The Impact of MRI-Based Advanced Neuroimaging on Neurooncologists' Clinical Decision-Making in Patients With Posttreatment High-Grade Glioma: A Prospective Survey-Based Study.

BACKGROUND. Advanced MRI-based neuroimaging techniques, such as perfusion and spectroscopy, have been increasingly incorporated into routine follow-up protocols in patients treated for high-grade glioma (HGG), to help differentiate tumor progression from treatment effect. However, these techniques' influence on clinical management remains poorly understood. OBJECTIVE. The purpose of this article was to evaluate the impact of MRI-based advanced neuroimaging on clinical decision-making in patients with HGG after treatment. METHODS. This prospective study, performed at a comprehensive cancer center from March 1, 2017, to October 31, 2020, included adult patients treated by chemoradiation for WHO grade 4 diffuse glioma who underwent MRI-based advanced neuroimaging (comprising multiple perfusion imaging sequences and spectroscopy) to further evaluate findings on conventional MRI equivocal for tumor progression versus treatment effect. The ordering neurooncologists completed surveys before and after each advanced neuroimaging session. The percent of episodes of care with a change between the intended and actual management plan on the surveys conducted before and after advanced neuroimaging, respectively, was computed and compared with a published percent using the Wald test for independent samples proportions. RESULTS. The study included 63 patients (mean age, 54.6 ± 12.9 [SD] years; 36 women, 27 men) who underwent 70 advanced neuroimaging sessions. Ordering neurooncologists' intended and actual management plans on the surveys completed before and after advanced neuroimaging, respectively, differed in 44% (31/70; 95% CI: 33-56%) of episodes, which differed from the published frequency of 8.5% (5/59) (p < .001). These management plan changes included selection of a different plan for six of eight episodes with an intended plan to enroll patients in a clinical trial, 12 of 19 episodes with an intended plan to change chemotherapeutic agents, four of eight episodes with an intended plan of surgical intervention, and one of two episodes with an intended plan of reirradiation. The ordering neurooncologists found advanced neuroimaging to be helpful in 93% (65/70; 95% CI: 87-99%) of episodes. CONCLUSION. Neurooncologists' management plans changed in a substantial fraction of adult patients with HGG who underwent advanced neuroimaging to further evaluate conventional MRI findings equivocal for tumor progression versus treatment effect. CLINICAL IMPACT. The findings support incorporation of advanced neuroimaging into HGG posttreatment monitoring protocols.

Cerebrovascular Reactivity Mapping Using Resting-State Functional MRI in Patients With Gliomas.

BACKGROUND: Recently, a data-driven regression analysis method was developed to utilize the resting-state (rs) blood oxygenation level-dependent signal for cerebrovascular reactivity (CVR) mapping (rs-CVR), which was previously optimized by comparing with the CO2 inhalation-based method in health subjects and patients with neurovascular diseases. PURPOSE: To investigate the agreement of rs-CVR and the CVR mapping with breath-hold MRI (bh-CVR) in patients with gliomas. STUDY TYPE: Retrospective. POPULATION: Twenty-five patients (12 males, 13 females; mean age ± SD, 48 ± 13 years) with gliomas. FIELD STRENGTH/SEQUENCE: Dynamic T2*-weighted gradient-echo echo-planar imaging during a breath-hold paradigm and during the rs on a 3-T scanner. ASSESSMENT: rs-CVR with various frequency ranges and resting-state fluctuation amplitude (RSFA) were assessed. The agreement between each rs-based CVR measurement and bh-CVR was determined by voxel-wise correlation and Dice coefficient in the whole brain, gray matter, and the lesion region of interest (ROI). STATISTICAL TESTS: Voxel-wise Pearson correlation, Dice coefficient, Fisher Z-transformation, repeated-measure analysis of variance and post hoc test with Bonferroni correction, and nonparametric repeated-measure Friedman test and post hoc test with Bonferroni correction were used. Significance was set at P < 0.05. RESULTS: Compared with bh-CVR, the highest correlations were found at the frequency bands of 0.04-0.08 Hz and 0.02-0.04 Hz for rs-CVR in both whole brain and the lesion ROI. RSFA had significantly lower correlations than did rs-CVR of 0.02-0.04 Hz and a wider frequency range (0-0.1164 Hz). Significantly higher correlations and Dice coefficient were found in normal tissues than in the lesion ROI for all three methods. DATA CONCLUSION: The optimal frequency ranges for rs-CVR are determined by comparing with bh-CVR in patients with gliomas. The rs-CVR method outperformed the RSFA. Significantly higher correlation and Dice coefficient between rs- and bh-CVR were found in normal tissue than in the lesion. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 2.

