Treatment effects of N-acetyl cysteine on resting-state functional MRI and cognitive performance in patients with chronic mild traumatic brain injury: a longitudinal study.

Mild traumatic brain injury (mTBI) is a significant public health concern, specially characterized by a complex pattern of abnormal neural activity and functional connectivity. It is often associated with a broad spectrum of short-term and long-term cognitive and behavioral symptoms including memory dysfunction, headache, and balance difficulties. Furthermore, there is evidence that oxidative stress significantly contributes to these symptoms and neurophysiological changes. The purpose of this study was to assess the effect of N-acetylcysteine (NAC) on brain function and chronic symptoms in mTBI patients. Fifty patients diagnosed with chronic mTBI participated in this study. They were categorized into two groups including controls (CN, n = 25), and patients receiving treatment with N-acetyl cysteine (NAC, n = 25). NAC group received 50 mg/kg intravenous (IV) medication once a day per week. In the rest of the week, they took one 500 mg NAC tablet twice per day. Each patient underwent rs-fMRI scanning at two timepoints including the baseline and 3 months later at follow-up, while the NAC group received a combination of oral and IV NAC over that time. Three rs-fMRI metrics were measured including fractional amplitude of low frequency fluctuations (fALFF), degree centrality (DC), and functional connectivity strength (FCS). Neuropsychological tests were also assessed at the same day of scanning for each patient. The alteration of rs-fMRI metrics and cognitive scores were measured over 3 months treatment with NAC. Then, the correlation analysis was executed to estimate the association of rs-fMRI measurements and cognitive performance over 3 months (p < 0.05). Two significant group-by-time effects demonstrated the changes of rs-fMRI metrics particularly in the regions located in the default mode network (DMN), sensorimotor network, and emotional circuits that were significantly correlated with cognitive function recovery over 3 months treatment with NAC (p < 0.05). NAC appears to modulate neural activity and functional connectivity in specific brain networks, and these changes could account for clinical improvement. This study confirmed the short-term therapeutic efficacy of NAC in chronic mTBI patients that may contribute to understanding of neurophysiological effects of NAC in mTBI. These findings encourage further research on long-term neurobehavioral assessment of NAC assisting development of therapeutic plans in mTBI.

Exploring Functional Connectivity in Chronic Spinal Cord Injury Patients With Neuropathic Pain Versus Without Neuropathic Pain.

The great majority of spinal cord injury (SCI) patients have debilitating chronic pain. Despite decades of research, these pain pathways of neuropathic pain (NP) are unknown. SCI patients have been shown to have abnormal brain pain pathways. We hypothesize that SCI NP patients' pain matrix is altered compared to SCI patients without NP. This study examines the functional connectivity (FC) in SCI patients with moderate-severe chronic NP compared to SCI patients with mild-no NP. These groups were compared to control subjects. The Neuropathic Pain Questionnaire and neurological evaluation based on the International Standard Neurological Classification of SCI were utilized to define the severity and level of injury. Of the 10 SCI patients, 7 (48.6 ± 17.02 years old, 6 male and 1 female) indicated that they had NP and 3 did not have NP (39.33 ± 8.08 years old, 2 male and 1 female). Ten uninjured neurologically intact participants were used as controls (24.8 ± 4.61 years old, 5 male and 5 female). FC metrics were obtained from the comparisons of resting-state functional magnetic resonance imaging among our various groups (controls, SCI with NP, and SCI without NP). For each comparison, a region-of-interest (ROI)-to-ROI connectivity analysis was pursued, encompassing a total of 175 ROIs based on a customized atlas derived from the AAL3 atlas. The analysis accounted for covariates such as age and sex. To correct for multiple comparisons, a strict Bonferroni correction was applied with a significance level of p < 0.05/NROIs. When comparing SCI patients with moderate-to-severe pain to those with mild-to-no pain, specific thalamic nuclei had altered connections. These nuclei included: medial pulvinar; lateral pulvinar; medial geniculate nucleus; lateral geniculate nucleus; and mediodorsal magnocellular nucleus. There was increased FC between the lateral geniculate nucleus and the anteroventral nucleus in NP post-SCI. Our analysis additionally highlights the relationships between the frontal lobe and temporal lobe with pain. This study successfully identifies thalamic neuroplastic changes that occur in patients with SCI who develop NP. It additionally underscores the pain matrix and involvement of the frontal and temporal lobes as well. Our findings complement that the development of NP post-SCI involves cognitive, emotional, and behavioral influences.

Metal artifact reduction around cervical spine implant using diffusion tensor imaging at 3T: A phantom study.

