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Background: Misdiagnosis is common in multiple sclerosis (MS) as a proportion of patients present with atypical clinical/magnetic resonance imaging (MRI) findings. The central vein sign has the potential to be a non-invasive, MS-specific biomarker. Objective: To test the accuracy of the central vein sign in predicting a diagnosis of MS in patients with diagnostic uncertainty at disease presentation using T2*-weighted, 3 T MRI. Methods: In this prospective pilot study, we recruited individuals with symptoms unusual for MS but with brain MRI consistent with the disease, and those with a typical clinical presentation of MS whose MRI did not suggest MS. We calculated the proportion of lesions with central veins for each patient and compared the results to the eventual clinical diagnoses. The optimal central vein threshold for diagnosis was established. Results: Thirty-eight patients were scanned, 35 of whom have received a clinical diagnosis. Median percentage of lesions with central veins was 51% in MS and 28% in non-MS. A threshold of 40.7% lesions with central veins resulted in 100% sensitivity and 73.9% specificity. Conclusion: The central vein sign assessed with a clinically available T2* scan can successfully diagnose MS in cases of diagnostic uncertainty. The central vein sign should be considered as a diagnostic biomarker in MS.

Automated segmentation of tumor epithelial tissue from histological images is a fundamental aspiration of digital pathology to improve biomarker assessment and tissue diagnosis. Accurate tumour segmentation is an important step in many automated digital image analysis applications to be used in clinical practice. In particular, segmentation of tumour, non-tumour epithelium and stromal tissue compartments on immunohistochemistry images presents a challenge. Many artifacts, such as staining and/or illumination variations, can confound image analysis. In this paper, we propose a cascade-learning approach which can diminish the impact of these artifacts. It consists of (a) a set of novel invariant features that encodes meaningful information about the appearance and shape of the region of interest and (b) a novel level set formulation where contour evolution is driven by a probabilistic model of the appearance of the region (based on fuzzy c-means). The merit of our approach is that it exploits both appearance and shape information and combines them in the tissue classification framework. We evaluate the performance of our approach on the segmentation of tumour epithelium in colorectal cancer. The experimental results show that our approach is robust to staining differences, additive noise, intensity inhomogeneities, and can cope with a limited number of training samples, when compared to the state-of-the-art tumour epithelial segmentation methods.

Very brief description of the PsychoPy/PsychoJS/Pavlovia project, where it came from and where it's going in the next year or so. This is a Powerpoint version of the slides (originally presented as a web page).

Many researchers in the behavioral sciences depend on research software that presents stimuli, and records response times, with sub-millisecond precision. There are a large number of software packages with which to conduct these behavioral experiments and measure response times and performance of participants. Very little information is available, however, on what timing performance they achieve in practice. Here we report a wide-ranging study looking at the precision and accuracy of visual and auditory stimulus timing and response times, measured with a Black Box Toolkit. We compared a range of popular packages: PsychoPy, E-Prime®, NBS Presentation®, Psychophysics Toolbox, OpenSesame, Expyriment, Gorilla, jsPsych, Lab.js and Testable. Where possible, the packages were tested on Windows, macOS, and Ubuntu, and in a range of browsers for the online studies, to try to identify common patterns in performance. Among the lab-based experiments, Psychtoolbox, PsychoPy, Presentation and E-Prime provided the best timing, all with mean precision under 1 millisecond across the visual, audio and response measures. OpenSesame had slightly less precision across the board, but most notably in audio stimuli and Expyriment had rather poor precision. Across operating systems, the pattern was that precision was generally very slightly better under Ubuntu than Windows, and that macOS was the worst, at least for visual stimuli, for all packages. Online studies did not deliver the same level of precision as lab-based systems, with slightly more variability in all measurements. That said, PsychoPy and Gorilla, broadly the best performers, were achieving very close to millisecond precision on several browser/operating system combinations. For response times (measured using a high-performance button box), most of the packages achieved precision at least under 10 ms in all browsers, with PsychoPy achieving a precision under 3.5 ms in all. There was considerable variability between OS/browser combinations, especially in audio-visual synchrony which is the least precise aspect of the browser-based experiments. Nonetheless, the data indicate that online methods can be suitable for a wide range of studies, with due thought about the sources of variability that result. The results, from over 110,000 trials, highlight the wide range of timing qualities that can occur even in these dedicated software packages for the task. We stress the importance of scientists making their own timing validation measurements for their own stimuli and computer configuration.

There is currently no brain atlas available to specifically determine stereotaxic coordinates for neurosurgery in Lister hooded rats despite the popularity of this strain for behavioural neuroscience studies in the United Kingdom and elsewhere. We have created a dataset, which we refer to as ‘Ratlas-LH’ (for Lister hooded). Ratlas-LH combines in vivo magnetic resonance images of the brain of young adult male Lister hooded rats with ex vivo micro-computed tomography images of the ex vivo skull, as well as a set of delineations of brain regions, adapted from the Waxholm Space Atlas of the Sprague Dawley Rat Brain. Ratlas-LH was produced with an isotropic resolution of 0.15 mm. It has been labelled in such a way as to provide a stereotaxic coordinate system for the determination of distances relative to the skull landmark of bregma. We have demonstrated that the atlas can be used to determine stereotaxic coordinates to accurately target brain regions in the Lister hooded rat brain. Ratlas-LH is freely available to facilitate neurosurgical procedures in the Lister hooded rat.