Synthetic generation of DSC-MRI-derived relative CBV maps from DCE MRI of brain tumors.

PURPOSE: Perfusion MRI with gadolinium-based contrast agents is useful for diagnosis and treatment response evaluation of brain tumors. Dynamic susceptibility contrast (DSC) MRI and dynamic contrast enhanced (DCE) MRI are two gadolinium-based contrast agent perfusion imaging techniques that provide complementary information about the tumor vasculature. However, each requires a separate administration of a gadolinium-based contrast agent. The purpose of this retrospective study was to determine the feasibility of synthesizing relative cerebral blood volume (rCBV) maps, as computed from DSC MRI, from DCE MRI of brain tumors. METHODS: One hundred nine brain-tumor patients underwent both DCE and DSC MRI. Relative CBV maps were computed from the DSC MRI, and blood plasma volume fraction maps were computed from the DCE MRIs. Conditional generative adversarial networks were developed to synthesize rCBV maps from the DCE MRIs. Tumor-to-white matter ratios were calculated from real rCBV, synthetic rCBV, and plasma volume fraction maps and compared using correlation analysis. Real and synthetic rCBV in white and gray matter regions were also compared. RESULTS: Pearson correlation analysis showed that both the tumor rCBV and tumor-to-white matter ratios in the synthetic and real rCBV maps were strongly correlated (ρ = 0.87, P < .05 and ρ = 0.86, P < .05, respectively). Tumor plasma volume fraction and real rCBV were not strongly correlated (ρ = 0.47). Bland-Altman analysis showed a mean difference between the synthetic and real rCBV tumor-to-white matter ratios of 0.20 with a 95% confidence interval of ±0.47. CONCLUSION: Realistic rCBV maps can be synthesized from DCE MRI and contain quantitative information, enabling robust brain-tumor perfusion imaging of DSC and DCE parameters with a single gadolinium-based contrast agent administration.

Effect of brain normalization methods on the construction of functional connectomes from resting-state functional MRI in patients with gliomas.

PURPOSE: Spatial normalization is an essential step in resting-state functional MRI connectomic analysis with atlas-based parcellation, but brain lesions can confound it. Cost-function masking (CFM) is a popular compensation approach, but may not benefit modern normalization methods. This study compared three normalization methods with and without CFM and determined their impact on connectomic measures in patients with glioma. METHODS: Fifty patients with glioma were included. T1 -weighted images were normalized using three different methods in SPM12, with and without CFM, which were then overlaid on the ICBM152 template and scored by two neuroradiologists. The Dice coefficient of gray-matter correspondence was also calculated. Normalized resting-state functional MRI data were parcellated using the AAL90 atlas to construct an individual connectivity matrix and calculate connectomic measures. The R2 among the different normalization methods was calculated for the connectivity matrices and connectomic measures. RESULTS: The older method (Original) performed significantly worse than the modern methods (Default and DARTEL; P < .005 in observer ranking). The use of CFM did not significantly improve the normalization results. The Original method had lower correlation with the Default and DARTEL methods (R2 = 0.71-0.74) than Default with DARTEL (R2 = 0.96) in the connectivity matrix. The clustering coefficient appears to be the most, and modularity the least, sensitive connectomic measures to normalization performance. CONCLUSION: The spatial normalization method can have an impact on resting-state functional MRI connectome and connectomic measures derived using atlas-based brain parcellation. In patients with glioma, this study demonstrated that Default and DARTEL performed better than the Original method, and that CFM made no significant difference.