PURPOSE: Diffusion MRI continues to play a key role in non-invasively assessing spinal cord integrity and pre-operative injury evaluation. However, post-operative Diffusion Tensor Imaging (DTI) acquisition of patients with metal implants results in severe geometric distortion. We propose and demonstrate a method to alleviate the technical challenges facing the acquisition of DTI on post-operative cases and longitudinal evaluation of therapeutics. MATERIAL AND METHODS: The described technique is based on the combination of the reduced Field-Of-View (rFOV) strategy and the phase segmented EPI, termed rFOV-PS-EPI. A custom-built phantom based on a cervical spine model with metal implants was used to collect DTI data at 3 Tesla scanner using: rFOV-PS-EPI, reduced Field-Of-View single-shot EPI (rFOV-SS-EPI), and conventional full FOV techniques including SS-EPI, PS-EPI, and readout-segmented EPI (RS-EPI). Geometric distortion, SNR, and signal void were assessed to evaluate images and compare the sequences. A two-sample t-test was performed with p-value of 0.05 or less to indicate statistical significance. RESULTS: The reduced FOV techniques showed better capability to reduce distortions compared to the Full FOV techniques. The rFOV-PS-EPI method provided DTI images of the phantom at the level of the hardware whereas the conventional rFOV-SS-EPI is useful only when the metal is approximately 20 mm away. In addition, compared to the rFOV-SS-EPI technique, the suggested approach produced smaller signal voids area as well as significantly reduced geometric distortion in Circularity (p < 0.005) and Eccentricity (p < 0.005) measurements. No statistically significant differences were found for these geometric distortion measurements between the rFOV-PS-EPI DTI sequence and conventional structural T2 images (p > 0.05). CONCLUSION: The combination of rFOV and a phase-segmented acquisition approach is effective for reducing metal-induced distortions in DTI scan on spinal cord with metal hardware at 3 T.

Harmonization of multi-site diffusion tensor imaging data for cervical and thoracic spinal cord at 1.5 T and 3 T using longitudinal ComBat.

MRI scanner hardware, field strengths, and sequence parameters are major variables in diffusion studies of the spinal cord. Reliability between scanners is not well known, particularly for the thoracic cord. DTI data was collected for the entire cervical and thoracic spinal cord in thirty healthy adult subjects with different MR vendors and field strengths. DTI metrics were extracted and averaged for all slices within each vertebral level. Metrics were examined for variability and then harmonized using longitudinal ComBat (longComBat). Four scanners were used: Siemens 3 T Prisma, Siemens 1.5 T Avanto, Philips 3 T Ingenia, Philips 1.5 T Achieva. Average full cord diffusion values/standard deviation for all subjects and scanners were FA: 0.63, σ = 0.10, MD: 1.11, σ = 0.12 × 10-3 mm2/s, AD: 1.98, σ = 0.55 × 10-3 mm2/s, RD: 0.67, σ = 0.31 × 10-3 mm2/s. FA metrics averaged for all subjects by level were relatively consistent across scanners, but large variability was found in diffusivity measures. Coefficients of variation were lowest in the cervical region, and relatively lower for FA than diffusivity measures. Harmonized metrics showed greatly improved agreement between scanners. Variability in DTI of the spinal cord arises from scanner hardware differences, pulse sequence differences, physiological motion, and subject compliance. The use of longComBat resulted in large improvement in agreement of all DTI metrics between scanners. This study shows the importance of harmonization of diffusion data in the spinal cord and potential for longitudinal and multisite clinical research and clinical trials.

Characteristic dynamic functional connectivity during sevoflurane-induced general anesthesia.

General anesthesia (GA) during surgery is commonly maintained by inhalational sevoflurane. Previous resting state functional MRI (rs-fMRI) studies have demonstrated suppressed functional connectivity (FC) of the entire brain networks, especially the default mode networks, transitioning from the awake to GA condition. However, accuracy and reliability were limited by previous administration methods (e.g. face mask) and short rs-fMRI scans. Therefore, in this study, a clinical scenario of epilepsy patients undergoing laser interstitial thermal therapy was leveraged to acquire 15 min of rs-fMRI while under general endotracheal anesthesia to maximize the accuracy of sevoflurane level. Nine recruited patients had fMRI acquired during awake and under GA, of which seven were included in both static and dynamic FC analyses. Group independent component analysis and a sliding-window method followed by k-means clustering were applied to identify four dynamic brain states, which characterized subtypes of FC patterns. Our results showed that a low-FC brain state was characteristic of the GA condition as a single featuring state during the entire rs-fMRI session; In contrast, the awake condition exhibited frequent fluctuations between three distinct brain states, one of which was a highly synchronized brain state not seen in GA. In conclusion, our study revealed remarkable dynamic connectivity changes from awake to GA condition and demonstrated the advantages of dynamic FC analysis for future studies in the assessments of the effects of GA on brain functional activities.

