Guidelines for Specialized Epilepsy Centers: Executive Summary of the Report of the National Association of Epilepsy Centers Guideline Panel.

The National Association of Epilepsy Centers first published the guidelines for epilepsy centers in 1990, which were last updated in 2010. Since that update, epilepsy care and the science of guideline development have advanced significantly, including the importance of incorporating a diversity of stakeholder perspectives such as those of patients and their caregivers. Currently, despite extensive published data examining the efficacy of treatments and diagnostic testing for epilepsy, there remain significant gaps in data identifying the essential services needed for a comprehensive epilepsy center and the optimal manner for their delivery. The trustworthy consensus-based statements (TCBS) process produces unbiased, scientifically valid guidelines through a transparent process that incorporates available evidence and expert opinion. A systematic literature search returned 5937 relevant studies from which 197 articles were retained for data extraction. A panel of 41 stakeholders with diverse expertise evaluated this evidence and drafted recommendations following the TCBS process. The panel reached consensus on 52 recommendations covering services provided by specialized epilepsy centers in both the inpatient and outpatient settings in major topic areas including epilepsy monitoring unit care, surgery, neuroimaging, neuropsychology, genetics, and outpatient care. Recommendations were informed by the evidence review and reflect the consensus of a broad panel of expert opinions.

EMG-projected MEG High-Resolution Source Imaging of Human Motor Execution: Brain-Muscle Coupling above Movement Frequencies.

Magnetoencephalography (MEG) is a non-invasive functional imaging technique for pre-surgical mapping. However, movement-related MEG functional mapping of primary motor cortex (M1) has been challenging in presurgical patients with brain lesions and sensorimotor dysfunction due to the large numbers of trails needed to obtain adequate signal to noise. Moreover, it is not fully understood how effective the brain communication is with the muscles at frequencies above the movement frequency and its harmonics. We developed a novel Electromyography (EMG)-projected MEG source imaging technique for localizing M1 during ~1 minute recordings of left and right self-paced finger movements (~1 Hz). High-resolution MEG source images were obtained by projecting M1 activity towards the skin EMG signal without trial averaging. We studied delta (1-4 Hz), theta (4-7 Hz), alpha (8-12 Hz), beta (15-30 Hz), and gamma (30-90 Hz) bands in 13 healthy participants (26 datasets) and two presurgical patients with sensorimotor dysfunction. In healthy participants, EMG-projected MEG accurately localized M1 with high accuracy in delta (100.0%), theta (100.0%), and beta (76.9%) bands, but not alpha (34.6%) and gamma (0.0%) bands. Except for delta, all other frequency bands were above the movement frequency and its harmonics. In both presurgical patients, M1 activity in the affected hemisphere was also accurately localized, despite highly irregular EMG movement patterns in one patient. Altogether, our EMG-projected MEG imaging approach is highly accurate and feasible for M1 mapping in presurgical patients. The results also provide insight into movement related brain-muscle coupling above the movement frequency and its harmonics.

Magnetoencephalogram-based brain-computer interface for hand-gesture decoding using deep learning.

Advancements in deep learning algorithms over the past decade have led to extensive developments in brain-computer interfaces (BCI). A promising imaging modality for BCI is magnetoencephalography (MEG), which is a non-invasive functional imaging technique. The present study developed a MEG sensor-based BCI neural network to decode Rock-Paper-scissors gestures (MEG-RPSnet). Unique preprocessing pipelines in tandem with convolutional neural network deep-learning models accurately classified gestures. On a single-trial basis, we found an average of 85.56% classification accuracy in 12 subjects. Our MEG-RPSnet model outperformed two state-of-the-art neural network architectures for electroencephalogram-based BCI as well as a traditional machine learning method, and demonstrated equivalent and/or better performance than machine learning methods that have employed invasive, electrocorticography-based BCI using the same task. In addition, MEG-RPSnet classification performance using an intra-subject approach outperformed a model that used a cross-subject approach. Remarkably, we also found that when using only central-parietal-occipital regional sensors or occipitotemporal regional sensors, the deep learning model achieved classification performances that were similar to the whole-brain sensor model. The MEG-RSPnet model also distinguished neuronal features of individual hand gestures with very good accuracy. Altogether, these results show that noninvasive MEG-based BCI applications hold promise for future BCI developments in hand-gesture decoding.