(TS)2WM: Tumor Segmentation and Tract Statistics for Assessing White Matter Integrity with Applications to Glioblastoma Patients.

Glioblastoma (GBM) brain tumor is the most aggressive white matter (WM) invasive cerebral primary neoplasm. Due to its inherently heterogeneous appearance and shape, previous studies pursued either the segmentation precision of the tumors or qualitative analysis of the impact of brain tumors on WM integrity with manual delineation of tumors. This paper aims to develop a comprehensive analytical pipeline, called (TS)2WM, to integrate both the superior performance of brain tumor segmentation and the impact of GBM tumors on the WM integrity via tumor segmentation and tract statistics using the diffusion tensor imaging (DTI) technique. The (TS)2WM consists of three components: (i) A dilated densely connected convolutional network (D2C2N) for automatically segment GBM tumors. (ii) A modified structural connectome processing pipeline to characterize the connectivity pattern of WM bundles. (iii) A multivariate analysis to delineate the local and global associations between different DTI-related measurements and clinical variables on both brain tumors and language-related regions of interest. Among those, the proposed D2C2N model achieves competitive tumor segmentation accuracy compared with many state-of-the-art tumor segmentation methods. Significant differences in various DTI-related measurements at the streamline, weighted network, and binary network levels (e.g., diffusion properties along major fiber bundles) were found in tumor-related, language-related, and hand motor-related brain regions in 62 GBM patients as compared to healthy subjects from the Human Connectome Project.

Presurgical resting-state functional MRI language mapping with seed selection guided by regional homogeneity.

PURPOSE: Resting-state functional MRI (rs-FMRI) has shown potential for presurgical mapping of eloquent cortex when a patient's performance on task-based FMRI is compromised. The seed-based analysis is a practical approach for detecting rs-FMRI functional networks; however, seed localization remains challenging for presurgical language mapping. Therefore, we proposed a data-driven approach to guide seed localization for presurgical rs-FMRI language mapping. METHODS: Twenty-six patients with brain tumors located in left perisylvian regions had undergone task-based FMRI and rs-FMRI before tumor resection. For the seed-based rs-FMRI language mapping, a seeding approach that integrates regional homogeneity and meta-analysis maps (RH+MA) was proposed to guide the seed localization. Canonical and task-based seeding approaches were used for comparison. The performance of the 3 seeding approaches was evaluated by calculating the Dice coefficients between each rs-FMRI language mapping result and the result from task-based FMRI. RESULTS: With the RH+MA approach, selecting among the top 6 seed candidates resulted in the highest Dice coefficient for 81% of patients (21 of 26) and the top 9 seed candidates for 92% of patients (24 of 26). The RH+MA approach yielded rs-FMRI language mapping results that were in greater agreement with the results of task-based FMRI, with significantly higher Dice coefficients (P < .05) than that of canonical and task-based approaches within putative language regions. CONCLUSION: The proposed RH+MA approach outperformed the canonical and task-based seed localization for rs-FMRI language mapping. The results suggest that RH+MA is a robust and feasible method for seed-based functional connectivity mapping in clinical practice.

Loneliness and depression dissociated on parietal-centered networks in cognitive and resting states.

