Resting-state Functional MR Imaging Research Articles

Total sleep deprivation alters spontaneous brain activity in medical staff during routine clinical work: a resting-state functional MR imaging study.

To assess the effect of total sleep deprivation (TSD) on spontaneous brain activity in medical staff during routine clinical practice. A total of 36 medical staff members underwent resting-state functional MRI (rs-fMRI) scans and neuropsychological tests twice, corresponding to rested wakefulness (RW) after normal sleep and 24 h of acute TSD. The rs-fMRI features, including the mean fractional amplitude of low-frequency fluctuation (mfALFF), z-score transformed regional homogeneity (zReHo), and functional connectivity (zFC), were compared between RW and TSD. Correlation coefficients between the change in altered rs-fMRI features and the change in altered scores of neuropsychological tests after TSD were calculated. Receiver operating characteristic (ROC) and logistic regression analyses were performed to evaluate the diagnostic efficacy of significantly altered rs-fMRI features in distinguishing between RW and TSD states. Brain regions, including right superior temporal gyrus, bilateral postcentral gyrus, left medial superior frontal gyrus, left middle temporal gyrus, right precentral gyrus, and left precuneus, showed significantly enhanced rs-fMRI features (mfALFF, zReHo, zFC) after TSD. Moreover, the changes in altered rs-fMRI features of the right superior temporal gyrus, bilateral postcentral gyrus, left middle temporal gyrus, and left precuneus were significantly correlated with the changes in several altered scores of neuropsychological tests. The combination of mfALFF (bilateral postcentral gyrus) and zFC (left medial superior frontal gyrus and left precuneus) showed the highest area under the curve (0.870) in distinguishing RW from TSD. Spontaneous brain activity alterations occurred after TSD in routine clinical practice, which might explain the reduced performances of these participants in neurocognitive tests after TSD. These alterations might be potential imaging biomarkers for assessing the impact of TSD and distinguishing between RW and TSD states.

104-OR: Identifying Painful Diabetic Neuropathy Subtypes from Resting-State Functional Magnetic Resonance Brain Imaging—A Novel Unsupervised Machine Learning Approach

The use of neuroimaging methods to develop biomarkers in painful DN have yielded promising results but have yet to demonstrate clear clinical utility. Our aim was to delineate the biological heterogeneity in painful DN by first defining the functional connectivity subtypes in patients then assessing the clinical significance with respect to prediction of treatment outcomes. Methods: 82 painful-DN subjects and 36 HV underwent resting-state functional MR imaging (RS-fMRI). Painful-DN subjects were divided into training (n=48) and testing (n=34) datasets. Clinical pain subtypes were identified by analysing, via unsupervised, machine learning (k-means algorithm), the RS-fMRI functional connectivity of key somatosensory/nociceptive brain regions. Patients in our testing dataset were divided into responders (VAS<4; n=23) and non-responders (VAS>4; n=11). Results: RS-fMRI functional connectivity defines two clinically relevant painful-DN subtypes. The two subtypes were characterised by strong functional connectivity differences in the postcentral (p<0.001, 95%CI=0.22:0.65) and precentral (p=0.002, 95%CI=0.15:0.59) parietal cortex functional connectivity. The interhemispheric connectivity between homologous regions was also notable. RS-fMRI functional connectivity differences in the default mode network (p=0.002;95%CI=-0.35:-0.08) was also identified. The performance of our unsupervised k-means model to predict treatment response was accuracy=0.77, recall=0.83, precision=0.83 and an AUC=0.73. Conclusion: We have identified neurobiological markers of painful DN subtypes from brain functional connectivity using an unsupervised data-driven approach. The subtype whose functional connectivity differed most from HV failed to respond to neuropathic pain treatment. External validation on a large independent dataset is now required to confirm future clinical utility. Disclosure D.Selvarajah: None. K.Teh: None. A.Anandhanarayanan: None. G.P.Sloan: None. S.Tesfaye: Advisory Panel; Bayer Inc., Wörwag Pharma GmbH & Co. KG, Angelini, Speaker's Bureau; Viatris Inc., Nevro Corp., Procter & Gamble, Novo Nordisk, Berlin-Chemie AG. Funding National Institute for Health and Care Research Efficacy and Mechanisms Evaluation; European Foundation for the Study of Diabetes

