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Updated: Aug 29, 2025
Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images
Published on: January 7, 2019
Segmentation and volume quantification of MR Images for the detection and monitoring multiple sclerosis progression
Abstract:
Multiple Sclerosis (MS) lesions detection and disease's progression monitoring at the same time, play an important role. The purpose of this research is to demonstrate a method for detecting MS plaques and volume estimation from MR Images for monitoring the progression of the disease and the brain atrophy caused. In the proposed research, a clustering-based method is utilized in order to delineate MS plaques in brain, based on anatomical information, brain geometry and lesion features. In addition to volumetric information concerning lesions and whole brain volume, volume quantification is employed to estimate MS atrophy by measuring Brain Parenchymal Fraction (BPF). In the present study, Fluid Attenuated Inversion Recovery (FLAIR) images were utilized for the detection of MS lesions and BPF evaluation, while Tl-weighted MR Images utilized in volume estimation. 30 MS patients were included in a dataset consisted of 3D FLAIR and T1-weighted MR images in order to evaluate the proposed technique. MRI scans performed in two different clinical visits, a baseline and a visit after 6 months. The results extracted in segmentation of MS lesions in terms of sensitivity is 73.80 %. The BPF at baseline estimated to 0.82 ± 0.01, and at 1stfollow up, 0.83 ± 0.01. Finally, the brain volume loss between baseline and after 6 months is 0.4%.
Insights
This study introduces a new method for detecting Multiple Sclerosis (MS) lesions and estimating brain atrophy using MRI scans. The technique aids in monitoring disease progression and brain volume loss over time.
Area of Science:
- Medical Imaging
- Neurology
- Radiology
Background:
- Multiple Sclerosis (MS) lesion detection and disease progression monitoring are crucial for patient management.
- Accurate assessment of brain atrophy is essential for understanding MS progression.
Purpose of the Study:
- To present a novel method for detecting MS plaques and estimating brain volume from MR images.
- To enable simultaneous monitoring of MS disease progression and associated brain atrophy.
Main Methods:
- A clustering-based approach was used to delineate MS plaques using anatomical, geometrical, and lesion features.
- Brain Parenchymal Fraction (BPF) was calculated to quantify MS-related atrophy.
- 3D FLAIR and T1-weighted MR images from 30 MS patients across two visits (baseline and 6-month follow-up) were utilized.
Main Results:
- The proposed technique achieved a sensitivity of 73.80% in segmenting MS lesions.
- Mean BPF at baseline was 0.82 ± 0.01, increasing slightly to 0.83 ± 0.01 at follow-up.
- A minimal brain volume loss of 0.4% was observed between baseline and the 6-month follow-up.
Conclusions:
- The developed method effectively detects MS lesions and quantifies brain atrophy.
- This approach offers a valuable tool for monitoring MS progression and brain volume changes over time.
