imaging (MRI) features and clinical factors associated with the rate of recovery and the likelihood of resistance to it, using a penalized mixture cure model (MCM).
Methods: Data from 185 individuals with a baseline CDR of 0.5 in the OASIS-3 database were analyzed. OASIS-3 is a retrospective compilation of data for 1378 participants that were collected across several ongoing projects through the WUSTL Knight ADRC over 30 years. Structural MRI features and clinical measures were assessed using the latency and incidence components of an MCM. The latency component evaluated factors influencing recovery rates, while the incidence component identified predictors of resistance.
Results: The latency component revealed that increasing right rostral middle frontal thickness (hazard ratio [HR]=2.06) was linked to faster recovery, while right frontal pole thickness (HR=0.48) predicted slower recovery. The cure component identified left bankssts volume (odds ratio [OR]=2.21) as a key predictor of resistance, whereas left pars orbitalis thickness (OR=0.56) was protective. Notably, right supramarginal thickness was paradoxically associated with both faster recovery (HR=1.24) and increased resistance (OR=1.48), potentially acting as a proxy for both compensatory mechanisms and maladaptive changes.
Conclusion: The MCM revealed complex, context-dependent roles of structural MRI features in recovery and resistance trajectories, with frontal and temporal regions pivotal to cognitive outcomes. These findings highlight the value of MCM in advancing personalized therapeutic strategies and understanding recovery dynamics.
Methods: Data from 185 individuals with a baseline CDR of 0.5 in the OASIS-3 database were analyzed. OASIS-3 is a retrospective compilation of data for 1378 participants that were collected across several ongoing projects through the WUSTL Knight ADRC over 30 years. Structural MRI features and clinical measures were assessed using the latency and incidence components of an MCM. The latency component evaluated factors influencing recovery rates, while the incidence component identified predictors of resistance.
Results: The latency component revealed that increasing right rostral middle frontal thickness (hazard ratio [HR]=2.06) was linked to faster recovery, while right frontal pole thickness (HR=0.48) predicted slower recovery. The cure component identified left bankssts volume (odds ratio [OR]=2.21) as a key predictor of resistance, whereas left pars orbitalis thickness (OR=0.56) was protective. Notably, right supramarginal thickness was paradoxically associated with both faster recovery (HR=1.24) and increased resistance (OR=1.48), potentially acting as a proxy for both compensatory mechanisms and maladaptive changes.
Conclusion: The MCM revealed complex, context-dependent roles of structural MRI features in recovery and resistance trajectories, with frontal and temporal regions pivotal to cognitive outcomes. These findings highlight the value of MCM in advancing personalized therapeutic strategies and understanding recovery dynamics.
Keywords: Alzheimer disease (AD), Cognitive recovery, Clinical dementia rating (CDR), Penalized mixture cure model (MCM), Structural magnetic resonance imaging (MRI)
Type of Study: Original |
Subject:
Cognitive Neuroscience
Received: 2025/01/20 | Accepted: 2025/04/27 | Published: 2025/07/1
Received: 2025/01/20 | Accepted: 2025/04/27 | Published: 2025/07/1
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