Disruption of cerebellar-cortical functional connectivity predicts balance instability in alcohol use disorder

BackgroundA neural substrate of alcohol-related instability of gait and balance is the cerebellum. Whether disruption of neural communication between cerebellar and cortical brain regions exerts an influence on ataxia in alcohol use disorder (AUD) was the focus of this study. MethodsStudy groups comprised 32 abstinent AUD participants and 22 age- and sex-matched healthy controls (CTL). All participants underwent clinical screening, motor testing, and resting-state functional MR imaging analyzed for functional connectivity (FC) among 90 regions across the whole cerebrum and cerebellum. Ataxia testing quantified gait and balance with the Fregly-Graybiel Ataxia Battery conducted with and without vision. ResultsThe AUD group achieved lower scores than the CTL group on balance performance, which was disproportionately worse for eyes open than eyes closed in the AUD relative to the CTL group. Differences in ataxia were accompanied by differences in FC marked by cerebellar-frontal and cerebellar-parietal hyperconnectivity and cortico-cortical hypoconnectivity in the AUD relative to the control group. Lifetime alcohol consumption correlated significantly with AUD-related FC aberrations, which explained upwards of 69% of the AUD ataxia score variance. ConclusionHeavy, chronic alcohol consumption is associated with disorganized neural communication among cerebellar–cortical regions and contributes to ataxia in AUD. Ataxia, which is known to accelerate with age and be exacerbated with AUD, can threaten functional independence. Longitudinal studies are warranted to address whether extended sobriety quells ataxia and normalizes aberrant FC contributing to instability.

Dynamic Brain Connectivity in Resting State Functional MR Imaging.

Dynamic functional connectivity adds another dimension to resting-state functional MR imaging analysis. In recent years, dynamic functional connectivity has been increasingly used in resting-state functional MR imaging, and several studies have demonstrated that dynamic functional connectivity patterns correlate with different physiologic and pathologic brain states. In fact, evidence suggests that dynamic functional connectivity is a more sensitive marker than static functional connectivity; therefore, it might be a promising tool to add to clinical functional neuroimaging. This article provides a broad overview of dynamic functional connectivity and reviews its general principles, techniques, and potential clinical applications.

Resting State Functional MR Imaging of Language Function.

Resting state functional MR imaging methods can provide localization of the language system; however, presurgical functional localization of the language system with task-based functional MR imaging is the current standard of care before resection of brain tumors. These methods provide similar results and comparing them could be helpful for presurgical planning. We combine information from 3 data resources to provide quantitative information on the components of the language system. Tables and figures compare anatomic information, localization information from resting state fMR imaging, and activation patterns in different components of the language system expected from commonly used task fMR imaging experiments.

Introduction to Functional MR Imaging.

During the past decade, functional MR imaging has rapidly moved from the research environment into clinical practice. Preoperative functional MR imaging is now standard clinical practice not only in major academic institutions, but also in community neurosurgical and neuroradiologic practices. The clinical use of functional MR imaging will only increase in the years to come. Application of functional MR imaging (including resting-state functional MR imaging) to the context of neuropsychiatric diseases is likely to continue to advance.

Disrupted Functional and Structural Connectivity in Angelman Syndrome.

