Artificial Intelligence Screening of Medical School Applications: Development and Validation of a Machine-Learning Algorithm.

PURPOSE: To explore whether a machine-learning algorithm could accurately perform the initial screening of medical school applications. METHOD: Using application data and faculty screening outcomes from the 2013 to 2017 application cycles (n = 14,555 applications), the authors created a virtual faculty screener algorithm. A retrospective validation using 2,910 applications from the 2013 to 2017 cycles and a prospective validation using 2,715 applications during the 2018 application cycle were performed. To test the validated algorithm, a randomized trial was performed in the 2019 cycle, with 1,827 eligible applications being reviewed by faculty and 1,873 by algorithm. RESULTS: The retrospective validation yielded area under the receiver operating characteristic (AUROC) values of 0.83, 0.64, and 0.83 and area under the precision-recall curve (AUPRC) values of 0.61, 0.54, and 0.65 for the invite for interview, hold for review, and reject groups, respectively. The prospective validation yielded AUROC values of 0.83, 0.62, and 0.82 and AUPRC values of 0.66, 0.47, and 0.65 for the invite for interview, hold for review, and reject groups, respectively. The randomized trial found no significant differences in overall interview recommendation rates according to faculty or algorithm and among female or underrepresented in medicine applicants. In underrepresented in medicine applicants, there were no significant differences in the rates at which the admissions committee offered an interview (70 of 71 in the faculty reviewer arm and 61 of 65 in the algorithm arm; P = .14). No difference in the rate of the committee agreeing with the recommended interview was found among female applicants (224 of 229 in the faculty reviewer arm and 220 of 227 in the algorithm arm; P = .55). CONCLUSIONS: The virtual faculty screener algorithm successfully replicated faculty screening of medical school applications and may aid in the consistent and reliable review of medical school applicants.

Signatures of medical student applicants and academic success.

The acceptance of students to a medical school places a considerable emphasis on performance in standardized tests and undergraduate grade point average (uGPA). Traditionally, applicants may be judged as a homogeneous population according to simple quantitative thresholds that implicitly assume a linear relationship between scores and academic success. This 'one-size-fits-all' approach ignores the notion that individuals may show distinct patterns of achievement and follow diverse paths to success. In this study, we examined a dataset composed of 53 variables extracted from the admissions application records of 1,088 students matriculating to NYU School of Medicine between the years 2006-2014. We defined training and test groups and applied K-means clustering to search for distinct groups of applicants. Building an optimized logistic regression model, we then tested the predictive value of this clustering for estimating the success of applicants in medical school, aggregating eight performance measures during the subsequent medical school training as a success factor. We found evidence for four distinct clusters of students-we termed 'signatures'-which differ most substantially according to the absolute level of the applicant's uGPA and its trajectory over the course of undergraduate education. The 'risers' signature showed a relatively higher uGPA and also steeper trajectory; the other signatures showed each remaining combination of these two main factors: 'improvers' relatively lower uGPA, steeper trajectory; 'solids' higher uGPA, flatter trajectory; 'statics' both lower uGPA and flatter trajectory. Examining the success index across signatures, we found that the risers and the statics have significantly higher and lower likelihood of quantifiable success in medical school, respectively. We also found that each signature has a unique set of features that correlate with its success in medical school. The big data approach presented here can more sensitively uncover success potential since it takes into account the inherent heterogeneity within the student population.

MR Imaging Applications in Mild Traumatic Brain Injury: An Imaging Update.

Mild traumatic brain injury (mTBI), also commonly referred to as concussion, affects millions of Americans annually. Although computed tomography is the first-line imaging technique for all traumatic brain injury, it is incapable of providing long-term prognostic information in mTBI. In the past decade, the amount of research related to magnetic resonance (MR) imaging of mTBI has grown exponentially, partly due to development of novel analytical methods, which are applied to a variety of MR techniques. Here, evidence of subtle brain changes in mTBI as revealed by these techniques, which are not demonstrable by conventional imaging, will be reviewed. These changes can be considered in three main categories of brain structure, function, and metabolism. Macrostructural and microstructural changes have been revealed with three-dimensional MR imaging, susceptibility-weighted imaging, diffusion-weighted imaging, and higher order diffusion imaging. Functional abnormalities have been described with both task-mediated and resting-state blood oxygen level-dependent functional MR imaging. Metabolic changes suggesting neuronal injury have been demonstrated with MR spectroscopy. These findings improve understanding of the true impact of mTBI and its pathogenesis. Further investigation may eventually lead to improved diagnosis, prognosis, and management of this common and costly condition. (©) RSNA, 2016.