Malignant melanoma is one of the most aggressive forms of skin cancer. Early detection is important as it significantly improves survival rates. Consequently, accurate discrimination of malignant skin lesions from benign lesions such as seborrheic keratoses or benign nevi is crucial, while accurate computerised classification of skin lesion images is of great interest to support diagnosis. In this paper, we propose a fully automatic computerised method to classify skin lesions from dermoscopic images. Our approach is based on a novel ensemble scheme for convolutional neural networks (CNNs) that combines intra-architecture and inter-architecture network fusion. The proposed method consists of multiple sets of CNNs of different architecture that represent different feature abstraction levels. Each set of CNNs consists of a number of pre-trained networks that have identical architecture but are fine-tuned on dermoscopic skin lesion images with different settings. The deep features of each network were used to train different support vector machine classifiers. Finally, the average prediction probability classification vectors from different sets are fused to provide the final prediction. Evaluated on the 600 test images of the ISIC 2017 skin lesion classification challenge, the proposed algorithm yields an area under receiver operating characteristic curve of 87.3% for melanoma classification and an area under receiver operating characteristic curve of 95.5% for seborrheic keratosis classification, outperforming the top-ranked methods of the challenge while being simpler compared to them. The obtained results convincingly demonstrate our proposed approach to represent a reliable and robust method for feature extraction, model fusion and classification of dermoscopic skin lesion images.

BACKGROUND AND AIMS Immunohistochemistry (IHC) is an essential component of biomarker research in cancer. Automated biomarker quantification is hampered by the failure of computational algorithms to discriminate 'negative' tumour cells from 'negative' stromal cells. We sought to develop an algorithm for segmentation of tumour epithelium in colorectal cancer (CRC), irrespective of the biomarker expression in the cells. METHODS AND RESULTS We developed tumour parcellation and quantification (TuPaQ) to segment tumour epithelium and parcellate sections into 'epithelium' and 'non-epithelium'. TuPaQ comprises image pre-processing, extraction of regions of interest (ROIs) and quantification of tumour epithelium (total area occupied by epithelium and number of nuclei in the occupied area). A total of 286 TMA cores from CRC were manually annotated and analysed using the commercial halo software to provide ground truth. The performance of TuPaQ was evaluated against the ground truth using a variety of metrics. The image size of each core was 7000 × 7000 pixels and each core was analysed in a matter of seconds. Pixel × pixel analysis showed a sensitivity of 84% and specificity of 95% in detecting epithelium. The mean tumour area obtained by TuPaQ was very close to the area quantified after manual annotation (r = 0.956, P < 0.001). Moreover, quantification of tumour nuclei by TuPaQ correlated very strongly with that of halo (r = 0.891, P < 0.001). CONCLUSION TuPaQ is a very rapid and accurate method of separating the epithelial and stromal compartments of colorectal tumours. This will allow more accurate and objective analysis of immunohistochemistry.

ObjectiveTo determine whether the assessment of brain white matter lesion (WML) central veins differentiate patients with primary progressive MS (PPMS) from relapsing-remitting MS (RRMS) and ischemic small vessel disease (SVD) using 3T MRI.MethodsIn this cross-sectional study, 71 patients with PPMS, RRMS, and SVD were imaged using a T2*-weighted sequence. Two blinded raters identified the total number of WMLs, proportion of WMLs in periventricular, deep white matter (DWM) and juxtacortical regions, and proportion of WMLs with central veins in all patient groups. The proportions were compared between disease groups, including effect sizes. MS or SVD was categorized using a threshold of ≥40% WMLs with central veins as indicative of MS. Interrater and intrarater reproducibility was calculated.ResultsThe mean proportion of WMLs with central veins was 68.4% in PPMS, 74.3% in RRMS, and 4.7% in SVD. The difference in proportions between PPMS and SVD groups was significant (p < 0.0005; effect size: 3.8) but not significant between MS subtypes (p = 0.3; effect size: 0.29). Distribution of WMLs was similar across both MS groups, but despite SVD patients having more DWM lesions than PPMS patients, proportions of WMLs with central veins remained low (2.75% in SVD; 62.5% in PPMS). Interrater and intrarater reproducibility comparing proportions of WMLs with central veins across all patients was 0.86 and 0.90, respectively. Level of agreement between the proportion of WML central veins and established diagnosis was 0.84 and 0.82 for each rater.ConclusionsWML central veins could be used to differentiate PPMS from SVD but not between MS subtypes.