Machine learning-based classification of chronic traumatic brain injury using hybrid diffusion imaging.

Background and purpose: Traumatic brain injury (TBI) can cause progressive neuropathology that leads to chronic impairments, creating a need for biomarkers to detect and monitor this condition to improve outcomes. This study aimed to analyze the ability of data-driven analysis of diffusion tensor imaging (DTI) and neurite orientation dispersion imaging (NODDI) to develop biomarkers to infer symptom severity and determine whether they outperform conventional T1-weighted imaging. Materials and methods: A machine learning-based model was developed using a dataset of hybrid diffusion imaging of patients with chronic traumatic brain injury. We first extracted the useful features from the hybrid diffusion imaging (HYDI) data and then used supervised learning algorithms to classify the outcome of TBI. We developed three models based on DTI, NODDI, and T1-weighted imaging, and we compared the accuracy results across different models. Results: Compared with the conventional T1-weighted imaging-based classification with an accuracy of 51.7-56.8%, our machine learning-based models achieved significantly better results with DTI-based models at 58.7-73.0% accuracy and NODDI with an accuracy of 64.0-72.3%. Conclusion: The machine learning-based feature selection and classification algorithm based on hybrid diffusion features significantly outperform conventional T1-weighted imaging. The results suggest that advanced algorithms can be developed for inferring symptoms of chronic brain injury using feature selection and diffusion-weighted imaging.

Case report: Utilizing diffusion-weighted MRI on a patient with chronic low back pain treated with spinal cord stimulation.

Diffusion-weighted magnetic resonance imaging (dwMRI) has increasingly demonstrated greater utility in analyzing neuronal microstructure. In patients with chronic low back pain (cLBP), using dwMRI to observe neuronal microstructure can lead to non-invasive biomarkers which could provide clinicians with an objective quantitative prognostic tool. In this case report, we investigated dwMRI for the development of non-invasive biomarkers by conducting a region-based analysis of a 55-year-old male patient with failed back surgery syndrome (FBSS) treated with spinal cord stimulation (SCS). We hypothesized that dwMRI could safely generate quantitative data reflecting cerebral microstructural alterations driven by neuromodulation. Neuroimaging was performed at 6- and 12- months post-SCS implantation. The quantitative maps generated included diffusion tensor imaging (DTI) parameters; fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD) computed from whole brain tractography. To examine specific areas of the brain, 44 regions of interest (ROIs), collectively representing the pain NeuroMatrix, were extracted and registered to the patient's diffusion space. Average diffusion indices were calculated from the ROIs at both 6- and 12- months. Regions with >10% relative change in at least 3 of the 4 maps were reported. Using this selection criterion, 8 ROIs demonstrated over 10% relative changes. These ROIs were mainly located in the insular gyri. In addition to the quantitative data, a series of questionnaires were administered during the 6- and 12-month visits to assess pain intensity, functional disability, and quality of life. Overall improvements were observed in these components, with the Pain Catastrophizing Scale (PCS) displaying the greatest change. Lastly, we demonstrated the safety of dwMRI for a patient with SCS. In summary, the results from the case report prompt further investigation in applying dwMRI in a larger cohort to better correlate the influence of SCS with brain microstructural alterations, supporting the utility of dwMRI to generate non-invasive biomarkers for prognostication.

Automated subfield volumetric analysis of amygdala, hippocampus, and thalamic nuclei in mesial temporal lobe epilepsy.

