NOMIS
NOMIS quantifies morphometric deviations in the adult human brain by comparing individual MRI-derived FreeSurfer morphometric measures to normative models built from MRI data of 6,909 cognitively healthy individuals aged 18–100.
Key Features:
- Extensive normative dataset: Normative models derived from MRI of 6,909 cognitively healthy individuals aged 18–100.
- FreeSurfer integration: Computes morphometric measures using the FreeSurfer pipeline.
- Scope of measures: Models 1,344 morphometric measures.
- Personal characteristic adjustments: Accounts for age, sex, and intracranial volume (head size) in modeling.
- Image quality adjustments: Accounts for image quality factors including resolution, contrast-to-noise ratio, and surface reconstruction defects.
- Z-score generation: Generates Z-scores that quantify deviation from normative values for each morphometric measure.
- Z-score variants: Provides four versions of Z-score calculations that all account for head size and image quality and optionally include age and/or sex adjustments.
Scientific Applications:
- Multi-site neuromorphometric research: Enables normative comparisons across sites and cohorts in adulthood.
- Aging research: Assesses age-related deviations in brain morphometry using normative reference values.
- Neurodegenerative disease studies: Quantifies morphometric deviations relevant to research on neurodegenerative diseases.
- Cognitive health and population comparisons: Facilitates comparison of brain morphometry across populations and settings to study cognitive health.
Methodology:
Computes morphometric measures with the FreeSurfer pipeline; builds statistical normative models from MRI data of 6,909 cognitively healthy individuals aged 18–100; models 1,344 morphometric measures while adjusting for age, sex, intracranial volume and image quality factors (resolution, contrast-to-noise ratio, surface reconstruction defects); generates per-measure Z-scores and provides four Z-score variants with head size and image quality accounted and optional age/sex adjustments.
Topics
Details
- License:
- BSD-3-Clause
- Tool Type:
- command-line tool
- Programming Languages:
- Python
- Added:
- 3/19/2021
- Last Updated:
- 4/11/2021
Operations
Data Inputs & Outputs
Regression analysis
Publications
Potvin O, Dieumegarde L, Duchesne S. NOMIS: Quantifying morphometric deviations from normality over the lifetime of the adult human brain. Unknown Journal. 2021. doi:10.1101/2021.01.25.428063.