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Updated: Aug 5, 2026
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Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping
Published on: September 25, 2019
Methodological Choices Strongly Modulate the Sensitivity and Specificity of Lesion-Symptom Mapping Analyses
Margaret Jane Moore1, Chris Rorden2, Gail A Robinson1,3
1Queensland Brain Institute, University of Queensland, St. Lucia, Queensland, Australia.
Human Brain Mapping
|July 30, 2026
Summary
Choosing the right analysis design is crucial for accurate lesion-symptom mapping. Large, diverse samples and specific correction methods significantly improve sensitivity and specificity in stroke survivor studies.
Area of Science:
- Neuroscience
- Neurology
- Medical Imaging
Background:
- Lesion-symptom mapping (LSM) is vital for understanding brain function.
- LSM results are sensitive to methodological choices, impacting reliability.
- Optimal LSM parameters require clarification for consistent, accurate findings.
Purpose of the Study:
- To investigate how different methodological choices in lesion-symptom mapping (LSM) analyses affect accuracy.
- To provide evidence-based recommendations for optimizing LSM study designs.
- To inform researchers on maximizing sensitivity and specificity in brain lesion studies.
Main Methods:
- A large-scale simulation approach using clinical imaging data from 959 stroke survivors.
- Conducted 384,780 LSM analyses with varied sample inclusion criteria, correction factors, and analysis types (univariate vs. multivariate).
- Evaluated analysis accuracy using metrics like target coverage, Dice similarity coefficient, and false positives.
Main Results:
- Analysis accuracy varied significantly based on design; larger, diverse samples improved performance.
- Direct total lesion volume controls outperformed other correction methods.
- False discovery rate corrections maximized target coverage, while permutation corrections yielded better Dice coefficients.
- Univariate analyses showed higher target hit rates and coverage, whereas multivariate analyses had better Dice coefficients.
Conclusions:
- Specific LSM design choices substantially modulate study sensitivity and specificity.
- Recommendations for maximizing accuracy include using large, diverse samples and appropriate statistical corrections (e.g., False Discovery Rate or permutation).
- Understanding the trade-offs between univariate and multivariate approaches is key for interpreting lesion-effect relationships.