Quantification of normal-appearing white matter tract integrity in multiple sclerosis: a diffusion kurtosis imaging study.

Our aim was to characterize the nature and extent of pathological changes in the normal-appearing white matter (NAWM) of patients with multiple sclerosis (MS) using novel diffusion kurtosis imaging-derived white matter tract integrity (WMTI) metrics and to investigate the association between these WMTI metrics and clinical parameters. Thirty-two patients with relapsing-remitting MS and 19 age- and gender-matched healthy controls underwent MRI and neurological examination. Maps of mean diffusivity, fractional anisotropy and WMTI metrics (intra-axonal diffusivity, axonal water fraction, tortuosity and axial and radial extra-axonal diffusivity) were created. Tract-based spatial statistics analysis was performed to assess for differences in the NAWM between patients and controls. A region of interest analysis of the corpus callosum was also performed to assess for group differences and to evaluate correlations between WMTI metrics and measures of disease severity. Mean diffusivity and radial extra-axonal diffusivity were significantly increased while fractional anisotropy, axonal water fraction, intra-axonal diffusivity and tortuosity were decreased in MS patients compared with controls (p values ranging from <0.001 to <0.05). Axonal water fraction in the corpus callosum was significantly associated with the expanded disability status scale score (ρ = -0.39, p = 0.035). With the exception of the axial extra-axonal diffusivity, all metrics were correlated with the symbol digits modality test score (p values ranging from 0.001 to <0.05). WMTI metrics are thus sensitive to changes in the NAWM of MS patients and might provide a more pathologically specific, clinically meaningful and practical complement to standard diffusion tensor imaging-derived metrics.

Gray Matter Correlates of Cognitive Performance Differ between Relapsing-Remitting and Primary-Progressive Multiple Sclerosis.

Multiple Sclerosis (MS) is a chronic inflammatory/demyelinating and neurodegenerative disease of the central nervous system (CNS). Most patients experience a relapsing-remitting (RR) course, while about 15-20% of patients experience a primary progressive (PP) course. Cognitive impairment affects approximately 40-70% of all MS patients and differences in cognitive impairment between RR-MS and PP-MS have been found. We aimed to compare RR-MS and PP-MS patients in terms of cognitive performance, and to investigate the MRI correlates of cognitive impairment in the two groups using measures of brain volumes and cortical thickness. Fifty-seven patients (42 RR-MS, 15 PP-MS) and thirty-eight matched controls underwent neuropsychological (NP) testing and MRI. PP-MS patients scored lower than RR-MS patients on most of the NP tests in absence of any specific pattern. PP-MS patients showed significantly lower caudate volume. There was no significant difference in MRI correlates of cognitive impairment between the two groups except for a prevalent association with MRI measures of cortical GM injury in RR-MS patients and with MRI measures of subcortical GM injury in PP-MS patients. This suggests that although cognitive impairment results from several factors, cortical and subcortical GM injury may play a different role depending on the disease course.

N-acetyl-aspartate levels correlate with intra-axonal compartment parameters from diffusion MRI.

Diffusion MRI combined with biophysical modeling allows for the description of a white matter (WM) fiber bundle in terms of compartment specific white matter tract integrity (WMTI) metrics, which include intra-axonal diffusivity (Daxon), extra-axonal axial diffusivity (De||), extra-axonal radial diffusivity (De┴), axonal water fraction (AWF), and tortuosity (α) of extra-axonal space. Here we derive these parameters from diffusion kurtosis imaging to examine their relationship to concentrations of global WM N-acetyl-aspartate (NAA), creatine (Cr), choline (Cho) and myo-Inositol (mI), as measured with proton MR spectroscopy ((1)H-MRS), in a cohort of 25 patients with mild traumatic brain injury (MTBI). We found statistically significant (p<0.05) positive correlations between NAA and Daxon, AWF, α, and fractional anisotropy; negative correlations between NAA and De,┴ and the overall radial diffusivity (D┴). These correlations were supported by similar findings in regional analysis of the genu and splenium of the corpus callosum. Furthermore, a positive correlation in global WM was noted between Daxon and Cr, as well as a positive correlation between De|| and Cho, and a positive trend between De|| and mI. The specific correlations between NAA, an endogenous probe of the neuronal intracellular space, and WMTI metrics related to the intra-axonal space, combined with the specific correlations of De|| with mI and Cho, both predominantly present extra-axonally, corroborate the overarching assumption of many advanced modeling approaches that diffusion imaging can disentangle between the intra- and extra-axonal compartments in WM fiber bundles. Our findings are also generally consistent with what is known about the pathophysiology of MTBI, which appears to involve both intra-axonal injury (as reflected by a positive trend between NAA and Daxon) as well as axonal shrinkage, demyelination, degeneration, and/or loss (as reflected by correlations between NAA and De┴, AWF, and α).

