Neuroimaging Findings in US Government Personnel and Their Family Members Involved in Anomalous Health Incidents.

Importance: US government personnel stationed internationally have reported anomalous health incidents (AHIs), with some individuals experiencing persistent debilitating symptoms. Objective: To assess the potential presence of magnetic resonance imaging (MRI)-detectable brain lesions in participants with AHIs, with respect to a well-matched control group. Design, Setting, and Participants: This exploratory study was conducted at the National Institutes of Health (NIH) Clinical Center and the NIH MRI Research Facility between June 2018 and November 2022. Eighty-one participants with AHIs and 48 age- and sex-matched control participants, 29 of whom had similar employment as the AHI group, were assessed with clinical, volumetric, and functional MRI. A high-quality diffusion MRI scan and a second volumetric scan were also acquired during a different session. The structural MRI acquisition protocol was optimized to achieve high reproducibility. Forty-nine participants with AHIs had at least 1 additional imaging session approximately 6 to 12 months from the first visit. Exposure: AHIs. Main Outcomes and Measures: Group-level quantitative metrics obtained from multiple modalities: (1) volumetric measurement, voxel-wise and region of interest (ROI)-wise; (2) diffusion MRI-derived metrics, voxel-wise and ROI-wise; and (3) ROI-wise within-network resting-state functional connectivity using functional MRI. Exploratory data analyses used both standard, nonparametric tests and bayesian multilevel modeling. Results: Among the 81 participants with AHIs, the mean (SD) age was 42 (9) years and 49% were female; among the 48 control participants, the mean (SD) age was 43 (11) years and 42% were female. Imaging scans were performed as early as 14 days after experiencing AHIs with a median delay period of 80 (IQR, 36-544) days. After adjustment for multiple comparisons, no significant differences between participants with AHIs and control participants were found for any MRI modality. At an unadjusted threshold (P < .05), compared with control participants, participants with AHIs had lower intranetwork connectivity in the salience networks, a larger corpus callosum, and diffusion MRI differences in the corpus callosum, superior longitudinal fasciculus, cingulum, inferior cerebellar peduncle, and amygdala. The structural MRI measurements were highly reproducible (median coefficient of variation <1% across all global volumetric ROIs and <1.5% for all white matter ROIs for diffusion metrics). Even individuals with large differences from control participants exhibited stable longitudinal results (typically, <±1% across visits), suggesting the absence of evolving lesions. The relationships between the imaging and clinical variables were weak (median Spearman ρ = 0.10). The study did not replicate the results of a previously published investigation of AHIs. Conclusions and Relevance: In this exploratory neuroimaging study, there were no significant differences in imaging measures of brain structure or function between individuals reporting AHIs and matched control participants after adjustment for multiple comparisons.

Serum NfL and GFAP as biomarkers of progressive neurodegeneration in TBI.

BACKGROUND: We examined spatial patterns of brain atrophy after mild, moderate, and severe traumatic brain injury (TBI), the relationship between progression of brain atrophy with initial traumatic axonal injury (TAI), cognitive outcome, and with serum biomarkers of brain injury. METHODS: A total of 143 patients with TBI and 43 controls were studied cross-sectionally and longitudinally up to 5 years with multiple assessments, which included brain magnetic resonance imaging, cognitive testing, and serum biomarkers. RESULTS: TBI patients showed progressive volume loss regardless of injury severity over several years, and TAI was independently associated with accelerated brain atrophy. Cognitive performance improved over time. Higher baseline serum neurofilament light (NfL) and glial fibrillary acidic protein (GFAP) were associated with greater rate of brain atrophy over 5 years. DISCUSSSION: Spatial patterns of atrophy differ by injury severity and TAI is associated with the progression of brain atrophy. Serum NfL and GFAP show promise as non-invasive prognostic biomarkers of progressive neurodegeneration in TBI. HIGHLIGHTS: In this longitudinal study of patient with mild, moderate, and severe traumatic brain injury (TBI) who were assessed with paired magnetic resonance imaging (MRI), blood biomarkers, and cognitive assessments, we found that brain atrophy after TBI is progressive and continues for many years even after a mild head trauma without signs of brain injury on conventional MRI. We found that spatial pattern of brain atrophy differs between mild, moderate, and severe TBI, where in patients with mild TBI , atrophy is mainly seen in the gray matter, while in those with moderate to severe brain injury atrophy is predominantly seen in the subcortical gray matter and whiter matter. Cognitive performance improves over time after a TBI. Serum measures of neurofilament light or glial fibrillary acidic protein are associated with progression of brain atrophy after TBI.