Purpose: Identifying relationships between clinical features and quantitative characteristics of the amygdala-hippocampal and thalamic subregions in mesial temporal lobe epilepsy (mTLE) may offer insights into pathophysiology and the basis for imaging prognostic markers of treatment outcome. Our aim was to ascertain different patterns of atrophy or hypertrophy in mesial temporal sclerosis (MTS) patients and their associations with post-surgical seizure outcomes. To assess this aim, this study is designed in 2 folds: (1) hemispheric changes within MTS group and (2) association with postsurgical seizure outcomes. Methods and materials: 27 mTLE subjects with mesial temporal sclerosis (MTS) were scanned for conventional 3D T1w MPRAGE images and T2w scans. With respect to 12 months post-surgical seizure outcomes, 15 subjects reported being seizure free (SF) and 12 reported continued seizures. Quantitative automated segmentation and cortical parcellation were performed using Freesurfer. Automatic labeling and volume estimation of hippocampal subfields, amygdala, and thalamic subnuclei were also performed. The volume ratio (VR) for each label was computed and compared between (1) between contralateral and ipsilateral MTS using Wilcoxon rank-sum test and (2) SF and not seizure free (NSF) groups using linear regression analysis. False Discovery rate (FDR) with significant level of 0.05 were used in both analyses to correct for multiple comparisons. Results: Amygdala: The medial nucleus of the amygdala was the most significantly reduced in patients with continued seizures when compared to patients who remained seizure free. Hippocampus: Comparison of ipsilateral and contralateral volumes with seizure outcomes showed volume loss was most evident in the mesial hippocampal regions such as CA4 and hippocampal fissure. Volume loss was also most explicit in the presubiculum body in patients with continued seizures at the time of their follow-up. Ipsilateral MTS compared to contralateral MTS analysis showed the heads of the ipsilateral subiculum, presubiculum, parasubiculum, dentate gyrus, CA4, and CA3 were more significantly affected than their respective bodies. Volume loss was most noted in mesial hippocampal regions. Thalamus: VPL and PuL were the most significantly reduced thalamic nuclei in NSF patients. In all statistically significant areas, volume reduction was observed in the NSF group. No significant volume reductions were noted in the thalamus and amygdala when comparing ipsilateral to contralateral sides in mTLE subjects. Conclusions: Varying degrees of volume loss were demonstrated in the hippocampus, thalamus, and amygdala subregions of MTS, especially between patients who remained seizure-free and those who did not. The results obtained can be used to further understand mTLE pathophysiology. Clinical relevance/application: In the future, we hope these results can be used to deepen the understanding of mTLE pathophysiology, leading to improved patient outcomes and treatments.

Neuroimaging findings in 4342 hospitalized COVID-19 subjects: A multicenter report from the United States and Europe.

BACKGROUND AND PURPOSE: To determine the incidence of acute neuroimaging (NI) findings and comorbidities in the coronavirus disease of 2019 (COVID-19)-infected subjects in seven U.S. and four European hospitals. METHODS: This is a retrospective study of COVID-19-positive subjects with the following inclusion criteria: age >18, lab-confirmed COVID-19 infection, and acute NI findings (NI+) attributed to COVID-19 on CT or MRI brain. NI+ and comorbidities in total hospitalized COVID-19-positive (TN) subjects were assessed. RESULTS: A total of 37,950 COVID-19-positive subjects were reviewed and 4342 underwent NI. NI+ incidence in subjects with NI was 10.1% (442/4342) including 7.9% (294/3701) in the United States and 22.8% (148/647) in Europe. NI+ incidence in TN was 1.16% (442/37,950). In NI (4342), incidence of ischemic stroke was 6.4% followed by intracranial hemorrhage (ICH) (3.8%), encephalitis (0.5%), sinus venous thrombosis (0.2%), and acute disseminated encephalomyelitis (ADEM) (0.2%). White matter involvement was seen in 57% of NI+. Hypertension was the most common comorbidity (54%) before cardiac disease (28.8%) and diabetes mellitus (27.7%). Cardiac disease (p < .025), diabetes (p < .014), and chronic kidney disease (p < .012) were more common in the United States. CONCLUSION: This multicenter, multinational study investigated the incidence and spectrum of NI+ in 37,950 hospitalized adult COVID-19 subjects including regional differences in incidences of NI+, associated comorbidities, and other demographics. NI+ incidence in TN was 1.16% including 0.95% in the United States and 2.09% in Europe. ICH, encephalitis, and ADEM were common in Europe, while ischemic strokes were more common in the United States. In this cohort, incidence and distribution of NI+ helped characterize the neurological complications of COVID-19.

The role of the insula in chronic pain following spinal cord injury: A resting-state fMRI study.

