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Odense-Oxford PET Image Analysis (OPETIA): An FSL-based toolbox for multimodal neuroimaging
Mohammadtaha Parsayan1, Sasan Andalib1, Thomas Lund Andersen2
1Research Unit of Neurology, Department of Clinical Research, Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark; Department of Neurology, Odense University Hospital, Odense, Denmark.
Neuroimage
|May 19, 2025
Summary
A new toolbox, Odense-Oxford PET Image Analysis (OPETIA), offers user-friendly, quantitative analysis for multimodal neuroimaging. It shows high reproducibility and improved detection of Alzheimer's disease group differences compared to existing tools.
Area of Science:
- Neuroimaging
- Medical Image Analysis
- Quantitative Analysis
Background:
- Advanced analysis of MRI and PET images is crucial for brain structure and function assessment, aiding diagnosis and treatment.
- Current clinical software often lacks accurate quantification capabilities for multimodal neuroimaging data.
- The Functional Magnetic Resonance Imaging of the Brain Software Library (FSL) is powerful for MRI but underutilized for PET analysis.
Purpose of the Study:
- To develop a user-friendly, multimodal neuroimage analysis toolbox named Odense-Oxford PET Image Analysis (OPETIA).
- To enable automatic preprocessing of MRI and PET images and calculation of SUV and SUVR metrics.
- To assess OPETIA's efficacy and compare its performance against established tools like SPM12 for Alzheimer's disease research.
Main Methods:
- Developed OPETIA using FSL and Python, featuring a graphical user interface for automated analysis.
- Processed static 18F-fluorodeoxyglucose (FDG) PET and MRI data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset.
- Compared OPETIA's Standardized Uptake Value Ratio (SUVR) measurements with Statistical Parametric Mapping (SPM12), assessing reproducibility and group difference detection.
Main Results:
- OPETIA demonstrated a close association with SPM12 results (r > 0.8, p < 0.01) but yielded significantly larger SUVR values.
- Both tools exhibited high reproducibility (Cronbach's Alpha > 0.9).
- OPETIA detected significantly larger effect sizes (Cohen's d = 0.22) for Alzheimer's disease group differences compared to SPM12 (d = 0.04).
Conclusions:
- OPETIA is a user-friendly and robust tool for quantitative analysis of multimodal neuroimaging.
- Its enhanced sensitivity in detecting group differences suggests potential for improved clinical applications in neurodegenerative diseases.
- The systematic difference in SUVR measurements warrants further investigation for precise clinical interpretation.
