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

TL;DR

This paper introduces TRAECR, a comprehensive pre-processing tool for PET imaging data, aiding statisticians in data preparation for advanced statistical modeling in clinical research.

Contribution

The paper presents a novel integrated pre-processing and visualization tool, TRAECR, specifically designed for PET imaging data to enhance statistical analysis workflows.

Findings

Facilitates data pre-processing for PET imaging analysis.

Improves data harmonization across different imaging sites.

Supports better statistical modeling of PET data.

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.