Background \ud \ud Recent studies have shown that the brain of patients with gastrointestinal disease differ both structurally and functionally from that of controls. Highly somatizing diverticular disease (HSDD) patients were also shown to differ from low somatizing (LSDD) patients functional-ly. This study aimed to investigate how they differed structurally.\ud \ud Methods \ud \ud Four diseases subgroups were studied in a cross-sectional design: 20 patients with asympto-matic diverticular disease (ADD), 18 LSDD, 16 HSDD, and 18 with irritable bowel syn-drome. We divided DD patients into LSDD and HSDD using a cutoff of 6 on the Patient Health Questionnaire 12 Somatic Symptom (PHQ12-SS) scale. All patients underwent a 1-mm isotropic structural brain MRI scan and were assessed for somatization, hospital anxiety, depression, and pain catastrophizing. Whole brain volumetry, cortical thickness analysis and voxel-based morphometry were carried out using Freesurfer and SPM.\ud \ud Key Results \ud \ud We observed decreases in grey matter density in the left and right dorso-lateral prefrontal cortex (dlPFC), and in the mid-cingulate and motor cortex, and increases in the left (19, 20) and right (19, 38) Brodmann Areas. The average cortical thickness differed overall across groups (P=0.002) and regionally: HSDD>ADD in the posterior cingulate cortex (P=0.03), HSDD>LSDD in the dlPFC (P=0.03) and in the ventro-lateral PFC (P

Verbal irony is a figure of speech that communicates the opposite of what is said, while sarcasm is a form of irony that is directed at a person, with the intent to criticise. The current study used functional magnetic resonance imaging (fMRI) with the aim of mapping the neural networks involved in the processing of sarcastic and non-sarcastic irony. Participants read short texts describing an interaction between two characters, which ended in either a literal, sarcastic, or non-sarcastic ironic comment. Results showed that the mentalising network (mPFC) and semantic network (IFG) were more activated for non-sarcastic irony than for literal controls. This would suggest that interpreting this kind of language involves understanding that the speaker does not mean what they literally say, as well as processes involved in conflict detection and resolution. Sarcastic irony recruited more of the semantic network, as well as areas associated with humour appreciation and subcortical structures, indicating that more complex neural mechanisms underlie the comprehension of sarcastic versus non-sarcastic irony.

One of the main challenges in cancer surgery is ensuring that all tumour cells are removed during surgery, while sparing as much healthy tissue as possible. Histopathology, the gold-standard technique for cancer diagnosis, is often impractical for intra-operative use because of the time-consuming tissue preparation procedures (sectioning and staining). Raman micro-spectroscopy is a powerful technique that can discriminate between tumours and healthy tissues with high accuracy, based entirely on intrinsic chemical differences. However, raster-scanning Raman micro-spectroscopy is a slow imaging technique that typically requires data acquisition times as long as several days for typical tissue samples obtained during surgery (1 × 1 cm 2 ) – in particular when high signal-to-noise ratio spectra are required to ensure accurate diagnosis. In this paper we present two techniques based on selective sampling Raman micro-spectroscopy that can overcome these limitations. In selective sampling, information regarding the spatial features of the tissue, either measured by an alternative optical technique or estimated in real-time from the Raman spectra, can be used to drastically reduce the number of Raman spectra required for diagnosis. These sampling strategies allowed diagnosis of basal cell carcinoma in skin tissue samples excised during Mohs micrographic surgery faster than frozen section histopathology, and two orders of magnitude faster than previous techniques based on raster-scanning Raman microscopy. Further development of these techniques may help during cancer surgery by providing a fast and objective way for surgeons to ensure the complete removal of tumour cells while sparing as much healthy tissue as possible.

The aim of this study was to optimise a pulse sequence for high-resolution imaging sensitive to the effects of conventional macromolecular magnetisation transfer (MTm) and nuclear Overhauser enhancement (NOE), and to use it to investigate variations in these parameters across the cerebral cortex. A high-spatial-resolution magnetisation transfer-prepared turbo field echo (MT-TFE) sequence was designed to have high sensitivity to MTm and NOE effects, whilst being robust to B0 and B1 inhomogeneities, and producing a good point spread function across the cortex. This was achieved by optimising the saturation and imaging components of the sequence using simulations based on the Bloch equations, including exchange and an image simulator. This was used to study variations in these parameters across the cortex. Using the sequence designed to be sensitive to NOE and MTm, a variation in signals corresponding to a variation in MTm and NOE across the cortex, consistent with a reduction in myelination from the white matter surface to the pial surface of the cortex, was observed. In regions in which the stria was visible on T2*-weighted images, it could also be detected in signals sensitive to MTm and NOE. There was greater variation in signals sensitive to NOE, suggesting that the NOE signal is more sensitive to myelination. A sequence has been designed to image variations in MTm and NOE at high spatial resolution and has been used to investigate variations in contrast in these parameters across the cortex. Copyright © 2013 John Wiley & Sons, Ltd.