Simultaneous Acquisition of Diffusion Tensor and Dynamic Diffusion MRI.

BACKGROUND: Dynamic diffusion magnetic resonance imaging (ddMRI) metrics can assess transient microstructural alterations in tissue diffusivity but requires additional scan time hindering its clinical application. PURPOSE: To determine whether a diffusion gradient table can simultaneously acquire data to estimate dynamic and diffusion tensor imaging (DTI) metrics. STUDY TYPE: Prospective. SUBJECTS: Seven healthy subjects, 39 epilepsy patients (15 female, 31 male, age ± 15). FIELD STRENGTH/SEQUENCE: Two-dimensional diffusion MRI (b = 1000 s/mm2 ) at a field strength of 3 T. Sessions in healthy subjects-standard ddMRI (30 directions), standard DTI (15 and 30 directions), and nested cubes scans (15 and 30 directions). Sessions in epilepsy patients-two 30 direction (standard ddMRI, 10 nested cubes) or two 15 direction scans (standard DTI, 5 nested cubes). ASSESSMENT: Fifteen direction DTI was repeated twice for within-session test-retest measurements in healthy subjects. Bland-Altman analysis computed bias and limits of agreement for DTI metrics using test-retest scans and standard 15 direction vs. 5 nested cubes scans. Intraclass correlation (ICC) analysis compared tensor metrics between 15 direction DTI scans (standard vs. 5 nested cubes) and the coefficients of variation (CoV) of trace and apparent diffusion coefficient (ADC) between 30 direction ddMRI scans (standard vs. 10 nested cubes). STATISTICAL TESTS: Bland-Altman and ICC analysis using a P-value of 0.05 for statistical significance. RESULTS: Correlations of mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were strong and significant in gray (ICC > 0.95) and white matter (ICC > 0.95) between standard vs. nested cubes DTI acquisitions. Correlation of white matter fractional anisotropy was also strong (ICC > 0.95) and significant. ICCs of the CoV of dynamic ADC measured using repeated cubes and nested cubes acquisitions were modest (ICC >0.60), but significant in gray matter. CONCLUSION: A nested cubes diffusion gradient table produces tensor-based and dynamic diffusion measurements in a single acquisition. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 1.

Comparison of Deformation Patterns Excited in the Human Brain In Vivo by Harmonic and Impulsive Skull Motion.

Noninvasive measurements of brain deformation in human participants in vivo are needed to develop models of brain biomechanics and understand traumatic brain injury (TBI). Tagged magnetic resonance imaging (tagged MRI) and magnetic resonance elastography (MRE) are two techniques to study human brain deformation; these techniques differ in the type of motion and difficulty of implementation. In this study, oscillatory strain fields in the human brain caused by impulsive head acceleration and measured by tagged MRI were compared quantitatively to strain fields measured by MRE during harmonic head motion at 10 and 50 Hz. Strain fields were compared by registering to a common anatomical template, then computing correlations between the registered strain fields. Correlations were computed between tagged MRI strain fields in six participants and MRE strain fields at 10 Hz and 50 Hz in six different participants. Correlations among strain fields within the same experiment type were compared statistically to correlations from different experiment types. Strain fields from harmonic head motion at 10 Hz imaged by MRE were qualitatively and quantitatively similar to modes excited by impulsive head motion, imaged by tagged MRI. Notably, correlations between strain fields from 10 Hz MRE and tagged MRI did not differ significantly from correlations between strain fields from tagged MRI. These results suggest that low-frequency modes of oscillation dominate the response of the brain during impact. Thus, low-frequency MRE, which is simpler and more widely available than tagged MRI, can be used to illuminate the brain's response to head impact.

Segmented 3D Echo Planar Acquisition for Rapid Susceptibility-Weighted Imaging: Application to Microhemorrhage Detection in Traumatic Brain Injury.

