(f)MRI Quality Control

- a scalable workflow for BIDS data

• Quality standards        – What is a good and bad image ?

• Quality assessment         – How to measure quality ?
• Quality data acquisition - How to get quality data ?

• Quality impact – How does bad quality influence results?

QC workflow for (f)MRI data

MRI image artifacts

Head motion during MRI acquisition reduces gray matter volume and thickness estimates

Reuter et al. 2015, Neuroimage

N=12

Variations in structural MRI quality significantly impact commonly used measures of brain anatomy

Gilmore et al. 2021, Brain Informatics

Healthy Brain Network N=388; age range 5-21

https://doi.org/10.1162/imag_a_00022

The impact of MRI image quality on
statistical and predictive analysis of voxel
based morphology

Felix Hoffstaedter, Nicolás Nieto, Simon B. Eickhoff, Kaustubh R. Patil

• Quantify impact of quality on univariate statistics and machine learning classification
   

1. Group effects (T-test) of sex on gray matter volume
2. Sex prediction from GM using logistic regression

CAT12 - IQR (Image Quality Rating)

• NCR (Noise Contrast Ratio):
  local standard deviation in the optimized WM segment, scaled by the minimum tissue contrast.

• ICR (Inhomogeneity Contrast Ratio): global standard deviation within the optimized WM segment

• RES (RMS resolution): RMS value of the voxel size

Data

Raw data (N=4125):
AOMIC (N=928)      young adults
eNKI (N=818)       life span
CamCan (N=651)     aging 
SALD (N=494)       life span
1000brains(N=1234) aging

Features

Data

Raw data (N=4125):
AOMIC (N=928)      young adults
eNKI (N=818)       life span
CamCan (N=651)     aging 
SALD (N=494)       life span
1000brains(N=1234) aging

Features

Subsamples low & high quality

balanced for sex & age

T-tests on pooled data

Sex/gender prediction logistic regression

Next steps

• Add new datasets.
  • Add datasets with variable Q: ABIDE, ADNI, ABCD
  • Use retest datasets for within subject effects: CoRR & OASIS3
     
• Replicate effect of quality on analyses approach with EulerNr.
  • Robust analysis targets ?
     
•  Extend to functional MRI data:
  • Identify useful image quality markers for fMRI
  • Task or rest?

QC workflow for (f)MRI data

•  MRIQC - standalone open-source project extracts no-reference IQMs (image quality metrics) from structural (T1w and T2w) and functional MRI data

• CAT12 - Computational Anatomy Toolbox for SPM12 is a powerful suite of tools for morphometric analyses including the estimation of image quality metrics for T1w

QC workflow for (f)MRI data

• BIDS                – Brain Imaging Data Structure
   
• Containers     – Singularity and Docker
   
• Datalad           - Distributed Data Management

BIDS- Brain Imaging Data Structure

Containers - Singularity & Docker

• analysis code
• binary dependencies
• configuration files
• environment variables
• data dependencies

Distributed Data Management

• CLONE DATA
   
• Look at data structure without content present
   
• Automatic download of single files or all data
   
• Easy sharing of data via common platforms

QC workflow for (f)MRI data

MRIQC

MRIQC                   CAT12

Next steps

• Create database of Quality measures
   
• QC your dataset: Let's run QCworkflow together
   
• Share your QC experiences and data
   
•  Extend to functional MRI data:
  • Identify useful image quality markers for fMRI
  • Task or rest?