Purpose To present an improved three-dimensional (3D) interleaved phase sensitive inversion recovery (PSIR) sequence including a concomitantly acquired new contrast, null point imaging (NPI), to help detect and classify abnormalities in cortical gray matter. Methods The 3D gradient echo PSIR images were acquired at 0.6 mm isotropic resolution on 11 multiple sclerosis (MS) patients and 9 controls subjects using a 7 Tesla (T) MRI scanner, and 2 MS patients at 3T. Cortical abnormalities were delineated on the NPI/PSIR data and later classified according to position in the cortex. Results The NPI helped detect cortical lesions within the cortical ribbon with increased, positive contrast compared with the PSIR. It also provided improved intrinsic delineation of the ribbon, increasing confidence in classifying the lesions' locations. Conclusion The proposed PSIR facilitates the classification of cortical lesions by providing two T1-weighted 3D datasets with isotropic resolution, including the NPI showing cortical lesions with clear delineation of the gray/white matter boundary and minimal partial volume effects. Magn Reson Med 76:1512–1516, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Patch-based Multi-Atlas Segmentation methods typically transform a priori expert delineations of atlas images onto a new target image where they are fused based on local patch similarities. To improve efficiency and accuracy, we build a population template offline and a Target-Specific Template (TST) at runtime, which act as intermediate steps. At the regional level, we build a manifold for each label rather than globally, and from the deformation fields rather than from images, in order to better model the geometry of atlases and target with the aim to improve the similarity between TST and target. At the local level, we further refine the resulting weights in those areas prone to registration errors with patches sampled from the warped- and target-gray matter probability images. We evaluated our approach on the standard NIREP dataset for which it achieved state-of-the-art performance while being up to 16 times faster than competing approaches.

Adolescence is characterized by major developmental changes that may render the individual vulnerable to stress and the development of psychopathologies in a sex-specific manner. Earlier we reported lower anxiety-like behavior and higher risk-taking and novelty seeking in rats previously exposed to peri-pubertal stress. Here we studied whether pen-pubertal stress affected the acquisition and extinction of fear memories and/or the associated functional engagement of various brain regions, as assessed with 2-deoxyglucose. We showed that while pen-pubertal stress reduced freezing during the acquisition of fear memories (training) in both sexes, it had a sex-specific effect on extinction of these memories. Moreover hippocampus, basal amygdala and cingulate and motor cortices showed higher metabolic rates during extinction in rats exposed to pen-pubertal stress. Interestingly, activation of the infralimbic cortex was negatively correlated with freezing during extinction only in control males, while only males stressed during puberty showed a significant correlation between behavior during extinction and metabolic activation of hippocampus, amygdala and paraventricular nucleus. No correlations between brain activation and behavior during extinction were observed in females (control or stress). These results indicate that exposure to pen-pubertal stress affects behavior and brain metabolism when the individual is exposed to an additional stressful challenge. Some of these effects are sex-specific. (C) 2012 Elsevier Inc. All rights reserved.

Here we examined sex differences in the volumes of grey and white matter, and in grey-matter "density," in a group of typically developing adolescents participating in the Saguenay Youth Study (n=419; 12-18 years). In male adolescents, we also investigated the role of a functional polymorphism in androgen-receptor gene (AR) in moderating the effect of testosterone on volumes of grey and white matter and grey-matter density. Overall, both absolute and relative volumes of white matter were larger in male vs. females adolescents. The relative grey-matter volumes were slightly larger in female than male adolescents and so was the grey-matter density in a large number of cortical regions. In male adolescents, functional polymorphism of AR moderated the effect of testosterone on relative white- and grey-matter volumes. Following a discussion of several methodological and interpretational issues, we outline future directions in investigating brain-behavior relationships vis-à-vis psychopathology.

With anatomical magnetic resonance imaging, the signal intensity of the corticospinal tract (CST) at the level of the internal capsule is often paradoxically similar to that of grey matter. As shown previously in histological studies, this is likely due to the presence of very large axons. We measured the apparent grey‐matter density (aGMd) of the putative CST (pCST) in a large cohort of adolescents (n = 409, aged 12–18 years). We tested the following hypotheses: (1) The aGMd in the pCST shows a hemispheric asymmetry that is, in turn, related to hand preference; (2) the maturation of the CST during adolescence differs between both sexes, due to the influence of testosterone; (3) variations in aGMd in the pCST reflect inter‐individual differences in manual skills. We confirmed the first two predictions. Thus, we found a strong left > right hemispheric asymmetry in aGMd that was, on average, less marked in the 40 left‐handed subjects. Apparent GMd in the pCST increased with age in adolescent males but not females, and this was particularly related to rising plasma levels of testosterone in male adolescents. This finding is compatible with the idea that testosterone influences axonal calibre rather than myelination. The third prediction, namely that of a relationship between age‐related changes in manual skills and maturation of the pCST, was not confirmed. We conclude that the leftward asymmetry of the pCST may reflect an early established asymmetry in the number of large corticomotoneuronal fibres in the pCST. Hum Brain Mapp, 2009. © 2009 Wiley‐Liss, Inc.

