ABSTRACT
We present a comprehensive study on the non-invasive measurement of hippocampal perfusion. Using high-resolution 7 tesla arterial spin labeling (ASL) data, we generated robust perfusion maps and observed significant variations in perfusion among hippocampal subfields, with CA1 exhibiting the lowest perfusion levels. Notably, these perfusion differences were robust and already detectable with 50 perfusion-weighted images per subject, acquired in 5 min. To understand the underlying factors, we examined the influence of image quality metrics, various tissue microstructure and morphometric properties, macrovasculature, and cytoarchitecture. We observed higher perfusion in regions located closer to arteries, demonstrating the influence of vascular proximity on hippocampal perfusion. Moreover, ex vivo cytoarchitectonic features based on neuronal density differences appeared to correlate stronger with hippocampal perfusion than morphometric measures like gray matter thickness. These findings emphasize the interplay between microvasculature, macrovasculature, and metabolic demand in shaping hippocampal perfusion. Our study expands the current understanding of hippocampal physiology and its relevance to neurological disorders. By providing in vivo evidence of perfusion differences between hippocampal subfields, our findings have implications for diagnosis and potential therapeutic interventions. In conclusion, our study provides a valuable resource for extensively characterizing hippocampal perfusion.
Subject(s)
Arteries , Benchmarking , Perfusion , Hippocampus/diagnostic imaging , Magnetic Resonance ImagingABSTRACT
Production of metal debris from implant wear and corrosion processes is now a well understood occurrence following hip arthroplasty. Evidence has shown that metal ions can enter the bloodstream and travel to distant organs including the brain, and in extreme cases, can induce sensorial and neurological diseases. Our objective was tosimultaneously analyze brain anatomy and physiology in patients with long-term and well-functioning implants. Included were subjects who had received total hip or hip resurfacing arthroplastywith an implantation time of a minimum of 7 years (n = 28) and age- and sex-matched controls (n = 32). Blood samples were obtained to measure ion concentrations of cobalt and chromium, and the Montreal Cognitive Assessment was performed. 3T MRI brain scans were completed with an MPRAGE sequence for ROI segmentation and multiecho gradient echo sequences to generate QSM and R2* maps. Mean QSM and R2* values were recorded for five deep brain and four middle and cortical brain structures on both hemispheres: pallidum, putamen, caudate, amygdala, hippocampus, anterior cingulate, inferior temporal, and cerebellum. No differences in QSM or R2* or cognition scores were found between both groups (p > 0.6654). No correlation was found between susceptibility and blood ion levels for cobalt or chromium in any region of the brain. No correlation was found between blood ion levels and cognition scores. Clinical significance: Results suggest that metal ions released by long-term and well-functioning implants do not affect brain integrity.
Subject(s)
Arthroplasty, Replacement, Hip , Brain , Chromium , Cobalt , Hip Prosthesis , Magnetic Resonance Imaging , Humans , Male , Female , Middle Aged , Brain/diagnostic imaging , Aged , Chromium/blood , Cobalt/blood , Adult , Case-Control StudiesABSTRACT
The cholinergic innervation of the cortex originates almost entirely from populations of neurons in the basal forebrain (BF). Structurally, the ascending BF cholinergic projections are highly branched, with individual cells targeting multiple different cortical regions. However, it is not known whether the structural organization of basal forebrain projections reflects their functional integration with the cortex. We therefore used high-resolution 7T diffusion and resting state functional MRI in humans to examine multimodal gradients of BF cholinergic connectivity with the cortex. Moving from anteromedial to posterolateral BF, we observed reduced tethering between structural and functional connectivity gradients, with the most pronounced dissimilarity localized in the nucleus basalis of Meynert (NbM). The cortical expression of this structure-function gradient revealed progressively weaker tethering moving from unimodal to transmodal cortex, with the lowest tethering in midcingulo-insular cortex. We used human [18F] fluoroethoxy-benzovesamicol (FEOBV) PET to demonstrate that cortical areas with higher concentrations of cholinergic innervation tend to exhibit lower tethering between BF structural and functional connectivity, suggesting a pattern of increasingly diffuse axonal arborization. Optogenetic tracing of cholinergic projections and [18F] FEOBV PET in mice confirmed a gradient of axonal arborization across individual BF cholinergic neurons. Like humans, cholinergic neurons with the highest arborization project to cingulo-insular areas of the mouse isocortex. Altogether, our findings reveal that BF cholinergic neurons vary in their branch complexity, with certain subpopulations exhibiting greater modularity and others greater diffusivity in the functional integration of their cortical targets.
