Boubakeur Belaroussi

Incident lacunes preferentially localize to the edge of white matter hyperintensities: insights into the pathophysiology of cerebral small vessel disease

White matter hyperintensities and lacunes are among the most frequent abnormalities on brain magnetic resonance imaging. They are commonly related to cerebral small vessel disease and associated with both stroke and dementia. We examined the spatial relationships between incident lacunes and white matter hyperintensities and related these findings to information on vascular anatomy to study possible mechanistic links between the two lesion types. Two hundred and seventy-six patients with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), a genetically defined small vessel disease with mutations in the NOTCH3 gene were followed with magnetic resonance imaging over a total of 633 patient years. Using difference images and Jacobian maps from registered images we identified 104 incident lacunes. The majority (n = 95; 91.3%) of lacunes developed at the edge of a white matter hyperintensity whereas few lacunes were found to develop fully within (n = 6; 5.8%) or outside (n = 3; 2.9%) white matter hyperintensities. Adding information on vascular anatomy revealed that the majority of incident lacunes developed proximal to a white matter hyperintensity along the course of perforating vessels supplying the respective brain region. We further studied the spatial relationship between prevalent lacunes and white matter hyperintensities both in 365 patients with CADASIL and in 588 elderly subjects from the Austrian Stroke Prevention Study. The results were consistent with the results for incident lacunes. Lesion prevalence maps in different disease stages showed a spread of lesions towards subcortical regions in both cohorts. Our findings suggest that the mechanisms of lacunes and white matter hyperintensities are intimately connected and identify the edge of white matter hyperintensities as a predilection site for lacunes. Our observations further support and refine the concept of the white matter hyperintensity penumbra.

Multiple sclerosis lesion formation and early evolution revisited: A weekly high-resolution magnetic resonance imaging study

Background: Several magnetic resonance imaging (MRI) studies investigated the evolution of multiple sclerosis (MS) lesions to understand the pathophysiological mechanisms leading to blood-brain barrier breakdown and lesion formation. Only a few assessed the early natural history of MS lesions using short-interval longitudinal MRI. Objective: The purpose of this study was to characterize MS lesion occurrence and early evolution on high-resolution MRI acquired at weekly intervals. Methods: Active lesions were characterized on 3D fluid attenuation inversion recovery (FLAIR) and gadolinium-enhanced 3D T1-weighted MRI performed weekly (seven weeks) on five untreated patients with relapsing–remitting MS (RRMS). Results: Active lesions (n=212) were detected in all patients. All showed contrast-enhancement on at least one time-point. Most new lesions (83.5%) were visible on FLAIR and post-contrast T1-weighted images at first detection; 11.2% showed activity on FLAIR images, one or more weeks before the appearance of contrast-enhancement; 12.5% enhanced before being apparent on FLAIR. Conclusion: Blood brain barrier disruption is a constant step in the natural history of active MS lesions, but does not always constitute the initial event. These findings are consistent with the existence of a subpopulation of lesions with an ‘inside-out’ genesis, where neurodegenerative processes might precede microglial activation, and a subsequent adaptive immune response.

Atlas-based liver segmentation and hepatic fat-fraction assessment for clinical trials

Automated assessment of hepatic fat-fraction is clinically important. A robust and precise segmentation would enable accurate, objective and consistent measurement of hepatic fat-fraction for disease quantification, therapy monitoring and drug development. However, segmenting the liver in clinical trials is a challenging task due to the variability of liver anatomy as well as the diverse sources the images were acquired from. In this paper, we propose an automated and robust framework for liver segmentation and assessment. It uses single statistical atlas registration to initialize a robust deformable model to obtain fine segmentation. Fat-fraction map is computed by using chemical shift based method in the delineated region of liver. This proposed method is validated on 14 abdominal magnetic resonance (MR) volumetric scans. The qualitative and quantitative comparisons show that our proposed method can achieve better segmentation accuracy with less variance comparing with two other atlas-based methods. Experimental results demonstrate the promises of our assessment framework.

