Keywords

MRI scans, volumetric analyses, T1-weighted images, registration-based pipelines

Abstract

Pre-processing MRI scans prior to performing volumetric analyses is common practice in MRI studies. As pre-processing steps adjust the voxel intensities, the space in which the scan exists, and the amount of data in the scan, it is possible that the steps have an effect on the volumetric output. To date, studies have compared between and not within pipelines, and so the impact of each step is unknown. This study aims to quantify the effects of preprocessing steps on volumetric measures in T1-weighted scans within a single pipeline. It was our hypothesis that pre-processing steps would significantly impact ROI volume estimations. One hundred fifteen participants from the OASIS dataset were used, where each participant contributed three scans. All scans were then pre-processed using a step-wise pipeline. Bilateral hippocampus, putamen, and middle temporal gyrus volume estimations were assessed following each successive step, and all data were processed by the same pipeline 5 times. Repeated-measures analyses tested for a main effects of pipeline step, scan-rescan (for MRI scanner consistency) and repeated pipeline runs (for algorithmic consistency). A main effect of pipeline step was detected, and interestingly an interaction between pipeline step and ROI exists. No effect for either scan-rescan or repeated pipeline run was detected. We then supply a correction for noise in the data resulting from preprocessing.

Original Publication Citation

Muncy NM, Hedges-Muncy AM, Kirwan CB (2017) Discrete pre-processing step effects in registration-based pipelines, a preliminary volumetric study on T1-weighted images. PLoS ONE 12(10): e0186071. https://doi.org/10.1371/ journal.pone.0186071

Document Type

Peer-Reviewed Article

Publication Date

2017-10-12

Publisher

PLOS ONE

Language

English

College

Family, Home, and Social Sciences

Department

Psychology

University Standing at Time of Publication

Full Professor

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Psychology Commons

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