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PIPEMAT-RS: Development and Validation of a Standardized MATLAB Pipeline for Resting-State EEG Preprocessing

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PhiPipe: A multi-modal MRI data processing pipeline with test-retest reliability and predicative validity

Yang Hu^1,2, Qingfeng Li^1,2, Kaini Qiao^1,2

¹Laboratory of Psychological Health and Imaging, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Human Brain Mapping

|December 30, 2022

Summary

PhiPipe is a new multi-modal magnetic resonance imaging (MRI) processing pipeline. It offers reliable and valid brain features for neuroimaging research, outperforming existing single-modality pipelines.

Keywords:

image processing multimodal MRI reliability validity

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Area of Science:

Neuroimaging
Medical Image Analysis
Brain Imaging

Background:

Magnetic resonance imaging (MRI) is crucial for non-invasive in vivo human brain analysis.
Standard MRI data processing involves pipelines, but multi-modal pipelines are scarce.
Assessing the reliability and validity of MRI processing pipelines is critical but often inadequate.

Purpose of the Study:

Introduce PhiPipe, a novel multi-modal MRI processing pipeline.
Evaluate the test-retest reliability and predictive validity of PhiPipe's outputs.
Provide a reliable and valid solution for multi-modal neuroimaging data processing.

Main Methods:

Developed PhiPipe to process T1-weighted, resting-state BOLD, and diffusion-weighted MRI data.
Assessed test-retest reliability using intra-class correlations (ICC) on four public datasets.
Evaluated predictive validity by correlating brain features with chronological age in three datasets.

Main Results:

PhiPipe demonstrated comparable or superior reliability and validity against DPARSF and PANDA.
Results were consistent with prior neuroimaging studies.
Multivariate reliability and predictive validity were also confirmed.

Conclusions:

PhiPipe offers a user-friendly solution for processing multi-modal MRI data.
Reliability and validity assessments aid researchers in experimental design and analysis.
This study establishes a framework for evaluating MRI processing pipeline performance.