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Independent component analysis: a reliable alternative to general linear model for task-based fMRI.

Kostakis Gkiatis1,2, Kyriakos Garganis2, Irene Karanasiou1,3

  • 1School of Electrical and Computer Engineering, National Technical University of Athens, Athens, Greece.

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|September 4, 2023
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Summary

Independent Component Analysis (ICA) shows improved performance over the General Linear Model (GLM) for analyzing functional magnetic resonance imaging (fMRI) in neurosurgical patients. Integrating both methods enhances reliable results for presurgical language mapping.

Keywords:
GLMICAbrain mappingepilepsyfMRIlanguage mappingneuroimagingpresurgical evaluation

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Area of Science:

  • Neuroimaging
  • Medical Statistics
  • Brain Surgery

Background:

  • Functional magnetic resonance imaging (fMRI) is crucial for presurgical planning.
  • Traditional statistical analysis in fMRI, like the General Linear Model (GLM), has seen limited advancements.
  • Independent Component Analysis (ICA) offers a potential alternative for fMRI statistical analysis.

Purpose of the Study:

  • To evaluate the efficacy of Independent Component Analysis (ICA) in separating language task activation in fMRI.
  • To compare the performance of ICA against the General Linear Model (GLM) in presurgical fMRI analysis.
  • To assess the utility of ICA and GLM in patients with brain lesions undergoing neurosurgery.

Main Methods:

  • Sixty neurosurgical patients and 20 controls underwent fMRI language mapping.
  • Patients were categorized into groups based on lesion characteristics (static vs. progressive).
  • fMRI statistical maps generated by ICA and GLM were evaluated by experts.

Main Results:

  • ICA and GLM showed similar performance in control subjects.
  • ICA demonstrated statistically superior performance compared to GLM in patients with both static and progressive lesions (p < 0.01801 and p < 0.0237, respectively).
  • Combining ICA and GLM yielded reliable results in 240 out of 259 scans, increasing task-based fMRI sensitivity.

Conclusions:

  • ICA offers advantages over GLM in fMRI analysis for patients with brain lesions, irrespective of symptom chronicity.
  • GLM may be more susceptible to artifacts caused by lesions or patient motion.
  • ICA provides reliable fMRI results suitable for surgical planning, considering patient-specific factors.