Early visual cortical structural changes in diabetic patients without diabetic retinopathy.

BACKGROUND: It is known that diabetic patients have changes in cortical morphometry as compared to controls, but it remains to be clarified whether the visual cortex is a disease target, even when diabetes complications such as retinopathy are absent. Therefore, we compared type 2 diabetes patients without diabetic retinopathy with control subjects using magnetic resonance imaging to assess visual cortical changes when retinal damage is not yet present. METHODS: We performed T1-weighted imaging in 24 type 2 diabetes patients without diabetic retinopathy and 27 age- and gender-matched controls to compare gray matter changes in the occipital cortex between groups using voxel based morphometry. RESULTS: Patients without diabetic retinopathy showed reduced gray matter volume in the occipital lobe when compared with controls. CONCLUSIONS: Reduced gray matter volume in the occipital cortex was found in diabetic patients without retinal damage. We conclude that cortical early visual processing regions may be affected in diabetic patients even before retinal damage occurs.

Extending Inferential Group Analysis in Type 2 Diabetic Patients with Multivariate GLM Implemented in SPM8.

BACKGROUND: Although voxel based morphometry studies are still the standard for analyzing brain structure, their dependence on massive univariate inferential methods is a limiting factor. A better understanding of brain pathologies can be achieved by applying inferential multivariate methods, which allow the study of multiple dependent variables, e.g. different imaging modalities of the same subject. OBJECTIVE: Given the widespread use of SPM software in the brain imaging community, the main aim of this work is the implementation of massive multivariate inferential analysis as a toolbox in this software package. applied to the use of T1 and T2 structural data from diabetic patients and controls. This implementation was compared with the traditional ANCOVA in SPM and a similar multivariate GLM toolbox (MRM). METHOD: We implemented the new toolbox and tested it by investigating brain alterations on a cohort of twenty-eight type 2 diabetes patients and twenty-six matched healthy controls, using information from both T1 and T2 weighted structural MRI scans, both separately - using standard univariate VBM - and simultaneously, with multivariate analyses. RESULTS: Univariate VBM replicated predominantly bilateral changes in basal ganglia and insular regions in type 2 diabetes patients. On the other hand, multivariate analyses replicated key findings of univariate results, while also revealing the thalami as additional foci of pathology. CONCLUSION: While the presented algorithm must be further optimized, the proposed toolbox is the first implementation of multivariate statistics in SPM8 as a user-friendly toolbox, which shows great potential and is ready to be validated in other clinical cohorts and modalities.

Early disrupted neurovascular coupling and changed event level hemodynamic response function in type 2 diabetes: an fMRI study.

Type 2 diabetes (T2DM) patients develop vascular complications and have increased risk for neurophysiological impairment. Vascular pathophysiology may alter the blood flow regulation in cerebral microvasculature, affecting neurovascular coupling. Reduced fMRI signal can result from decreased neuronal activation or disrupted neurovascular coupling. The uncertainty about pathophysiological mechanisms (neurodegenerative, vascular, or both) underlying brain function impairments remains. In this cross-sectional study, we investigated if the hemodynamic response function (HRF) in lesion-free brains of patients is altered by measuring BOLD (Blood Oxygenation Level-Dependent) response to visual motion stimuli. We used a standard block design to examine the BOLD response and an event-related deconvolution approach. Importantly, the latter allowed for the first time to directly extract the true shape of HRF without any assumption and probe neurovascular coupling, using performance-matched stimuli. We discovered a change in HRF in early stages of diabetes. T2DM patients show significantly different fMRI response profiles. Our visual paradigm therefore demonstrated impaired neurovascular coupling in intact brain tissue. This implies that functional studies in T2DM require the definition of HRF, only achievable with deconvolution in event-related experiments. Further investigation of the mechanisms underlying impaired neurovascular coupling is needed to understand and potentially prevent the progression of brain function decrements in diabetes.

Comparison of acoustic radiation force impulse/serum noninvasive markers for fibrosis prediction in liver transplant.