ABSTRACT
The basal forebrain cholinergic neurons provide acetylcholine to the cortex via large projections. Recent molecular imaging work in humans indicates that the cortical cholinergic innervation is not uniformly distributed, but rather may disproportionately innervate cortical areas relevant to supervisory attention. In this study, we therefore reexamined the spatial relationship between acetylcholinergic modulation and attention in the human cortex using meta-analytic strategies targeting both pharmacological and non-pharmacological neuroimaging studies. We found that pharmaco-modulation of acetylcholine evoked both increased activity in the anterior cingulate and decreased activity in the opercular and insular cortex. In large independent meta-analyses of non-pharmacological neuroimaging research, we demonstrate that during attentional engagement these cortical areas exhibit (1) task-related co-activation with the basal forebrain, (2) task-related co-activation with one another, and (3) spatial overlap with dense cholinergic innervations originating from the basal forebrain, as estimated by multimodal positron emission tomography and magnetic resonance imaging. Finally, we provide meta-analytic evidence that pharmaco-modulation of acetylcholine also induces a speeding of responses to targets with no apparent tradeoff in accuracy. In sum, we demonstrate in humans that acetylcholinergic modulation of midcingulo-insular hubs of the ventral attention/salience network via basal forebrain afferents may coordinate selection of task relevant information, thereby facilitating cognition and behavior.
Subject(s)
Acetylcholine , Attention , Humans , Cognition/physiology , Neuroimaging , Cholinergic Agents/pharmacologyABSTRACT
Focal epilepsy is characterized by repeated spontaneous seizures that originate from cortical epileptogenic zone networks (EZN). Analysis of intracerebral recordings showed that subcortical structures, and in particular the thalamus, play an important role in seizure dynamics as well, supporting their structural alterations reported in the neuroimaging literature. Nonetheless, between-patient differences in EZN localization (e.g., temporal vs. non-temporal lobe epilepsy) as well as extension (i.e., number of epileptogenic regions) might impact the magnitude as well as spatial distribution of subcortical structural changes. Here we used 7 Tesla MRI T1 data to provide an unprecedented description of subcortical morphological (volume, tissue deformation, and shape) and longitudinal relaxation (T1 ) changes in focal epilepsy patients and evaluate the impact of the EZN and other patient-specific clinical features. Our results showed variable levels of atrophy across thalamic nuclei that appeared most prominent in the temporal lobe epilepsy group and the side ipsilateral to the EZN, while shortening of T1 was especially observed for the lateral thalamus. Multivariate analyses across thalamic nuclei and basal ganglia showed that volume acted as the dominant discriminator between patients and controls, while (posterolateral) thalamic T1 measures looked promising to further differentiate patients based on EZN localization. In particular, the observed differences in T1 changes between thalamic nuclei indicated differential involvement based on EZN localization. Finally, EZN extension was found to best explain the observed variability between patients. To conclude, this work revealed multi-scale subcortical alterations in focal epilepsy as well as their dependence on several clinical characteristics.
Subject(s)
Epilepsies, Partial , Epilepsy, Temporal Lobe , Humans , Epilepsies, Partial/diagnostic imaging , Basal Ganglia/diagnostic imaging , Seizures , Thalamus/diagnostic imaging , Magnetic Resonance ImagingABSTRACT
We present a comprehensive study on the non-invasive measurement of hippocampal perfusion. Using high-resolution 7 Tesla arterial spin labelling data, we generated robust perfusion maps and observed significant variations in perfusion among hippocampal subfields, with CA1 exhibiting the lowest perfusion levels. Notably, these perfusion differences were robust and detectable even within five minutes and just fifty perfusion-weighted images per subject. To understand the underlying factors, we examined the influence of image quality metrics, various tissue microstructure and morphometry properties, macrovasculature and cytoarchitecture. We observed higher perfusion in regions located closer to arteries, demonstrating the influence of vascular proximity on hippocampal perfusion. Moreover, ex vivo cytoarchitectonic features based on neuronal density differences appeared to correlate stronger with hippocampal perfusion than morphometric measures like gray matter thickness. These findings emphasize the interplay between microvasculature, macrovasculature, and metabolic demand in shaping hippocampal perfusion. Our study expands the current understanding of hippocampal physiology and its relevance to neurological disorders. By providing in vivo evidence of perfusion differences between hippocampal subfields, our findings have implications for diagnosis and potential therapeutic interventions. In conclusion, our study provides a valuable resource for extensively characterising hippocampal perfusion.
