Peak width of skeletonized mean diffusivity and cognitive performance in cerebral amyloid angiopathy

Peak width of skeletonized mean diffusivity as a marker of small vessel disease in patients with temporal lobe epilepsy with hippocampal sclerosis

OBJECTIVE

White matter abnormalities in patients with temporal lobe epilepsy (TLE) and hippocampal sclerosis (HS) are well known. Peak width of skeletonized mean diffusivity (PSMD) is a novel marker for quantifying white matter integrity that may reflect small vessel disease. In this study, we aimed to quantify the extent of white matter damage in patients with TLE and HS by using PSMD.

METHODS

We enrolled 52 patients with TLE with HS and 54 age- and sex-matched healthy controls. Diffusion tensor imaging (DTI) was performed using a 3-T magnetic resonance imaging scanner. We measured PSMD using DTI findings and compared PSMD between patients with TLE with HS and healthy controls. We also evaluated the correlation between PSMD and clinical factors in patients with TLE and HS.

RESULTS

PSMD differed significantly between healthy controls and patients with TLE and HS, and it was higher in the patients (2.375 × 10-4 mm2/s vs. 2.108 × 10-4 mm2/s, p < .001). Furthermore, PSMD in the ipsilateral hemisphere of the HS was higher than in the contralateral hemisphere of the HS (2.472 × 10-4 mm2/s vs. 2.258 × 10-4 mm2/s, p = .040). PSMD was positively correlated with age (r = .512, p < .001) and age at seizure onset (r = .423, p = .002) in patients with TLE and HS.

SIGNIFICANCE

Patients with TLE and HS had higher PSMD values than healthy controls, and PSMD was positively correlated with age. These findings provide evidence of white matter damage probably due to small vessel disease in patients with TLE and HS and support the feasibility of PSMD as a promising imaging marker for epileptic disorders.

Brain MRI Detection of an Abnormal Peak Width of Skeletonized Mean Diffusivity in REM Sleep Behavior Disorder

BACKGROUND AND PURPOSE

Peak width of skeletonized mean diffusivity (PSMD) is a novel marker of white matter damage, which may be related to small vessel disease. This study aimed to investigate the presence of white matter damage in patients with isolated rapid eye movement sleep behavior disorder (RBD) using PSMD.

METHODS

We enrolled patients with newly diagnosed isolated RBD confirmed by polysomnography and age- and sex-matched healthy controls. Diffusion tensor imaging (DTI) was conducted using a 3-Tesla MRI scanner. We measured the PSMD based on DTI in several steps, including preprocessing, skeletonization, application of a custom mask, and histogram analysis, using the Functional Magnetic Resonance Imaging of the Brain Software Library program. We compared the incidence of PSMD between patients with RBD and healthy controls and performed a correlation analysis between PSMD and clinical factors in patients with RBD.

RESULTS

Thirty patients with isolated RBD and 41 healthy controls were enrolled. The PSMD was significantly higher in patients with RBD than that in the healthy controls (3.078 vs. 2.746 × 10-4 mm2/s, p = 0.001). In addition, PSMD positively correlated with age in patients with RBD (r = 0.477, p = 0.007). However, PSMD was not associated with other clinical or polysomnographic factors.

CONCLUSION

Patients with isolated RBD had a higher PSMD than healthy controls, indicating the evidence of white matter damage in patients with RBD. This finding highlights the potential of PSMD as a marker for detecting white matter damage, which may be related to small vessel diseases, in patients with sleep disorders.

Evidence of small vessel disease in patients with juvenile myoclonic epilepsy based on the peak width of skeletonized mean diffusivity

OBJECTIVES

Peak width of skeletonized mean diffusivity (PSMD) is a novel marker of white matter changes probably due to small vessel disease. This study aimed to investigate the presence of white matter changes in juvenile myoclonic epilepsy (JME) using PSMD.

METHODS

We enrolled patients with JME and age- and sex-matched healthy controls. We performed diffusion tensor imaging (DTI) using a three tesla magnetic resonance imaging scanner. We measured the PSMD based on DTI in several steps, including preprocessing, skeletonization, application of a custom mask, and histogram analysis, using the FSL program. We compared the PSMD between patients with JME and healthy controls and the PSMD according to the antiseizure medication (ASM) response among the patients with JME. We also performed a correlation analysis between the PSMD and clinical factors in patients with JME.

RESULTS

We enrolled the 42 patients with newly diagnosed JME and 42 healthy controls. There was a significant difference in the PSMD between patients with JME and healthy controls. PSMD was higher in patients with JME than in healthy controls (2.234 vs. 2.085 × 10-4 mm2/s, p = 0.013). In addition, the PSMD was higher in patients with JME who were ASM poor responders than in those who were ASM good responders (2.586 vs. 2.176 × 10-4 mm2/s, p = 0.007). The PSMD was positively correlated with age (r = 0.364, p = 0.017).

CONCLUSION

Patients with JME have a higher PSMD than healthy controls, indicating evidence of white matter changes in patients with JME. In addition, white matter changes are related to the ASM response in patients with JME. This finding also highlights the potential of PSMD as a marker for detecting white matter changes probably due to small vessel disease in patients with epilepsy, which would require further studies.

