Neurobiological origin of spurious brain morphological changes: A quantitative MRI study.

The high gray-white matter contrast and spatial resolution provided by T1-weighted magnetic resonance imaging (MRI) has made it a widely used imaging protocol for computational anatomy studies of the brain. While the image intensity in T1-weighted images is predominantly driven by T1, other MRI parameters affect the image contrast, and hence brain morphological measures derived from the data. Because MRI parameters are correlates of different histological properties of brain tissue, this mixed contribution hampers the neurobiological interpretation of morphometry findings, an issue which remains largely ignored in the community. We acquired quantitative maps of the MRI parameters that determine signal intensities in T1-weighted images (R1 (=1/T1), R2 *, and PD) in a large cohort of healthy subjects (n = 120, aged 18-87 years). Synthetic T1-weighted images were calculated from these quantitative maps and used to extract morphometry features-gray matter volume and cortical thickness. We observed significant variations in morphometry measures obtained from synthetic images derived from different subsets of MRI parameters. We also detected a modulation of these variations by age. Our findings highlight the impact of microstructural properties of brain tissue-myelination, iron, and water content-on automated measures of brain morphology and show that microstructural tissue changes might lead to the detection of spurious morphological changes in computational anatomy studies. They motivate a review of previous morphological results obtained from standard anatomical MRI images and highlight the value of quantitative MRI data for the inference of microscopic tissue changes in the healthy and diseased brain. Hum Brain Mapp 37:1801-1815, 2016. © 2016 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc

A tensor-based morphometry analysis of regional differences in brain volume in relation to prenatal alcohol exposure

Reductions in brain volumes represent a neurobiological signature of fetal alcohol spectrum disorders (FASD). Less clear is how regional brain tissue reductions differ after normalizing for brain size differences linked with FASD and whether these profiles can predict the degree of prenatal exposure to alcohol. To examine associations of regional brain tissue excesses/deficits with degree of prenatal alcohol exposure and diagnosis with and without correction for overall brain volume, tensor-based morphometry (TBM) methods were applied to structural imaging data from a well-characterized, demographically homogeneous sample of children diagnosed with FASD (n = 39, 9.6–11.0 years) and controls (n = 16, 9.5–11.0 years). Degree of prenatal alcohol exposure was significantly associated with regionally pervasive brain tissue reductions in: (1) the thalamus, midbrain, and ventromedial frontal lobe, (2) the superior cerebellum and inferior occipital lobe, (3) the dorsolateral frontal cortex, and (4) the precuneus and superior parietal lobule. When overall brain size was factored out of the analysis on a subject-by-subject basis, no regions showed significant associations with alcohol exposure. FASD diagnosis was associated with a similar deformation pattern, but few of the regions survived FDR correction. In data-driven independent component analyses (ICA) regional brain tissue deformations successfully distinguished individuals based on extent of prenatal alcohol exposure and to a lesser degree, diagnosis. The greater sensitivity of the continuous measure of alcohol exposure compared with the categorical diagnosis across diverse brain regions underscores the dose dependence of these effects. The ICA results illustrate that profiles of brain tissue alterations may be a useful indicator of prenatal alcohol exposure when reliable historical data are not available and facial features are not apparent

PSACNN: Pulse Sequence Adaptive Fast Whole Brain Segmentation

With the advent of convolutional neural networks~(CNN), supervised learning methods are increasingly being used for whole brain segmentation. However, a large, manually annotated training dataset of labeled brain images required to train such supervised methods is frequently difficult to obtain or create. In addition, existing training datasets are generally acquired with a homogeneous magnetic resonance imaging~(MRI) acquisition protocol. CNNs trained on such datasets are unable to generalize on test data with different acquisition protocols. Modern neuroimaging studies and clinical trials are necessarily multi-center initiatives with a wide variety of acquisition protocols. Despite stringent protocol harmonization practices, it is very difficult to standardize the gamut of MRI imaging parameters across scanners, field strengths, receive coils etc., that affect image contrast. In this paper we propose a CNN-based segmentation algorithm that, in addition to being highly accurate and fast, is also resilient to variation in the input acquisition. Our approach relies on building approximate forward models of pulse sequences that produce a typical test image. For a given pulse sequence, we use its forward model to generate plausible, synthetic training examples that appear as if they were acquired in a scanner with that pulse sequence. Sampling over a wide variety of pulse sequences results in a wide variety of augmented training examples that help build an image contrast invariant model. Our method trains a single CNN that can segment input MRI images with acquisition parameters as disparate as $T_1$-weighted and $T_2$-weighted contrasts with only $T_1$-weighted training data. The segmentations generated are highly accurate with state-of-the-art results~(overall Dice overlap$=0.94$), with a fast run time~($\approx$ 45 seconds), and consistent across a wide range of acquisition protocols.Comment: Typo in author name corrected. Greves -> Grev