OBJECTIVES: Fibrosis, related to several causes, can be diagnosed in children and adolescents' liver grafts that are >1 year old. At present, liver biopsy is the gold standard for assessing liver damage in the posttransplant setting. We aimed to evaluate the accuracy of noninvasive biomarkers of fibrosis, namely, acoustic radiation force impulse (ARFI), aspartate-to-platelet ratio index, and aspartate aminotransferase/alanine aminotransferase (AST/ALT) ratio index, either alone or in combination, for predicting fibrosis in pediatric patients submitted to liver transplantation. METHODS: We prospectively assessed liver fibrosis in 30 children/adolescents with liver transplant through biopsy (liver transplant follow-up during 12 months). ARFI with Virtual Touch Software (Acuson 2000) was performed, and blood samples were taken to determine liver function and platelet count. Two groups were analyzed according to the histopathologic stage of fibrosis, namely, none/mild (F0-F1) versus significant fibrosis (F2-4). RESULTS: The mean age of the 30 patients was 11 years (3-18 years), with a mean posttransplant period of assessment of 6.5 years. Twenty-four patients (80%) presented stage F0-F1 fibrosis and 6 patients (20%) presented stage F2-4. The area under the curve using receiver operating characteristic analysis for ARFI, aspartate-to-platelet ratio index, and AST/ALT ratio index for significant fibrosis was 0.76 (P = 0.052), 0.74 (P = 0.066), and 0.69 (P = 0.162), respectively. Through multivariate logistic regression analysis, the only independent predictor of significant fibrosis was ARFI (odds ratio 10.7, 95% confidence interval 1.2-95.7; P = 0.045). The combination of ARFI and AST/ALT ratio index presented a good diagnostic accuracy of fibrosis (area under the curve of 0.83; P = 0.013). CONCLUSIONS: ARFI may serve as a potential method for assessing significant fibrosis in pediatric patients with liver transplant, particularly in combination with AST/ALT ratio index.

A brief history of voxel-based grey matter analysis in Alzheimer's disease.

Voxel-based morphometry (VBM) and cortical thickness measurement are common techniques to identify regional atrophy in neurodegenerative diseases such as Alzheimer's disease (AD). Because studies employing these methods draw conclusions regarding patterns of regional cortical degeneration, it is important to be aware of their possible limitations. To evaluate the effect of different VBM versions, we performed voxel-based analyses through successive versions-from SPM99 to SPM8-as well as FSL-VBM on n = 20 AD patients and n = 20 controls. Reproducibility was assessed in an independent sample, again of n = 20 per group, from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Further, we tested the hypothesis that VBM can sensitively detect hippocampal atrophy, but is relatively insensitive to changes in the cortical ribbon, by contrasting VBM with FreeSurfer cortical thickness measurements. The results with both datasets confirmed that VBM preferentially identifies grey matter lesions in the mesial temporal lobe but is largely insensitive to isocortical atrophy. In contrast, FreeSurfer identified thinning of cortical ribbon association cortex more significant in post- rather than pre-Rolandic areas and with relative preservation of primary sensory-motor regions-in other words precisely as would be expected in AD. The results highlight a bias that VBM has toward detecting mesial temporal lobe atrophy. This finding has important implications for interpretation of clinical and cognitive studies in AD.

VBM with viscous fluid registration of gray matter segments in SPM.

Improved registration of gray matter segments in SPM has been achieved with the DARTEL algorithm. Previous work from our group suggested, however, that such improvements may not translate to studies of clinical groups. To address the registration issue in atrophic brains, this paper relaxed the condition of diffeomorphism, central to DARTEL, and made use of a viscous fluid registration model with limited regularization constraints to register the modulated gray matter probability maps to an intra-population template. Quantitative analysis of the registration results after the additional viscous fluid step showed no worsening of co-localization of fiducials compared to DARTEL or unified segmentation methods, and the resulting voxel based morphometry (VBM) analyses were able to better identify atrophic regions and to produce results with fewer apparent false positives. DARTEL showed great sensitivity to atrophy, but the resulting VBM maps presented broad, amorphous regions of significance that are hard to interpret. We propose that the condition of diffeomorphism is not necessary for basic VBM studies in atrophic populations, but also that it has disadvantages that must be taken into consideration before a study. The presented viscous fluid registration method is proposed for VBM studies to enhance sensitivity and localizing power.

MRI detection of tissue pathology beyond atrophy in Alzheimer's disease: introducing T2-VBM.