BACKGROUND: Susceptibility-weighted imaging (SWI) provides superior image contrast of cerebral microhemorrhages (CMBs). It is based on a three-dimensional (3D) gradient echo (GRE) sequence with a relatively long imaging time. PURPOSE: To evaluate whether an accelerated 3D segmented echo planar imaging SWI is comparable to GRE SWI in detecting CMBs in traumatic brain injury (TBI). STUDY TYPE: Prospective. SUBJECTS: Four healthy volunteers and 46 consecutive subjects (38.0 ± 14.4 years, 16 females; 12 mild, 13 moderate, and 7 severe TBI). FIELD STRENGTH/SEQUENCE: A 3 T scanner/3D gradient echo and 3D segmented echo planar imaging (segEPI). ASSESSMENT: Brain images were acquired using GRE and segEPI in a single session (imaging time = 9 minutes 47 seconds and 1 minute 30 seconds, respectively). The signal-to-noise ratio (SNR) calculated from healthy volunteer thalamus and centrum semiovale were compared. CMBs were counted by three raters blinded to diagnostic information. STATISTICAL TESTS: A t-test was used to assess SNR difference. Pearson correlation and Wilcoxon signed-rank test were performed using CMB counts. The intermethod agreement was evaluated using Bland-Altman method. Intermethod and interrater reliabilities of image-based diffuse axonal injury (DAI) diagnoses were evaluated using Cohen's kappa and percent agreement. P ≤ 0.05 was considered statistically significant. RESULTS: Thalamus SNRs were 16.9 ± 2.2 and 16.5 ± 3 for GRE and segEPI (P = 0.84), respectively. Centrum semiovale SNRs were 25.8 ± 4.6 and 21.1 ± 2.7 (P = 0.13). The correlation coefficient of CMBs was 0.93, and differences were not significant (P = 0.56-0.85). For DAI diagnoses, Cohen's kappa was 0.62-0.84 and percent agreement was 85%-94%. DATA CONCLUSION: CMB counts on segEPI and GRE were highly correlated, and DAI diagnosis was made equally effectively. segEPI SWI can potentially replace GRE SWI in detecting TBI CMBs, especially when time constraints are critical. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.

Brain and blood biomarkers of tauopathy and neuronal injury in humans and rats with neurobehavioral syndromes following blast exposure.

Traumatic brain injury (TBI) is a risk factor for the later development of neurodegenerative diseases that may have various underlying pathologies. Chronic traumatic encephalopathy (CTE) in particular is associated with repetitive mild TBI (mTBI) and is characterized pathologically by aggregation of hyperphosphorylated tau into neurofibrillary tangles (NFTs). CTE may be suspected when behavior, cognition, and/or memory deteriorate following repetitive mTBI. Exposure to blast overpressure from improvised explosive devices (IEDs) has been implicated as a potential antecedent for CTE amongst Iraq and Afghanistan Warfighters. In this study, we identified biomarker signatures in rats exposed to repetitive low-level blast that develop chronic anxiety-related traits and in human veterans exposed to IED blasts in theater with behavioral, cognitive, and/or memory complaints. Rats exposed to repetitive low-level blasts accumulated abnormal hyperphosphorylated tau in neuronal perikarya and perivascular astroglial processes. Using positron emission tomography (PET) and the [18F]AV1451 (flortaucipir) tau ligand, we found that five of 10 veterans exhibited excessive retention of [18F]AV1451 at the white/gray matter junction in frontal, parietal, and temporal brain regions, a typical localization of CTE tauopathy. We also observed elevated levels of neurofilament light (NfL) chain protein in the plasma of veterans displaying excess [18F]AV1451 retention. These findings suggest an association linking blast injury, tauopathy, and neuronal injury. Further study is required to determine whether clinical, neuroimaging, and/or fluid biomarker signatures can improve the diagnosis of long-term neuropsychiatric sequelae of mTBI.

Lesion size and shape in central vein sign assessment for multiple sclerosis diagnosis: An in vivo and postmortem MRI study.