Opposing brain differences in 16p11.2 deletion and duplication carriers

Deletions and duplications of the recurrent ∼600 kb chromosomal BP4–BP5 region of 16p11.2 are associated with a broad variety of neurodevelopmental outcomes including autism spectrum disorder. A clue to the pathogenesis of the copy number variant (CNV)'s effect on the brain is that the deletion is associated with a head size increase, whereas the duplication is associated with a decrease. Here we analyzed brain structure in a clinically ascertained group of human deletion (N = 25) and duplication (N = 17) carriers from the Simons Variation in Individuals Project compared with age-matched controls (N = 29 and 33, respectively). Multiple brain measures showed increased size in deletion carriers and reduced size in duplication carriers. The effects spanned global measures of intracranial volume, brain size, compartmental measures of gray matter and white matter, subcortical structures, and the cerebellum. Quantitatively, the largest effect was on the thalamus, but the collective results suggest a pervasive rather than a selective effect on the brain. Detailed analysis of cortical gray matter revealed that cortical surface area displays a strong dose-dependent effect of CNV (deletion > control > duplication), whereas average cortical thickness is less affected. These results suggest that the CNV may exert its opposing influences through mechanisms that influence early stages of embryonic brain development

MRI investigation of the sensorimotor cortex and the corticospinal tract after acute spinal cord injury: a prospective longitudinal study

BACKGROUND: In patients with chronic spinal cord injury, imaging of the spinal cord and brain above the level of the lesion provides evidence of neural degeneration; however, the spatial and temporal patterns of progression and their relation to clinical outcomes are uncertain. New interventions targeting acute spinal cord injury have entered clinical trials but neuroimaging outcomes as responsive markers of treatment have yet to be established. We aimed to use MRI to assess neuronal degeneration above the level of the lesion after acute spinal cord injury. METHODS: In our prospective longitudinal study, we enrolled patients with acute traumatic spinal cord injury and healthy controls. We assessed patients clinically and by MRI at baseline, 2 months, 6 months, and 12 months, and controls by MRI at the same timepoints. We assessed atrophy in white matter in the cranial corticospinal tracts and grey matter in sensorimotor cortices by tensor-based analyses of T1-weighted MRI data. We used cross-sectional spinal cord area measurements to assess atrophy at cervical level C2/C3. We used myelin-sensitive magnetisation transfer (MT) and longitudinal relaxation rate (R1) maps to assess microstructural changes associated with myelin. We also assessed associations between MRI parameters and clinical improvement. All analyses of brain scans done with statistical parametric mapping were corrected for family-wise error. FINDINGS: Between Sept 17, 2010, and Dec 31, 2012, we recruited 13 patients and 18 controls. In the 12 months from baseline, patients recovered by a mean of 5·27 points per log month (95% CI 1·91–8·63) on the international standards for the neurological classification of spinal cord injury (ISNCSCI) motor score (p=0·002) and by 10·93 points per log month (6·20–15·66) on the spinal cord independence measure (SCIM) score (p<0·0001). Compared with controls, patients showed a rapid decline in cross-sectional spinal cord area (patients declined by 0·46 mm per month compared with a stable cord area in controls; p<0·0001). Patients had faster rates than controls of volume decline of white matter in the cranial corticospinal tracts at the level of the internal capsule (right Z score 5·21, p=0·0081; left Z score 4·12, p=0·0004) and right cerebral peduncle (Z score 3·89, p=0·0302) and of grey matter in the left primary motor cortex (Z score 4·23, p=0·041). Volume changes were paralleled by significant reductions of MT and R1 in the same areas and beyond. Improvements in SCIM scores at 12 months were associated with a reduced loss in cross-sectional spinal cord area over 12 months (Pearson's correlation 0·77, p=0·004) and reduced white matter volume of the corticospinal tracts at the level of the right internal capsule (Z score 4·30, p=0·0021), the left internal capsule (Z score 4·27, p=0·0278), and left cerebral peduncle (Z score 4·05, p=0·0316). Improvements in ISNCSCI motor scores were associated with less white matter volume change encompassing the corticospinal tract at the level of the right internal capsule (Z score 4·01, p<0·0001). INTERPRETATION: Extensive upstream atrophic and microstructural changes of corticospinal axons and sensorimotor cortical areas occur in the first months after spinal cord injury, with faster degenerative changes relating to poorer recovery. Structural volumetric and microstructural MRI protocols remote from the site of spinal cord injury could serve as neuroimaging biomarkers in acute spinal cord injury