Neuroimaging in schizophrenia: A review article.

In this review article we have consolidated the imaging literature of patients with schizophrenia across the full spectrum of modalities in radiology including computed tomography (CT), morphologic magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), magnetic resonance spectroscopy (MRS), positron emission tomography (PET), and magnetoencephalography (MEG). We look at the impact of various subtypes of schizophrenia on imaging findings and the changes that occur with medical and transcranial magnetic stimulation (TMS) therapy. Our goal was a comprehensive multimodality summary of the findings of state-of-the-art imaging in untreated and treated patients with schizophrenia. Clinical imaging in schizophrenia is used to exclude structural lesions which may produce symptoms that may mimic those of patients with schizophrenia. Nonetheless one finds global volume loss in the brains of patients with schizophrenia with associated increased cerebrospinal fluid (CSF) volume and decreased gray matter volume. These features may be influenced by the duration of disease and or medication use. For functional studies, be they fluorodeoxyglucose positron emission tomography (FDG PET), rs-fMRI, task-based fMRI, diffusion tensor imaging (DTI) or MEG there generally is hypoactivation and disconnection between brain regions. However, these findings may vary depending upon the negative or positive symptomatology manifested in the patients. MR spectroscopy generally shows low N-acetylaspartate from neuronal loss and low glutamine (a neuroexcitatory marker) but glutathione may be elevated, particularly in non-treatment responders. The literature in schizophrenia is difficult to evaluate because age, gender, symptomatology, comorbidities, therapy use, disease duration, substance abuse, and coexisting other psychiatric disorders have not been adequately controlled for, even in large studies and meta-analyses.

Functional topologies of spatial cognition predict cognitive and motor progression in Parkinson's.

Background: Spatial cognition deteriorates in Parkinson's disease (PD), but the neural substrates are not understood, despite the risk for future dementia. It is also unclear whether deteriorating spatial cognition relates to changes in other cognitive domains or contributes to motor dysfunction. Objective: This study aimed to identify functional connectivity abnormalities in cognitively normal PD (PDCN) in regions that support spatial cognition to determine their relationship to interfacing cognitive functions and motor disability, and to determine if they predict cognitive and motor progression 2 years later in a PDCN subsample. Methods: Sixty-three PDCN and 43 controls underwent functional MRI while judging whether pictures, rotated at various angles, depicted the left or right hand. The task activates systems that respond to increases in rotation angle, a proxy for visuospatial difficulty. Angle-modulated functional connectivity was analyzed for frontal cortex, posterior cortex, and basal ganglia regions. Results: Two aberrant connectivity patterns were found in PDCN, which were condensed into principal components that characterized the strength and topology of angle-modulated connectivity. One topology related to a marked failure to amplify frontal, posterior, and basal ganglia connectivity with other brain areas as visuospatial demands increased, unlike the control group (control features). Another topology related to functional reorganization whereby regional connectivity was strengthened with brain areas not recruited by the control group (PDCN features). Functional topologies correlated with diverse cognitive domains at baseline, underscoring their influences on spatial cognition. In PDCN, expression of topologies that were control features predicted greater cognitive progression longitudinally, suggesting inefficient communications within circuitry normally recruited to handle spatial demands. Conversely, stronger expression of topologies that were PDCN features predicted less longitudinal cognitive decline, suggesting functional reorganization was compensatory. Parieto-occipital topologies (control features) had different prognostic implications for longitudinal changes in motor disability. Expression of one topology predicted less motor decline, whereas expression of another predicted increased postural instability and gait disturbance (PIGD) feature severity. Concurrently, greater longitudinal decline in spatial cognition predicted greater motor and PIGD feature progression, suggesting deterioration in shared substrates. Conclusion: These novel discoveries elucidate functional mechanisms of visuospatial cognition in PDCN, which foreshadow future cognitive and motor disability.