BACKGROUND: The "central vein sign" (CVS), a linear hypointensity on T2*-weighted imaging corresponding to a central vein/venule, is associated with multiple sclerosis (MS) lesions. The effect of lesion-size exclusion criteria on MS diagnostic accuracy has not been extensively studied. OBJECTIVE: Investigate the optimal lesion-size exclusion criteria for CVS use in MS diagnosis. METHODS: Cross-sectional study of 163 MS and 51 non-MS, and radiological/histopathological correlation of 5 MS and 1 control autopsy cases. The effects of lesion-size exclusion on MS diagnosis using the CVS, and intralesional vein detection on histopathology were evaluated. RESULTS: CVS+ lesions were larger compared to CVS- lesions, with effect modification by MS diagnosis (mean difference +7.7 mm3, p = 0.004). CVS percentage-based criteria with no lesion-size exclusion showed the highest diagnostic accuracy in differentiating MS cases. However, a simple count of three or more CVS+ lesions greater than 3.5 mm is highly accurate and can be rapidly implemented (sensitivity 93%; specificity 88%). On magnetic resonance imaging (MRI)-histopathological correlation, the CVS had high specificity for identifying intralesional veins (0/7 false positives). CONCLUSION: Lesion-size measures add important information when using CVS+ lesion counts for MS diagnosis. The CVS is a specific biomarker corresponding to intralesional veins on histopathology.

ErbB Signaling Pathway Genes Are Differentially Expressed in Monozygotic Twins Discordant for Sports-Related Concussion.

Transcriptional changes involved in neuronal recovery after sports-related concussion (SRC) may be obscured by inter-individual variation in mRNA expression and nonspecific changes related to physical exertion. Using a co-twin study, the objective of this study was to identify important differences in mRNA expression among a single pair of monozygotic (MZ) twins discordant for concussion. A pair of MZ twins were enrolled as part of a larger study of concussion biomarkers among collegiate athletes. During the study, Twin A sustained SRC, allowing comparison of mRNA expression to the nonconcussed Twin B. Twin A clinically recovered by Day 7. mRNA expression was measured pre-injury and at 6 h and 7 days postinjury using Affymetrix HG-U133 Plus 2.0 microarray. Changes in mRNA expression from pre-injury to each postinjury time point were compared between the twins; differences >1.5-fold were considered important. Kyoto Encyclopedia of Genes and Genomes identified biologic networks associated with important transcripts. Among 38,000 analyzed genes, important changes were identified in 153 genes. The ErbB (epidermal growth factor receptor) signaling pathway was identified as the top transcriptional network from pre-injury to 7 days postinjury. Genes in this pathway with important transcriptional changes included epidermal growth factor (2.41), epiregulin (1.73), neuregulin 1 (1.54) and mechanistic target of rapamycin (1.51). In conclusion, the ErbB signaling pathway was identified as a potential regulator of clinical recovery in a MZ twin pair discordant for SRC. A co-twin study design may be a useful method for identifying important gene pathways associated with concussion recovery.

Effect of disease-modifying therapies on subcortical gray matter atrophy in multiple sclerosis.

BACKGROUND: The effects of disease-modifying therapies (DMTs) on region-specific brain atrophy in multiple sclerosis (MS) are unclear. OBJECTIVE: To determine the effects of higher versus lower efficacy DMTs on rates of brain substructure atrophy in MS. METHODS: A non-randomized, observational cohort of people with MS followed with annual brain magnetic resonance imaging (MRI) was evaluated retrospectively. Whole brain, subcortical gray matter (GM), cortical GM, and cerebral white matter (WM) volume fractions were obtained. DMTs were categorized as higher (DMT-H: natalizumab and rituximab) or lower (DMT-L: interferon-beta and glatiramer acetate) efficacy. Follow-up epochs were analyzed if participants had been on a DMT for ⩾6 months prior to baseline and had at least one follow-up MRI while on DMTs in the same category. RESULTS: A total of 86 DMT epochs (DMT-H: n = 32; DMT-L: n = 54) from 78 participants fulfilled the study inclusion criteria. Mean follow-up was 2.4 years. Annualized rates of thalamic (-0.15% vs -0.81%; p = 0.001) and putaminal (-0.27% vs -0.73%; p = 0.001) atrophy were slower during DMT-H compared to DMT-L epochs. These results remained significant in multivariate analyses including demographics, clinical characteristics, and T2 lesion volume. CONCLUSION: DMT-H treatment may be associated with slower rates of subcortical GM atrophy, especially of the thalamus and putamen. Thalamic and putaminal volumes are promising imaging biomarkers in MS.

Brain and retinal atrophy in African-Americans versus Caucasian-Americans with multiple sclerosis: a longitudinal study.

