Related Experiment Video
Updated: Jan 24, 2026

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images
Published on: January 7, 2019
T1- and diffusion tensor-based fractal dimension of white and grey matter in multiple sclerosis
Weronika Mazur-Rosmus1, Zofia Schneider1, Agnieszka Słowik2
1LaTiS NMR Tomography and Spectroscopy Laboratory, Department of Fossil Fuels, Faculty of Geology, Geophysics and Environmental Protection, AGH University of Krakow, Krakow, Poland.
Introduction:
Multiple sclerosis (MS) changes brain microstructure even at early disease stages, with changes detectable in normal-appearing white matter (NAWM) and grey matter (GM). Diffusion tensor imaging (DTI) is sensitive to such alterations, while fractal dimension (FD) provides complementary information on tissue complexity. We hypothesized that T1-based FD offers additional diagnostic value beyond DTI-derived metrics of tissue integrity, including fractional anisotropy (FA) and mean diffusivity (MD).
Methods:
MRI data were acquired from 120 patients with relapsing-remitting MS and low mean Expanded Disability Status Scale (EDSS) scores, as well as 75 healthy control (HC) participants. FD, FA, and MD were quantified in global brain tissues and within white matter (WM) skeletons, both with and without lesion masking. The interactions between FD and DTI metrics were assessed, and classification models were constructed to evaluate diagnostic performance.
Results:
WM in MS exhibited reduced FD and FA alongside elevated MD, consistent with demyelination and axonal degradation. GM demonstrated higher FD, FA, and MD values, suggesting a more nuanced interplay of inflammatory remodeling, dendritic reorganization and compensatory structural adaptation. The limited impact of lesion masking on group-average metrics, but its marked effect on FD-DTI interactions, revealed that lesions regulate structural variance without dominating global tissue complexity. FD proved particularly sensitive at tissue interfaces, where geometry is disrupted, whereas WM skeleton analyses reflected preserved regularity of core tracts, even amid microstructural degeneration.
Discussion:
Our findings support the concept of a surface-in gradient of complexity loss in MS. Combining FD with FA and MD substantially improved classification accuracy, particularly in WM skeleton-based models, emphasizing the diagnostic potential of geometric-microstructural integration. Widespread associations of FA with clinical covariates and age further suggest that diffuse WM alterations underpin both cognitive and clinical decline.
Insights
Fractal dimension (FD) combined with diffusion tensor imaging (DTI) metrics like fractional anisotropy (FA) and mean diffusivity (MD) significantly enhances the diagnosis of multiple sclerosis (MS) brain changes. This geometric-microstructural integration offers improved accuracy in detecting early disease alterations.
Area of Science:
- Neuroimaging
- Biomedical Engineering
- Radiology
Background:
- Multiple sclerosis (MS) causes early brain microstructure changes in normal-appearing white matter (NAWM) and grey matter (GM).
- Diffusion tensor imaging (DTI) detects microstructural alterations, while fractal dimension (FD) quantifies tissue complexity.
- Existing DTI metrics like fractional anisotropy (FA) and mean diffusivity (MD) assess tissue integrity.
Purpose of the Study:
- To investigate if T1-based FD provides additional diagnostic value beyond DTI metrics in MS.
- To evaluate the diagnostic performance of combining FD with FA and MD for MS detection.
Main Methods:
- MRI data from 120 relapsing-remitting MS patients and 75 healthy controls (HC) were analyzed.
- Quantified FD, FA, and MD in global brain tissues and white matter (WM) skeletons, with and without lesion masking.
- Constructed classification models to assess diagnostic performance of integrated metrics.
Main Results:
- MS white matter showed reduced FD and FA, with elevated MD, indicating demyelination and axonal damage.
- Grey matter exhibited higher FD, FA, and MD, suggesting complex remodeling and adaptation.
- Combining FD with FA and MD substantially improved classification accuracy, especially in WM skeleton analyses.
Conclusions:
- T1-based FD offers complementary diagnostic information to DTI metrics in MS.
- Geometric-microstructural integration of FD, FA, and MD shows significant diagnostic potential for MS.
- Diffuse white matter alterations, detectable via these metrics, correlate with clinical decline.
Related Concept Videos
Collisions in Multiple Dimensions: Introduction
Collisions in Multiple Dimensions: Problem Solving
A small car of mass 1,200 kg traveling east at 60 km/h collides at an intersection with a truck of mass 3,000 kg traveling due north at 40 km/h. The two vehicles are locked together. What is the...
Diffusion
Inertia Tensor
The diagonal components of the inertia tensor matrix represent the moments of inertia concerning the principal axes of the object. These primary axes are defined as the axes where the object experiences the least...
The Atomic Theory of Matter
Classifying Matter by State

