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Updated: Jan 5, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
Combining quantitative susceptibility mapping to the morphometric index in differentiating between progressive
Minako Azuma1, Toshinori Hirai1, Takeshi Nakaura2
1Department of Radiology, Faculty of Medicine, University of Miyazaki, Miyazaki, Japan.
Purpose:
To determine whether the susceptibility value in the deep gray matter obtained by quantitative susceptibility mapping (QSM) provides additive value to the morphometric index for differentiating progressive supranuclear palsy (PSP) from Parkinson's disease (PD).
Materials And Methods:
PSP- (n = 8) and PD patients (n = 18) and 18 age-matched healthy controls who underwent QSM and 3D magnetization-prepared rapid gradient echo (MPRAGE) sequences. The mean susceptibility values (MSVs) of the deep gray matter structures on QSM- and areas of the midbrain (morphometric index, MI) on 3D MPRAGE images were measured by two neuroradiologists. Analysis of variance, the Scheffe test and receiver operating characteristic (ROC) analysis were conducted to assess differences and discriminate among PSP, PD and controls by the MSVs and the MI. Using the MSV of a structure with the best area under the curve (AUC) and the MI, we created a decision tree to differentiate between PSP and PD.
Results:
The MSVs of the globus pallidus (GP) and substantia nigra (SN) were significantly higher in PSP than PD and the controls (p < .05). By ROC analysis (PSP vs PD), AUC was greatest (0.903) for the GP. The MI was significantly smaller in PSP than PD and the controls (p < .05); AUC (PSP vs PD) was 0.917. The decision tree using cutoff values of 244 parts per billion for MSV of the GP and 74.0 mm2 for MI served to completely differentiate between PSP and PD.
Conclusion:
The MSV in the GP on QSM images adds value to the MI for differentiating PSP from PD.
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