An Automated and Robust Framework for Quantification of Muscle and Fat in the Thigh

The tissue quantification in the thigh (e.g. cross-sectional areas of adipose tissue and muscle) is important, since their quantities reflect adverse metabolic effects and muscle function. Traditional manual analysis is time-consuming and operator-dependent, especially in the case of multi-slices or 3D datasets. In clinical trials, there are a large amount of datasets acquired from magnetic resonance imaging (MRI) or X-ray computed tomography (CT) that requires automatic labeling of individual tissues. Since most segmentation algorithms are not suited for different modalities, we present an automatic and robust framework for the quantitative assessment of muscle and fat tissues on 3D MR or CT data. In our framework, a variational Bayesian Gaussian mixture model is used to cluster regions of interest in images into adipose tissues (fat and marrow), muscle, bone and background. The identification of each cluster is based on marrow detection. Furthermore, we use a combination of parametric and geodesic active contour models to distinguish different adipose tissues in 3D images. To validate our proposed framework, we have conducted preliminary experiments on five volumetric mid-thigh axial datasets of MR and CT images from clinical trials.

ACCURACY OF BMAS HIPPOCAMPUS SEGMENTATION USING THE HARMONIZED HIPPOCAMPAL PROTOCOL

 Hippocampal volume (HCV) measured with MRI has been widely used as a key biomarker for both improving subject selection and monitoring treatment efficacy in Alzheimer’s Disease (AD) studies. However various hippocampal protocols exist in the literature, each including a different set of subfields and sub-structures, potentially leading to confusion and additional complexity for direct comparison and consistency in reporting study results.

Automatic Liver Segmentation and Hepatic Fat Fraction Assessment in MRI

Automated assessment of hepatic fat fraction is clinically important. A robust and precise segmentation would enable accurate, objective and consistent measurement of liver fat fraction for disease quantification, therapy monitoring and drug development. However, segmenting the liver in clinical trials is a challenging task due to the variability of liver anatomy as well as the diverse sources the images were acquired from. In this paper, we propose an automated and robust framework for liver segmentation and assessment. It uses single statistical atlas registration to initialize a robust deformable model to get fine segmentation. Fat fraction map is computed by using chemical shift based method in the delineated region of liver. This proposed method is validated on 14 abdominal magnetic resonance (MR) volumetric scans. The qualitative and quantitative comparisons show that our proposed method can achieve better segmentation accuracy with less variance comparing with an automatic graph cut method. Experimental results demonstrate the promises of our assessment framework.

Reproducibility of intracranial and hippocampal volume quantification at 1.5T and 3T MRI: Application to ADNI I

in metabolite levels of the phosphomonoesters phosphocholine (PCho) and phosphoethanolamine (PEtn), and of the phosphodiesters glycerophosphocholine (GPCho) and glycerophosphoethanolamine (GPEtn), inorganic phosphate, phosphocreatine and ATP. Results: High quality 31 P-MRSI spectra with well resolved resonance for phospholipids were obtained (see Figure). Relative levels of PCho, PEtn, GPCho and GPEtn to total phosphorus signal and the ratio of phosphomonoesters to phosphodiesters will be presented for medial temporal lobe, medial prefrontal cortex and posterior cingulate cortex. It is anticipated that data will be presented from a total number of approximately 20 patients. Conclusions: This clinical study will be the first to provide information on brain phospholipid metabolism in multiple brain regions in patients with Alzheimer’s disease. Souvenaid is a registered trademark of N.V. Nutricia.