Relationship between iron accumulation and white matter injury in multiple sclerosis: a case-control study.

Despite the increasing development and applications of iron imaging, the pathophysiology of iron accumulation in multiple sclerosis (MS), and its role in disease progression and development of clinical disability, is poorly understood. The aims of our study were to determine the presence and extent of iron in T2 visible lesions and gray and white matter using magnetic field correlation (MFC) MRI and correlate with microscopic white matter (WM) injury as measured by diffusion tensor imaging (DTI). This is a case-control study including a series of 31 patients with clinically definite MS. The mean age was 39 years [standard deviation (SD) = 9.55], they were 11 males and 20 females, with a disease duration average of 3 years (range 0-13) and a median EDSS of 2 (0-4.5). Seventeen healthy volunteers (6 males and 11 females) with a mean age of 36 years (SD = 11.4) were recruited. All subjects underwent MR imaging on a 3T scanner using T2-weighted sequence, 3D T1 MPRAGE, MFC, single-shot DTI and post-contrast T1. T2-lesion volumes, brain volumetry, DTI parameters and iron quantification were calculated and multiple correlations were exploited. Increased MFC was found in the putamen (p = 0.061), the thalamus (p = 0.123), the centrum semiovale (p = 0.053), globus pallidus (p = 0.008) and gray matter (GM) (p = 0.004) of MS patients compared to controls. The mean lesional MFC was 121 s(-2) (SD = 67), significantly lower compared to the GM MFC (<0.0001). The GM mean diffusivity (MD) was inversely correlated with the MFC in the centrum semiovale (p < 0.001), and in the splenium of the corpus callosum (p < 0.001). Patients with MS have increased iron in the globus pallidus, putamen and centrum with a trend toward increased iron in all the brain structures. Quantitative iron evaluation of WM and GM may improve the understanding of MS pathophysiology, and might serve as a surrogate marker of disease progression.

Impaired cerebrovascular reactivity in multiple sclerosis.

IMPORTANCE: Cerebrovascular reactivity (CVR) is an inherent indicator of the dilatory capacity of cerebral arterioles for a vasomotor stimulus for maintaining a spontaneous and instant increase of cerebral blood flow (CBF) in response to neural activation. The integrity of this mechanism is essential to preserving healthy neurovascular coupling; however, to our knowledge, no studies have investigated whether there are CVR abnormalities in multiple sclerosis (MS). OBJECTIVE: To use hypercapnic perfusion magnetic resonance imaging to assess CVR impairment in patients with MS. DESIGN, SETTING, AND PARTICIPANTS: A total of 19 healthy volunteers and 19 patients with MS underwent perfusion magnetic resonance imaging based on pseudocontinuous arterial spin labeling to measure CBF at normocapnia (ie, breathing room air) and hypercapnia. The hypercapnia condition is achieved by breathing 5% carbon dioxide gas mixture, which is a potent vasodilator causing an increase of CBF. MAIN OUTCOMES AND MEASURES: Cerebrovascular reactivity was calculated as the percent increase of normocapnic to hypercapnic CBF normalized by the change in end-tidal carbon dioxide, which was recorded during both conditions. Group analysis was performed for regional and global CVR comparison between patients and controls. Regression analysis was also performed between CVR values, lesion load, and brain atrophy measures in patients with MS. RESULTS: A significant decrease of mean (SD) global gray matter CVR was found in patients with MS (3.56 [0.81]) compared with healthy controls (5.08 [1.56]; P = .001). Voxel-by-voxel analysis showed diffuse reduction of CVR in multiple regions of patients with MS. There was a significant negative correlation between gray matter CVR and lesion volume (R = 0.6, P = .004) and a significant positive correlation between global gray matter CVR and gray matter atrophy index (R = 0.5, P = .03). CONCLUSIONS AND RELEVANCE: Our quantitative imaging findings suggest impairment in functional cerebrovascular pathophysiology, by measuring a diffuse decrease in CVR, which may be the underlying cause of neurodegeneration in MS.

