Segmental Abnormalities of White Matter Microstructure in End-Stage Renal Disease Patients: An Automated Fiber Quantification Tractography Study

Abstract

Background and Purpose: End-stage renal disease (ESRD) results in extensive white matter abnormalities, but the specific damage segment cannot be identified. This study aimed to determine the segmental abnormalities of white matter microstructure in ESRD and its relationship with cognitive and renal function indicators.Methods: Eighteen ESRD patients and 19 healthy controls (HCs) were prospectively recruited. All participants underwent DTI and clinical assessments. Automatic fiber quantification (AFQ) was applied to generate bundle profiles along 16 main white matter tracts. We compared the DTI parameters between groups. Besides, we used partial correlation and multiple linear regression analyses to explore the associations between white matter integrity and cognitive performance as well as renal function indicators.Results: In the global tract level, compared to HCs, ESRD patients had greater MD, AD, and RD values and lower FA value in several fibers (P < 0.05, FDR correction). In the point-wise level, extensive damage existed in specific locations of different fiber tracts, particularly in the left hemisphere (P < 0.05, FDR correction). Among these tracts, the mean AD values of the left cingulum cingulate correlated negatively with MoCA score. Urea and UA level were independent predictors of the AD value of superior component of the left corticospinal. Besides, urea level was the independent predictors of mean MD value of left anterior thalamic radiation (ATR).Conclusion: White matter fiber tract damage in ESRD patients may be characterized by abnormalities in its specific location, especially in the left hemisphere. Aberrational specific located fibers were related to cognitive impairment and renal dysfunction.

Lesions in White Matter in Wilson’s Disease and Correlation with Clinical Characteristics

“…As frontal-temporal association fibers, previous studies indicated that they may be associated with symptoms of cognitive decline. [32][33][34] Studies focusing on neuropsychological impairments in WD have highlighted that patients with WD showing neurological signs present significant deficits in a wide range of cognitive domains. 35 The UF fiber links the anterior temporal lobe to the medial and lateral orbitofrontal cortex and plays a role in episodic memory, language, semantic activities, and social-emotional processing.…”

Exploring the Structural Plasticity Mechanism of Corticospinal Tract during Stroke Rehabilitation Based Automated Fiber Quantification Tractography

“…We also performed data format conversion, head motion eddy correction, gradient orientation correction, brain mask acquisition, and tensor calculation using the Functional MRI of the Brain Software Library version 6.0.3 commands to generate FA, MD, AD, RD, S0, and other files. 9,16,17…”

“…We also performed data format conversion, head motion eddy correction, gradient orientation correction, brain mask acquisition, and tensor calculation using the Functional MRI of the Brain Software Library version 6.0.3 commands to generate FA, MD, AD, RD, S0, and other files. 9,16,17 CST tracking and extraction were performed using the MATLAB platform and open-source AFQ software (https:// github.com/yeatmanlab/AFQ). The process mainly included (1) converting the data obtained from the previous steps into a dt6 file in MATLAB format using the dtiMakeDt-6FromFsl command; (2) setting the tracking parameters for FA threshold greater than 0.2 and turning angle less than 45° for whole-brain fiber tracking; (3) segmenting 20 major fiber tracts from whole-brain fibers; (4) cleaning up the raw fiber tracts based on the average length or 4 standard deviations of fiber bundle cores to clean up the original fiber bundles; (5) equally dividing the CST into 100 subsegments from the midbrain to the primary motor cortex and extracting diffusion tensor values for each segment; to comprehensively assess the microstructural changes in the CST during stroke rehabilitation, we computed the FA, MD, AD, and RD values for each subsegment, as these indexes provide distinct perspectives on fiber bundle damage 18 ; (6) to facilitate inter-group comparisons, the data of the subjects with right hemisphere cerebral infarction were flipped left-right; consequently, the left-side data of all patients represented the ipsilesional side, while the right-side data represented the contralesional side; correspondingly, accounting for the potential systematic effects from hemispheric differences, for the HC group, a new set of data, including bilateral corticospinal data, was generated after flipping the left and right hemispheres; and (7) extracting CST information, with the left CST being ipsilateral to the lesion and the right CST being contralateral to the lesion (Figure 1).…”

“…Automated fiber quantification (AFQ) tractography facilitates fine-grained analysis of the CST. AFQ is a new method for DTI analysis, 8,9 and it can automatically track 20 main fiber bundles including the CST; each fiber bundle can be equally divided into several segments, and indexes reflecting the severity of damage to the microstructure of any part of the fiber bundle, such as fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD), can be calculated for each segment. In addition, the AFQ results show highly reliable and reproducible.…”

Alterations in White Matter Fiber Tracts Characterized by Automated Fiber-Tract Quantification and Their Correlations With Cognitive Impairment in Neuromyelitis Optica Spectrum Disorder Patients

“…Automated fiber-tract quantification (AFQ) is an advanced DTI method for automated reconstruction of WM fiber tracts and segmentation of the fiber tracts into multiple nodes. It can provide more detailed information on WM damage and has been applied to MCI, schizophrenia, cerebral small vessel disease, benign childhood epilepsy, end-stage renal disease, and so on (Sun et al, 2015;Chen et al, 2020;Jiang et al, 2021;Shu et al, 2021;Stone et al, 2021). To our knowledge, the application of AFQ for patients with NMOSD has not been studied.…”