BACKGROUND: Perceived loneliness, an increasingly prevalent social issue, is closely associated with major depressive disorder (MDD). However, the neural mechanisms previously implicated in key cognitive and affective processes in loneliness and MDD still remain unclear. Such understanding is critical for delineating the psychobiological basis of the relationship between loneliness and MDD. METHODS: We isolated the unique and interactive cognitive and neural substrates of loneliness and MDD among 27 MDD patients (mean age = 51.85 years, 20 females), and 25 matched healthy controls (HCs; mean age = 48.72 years, 19 females). We assessed participants' behavioral performance and neural regional and network functions on a Stroop color-word task, and their resting-state neural connectivity. RESULTS: Behaviorally, we found greater incongruence-related accuracy cost in MDD patients, but reduced incongruence effect on reaction time in lonelier individuals. When performing the Stroop task, loneliness positively predicted prefrontal-anterior cingulate-parietal connectivity across all participants, whereas MDD patients showed a decrease in connectivity compared to controls. Furthermore, loneliness negatively predicted parietal and cerebellar activities in MDD patients, but positively predicted the same activities in HCs. During resting state, MDD patients showed reduced parietal-anterior cingulate connectivity, which again positively correlated with loneliness in this group. CONCLUSIONS: We speculate the distinct neurocognitive profile of loneliness might indicate increase in both bottom-up attention and top-down executive control functions. However, the upregulated cognitive control processes in lonely individuals may eventually become exhausted, which may in turn predispose to MDD onset.

Accuracy of Presurgical Functional MR Imaging for Language Mapping of Brain Tumors: A Systematic Review and Meta-Analysis.

Purpose To compare functional magnetic resonance (MR) imaging for language mapping (hereafter, language functional MR imaging) with direct cortical stimulation (DCS) in patients with brain tumors and to assess factors associated with its accuracy. Materials and Methods PubMed/MEDLINE and related databases were searched for research articles published between January 2000 and September 2016. Findings were pooled by using bivariate random-effects and hierarchic summary receiver operating characteristic curve models. Meta-regression and subgroup analyses were performed to evaluate whether publication year, functional MR imaging paradigm, magnetic field strength, statistical threshold, and analysis software affected classification accuracy. Results Ten articles with a total of 214 patients were included in the analysis. On a per-patient basis, the pooled sensitivity and specificity of functional MR imaging was 44% (95% confidence interval [CI]: 14%, 78%) and 80% (95% CI: 54%, 93%), respectively. On a per-tag basis (ie, each DCS stimulation site or "tag" was considered a separate data point across all patients), the pooled sensitivity and specificity were 67% (95% CI: 51%, 80%) and 55% (95% CI: 25%, 82%), respectively. The per-tag analysis showed significantly higher sensitivity for studies with shorter functional MR imaging session times (P = .03) and relaxed statistical threshold (P = .05). Significantly higher specificity was found when expressive language task (P = .02), longer functional MR imaging session times (P < .01), visual presentation of stimuli (P = .04), and stringent statistical threshold (P = .01) were used. Conclusion Results of this study showed moderate accuracy of language functional MR imaging when compared with intraoperative DCS, and the included studies displayed significant methodologic heterogeneity. © RSNA, 2017 Online supplemental material is available for this article.

The relationships between brain structural changes and perceived loneliness in older adults suffering from late-life depression.

OBJECTIVE: Late-life depression is a significant health risk factor for older adults, part of which is perceived loneliness. In this voxel-based morphometry study, we examined the relationships between perceived loneliness and depression recurrence. METHODS: Fifty-two older adults were recruited, and they were split into 3 groups: single episode, multiple episodes, or normal control groups, according to their clinical histories. RESULTS: This result suggests the level of functioning regarding the reward system may be negatively related to the number of depressive episodes. Taken together, the findings of this study offer important insight into the neural underpinnings of the course and chronicity of late-life depression.

Arterial spin-labeling perfusion imaging of childhood encephalitis: correlation with seizure and clinical outcome.

