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Objective: Cortical thinning, previously identified during prodromal stages of Alzheimer's disease (AD), is a "candidate" biomarker implemented in AD clinical therapy trials. We investigated the effect of donepezil treatment on cortical thickness in mild cognitively impaired subjects with the amnestic syndrome of the hippocampal type, a prodromal at-risk group for progression to AD dementia., Methods: Data were from a longitudinal analysis of a community-based multicenter suspected prodromal AD cohort diagnosed by the Free and Cued Selective Reminding Test (81 donepezil vs 92 placebo) enrolled in a double-blind, randomized, placebo-controlled parallel group design using donepezil (10 mg/day). The study started in November 2006 and concluded in August 2010. All subjects underwent 2 brain structural magnetic resonance imaging (MRI) scans, at baseline and at the end of the trial. Structural MRI images had been processed using the automated pipeline for longitudinal segmentation and surface reconstruction implemented in FreeSurfer. The primary outcome measure of this post hoc study was the annualized percentage change (APC) of cortical thickness., Results: The donepezil group exhibited reduced APC cortical thinning compared to placebo in the rostral anterior cingulate (right: P = .048; left: P = .032), the orbitofrontal (right: P = .012; left: P < .048), and the right inferior frontal (P = .022) cortices and in the right insula (P = .010). These results were not statistically significant after Bonferroni correction likely due to insufficient power for cortical thickness measurements in the study group powered for the predefined hippocampus outcome., Conclusions: Our findings support the hypothesis that cortical thickness is a reliable candidate surrogate outcome in early predementia AD trials. In addition, donepezil treatment may have an impact on cortical structure/morphology in areas innervated by the medial and lateral cholinergic pathways., Trial Registration: ClinicalTrials.gov identifier: NCT00403520., (© Copyright 2016 Physicians Postgraduate Press, Inc.)

We investigated the utility of sulcal width measures in the diagnosis of Alzheimer's disease (AD). Sixty-six biologically confirmed AD patients (positive amyloid positron emission tomography [PET] and/or AD cerebrospinal fluid profile) were contrasted to 35 controls with negative amyloid PET. Patients were classified into prodromal or dementia stages as well as into late onset (LOAD, n = 31) or early onset (EOAD, n = 35) subgroups according to their age of onset. An automated method was used to calculate sulcal widths and hippocampal volumes (HV). In EOAD, the greatest ability to differentiate patients from age-matched controls, regardless of severity, was displayed by sulcal width of the temporoparietal cortex. In this region, diagnosis accuracy was better than the HV, especially at prodromal stage. In LOAD, HV provided the best discrimination power from age-matched controls. In conclusion, sulcal width measures are better markers than the HV for identifying prodromal AD in patients aged <65 years. In contrast, in older patients, the risk of over-diagnosis from using only sulcal enlargement is important., (Copyright © 2015 Elsevier Inc. All rights reserved.)

While the clinical presentation of posterior cortical atrophy is clearly distinct from typical Alzheimer's disease, neuropathological studies have suggested that most patients with posterior cortical atrophy have Alzheimer's disease with an atypical visual presentation. We analysed in vivo pathophysiological markers of Alzheimer's disease such as cerebrospinal fluid biomarkers and positron emission tomography imaging with ¹¹C-labelled Pittsburgh compound-B in posterior cortical atrophy to determine whether biochemical profile and fibrillar amyloid-β burden topography are associated with the clinical presentation. Nine patients with posterior cortical atrophy and nine with typical Alzheimer's disease individually matched for age, duration and severity of the disease and 10 cognitively normal age-matched controls were included. ¹¹C-labelled Pittsburgh compound-B images were analysed both using volumes of interest and on a voxel-wise basis using statistical parametric mapping, taking into account the individual regional cortical atrophy. Cerebrospinal fluid biomarkers did not differ between posterior cortical atrophy and patients with Alzheimer's disease. Compared with normal controls, both posterior cortical atrophy and Alzheimer's disease groups showed increased ¹¹C-labelled Pittsburgh compound-B uptake. No significant difference was found in regional or global ¹¹C-labelled Pittsburgh compound-B binding between posterior cortical atrophy and Alzheimer's disease groups with both volumes of interest and voxel-wise basis using statistical parametric mapping methods. Our findings demonstrate that cerebrospinal fluid biomarkers and positron emission tomography imaging with ¹¹C-labelled Pittsburgh compound-B may be useful in identifying an atypical visual form of Alzheimer's disease. The similar topography of fibrillar amyloid-β deposition between typical Alzheimer's disease and posterior cortical atrophy groups suggests that, although amyloid-β accumulation plays a critical role in the pathogenesis of Alzheimer's disease, other factors such as neurofibrillary tangles may contribute to the different clinical features observed in posterior cortical atrophy.