This work investigated alterations in functional connectivity (FC) and associated structures in patients with Angelman syndrome (AS) by using integrated quantitative imaging analysis and connectivity measures. We obtained 3T brain MR imaging, including resting-state functional MR imaging, diffusion tensor imaging, and 3D T1-weighted imaging from children with AS (n = 14) and age- and sex-matched controls (n = 28). The brains of patients with AS were analyzed by measuring FC, white matter microstructural analysis, cortical thickness, and brain volumes; these were compared with brains of controls. Interregional FC analysis revealed significantly reduced intra- and interhemispheric FC, especially in the basal ganglia and thalamus, in patients with AS. Significant reductions in fractional anisotropy were found in the corpus callosum, cingulum, posterior limb of the internal capsules, and arcuate fasciculus in patients with AS. Quantitative structural analysis also showed gray matter volume loss of the basal ganglia and diffuse WM volume reduction in AS compared with the control group. This integrated quantitative MR imaging analysis demonstrated poor functional and structural connectivity, as well as brain volume reduction, in children with AS, which may explain the motor and language dysfunction observed in this well-characterized neurobehavioral phenotype.

Structural and Functional Alterations in Hemodialysis Patients: A Voxel-Based Morphometry and Functional Connectivity Study.

Structural and functional brain alterations have been always observed in end-stage renal disease (ESRD) patients undergoing hemodialysis. The present study aimed to investigate the gray matter volume (GMV) changes in hemodialysis patients compared with those noted in healthy subjects, as well as explore the associated functional connectivity alterations based on the abnormal GMV regions. The experiments revealed the effects of regional morphometry aberrance on the brain functional integrity. A total of 46 hemodialysis patients (53.11 ± 1.58 years, 28 males) and 47 healthy subjects (55.57 ± 0.86 years, 22 males) were enrolled in the present study. All subjects underwent high-resolution T1-weighted imaging, resting-state functional MR imaging, and laboratory examinations were performed in hemodialysis patients. The GMV deficits were analyzed using voxel-based morphometry (VBM) and regions with GMV alteration were defined as seeds for functional connectivity analysis. Correlation analyses between significantly different regions and the results of the blood examination were further performed. We found that bilateral thalamus exhibited significantly increased volumes in the hemodialysis patients compared with those of the healthy subjects. However, the bilateral rectus, bilateral caudate, and bilateral temporal gyrus demonstrated significantly decreased volumes. When the regions with GMV alterations were defined as seeds, the hemodialysis patients exhibited decreased integrations in the thalamo-cortical network and within the basal-ganglia connection. The present study revealed the presence of different types of structural and functional brain impairments in hemodialysis patients.

Multivariate Pattern Classification of Primary Insomnia Using Three Types of Functional Connectivity Features.

Objective: To explore whether or not functional connectivity (FC) could be used as a potential biomarker for classification of primary insomnia (PI) at the individual level by using multivariate pattern analysis (MVPA).Methods: Thirty-eight drug-naive patients with PI, and 44 healthy controls (HC) underwent resting-state functional MR imaging. Voxel-wise functional connectivity strength (FCS), large-scale functional connectivity (large-scale FC) and regional homogeneity (ReHo) were calculated for each participant. We used support vector machine (SVM) with the three types of metrics as features separately to classify patients from healthy controls. Then we evaluated its classification performances. Finally, FC metrics with significant high classification performance were compared between the two groups and were correlated with clinical characteristics, i.e., Insomnia Severity Index (ISI), Pittsburgh Sleep Quality Index (PSQI), Self-rating Anxiety Scale (SAS), Self-rating Depression Scale (SDS) in the patients' group.Results: The best classifier could reach up to an accuracy of 81.5%, with a sensitivity of 84.9%, specificity of 79.1%, and area under the receiver operating characteristic curve (AUC) of 83.0% (all P < 0.001). Right anterior insular cortex (BA48), left precuneus (BA7), and left middle frontal gyrus (BA8) showed high classification weights. In addition, the right anterior insular cortex (BA48) and left middle frontal gyrus (BA8) were the overlapping regions between MVPA and group comparison. Correlation analysis showed that FCS in left middle frontal gyrus and head of right caudate nucleus were correlated with PSQI and SDS, respectively.Conclusion: The current study suggests abnormal FCS in right anterior insular cortex (BA48) and left middle frontal gyrus (BA8) might serve as a potential neuromarkers for PI.

