Evaluation of atlas-based segmentation of hippocampi in healthy humans

Introduction and aim: Region of interest (ROI)-based functional magnetic resonance imaging (fMRI) data analysis relies on extracting signals from a specific area which is presumed to be involved in the brain activity being studied. The hippocampus is of interest in many functional connectivity studies for example in epilepsy as it plays an important role in epileptogenesis. In this context, ROI may be defined using different techniques. Our study aims at evaluating the spatial correspondence of hippocampal ROIs obtained using three brain atlases with hippocampal ROI obtained using an automatic segmentation algorithm dedicated to the hippocampus. Material and methods: High-resolution volumetric T1-weighted MR images of 18 healthy volunteers (five females) were acquired on a 3T scanner. Individual ROIs for both hippocampi of each subject were segmented from the MR images using an automatic hippocampus and amygdala segmentation software called SACHA providing the gold standard ROI for comparison with the atlas-derived results. For each subject, hippocampal ROIs were also obtained using three brain atlases: PickAtlas available as a commonly used software toolbox; automated anatomical labeling (AAL) atlas included as a subset of ROI into PickAtlas toolbox and a frequency-based brain atlas by Hammers et al. The levels of agreement between the SACHA results and those obtained using the atlases were assessed based on quantitative indices measuring volume differences and spatial overlap. The comparison was performed in standard Montreal Neurological Institute space, the registration being obtained with SPM5 (http://www.fil.ion.ucl.ac.uk/spm/). Results: The mean volumetric error across all subjects was 73% for hippocampal ROIs derived from AAL atlas; 20% in case of ROIs derived from the Hammers atlas and 107% for ROIs derived from PickAtlas. The mean false-positive and false-negative classification rates were 60% and 10% respectively for the AAL atlas; 16% and 32% for the Hammers atlas and 6% and 72% for the PickAtlas. Conclusion: Though atlas-based ROI definition may be convenient, the resulting ROIs may be poor representations of the hippocampus in some studies critical to under- or oversampling. Performance of the AAL atlas was inferior to that of the Hammers atlas. Hippocampal ROIs derived from PickAtlas are highly significantly smaller, and this results in the worst performance out of three atlases. It is advisable that the defined ROIs should be verified with knowledge of neuroanatomy before using it for further data analysis

Systems modeling of white matter microstructural abnormalities in Alzheimer's disease

INTRODUCTION: Microstructural abnormalities in white matter (WM) are often reported in Alzheimer's disease (AD). However, it is unclear which brain regions have the strongest WM changes in presymptomatic AD and what biological processes underlie WM abnormality during disease progression. METHODS: We developed a systems biology framework to integrate matched diffusion tensor imaging (DTI), genetic and transcriptomic data to investigate regional vulnerability to AD and identify genetic risk factors and gene subnetworks underlying WM abnormality in AD. RESULTS: We quantified regional WM abnormality and identified most vulnerable brain regions. A SNP rs2203712 in CELF1 was most significantly associated with several DTI-derived features in the hippocampus, the top ranked brain region. An immune response gene subnetwork in the blood was most correlated with DTI features across all the brain regions. DISCUSSION: Incorporation of image analysis with gene network analysis enhances our understanding of disease progression and facilitates identification of novel therapeutic strategies for AD

Assessment of White Matter Hyperintensity, Cerebral Blood Flow, and Cerebral Oxygenation in Older Subjects Stratified by Cerebrovascular Risk