The alignment and normalization of individual brain structures is a prerequisite for group-level analyses of structural and functional neuroimaging data. The techniques currently available are either based on volume and/or surface attributes, with limited insight regarding the consistent alignment of anatomical landmarks across individuals. This article details a global, geometric approach that performs the alignment of the exhaustive sulcal imprints (cortical folding patterns) across individuals. This DIffeomorphic Sulcal-based COrtical (DISCO) technique proceeds to the automatic extraction, identification and simplification of sulcal features from T1-weighted Magnetic Resonance Image (MRI) series. These features are then used as control measures for fully-3-D diffeomorphic deformations. Quantitative and qualitative evaluations show that DISCO correctly aligns the sulcal folds and gray and white matter volumes across individuals. The comparison with a recent, iconic diffeomorphic approach (DARTEL) highlights how the absence of explicit cortical landmarks may lead to the misalignment of cortical sulci. We also feature DISCO in the automatic design of an empirical sulcal template from group data. We also demonstrate how DISCO can efficiently be combined with an image-based deformation (DARTEL) to further improve the consistency and accuracy of alignment performances. Finally, we illustrate how the optimized alignment of cortical folds across subjects improves sensitivity in the detection of functional activations in a group-level analysis of neuroimaging data.

Neuroimaging at the group level requires spatial normalization of individual structural data. We propose a geometric approach that consists in matching a series of cortical surfaces through diffeomorphic registration of their sulcal imprints. The resulting 3D transforms naturally extends to the entire MRI volumes. The Diffeomorphic Sulcal-based COrtical (DISCO) registration integrates two recent technical outcomes: 1) the automatic extraction, identification and simplification of numerous sulci from T1-weighted MRI data series hereby revealing the sulcal imprint and 2) the measure-based diffeomorphic registration of those crucial anatomical landmarks. We show how the DISCO registration may be used to elaborate a sulcal template which optimizes the distribution of constraints over the entire cortical ribbon. DISCO was evaluated through a group of 20 individual brains. Quantitative and qualitative indices attest how this approach may improve both alignment of sulcal folds and overlay of gray and white matter volumes at the group level.

Focal cortical dysplasia (FCD), a malformation of cortical development, is an important cause of pharmacoresistant epilepsy. Small FCD lesions are difficult to distinguish from normal cortex and remain often overlooked on radiological MRI inspection. This paper presents a method to detect small FCD lesions on T1-MRI relying on surface-based features that model their textural and morphometric characteristics. The automatic detection was performed by a two step classification. First, a vertex-wise classifier based on a neural-network bagging trained on manual labels. Then, a cluster-wise classification designed to remove false positive clusters. The method was tested on 19 patients with small FCD. At the first classification step, 18/19 (95%) lesions were detected. The second classification step kept 13/19 (68%) lesions and decreased efficiently the amount of false positive. This new approach may assist the presurgical evaluation of patients with intractable epilepsy, especially those with unremarkable MRI findings.

Focal cortical dysplasia (FCD) is the most frequent malformation of cortical development in patients with medically intractable epilepsy. On MRI, FCD lesions are not easily differentiable from the normal cortex and defining their spatial extent is challenging. In this paper, we introduce a method to segment FCD lesions on T1-weighted MRI. It relies on two successive three-dimensional deformable models, whose evolutions are based on the level set framework. The first deformable model is driven by probability maps obtained from three MRI features: cortical thickness, relative intensity and gradient. These features correspond to the visual characteristics of FCD and allow discriminating lesions and normal tissues. In a second stage, the previous result is expanded towards the underlying and overlying cortical boundaries, throughout the whole cortical section. The method was quantitatively evaluated by comparison with manually traced labels in 18 patients with FCD. The automated segmentations achieved a strong agreement with the manuals labels, demonstrating the applicability of the method to assist the delineation of FCD lesions on MRI. This new approach may become a useful tool for the presurgical evaluation of patients with intractable epilepsy related to cortical dysplasia.