Classification algorithms using multiple MRI features in mild traumatic brain injury.

OBJECTIVE: The purpose of this study was to develop an algorithm incorporating MRI metrics to classify patients with mild traumatic brain injury (mTBI) and controls. METHODS: This was an institutional review board-approved, Health Insurance Portability and Accountability Act-compliant prospective study. We recruited patients with mTBI and healthy controls through the emergency department and general population. We acquired data on a 3.0T Siemens Trio magnet including conventional brain imaging, resting-state fMRI, diffusion-weighted imaging, and magnetic field correlation (MFC), and performed multifeature analysis using the following MRI metrics: mean kurtosis (MK) of thalamus, MFC of thalamus and frontal white matter, thalamocortical resting-state networks, and 5 regional gray matter and white matter volumes including the anterior cingulum and left frontal and temporal poles. Feature selection was performed using minimal-redundancy maximal-relevance. We used classifiers including support vector machine, naive Bayesian, Bayesian network, radial basis network, and multilayer perceptron to test maximal accuracy. RESULTS: We studied 24 patients with mTBI and 26 controls. Best single-feature classification uses thalamic MK yielding 74% accuracy. Multifeature analysis yields 80% accuracy using the full feature set, and up to 86% accuracy using minimal-redundancy maximal-relevance feature selection (MK thalamus, right anterior cingulate volume, thalamic thickness, thalamocortical resting-state network, thalamic microscopic MFC, and sex). CONCLUSION: Multifeature analysis using diffusion-weighted imaging, MFC, fMRI, and volumetrics may aid in the classification of patients with mTBI compared with controls based on optimal feature selection and classification methods. CLASSIFICATION OF EVIDENCE: This study provides Class III evidence that classification algorithms using multiple MRI features accurately identifies patients with mTBI as defined by American Congress of Rehabilitation Medicine criteria compared with healthy controls.

Myoinositol and glutamate complex neurometabolite abnormality after mild traumatic brain injury.

OBJECTIVE: To obtain quantitative neurometabolite measurements, specifically myoinositol (mI) and glutamate plus glutamine (Glx), markers of glial and neuronal excitation, in deep gray matter structures after mild traumatic brain injury (mTBI) using proton magnetic resonance spectroscopy ((1)H-MRS) and to compare these measurements against normal healthy control subjects. METHODS: This study approved by the institutional review board is Health Insurance Portability and Accountability Act compliant. T1-weighted MRI and multi-voxel (1)H-MRS imaging were acquired at 3 tesla from 26 patients with mTBI an average of 22 days postinjury and from 13 age-matched healthy controls. Two-way analysis of variance was used to compare patients and controls for mean N-acetylaspartate, choline, creatine (Cr), Glx, and mI levels as well as the respective ratios to Cr within the caudate, globus pallidus, putamen, and thalamus. RESULTS: Quantitative putaminal mI was higher in patients with mTBI compared with controls (p = 0.02). Quantitative neurometabolite ratios of putaminal mI and Glx relative to Cr, mI/Cr, and Glx/Cr were also higher among patients with mTBI compared with controls (p = 0.01 and 0.02, respectively). No other differences in neurometabolite levels or ratios were observed in any other brain region evaluated. CONCLUSION: Increased putaminal mI, mI/Cr, and Glx/Cr in patients after mTBI compared with control subjects supports the notion of a complex glial and excitatory response to injury without concomitant neuronal loss, evidenced by preserved N-acetylaspartate levels in this region.

Characterization of thalamo-cortical association using amplitude and connectivity of functional MRI in mild traumatic brain injury.