Uric Acid Has Different Effects on Spontaneous Brain Activities of Males and Females: A Cross-Sectional Resting-State Functional MR Imaging Study.

ObjectiveTo explore the relationship among serum uric acid (SUA) levels in different states of disease, human cognition, and spontaneous brain activities by resting-state functional MRI (rs-fMRI).MethodsWe prospectively recruited 100 subjects (age 58 ± 11 years, 55 females) who underwent fasting blood sampling, cognitive tests and rs-fMRI scans. The subjects were divided into two groups by sex and each sex group was further stratified into three subgroups according to SUA level in different states of disease. The amplitude of low-frequency fluctuation (ALFF) method was applied to assess spontaneous brain activity among groups. Pearson’s correlation analysis was used to investigate the relationships between the mean ALFF values (mALFF) and cognitive tests.ResultsA total of 97 patients completed the study protocol successfully. Significant differences in age, education level, number connection test (NCT), and word fluency were observed among the three subgroups in males (all P < 0.05). Results of group-by-sex interaction were distributed in bilateral pallidum and putamen [voxel P-value < 0.001, cluster P-value < 0.05, Gaussian random field (GRF)-corrected]. The tendency of the SUA effect on mALFF was different in males and females, particularly in corresponding High SUA subgroups (that is pre-hyperuricemia, both P < 0.001). Among the male subjects, mALFF values of the bilateral pallidum and putamen negatively correlated with attention/executive function.ConclusionOur results suggest that elevated SUA levels have different effects on spontaneous brain activities and cognitive function in males and females. Males with pre-hyperuricemia and hyperuricemia are more susceptible to changes in spontaneous brain activities and lower neuropsychological assessment scores, particularly in word fluency tests and NCT, compared to females.

A failed top-down control from the prefrontal cortex to the amygdala in generalized anxiety disorder: Evidence from resting-state fMRI with Granger causality analysis

In generalized anxiety disorder (GAD), abnormal top-down control from the prefrontal cortex (PFC) to the amygdala is a widely accepted hypothesis through which an "emotional dysregulation model" may be explained. However, whether and how the PFC directly exerts abnormal top-down control on the amygdala remains largely unknown. We aimed to investigate the amygdala-based effective connectivity by using Granger causality analysis (GCA). Thirty-five drug-naive patients with GAD and thirty-six healthy controls (HC) underwent resting-state functional MR imaging. We used seed-based Granger causality analysis to examine the effective connectivity between the bilateral amygdala and the whole brain. The amygdala-based effective connectivity was compared between the HC and GAD groups. The results showed that, in the HC group, the left middle frontal gyrus exerted an inhibitory influence on the right amygdala, while in the GAD group, this influence was disrupted (single voxel P < 0.001, Gaussian random field corrected with P < 0.01). Our findings support and advance the "insufficient top-down control" hypothesis by identifying a failed top-down control from the prefrontal cortex to the amygdala in GAD.

Postchemotherapy hippocampal functional connectivity patterns in patients with breast cancer: a longitudinal resting state functional MR imaging study

The hippocampus plays a key role in cognitive function and emotion regulation due to its wide connection with the whole brain. This study examined the acute effect of chemotherapy on hippocampal and subfield functional connectivity and neuropsychological status in breast cancer patients (BC). This IRB approved study included 29BC and 25 age matched healthy controls (HCs) who underwent resting state functional magnetic resonance imaging (Rs-fMRI), neuropsychological tests and blood examinations at baseline and one week after completing chemotherapy or in the same time interval. Within-group comparisons and group-by-time interactions analysis of hippocampus- and subregion- based functional connectivity were performed between the two groups. Functional connectivity changes were correlated with changes of blood examination and neuropsychological test scores in the BC group. The BC group had higher depression and anxiety scores, poorer performance on visual mobility, auditory memory and executive function than HCs (p < 0.05), and significantly abnormal estrodiol, total cholesterol and triglycerides (p < 0.05). BC survivors showed significant hippocampal functional connectivity changes mainly in the left insula, temporal lobe (Gaussian Random Field theory correction, P < 0.001) and the left inferior frontal gyrus (P < 0.01). The functional connections from the anterior hippocampus to the left temporal lobe were greater than the posterior hippocampus (P < 0.05). The hippocampus functional connectivity alterations were closely related to changes in depression scores, estrodiol and triglycerides (all p < 0.05). Chemotherapy induced especially anterior hippocampal functional connectivity abnormality, which is related to depression symptom, estrodiol and triglycerides disorders.