ABSTRACT
Like neocortical structures, the archicortical hippocampus differs in its folding patterns across individuals. Here, we present an automated and robust BIDS-App, HippUnfold, for defining and indexing individual-specific hippocampal folding in MRI, analogous to popular tools used in neocortical reconstruction. Such tailoring is critical for inter-individual alignment, with topology serving as the basis for homology. This topological framework enables qualitatively new analyses of morphological and laminar structure in the hippocampus or its subfields. It is critical for refining current neuroimaging analyses at a meso- as well as micro-scale. HippUnfold uses state-of-the-art deep learning combined with previously developed topological constraints to generate uniquely folded surfaces to fit a given subject's hippocampal conformation. It is designed to work with commonly employed sub-millimetric MRI acquisitions, with possible extension to microscopic resolution. In this paper, we describe the power of HippUnfold in feature extraction, and highlight its unique value compared to several extant hippocampal subfield analysis methods.
Subject(s)
Hippocampus , Magnetic Resonance Imaging , Humans , Hippocampus/diagnostic imaging , Hippocampus/anatomy & histology , Magnetic Resonance Imaging/methods , Neuroimaging/methodsABSTRACT
This study aimed to evaluate the use of diffusion kurtosis imaging (DKI) to detect microstructural abnormalities within the temporal pole (TP) and its temporopolar cortex in temporal lobe epilepsy (TLE) patients. DKI quantitative maps were obtained from fourteen lesional TLE and ten non-lesional TLE patients, along with twenty-three healthy controls. Data collected included mean (MK); radial (RK) and axial kurtosis (AK); mean diffusivity (MD) and axonal water fraction (AWF). Automated fiber quantification (AFQ) was used to quantify DKI measurements along the inferior longitudinal (ILF) and uncinate fasciculus (Unc). ILF and Unc tract profiles were compared between groups and tested for correlation with disease duration. To characterize temporopolar cortex microstructure, DKI maps were sampled at varying depths from superficial white matter (WM) towards the pial surface. Patients were separated according to the temporal lobe ipsilateral to seizure onset and their AFQ results were used as input for statistical analyses. Significant differences were observed between lesional TLE and controls, towards the most temporopolar segment of ILF and Unc proximal to the TP within the ipsilateral temporal lobe in left TLE patients for MK, RK, AWF and MD. No significant changes were observed with DKI maps in the non-lesional TLE group. DKI measurements correlated with disease duration, mostly towards the temporopolar segments of the WM bundles. Stronger differences in MK, RK and AWF within the temporopolar cortex were observed in the lesional TLE and noticeable differences (except for MD) in non-lesional TLE groups compared to controls. This study demonstrates that DKI has potential to detect subtle microstructural alterations within the temporopolar segments of the ILF and Unc and the connected temporopolar cortex in TLE patients including non-lesional TLE subjects. This could aid our understanding of the extrahippocampal areas, more specifically the temporal pole role in seizure generation in TLE and might inform surgical planning, leading to better seizure outcomes.