On average, African Americans with multiple sclerosis demonstrate higher inflammatory disease activity, faster disability accumulation, greater visual dysfunction, more pronounced brain tissue damage and higher lesion volume loads compared to Caucasian Americans with multiple sclerosis. Neurodegeneration is an important component of multiple sclerosis, which in part accounts for the clinical heterogeneity of the disease. Brain atrophy appears to be widespread, although it is becoming increasingly recognized that regional substructure atrophy may be of greater clinical relevance. Patient race (within the limitations of self-identified ancestry) is regarded as an important contributing factor. However, there is a paucity of studies examining differences in neurodegeneration and brain substructure volumes over time in African Americans relative to Caucasian American patients. Optical coherence tomography is a non-invasive and reliable tool for measuring structural retinal changes. Recent studies support its utility for tracking neurodegeneration and disease progression in vivo in multiple sclerosis. Relative to Caucasian Americans, African American patients have been found to have greater retinal structural injury in the inner retinal layers. Increased thickness of the inner nuclear layer and the presence of microcystoid macular pathology at baseline predict clinical and radiological inflammatory activity, although whether race plays a role in these changes has not been investigated. Similarly, assessment of outer retinal changes according to race in multiple sclerosis remains incompletely characterized. Twenty-two African Americans and 60 matched Caucasian Americans with multiple sclerosis were evaluated with brain MRI, and 116 African Americans and 116 matched Caucasian Americans with multiple sclerosis were monitored with optical coherence tomography over a mean duration of 4.5 years. Mixed-effects linear regression models were used in statistical analyses. Grey matter (-0.9%/year versus -0.5%: P =0.02), white matter (-0.7%/year versus -0.3%: P =0.04) and nuclear thalamic (-1.5%/year versus -0.7%/year: P =0.02) atrophy rates were approximately twice as fast in African Americans. African Americans also exhibited higher proportions of microcystoid macular pathology (12.1% versus 0.9%, P =0.001). Retinal nerve fibre layer (-1.1% versus -0.8%: P =0.02) and ganglion cell+ inner plexiform layer (-0.7%/year versus -0.4%/year: P =0.01) atrophy rates were faster in African versus Caucasian Americans. African Americans on average exhibited more rapid neurodegeneration than Caucasian Americans and had significantly faster brain and retinal tissue loss. These results corroborate the more rapid clinical progression reported to occur, in general, in African Americans with multiple sclerosis and support the need for future studies involving African Americans in order to identify individual differences in treatment responses in multiple sclerosis.

Gradient nonlinearity effects on upper cervical spinal cord area measurement from 3D T1 -weighted brain MRI acquisitions.

PURPOSE: To explore (i) the variability of upper cervical cord area (UCCA) measurements from volumetric brain 3D T1 -weighted scans related to gradient nonlinearity (GNL) and subject positioning; (ii) the effect of vendor-implemented GNL corrections; and (iii) easily applicable methods that can be used to retrospectively correct data. METHODS: A multiple sclerosis patient was scanned at seven sites using 3T MRI scanners with the same 3D T1 -weighted protocol without GNL-distortion correction. Two healthy subjects and a phantom were additionally scanned at a single site with varying table positions. The 2D and 3D vendor-implemented GNL-correction algorithms and retrospective methods based on (i) phantom data fit, (ii) normalization with C2 vertebral body diameters, and (iii) the Jacobian determinant of nonlinear registrations to a template were tested. RESULTS: Depending on the positioning of the subject, GNL introduced up to 15% variability in UCCA measurements from volumetric brain T1 -weighted scans when no distortion corrections were used. The 3D vendor-implemented correction methods and the three proposed methods reduced this variability to less than 3%. CONCLUSIONS: Our results raise awareness of the significant impact that GNL can have on quantitative UCCA studies, and point the way to prospectively and retrospectively managing GNL distortions in a variety of settings, including clinical environments. Magn Reson Med 79:1595-1601, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Balance in multiple sclerosis: relationship to central brain regions.