BACKGROUND AND PURPOSE: Spinal cord injury (SCI) results in the loss of motor and sensory function from disconnections between efferent and afferent pathways. Most SCI patients are affected with chronic neuropathic pain, but there is a paucity of data concerning neuroplastic changes following SCI. Chronic pain disrupts default networks and is associated with abnormal insular connectivity. The posterior insula (PI) is associated with the degree of pain and intensity of pain. The anterior insula (AI) is related to signal changes. Comprehension of SCI pain mechanisms is essential to elucidate effective treatment options. METHODS: This study examines the insular gyri functional connectivity (FC) of seven (five male, two female) SCI participants with moderate-severe chronic pain compared to 10 (five male, five female) healthy controls (HC). All subjects had 3-Tesla MRI performed and resting-state functional MRI (fMRI) was acquired. FC metrics were obtained from the comparisons of resting-state fMRI among our various groups. A seed-to-voxel analysis was pursued, encompassing six gyri of the insula. For multiple comparisons, a correction was applied with a significance level of p < .05. RESULTS: There were significant differences in FC of the insula between SCI participants with chronic pain compared with HC. In the SCI participants, there was hyperconnectivity of the AI and PI to the frontal pole. In addition, there was increased FC noted between the PI and the anterior cingulate cortex. Hyperconnectivity was also observed between the AI and the occipital cortex. CONCLUSIONS: These findings illustrate that there is a complex hyperconnectivity and modulation of pain pathways after traumatic SCI.

Resting-State fMRI Can Detect Alterations in Seizure Onset and Spread Regions in Patients with Non-Lesional Epilepsy: A Pilot Study.

Introduction: Epilepsy is defined as non-lesional (NLE) when a lesion cannot be localized via standard neuroimaging. NLE is known to have a poor response to surgery. Stereotactic electroencephalography (sEEG) can detect functional connectivity (FC) between zones of seizure onset (OZ) and early (ESZ) and late (LSZ) spread. We examined whether resting-state fMRI (rsfMRI) can detect FC alterations in NLE to see whether noninvasive imaging techniques can localize areas of seizure propagation to potentially target for intervention. Methods: This is a retrospective study of 8 patients with refractory NLE who underwent sEEG electrode implantation and 10 controls. The OZ, ESZ, and LSZ were identified by generating regions around sEEG contacts that recorded seizure activity. Amplitude synchronization analysis was used to detect the correlation of the OZ to the ESZ. This was also done using the OZ and ESZ of each NLE patient for each control. Patients with NLE were compared to controls individually using Wilcoxon tests and as a group using Mann-Whitney tests. Amplitude of low-frequency fluctuations (ALFF), fractional ALFF (fALFF), regional homogeneity (ReHo), degree of centrality (DoC), and voxel-mirrored homotopic connectivity (VMHC) were calculated as the difference between NLE and controls and compared between the OZ and ESZ and to zero. A general linear model was used with age as a covariate with Bonferroni correction for multiple comparisons. Results: Five out of 8 patients with NLE showed decreased correlations from the OZ to the ESZ. Group analysis showed patients with NLE had lower connectivity with the ESZ. Patients with NLE showed higher fALFF and ReHo in the OZ but not the ESZ, and higher DoC in the OZ and ESZ. Our results indicate that patients with NLE show high levels of activity but dysfunctional connections in seizure-related areas. Discussion: rsfMRI analysis showed decreased connectivity directly between seizure-related areas, while FC metric analysis revealed increases in local and global connectivity in seizure-related areas. FC analysis of rsfMRI can detect functional disruption that may expose the pathophysiology underlying NLE.

Effect of Enlarged Perivascular Spaces in Reliable Distinction of Prospective Targeting During Deep Brain Stimulation in Patients With Advanced Parkinson's Disease: A Study of Deterministic and Probabilistic Tractography.

BACKGROUND: Precise electrode position is vital for effective deep brain stimulation in treating motor symptoms in Parkinson's disease (PD). Enlarged perivascular spaces (PVSs) are associated with pathophysiology of neurodegenerative diseases including PD and may affect the microstructure of surrounding brain tissue. OBJECTIVE: To quantify the clinical implications of enlarged PVS on tractography-based stereotactic targeting in patients with advanced PD selected to undergo deep brain stimulation. METHODS: Twenty patients with PD underwent MRI scanning. The PVS areas were visualized and segmented. Based on the size of the PVS areas, the patient group was split into 2 categories of large vs small PVSs. Probabilistic and deterministic tractography methods were applied to a diffusion-weighted data set. Fiber assignment was performed using motor cortex as an initiation seed and the globus pallidus interna and subthalamic nucleus, separately, as inclusion masks. Two exclusion masks used consisted of cerebral peduncles and the PVS mask. The center of gravity of the tract density map was measured and compared between the tracts generated with and without consideration of the PVS mask. RESULTS: The average differences between the center of gravity of the tracts made by excluding PVS and without excluding PVS using deterministic and probabilistic tractography methods were less than 1 mm. Statistical analysis showed nonsignificant differences between deterministic and probabilistic methods and differences between patients with large and small PVSs ( P > .05). CONCLUSION: This study demonstrated that the presence of enlarged PVS is unlikely to affect targeting of basal ganglia nuclei based on tractography.