PURPOSE: In childhood encephalitis, perfusion abnormalities have been infrequently reported to associate with clinical status. We investigated whether perfusion abnormalities correlated with seizure and clinical outcome in encephalitis. METHODS: We retrospectively analyzed the MR studies of 77 pediatric patients with encephalitis. Pseudo-continuous arterial spin-labeling (ASL) imaging was performed on a 3-T scanner. The patients were divided into five groups according to ASL perfusion imaging pattern: normal perfusion (NP), focal hypoperfusion (Lf), extreme global hypoperfusion (LE), focal hyperperfusion (Hf), and extreme global hyperperfusion (HE). Clinical outcome at 3 weeks was dichotomized to unfavorable or favorable outcome according to the Glasgow outcome scale. Multivariate logistic regression was conducted to predict unfavorable outcome and presence of seizure separately, based on explanatory variables including age, sex, and ASL pattern. RESULTS: Twenty-seven (35%) patients were designated as in group Hf, five (7%) in group Lf, 11 (14%) in group LE, none in group HE, and 34 (44%) in group NP. Multivariate logistic regression analysis showed that ASL pattern was significantly associated with unfavorable outcome (P = 0.005) and with presence of seizure (P = 0.005). For ASL pattern, group LE was 17.31 times as likely to have an unfavorable outcome as group NP (odds ratio confidence interval [CI] 3.084, 97.105; P = 0.001). Group Hf was 6.383 times as likely to have seizure as group NP (CI 1.765, 23.083; P = 0.005). CONCLUSIONS: In childhood encephalitis, patients with extreme global hypoperfusion had poor neurological outcome and those with focal hypoperfusion were more likely to have seizure.

Arterial spin-labeling perfusion imaging of children with subdural hemorrhage: Perfusion abnormalities in abusive head trauma.

BACKGROUND AND PURPOSE: Perfusion abnormalities have not been well described in children with subdural hemorrhage (SDH). We investigated whether patients with abusive head trauma (AHT+) had more perfusion abnormalities than those without (AHT-). MATERIALS AND METHODS: We reviewed the perfusion MR studies of 12 infants with SDH and 21 controls. The perfusion images were obtained using a pseudo-continuous arterial spin-labeling sequence with volumetric fast spin-echo readout. An MR perfusion scoring system (0-6 points) was devised to facilitate appraisal of the extent of abnormalities. An asymmetry index (AI) was calculated for each region of perfusion abnormality. Comparison of perfusion scores across the AHT+, AHT-, and control groups was performed. The AIs of the hypoperfused lesions and hyperperfused lesions in patients were separately compared with those of the controls. The neurological outcomes of the patients were associated with imaging abnormalities. RESULTS: Perfusion abnormalities were found in five (83%) of six AHT+ patients and in one (17%) of six AHT- patients. The AHT+ group recorded a significantly higher perfusion score than did both the AHT- group and the controls. Four patients with hypoperfused lesions exhibited significantly lower AI (P=.002) than did the controls, and three patients with hyperperfused lesions had significantly higher AI (P=.006) than did the controls. Of the four patients with hypoperfused lesions, two expired and one experienced hemiparesis. CONCLUSIONS: Patients with AHT have higher perfusion abnormality scores than patients with other causes of SDH and controls. Moreover, hypoperfusion may suggest a poor clinical outcome.

Neural correlates of motor recovery after robot-assisted stroke rehabilitation: a case series study.

Robot-assisted bilateral arm therapy (RBAT) has shown promising results in stroke rehabilitation; however, connectivity mapping of the sensorimotor networks after RBAT remains unclear. We used fMRI before and after RBAT and a dose-matched control intervention (DMCI) to explore the connectivity changes in 6 subacute stroke patients. Sensorimotor functions improved in the RBAT and DMCI groups after treatment. Enhanced activation changes were observed in bilateral primary motor cortex (M1) and bilateral supplementary motor area (SMA) after RBAT. Dynamic causal model analysis revealed that interhemispheric connections were enhanced in RBAT patients. These preliminary findings suggest that intracortical and intercortical coupling might underlie poststroke RBAT.

Arterial spin-labeling perfusion imaging of childhood meningitis: a case series.