The purpose of this study was to examine sex differences in the maturation of white matter during adolescence (12 to 18 years of age). We measured lobular volumes of white matter and white-matter “density” throughout the brain using T1-weighted images, and estimated the myelination index using magnetisation-transfer ratio (MTR). In male adolescents, we observed age-related increases in white-matter lobular volumes accompanied by decreases in the lobular values of white-matter MTR. White-matter density in the putative cortico-spinal tract (pCST) decreased with age. In female adolescents, on the other hand, we found only small age-related increase in white-matter volumes and no age-related changes in white-matter MTR, with the exception of the frontal lobe where MTR increased. White-matter density in the pCST also increased with age. These results suggest that sex-specific mechanisms may underlie the growth of white matter during adolescence. We speculate that these mechanisms involve primarily age-related increases in axonal calibre in males and increased myelination in females.

Teratogens, such as alcohol or anti-epileptic drugs, affect the size of the corpus callosum. Here we report findings obtained in a case-control study that investigated possible effects of teratogens contained in cigarette smoke on the size and structural properties of this structure. We recruited and scanned with magnetic resonance imaging a total of 408 adolescents (12 to 18 years of age); a subsample of 300 adolescents is considered in this report. Cases (n=146) were exposed to maternal cigarette smoking during pregnancy; non-exposed controls (n=154) were matched to cases by maternal education. We measured the size of corpus callosum (CC) and its sections (corrected for brain size), as well as mean values of magnetization-transfer ratio (MTR) in each CC section. Corpus callosum, and especially its posterior part, was smaller in the exposed vs. non-exposed female adolescents; no significant effects were found in males. Exposed and non-exposed subjects did not differ in the MTR-based index of myelination in either gender in any CC section. Given the lack of exposure effect on the myelination index, this finding might reflect a lower number of inter-hemispheric connections in female offspring of mothers who smoked during pregnancy.

This manuscript tackles the reconstruction of 3-D volumes via mono-modal registration of series of 2-D biological images (histological sections, autoradiographs, cryosections, etc.). The process of acquiring these images typically induces composite transformations that we model as a number of rigid or affine local transformations embedded in an elastic one. We propose a registration approach closely derived from this model. Given a pair of input images, we first compute a dense similarity field between them with a block matching algorithm. We use as a similarity measure an extension of the classical correlation coefficient that improves the consistency of the field. A hierarchical clustering algorithm then automatically partitions the field into a number of classes from which we extract independent pairs of sub-images. Our clustering algorithm relies on the Earth mover’s distribution metric and is additionally guided by robust least-square estimation of the transformations associated with each cluster. Finally, the pairs of sub-images are, independently, affinely registered and a hybrid affine/non-linear interpolation scheme is used to compose the output registered image. We investigate the behavior of our approach on several batches of histological data and discuss its sensitivity to parameters and noise.

Background Cortical lesions account for a larger proportion of brain demyelination than white matter (WM) lesions. They are often missed on conventional MRI. Recently studies improved the detection of cortical lesions using 7T T2 ⁎ , 7T MPRAGE and 3T DIR but it seems that we are still able to detect only "the tip of the iceberg". In this study we report for the first time the systematic use of high resolution MTR in MS and compare MTR lesion detection with 7T MPRAGE, 7T T2 ⁎ and 3T 3D DIR. Objectives We report the use of high resolution, fast, magnetisation transfer imaging (MTI) at 7T in MS focusing on the detection of cortical lesions. Subjects and methods Eighteen patients with MS were scanned (Expanded Disability Status Scale score: 3.0, mean age: 48 years, mean disease duration: 7.25 years). The scans were compared to nine healthy control subjects (mean age 36.5 years). Data acquisition We acquired 7T MPRAGE images, 7T MTR maps, 7T T2 ⁎ and 3T 3D DIR. The WM was segmented from the MPRAGE and removed to obtain only the cortical grey matter ribbon (cGMR) mask. The mask was then applied to the different modalities (MPRAGE, MTR, DIR, T2 ⁎ w) previously registered onto the MPRAGE volume. The analysis of the cGMR was performed by two observers blinded to the disease state. Results In patients with MS 365 lesions in total were detected with 7T MTR (mean 20.28 lesions per patient), 289 lesions were detected with 7T MPRAGE (mean 16.06 lesions) and 231 lesions were detected with 7T T2 ⁎ (mean 12.83 lesions). In the 8 MS subjects who had 3T 3D DIR acquired on the same day, a total of 136 lesions (mean 17 lesions per patient) were detected as opposed to 171 lesions with 7T MTR, 147 lesions were detected with 7T MPRAGE and 126 lesions with 7T T2 ⁎ in the same patients. Conclusion We found that 7T MTR, in less than 10min scanning time, was able to detect cortical lesions. In this study we found that 7T MTR was better in detecting intracortical lesions in comparison with 7T T2 ⁎ , 7T MPRAGE, and 3T 3D DIR. since only a very few intracortical lesions were detected in healthy controls in our blind assessment, it is likely that the lesions detected represent focal grey matter demyelination. High resolution MT imaging has especially revealed cortical changes that have not been recognised by other MR sequences. MTR maps were noisier than MPRAGE, T2 ⁎ and DIR, but also better in localising cortical lesions. As MTR is more pathologically specific than other sequences in detecting tissue myelination, it raises the possibility that high resolution MTR will be able to demonstrate cortical remyelination in vivo .