High-resolution MRI of the brain has made it possible to identify focal cortical dysplasia (FCD) in an increasing number of patients. There is evidence for structural abnormalities extending beyond the visually identified FCD lesion. Voxel-based morphometry (VBM) has the potential of detecting both lesions and extra-lesional abnormalities because it performs a whole brain voxel-wise comparison. However, on T1-weighted MRI, FCD lesions are characterized by a wide spectrum of signal hyperintensity that may compromise the results of the segmentation step in VBM. Our purpose was to investigate gray matter (GM) changes in individual FCD patients using voxel-based morphometry (VBM). In addition, we sought to assess the performance of this technique for FCD detection with respect to lesion intensity using an operator designed to emphasize areas of hyperintense T1 signal. We studied 27 patients with known FCD and focal epilepsy and 39 healthy controls. We compared the GM map of each subject (controls and patients) with the average GM map of all controls and obtained a GM z-score map for each individual. The protocol being designed to achieve a maximal specificity, no differences in GM concentration were found in the control group. The z-score maps showed an increase in GM that coincided with the lesion in 21/27 (78%) patients. Five of the six remaining patients whose lesions were not detected by VBM presented with a strong lesion hyperintensity, and a significant part of their lesion was misclassified as white matter. In 16/27 (59%) patients, there were additional areas of GM increase distant from the primary lesion. Areas of GM decrease were found in 8/27 (30%) patients. In conclusion, individual voxel-based analysis was able to detect FCD in a majority of patients. Moreover, FCD was often associated with widespread GM changes extending beyond the visible lesion. In its current form, however, individual VBM may be unable to detect lesions characterized by strong signal intensity abnormalities.

Purpose: On MRI, focal cortical dysplasia (FCD) is characterized by a combination of increased cortical thickness, hyperintense signal within the dysplastic lesion, and blurred transition between gray and white matter (GM-WM). The visual identification of these abnormal characteristics may be difficult, and it is unclear to what degree these features occur among different FCD lesions. Our purpose was to investigate the pattern of occurrence of abnormal MRI characteristics in FCD by using a set of computational models and to generate quantitative lesion profiling., Methods: A set of voxel-wise operators was applied to high-resolution 3D T1-weighted MRI in 23 patients with histologically proven FCD and 39 healthy controls, creating maps of GM thickness, maps of relative intensity highlighting areas with hyperintense signal, and maps of gradient magnitude modeling the GM-WM transition. All FCD lesions were segmented manually on the T1-weighted MRI., Results: FCD volumes ranged from 734 mm3 to 80,726 mm3 (mean, 8,629 mm3 +/- 16,238). The manually segmented FCD lesions were used to estimate features in the lesional area and to determine possible local variations of each feature by means of a histogram. In 78% of the patients, FCD lesions were characterized by simultaneous GM thickening, hyperintense signal, and blurring of the GM-WM transition. Moreover, in all patients, the FCD lesion had at least two of these three characteristics., Conclusions: The three features occurred regardless of the lesion volume, and they characterized not only large FCD lesions, but also subtle ones that had been overlooked by conventional radiologic inspection before surgery.

Focal cortical dysplasia (FCD), a malformation of cortical development, is an important cause of medically intractable epilepsy. FCD lesions are difficult to distinguish from non-lesional cortex and their delineation on MRI is a challenging task. This paper presents a method to segment FCD lesions on T1-weighted MRI, based on a 3D deformable model, implemented using the level set framework. The deformable model is driven by three MRI features: cortical thickness, relative intensity and gradient. These features correspond to the visual characteristics of FCD and allow to differentiate lesions from normal tissues. The proposed method was tested on 18 patients with FCD and its performance was quantitatively evaluated by comparison with the manual tracings of two trained raters. The validation showed that the similarity between the level set segmentation and the manual labels is similar to the agreement between the two human raters. This new approach may become a useful tool for the presurgical evaluation of patients with intractable epilepsy.