A FastSurfer Database for Age‐Specific Brain Volumes in Healthy Children: A Tool for Quantifying Localized and Global Brain Volume Alterations in Pediatric Patients

TL;DR

This study validates FastSurfer, a fast brain imaging tool, for analyzing brain volumes in children and creates growth charts to track brain development.

Contribution

This is the first validation of FastSurfer for pediatric brain segmentation and the generation of age-specific growth charts for 15 brain regions.

Findings

FastSurfer showed high agreement with FreeSurfer (mean DSC of 0.90, ICC of 0.87).

Growth charts revealed varying brain region growth patterns across ages.

FastSurfer is accurate and fast, making it suitable for clinical use in pediatric populations.

Abstract

MRI‐based whole‐brain manual segmentation methods are considered the gold standard for brain volumetric analysis, but are time‐consuming and prone to human error. Automated segmentation tools like FreeSurfer can identify differences in brain volumes between healthy and non‐healthy individuals. Deep‐learning‐based segmentation tools, such as FastSurfer, offer faster processing times, but further validation is needed, particularly in pediatric cases. This study aims to compare FastSurfer with FreeSurfer in a pediatric cohort and compare the volume estimates with previously published reference values.

A multicenter cohort of 448 subjects aged 4–18 years from three centers was used to compare FastSurfer with FreeSurfer. Validation metrics, including the Dice Similarity Coefficient (DSC), relative volume differences (RVD), and intraclass correlation coefficient (ICC), were computed. Hemispheric asymmetries were assessed by calculating a hemispheric asymmetry index.

The segmentation methods demonstrated high agreement, with a mean DSC across subjects and regions of interest of 0.90 (95% CI: 0.79; 0.95), RVD of 0.3% (95% CI: −7.6%; 7.4%), and ICC of 0.87 (95% CI: 0.52; 0.94). After a visual inspection, which led to the exclusion of 12 subjects with segmentation errors, growth charts for relative volume estimates of 15 anatomical brain regions were generated, revealing varying growth patterns across ages. A potential clinical application is illustrated by plotting a patient's data on these growth charts, showing a specific atrophy pattern.

To our knowledge, this is the first study investigating the use of FastSurfer in volumetric analysis of a pediatric population. Our findings suggest that FastSurfer is a reliable segmentation tool for pediatric data and is particularly promising for clinical practice due to its high accuracy despite rapid processing times. The morphometric data, growth charts, and code are publicly accessible.

This study aims to validate FastSurfer for pediatric brain segmentation against the widely used FreeSurfer. The considered metrics showed high agreement. Age‐specific growth charts for 15 brain regions, revealing varied growth patterns, were also generated

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