Association of Brain Age, Lesion Volume, and Functional Outcome in Patients With Stroke.

BACKGROUND AND OBJECTIVES: Functional outcomes after stroke are strongly related to focal injury measures. However, the role of global brain health is less clear. In this study, we examined the impact of brain age, a measure of neurobiological aging derived from whole-brain structural neuroimaging, on poststroke outcomes, with a focus on sensorimotor performance. We hypothesized that more lesion damage would result in older brain age, which would in turn be associated with poorer outcomes. Related, we expected that brain age would mediate the relationship between lesion damage and outcomes. Finally, we hypothesized that structural brain resilience, which we define in the context of stroke as younger brain age given matched lesion damage, would differentiate people with good vs poor outcomes. METHODS: We conducted a cross-sectional observational study using a multisite dataset of 3-dimensional brain structural MRIs and clinical measures from the ENIGMA Stroke Recovery. Brain age was calculated from 77 neuroanatomical features using a ridge regression model trained and validated on 4,314 healthy controls. We performed a 3-step mediation analysis with robust mixed-effects linear regression models to examine relationships between brain age, lesion damage, and stroke outcomes. We used propensity score matching and logistic regression to examine whether brain resilience predicts good vs poor outcomes in patients with matched lesion damage. RESULTS: We examined 963 patients across 38 cohorts. Greater lesion damage was associated with older brain age (ß = 0.21; 95% CI 0.04-0.38, p = 0.015), which in turn was associated with poorer outcomes, both in the sensorimotor domain (ß = -0.28; 95% CI -0.41 to -0.15, p < 0.001) and across multiple domains of function (ß = -0.14; 95% CI -0.22 to -0.06, p < 0.001). Brain age mediated 15% of the impact of lesion damage on sensorimotor performance (95% CI 3%-58%, p = 0.01). Greater brain resilience explained why people have better outcomes, given matched lesion damage (odds ratio 1.04, 95% CI 1.01-1.08, p = 0.004). DISCUSSION: We provide evidence that younger brain age is associated with superior poststroke outcomes and modifies the impact of focal damage. The inclusion of imaging-based assessments of brain age and brain resilience may improve the prediction of poststroke outcomes compared with focal injury measures alone, opening new possibilities for potential therapeutic targets.

Metal Artifact Reduction Around Cervical Spine Implant Using Diffusion Tensor Imaging at 3T: A Phantom Study.

Diffusion MRI continues to play a key role in non-invasively assessing spinal cord integrity and pre-operative injury evaluation. However, post-operative Diffusion Tensor Imaging (DTI) acquisition of a patient with a metal implant results in severe geometric image distortion. A method has been proposed here to alleviate the technical challenges facing the acquisition of DTI in post-operative cases and to evaluate longitudinal therapeutics. The described technique is based on the combination of the reduced Field-Of-View (rFOV) strategy and the phase segmented acquisition scheme (rFOV-PS-EPI) for significantly mitigating metal-induced distortions. A custom-built phantom based on spine model with metal implant was used to collect high-resolution DTI data at 3 Tesla scanner using a home-grown diffusion MRI pulse sequence, rFOV-PS-EPI, single-shot (rFOV-SS-EPI), and the conventional full FOV techniques including SS-EPI, PS-EPI, and the readout-segmented (RS-EPI). This newly developed method provides high-resolution images with significant reduced metal-induced artifacts. In contrast to the other techniques, the rFOV-PS-EPI allows DTI measurement at the level of the metal hardware whereas the current rFOV-SS-EPI is useful when the metal is approximately 20 mm away. The developed approach enables high-resolution DTI in patients with metal implant.

Evaluation of eight registration algorithms applied to the insula and insular gyri.