Subject(s)
Epilepsy, Temporal Lobe , White Matter , Humans , Epilepsy, Temporal Lobe/diagnostic imaging , Diffusion Tensor Imaging/methods , Temporal Lobe/diagnostic imaging , White Matter/diagnostic imaging , SeizuresABSTRACT
Tractography combined with regions of interest (ROIs) has been used to non-invasively study the structural connectivity of the cortex as well as to assess the reliability of these connections. However, the subcortical connectome (subcortex to subcortex) has not been comprehensively examined, in part due to the difficulty of performing tractography in this complex and compact region. In this study, we performed an in vivo investigation using tractography to assess the feasibility and reliability of mapping known connections between structures of the subcortex using the test-retest dataset from the Human Connectome Project (HCP). We further validated our observations using a separate unrelated subjects dataset from the HCP. Quantitative assessment was performed by computing tract densities and spatial overlap of identified connections between subcortical ROIs. Further, known connections between structures of the basal ganglia and thalamus were identified and visually inspected, comparing tractography reconstructed trajectories with descriptions from tract-tracing studies. Our observations demonstrate both the feasibility and reliability of using a data-driven tractography-based approach to map the subcortical connectome in vivo.
Subject(s)
Connectome , Cerebral Cortex , Diffusion Magnetic Resonance Imaging , Feasibility Studies , Humans , Reproducibility of ResultsABSTRACT
Mutations of the mitochondrial DNA are an important cause of inherited diseases that can severely affect the tissue's homeostasis and integrity. The m.3243A > G mutation is the most commonly observed across mitochondrial disorders and is linked to multisystemic complications, including cognitive deficits. In line with in vitro experiments demonstrating the m.3243A > G's negative impact on neuronal energy production and integrity, m.3243A > G patients show cerebral grey matter tissue changes. However, its impact on the most neuron dense, and therefore energy-consuming brain structure-the cerebellum-remains elusive. In this work, we used high-resolution structural and functional data acquired using 7â T MRI to characterize the neurodegenerative and functional signatures of the cerebellar cortex in m.3243A > G patients. Our results reveal altered tissue integrity within distinct clusters across the cerebellar cortex, apparent by their significantly reduced volume and longitudinal relaxation rate compared with healthy controls, indicating macroscopic atrophy and microstructural pathology. Spatial characterization reveals that these changes occur especially in regions related to the frontoparietal brain network that is involved in information processing and selective attention. In addition, based on resting-state functional MRI data, these clusters exhibit reduced functional connectivity to frontal and parietal cortical regions, especially in patients characterized by (i) a severe disease phenotype and (ii) reduced information-processing speed and attention control. Combined with our previous work, these results provide insight into the neuropathological changes and a solid base to guide longitudinal studies aimed to track disease progression.
ABSTRACT
BACKGROUND: Diffusion kurtosis imaging (DKI) quantifies the non-Gaussian diffusion of water within tissue microstructure. However, it has increased fitting parameters and requires higher b-values. Evaluation of DKI reproducibility is important for clinical purposes. PURPOSE: To assess the reproducibility in whole-brain high-resolution DKI at varying b-values. STUDY TYPE: Retrospective. SUBJECTS AND PHANTOMS: In all, 44 individuals from the test-retest Human Connectome Project (HCP) database and 12 3D-printed phantoms. FIELD STRENGTH/SEQUENCE: Diffusion-weighted multiband echo-planar imaging sequence at 3T and 9.4T. magnetization-prepared rapid acquisition gradient echo at 3T for in vivo structural data only. ASSESSMENT: From HCP data with b-values = 1000, 2000, 3000 s/mm2 (dataset A), two additional datasets with b-values = 1000, 3000 s/mm2 (dataset B) and b-values = 1000, 2000 s/mm2 (dataset C) were extracted. Estimated DKI metrics from each dataset were used for evaluating reproducibility and fitting quality in white matter (WM) and gray matter (GM) based on whole-brain and regions of interest (ROIs). STATISTICAL TESTS: DKI reproducibility was assessed using the within-subject coefficient of variation (CoV), fitting residuals to evaluate DKI fitting accuracy and Pearson's correlation to investigate the presence of systematic biases. Repeated measures analysis of variance was used for statistical comparison. RESULTS: Datasets A and B exhibited lower DKI CoVs (<20%) compared to C (<50%) in both WM and GM ROIs (all P < 0.05). This effect varies between DKI and DTI parameters (P < 0.005). Whole-brain fitting residuals were consistent across datasets (P > 0.05), but lower residuals in dataset B were detected for the WM ROIs (P < 0.001). A similar trend was observed for the phantom data CoVs (<7.5%) at varying fiber orientations for datasets A and B. Finally, dataset C was characterized by higher residuals across the different fiber crossings (P < 0.05). DATA CONCLUSION: The study demonstrates that high reproducibility can still be achieved within a reasonable scan time, specifically dataset B, supporting the potential of DKI for aiding clinical tools in detecting microstructural changes.