INTRODUCTION: Conventional magnetic resonance imaging (MRI), which is mainly used to detect complications, is ineffective in determining the neurological status of patients with meningitis. Hemodynamic change in the brain may be more indicative of the neurological status but few imaging studies have verified this. Arterial spin-labeling (ASL) perfusion, a noninvasive MR method requiring no contrast agent injection, can be used to measure cerebral blood flow (CBF). CASE REPORTS: We describe three pediatric patients with meningitis, who all showed regions of increased CBF on perfusion imaging. One patient, presenting with headache and conscious disturbance, had CBF changes in the frontal, temporal, and occipital regions. The other two patients, presenting with hallucinations, memory deficits, and seizures, had CBF changes in the frontal and temporal regions. CONCLUSION: ASL perfusion imaging may be helpful in assessing patients with meningitis, demonstrating CBF changes more strongly correlating with the neurological status, and detecting active brain abnormalities.

Assessment of vessel permeability by combining dynamic contrast-enhanced and arterial spin labeling MRI.

The forward volumetric transfer constant (K(trans)), a physiological parameter extracted from dynamic contrast-enhanced (DCE) MRI, is weighted by vessel permeability and tissue blood flow. The permeability × surface area product per unit mass of tissue (PS) in brain tumors was estimated in this study by combining the blood flow obtained through pseudo-continuous arterial spin labeling (PCASL) and K(trans) obtained through DCE MRI. An analytical analysis and a numerical simulation were conducted to understand how errors in the flow and K(trans) estimates would propagate to the resulting PS. Fourteen pediatric patients with brain tumors were scanned on a clinical 3-T MRI scanner. PCASL perfusion imaging was performed using a three-dimensional (3D) fast-spin-echo readout module to determine blood flow. DCE imaging was performed using a 3D spoiled gradient-echo sequence, and the K(trans) map was obtained with the extended Tofts model. The numerical analysis demonstrated that the uncertainty of PS was predominantly dependent on that of K(trans) and was relatively insensitive to the flow. The average PS values of the whole tumors ranged from 0.006 to 0.217 min(-1), with a mean of 0.050 min(-1) among the patients. The mean K(trans) value was 18% lower than the PS value, with a maximum discrepancy of 25%. When the parametric maps were compared on a voxel-by-voxel basis, the discrepancies between PS and K(trans) appeared to be heterogeneous within the tumors. The PS values could be more than two-fold higher than the K(trans) values for voxels with high K(trans) levels. This study proposes a method that is easy to implement in clinical practice and has the potential to improve the quantification of the microvascular properties of brain tumors.

Bladder dysfunction induced by cerebral hypoperfusion after bilateral common carotid artery occlusion in rats.

AIMS: The role of forebrain in controlling micturition has been studied extensively using rat model with ischemic injury; however, the influence of cerebral hypoperfusion on voiding function remains unclear. The study was conducted to evaluate the bladder dysfunction and the temporal expression of bladder nerve growth factor (NGF) after cerebral hypoperfusion induced by bilateral common carotid artery occlusion (BCCAO). MATERIALS AND METHODS: Forty female rats were subjected to either BCCAO or sham operation. Cerebral T2-weighted magnetic resonance images (MRI) and diffusion and perfusion change were studied to characterize the extent of the ischemic injury in the cortex and hippocampus. On 1, 7, and 28 days after BCCAO, the bladder dysfunction was assessed by cystometric studies, and the expressions of NGF in bladder muscle and urothelium were measured by immunohistochemistry and real-time polymerase chain reaction. RESULTS: In the MRI study, cerebral blood flow in the cortex and hippocampus was significantly decreased from 1 day and subsequently returned to sham-operated level at 28 days after BCCAO. Compared with the sham-operated group, significant reduction in voided volume and intercontraction interval was found from 1 to 28 days after cerebral hypoperfusion. The NGF immunoreactivity and mRNA in the bladder muscle and urothelium were transiently increased at 1 day, and declined significantly at 28 days after BCCAO. CONCLUSIONS: Our results indicate that bladder dysfunction may be caused by cerebral hypoperfusion and is less likely related to bladder NGF expression.