PURPOSE: To examine thalamic and cortical injuries using fractional amplitude of low-frequency fluctuations (fALFFs) and functional connectivity MRI (fcMRI) based on resting state (RS) and task-related fMRI in patients with mild traumatic brain injury (MTBI). MATERIALS AND METHODS: Twenty-seven patients and 27 age-matched controls were recruited. The 3 Tesla fMRI at RS and finger tapping task were used to assess fALFF and fcMRI patterns. fALFFs were computed with filtering (0.01-0.08 Hz) and scaling after preprocessing. fcMRI was performed using a standard seed-based correlation method, and delayed fcMRI (coherence) in frequency domain were also performed between thalamus and cortex. RESULTS: In comparison with controls, MTBI patients exhibited significantly decreased fALFFs in the thalamus (and frontal/temporal subsegments) and cortical frontal and temporal lobes; as well as decreased thalamo-thalamo and thalamo-frontal/ thalamo-temporal fcMRI at rest based on RS-fMRI (corrected P < 0.05). This thalamic and cortical disruption also existed at task-related condition in patients. CONCLUSION: The decreased fALFFs (i.e., lower neuronal activity) in the thalamus and its segments provide additional evidence of thalamic injury in patients with MTBI. Our findings of fALFFs and fcMRI changes during motor task and resting state may offer insights into the underlying cause and primary location of disrupted thalamo-cortical networks after MTBI.

Tract-specific white matter correlates of fatigue and cognitive impairment in benign multiple sclerosis.

BACKGROUND: Although benign multiple sclerosis (BMS) is traditionally defined by the presence of mild motor involvement decades after disease onset, symptoms of fatigue and cognitive impairment are very common. OBJECTIVE: To investigate the association between micro-structural damage in the anterior thalamic (AT) tracts and in the corpus callosum (CC), as measured by diffusion tensor imaging (DTI) tractography, and fatigue and cognitive deficits. METHODS: DTI data were acquired from 26 BMS patients and 24 sex- and age-matched healthy controls. RESULTS: General and mental fatigue scores were significantly impaired in patients compared with controls (p≤0.05 for both) and 38% of patients resulted cognitively impaired. Mean diffusivity (MD) of the AT and CC tracts was significantly higher and fractional anisotropy (FA) was lower in patients compared with controls (p<0.001 for all). Fatigue was associated with increased MD (p=0.01) of the AT tracts whereas deficit of executive functions and verbal learning were associated with decreased FA in the body (p=0.004) and genu (p=0.008) of the CC. Deficits in processing speed and attention were associated with the T2 lesion volume of the AT tracts (p<0.01 for all). DISCUSSION: These findings suggest that fatigue and cognitive impairment are quite frequent in BMS patients and are, at least in part, related to micro-structural damage and T2LV of WM tracts connecting the brain cortical and sub-cortical regions of the two hemispheres.

Mild traumatic brain injury: longitudinal regional brain volume changes.

PURPOSE: To investigate longitudinal changes in global and regional brain volume in patients 1 year after mild traumatic brain injury (MTBI) and to correlate such changes with clinical and neurocognitive metrics. MATERIALS AND METHODS: This institutional review board-approved study was HIPAA compliant. Twenty-eight patients with MTBI (with 19 followed up at 1 year) with posttraumatic symptoms after injury and 22 matched control subjects (with 12 followed up at 1 year) were enrolled. Automated segmentation of brain regions to compute regional gray matter (GM) and white matter (WM) volumes was performed by using three-dimensional T1-weighted 3.0-T magnetic resonance imaging, and results were correlated with clinical metrics. Pearson and Spearman rank correlation coefficients were computed between longitudinal brain volume and neurocognitive scores, as well as clinical metrics, over the course of the follow-up period. RESULTS: One year after MTBI, there was measurable global brain atrophy, larger than that in control subjects. The anterior cingulate WM bilaterally and the left cingulate gyrus isthmus WM, as well as the right precuneal GM, showed significant decreases in regional volume in patients with MTBI over the 1st year after injury (corrected P < .05); this was confirmed by means of cross-sectional comparison with data in control subjects (corrected P < .05). Left and right rostral anterior cingulum WM volume loss correlated with changes in neurocognitive measures of memory (r = 0.65, P = .005) and attention (r = 0.60, P = .01). At 1-year follow-up, WM volume in the left cingulate gyrus isthmus correlated with clinical scores of anxiety (Spearman rank correlation r = -0.68, P = .007) and postconcussive symptoms (Spearman rank correlation r = -0.65, P = .01). CONCLUSION: These observations demonstrate structural changes to the brain 1 year after injury after a single concussive episode. Regional brain atrophy is not exclusive to moderate and severe traumatic brain injury but may be seen after mild injury. In particular, the anterior part of the cingulum and the cingulate gyrus isthmus, as well as the precuneal GM, may be distinctively vulnerable 1 year after MTBI.

Proton MR spectroscopy correlates diffuse axonal abnormalities with post-concussive symptoms in mild traumatic brain injury.