Subject(s)
Brain/diagnostic imaging , Diffusion Tensor Imaging/methods , Image Processing, Computer-Assisted/methods , Adult , Echo-Planar Imaging , Female , Humans , Male , Phantoms, Imaging , Reproducibility of Results , Retrospective Studies , Young AdultABSTRACT
Most neuroanatomical studies are based on T1-weighted MR images, whose intensity profiles are not solely determined by the tissue's longitudinal relaxation times (T1), but also affected by varying non-T1 contributions, hampering data reproducibility. In contrast, quantitative imaging using the MP2RAGE sequence, for example, allows direct characterization of the brain based on the tissue property of interest. Combined with 7 Tesla (7T) MRI, this offers unique opportunities to obtain robust high-resolution brain data characterized by a high reproducibility, sensitivity and specificity. However, specific MP2RAGE parameter choices - e.g., to emphasize intracortical myelin-dependent contrast variations - can substantially impact image quality and cortical analyses through remnants of B1+-related intensity variations, as illustrated in our previous work. To follow up on this: we (1) validate this protocol effect using a dataset acquired with a particularly B1+ insensitive set of MP2RAGE parameters combined with parallel transmission excitation; and (2) extend our analyses to evaluate the effects on hippocampal morphometry. The latter remained unexplored initially, but can provide important insights related to generalizability and reproducibility of neurodegenerative research using 7T MRI. We confirm that B1+ inhomogeneities have a considerably variable effect on cortical T1 estimates, as well as on hippocampal morphometry depending on the MP2RAGE setup. While T1 differed substantially across datasets initially, we show the inter-site T1 comparability improves after correcting for the spatially varying B1+ field using a separately acquired Sa2RAGE B1+ map. Finally, removal of B1+ residuals affects hippocampal volumetry and boundary definitions, particularly near structures characterized by strong intensity changes (e.g. cerebral spinal fluid). Taken together, we show that the choice of MP2RAGE parameters can impact T1 comparability across sites and present evidence that hippocampal segmentation results are modulated by B1+ inhomogeneities. This calls for careful (1) consideration of sequence parameters when setting acquisition protocols, as well as (2) acquisition of a B1+ map to correct MP2RAGE data for potential B1+ variations to allow comparison across datasets.
Subject(s)
Brain/physiology , Hippocampus/physiology , Image Processing, Computer-Assisted , Magnetic Resonance Imaging , Adult , Humans , Image Processing, Computer-Assisted/methods , Magnetic Resonance Imaging/methods , Male , Reproducibility of Results , Sensitivity and SpecificityABSTRACT
The zona incerta (ZI) is a small gray matter region of the deep brain first identified in the 19th century, yet direct in vivo visualization and characterization has remained elusive. Noninvasive detection of the ZI and surrounding region could be critical to further our understanding of this widely connected but poorly understood deep brain region and could contribute to the development and optimization of neuromodulatory therapies. We demonstrate that high resolution (submillimetric) longitudinal (T1) relaxometry measurements at high magnetic field strength (7 T) can be used to delineate the ZI from surrounding white matter structures, specifically the fasciculus cerebellothalamicus, fields of Forel (fasciculus lenticularis, fasciculus thalamicus, and field H), and medial lemniscus. Using this approach, we successfully derived in vivo estimates of the size, shape, location, and tissue characteristics of substructures in the ZI region, confirming observations only previously possible through histological evaluation that this region is not just a space between structures but contains distinct morphological entities that should be considered separately. Our findings pave the way for increasingly detailed in vivo study and provide a structural foundation for precise functional and neuromodulatory investigation.