Magnetoencephalography Language Mapping Using Auditory Memory Retrieval and Silent Repeating Task.

PURPOSE: The study aims to (1) examine the spatiotemporal map of magnetoencephalography-evoked responses during an Auditory Memory Retrieval and Silent Repeating (AMRSR) task, and determine the hemispheric dominance for language, and (2) evaluate the accuracy of the AMRSR task in Wernicke and Broca area localization. METHODS: In 30 patients with brain tumors and/or epilepsies, the AMRSR task was used to evoke magnetoencephalography responses. We applied Fast VEctor-based Spatial-Temporal Analyses with minimum L1-norm source imaging method to the magnetoencephalography responses for localizing the brain areas evoked by the AMRSR task. RESULTS: The Fast-VEctor-based Spatial-Temporal Analysis found consistent activation in the posterior superior temporal gyrus around 300 to 500 ms, and another activation in the frontal cortex (pars opercularis and/or pars triangularis) around 600 to 900 ms, which were localized to the Wernicke area (BA 22) and Broca area (BA 44 and BA 45), respectively. The language-dominant hemispheric laterization elicited by the AMRSR task was comparable with the result from an Auditory Dichotic task result given to the same patient, with the exception that AMRSR is more sensitive on bilateral language laterization cases on finding the Wernicke and Broca areas. CONCLUSIONS: For all patients who successfully finished the AMRSR task, Fast-VEctor-based Spatial-Temporal Analysis could establish accurate and robust localizations of Broca and Wernicke area and determine hemispheric dominance. For subjects with normal auditory functionality, the AMRSR paradigm evaluation showed significant promise in providing reliable assessments of cerebral language dominance and language network localization.

Detection of Chronic Blast-Related Mild Traumatic Brain Injury with Diffusion Tensor Imaging and Support Vector Machines.

Blast-related mild traumatic brain injury (bmTBI) often leads to long-term sequalae, but diagnostic approaches are lacking due to insufficient knowledge about the predominant pathophysiology. This study aimed to build a diagnostic model for future verification by applying machine-learning based support vector machine (SVM) modeling to diffusion tensor imaging (DTI) datasets to elucidate white-matter features that distinguish bmTBI from healthy controls (HC). Twenty subacute/chronic bmTBI and 19 HC combat-deployed personnel underwent DTI. Clinically relevant features for modeling were selected using tract-based analyses that identified group differences throughout white-matter tracts in five DTI metrics to elucidate the pathogenesis of injury. These features were then analyzed using SVM modeling with cross validation. Tract-based analyses revealed abnormally decreased radial diffusivity (RD), increased fractional anisotropy (FA) and axial/radial diffusivity ratio (AD/RD) in the bmTBI group, mostly in anterior tracts (29 features). SVM models showed that FA of the anterior/superior corona radiata and AD/RD of the corpus callosum and anterior limbs of the internal capsule (5 features) best distinguished bmTBI from HCs with 89% accuracy. This is the first application of SVM to identify prominent features of bmTBI solely based on DTI metrics in well-defined tracts, which if successfully validated could promote targeted treatment interventions.

Internetwork Connectivity Predicts Cognitive Decline in Parkinson's and Is Altered by Genetic Variants.

