TRAECR: A Tool for Preprocessing Positron Emission Tomography Imaging for Statistical Modeling

Area of Science:

• Neuroimaging
• Statistical Modeling
• Medical Diagnostics

Background:

• Positron emission tomography (PET) is crucial for diagnosing and monitoring diseases like Alzheimer's disease (AD) and cancer.
• Statistical modeling of PET data is vital for advancing research, particularly in evaluating treatments and understanding disease mechanisms.
• Preparing PET imaging data for analysis is a complex but necessary step for robust statistical modeling.

Purpose of the Study:

• To provide statisticians with background information and tools for developing statistical models for PET imaging.
• To introduce a novel tool, TRAECR, for pre-processing and visualizing PET imaging data.
• To facilitate the preparation of PET data for statistical analysis in research settings.

Main Methods:

• Development of the TRAECR (Template registration, MRI-PET co-Registration, Anatomical brain Extraction and COMBAT/RAVEL harmonization) tool.
• Implementation of pre-processing steps including template registration and MRI-PET co-registration.
• Application of anatomical brain extraction and harmonization techniques (COMBAT/RAVEL).

Main Results:

• TRAECR provides a streamlined workflow for PET data pre-processing.
• The tool facilitates essential steps for preparing imaging data for statistical analysis.
• Enhanced data preparation enables more accurate statistical modeling of PET imaging.

Conclusions:

• TRAECR is a valuable tool for statisticians working with PET imaging data.
• Effective pre-processing of PET data is critical for advancing research in areas like Alzheimer's disease.
• This tool supports the development of advanced statistical models for neuroimaging research.