Search

• Thalamic tissue damage in multiple sclerosis (MS) exhibits a distinct gradient from the ventricular surface. • Quantitative gradient-recalled echo (qGRE) MRI analysis reveals a steeper periventricular thalamic gradient of tissue integrity in MS patients compared to healthy controls. • Increased thalamic gradient correlates with longer disease duration and higher expanded disability status scale (EDSS) scores, suggesting a link between periventricular thalamic gradient and clinical disability in MS. Thalamic tissue damage in multiple sclerosis (MS) follows a 'surface-in' gradient from the ventricular surface. The clinical consequences of this gradient are not completely understood. Using quantitative gradient-recalled echo (qGRE) MRI, we evaluated a periventricular thalamic gradient of tissue integrity in MS and its relationship with clinical variables. Structural and qGRE MRI scans were acquired for a cohort of MS patients and healthy controls (HC). qGRE-derived R2t* values were used as a measure of tissue integrity. Thalamic segmentations were divided into 1-mm concentric bands radiating from the ventricular surface, excluding the CSF-adjacent band. Median R2t* values within these bands were used to calculate the periventricular thalamic gradient. We included 44 MS patients and 17 HC. R2t* increased slightly with distance from the ventricular surface in HC. MS patients had a steeper periventricular thalamic gradient compared to HC (mean slope 0.55 vs. 0.36; p < 0.001), which correlated with longer disease duration (β = 0.001 /year; p = 0.027) and higher Expanded Disability Status Scale (EDSS) score (β = 0.07 /EDSS point; p = 0.019). Left and right thalamus were symmetrically affected. We detected an increased thalamic gradient in MS in vivo using qGRE MRI, which correlated with disease duration and greater clinical disability. These findings further support the 'surface-in' pathology hypothesis in MS and suggest a CSF-mediated process given symmetric bi-thalamic involvement. [ABSTRACT FROM AUTHOR]

Amyloid-beta plaques are a hallmark of Alzheimer's disease (AD) that can be assessed by amyloid imaging (e.g., Pittsburgh B compound [PiB]) and summarized as a scalar value. Summary values may have clinical utility but are an average over many regions of interest, potentially obscuring important topography. This study investigates the longitudinal evolution of amyloid topographies in cognitively normal older adults who had normal (N = 131) or abnormal (N = 26) PiB scans at baseline. At 3 years follow-up, 16 participants with a previously normal PiB scan had conversion to PiB scans consistent with preclinical AD. We investigated the multivariate relationship (canonical correlation) between baseline and follow-up PiB topographies. Furthermore, we used penalized regression to investigate the added information derived from PiB topography compared to summary measures. PiB accumulation can be local, that is, a topography predicting the same topography in the future, and/or distributed, that is, one topography predicting another. Both local and distributed PiB accumulation was associated with conversion of PiB status. Additionally, elements of the multivariate topography, and not the commonly used summary scalar, correlated with future PiB changes. Consideration of the entire multivariate PiB topography provides additional information regarding the development of amyloid-beta pathology in very early preclinical AD. [ABSTRACT FROM AUTHOR]

Abstract: Alzheimer's disease (AD) has a long preclinical phase in which amyloid and tau cerebral pathology accumulate without producing cognitive symptoms. Resting state functional connectivity magnetic resonance imaging has demonstrated that brain networks degrade during symptomatic AD. It is unclear to what extent these degradations exist before symptomatic onset. In this study, we investigated graph theory metrics of functional integration (path length), functional segregation (clustering coefficient), and functional distinctness (modularity) as a function of disease severity. Further, we assessed whether these graph metrics were affected in cognitively normal participants with cerebrospinal fluid evidence of preclinical AD. Clustering coefficient and modularity, but not path length, were reduced in AD. Cognitively normal participants who harbored AD biomarker pathology also showed reduced values in these graph measures, demonstrating brain changes similar to, but smaller than, symptomatic AD. Only modularity was significantly affected by age. We also demonstrate that AD has a particular effect on hub-like regions in the brain. We conclude that AD causes large-scale disconnection that is present before onset of symptoms. [Copyright &y& Elsevier]