In Parkinson's disease (PD) functional changes in the brain occur years before significant cognitive symptoms manifest yet core large-scale networks that maintain cognition and predict future cognitive decline are poorly understood. The present study investigated internetwork functional connectivity of visual (VN), anterior and posterior default mode (aDMN, pDMN), left/right frontoparietal (LFPN, RFPN), and salience (SN) networks in 63 cognitively normal PD (PDCN) and 43 healthy controls who underwent resting-state functional MRI. The functional relevance of internetwork coupling topologies was tested by their correlations with baseline cognitive performance in each group and with 2-year cognitive changes in a PDCN subsample. To disentangle heterogeneity in neurocognitive functioning, we also studied whether α-synuclein (SNCA) and microtubule-associated protein tau (MAPT) variants alter internetwork connectivity and/or accelerate cognitive decline. We found that internetwork connectivity was largely preserved in PDCN, except for reduced pDMN-RFPN/LFPN couplings, which correlated with poorer baseline global cognition. Preserved internetwork couplings also correlated with domain-specific cognition but differently for the two groups. In PDCN, stronger positive internetwork coupling topologies correlated with better cognition at baseline, suggesting a compensatory mechanism arising from less effective deployment of networks that supported cognition in healthy controls. However, stronger positive internetwork coupling topologies typically predicted greater longitudinal decline in most cognitive domains, suggesting that they were surrogate markers of neuronal vulnerability. In this regard, stronger aDMN-SN, LFPN-SN, and/or LFPN-VN connectivity predicted longitudinal decline in attention, working memory, executive functioning, and visual cognition, which is a risk factor for dementia. Coupling strengths of some internetwork topologies were altered by genetic variants. PDCN carriers of the SNCA risk allele showed amplified anticorrelations between the SN and the VN/pDMN, which supported cognition in healthy controls, but strengthened pDMN-RFPN connectivity, which maintained visual memory longitudinally. PDCN carriers of the MAPT risk allele showed greater longitudinal decline in working memory and increased VN-LFPN connectivity, which in turn predicted greater decline in visuospatial processing. Collectively, the results suggest that cognition is maintained by functional reconfiguration of large-scale internetwork communications, which are partly altered by genetic risk factors and predict future domain-specific cognitive progression.

Comprehensive assessment of in vivo lumbar spine intervertebral discs using a 3D adiabatic T1ρ prepared ultrashort echo time (UTE-Adiab-T1ρ) pulse sequence.

BACKGROUND: T1ρ has been extensively reported as a sensitive biomarker of biochemical changes in the nucleus pulposus (NP) and annulus fibrosis of intervertebral discs (IVDs). However, no T1ρ study of cartilaginous endplates (CEPs) has yet been reported because the relatively long echo times (TEs) of conventional clinical T1ρ sequences cannot effectively capture the fast-decaying magnetic resonance signals of CEPs, which have very short T2/T2*s. This can be overcome by using ultrashort echo time (UTE) T1ρ acquisitions. METHODS: Seventeen subjects underwent UTE with adiabatic T1ρ preparation (UTE-Adiab-T1ρ) and T2-weighted fast spin echo imaging of their lumbar spines. Each IVD was manually segmented into seven regions (i.e., outer anterior annulus fibrosis, inner anterior annulus fibrosis, outer posterior annulus fibrosis, inner posterior annulus fibrosis, superior CEP, inferior CEP, and NP). T1ρ values of these sub-regions were correlated with IVD modified Pfirrmann grades and subjects' ages. In addition, T1ρ values were compared in subjects with and without low back pain (LBP). RESULTS: Correlations of T1ρ values of the outer posterior annulus fibrosis, superior CEP, inferior CEP, and NP with modified Pfirrmann grades were significant (P<0.05) with R values of 0.51, 0.36, 0.38, and -0.94, respectively. Correlations of T1ρ values of the outer anterior annulus fibrosis, outer posterior annulus fibrosis, and NP with ages were significant with R equal to 0.52, 0.71, and -0.76, respectively. T1ρ differences of the outer posterior annulus fibrosis, inferior CEP, and NP between the subjects with and without LBP were significant (P=0.005, 0.020, and 0.000, respectively). CONCLUSIONS: The UTE-Adiab-T1ρ sequence can quantify T1ρ of whole IVDs including CEPs. This is an advance, and of value for comprehensive assessment of IVD degeneration.

Semantic Recollection in Parkinson's Disease: Functional Reconfiguration and MAPT Variants.