The aim of this study was to optimise a pulse sequence for high-resolution imaging sensitive to the effects of conventional macromolecular magnetisation transfer (MT(m)) and nuclear Overhauser enhancement (NOE), and to use it to investigate variations in these parameters across the cerebral cortex. A high-spatial-resolution magnetisation transfer-prepared turbo field echo (MT-TFE) sequence was designed to have high sensitivity to MT(m) and NOE effects, whilst being robust to B0 and B1 inhomogeneities, and producing a good point spread function across the cortex. This was achieved by optimising the saturation and imaging components of the sequence using simulations based on the Bloch equations, including exchange and an image simulator. This was used to study variations in these parameters across the cortex. Using the sequence designed to be sensitive to NOE and MT(m), a variation in signals corresponding to a variation in MT(m) and NOE across the cortex, consistent with a reduction in myelination from the white matter surface to the pial surface of the cortex, was observed. In regions in which the stria was visible on T2*-weighted images, it could also be detected in signals sensitive to MT(m) and NOE. There was greater variation in signals sensitive to NOE, suggesting that the NOE signal is more sensitive to myelination. A sequence has been designed to image variations in MT(m) and NOE at high spatial resolution and has been used to investigate variations in contrast in these parameters across the cortex.

Background There is no absolute biomarker for the diagnosis of multiple sclerosis (MS). White matter lesion (WML) central veins detected using T2* weighted imaging is proving promising. Objectives To confirm if the proportion of WMLs with central veins can predict the clinical diagnosis in a cohort of patients with diagnostic uncertainty of MS. Methods Patients had a 3T T2* weighted MRI scan and then followed up by their neurologists until a diagnosis was confirmed. The T2* scan was reviewed by a rater blinded to all clinical data and a radiological diagnosis of MS or non-MS made, based purely on the proportion of WMLs with central veins (≥40%=MS). A simpler diagnostic rule of identifying 6 WMLs with central veins for a diagnosis of MS was also employed. Results Of the 22 patients scanned to date, 10 patients have received a clinical diagnosis. Two of three patients who were diagnosed with MS had more than 40% of WMLs with central veins. The remaining 7 patients who were diagnosed as non-MS had less than 40% of WMLs with central veins. 9/10 MRI diagnoses appear to be correct. Identifying a subset of 6 WMLs with central veins led to 8/10 correct diagnoses. Conclusions WML central veins appear to be of value in the diagnostic process for MS when other tests fail at initial presentation.

Histological tissue preparation stages (e.g., cutting, sectioning, etc.) often introduce tissue distortions that prevent a smooth 3D reconstruction from being built. In this paper, we propose a method to correct histology distortions by running a piecewise registration scheme. It takes the information of several consecutive slices in a neighborhood into account. In order to achieve an accurate anatomic presentation, we run the method iteratively with the assistance from a pre-segmented brain atlas. The registration parameters are optimized to accommodate different brain sub-regions, e.g., cerebellum, hippocampus, etc. The results are evaluated by both visual and quantitative approaches. The proposed method has been proved to be robust enough for reconstructing an accurate and smooth mouse brain volume.

This paper tackles two problems: (1) the reconstruction of 3-D volumes from 2-D post-mortem slices (e.g., histology, autoradiography, immunohistochemistry) in the absence of external reference, and (2) the quantitative evaluation of the 3-D reconstruction. We note that the quality of a reconstructed volume is usually assessed by considering the smoothness of some reconstructed structures of interest (e.g., the gray–white matter surfaces in brain images). Here we propose to use smoothness as a means to drive the reconstruction process itself. From a pair-wise rigid reconstruction of the 2-D slices, we first extract the boundaries of structures of interest. Those are then smoothed with a min–max curvature flow confined to the 2-D planes in which the slices lie. Finally, for each slice, we estimate a linear or flexible transformation from the sparse displacement field computed from the flow, which we apply to the original 2-D slices to obtain a smooth volume. In addition, we present a co-occurrence matrix-based technique to quantify the smoothness of reconstructed volumes. We discuss and validate the application of both our reconstruction approach and the smoothness measure on synthetic examples as well as real histological data.