Dizziness, postural instability, and ataxia are among the most debilitating symptoms of multiple sclerosis (MS), reflecting, in large part, dysfunctional integration of visual, somatosensory, and vestibular sensory cues. However, the role of MS-related supratentorial lesions in producing such symptoms is poorly understood. In this study, motor control test (MCT) and dynamic sensory organization test (SOT) scores of 58 MS patients were compared to those of 72 healthy controls; correlations were determined between the MS scores of 49 patients and lesion volumes within 26 brain regions. Depending upon platform excursion direction and magnitude, MCT latencies, which were longer in MS patients than controls (p < 0.0001), were correlated with lesion volumes in the cortex, medial frontal lobes, temporal lobes, and parietal opercula (r's ranging from 0.20 to 0.39). SOT test scores were also impacted by MS and correlated with lesions in these same brain regions as well as within the superior frontal lobe (r's ranging from - 0.28 to - 0.40). The strongest and most consistent correlations occurred for the most challenging tasks in which incongruent visual and proprioceptive feedback were given. This study demonstrates that supratentorial lesion volumes are associated with quantitative balance measures in MS, in accord with the concept that balance relies upon highly convergent and multimodal neural pathways involving the skin, muscles, joints, eyes, and vestibular system.

Statistical Characterization of Human Brain Deformation During Mild Angular Acceleration Measured In Vivo by Tagged Magnetic Resonance Imaging.

Understanding of in vivo brain biomechanical behavior is critical in the study of traumatic brain injury (TBI) mechanisms and prevention. Using tagged magnetic resonance imaging, we measured spatiotemporal brain deformations in 34 healthy human volunteers under mild angular accelerations of the head. Two-dimensional (2D) Lagrangian strains were examined throughout the brain in each subject. Strain metrics peaked shortly after contact with a padded stop, corresponding to the inertial response of the brain after head deceleration. Maximum shear strain of at least 3% was experienced at peak deformation by an area fraction (median±standard error) of 23.5±1.8% of cortical gray matter, 15.9±1.4% of white matter, and 4.0±1.5% of deep gray matter. Cortical gray matter strains were greater in the temporal cortex on the side of the initial contact with the padded stop and also in the contralateral temporal, frontal, and parietal cortex. These tissue-level deformations from a population of healthy volunteers provide the first in vivo measurements of full-volume brain deformation in response to known kinematics. Although strains differed in different tissue type and cortical lobes, no significant differences between male and female head accelerations or strain metrics were found. These cumulative results highlight important kinematic features of the brain's mechanical response and can be used to facilitate the evaluation of computational simulations of TBI.

Robust skull stripping using multiple MR image contrasts insensitive to pathology.

Automatic skull-stripping or brain extraction of magnetic resonance (MR) images is often a fundamental step in many neuroimage processing pipelines. The accuracy of subsequent image processing relies on the accuracy of the skull-stripping. Although many automated stripping methods have been proposed in the past, it is still an active area of research particularly in the context of brain pathology. Most stripping methods are validated on T1-w MR images of normal brains, especially because high resolution T1-w sequences are widely acquired and ground truth manual brain mask segmentations are publicly available for normal brains. However, different MR acquisition protocols can provide complementary information about the brain tissues, which can be exploited for better distinction between brain, cerebrospinal fluid, and unwanted tissues such as skull, dura, marrow, or fat. This is especially true in the presence of pathology, where hemorrhages or other types of lesions can have similar intensities as skull in a T1-w image. In this paper, we propose a sparse patch based Multi-cONtrast brain STRipping method (MONSTR),2 where non-local patch information from one or more atlases, which contain multiple MR sequences and reference delineations of brain masks, are combined to generate a target brain mask. We compared MONSTR with four state-of-the-art, publicly available methods: BEaST, SPECTRE, ROBEX, and OptiBET. We evaluated the performance of these methods on 6 datasets consisting of both healthy subjects and patients with various pathologies. Three datasets (ADNI, MRBrainS, NAMIC) are publicly available, consisting of 44 healthy volunteers and 10 patients with schizophrenia. Other three in-house datasets, comprising 87 subjects in total, consisted of patients with mild to severe traumatic brain injury, brain tumors, and various movement disorders. A combination of T1-w, T2-w were used to skull-strip these datasets. We show significant improvement in stripping over the competing methods on both healthy and pathological brains. We also show that our multi-contrast framework is robust and maintains accurate performance across different types of acquisitions and scanners, even when using normal brains as atlases to strip pathological brains, demonstrating that our algorithm is applicable even when reference segmentations of pathological brains are not available to be used as atlases.

Longitudinal multiple sclerosis lesion segmentation: Resource and challenge.