Simultaneous Quantitative MRI Mapping of T1, T2* and Magnetic Susceptibility with Multi-Echo MP2RAGE.

The knowledge of relaxation times is essential for understanding the biophysical mechanisms underlying contrast in magnetic resonance imaging. Quantitative experiments, while offering major advantages in terms of reproducibility, may benefit from simultaneous acquisitions. In this work, we demonstrate the possibility of simultaneously recording relaxation-time and susceptibility maps with a prototype Multi-Echo (ME) Magnetization-Prepared 2 RApid Gradient Echoes (MP2RAGE) sequence. T1 maps can be obtained using the MP2RAGE sequence, which is relatively insensitive to inhomogeneities of the radio-frequency transmit field, [Formula: see text]. As an extension, multiple gradient echoes can be acquired in each of the MP2RAGE readout blocks, which permits the calculation of [Formula: see text] and susceptibility maps. We used computer simulations to explore the effects of the parameters on the precision and accuracy of the mapping. In vivo parameter maps up to 0.6 mm nominal resolution were acquired at 7 T in 19 healthy volunteers. Voxel-by-voxel correlations and the test-retest reproducibility were used to assess the reliability of the results. When using optimized paramenters, T1 maps obtained with ME-MP2RAGE and standard MP2RAGE showed excellent agreement for the whole range of values found in brain tissues. Simultaneously obtained [Formula: see text] and susceptibility maps were of comparable quality as Fast Low-Angle SHot (FLASH) results. The acquisition times were more favorable for the ME-MP2RAGE (≈ 19 min) sequence as opposed to the sum of MP2RAGE (≈ 12 min) and FLASH (≈ 10 min) acquisitions. Without relevant sacrifice in accuracy, precision or flexibility, the multi-echo version may yield advantages in terms of reduced acquisition time and intrinsic co-registration, provided that an appropriate optimization of the acquisition parameters is performed

