Early Segmental White Matter Fascicle Microstructural Damage Predicts the Corresponding Cognitive Domain Impairment in Cerebral Small Vessel Disease Patients by Automated Fiber Quantification

Huang, Lili; Chen, Xin; Sun, Wei; Chen, Haifeng; Ye, Qing; Yang, Dan; Li, Mengchun; Luo, Caimei; Ma, Jun; Shao, Pengfei; Xu, Hengheng; Zhang, Bing; Zhu, Xiaolei; Xu, Yun

doi:10.3389/fnagi.2020.598242

Cited by 24 publications

(40 citation statements)

References 60 publications

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“…Besides, a study related to reduced attention of young bilingual adults showed that the integrity of the white matter fibers connecting the anterior cingulate cortex and the frontal regions was decreased, and this manifestation only exists in the right hemisphere (Mamiya et al, 2018). Similarly, Huang et al (2020) also reported that the right ATR was associated with executive function in cerebral small vessel disease patients.…”

Section: Discussionmentioning

confidence: 95%

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

et al. 2021

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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.

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Section: Discussionmentioning

confidence: 95%

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

et al. 2021

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“…Our results extend the present literature on white matter abnormalities and their impacts on processing speed in CSVD, providing evidence for the importance of the SWM. A number of CSVD studies have found strong associations of cognitive performance with diffusion MRI measures in the DWM (O’Sullivan et al ., 2005; Quinque et al ., 2012; Tuladhar et al ., 2015; Chen et al ., 2019; Huang et al ., 2020; Liu et al ., 2020; Vergoossen et al ., 2021) and in white matter areas without visible WMH (M. O’Sullivan et al ., 2004; M.…”

Section: Discussionmentioning

confidence: 99%

“…Conventional diffusion measures (e.g., FA, MD) (Michael O'Sullivan et al, 2004;O'Sullivan et al, 2005;Nitkunan et al, 2008;Schmidt et al, 2010;Quinque et al, 2012;Lawrence et al, 2013;Tuladhar et al, 2015;Baykara et al, 2016;Moonen et al, 2017;Zeestraten et al, 2017;Tozer et al, 2018;Chen et al, 2019;Wei et al, 2019;Huang et al, 2020;Liu et al, 2020;Du et al, 2021;Vergoossen et al, 2021) Advanced diffusion measures (e.g. FW, NODDI, DKI, IVIM) (Zhang, Wong, van de Haar, et al, 2017;Duering et al, 2018;Gesierich et al, 2020;Konieczny et al, 2021) Structural network measures (Lawrence et al, 2014;Reijmer et al, 2016;Tuladhar et al, 2016Tuladhar et al, , 2017Heinen et al, 2018;van Leijsen et al, 2019;Boot et al, 2020;Gesierich et al, 2020;Liu et al, 2020;Du et al, 2021) Study findings: White matter regions related to cognitive performance in CSVD…”

Section: Csvd Dmri Study Methodologymentioning

confidence: 99%

Superficial white matter microstructure affects processing speed in cerebral small vessel disease

Wang

Zhang

Huang

et al. 2022

Preprint

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White matter hyperintensities (WMH) are a typical feature of cerebral small vessel disease (CSVD). This condition contributes to about 50% of dementias worldwide, a massive health burden in aging. Microstructural alterations in the deep white matter (DWM) have been widely examined in CSVD. However, little is known about abnormalities in the superficial white matter (SWM) and their relevance for processing speed, the main cognitive deficit in CSVD. In this paper, 141 patients with CSVD were studied. Processing speed was assessed by the completion time of the Trail Making Test Part A. White matter abnormalities were assessed by WMH burden (lesion volume on T2-FLAIR) and diffusion MRI, including DTI and free-water (FW) imaging microstructure measures. The results of our study indicate that the superficial white matter may play a particularly important role in cognitive decline in CSVD. SWM imaging measures resulted in a large contribution to processing speed, despite a relatively small WMH burden in the SWM. SWM FW had the strongest association with processing speed among all imaging markers and, unlike the other diffusion MRI measures, significantly increased between two patient subgroups with the lowest WMH burdens (possibly representing early stages of disease). When comparing two patient subgroups with the highest WMH burdens, the involvement of WMH in the SWM was accompanied by significant differences in processing speed and white matter microstructure. Given significant effects of WMH volume and regional FW on processing speed, we performed a mediation analysis. SWM FW was found to fully mediate the association between WMH volume and processing speed, while no mediation effect of DWM FW was observed. Overall, our findings identify SWM abnormalities in CSVD and suggest that the SWM has an important contribution to processing speed. Results indicate that FW in the SWM is a sensitive marker of microstructural changes associated with cognition in CSVD. This study extends the current understanding of CSVD-related dysfunction and suggests that the SWM, as an understudied region, can be a potential target for monitoring pathophysiological processes in future research.

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“…The following steps were used through MATLAB 2019a: normalized T1 images to template space and segmented images into gray matter, white matter, and cerebrospinal uid; visual inspection; the total intracranial volume was evaluated; check for data homogeneity; the Gaussian kernel of full width at half maximum 6 mm (FWHM = 6 mm) was used. The "brain volume/ intracranial volume (ICV) x 100%" was used to display WMHs, gray and white matter volume [19].…”

Section: Structural Datamentioning

confidence: 99%

Structural Brain Network Measures in Elderly Patients with Cerebral Small Vessel Disease and Depressive Symptoms

Zhao

Feng

et al. 2022

Preprint

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Objectives: To investigate whether there is a difference in the incidence of depression between patients with small cerebral vascular disease (CSVD) and normal controls (NC), and the relationship between depression and white matter fiber damage and structural brain network in elderly patients with CSVD. Method: A total of 115 elderly subjects were consecutively recruited from the neurology clinic, including 36 patients with CSVD with depressive state, 34 patients with CSVD without depressive state, and 45 NCs. A detailed neuropsychological assessment and multimodal MRI were performed. Based on TBSS analysis and structural network analysis, differences between groups were compared, and logistic regression was used to determine the predictive value of TBSS indicators and structural brain network measures for depression in CSVD patients. Results: Group differences were found in global TBSS analysis and brain network measures. After adjusting for age, gender, education level, and vascular risk factors (VRF), there were significant correlations between TBSS indicators and structural network indicators and depression, including: FA (r= -0.291, p <0.05), ELocal (r = -0.278, p < 0.01) and in network strength (r = - 0.403, p < 0.001). At the same time, ELocal was an independent risk factor for depression in patients with CSVD.Conclusions: Changes in FA, MD values and structural network indicators in DTI parameters can predict the depressive state of CSVD to a certain extent, providing a more direct structural basis for the hypothesis of abnormal neural circuits in the pathogenesis of vascular depression. In addition, we believe that abnormal white matter alterations in subcortical neural circuits affect the microstructural function of brain connections, which may be a mechanism for the concomitant depressive symptoms in CSVD patients.

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Early Segmental White Matter Fascicle Microstructural Damage Predicts the Corresponding Cognitive Domain Impairment in Cerebral Small Vessel Disease Patients by Automated Fiber Quantification

Cited by 24 publications

References 60 publications

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

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

Superficial white matter microstructure affects processing speed in cerebral small vessel disease

Structural Brain Network Measures in Elderly Patients with Cerebral Small Vessel Disease and Depressive Symptoms

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