Voxel-based morphometry (VBM) of T1-weighted magnetic resonance (MR) images has been widely used to identify regional atrophy in neurodegenerative conditions such as Alzheimer's disease (AD). In theory, however, T2-weighting should be more sensitive to tissue pathology, though until recently, volumetric T2-weighted images were unavailable. We tested the hypothesis that T2-VBM would be more sensitive to grey matter pathology in AD than T1-VBM using the recently-developed SPACE acquisition, which provides true-3D, high-resolution T2-weighted images. This was contrasted to conventional T1-weighted MPRAGE images acquired at the same session and resolution. All of the atrophic regions identified with T1-VBM were also identified with T2-VBM. Additional abnormalities were, however, identified with T2-VBM and the distribution of these bore a striking resemblance to the distribution of amyloid plaque deposition in AD, suggesting that T2-VBM detects signal changes due to histopathology over and above those attributable to atrophy. In keeping with this hypothesis, the relevant statistical tests demonstrated that the difference in sensitivity was caused by an apparent change in T2-weighted signal intensity that was not present in T1-weighted images. These results suggest that T2-VBM has the potential to advance VBM beyond atrophy detection to more expansive applications in tissue pathology mapping.

Comparative reliability of total intracranial volume estimation methods and the influence of atrophy in a longitudinal semantic dementia cohort.

BACKGROUND AND PURPOSE: Total intracranial volume (TIV) as a measure of premorbid brain size is often used to correct volumes of interest for interindividual differences in magnetic resonance imaging (MRI) studies. We directly compared the reliability of different TIV estimation methods to address whether such methods are influenced by brain atrophy in the neurodegenerative disease, semantic dementia. METHODS: We contrasted several manual approaches using T1-weighted, T2-weighted, and proton density (PD) acquisitions with 2 automated methods (statistical parametric mapping 5 [SPM5] and FreeSurfer [FS]) in a cohort of semantic dementia subjects (n= 11) that had been imaged longitudinally. RESULTS: Novel mid-cranial sampling of either PD or T2-weighted images were least susceptible to atrophy: of these, the PD method was both more precise and more user-friendly. SPM5 also produced good results, providing automation for only a small loss in precision compared to the best manual methods. The T1 method that underestimated TIV as atrophy progressed was the least reproducible and the most labor-intensive. Fully automated FS overestimated TIV with progressive atrophy, and the results were even worse after optimizing the transformation. CONCLUSION: The mid-cranial sampling of PD images achieved the best combination of precision, reliability, and user-friendliness. SPM5 is an attractive alternative if the highest level of precision is not required.

Impact of inconsistent resolution on VBM studies.

This paper considers the effects of using magnetic resonance scans with different voxel dimensions in voxel-based morphometry studies. This is of potential relevance to many longitudinal studies or any ad-hoc study that relies on pre-existing databases of subjects. In order to study this effect, a group of controls were contrasted with a group of semantic dementia as well as with a group of Alzheimer's disease patients using a mixture of different voxel dimensions scans on each side of the statistical test. Scans were interpolated using a sinc function in order to obtain a different voxel depth. The effects were measured by comparing the output of each analysis to the benchmark in which all scans had the original depth (and highest resolution), both visually and through the computation of the root-mean-square error difference between the resulting t-maps. It was shown that the impact is highly dependent on the scan itself, with some images showing more robustness to the interpolation process, and hence yielding fewer differences. A measure of robustness is proposed, which may be used in order to understand the impact of mixing different dimensions or adjusting them for each scan. Indiscriminate use of voxel dimensions on both groups was found to produce more errors (false positives/false negatives) than does an approach involving the use of balanced groups and a voxel dimension nuisance covariate.

The impact of skull-stripping and radio-frequency bias correction on grey-matter segmentation for voxel-based morphometry.

This study evaluates the application of (i) skull-stripping methods (hybrid watershed algorithm (HWA), brain surface extractor (BSE) and brain-extraction tool (BET2)) and (ii) bias correction algorithms (nonparametric nonuniform intensity normalisation (N3), bias field corrector (BFC) and FMRIB's automated segmentation tool (FAST)) as pre-processing pipelines for the technique of voxel-based morphometry (VBM) using statistical parametric mapping v.5 (SPM5). The pipelines were evaluated using a BrainWeb phantom, and those that performed consistently were further assessed using artificial-lesion masks applied to 10 healthy controls compared to the original unlesioned scans, and finally, 20 Alzheimer's disease (AD) patients versus 23 controls. In each case, pipelines were compared to each other and to those from default SPM5 methodology. The BET2+N3 pipeline was found to produce the least miswarping to template induced by real abnormalities, and performed consistently better than the other methods for the above experiments. Occasionally, the clusters of significant differences located close to the boundary were dragged out of the glass-brain projections -- this could be corrected by adding background noise to low-probability voxels in the grey matter segments. This method was confirmed in a one-dimensional simulation and was preferable to threshold and explicit (simple) masking which excluded true abnormalities.