In conjunction with the ISBI 2015 conference, we organized a longitudinal lesion segmentation challenge providing training and test data to registered participants. The training data consisted of five subjects with a mean of 4.4 time-points, and test data of fourteen subjects with a mean of 4.4 time-points. All 82 data sets had the white matter lesions associated with multiple sclerosis delineated by two human expert raters. Eleven teams submitted results using state-of-the-art lesion segmentation algorithms to the challenge, with ten teams presenting their results at the conference. We present a quantitative evaluation comparing the consistency of the two raters as well as exploring the performance of the eleven submitted results in addition to three other lesion segmentation algorithms. The challenge presented three unique opportunities: (1) the sharing of a rich data set; (2) collaboration and comparison of the various avenues of research being pursued in the community; and (3) a review and refinement of the evaluation metrics currently in use. We report on the performance of the challenge participants, as well as the construction and evaluation of a consensus delineation. The image data and manual delineations will continue to be available for download, through an evaluation website2 as a resource for future researchers in the area. This data resource provides a platform to compare existing methods in a fair and consistent manner to each other and multiple manual raters.

Consistent cortical reconstruction and multi-atlas brain segmentation.

Whole brain segmentation and cortical surface reconstruction are two essential techniques for investigating the human brain. Spatial inconsistences, which can hinder further integrated analyses of brain structure, can result due to these two tasks typically being conducted independently of each other. FreeSurfer obtains self-consistent whole brain segmentations and cortical surfaces. It starts with subcortical segmentation, then carries out cortical surface reconstruction, and ends with cortical segmentation and labeling. However, this "segmentation to surface to parcellation" strategy has shown limitations in various cohorts such as older populations with large ventricles. In this work, we propose a novel "multi-atlas segmentation to surface" method called Multi-atlas CRUISE (MaCRUISE), which achieves self-consistent whole brain segmentations and cortical surfaces by combining multi-atlas segmentation with the cortical reconstruction method CRUISE. A modification called MaCRUISE(+) is designed to perform well when white matter lesions are present. Comparing to the benchmarks CRUISE and FreeSurfer, the surface accuracy of MaCRUISE and MaCRUISE(+) is validated using two independent datasets with expertly placed cortical landmarks. A third independent dataset with expertly delineated volumetric labels is employed to compare segmentation performance. Finally, 200MR volumetric images from an older adult sample are used to assess the robustness of MaCRUISE and FreeSurfer. The advantages of MaCRUISE are: (1) MaCRUISE constructs self-consistent voxelwise segmentations and cortical surfaces, while MaCRUISE(+) is robust to white matter pathology. (2) MaCRUISE achieves more accurate whole brain segmentations than independently conducting the multi-atlas segmentation. (3) MaCRUISE is comparable in accuracy to FreeSurfer (when FreeSurfer does not exhibit global failures) while achieving greater robustness across an older adult population. MaCRUISE has been made freely available in open source.

Optical coherence tomography reflects brain atrophy in multiple sclerosis: A four-year study.

OBJECTIVE: The aim of this work was to determine whether atrophy of specific retinal layers and brain substructures are associated over time, in order to further validate the utility of optical coherence tomography (OCT) as an indicator of neuronal tissue damage in patients with multiple sclerosis (MS). METHODS: Cirrus high-definition OCT (including automated macular segmentation) was performed in 107 MS patients biannually (median follow-up: 46 months). Three-Tesla magnetic resonance imaging brain scans (including brain-substructure volumetrics) were performed annually. Individual-specific rates of change in retinal and brain measures (estimated with linear regression) were correlated, adjusting for age, sex, disease duration, and optic neuritis (ON) history. RESULTS: Rates of ganglion cell + inner plexiform layer (GCIP) and whole-brain (r = 0.45; p < 0.001), gray matter (GM; r = 0.37; p < 0.001), white matter (WM; r = 0.28; p = 0.007), and thalamic (r = 0.38; p < 0.001) atrophy were associated. GCIP and whole-brain (as well as GM and WM) atrophy rates were more strongly associated in progressive MS (r = 0.67; p < 0.001) than relapsing-remitting MS (RRMS; r = 0.33; p = 0.007). However, correlation between rates of GCIP and whole-brain (and additionally GM and WM) atrophy in RRMS increased incrementally with step-wise refinement to exclude ON effects; excluding eyes and then patients (to account for a phenotype effect), the correlation increased to 0.45 and 0.60, respectively, consistent with effect modification. In RRMS, lesion accumulation rate was associated with GCIP (r = -0.30; p = 0.02) and inner nuclear layer (r = -0.25; p = 0.04) atrophy rates. INTERPRETATION: Over time GCIP atrophy appears to mirror whole-brain, and particularly GM, atrophy, especially in progressive MS, thereby reflecting underlying disease progression. Our findings support OCT for clinical monitoring and as an outcome in investigative trials.