Subject(s)
Image Interpretation, Computer-Assisted , Magnetic Resonance Imaging , Neuroimaging , White Matter/anatomy & histology , White Matter/diagnostic imaging , Zona Incerta/anatomy & histology , Zona Incerta/diagnostic imaging , Adult , Aged , Female , Humans , Male , Middle Aged , Young AdultABSTRACT
BACKGROUND: Pulmonary rehabilitation (PR) is a cornerstone in the management of chronic obstructive pulmonary disease (COPD), targeting skeletal muscle to improve functional performance. However, there is substantial inter-individual variability in the effect of PR on functional performance, which cannot be fully accounted for by generic phenotypic factors. We performed an unbiased integrative analysis of the skeletal muscle molecular responses to PR in COPD patients and comprehensively characterized their baseline pulmonary and physical function, body composition, blood profile, comorbidities, and medication use. METHODS: Musculus vastus lateralis biopsies were obtained from 51 COPD patients (age 64 ± 1 years, sex 73% men, FEV1 , 34 (26-41) %pred.) before and after 4 weeks high-intensity supervised in-patient PR. Muscle molecular markers were grouped by network-constrained clustering, and their relative changes in expression values-assessed by qPCR and western blot-were reduced to process scores by principal component analysis. Patients were subsequently clustered based on these process scores. Pre-PR and post-PR functional performance was assessed by incremental cycle ergometry and 6 min walking test (6MWT). RESULTS: Eight molecular processes were discerned by network-constrained hierarchical clustering of the skeletal muscle molecular rehabilitation responses. Based on the resulting process scores, four clusters of patients were identified by hierarchical cluster analysis. Two major patient clusters differed in PR-induced autophagy (P < 0.001), myogenesis (P = 0.014), glucocorticoid signalling (P < 0.001), and oxidative metabolism regulation (P < 0.001), with Cluster 1 (C1; n = 29) overall displaying a more pronounced change in marker expression than Cluster 2 (C2; n = 16). General baseline characteristics did not differ between clusters. Following PR, both 6 min walking distance (+26.5 ± 8.3 m, P = 0.003) and peak load on the cycle ergometer test (+9.7 ± 1.9 W, P < 0.001) were improved. However, the functional improvement was more pronounced in C1, as a higher percentage of patients exceeded the minimal clinically important difference in peak workload (61 vs. 21%, P = 0.022) and both peak workload and 6 min walking test (52 vs. 8%, P = 0.008) upon PR. CONCLUSIONS: We identified patient groups with distinct skeletal muscle molecular responses to rehabilitation, associated with differences in functional improvements upon PR.
Subject(s)
Lung/metabolism , Lung/physiopathology , Muscle, Skeletal/metabolism , Muscle, Skeletal/physiopathology , Pulmonary Disease, Chronic Obstructive/epidemiology , Pulmonary Disease, Chronic Obstructive/rehabilitation , Aged , Body Composition , Cluster Analysis , Comorbidity , Disease Management , Exercise Therapy , Humans , Middle Aged , Muscle, Skeletal/pathology , Physical Functional Performance , Prospective Studies , Pulmonary Disease, Chronic Obstructive/diagnosis , Respiratory Function Tests , Severity of Illness IndexABSTRACT
One of the most common mitochondrial DNA (mtDNA) mutations, the A to G transition at base pair 3243, has been linked to changes in the brain, in addition to commonly observed hearing problems, diabetes and myopathy. However, a detailed quantitative description of m.3243A>G patients' brains has not been provided so far. In this study, ultra-high field MRI at 7T and volume- and surface-based data analyses approaches were used to highlight morphology (i.e. atrophy)-, microstructure (i.e. myelin and iron concentration)- and metabolism (i.e. cerebral blood flow)-related differences between patients (Nâ¯=â¯22) and healthy controls (Nâ¯=â¯15). The use of quantitative MRI at 7T allowed us to detect subtle changes of biophysical processes in the brain with high accuracy and sensitivity, in addition to typically assessed lesions and atrophy. Furthermore, the effect of m.3243A>G mutation load in blood and urine epithelial cells on these MRI measures was assessed within the patient population and revealed that blood levels were most indicative of the brain's state and disease severity, based on MRI as well as on neuropsychological data. Morphometry MRI data showed a wide-spread reduction of cortical, subcortical and cerebellar gray matter volume, in addition to significantly enlarged ventricles. Moreover, surface-based analyses revealed brain area-specific changes in cortical thickness (e.g. of the auditory cortex), and in T1, T2* and cerebral blood flow as a function of mutation load, which can be linked to typically m.3243A>G-related clinical symptoms (e.g. hearing impairment). In addition, several regions linked to attentional control (e.g. middle frontal gyrus), the sensorimotor network (e.g. banks of central sulcus) and the default mode network (e.g. precuneus) were characterized by alterations in cortical thickness, T1, T2* and/or cerebral blood flow, which has not been described in previous MRI studies. Finally, several hypotheses, based either on vascular, metabolic or astroglial implications of the m.3243A>G mutation, are discussed that potentially explain the underlying pathobiology. To conclude, this is the first 7T and also the largest MRI study on this patient population that provides macroscopic brain correlates of the m.3243A>G mutation indicating potential MRI biomarkers of mitochondrial diseases and might guide future (longitudinal) studies to extensively track neuropathological and clinical changes.