Objective: Cerebrovascular disease (CVD) is the fifth most common cause of mortality in the United States. Diagnosis of CVD at an early stage is critical for optimal intervention designed to prevent ongoing and future brain injury. CVD is commonly associated with abnormalities of the cerebral microvasculature leading to tissue dysfunction, neuronal injury and death, and resultant clinical symptoms, which in turn, further impacts cerebral autoregulation (CA). This series of studies aims to test the hypothesis that white matter hyperintensities (WMH) and cerebral hemodynamics (quantified by magnetic resonance imaging (MRI) and an by innovative hybrid near-infrared diffuse optical instrument) can be used as biomarkers to distinguish cognitively healthy older subjects with high or low risk for developing CVD. Methods: Using functional MRI, WMH and cerebral blood flow (CBF) were quantified in 26 cognitively healthy older subjects (age: 77.8 ± 6.8 years). In a follow-up study, significant variability in WMH quantification methodology was addressed, with sources of variability identified in selecting image center of gravity, software compatibility, thresholding techniques, and manual editing procedures. Accordingly, post-acquisition processing methods were optimized to develop a standardized protocol with less than 0.5% inter-rater variance. Using a novel laboratory-made hybrid near-infrared spectroscopy/diffuse correlation spectroscopy (NIRS/DCS) and a finger plethysmograph, low-frequency oscillations (LFOs) of CBF, cerebral oxygenation, and main arterial pressure (MAP) were simultaneously measured before, during, and after 70° head-up-tilting (HUT). Gains (associated with CAs) to magnify LFOs were determined by transfer function analyses with MAP as the input and cerebral hemodynamic parameters as the outputs. In a follow-up study, a fast software correlator for DCS and a parallel detection technique for NIRS/DCS were adapted to improve the sampling rate of hybrid optical measurements. In addition, a new DCS probe was developed to measure CBF at the occipital lobe, which represents a novel application of the NIRS/DCS technique. Results: MRI measurements demonstrate that deep WMH (dWMH) and periventricular WMH (pWMH) volumetric measures are associated with reduced regional cortical CBF in patients at high-risk of CVD. Moreover, CBF in white matter (WM) was reduced in regions demonstrating both pWMH and dWMHs. NIRS/DCS optical measurements demonstrate that at resting baseline, LFO gains in the high-risk group were relatively lower compared to the low-risk group. The lower baseline gains in the high-risk group may be attributed to compensatory mechanisms that allow the maintenance of a stronger steady-state CA. However, HUT resulted in smaller gain reductions in the high-risk group compared to the low-risk group, suggesting weaker dynamic CA in association with increased CVD risks. A noteworthy finding in these experiments was that CVD risk more strongly influenced CBF than cerebral oxygenation. Conclusions: Regional WMH volumes, cortical and WM CBF values, and LFO gains of cerebral hemodynamics demonstrate specific associations with CA and may serve as important potential biomarkers for early diagnosis of CVD. The high spatial resolution, large penetration depth, and variety of imaging-sequences afforded by MRI make it an appealing imaging modality for evaluation of CVD, although MRI is costly, time-limited, and requires transfer of subjects from bed to imaging facility. In contrast, low-cost, portable, mobile diffuse optical technologies provide a complementary alternative for early screening of CVD, that can further allow continuous monitoring of disease attenuation or progression at the subject’s bedside. Thus, development of both methodologies is essential for progress in our future understanding of CVD as a major contributor to the morbidity and mortality associated with CVD today

Magnetic resonance imaging of resting cerebral oxygen metabolism : applications in Alzheimer’s disease