BACKGROUND AND PURPOSE: Spatial registration is crucial in establishing correspondence between anatomic brain regions for research and clinical purposes. The insular cortex (IC) and gyri (IG) are implicated in various functions and pathologies including epilepsy. Optimizing registration of the insula to a common atlas can improve the accuracy of group-level analyses. Here, we compared six nonlinear, one linear, and one semiautomated registration algorithms (RAs) for registering the IC and IG to the Montreal Neurologic Institute standard space (MNI152). METHODS: 3T images acquired from 20 controls and 20 temporal lobe epilepsy patients with mesial temporal sclerosis underwent automated segmentation of the insula. This was followed by manual segmentation of the entire IC and six individual IGs. Consensus segmentations were created at 75% agreement for IC and IG before undergoing registration to MNI152 space with eight RAs. Dice similarity coefficients (DSCs) were calculated between segmentations after registration and the IC and IG in MNI152 space. Statistical analysis involved the Kruskal-Wallace test with Dunn's test for IC and two-way analysis of variance with Tukey's honest significant difference test for IG. RESULTS: DSCs were significantly different between RAs. Based on multiple pairwise comparisons, we report that certain RAs performed better than others across population groups. Additionally, registration performance differed according to specific IG. CONCLUSION: We compared different methods for registering the IC and IG to MNI152 space. We found differences in performance between RAs, which suggests that algorithm choice is important factor in analyses involving the insula.

Correlations of diffusion tensor imaging and clinical measures with spinal cord cross-sectional area measurements in pediatric spinal cord injury patients.

PURPOSE: The purpose of this work was to employ a semi-automatic method for measuring spinal cord cross-sectional area (SCCSA) and investigate the correlations between diffusion tensor imaging (DTI) metrics and SCCSA for the cervical and thoracic spinal cord for typically developing pediatric subjects and pediatric subject with spinal cord injury. METHODS: Ten typically developing (TD) pediatric subjects and ten pediatric subjects with spinal cord injury (SCI) were imaged using a Siemens Verio 3 T MR scanner to acquire DTI and high-resolution anatomic scans covering the cervical and thoracic spinal cord (C1-T12). SCCSA was measured using a semi-automated edge detection algorithm for the entire spinal cord. DTI metrics were obtained from whole cord axial ROIs at each vertebral level. SCCSA measures were compared to DTI metrics by vertebral level throughout the entire cord, and above and below the injury site. Correlation analysis was performed to compare SCCSA, DTI and clinical measures as determined by the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) examination. RESULTS: In subjects with SCI, FA and SCCSA had a positive correlation (r = 0.81, P < 0.01), while RD and SCCSA had a negative correlation (r = -0.68, P = 0.02) for the full spinal cord. FA and SCCSA were correlated above (r = 0.56, P < 0.01) and below (r = 0.54, P < 0.01) the injury site. TD subjects showed negative correlations between AD and SCCSA (r = -0.73, P = 0.01) and RD and SCCSA (r = -0.79, P < 0.01). CONCLUSION: The ability to quickly and effectively measure SCCSA in subjects with SCI has the potential to allow for a better understanding of the progression of atrophy following a SCI. Correlations between cord cross section and DTI metrics by vertebral level suggest that imaging inferior and superior to lesion may yield useful information for diagnosis and prognosis.

Vascular and neuronal effects of general anesthesia on the brain: An fMRI study.

BACKGROUND AND PURPOSE: A number of functional magnetic resonance imaging (fMRI) studies rely on application of anesthetic agents during scanning that can modulate and complicate interpretation of the measured hemodynamic blood oxygenation level-dependent (BOLD) response. The purpose of the present study was to investigate the effect of general anesthesia on two main components of BOLD signal including neuronal activity and vascular response. METHODS: Breath-holding (BH) fMRI was conducted in wakefulness and under anesthesia states in 9 patients with drug-resistant epilepsy who needed to get scanned under anesthesia during laser interstitial thermal therapy. BOLD and BOLD cerebrovascular reactivity (BOLD-CVR) maps were compared using t-test between two states to assess the effect of anesthesia on neuronal activity and vascular factors (p < .05). RESULTS: Overall, our findings revealed an increase in BOLD-CVR and decrease in BOLD response under anesthesia in several brain regions. The results proposed that the modulatory mechanism of anesthetics on neuronal and vascular components of BOLD signal may work in different ways. CONCLUSION: This experiment for the first human study showed that anesthesia may play an important role in dissociation between neuronal and vascular responses contributed to hemodynamic BOLD signal using BH fMRI imaging that may assist the implication of general anesthesia and interpretation of outcomes in clinical setting.

Deep learning-based multimodality classification of chronic mild traumatic brain injury using resting-state functional MRI and PET imaging.