Decline in semantic cognition in early stages of Parkinson's disease (PD) is a leading risk factor for future dementia, yet the underlying neural mechanisms are not understood. The present study addressed this gap by investigating the functional connectivity of regions involved in semantic recollection. We further examined whether microtubule-associated protein tau (MAPT) risk variants, which may accelerate cognitive decline, altered the strength of regional functional connections. Cognitively normal PD and healthy elder controls underwent fMRI while performing a fame-discrimination task, which activates the semantic network. Analyses focused on disturbances in fame-modulated functional connectivity in PD for regions that govern semantic recollection and interrelated processes. Group differences were found in multiple connectivity features, which were reduced into principal components that reflected the strength of fame-modulated regional couplings with other brain areas. Despite the absence of group differences in semantic cognition, two aberrant connectivity patterns were uncovered in PD. One pattern was related to a loss in frontal, parietal, and temporal connection topologies that governed semantic recollection in older controls. Another pattern was characterized by functional reconfiguration, wherein frontal, parietal, temporal and caudate couplings were strengthened with areas that were not recruited by controls. Correlations between principal component scores and cognitive measures suggested that reconfigured frontal coupling topologies in PD supported compensatory routes for accessing semantic content, whereas reconfigured parietal, temporal, and caudate connection topologies were detrimental or unrelated to cognition. Increased tau transcription diminished recruitment of compensatory frontal topologies but amplified recruitment of parietal topologies that were unfavorable for cognition. Collectively, the findings provide a new understanding of early vulnerabilities in the functional architecture of regional connectivity during semantic recollection in cognitively normal PD. The findings also have implications for tracking cognitive progression and selecting patients who stand to benefit from therapeutic interventions.

High contrast cartilaginous endplate imaging using a 3D adiabatic inversion-recovery-prepared fat-saturated ultrashort echo time (3D IR-FS-UTE) sequence.

Ultrashort echo time (UTE) sequences can image tissues with transverse T 2 /T 2 * relaxations too short to be efficiently observed on routine clinical MRI sequences, such as the vertebral body cartilaginous endplate (CEP). Here, we describe a 3D adiabatic inversion-recovery-prepared fat-saturated ultrashort echo time (3D IR-FS-UTE) sequence to highlight the CEP of vertebral bodies in comparison to the intervertebral disc (IVD) and bone marrow fat (BF) at 3 T. The IR-FS-UTE sequence used a 3D UTE sequence combined with an adiabatic IR preparation pulse centered in the middle of the water and fat peaks, while a fat saturation module was used to suppress the signal from fat. A slab-selective half pulse was used for signal excitation, and a 3D center-out cones trajectory was used for more efficient data sampling. The 3D IR-FS-UTE sequence was applied to an ex vivo human spine sample, as well as the spines of six healthy volunteers and of three patients with back pain. Bright continuous lines representing signal from CEP were found in healthy IVDs. The measured contrast-to-noise ratio was 18.5 ± 4.9 between the CEP and BF, and 20.3 ± 4.15 between the CEP and IVD for the six volunteers. Abnormal IVDs showed CEP discontinuity or irregularity in the sample and patient studies. In conclusion, the proposed 3D IR-FS-UTE sequence is feasible for imaging the vertebral body's CEP in vivo with high contrast.

Case report 68Ga-DOTATATE of optic nerve sheath meningioma.

We report a patient with an optic nerve sheath meningioma whose diagnosis and management were guided by using Gallium-68 DOTA-Tyr3-octreotatate (68Ga-DOTATATE). Positron Emission Tomography-Computed Tomography (PET-CT).

Resting-state magnetoencephalography source magnitude imaging with deep-learning neural network for classification of symptomatic combat-related mild traumatic brain injury.

Combat-related mild traumatic brain injury (cmTBI) is a leading cause of sustained physical, cognitive, emotional, and behavioral disabilities in Veterans and active-duty military personnel. Accurate diagnosis of cmTBI is challenging since the symptom spectrum is broad and conventional neuroimaging techniques are insensitive to the underlying neuropathology. The present study developed a novel deep-learning neural network method, 3D-MEGNET, and applied it to resting-state magnetoencephalography (rs-MEG) source-magnitude imaging data from 59 symptomatic cmTBI individuals and 42 combat-deployed healthy controls (HCs). Analytic models of individual frequency bands and all bands together were tested. The All-frequency model, which combined delta-theta (1-7 Hz), alpha (8-12 Hz), beta (15-30 Hz), and gamma (30-80 Hz) frequency bands, outperformed models based on individual bands. The optimized 3D-MEGNET method distinguished cmTBI individuals from HCs with excellent sensitivity (99.9 ± 0.38%) and specificity (98.9 ± 1.54%). Receiver-operator-characteristic curve analysis showed that diagnostic accuracy was 0.99. The gamma and delta-theta band models outperformed alpha and beta band models. Among cmTBI individuals, but not controls, hyper delta-theta and gamma-band activity correlated with lower performance on neuropsychological tests, whereas hypo alpha and beta-band activity also correlated with lower neuropsychological test performance. This study provides an integrated framework for condensing large source-imaging variable sets into optimal combinations of regions and frequencies with high diagnostic accuracy and cognitive relevance in cmTBI. The all-frequency model offered more discriminative power than each frequency-band model alone. This approach offers an effective path for optimal characterization of behaviorally relevant neuroimaging features in neurological and psychiatric disorders.

