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This paper introduces TRAECR, a new preprocessing tool designed to prepare positron emission tomography (PET) imaging data for statistical analysis. The tool performs template registration, MRI-PET co-registration, anatomical brain extraction, and data harmonization using COMBAT/RAVEL methods. TRAECR aims to facilitate statistical modeling of PET imaging in clinical applications such as cancer diagnosis, Alzheimer's disease research, and treatment effect evaluation.
Why it matters
This tool addresses a critical need in medical imaging research by standardizing the complex preprocessing steps required before statistical analysis of PET scans. It could accelerate research into disease-modifying treatments for Alzheimer's disease and improve the consistency and reproducibility of PET imaging studies across different research groups and clinical settings.
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arXiv:2511.04458v2 Announce Type: replace
Abstract: Positron emission tomography (PET) imaging is widely used in a number of clinical applications, including cancer and Alzheimer’s disease (AD) diagnosis, monitoring of disease development, and treatment effect evaluation. Statistical modeling of PET imaging is essential to address continually emerging scientific questions in these research fields, including hypotheses related to evaluation of effects of disease modifying treatments on amyloid reduction in AD and associations between amyloid reduction and cognitive function, among many others. In this paper, we provide background information and tools for statisticians interested in developing statistical models for PET imaging to pre-process and prepare data for analysis. We introduce our novel pre-processing and visualization tool TRAECR (Template registration, MRI-PET co-Registration, Anatomical brain Extraction and COMBAT/RAVEL harmonization) to facilitate data preparation for statistical analysis.
Source: TRAECR: A Tool for Preprocessing Positron Emission Tomography Imaging for Statistical Modeling