Small vessel disease in patients with restless legs syndrome evidenced by elevated peak width of skeletonized mean diffusivity

Peak width of skeletonized mean diffusivity (PSMD) is a novel marker of small vessel disease. This study aimed to investigate small vessel disease in patients with restless legs syndrome (RLS) using PSMD. We prospectively enrolled 65 patients with primary RLS and 59 age- and sex-matched healthy controls. Diffusion tensor imaging (DTI) was performed using a 3-T magnetic resonance imaging scanner in patients with RLS and healthy controls. We obtained PSMD by DTI in several steps, including preprocessing, skeletonization, application of a custom mask, and histogram analysis. We compared the PSMD between patients with RLS and healthy controls and performed a correlation analysis between the PSMD and clinical characteristics in patients with RLS. The PSMD significantly differed between patients with RLS and healthy controls; it was higher in patients with RLS than that in healthy controls (2.423 vs. 2.298 × 10-4 mm2/s, p = 0.017). The PSMD significantly differed according to the RLS severity (2.305 × 10-4 mm2/s, moderate RLS; 2.368 × 10-4 mm2/s, severe RLS; 2.477 × 10-4 mm2/s, very severe RLS; p = 0.003). Additionally, the PSMD was positively correlated with age (r = 0.522, p < 0.001) and RLS severity (r = 0.263, p = 0.033). Patients with RLS exhibited a higher PSMD than that in healthy controls, indicating the evidence of small-vessel disease in RLS and that the severity increased as RLS severity increased. These findings provide crucial information for clinical management and treatment strategies, highlighting the importance of addressing small vessel disease in patients with RLS.

Microstructural white matter damage on MRI is associated with disease severity in Dutch-type cerebral amyloid angiopathy

Peak width of skeletonized mean diffusivity (PSMD) is an emerging diffusion-MRI based marker to study subtle early alterations to white matter microstructure. We assessed PSMD over the clinical continuum in Dutch-type hereditary CAA (D-CAA) and its association with other CAA-related MRI-markers and cognitive symptoms. We included (pre)symptomatic D-CAA mutation-carriers and calculated PSMD from diffusion-MRI data. Associations between PSMD-levels, cognitive performance and CAA-related MRI-markers were assessed with linear regression models. We included 59 participants (25/34 presymptomatic/symptomatic; mean age 39/58 y). PSMD-levels increased with disease severity and were higher in symptomatic D-CAA mutation-carriers (median [range] 4.90 [2.77-9.50]mm2/s × 10-4) compared with presymptomatic mutation-carriers (2.62 [1.96-3.43]mm2/s × 10-4) p = <0.001. PSMD was positively correlated with age, CAA-SVD burden on MRI (adj.B [confidence interval] = 0.42 [0.16-0.67], p = 0.002), with number of cerebral microbleeds (adj.B = 0.30 [0.08-0.53], p = 0.009), and with both deep (adj.B = 0.46 [0.22-0.69], p = <0.001) and periventricular (adj.B = 0.38 [0.13-0.62], p = 0.004) white matter hyperintensities. Increasing PSMD was associated with decreasing Trail Making Test (TMT)-A performance (B = -0.42 [-0.69-0.14], p = 0.04. In D-CAA mutation-carriers microstructural white matter damage is associated with disease phase, CAA burden on MRI and cognitive impairment as reflected by a decrease in information processing speed. PSMD, as a global measure of alterations to the white matter microstructure, may be a useful tool to monitor disease progression in CAA.

Horizontal analysis and longitudinal cohort study of chronic renal failure correlates and cerebral small vessel disease relationship using peak width of skeletonized mean diffusivity

Background and purpose

Peak width of skeletonized mean diffusivity (PSMD) is an MRI-based biomarker that may reflect white matter lesions (WML). PSMD is based on skeletonization of MR DTI data and histogram analysis. Both chronic renal failure (CRF) and WML may be affected by multisystemic small-vessel disorder. We aimed to explore the relationship between PSMD and estimated glomerular filtration rate (eGFR).

Methods

Fifty followed-up CRF patients matched for age, sex, hypertension and smoking status were enrolled and classified into a progressive group (n = 16) and stable group (n = 34) based on eGFR levels. Longitudinal and horizontal differences of PSMD were compared between the progressive and stable groups at the initial and follow-up time points. Pearson's correlation was used for correlation of eGFR with PSMD and WML (per Fazekas scale score). ROC was used to measure the sensitivity of PSMD and WML score to changes of eGFR.

Results

At the follow-up time point, PSMD of the progressive group was significantly higher than at the initial time point (p < 0.001), and PSMD of the progressive group was significantly higher than stable group (p < 0.001). PSMD and eGFR were significantly correlated. AUC curves explored that ΔPSMD (PSMD changes at the follow-up and initial time points) and follow-up PSMD was better for the classification of progressive and stable groups.

Conclusion

PSMD has significant correlation with eGFR, PSMD can reveal a close relationship between WML and CRF.

Using Neuroimaging to Study Cerebral Amyloid Angiopathy and Its Relationship to Alzheimer's Disease

Cerebral amyloid angiopathy (CAA) is characterized by amyloid-β aggregation in the media and adventitia of the leptomeningeal and cortical blood vessels. CAA is one of the strongest vascular contributors to Alzheimer's disease (AD). It frequently co-occurs in AD patients, but the relationship between CAA and AD is incompletely understood. CAA may drive AD risk through damage to the neurovascular unit and accelerate parenchymal amyloid and tau deposition. Conversely, early AD may also drive CAA through cerebrovascular remodeling that impairs blood vessels from clearing amyloid-β. Sole reliance on autopsy examination to study CAA limits researchers' ability to investigate CAA's natural disease course and the effect of CAA on cognitive decline. Neuroimaging allows for in vivo assessment of brain function and structure and can be leveraged to investigate CAA staging and explore its associations with AD. In this review, we will discuss neuroimaging modalities that can be used to investigate markers associated with CAA that may impact AD vulnerability including hemorrhages and microbleeds, blood-brain barrier permeability disruption, reduced cerebral blood flow, amyloid and tau accumulation, white matter tract disruption, reduced cerebrovascular reactivity, and lowered brain glucose metabolism. We present possible areas for research inquiry to advance biomarker discovery and improve diagnostics.