The BOLD contrast employed in functional MRI studies is an ambiguous signal composed of changes in blood flow, blood volume and oxidative metabolism. In situations where the vasculature and metabolism may have been affected, such as in aging and in certain diseases, the dissociation of the more physiologically-specific components from the BOLD signal becomes crucial. The latest generation of calibrated functional MRI methods allows the estimation of both resting blood flow and absolute oxygen metabolism. The work presented here is based on one such proof-of-concept approach, dubbed QUO2, whereby taking into account, within a generalized model, both arbitrary changes in blood flow and blood O2 content during a combination of hypercapnia and hyperoxia breathing manipulations, yields voxel-wise estimates of resting oxygen extraction fraction and oxidative metabolism. In the first part of this thesis, the QUO2 acquisition protocol and data analysis were revisited in order to enhance the temporal stability of individual blood flow and BOLD responses, consequently improving reliability of the model-derived estimates. Thereafter, an assessment of the within and between-subject variability of the optimized QUO2 measurements was performed on a group of healthy volunteers. In parallel, an analysis was performed of the sensitivity of the model to different sources of random and systematic errors, respectively due to errors in measurements and choice of assumed parameters values. Moreover, the various impacts of the oxygen concentration administered during the hyperoxia manipulation were evaluated through a simulation and experimentally, indicating that a mild hyperoxia was beneficial. Finally, the influence of Alzheimer’s disease in vascular and metabolic changes was explored for the first time by applying the QUO2 approach in a cohort of probable Alzheimer’s disease patients and age-matched control group. Voxel-wise and region-wise differences in resting blood flow, oxygen extraction fraction, oxidative metabolism, transverse relaxation rate constant R2* and R2* changes during hypercapnia were identified. A series of limitations along with recommended solutions was given with regards to the delayed transit time, the susceptibility artifacts and the challenge of performing a hypercapnia manipulation in cohorts of elderly and Alzheimer’s patients.Le contraste BOLD employé dans les études d’imagerie par résonance magnétique fonctionnelle (IRMf) provient d’une combinaison ambigüe de changements du flux sanguin cérébral, du volume sanguin ainsi que du métabolisme oxydatif. Dans un contexte où les fonctions vasculaires ou métaboliques du cerveau ont pu être affectées, tel qu’avec l’âge ou certaines maladies, il est crucial d’effectuer une décomposition du signal BOLD en composantes physiologiquement plus spécifiques. La dernière génération de méthodes d’IRMf calibrée permet d’estimer à la fois le flux sanguin cérébral et le métabolisme oxydatif au repos. Le présent travail est basé sur une telle technique, appelée QUantitative O2 (QUO2), qui, via un model généralisé, prend en considération les changements du flux sanguin ainsi que ceux en concentrations sanguine d’O2 durant des périodes d’hypercapnie et d’hyperoxie, afin d’estimer, à chaque voxel, la fraction d’extraction d’oxygène et le métabolisme oxydatif au repos. Dans la première partie de cette thèse, le protocole d’acquisition ainsi que la stratégie d’analyse de l’approche QUO2 ont été revus afin d’améliorer la stabilité temporelle des réponses BOLD et du flux sanguin, conséquemment, afin d’accroître la fiabilité des paramètres estimés. Par la suite, une évaluation de la variabilité intra- et inter-sujet des différentes mesures QUO2 a été effectuée auprès d’un groupe de participants sains. En parallèle, une analyse de la sensibilité du model à différentes sources d’erreurs aléatoires (issues des mesures acquises) et systématiques (dues aux assomptions du model) a été réalisée. De plus, les impacts du niveau d’oxygène administré durant les périodes d’hyperoxie ont été évalués via une simulation puis expérimentalement, indiquant qu’une hyperoxie moyenne était bénéfique. Finalement, l’influence de la maladie d’Alzheimer sur les changements vasculaires et métaboliques a été explorée pour la première fois en appliquant le protocole QUO2 à une cohorte de patients Alzheimer et à un groupe témoin du même âge. Des différences en terme de flux sanguin, fraction d’oxygène extraite, métabolisme oxydatif, et taux de relaxation transverse R2* au repos comme en réponse à l’hypercapnie, ont été identifiées au niveau du voxel, ainsi qu’au niveau de régions cérébrales vulnérables à la maladie d’Alzheimer. Une liste de limitations accompagnées de recommandations a été dressée en ce qui a trait au temps de transit différé, aux artéfacts de susceptibilité magnétique, de même qu’au défi que représente l’hypercapnie chez les personnes âgées ou atteintes de la maladie d’Alzheimer

Systematic comparison of different techniques to measure hippocampal subfield volumes in ADNI2

OBJECTIVE: Subfield-specific measurements provide superior information in the early stages of neurodegenerative diseases compared to global hippocampal measurements. The overall goal was to systematically compare the performance of five representative manual and automated T1 and T2 based subfield labeling techniques in a sub-set of the ADNI2 population. METHODS: The high resolution T2 weighted hippocampal images (T2-HighRes) and the corresponding T1 images from 106 ADNI2 subjects (41 controls, 57 MCI, 8 AD) were processed as follows. A. T1-based: 1. Freesurfer + Large-Diffeomorphic-Metric-Mapping in combination with shape analysis. 2. FreeSurfer 5.1 subfields using in-vivo atlas. B. T2-HighRes: 1. Model-based subfield segmentation using ex-vivo atlas (FreeSurfer 6.0). 2. T2-based automated multi-atlas segmentation combined with similarity-weighted voting (ASHS). 3. Manual subfield parcellation. Multiple regression analyses were used to calculate effect sizes (ES) for group, amyloid positivity in controls, and associations with cognitive/memory performance for each approach. RESULTS: Subfield volumetry was better than whole hippocampal volumetry for the detection of the mild atrophy differences between controls and MCI (ES: 0.27 vs 0.11). T2-HighRes approaches outperformed T1 approaches for the detection of early stage atrophy (ES: 0.27 vs.0.10), amyloid positivity (ES: 0.11 vs 0.04), and cognitive associations (ES: 0.22 vs 0.19). CONCLUSIONS: T2-HighRes subfield approaches outperformed whole hippocampus and T1 subfield approaches. None of the different T2-HghRes methods tested had a clear advantage over the other methods. Each has strengths and weaknesses that need to be taken into account when deciding which one to use to get the best results from subfield volumetry

Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration: A united approach

Item does not contain fulltextCerebral small vessel disease (SVD) is a common accompaniment of ageing. Features seen on neuroimaging include recent small subcortical infarcts, lacunes, white matter hyperintensities, perivascular spaces, microbleeds, and brain atrophy. SVD can present as a stroke or cognitive decline, or can have few or no symptoms. SVD frequently coexists with neurodegenerative disease, and can exacerbate cognitive deficits, physical disabilities, and other symptoms of neurodegeneration. Terminology and definitions for imaging the features of SVD vary widely, which is also true for protocols for image acquisition and image analysis. This lack of consistency hampers progress in identifying the contribution of SVD to the pathophysiology and clinical features of common neurodegenerative diseases. We are an international working group from the Centres of Excellence in Neurodegeneration. We completed a structured process to develop definitions and imaging standards for markers and consequences of SVD. We aimed to achieve the following: first, to provide a common advisory about terms and definitions for features visible on MRI; second, to suggest minimum standards for image acquisition and analysis; third, to agree on standards for scientific reporting of changes related to SVD on neuroimaging; and fourth, to review emerging imaging methods for detection and quantification of preclinical manifestations of SVD. Our findings and recommendations apply to research studies, and can be used in the clinical setting to standardise image interpretation, acquisition, and reporting. This Position Paper summarises the main outcomes of this international effort to provide the STandards for ReportIng Vascular changes on nEuroimaging (STRIVE)

Improvement in Alzheimer's Disease MRI Images Analysis by Convolutional Neural Networks Via Topological Optimization

This research underscores the efficacy of Fourier topological optimization in refining MRI imagery, thereby bolstering the classification precision of Alzheimer's Disease through convolutional neural networks. Recognizing that MRI scans are indispensable for neurological assessments, but frequently grapple with issues like blurriness and contrast irregularities, the deployment of Fourier topological optimization offered enhanced delineation of brain structures, ameliorated noise, and superior contrast. The applied techniques prioritized boundary enhancement, contrast and brightness adjustments, and overall image lucidity. Employing CNN architectures VGG16, ResNet50, InceptionV3, and Xception, the post-optimization analysis revealed a marked elevation in performance. Conclusively, the amalgamation of Fourier topological optimization with CNNs delineates a promising trajectory for the nuanced classification of Alzheimer's Disease, portending a transformative impact on its diagnostic paradigms

Tau PET and multimodal brain imaging in patients at risk for chronic traumatic encephalopathy.

ObjectiveTo characterize individual and group-level neuroimaging findings in patients at risk for Chronic Traumatic Encephalopathy (CTE).MethodsEleven male patients meeting criteria for Traumatic Encephalopathy Syndrome (TES, median age: 64) underwent neurologic evaluation, 3-Tesla MRI, and PET with [18F]-Flortaucipir (FTP, tau-PET) and [11C]-Pittsburgh compound B (PIB, amyloid-PET). Six patients underwent [18F]-Fluorodeoxyglucose-PET (FDG, glucose metabolism). We assessed imaging findings at the individual patient level, and in group-level comparisons with modality-specific groups of cognitively normal older adults (CN). Tau-PET findings in patients with TES were also compared to a matched group of patients with mild cognitive impairment or dementia due to Alzheimer's disease (AD).ResultsAll patients with TES sustained repetitive head injury participating in impact sports, ten in American football. Three patients met criteria for dementia and eight had mild cognitive impairment. Two patients were amyloid-PET positive and harbored the most severe MRI atrophy, FDG hypometabolism, and FTP-tau PET binding. Among the nine amyloid-negative patients, tau-PET showed either mildly elevated frontotemporal binding, a "dot-like" pattern, or no elevated binding. Medial temporal FTP was mildly elevated in a subset of amyloid-negative patients, but values were considerably lower than in AD. Voxelwise analyses revealed a convergence of imaging abnormalities (higher FTP binding, lower FDG, lower gray matter volumes) in frontotemporal areas in TES compared to controls.ConclusionsMildly elevated tau-PET binding was observed in a subset of amyloid-negative patients at risk for CTE, in a distribution consistent with CTE pathology stages III-IV. FTP-PET may be useful as a biomarker of tau pathology in CTE but is unlikely to be sensitive to early disease stages