Artifactual microhemorrhage generated by susceptibility weighted image processing.

BACKGROUND: To report that artifactual microhemorrhages are introduced by the two-dimensional (2D) homodyne filtering method of generating susceptibility weighted images (SWI) when open-ended fringelines (OEF) are present in phase data. METHODS: SWI data from 28 traumatic brain injury (TBI) patients was obtained on a 3 tesla clinical Siemens scanner using both the product 3D gradient echo sequence (GRE) with generalized autocalibrating partially parallel acquisition acceleration and an in-house developed segmented echo planar imaging (sEPI) sequence without GRAPPA acceleration. SWI processing included (i) 2D homodyne method implemented on the scanner console and (ii) a 3D Fourier-based phase unwrapping followed by 3D high pass filtering. Original and enhanced magnitude and phase images were carefully reviewed for sites of type III OEFs and microhemorrhages by a neuroradiologist on a PACS workstation. RESULTS: Nineteen of 28 (68%) phase datasets acquired using GRAPPA-accelerated GRE acquisition demonstrated type III OEFs. In SWI images, artifactual microhemorrhages were found on 17 of 19 (89%) cases generated using 2D homodyne processing. Application of a 3D Fourier-based unwrapping method prior HP filtering minimized the appearance of the phase singularities in the enhanced phase, and did not generate microhemorrhage-like artifacts in magnitude images. CONCLUSION: The 2D homodyne filtering method may introduce artifacts mimicking intracranial microhemorrhages in SWI images when type III OEFs are present in phase images. Such artifacts could lead to overestimation of pathology, e.g., TBI. This work demonstrates that 3D phase unwrapping methods minimize this artifact. However, methods to properly combine phase across coils are needed to eliminate this artifact.

Thalamic lesions in multiple sclerosis by 7T MRI: Clinical implications and relationship to cortical pathology.

OBJECTIVE: Pathology in both cortex and deep gray matter contribute to disability in multiple sclerosis (MS). We used the increased signal-to-noise ratio of 7-tesla (7T) MRI to visualize small lesions within the thalamus and to relate this to clinical information and cortical lesions. METHODS: We obtained 7T MRI scans on 34 MS cases and 15 healthy volunteers. Thalamic lesion number and volume were related to demographic data, clinical disability measures, and lesions in cortical gray matter. RESULTS: Thalamic lesions were found in 24/34 of MS cases. Two lesion subtypes were noted: discrete, ovoid lesions, and more diffuse lesional areas lining the periventricular surface. The number of thalamic lesions was greater in progressive MS compared to relapsing-remitting (mean ±SD, 10.7 ±0.7 vs. 3.0 ±0.7, respectively, p < 0.001). Thalamic lesion burden (count and volume) correlated with EDSS score and measures of cortical lesion burden, but not with white matter lesion burden or white matter volume. CONCLUSIONS: Using 7T MRI allows identification of thalamic lesions in MS, which are associated with disability, progressive disease, and cortical lesions. Thalamic lesion analysis may be a simpler, more rapid estimate of overall gray matter lesion burden in MS.

Evaluating Model Misspecification in Independent Component Analysis.

Independent component analysis (ICA) is a popular blind source separation technique used in many scientific disciplines. Current ICA approaches have focused on developing efficient algorithms under specific ICA models, such as instantaneous or convolutive mixing conditions, intrinsically assuming temporal independence or autocorrelation of the sources. In practice, the true model is not known and different ICA algorithms can produce very different results. Although it is critical to choose an ICA model, there has not been enough research done on evaluating mixing models and assumptions, and how the associated algorithms may perform under different scenarios. In this paper, we investigate the performance of multiple ICA algorithms under various mixing conditions. We also propose a convolutive ICA algorithm for echoic mixing cases. Our simulation studies show that the performance of ICA algorithms is highly dependent on mixing conditions and temporal independence of the sources. Most instantaneous ICA algorithms fail to separate autocorrelated sources, while convolutive ICA algorithms depend highly on the model specification and approximation accuracy of unmixing filters.