Brain microstructure mediates sex-specific patterns of cognitive aging.

Normal brain aging is characterized by declining neuronal integrity, yet it remains unclear how microstructural injury influences cognitive aging and whether such mechanisms differ between sexes. Using restriction spectrum imaging (RSI), we examined sex differences in associations between brain microstructure and cognitive function in 147 community-dwelling older men and women (56-99 years). Gray and white matter microstructure correlated with global cognition, executive function, visuospatial memory, episodic memory, and logical memory, with the strongest associations for restricted, hindered and free isotropic diffusion. Associations were stronger for women than for men, a difference likely due to greater age-related variability in cognitive scores and microstructure in women. Isotropic diffusion mediated effects of age on cognition for both sexes, though distinct mediation patterns were present for women and men. For women, hippocampal and corpus callosum microstructure mediated age effects on verbal and visuospatial memory, respectively, whereas for men fiber microstructure (mainly fornix and corpus callosum) mediated age effects on executive function and visuospatial memory. These findings implicate sex-specific pathways by which changing brain cytoarchitecture contributes to cognitive aging, and suggest that RSI may be useful for evaluating risk for cognitive decline or monitoring efficacy of interventions to preserve brain health in later life.

Age and Sex Differences in the Associations of Pulse Pressure With White Matter and Subcortical Microstructure.

Midlife vascular disease increases risk for dementia and effects of vascular dysfunction on brain health differ between men and women. Elevated pulse pressure, a surrogate for arterial stiffness, contributes to cerebrovascular pathology and white matter damage that may advance cognitive aging; however, it remains unclear how associations between pulse pressure and neural integrity differ by sex and age. This study used restriction spectrum imaging to examine associations between pulse pressure and brain microstructure in community-dwelling women (N=88) and men (N=55), aged 56 to 97 (mean, 76.3) years. Restricted isotropic (presumed intracellular), hindered isotropic (presumed extracellular), neurite density, and free water diffusion were computed in white matter tracts and subcortical regions. After adjustment for age and sex, higher pulse pressure correlated with lower restricted isotropic diffusion in global white matter, with more pronounced associations in parahippocampal cingulum, as well as in thalamus and hippocampus. Subgroup analyses demonstrated stronger correlations between pulse pressure and restricted isotropic diffusion in association fibers for participants ≤75 years than for older participants, with stronger effects for women than men of this age group. Microstructure in parahippocampal cingulum and thalamus differed by pulse pressure level regardless of antihypertensive treatment. Increased pulse pressure may lead to widespread injury to white matter and subcortical structures, with greatest vulnerability for women in late middle to early older age. Restriction spectrum imaging could be useful for monitoring microstructural changes indicative of neuronal loss or shrinkage, demyelination, or inflammation that accompany age-related cerebrovascular dysfunction.

High-Contrast Lumbar Spinal Bone Imaging Using a 3D Slab-Selective UTE Sequence.