Inter-subject parcellation of functional Magnetic Resonance Imaging (fMRI) data based on a standard General Linear Model (GLM) and spectral clustering was recently proposed as a means to alleviate the issues associated with spatial normalization in fMRI. However, for all its appeal, a GLM-based parcellation approach introduces its own biases, in the form of a priori knowledge about the shape of Hemodynamic Response Function (HRF) and task-related signal changes, or about the subject behaviour during the task. In this paper, we introduce a data-driven version of the spectral clustering parcellation, based on Independent Component Analysis (ICA) and Partial Least Squares (PLS) instead of the GLM. First, a number of independent components are automatically selected. Seed voxels are then obtained from the associated ICA maps and we compute the PLS latent variables between the fMRI signal of the seed voxels (which covers regional variations of the HRF) and the principal components of the signal across all voxels. Finally, we parcellate all subjects data with a spectral clustering of the PLS latent variables. We present results of the application of the proposed method on both single-subject and multi-subject fMRI datasets. Preliminary experimental results, evaluated with intra-parcel variance of GLM t-values and PLS derived t-values, indicate that this data-driven approach offers improvement in terms of parcellation accuracy over GLM based techniques.

The aim of this study was to quantify changes in brain volume after exercise/heat-induced hypohydration in man.Eight active men completed intermittent exercise in a warm environment, until 2.9% ± 0.1% of body mass was lost. Subjects remained hypohydrated for 2 h after the end of exercise. Brain volume was measured before, immediately after, and 1 and 2 h after exercise using magnetic resonance imaging (Philips 3T Achieva, AE Eindhoven, The Netherlands). Measures of subjective feelings and core body temperature were also monitored. Blood samples were drawn to determine serum electrolyte concentrations and osmolality and to allow calculation of changes in blood and plasma volumes.Brain volume was not influenced by hypohydration (0.2% ± 0.4%; effect size (ES) = 0.2, P = 0.310). Reductions in ventricular (4.0% ± 1.8%; ES = 4.6, P0.001) and cerebrospinal fluid (3.1% ± 1.9%; ES = 3.3, P = 0.003) volumes were observed after exercise. Compared with preexercise levels, serum osmolality was elevated throughout the 2-h postexercise period (+10 ± 2 mOsm·kg, P0.001). Core temperature increased from 37.1°C ± 0.3°C at rest to 39.3°C ± 0.5°C at the end of exercise (P = 0.001).These data demonstrate that brain volume remains unchanged in response to moderate hypohydration and presence of serum hyperosmolality, suggesting that mechanisms are in place to defend brain volume.

We have previously shown that repeated exposure to mild novel cage stress prevents the onset of recent contextual fear memory deficits and attenuated amyloid deposition in the TASTPM mouse model of Alzheimer's disease. Here, we extended this investigation to remote contextual fear memory and extinction. TASTPM and wild-type mice acquired contextual fear at 4 months of age. Retention and extinction of contextual fear were assessed at 5.5 months prior to in vivo MRI assessment of regional T2 relaxation times and brain volumes followed by immunostaining to determine amyloid plaque load. Remote contextual fear memory was preserved in TASTPM mice regardless of the stress condition. Stress impaired extinction in wild-type mice but facilitated this process in TASTPM mice. Genotype-dependent effects of stress were observed on regional T2 times which were prolonged in the subiculum and thalamus of stressed TASTPM, possibly reflecting reduced amyloid pathology. Amyloid plaque load was particularly decreased in the retrosplenial cortex of stressed TASTPM mice, which also showed an overall reduction in the number of diffuse plaques. These findings support the hypothesis that repeated mild levels of stress induced by novel activities can delay the progression of pathological changes relevant to Alzheimer's disease.

International audience; OBJECTIVE:Previous studies have shown smaller brain volume and less gray matter in children with attention-deficit/hyperactivity disorder (ADHD). Relatively few morphological studies have examined structures thought to subserve inhibitory control, one of the diagnostic features of ADHD. We examined one such region, the pars opercularis, predicting a thinner cortex of the inferior frontal gyrus (IFG) in children with ADHD.METHOD:Structural images were obtained from 49 children (24 control; 25 ADHD combined subtype) aged 9 though 15 years. Images were processed using a volumetric pipeline to provide a fully automated estimate of regional volumes of gray and white matter. A further analysis using FreeSurfer provided measures of cortical thickness for each lobe, and for 13 regions in the frontal lobe.RESULTS:Relative to controls, children with ADHD had smaller whole brain volume and lower gray matter, but not white matter, volumes in all lobes. An analysis of frontal regions showed a significant interaction of group by region. Planned contrasts showed bilateral thinner cortex in the pars opercularis in children with ADHD.CONCLUSIONS:Children with ADHD showed both diffuse and regional gray matter abnormalities. Consistent with its putative role in response inhibition, the cortex of the pars opercularis was thinner in children with ADHD who, as expected, had significantly poorer inhibitory performance on a Go/No-go task. These differences held for both hemispheres raising the possibility that a developmental abnormality of IFG might drive development of inhibition difficulties.