Effect of 16P11.2 copy number variants on cognitive traits and brain structures

The 600kb 16p11.2 CNVs (breakpoints 4–5, 29.6-30.2 Mb-Hg19) are among the most frequent genetic risk factors for neurodevelopmental and psychiatric conditions: A 10-fold enrichment of deletions and duplications is observed in autism cohorts and a 10-fold enrichment of duplications in schizophrenia cohorts. Previous studies demonstrated “mirror” effects of both CNVs on body mass index and head circumference (deletion&gt;control&gt;duplication). However, the large global effect of brain size and the sample size of the two previous neuroimaging studies limited the interpretation of the analyses on regional brain structures, any estimate of the effect size, and the generalizability of the results across different ascertainments of the patients. In the first part of my Ph.D., I analyze structural magnetic resonance imaging (MRI) on 78 deletion carriers, 71 duplication carriers, and 212 controls. I show that both CNVs affect in a “mirror” way the volume and the cortical surface of the insula (Cohen’s d&gt;1), whilst other brain regions are preferentially altered in either the deletion carriers (calcarine cortex and superior, middle, transverse temporal gyri, Cohen’s d&gt;1) or the duplication carriers (caudate and hippocampus, Cohen’s d of 0.5 to 1). Results are generalizable across scanning sites, computational methods, age, sex, ascertainment for psychiatric disorders. They partially overlap with results of meta-analyses performed across psychiatric disorders. In the second part, I characterize the developmental trajectory of global brain metrics and regional brain structures in the 16p11.2 CNV carriers. I adapt a previously published longitudinal pipeline and normalizing method, derived from 339 typically developing individuals aged from 4.5 to 20 years old. From this population of reference, I Z-score our cross-sectional 16p11.2 dataset and show that all the brain alterations in the 16p11.2 carriers are already present at 4.5 years old and follow parallel trajectories to the controls. In summary, my results suggest that brain alterations, present in childhood and stable across adolescence and adulthood, are related to the risk conferred by the 16p11.2 CNVs, regardless of the carriers’ symptoms. Additional factors are therefore likely required for the development of psychiatric disorders. I highlight the relevance of studying genetic risk factors and mechanisms as a complement to groups defined by behavioral criteria. Further studies comparing multiple CNVs and monogenic conditions, from the earliest age, are required to understand the onset of neuroanatomical alterations and their overlap between different genetic risk factors for neurodevelopmental disorders. -- Les variations en nombre de copies (CNV), au locus 16p11.2 et d’une taille d’600kb (points de cassure 4–5, 29.6-30.2 Mb-Hg19) représentent un des facteurs de risque génétique les plus fréquents parmi les troubles psychiatriques : 10% d’enrichissement en délétion et duplication pour les troubles du spectre autistique, 10% d’enrichissement en duplication pour la schizophrénie. Les effets « miroirs » des deux CNVs sur l’indice de masse corporelle et le périmètre cranien ont déjà été démontrés (délétion&gt;contrôle&gt;duplication). Cependant, les différences en taille de cerveau et les échantillons des deux précédentes études de neuro- imagerie ont limité les analyses des régions cérébrales, l’estimation de la taille des effets, et la généralisation des résultats selon les modes de recrutement des patients. Dans cette thèse, j’analyse les images par résonance magnétique (IRM) de 78 porteurs de la délétion, 71 porteurs de la duplication et 212 participants contrôles. Je montre que les deux CNVs sont associées à des différences « en miroir » du volume et de la surface corticale de l’insula (Cohen’s d&gt;1), tandis que le cortex calcarin, les gyri temporaux supérieur, moyen et transverse sont préférentiellement altérés par la délétion (Cohen’s d&gt;1), les noyaux caudés et l’hippocampe sont préférentiellement altérés par la duplication (0.5&lt;Cohen’s d&lt;1). Les résultats sont généralisables à travers les differents sites d’IRM, les méthodes d’analyse computationnelle, les âges, les sexes et les divers diagnostiques psychiatriques des patients. Les résultats chevauchent partiellement ceux d’une méta-analyse sur plusieurs diagnostiques psychiatriques. Dans un second temps, je caractérise la trajectoire développementale de ces différences cérébrales. J’adapte un pipeline longitunal et une méthode de normalisation déjà publiés, construits à partir de 339 participants contrôles de 4.5 à 20 ans. Je calcule des Z-scores pour nos données transversales et montre que les différences cérébrales liées aux CNVs sont déjà présentes à 4.5 ans, avec les mêmes tailles d’effet et une trajectoire parallèle aux contrôles. En résumé, mes résultats suggèrent que les différences cérébrales, présentes dans la jeune enfance et stables à l’adolescence et l’âge adulte, sont liées au risque conféré par les CNVs en 16p11.2, quelque soient les symptômes. Des facteurs additionnels sont probablement nécessaires pour le développement de maladies psychiatriques. Je montre la pertinence d’étudier les facteurs de risque génétiques en complément des groupes de patients définis sur des critères comportementaux. Des études comparant diverses conditions génétiques, dès la naissance, sont nécessaires pour comprendre le début et le chevauchement des différences neuro-anatomiques observées pour différents facteurs de risque génétiques

Multi-modal characterization of rapid anterior hippocampal volume increase associated with aerobic exercise.