There are no established biomarkers for mild traumatic brain injury (mTBI), in part because post-concussive symptoms (PCS) are subjective and conventional imaging is typically unremarkable. To test whether diffuse axonal abnormalities quantified with three-dimensional (3D) proton magnetic resonance spectroscopic imaging (¹H-MRSI) correlated with patients' PCS, we retrospectively studied 26 mTBI patients (mean Glasgow Coma Scale [GCS] score of 14.7), 18- to 56-year-olds and 13 controls three to 55 days post-injury. All were scanned at 3 Tesla with T1- and T2-weighted MRI and 3D ¹H-MRSI (480 voxels over 360 cm³, ∼30% of the brain). On scan day, patients completed a symptom questionnaire, and those who indicated at least one of the most common subacute mTBI symptoms (headache, dizziness, sleep disturbance, memory deficits, blurred vision) were grouped as PCS-positive. Global gray matter and white matter (GM/WM) absolute concentrations of N-acetylaspartate (NAA), choline (Cho), creatine (Cr) and myo-inositol (mI) in PCS-positive and PCS-negative patients were compared to age- and gender-matched controls using two-way analysis of variance. The results showed that the PCS-negative group (n=11) and controls (n=8) did not differ in any GM or WM metabolite level. The PCS-positive patients (n=15) had lower WM NAA than the controls (n=12; 7.0 ± 0.6 versus 7.9 ± 0.5mM; p=0.0007). Global WM NAA, therefore, showed sensitivity to the TBI sequelae associated with common PCS in patients with mostly normal neuroimaging, as well as GCS scores. This suggests a potential biomarker role in a patient population in which objective measures of injury and symptomatology are currently lacking.

Diffuse axonal injury in mild traumatic brain injury: a 3D multivoxel proton MR spectroscopy study.

Since mild traumatic brain injury (mTBI) often leads to neurological symptoms even without clinical MRI findings, our goal was to test whether diffuse axonal injury is quantifiable with multivoxel proton MR spectroscopic imaging ((1)H-MRSI). T1- and T2-weighted MRI images and three-dimensional (1)H-MRSI (480 voxels over 360 cm(3), about 30 % of the brain) were acquired at 3 T from 26 mTBI patients (mean Glasgow Coma Scale score 14.7, 18-56 years old, 3-55 days after injury) and 13 healthy matched contemporaries as controls. The N-acetylaspartate (NAA), choline (Cho), creatine (Cr) and myo-inositol (mI) concentrations and gray-matter/white-matter (GM/WM) and cerebrospinal fluid fractions were obtained in each voxel. Global GM and WM absolute metabolic concentrations were estimated using linear regression, and patients were compared with controls using two-way analysis of variance. In patients, mean NAA, Cr, Cho and mI concentrations in GM (8.4 ± 0.7, 6.9 ± 0.6, 1.3 ± 0.2, 5.5 ± 0.6 mM) and Cr, Cho and mI in WM (4.8 ± 0.5, 1.4 ± 0.2, 4.6 ± 0.7 mM) were not different from the values in controls. The NAA concentrations in WM, however, were significantly lower in patients than in controls (7.2 ± 0.8 vs. 7.7 ± 0.6 mM, p = 0.0125). The Cho and Cr levels in WM of patients were positively correlated with time since mTBI. This (1)H-MRSI approach allowed us to ascertain that early mTBI sequelae are (1) diffuse (not merely local), (2) neuronal (not glial), and (3) in the global WM (not GM). These findings support the hypothesis that, similar to more severe head trauma, mTBI also results in diffuse axonal injury, but that dysfunction rather than cell death dominates shortly after injury.

Default-mode network disruption in mild traumatic brain injury.

