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Published on: September 12, 2011
On the Influence of Confounding Factors in Multisite Brain Morphometry Studies of Developmental Pathologies:
Abstract:
Pooling data acquired on different MR scanners is a commonly used practice to increase the statistical power of studies based on MRI-derived measurements. Such studies are very appealing since they should make it possible to detect more subtle effects related to pathologies. However, the influence of confounds introduced by scanner-related variations remains unclear. When studying brain morphometry descriptors, it is crucial to investigate whether scanner-induced errors can exceed the effect of the disease itself. More specifically, in the context of developmental pathologies such as autism spectrum disorders (ASD), it is essential to evaluate the influence of the scanner on age-related effects. In this paper, we studied a dataset composed of 159 anatomical MR images pooled from three different scanners, including 75 ASD patients and 84 healthy controls. We quantitatively assessed the effects of the age, pathology, and scanner factors on cortical thickness measurements. Our results indicate that scan pooling from different sites would be less fruitful in some cortical regions than in others. Although the effect of age is consistent across scanners, the interaction between the age and scanner factors is important and significant in some specific cortical areas.
Insights
Pooling MRI data from different scanners can increase study power but introduces confounds. Scanner variations significantly impact autism spectrum disorder (ASD) brain morphometry, especially age-related effects in specific cortical regions.
Area of Science:
- Neuroimaging
- Developmental Neuroscience
- Biostatistics
Background:
- Pooling data from multiple Magnetic Resonance Imaging (MRI) scanners enhances statistical power for detecting subtle pathological effects.
- Scanner-induced variations can confound MRI-derived measurements, potentially obscuring or mimicking disease-related findings.
- Understanding scanner effects is crucial for neuroimaging studies, particularly in developmental disorders like autism spectrum disorder (ASD).
Purpose of the Study:
- To quantitatively assess the impact of age, pathology (ASD), and scanner origin on cortical thickness measurements.
- To determine if scanner-related variations influence age-related effects in brain morphometry within the context of ASD.
- To evaluate the feasibility and limitations of pooling MRI data from different scanners for developmental neuroimaging research.
Main Methods:
- Utilized a dataset of 159 anatomical MRI scans from 75 individuals with ASD and 84 healthy controls, acquired across three different scanners.
- Performed quantitative analysis to assess the main effects and interactions of age, pathology, and scanner on cortical thickness.
- Employed statistical modeling to dissect the contributions of each factor to observed variations in brain morphometry.
Main Results:
- Scanner-specific variations were found to impact cortical thickness measurements, with varying degrees of influence across different brain regions.
- The effect of age on cortical thickness was generally consistent across scanners.
- A significant interaction between age and scanner factors was identified in specific cortical areas, indicating that scanner variability can modulate age-related changes.
Conclusions:
- Pooling MRI data from multiple scanners can be beneficial but requires careful consideration of scanner-specific confounds, especially in developmental studies.
- Scanner variability can significantly interact with age-related effects in cortical thickness, particularly in certain brain regions.
- The findings highlight the need for harmonizing MRI data or accounting for scanner effects to ensure the reliability of neuroimaging research in autism spectrum disorder and other developmental conditions.