The hippocampus has been shown to demonstrate a remarkable degree of plasticity in response to a variety of tasks and experiences. For example, the size of the human hippocampus has been shown to increase in response to aerobic exercise. However, it is currently unknown what underlies these changes. Here we scanned sedentary, young to middle-aged human adults before and after a six-week exercise intervention using nine different neuroimaging measures of brain structure, vasculature, and diffusion. We then tested two different hypotheses regarding the nature of the underlying changes in the tissue. Surprisingly, we found no evidence of a vascular change as has been previously reported. Rather, the pattern of changes is better explained by an increase in myelination. Finally, we show hippocampal volume increase is temporary, returning to baseline after an additional six weeks without aerobic exercise. This is the first demonstration of a change in hippocampal volume in early to middle adulthood suggesting that hippocampal volume is modulated by aerobic exercise throughout the lifespan rather than only in the presence of age related atrophy. It is also the first demonstration of hippocampal volume change over a period of only six weeks, suggesting gross morphometric hippocampal plasticity occurs faster than previously thought

Reliable brain morphometry from contrast-enhanced T1w-MRI in patients with multiple sclerosis.

Brain morphometry is usually based on non-enhanced (pre-contrast) T1-weighted MRI. However, such dedicated protocols are sometimes missing in clinical examinations. Instead, an image with a contrast agent is often available. Existing tools such as FreeSurfer yield unreliable results when applied to contrast-enhanced (CE) images. Consequently, these acquisitions are excluded from retrospective morphometry studies, which reduces the sample size. We hypothesize that deep learning (DL)-based morphometry methods can extract morphometric measures also from contrast-enhanced MRI. We have extended DL+DiReCT to cope with contrast-enhanced MRI. Training data for our DL-based model were enriched with non-enhanced and CE image pairs from the same session. The segmentations were derived with FreeSurfer from the non-enhanced image and used as ground truth for the coregistered CE image. A longitudinal dataset of patients with multiple sclerosis (MS), comprising relapsing remitting (RRMS) and primary progressive (PPMS) subgroups, was used for the evaluation. Global and regional cortical thickness derived from non-enhanced and CE images were contrasted to results from FreeSurfer. Correlation coefficients of global mean cortical thickness between non-enhanced and CE images were significantly larger with DL+DiReCT (r = 0.92) than with FreeSurfer (r = 0.75). When comparing the longitudinal atrophy rates between the two MS subgroups, the effect sizes between PPMS and RRMS were higher with DL+DiReCT both for non-enhanced (d = -0.304) and CE images (d = -0.169) than for FreeSurfer (non-enhanced d = -0.111, CE d = 0.085). In conclusion, brain morphometry can be derived reliably from contrast-enhanced MRI using DL-based morphometry tools, making additional cases available for analysis and potential future diagnostic morphometry tools

A probabilistic atlas of the human thalamic nuclei combining ex vivo MRI and histology

The human thalamus is a brain structure that comprises numerous, highly specific nuclei. Since these nuclei are known to have different functions and to be connected to different areas of the cerebral cortex, it is of great interest for the neuroimaging community to study their volume, shape and connectivity in vivo with MRI. In this study, we present a probabilistic atlas of the thalamic nuclei built using ex vivo brain MRI scans and histological data, as well as the application of the atlas to in vivo MRI segmentation. The atlas was built using manual delineation of 26 thalamic nuclei on the serial histology of 12 whole thalami from six autopsy samples, combined with manual segmentations of the whole thalamus and surrounding structures (caudate, putamen, hippocampus, etc.) made on in vivo brain MR data from 39 subjects. The 3D structure of the histological data and corresponding manual segmentations was recovered using the ex vivo MRI as reference frame, and stacks of blockface photographs acquired during the sectioning as intermediate target. The atlas, which was encoded as an adaptive tetrahedral mesh, shows a good agreement with with previous histological studies of the thalamus in terms of volumes of representative nuclei. When applied to segmentation of in vivo scans using Bayesian inference, the atlas shows excellent test-retest reliability, robustness to changes in input MRI contrast, and ability to detect differential thalamic effects in subjects with Alzheimer's disease. The probabilistic atlas and companion segmentation tool are publicly available as part of the neuroimaging package FreeSurfer