PURPOSE: To investigate the integrity of the default-mode network (DMN) by using independent component analysis (ICA) methods in patients shortly after mild traumatic brain injury (MTBI) and healthy control subjects, and to correlate DMN connectivity changes with neurocognitive tests and clinical symptoms. MATERIALS AND METHODS: This study was approved by the institutional review board and complied with HIPAA regulations. Twenty-three patients with MTBI who had posttraumatic symptoms shortly after injury (<2 months) and 18 age-matched healthy control subjects were included in this study. Resting-state functional magnetic resonance imaging was performed at 3 T to characterize the DMN by using ICA methods, including a single-participant ICA on the basis of a comprehensive template from core seeds in the posterior cingulate cortex (PCC) and medial prefrontal cortex (MPFC) nodes. ICA z images of DMN components were compared between the two groups and correlated with neurocognitive tests and clinical performance in patients by using Pearson and Spearman rank correlation. RESULTS: When compared with the control subjects, there was significantly reduced connectivity in the PCC and parietal regions and increased frontal connectivity around the MPFC in patients with MTBI (P < .01). These frontoposterior opposing changes within the DMN were significantly correlated (r = -0.44, P = .03). The reduced posterior connectivity correlated positively with neurocognitive dysfunction (eg, cognitive flexibility), while the increased frontal connectivity correlated negatively with posttraumatic symptoms (ie, depression, anxiety, fatigue, and postconcussion syndrome). CONCLUSION: These results showed abnormal DMN connectivity patterns in patients with MTBI, which may provide insight into how neuronal communication and information integration are disrupted among DMN key structures after mild head injury.

The role of gray and white matter segmentation in quantitative proton MR spectroscopic imaging.

Since the brain's gray matter (GM) and white matter (WM) metabolite concentrations differ, their partial volumes can vary the voxel's ¹H MR spectroscopy (¹H-MRS) signal, reducing sensitivity to changes. While single-voxel ¹H-MRS cannot differentiate between WM and GM signals, partial volume correction is feasible by MR spectroscopic imaging (MRSI) using segmentation of the MRI acquired for VOI placement. To determine the magnitude of this effect on metabolic quantification, we segmented a 1-mm³ resolution MRI into GM, WM and CSF masks that were co-registered with the MRSI grid to yield their partial volumes in approximately every 1 cm³ spectroscopic voxel. Each voxel then provided one equation with two unknowns: its i- metabolite's GM and WM concentrations C(i) (GM) , C(i) (WM) . With the voxels' GM and WM volumes as independent coefficients, the over-determined system of equations was solved for the global averaged C(i) (GM) and C(i) (WM) . Trading off local concentration differences offers three advantages: (i) higher sensitivity due to combined data from many voxels; (ii) improved specificity to WM versus GM changes; and (iii) reduced susceptibility to partial volume effects. These improvements made no additional demands on the protocol, measurement time or hardware. Applying this approach to 18 volunteered 3D MRSI sets of 480 voxels each yielded N-acetylaspartate, creatine, choline and myo-inositol C(i) (GM) concentrations of 8.5 ± 0.7, 6.9 ± 0.6, 1.2 ± 0.2, 5.3 ± 0.6 mM, respectively, and C(i) (WM) concentrations of 7.7 ± 0.6, 4.9 ± 0.5, 1.4 ± 0.1 and 4.4 ± 0.6mM, respectively. We showed that unaccounted voxel WM or GM partial volume can vary absolute quantification by 5-10% (more for ratios), which can often double the sample size required to establish statistical significance.

Characterizing brain oxygen metabolism in patients with multiple sclerosis with T2-relaxation-under-spin-tagging MRI.

In this study, venous oxygen saturation and oxygen metabolic changes in multiple sclerosis (MS) patients were assessed using a recently developed T2-relaxation-under-spin-tagging (TRUST) magnetic resonance imaging (MRI), which measures the superior sagittal venous sinus blood oxygenation (Yv) and cerebral metabolic rate of oxygen (CMRO(2)), an index of global oxygen consumption. Thirty patients with relapsing-remitting MS and 30 age-matched healthy controls were studied using TRUST at 3 T MR. The mean expanded disability status scale (EDSS) of the patients was 2.3 (range, 0 to 5.5). We found significantly increased Yv (P<0.0001) and decreased CMRO(2) (P=0.003) in MS patients (mean±s.d.: 65.9%±5.1% and 138.8±35.4 µmol per 100 g per minute) as compared with healthy control subjects (60.2%±4.0% and 180.2±24.8 µmol per 100 g per minute, respectively), implying decrease of oxygen consumption in MS. There was a significant positive correlation between Yv and EDSS and between Yv and lesion load in MS patients (n=30); on the contrary, there was a significant negative correlation between CMRO(2) and EDSS and between CMRO(2) and lesion load (n=12). There was no correlation between Yv and brain atrophy measures. This study showed preliminary evidence of the potential utility of TRUST in global oxygen metabolism. Our results of significant underutilization of oxygen in MS raise important questions regarding mitochondrial respiratory dysfunction and neurodegeneration of the disease.