Mild traumatic brain injury (mTBI) is a public health concern. The present study aimed to develop an automatic classifier to distinguish between patients with chronic mTBI (n = 83) and healthy controls (HCs) (n = 40). Resting-state functional MRI (rs-fMRI) and positron emission tomography (PET) imaging were acquired from the subjects. We proposed a novel deep-learning-based framework, including an autoencoder (AE), to extract high-level latent and rectified linear unit (ReLU) and sigmoid activation functions. Single and multimodality algorithms integrating multiple rs-fMRI metrics and PET data were developed. We hypothesized that combining different imaging modalities provides complementary information and improves classification performance. Additionally, a novel data interpretation approach was utilized to identify top-performing features learned by the AEs. Our method delivered a classification accuracy within the range of 79-91.67% for single neuroimaging modalities. However, the performance of classification improved to 95.83%, thereby employing the multimodality model. The models have identified several brain regions located in the default mode network, sensorimotor network, visual cortex, cerebellum, and limbic system as the most discriminative features. We suggest that this approach could be extended to the objective biomarkers predicting mTBI in clinical settings.

Amplitude synchronization of spontaneous activity of medial and lateral temporal gyri reveals altered thalamic connectivity in patients with temporal lobe epilepsy.

In this study, we examined whether amplitude synchronization of medial (MTL) and lateral (LTL) temporal lobes can detect unique alterations in patients with MTL epilepsy (mTLE) with mesial temporal sclerosis (MTS). This was a retrospective study of preoperative resting-state fMRI (rsfMRI) data from 31 patients with mTLE with MTS (age 23-69) and 16 controls (age 21-35). fMRI data were preprocessed based on a multistep preprocessing pipeline and registered to a standard space. Using each subject's T1-weighted scan, the MTL and LTL were automatically segmented, manually revised and then fit to a standard space using a symmetric normalization registration algorithm. Dual regression analysis was applied on preprocessed rsfMRI data to detect amplitude synchronization of medial and lateral temporal segments with the rest of the brain. We calculated the overlapped volume ratio of synchronized voxels within specific target regions including the thalamus (total and bilateral). A general linear model was used with Bonferroni correction for covariates of epilepsy duration and age of patient at scan to statistically compare synchronization in patients with mTLE with MTS and controls, as well as with respect to whether patients remained seizure-free (SF) or not (NSF) after receiving epilepsy surgery. We found increased ipsilateral positive connectivity between the LTLs and the thalamus and contralateral negative connectivity between the MTLs and the thalamus in patients with mTLE with MTS compared to controls. We also found increased asymmetry of functional connectivity between temporal lobe subregions and the thalamus in patients with mTLE with MTS, with increased positive connectivity between the LTL and the lesional-side thalamus as well as increased negative connectivity between the MTL and the nonlesional-side thalamus. This asymmetry was also seen in NSF patients but was not seen in SF patients and controls. Amplitude synchronization was an effective method to detect functional connectivity alterations in patients with mTLE with MTS. Patients with mTLE with MTS overall showed increased temporal-thalamic connectivity. There was increased functional involvement of the thalamus in MTS, underscoring its role in seizure spread. Increased functional thalamic asymmetry patterns in NSF patients may have a potential role in prognosticating patient response to surgery. Elucidating regions with altered functional connectivity to temporal regions can improve understanding of the involvement of different regions in the disease to potentially target for intervention or use for prognosis for surgery. Future studies are needed to examine the effectiveness of using patient-specific abnormalities in patterns to predict surgical outcome.

Case report: The promising application of dynamic functional connectivity analysis on an individual with failed back surgery syndrome.

Failed back surgery syndrome (FBSS), a chronic neuropathic pain condition, is a common indication for spinal cord stimulation (SCS). However, the mechanisms of SCS, especially its effects on supraspinal/brain functional connectivity, are still not fully understood. Resting state functional magnetic resonance imaging (rsfMRI) studies have shown characteristics in patients with chronic low back pain (cLBP). In this case study, we performed rsfMRI scanning (3.0 T) on an FBSS patient, who presented with chronic low back and leg pain following her previous lumbar microdiscectomy and had undergone permanent SCS. Appropriate MRI safety measures were undertaken to scan this subject. Seed-based functional connectivity (FC) was performed on the rsfMRI data acquired from the FBSS subject, and then compared to a group of 17 healthy controls. Seeds were identified by an atlas of resting state networks (RSNs), which is composed of 32 regions grouped into 8 networks. Sliding-window method and k-means clustering were used in dynamic FC analysis, which resulted in 4 brain states for each group. Our results demonstrated the safety and feasibility of 3T MRI scanning in a patient with implanted SCS system. Compared to the brain states of healthy controls, the FBSS subject presented very different FC patterns in less frequent brain states. The mean dwell time of brain states showed distinct distributions: the FBSS subject seemed to prefer a single state over the others. Although future studies with large sample sizes are needed to make statistical conclusions, our findings demonstrated the promising application of dynamic FC to provide more granularity with FC changes associated with different brain states in chronic pain.