Functional connectivity disruption of the substantia nigra associated with cognitive impairment in acute mild traumatic brain injury

PurposeMild traumatic brain injury is known to have frequent cognitive impairment. Accumulating evidence is pointing to the malfunctioning of the substantia nigra (SN) as an important factor for head trauma. However, it remains unknown whether changes in the SN-based resting state functional connectivity following mTBI at acute stage and its relationship with cognitive function. Materials and methods58 patients with mTBI and 30 age-, gender-, and years of education-matched healthy controls were enrolled in the current study. All of participants received resting state functional magnetic resonance imaging as well as neuropsychological assessment. The resting state functional MR imaging data were analyzed by using a standard seed-based whole-brain correlation method to characterize SN resting state networks. Student t tests were used to perform comparisons. The association between SN resting state networks and performance on neuropsychological measures was also investigated in patients with mTBI by using Pearson rank correlation. ResultsPatients with mTBI at acute stage exhibited reduced left SN-based functional connectivity with right insula and caudate and increased left SN-based functional connectivity with left precuneus and left middle occipital gyrus, and reduced right SN-based functional connectivity with left insula. Increased functional connectivity of left precuneus was negatively associated with neurocognitive functions as well (r = -0.266; P = 0.049). ConclusionThe present study indicated that patients with acute mTBI suffer from disruption in their SN resting state networks. Moreover, abnormal functional connectivity significantly correlated with cognitive function. Taking together, these results may better improve our understanding of the neuropathological mechanism underlying the neurocognitive symptoms associated with acute mTBI.

A Resting-State Functional MR Imaging and Spectroscopy Study of the Dorsal Hippocampus in the Chronic Unpredictable Stress Rat Model

Exposure to chronic stress leads to an array of anatomical, functional, and metabolic changes in the brain that play a key role in triggering psychiatric disorders such as depression. The hippocampus is particularly well known as a target of maladaptive responses to stress. To capture stress-induced changes in metabolic and functional connectivity in the hippocampus, stress-resistant (low-responders) or -susceptible (high-responders) rats exposed to a chronic unpredictable stress paradigm (categorized according to their hormonal and behavioral responses) were assessed by multimodal neuroimaging; the latter was achieved by using localized 1H MR spectroscopy and resting-state functional MRI (fMRI) at 11,7T data from stressed (n = 25) but also control (n = 15) male Wistar rats.Susceptible animals displayed increased GABA-glutamine (+19%) and glutamate-glutamine (+17%) ratios and decreased levels of macromolecules (-11%); these changes were positively correlated with plasma corticosterone levels. In addition, the neurotransmitter levels showed differential associations with functional connectivity between the hippocampus and the amygdala, the piriform cortex and thalamus between stress-resistant and -susceptible animals. Our observations are consistent with previously reported stress-induced metabolomic changes that suggest overall neurotransmitter dysfunction in the hippocampus. Their association with the fMRI data in this study reveals how local adjustments in neurochemistry relate to changes in the neurocircuitry of the hippocampus, with implications for its stress-associated dysfunctions.SIGNIFICANCE STATEMENT Chronic stress disrupts brain homeostasis, which may increase the vulnerability of susceptible individuals to neuropsychiatric disorders such as depression. Characterization of the differences between stress-resistant and -susceptible individuals on the basis of noninvasive imaging tools, such as magnetic resonance spectroscopy (MRS) and magnetic resonance imaging (MRI), contributes to improved understanding of the mechanisms underpinning individual differences in vulnerability and can facilitate the design of new diagnostic and intervention strategies. Using a combined functional MRI/MRS approach, our results demonstrate that susceptible- and non-susceptible subjects show differential alterations in hippocampal GABA and glutamate metabolism that, in turn, associate with changes in functional connectivity.