Subject(s)
Brain Mapping , Brain/diagnostic imaging , DNA, Mitochondrial/genetics , Mitochondrial Diseases/diagnostic imaging , Mitochondrial Diseases/genetics , Mutation/genetics , Adult , Analysis of Variance , Brain/pathology , Case-Control Studies , Correlation of Data , Diabetes Mellitus/etiology , Female , Hearing Loss/etiology , Humans , Image Processing, Computer-Assisted , Magnetic Resonance Imaging , Male , Middle Aged , Mitochondrial Diseases/complications , Muscular Diseases/etiology , Young AdultABSTRACT
High-resolution (functional) magnetic resonance imaging (MRI) at ultra high magnetic fields (7 Tesla and above) enables researchers to study how anatomical and functional properties change within the cortical ribbon, along surfaces and across cortical depths. These studies require an accurate delineation of the gray matter ribbon, which often suffers from inclusion of blood vessels, dura mater and other non-brain tissue. Residual segmentation errors are commonly corrected by browsing the data slice-by-slice and manually changing labels. This task becomes increasingly laborious and prone to error at higher resolutions since both work and error scale with the number of voxels. Here we show that many mislabeled, non-brain voxels can be corrected more efficiently and semi-automatically by representing three-dimensional anatomical images using two-dimensional histograms. We propose both a uni-modal (based on first spatial derivative) and multi-modal (based on compositional data analysis) approach to this representation and quantify the benefits in 7 Tesla MRI data of nine volunteers. We present an openly accessible Python implementation of these approaches and demonstrate that editing cortical segmentations using two-dimensional histogram representations as an additional post-processing step aids existing algorithms and yields improved gray matter borders. By making our data and corresponding expert (ground truth) segmentations openly available, we facilitate future efforts to develop and test segmentation algorithms on this challenging type of data.
Subject(s)
Gray Matter/anatomy & histology , Magnetic Resonance Imaging/methods , Female , Gray Matter/diagnostic imaging , Humans , Image Processing, Computer-Assisted , Magnetic Fields , MaleABSTRACT
Determination of cortical thickness using MRI has often been criticized due to the presence of various error sources. Specifically, anatomical MRI relying on T1 contrast may be unreliable due to spatially variable image contrast between gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF). Especially at ultra-high field (≥ 7T) MRI, transmit and receive B1 -related image inhomogeneities can hamper correct classification of tissue types. In the current paper, we demonstrate that residual B1+ (transmit) inhomogeneities in the T1 -weighted and quantitative T1 images using the MP2RAGE sequence at 7T lead to biases in cortical thickness measurements. As expected, post-hoc correction for the spatially varying B1+ profile reduced the apparent T1 values across the cortex in regions with low B1+, and slightly increased apparent T1 in regions with high B1+. As a result, improved contrast-to-noise ratio both at the GM-CSF and GM-WM boundaries can be observed leading to more accurate surface reconstructions and cortical thickness estimates. Overall, the changes in cortical thickness ranged between a 5% decrease to a 70% increase after B1+ correction, reducing the variance of cortical thickness values across the brain dramatically and increasing the comparability with normative data. More specifically, the cortical thickness estimates increased in regions characterized by a strong decrease of apparent T1 after B1+ correction in regions with low B1+ due to improved detection of the pial surface. The current results suggest that cortical thickness can be more accurately determined using MP2RAGE data at 7T if B1+ inhomogeneities are accounted for.
