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Updated: Sep 8, 2025
Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Published on: July 28, 2013
Quantitative Analysis of White Matter Hyperintensity: Comparison of Magnetic Resonance Imaging Image Analysis
Ken-Ichi Tabei1, Naoki Saji2, Noriko Ogama3
1School of Industrial Technology, Advanced Institute of Industrial Technology, Tokyo Metropolitan Public University Corporation, Tokyo, Japan; Department of Neurology, Graduate School of Medicine, Mie University, Mie, Japan.
Objective:
White matter hyperintensity (WMH), defined as abnormal signals on magnetic resonance imaging (MRI), is an important clinical indicator of aging and dementia. Although MRI image analysis software can automatically detect WMH, the quantitative accuracy of periventricular hyperintensity (PVH) and deep white matter hyperintensity (DWMH) is unknown.
Materials And Methods:
This study was a sub-analysis of MRI data from an ongoing hospital-based prospective cohort study (the Gimlet study). Between March 2016 and March 2017, we enrolled patients who visited our memory clinic and agreed to undergo medical assessments of cognitive function and fecal examination to study the gut microbiome. Participants with a history of stroke were excluded. WMH was independently quantitatively analyzed using two MRI imaging analysis software modalities: SNIPER and FUSION. Intraclass correlation coefficients and the mean difference in volume were calculated and compared between modalities.
Results:
The data of 87 patients (49 women, mean age 74.8 ± 7.9 years) were analyzed. Both total WMH and DWMH volumes obtained using FUSION were greater (p < 0.001), and PVH volume was smaller (p < 0.001) than those obtained using SNIPER. Intraclass correlation coefficients for the lesion measurements of WMH, PVH, and DWMH between the different software were 0.726 (p < 0.001), 0.673 (p < 0.001), and 0.048 (p = 0.231), respectively.
Conclusions:
There were significant differences in the quantitative data of WMH between the two MRI imaging analysis software modalities. Thus, care should be taken for quantitative assessments of WMH.
Insights
Quantitative analysis of white matter hyperintensity (WMH) using MRI software shows significant differences between modalities. Careful consideration is needed when assessing WMH volumes, particularly for periventricular (PVH) and deep white matter hyperintensity (DWMH).
Area of Science:
- Neuroimaging
- Medical image analysis
- Geriatric medicine
Background:
- White matter hyperintensity (WMH) on MRI is a key indicator of aging and dementia.
- Automated MRI analysis software can detect WMH, but its quantitative accuracy for periventricular (PVH) and deep white matter hyperintensity (DWMH) is not well-established.
Purpose of the Study:
- To compare the quantitative accuracy of two MRI imaging analysis software modalities (SNIPER and FUSION) for WMH, PVH, and DWMH.
- To evaluate the reliability of automated WMH volume measurements between different software.
Main Methods:
- Sub-analysis of MRI data from the Gimlet prospective cohort study.
- Quantitative analysis of WMH, PVH, and DWMH volumes using SNIPER and FUSION software.
- Comparison of volumetric measurements using intraclass correlation coefficients and mean difference analysis.
Main Results:
- Significant differences were observed in total WMH and DWMH volumes between FUSION and SNIPER software (p < 0.001).
- PVH volumes were smaller when measured with FUSION compared to SNIPER (p < 0.001).
- Intraclass correlation coefficients indicated moderate agreement for WMH (0.726) and PVH (0.673), but poor agreement for DWMH (0.048).
Conclusions:
- There are significant quantitative discrepancies in WMH measurements between SNIPER and FUSION MRI analysis software.
- The variability in DWMH measurements suggests caution is needed when interpreting results from different automated analysis tools.
- Clinical assessments relying on quantitative WMH data should carefully consider the software modality used.