Pre-treatment Resting-State Functional MR Imaging Predicts the Long-Term Clinical Outcome After Short-Term Paroxtine Treatment in Post-traumatic Stress Disorder.

Background: The chronic phase of post-traumatic stress disorder (PTSD) and the limited effectiveness of existing treatments creates the need for the development of potential biomarkers to predict response to antidepressant medication at an early stage. However, findings at present focus on acute therapeutic effect without following-up the long-term clinical outcome of PTSD. So far, studies predicting the long-term clinical outcome of short-term treatment based on both pre-treatment and post-treatment functional MRI in PTSD remains limited.Methods: Twenty-two PTSD patients were scanned using resting-state functional MRI (rs-fMRI) before and after 12 weeks of treatment with paroxetine. Twenty patients were followed up using the same psychopathological assessments 2 years after they underwent the second MRI scan. Based on clinical outcome, the follow-up patients were divided into those with remitted PTSD or persistent PTSD. Amplitude of low-frequency fluctuations (ALFF) and degree centrality (DC) derived from pre-treatment and post-treatment rs-fMRI were used as classification features in a support vector machine (SVM) classifier.Results: Prediction of long-term clinical outcome by combined ALFF and DC features derived from pre-treatment rs-fMRI yielded an accuracy rate of 72.5% (p < 0.005). The most informative voxels for outcome prediction were mainly located in the precuneus, superior temporal area, insula, dorsal medial prefrontal cortex, frontal orbital cortex, supplementary motor area, lingual gyrus, and cerebellum. Long-term outcome could not be successfully classified by post-treatment imaging features with accuracy rates <50%.Conclusions: Combined information from ALFF and DC from rs-fMRI data before treatment could predict the long-term clinical outcome of PTSD, which is critical for defining potential biomarkers to customize PTSD treatment and improve the prognosis.

Aberrant interhemispheric functional connectivity in first-episode, drug-naïve major depressive disorder.

Many studies have indicated that depression is associated with impairment of the topological organization of the brain functional network, which may lead to disruption of mood and cognition in depressive patients. The abnormality of homotopic connectivity provides a basis for the clinical manifestations of depression, such as emotional and cognitive disorders. Several studies have investigated the abnormal imbalance of homotopic regions between the hemispheres in depressive patients. However, the reported findings are inconsistent. Additionally, the published studies have focused on only the grey matter when investigating functional connectivity abnormalities of the bilateral cerebral hemispheres in major depressive disorder (MDD). The aim of this study is to investigate functional connectivity abnormalities of the bilateral cerebral hemispheres in patients with first-episode, drug-naïve MDD using a voxel-mirrored homotopic connectivity (VMHC) method. Based on DSM-IV diagnostic criteria, 23 first-episode, drug-naïve MDD patients were recruited, together with 20 gender- and age-matched healthy normal controls. A Philips Achieva 3.0T MRI scanner was used to acquire brain functional images at resting state as well as high-resolution structural images. The functional images were preprocessed by using Data Processing Assistant for Resting-State Functional MR Imaging toolkit and SPM8.VMHC between the bilateral hemispheres was computed and compared between the MDD and control groups. The correlation between the VMHC values of the abnormal homotopy function areas and the Hamilton Depression Rating Scale (HAMD) was evaluated in the MDD patients. Compared with the control group, the MDD patients showed significantly decreased VMHC values in the bilateral brain regions including the insular, putamen, and frontal white matter. The MDD patients did not exhibit increased VMHC values in any brain regions compared with the normal controls. In addition, a negative correlation was observed between the VMHC value in the frontal lobe white-matter and the HAMD in the MDD patients. Abnormalities in brain homotopic functional connectivity observed in this study may indicate abnormal neural circuits related to aberrant cognition and emotional processing in MDD. Although the physiological significance underlaying abnormal VMHC in white matter in the frontal lobe needs further research, our study new angle to investigate the role of white-matter abnormalities in MDD as well as other psychiatric disorders.

