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Updated: Aug 24, 2026
Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
Published on: November 8, 2012
Segmental disturbance of white matter microstructure in predicting mild cognitive impairment in idiopathic
Ziyang Yu1, Huize Pang2, Hongmei Yu3
1School of Medicine, Xiamen University, Xiamen, Fujian Province, China; Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning Province, China.
Purpose:
The neurobiological mechanisms and an early identification of MCI in idiopathic Parkinson's disease (IPD) remain unclear. To investigate the abnormalities of types of white matter (WM) fiber tracts segmentally and establish reliable indicator in IPD-MCI.
Methods:
Forty IPD with normal cognition (IPD-NCI), thirty IPD-MCI, and thirty healthy controls were included. Automated fiber quantification was applied to extract the fractional anisotropy (FA) and mean diffusivity (MD) values at 100 locations along the major fibers. Partial correlation was performed between diffusion values and cognitive performance. Furthermore, machine learning analyses were conducted to determine the imaging biomarker of MCI. Permutation tests were performed to evaluate the pointwise differences under the FWE correction.
Results:
IPD-MCI had similar but more severe and widespread WM degeneration in the association, projection, and commissural fibers compared with IPD-NCI. Meanwhile, IPD-MCI showed distinct degeneration pattern in the association fibers. The FA of the anterior segment of right inferior fronto-occipital fasciculus (IFOF) was positively correlated with MoCA (P < 0.05) and executive function (P < 0.05). The MD of the middle and posterior segment of left superior longitudinal fasciculus (SLF) was negatively correlated with MoCA P < 0.05), executive (P < 0.05), visuospatial function (P < 0.05). Furthermore, the AUC of support vector machine model was 0.80 in the validation dataset. The FA of anterior segment of right IFOF contribute the most.
Conclusion:
This study demonstrated that regional tract-specific microstructural degeneration, especially the association fibers, can be used to predict MCI in IPD. Especially, the right IFOF may be a significant imaging biomarker in predicting IPD with MCI.
Insights
Early identification of mild cognitive impairment (MCI) in idiopathic Parkinson's disease (IPD) is possible. White matter degeneration in specific tracts, particularly the right inferior fronto-occipital fasciculus, serves as a key imaging biomarker for predicting MCI in IPD patients.
Area of Science:
- Neuroimaging
- Neuroscience
- Biomarkers
Background:
- Idiopathic Parkinson's disease (IPD) often involves cognitive decline, with mild cognitive impairment (MCI) being a common complication.
- Understanding the neurobiological underpinnings and early detection of MCI in IPD is crucial for timely intervention.
Purpose of the Study:
- To investigate white matter (WM) fiber tract abnormalities in IPD with MCI (IPD-MCI) compared to IPD with normal cognition (IPD-NCI) and healthy controls.
- To identify reliable imaging biomarkers for early detection of MCI in IPD.
Main Methods:
- Utilized automated fiber quantification to analyze fractional anisotropy (FA) and mean diffusivity (MD) values in major fiber tracts across three groups: IPD-NCI, IPD-MCI, and healthy controls.
- Employed partial correlation and machine learning (support vector machine) analyses to identify significant diffusion values and predict MCI.
- Performed permutation tests with FWE correction for robust statistical evaluation.
Main Results:
- IPD-MCI exhibited more severe and widespread WM degeneration in association, projection, and commissural fibers than IPD-NCI, with distinct patterns in association fibers.
- Fractional anisotropy (FA) in the anterior right inferior fronto-occipital fasciculus (IFOF) correlated positively with cognitive scores (MoCA, executive function).
- Mean diffusivity (MD) in the left superior longitudinal fasciculus (SLF) correlated negatively with cognitive scores. A support vector machine model achieved an AUC of 0.80, with right IFOF FA being the most significant predictor.
Conclusions:
- Regional, tract-specific microstructural degeneration, particularly in association fibers, can predict MCI in IPD.
- The right inferior fronto-occipital fasciculus (IFOF) shows promise as a significant imaging biomarker for predicting MCI in idiopathic Parkinson's disease.