Subject(s)
Brain Mapping , Cerebral Cortex/physiology , Gray Matter/diagnostic imaging , Adult , Aged , Cerebral Cortex/diagnostic imaging , Cerebrospinal Fluid/diagnostic imaging , Female , Healthy Volunteers , Humans , Image Processing, Computer-Assisted , Magnetic Resonance Imaging , Male , Middle Aged , White Matter , Young AdultABSTRACT
Arterial spin labeling (ASL) is the primary non-invasive MRI approach to measure baseline cerebral blood flow (CBF) in healthy subjects and patients. ASL also allows concurrent functional BOLD signal and CBF measurements, but the latter typically suffer from low contrast-to-noise (CNR) ratio. Ultra-high-field imaging significantly boosts BOLD signal CNR. However, it is contested whether also CBF CNR benefits from increasing magnetic field strength, especially given that technical challenges related to field inhomogeneities and power deposition constraints exist. Recently, we presented an optimized PASL technique that utilizes tr-FOCI inversion pulses and dielectric pads to overcome the temporal resolution limitations of previous 7T ASL implementations (Ivanov et al., in press; 2017). The primary goal of this study was to compare its performance to that of 3T ASL approaches - both pulsed ASL (PASL) and pseudo-continuous (pCASL) - concerning functional studies using simultaneous CBF and BOLD signal acquisition. To this aim, we investigated a wide range of parameters that can influence CBF and BOLD signal sensitivities: spatial resolution, labeling scheme, parallel imaging and echo time. We found that 7T ASL is superior in terms of CBF and BOLD temporal signal-to-noise ratio (SNR) and activation volume compared to all 3T ASL variants, in particular at high spatial resolution. Our results show that the advantages of 7T for ASL stem from increased image SNR, especially when parallel imaging is used. The gray matter baseline CBF was in good agreement for all 3T ASL variants, but a significantly lower value was obtained at 7T. The labeling scheme utilized was also found to significantly influence the measured perfusion territories CBF. In conclusion, a single-echo accelerated 7T PASL is recommended for high spatial and temporal resolution CBF and BOLD imaging, while a 3T dual-echo pCASL approach without parallel imaging may be preferred for low (i.e., 3mm isotropic and lower) resolution functional perfusion and BOLD applications.
Subject(s)
Brain/diagnostic imaging , Image Processing, Computer-Assisted/methods , Magnetic Resonance Imaging/methods , Adult , Brain/blood supply , Cerebrovascular Circulation/physiology , Female , Humans , Male , Signal-To-Noise Ratio , Spin Labels , Young AdultABSTRACT
Different magnetic resonance (MR) parameters, such as R1 (=1/T1) or T2∗, have been used to visualize non-invasively the myelin distribution across the cortical sheet. Myelin contrast is consistently enhanced in the primary sensory and some higher order cortical areas (such as MT or the cingulate cortex), which renders it suitable for subject-specific anatomical cortical parcellation. However, no systematic comparison has been performed between the previously proposed MR parameters, i.e., the longitudinal and transversal relaxation values (or their ratios), for myelin mapping at 7 Tesla. In addition, usually these MR parameters are acquired in a non-quantitative manner ("weighted" parameters). Here, we evaluated the differences in 'parcellability,' contrast-to-noise ratio (CNR) and inter- and intra-subject variability and reproducibility, respectively, between high-resolution cortical surface maps based on these weighted MR parameters and their quantitative counterparts in ten healthy subjects. All parameters were obtained in a similar acquisition time and possible transmit- or receive-biases were removed during post-processing. It was found that CNR per unit time and parcellability were lower for the transversal compared to the longitudinal relaxation parameters. Further, quantitative R1 was characterized by the lowest inter- and intra-subject coefficient of variation (5.53 and 1.63%, respectively), making R1 a better parameter to map the myelin distribution compared to the other parameters. Moreover, quantitative MRI approaches offer the advantage of absolute rather than relative characterization of the underlying biochemical composition of the tissue, allowing more reliable comparison within subjects and between healthy subjects and patients. Finally, we explored two parcellation methods (thresholding the MR parameter values vs. surface gradients of these values) to determine areal borders based on the cortical surface pattern. It is shown that both methods are partially observer-dependent, needing manual interaction (i.e., choice of threshold or connecting high gradient values) to provide unambiguous borders.