Abnormal Blood Oxygen Level-Dependent Fluctuations in Focal Cortical Dysplasia and the Perilesional Zone: Initial Findings.

Focal cortical dysplasia is a common cause of intractable epilepsy for which neurosurgery is an option. Delineations of a focal cortical dysplasia lesion on structural brain images may not necessarily reflect the functional borders of normal tissue. Our objective was to determine whether abnormalities in spontaneous blood oxygen level-dependent fluctuations arise in focal cortical dysplasia lesions and proximal regions. Fourteen patients with focal cortical dysplasia-related epilepsy and 16 healthy controls underwent structural and resting-state functional MR imaging. Three known blood oxygen level-dependent measures were determined, including the fractional amplitude of low-frequency fluctuations, regional homogeneity, and wavelet entropy. These measures were evaluated in the lesion and perilesional zone and normalized to the contralateral cortex of patients with focal cortical dysplasia and healthy controls. Patients showed significantly decreased fractional amplitude of low-frequency fluctuations and increased wavelet entropy in the focal cortical dysplasia lesion and the perilesional zone (≤2 cm) relative to the contralateral homotopic cortex and the same regions in healthy controls. Regional homogeneity was significantly increased in the focal cortical dysplasia lesion compared with the contralateral homotopic cortex and healthy controls. Abnormalities in spontaneous blood oxygen level-dependent fluctuations were seen up to 2 cm distant from the radiologically visible boundary. It was demonstrated that functional boundaries go beyond structural boundaries of focal cortical dysplasia lesions. Validation is required to reveal whether this information is valuable for surgical planning and outcome evaluation of focal cortical dysplasia lesions and comparing current results with electrophysiologic analysis.

Functional MR Imaging: Blood Oxygen Level-Dependent and Resting State Techniques in Mild Traumatic Brain Injury.

This article discusses mild traumatic brain injury (mTBI)-associated effects on brain functional connectivity assessed via resting-state functional MR (fMR) imaging. Several studies have reported acute post-injury default mode network hyperconnectivity, followed by a period of decreased connectivity before later connectivity normalization in some patients. Other studies have reported mTBI associated effects on connectivity that remain evident for up to 5-years or more. Discordance in the published literature regarding the direction of network connectivity changes (eg, increased versus decreased connectivity) may reflect differences in timing of data collection post-injury, as well as the need to standardize MR imaging acquisition protocols and processing methods.

Application of Resting State Functional MR Imaging to Presurgical Mapping: Language Mapping.

Resting state functional MR imaging (rs-fMR imaging) has become an indispensable tool for examining brain function. The greatest opportunity to translate rs-fMR imaging from the research domain into clinical use is as a tool for examining intrinsic brain networks for preoperative planning. Many studies have demonstrated concordance of intrinsic motor networks from rs-fMR imaging data with task-fMR imaging and direct cortical stimulation. Earlier reports show concordance of language networks as well, although more recent studies with larger numbers of subjects demonstrate subject-level variability that needs to be further investigated and addressed before widespread implementation of rs-fMR imaging for preoperative planning.

Machine Learning Applications to Resting-State Functional MR Imaging Analysis.

Machine learning is one of the most exciting and rapidly expanding fields within computer science. Academic and commercial research entities are investing in machine learning methods, especially in personalized medicine via patient-level classification. There is great promise that machine learning methods combined with resting state functional MR imaging will aid in diagnosis of disease and guide potential treatment for conditions thought to be impossible to identify based on imaging alone, such as psychiatric disorders. We discuss machine learning methods and explore recent advances.