Magnetization transfer is an important source of contrast in magnetic resonance imaging which is sensitive to the concentration of macromolecules and other solutes present in the tissue. Magnetization transfer effects can be visualized in magnetization transfer ratio images or quantified via the z-spectrum. This paper presents methods of measuring the z-spectrum and of producing high-resolution MTR images and maps of z-spectrum asymmetry in vivo at 7 T, within SAR limits. It also uses a 3-compartment model to measure chemical exchange and magnetization transfer parameters from the z-spectrum data. The peak in the z-spectrum associated with chemical exchange between amide and water protons (amide proton transfer, APT, effects) is much more apparent at 7 T than at 3 T. Furthermore at 7 T quantitative APT results varied between the corpus callosum and other white matter structures, suggesting that quantitative APT imaging could be used as a method of measuring myelination. The results also suggest that chemical exchange is not responsible for the phase shift observed in susceptibility weighted images between grey matter and white matter.

International audience; A common Single-Nucleotide Polymorphism in the Brain-Derived Neurotrophic Factor (BDNF) gene coding the Val66Met substitution in the pro-BDNF protein has been associated with a number of behavioural and neuroanatomical phenotypes; the latter include, for example, regional differences in volumes of the hippocampus and prefrontal grey matter. Here, we show that the observed regional differences may not stem from a localised effect of this gene. Our analysis of regional brain volume in a cohort of 331 adolescents indicates that the Val66Met substitution has a global effect on brain volume, and that the observed local differences are to be expected if brain allometry-the covariance pattern of regional brain volumes-is taken into account.

Inter-subject parcellation of functional Magnetic Resonance Imaging (fMRI) data based on a standard General Linear Model (GLM) and spectral clustering was recently proposed as a means to alleviate the issues associated with spatial normalization in fMRI. However, for all its appeal, a GLM-based parcellation approach introduces its own biases, in the form of a priori knowledge about the shape of Hemodynamic Response Function (HRF) and task-related signal changes, or about the subject behaviour during the task. In this paper, we introduce a data-driven version of the spectral clustering parcellation, based on Independent Component Analysis (ICA) and Partial Least Squares (PLS) instead of the GLM. First, a number of independent components are automatically selected. Seed voxels are then obtained from the associated ICA maps and we compute the PLS latent variables between the fMRI signal of the seed voxels (which covers regional variations of the HRF) and the principal components of the signal across all voxels. Finally, we parcellate all subjects data with a spectral clustering of the PLS latent variables. We present results of the application of the proposed method on both single-subject and multi-subject fMRI datasets. Preliminary experimental results, evaluated with intra-parcel variance of GLM t-values and PLS derived t-values, indicate that this data-driven approach offers improvement in terms of parcellation accuracy over GLM based techniques.

Inter-subject parcellation of functional Magnetic Resonance Imaging (fMRI) data based on a standard General Linear Model (GLM) and spectral clustering was recently proposed as a means to alleviate the issues associated with spatial normalization in fMRI. However, for all its appeal, a GLM-based parcellation approach introduces its own biases, in the form of a priori knowledge about the shape of Hemodynamic Response Function (HRF) and task-related signal changes, or about the subject behaviour during the task. In this paper, we introduce a data-driven version of the spectral clustering parcellation, based on Independent Component Analysis (ICA) and Partial Least Squares (PLS) instead of the GLM. First, a number of independent components are automatically selected. Seed voxels are then obtained from the associated ICA maps and we compute the PLS latent variables between the fMRI signal of the seed voxels (which covers regional variations of the HRF) and the principal components of the signal across all voxels. Finally, we parcellate all subjects data with a spectral clustering of the PLS latent variables. We present results of the application of the proposed method on both single-subject and multi-subject fMRI datasets. Preliminary experimental results, evaluated with intra-parcel variance of GLM t-values and PLS derived t-values, indicate that this data-driven approach offers improvement in terms of parcellation accuracy over GLM based techniques.

Brain atlases are commonly used in a number of applications such as MRI segmentation and surgery targetting. Our goal is to register a basal ganglia atlas to a subject using MR image registration. Existing registration methods are for the most part either too constrained (linear registration) or can deform deep brain ROIs into implausible anatomical shapes. We developed a block-matching registration method suitable for atlas registration, using a new confidence-based regularization of the vector field. The method was used to register a set of 17 manually segmented MRI onto one subject. Results show that basal ganglia structures were better registered than when using an affine registration method.

The growth of white matter during human adolescence shows a striking sexual dimorphism; the volume of white matter increases with age slightly in girls and steeply in boys. Here, we provide evidence supporting the role of androgen receptor (AR) in mediating the effect of testosterone on white matter. In a large sample of typically developing adolescents (n= 408, 204 males), we used magnetic resonance imaging and acquired T1-weighted and magnetization transfer ratio (MTR) images. We also measured plasma levels of testosterone and genotyped a functional polymorphism in the AR gene, namely the number of CAG repeats in exon 1 believed to be inversely proportional to the AR transcriptional activity. We found that the testosterone-related increase of white-matter volume was stronger in male adolescents with the lower versus higher number of CAG repeats in the AR gene, with testosterone explaining, respectively, 26 and 8% of variance in the volume. The MTR results suggest that this growth is not related to myelination; the MTR decreased with age in male adolescents. We speculate that testosterone affects axonal caliber rather than the thickness of the myelin sheath.