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Voxel-based analysis and multivariate pattern analysis of diffusion tensor imaging study in anti-NMDA receptor
Yanli Liang1, Luhui Cai1, Xia Zhou1
1Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Purpose:
This study aimed to investigate brain white matter (WM) changes and their relationship to cognition in patients with anti-N-methyl-D-aspartate (anti-NMDA) receptor encephalitis. Multivariate pattern analysis (MVPA) was used to explore brain regions that play an important role in classification.
Methods:
Fifteen patients and fifteen controls underwent Montreal Cognitive Assessment (MoCA) and diffusion tensor imaging. Based on fractional anisotropy (FA) and mean diffusivity (MD) for MVPA classification, the weights of each brain region were calculated.
Results:
Compared with the controls, the patients showed an FA reduction in right middle temporal gyrus, left middle cerebellar peduncle, right praecuneus, and an MD increase in left medial temporal gyrus and left frontal lobe. The MoCA score for patients was lower than controls, especially in executive function, fluency, delayed recall and visual perception items. The FA value of right praecuneus was positively correlated with total MoCA score and fluency score. The MD of left frontal lobe was negatively correlated with total MoCA score, and MD of the left medial temporal gyrus was positively correlated with delayed recall. The accuracy, sensitivity and specificity of classification based on FA were 70%, 60% and 80%, respectively. Based on MD, they were each 80%. The brain regions with large weights from FA and MD overlap in temporal lobe, cerebellum and hippocampus.
Conclusions:
These results suggest that WM changes are associated with cognitive deficits. MVPA based on FA and MD has good classification ability. Our study may provide new insights into the pathophysiological mechanisms of residual cognitive deficits.
Insights
Brain white matter changes in anti-N-methyl-D-aspartate receptor encephalitis patients are linked to cognitive deficits. Diffusion tensor imaging and machine learning accurately classify patients based on these white matter alterations.
Area of Science:
- Neuroscience
- Neurology
- Radiology
Background:
- Anti-N-methyl-D-aspartate (anti-NMDA) receptor encephalitis is an autoimmune disorder that can cause significant neurological and psychiatric symptoms.
- Cognitive deficits, particularly in memory, executive function, and perception, are common residual symptoms following treatment.
- Understanding the underlying brain changes, especially in white matter (WM), is crucial for diagnosing and managing these deficits.
Purpose of the Study:
- To investigate white matter (WM) alterations in patients with anti-NMDA receptor encephalitis.
- To explore the relationship between WM changes and cognitive function in these patients.
- To assess the utility of multivariate pattern analysis (MVPA) using diffusion tensor imaging (DTI) metrics for classifying patients.
Main Methods:
- Fifteen patients with anti-NMDA receptor encephalitis and fifteen healthy controls underwent DTI and the Montreal Cognitive Assessment (MoCA).
- Fractional anisotropy (FA) and mean diffusivity (MD) values were extracted from various brain regions.
- MVPA was employed to classify patients based on FA and MD, calculating regional weights.
Main Results:
- Patients exhibited reduced FA in the right middle temporal gyrus and right precuneus, and increased MD in the left medial temporal gyrus and left frontal lobe compared to controls.
- Cognitive impairments were noted in executive function, fluency, delayed recall, and visual perception.
- FA in the right precuneus correlated positively with MoCA and fluency scores; MD in the left frontal lobe correlated negatively with MoCA scores. MD in the left medial temporal gyrus correlated positively with delayed recall. MVPA achieved 70-80% accuracy in classification.
- Key brain regions identified by MVPA (temporal lobe, cerebellum, hippocampus) showed overlapping importance for both FA and MD.
Conclusions:
- White matter microstructural changes, detectable by DTI, are significantly associated with cognitive impairments in anti-NMDA receptor encephalitis.
- MVPA using FA and MD demonstrates robust classification capabilities, aiding in understanding disease-specific patterns.
- These findings offer insights into the pathophysiology of persistent cognitive deficits and highlight DTI as a valuable tool for assessment.