Quantifying neocortical structural changes for clinical trials in Alzheimer’s disease: Comparison between tensor-based morphometry and longitudinal freesurfer

value ratio (SUVRs) 1.1, measured from a standard space template consisting of 6 cortical regions. For comparison to a wholecerebellar reference region, a second normalization was performed on the longitudinal data using a centrum semiovale region as a correction factor (Figure). This method has been shown to improve signal to noise, while preserving the ability to use cerebellar SUVRs at baseline. Analysis-of-Covariance models adjusted by baseline, study, treatment and age were used to assess baselineto-endpoint change between treatment and placebo groups. For sample size estimations, 80% power and a1⁄40.05 were used to detect magnitude of observed 18 month changes from baseline in the placebo group. Results:Using a whole-cerebellar reference region at baseline and endpoint, least squares mean SUVRs for the placebo group increased 0.00460.0129 (0.49%60.91), and for the active treatment group decreased 0.00660.0137 (0.19%6 0.96)(p1⁄40.62). Power analysis revealed a sample size of n1⁄44056 to detect a difference between 18 month placebo group change and baseline SUVRs (i.e. no change in treatment group from baseline). White matter adjustments resulted in a mean increase of 0.01160.0075 (0.79%60.54) in the placebo group and mean decrease of 0.00860.008 (-0.6%60.57) in the active treatment group (p1⁄40.08); the calculated sample size fell to n1⁄4421. Conclusions:Adjusting longitudinal SUVRs with a white matter reference region in these phase 3 anti-amyloid treatment trials increased mean change detection and decreased variance. This method resulted in a substantial improvement in statistical power to detect change. Reference: Abhinay Joshi, Michael Pontecorvo, Michael A. Navitsky, Ian A. Kennedy, Mark Mintun, Michael D. Devous. Measuring change in beta–amylod burden over time using florbetapir-PET and a subcortical white matter reference region. Alzheimer’s Dement. 2014;10(4):902.

A jacobian-based method to assess changes in cortical thickness: Application to ADNI data and comparison with longitudinal freesurfer

ERC and ADAS13 scores were 35%, 30% and 7%. Thirty-eight (38) CN subjects progressed to incident MCI, but neither age nor education predicted progression. In univariate Cox models, ADAS13 score (c1⁄414.2, p<.0001) and ERC normalized volume (c1⁄46.2, p1⁄40.01) predicted progression, while amyloid SUVR showed a trend toward significant prediction (c1⁄43.2, p1⁄4.07). In multivariate Cox regression, only ADAS13 scores predicted progression (c 1⁄48.3, p1⁄4.004). Using dichotomized variables, all predictors were significant in univariate analyses, but none provided unique variance in multivariate models. The estimated 2.1 year progression rates to MCI and 95% CIs were:

Baseline clinical scores and volumetric MRI parameters across subjects randomized in mild-to-moderate (BMS CN156-013) and predementia (BMS CN156-018) Alzheimer's disease clinical trials of avagacestat

the safety and tolerability of avagacestat in patients with PDAD. Key entry criteria for subjects included: memory complaints documented by subject or study partner, objective memory loss on the Wechsler Memory Scale Logical Memory II or the Free & Cued Selective Reminding Test, a CDR-global score of 0.5 with a memory box score of 0.5, and a MMSE of 24-30. Entry criteria required that subjects not meet DSM-IV criteria for dementia, and their MRI findings show no alternative cause for cognitive impairment. After meeting all key criteria, subjects underwent lumbar puncture and were included if their CSF amyloid-beta42 levels < 200pg/mL or total tau/amyloid-beta42 ratio of 0.39. Co-medication with a stable dose of a marketed cholinesterase inhibitor or memantine was permitted. Results: Randomization completed in September 2011, approximately 24 months after first patient visit. Of 1350 subjects enrolled at 72 centers in North America and Europe; 263 (19%) were randomized. Nearly 800 enrolled subjects (approximately 60%) were excluded prior to CSF testing due to clinical criteria. Of nearly 550 subjects whomet the clinical inclusion criteria and completed the lumbar puncture, approximately one-half met the CSF biomarker criteria for study entry. There were 104 subjects who met entry requirements except the CSF criteria, whowere enrolled into a nonrandomized observational cohort. The major reasons for exclusion were cognitive criteria, abnormal laboratory tests, meeting dementia criteria, compliance to protocol issues, MRI findings, or concurrent medications. Conclusions: The recruitment of this study population of subjects with PDAD demonstrates both the feasibility and challenges of trials, which require both clinical phenotypic features as well as CSF criteria. Efforts are warranted to refine entry criteria and decrease screen failures.