Ultra-short echo time (UTE) MRI with post-processing is a promising technique in bone imaging that produces a similar contrast to computed tomography (CT). Here, we propose a 3D slab-selective ultrashort echo time (UTE) sequence together with image post-processing to image bone structures in the lumbar spine. We also explore the intermodality agreement between the UTE and CT images. The lumbar spines of two healthy volunteers were imaged with 3D UTE using five different resolutions to determine the best imaging protocol. Then, four patients with low back pain were imaged with both the 3D UTE sequence and CT to investigate agreement between the imaging methods. Two other patients with low back pain were then imaged with the 3D UTE sequence and clinical conventional T1-weighted and T2-weighted fast spin-echo (FSE) MRI sequences for qualitative comparison. The 3D UTE sequence together with post-processing showed high contrast images of bone and high intermodality agreement with CT images. In conclusion, post-processed slab-selective UTE imaging is a feasible approach for highlighting bone structures in the lumbar spine and demonstrates significant anatomical correlation with CT images.

Associations between age and brain microstructure in older community-dwelling men and women: the Rancho Bernardo Study.

Cytoarchitectural brain changes during normal aging remain poorly characterized, and it is unclear whether patterns of brain aging differ by sex. This study used restriction spectrum imaging to examine associations between age and brain microstructure in 147 community-dwelling participants (aged 56-99 years). Widespread associations with age in multiple diffusion compartments, including increased free water, decreased restricted and hindered diffusion, and reduced neurite complexity, were observed in the cortical gray matter, the white matter tracts, and the hippocampus. Age differences in cortical microstructure were largely independent of atrophy. Associations were mostly global, although foci of stronger effects emerged in the fornix, anterior thalamic radiation and commissural fibers, and the medial temporal, orbitofrontal, and occipital cortices. Age differences were stronger and more widespread for women than men, even after adjustment for education, hypertension, and body mass index. Restriction spectrum imaging may be a convenient, noninvasive tool for monitoring changes in diffusion properties that are thought to reflect reduced cellular fractions and neurite density or complexity, which occur with typical aging, and for detecting sex differences in patterns of brain aging.

Myelin Imaging in Human Brain Using a Short Repetition Time Adiabatic Inversion Recovery Prepared Ultrashort Echo Time (STAIR-UTE) MRI Sequence in Multiple Sclerosis.

Background Water signal contamination is a major challenge for direct ultrashort echo time (UTE) imaging of myelin in vivo because water contributes most of the signals detected in white matter. Purpose To validate a new short repetition time (TR) adiabatic inversion recovery (STAIR) prepared UTE (STAIR-UTE) sequence designed to suppress water signals and to allow imaging of ultrashort T2 protons of myelin in white matter using a clinical 3-T scanner. Materials and Methods In this prospective study, an optimization framework was used to obtain the optimal inversion time for nulling water signals using STAIR-UTE imaging at different TRs. Numeric simulation and phantom studies were performed. Healthy volunteers and participants with multiple sclerosis (MS) underwent MRI between November 2018 and October 2019 to compare STAIR-UTE and a clinical T2-weighted fluid-attenuated inversion recovery sequence for assessment of MS lesions. UTE measures of myelin were also performed to allow comparison of signals in lesions and with those in normal-appearing white matter (NAWM) in patients with MS and in normal white matter (NWM) in healthy volunteers. Results Simulation and phantom studies both suggest that the proposed STAIR-UTE technique can effectively suppress long T2 tissues with a broad range of T1s. Ten healthy volunteers (mean age, 33 years ± 8 [standard deviation]; six women) and 10 patients with MS (mean age, 51 years ± 16; seven women) were evaluated. The three-dimensional STAIR-UTE sequence effectively suppressed water components in white matter and selectively imaged myelin, which had a measured T2* value of 0.21 msec ± 0.04 in the volunteer study. A much lower mean UTE measure of myelin proton density was found in MS lesions (3.8 mol/L ± 1.5), and a slightly lower mean UTE measure was found in NAWM (7.2 mol/L ± 0.8) compared with that in NWM (8.0 mol/L ± 0.8) in the healthy volunteers (P < .001 for both comparisons). Conclusion The short repetition time adiabatic inversion recovery-prepared ultrashort echo time sequence provided efficient water signal suppression for volumetric imaging of myelin in the brain and showed excellent myelin signal contrast as well as marked ultrashort echo time signal reduction in multiple sclerosis lesions and a smaller reduction in normal-appearing white matter compared with normal white matter in volunteers. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Messina and Port in this issue.