Comparison of three-dimensional pseudo-continuous arterial spin labeling perfusion imaging with gradient-echo and spin-echo dynamic susceptibility contrast MRI.

PURPOSE: To compare the relative cerebral blood flow (CBF) obtained by pseudo-continuous arterial spin labeling sequence incorporated with volumetric fast spin-echo readout (3D-PCASL) with those by gradient-echo (GE) and spin-echo (SE) dynamic susceptibility contrast (DSC) MRI. MATERIALS AND METHODS: Thirty patients with various neurological diseases participated in this study. In addition to 3D-PCASL, 15 patients received GE-DSC and the others received SE-DSC imaging on a 3 Tesla scanner. A cortical gray matter (GM) to white matter (WM) and a thalamus (TM) to WM CBF ratio were determined from each perfusion scan. In addition, histograms of relative CBF distributions were obtained from each method for comparison. RESULTS: Significant correlations of CBF ratios were found between 3D-PCASL and the two DSC methods (P < 0.05). The 3D-PCASL resulted in GM/WM CBF ratios similar to SE-DSC but significantly smaller than GE-DSC (P = 2.3 × 10(-7) ). TM/WM CBF ratio obtained by 3D-PCASL was significantly smaller than those by GE- and SE-DSC (P = 4.1 × 10(-7) and 1.2 × 10(-6) , respectively). The histogram of relative CBF maps obtained from SE-DSC, after applied spatial smoothing, agreed well with that from 3D-PCASL. CONCLUSION: This study suggested that perfusion images obtained from 3D-PCASL exhibited significant correlations with DSC-MRI, with greater microvascular weighting like SE-DSC.

Value of enhancement technique in 3D-T2-STIR images of the brachial plexus.

OBJECTIVE: Imaging the brachial plexus is a challenge because of its complicated structure. The purpose of this study is to improve the diagnostic ability for brachial plexus via 3-dimensional T2-weighted short inversion time inversion recovery (3D-T2-STIR) technique with contrast agent administration. METHODS: Thirty patients with brachial plexopathies were recruited. The STIR sequences without and with contrast agent administration were performed on each subject. The grade of the diagnostic ability and the contrast ratio were assessed. RESULTS: After contrast agent administration, signals of the adjacent vessels were suppressed because of reduced T1 relaxation time similar to that of fat tissues. The outlines of nerves would be prominent with respect to surrounding tissues. Both diagnostic ability and contrast ratio were improved on 3D-T2-STIR with contrast agent administration. CONCLUSIONS: The maximum-intensity projection image of 3D-T2-STIR technique with contrast agent was superior to that without. It might be a better way to evaluate anatomies and pathologies of the brachial plexus. These advantages would improve the understanding and neurosurgical planning for brachial plexopathies in the future.

Comparative analysis of brain language templates with primary language areas detected from presurgical fMRI of brain tumor patients.

INTRODUCTION: Functional brain templates are often used in the analysis of clinical functional MRI (fMRI) studies. However, these templates are mostly built based on anatomy or fMRI of healthy subjects, which have not been fully vetted in clinical cohorts. Our aim was to evaluate language templates by comparing with primary language areas (PLAs) detected from presurgical fMRI of brain tumor patients. METHODS: Four language templates (A-D) based on anatomy, task-based fMRI, resting-state fMRI, and meta-analysis, respectively, were compared with PLAs detected by fMRI with word generation and sentence completion paradigms. For each template, the fraction of PLA activations enclosed by the template (positive inclusion fraction, [PIF]), the fraction of activations within the template but that did not belong to PLAs (false inclusion fraction, [FIF]), and their Dice similarity coefficient (DSC) with PLA activations were calculated. RESULTS: For anterior PLAs, Template A had the greatest PIF (median, 0.95), whereas Template D had both the lowest FIF (median, 0.074), and the highest DSC (median, 0.30), which were all significant compared to other templates. For posterior PLAs, Templates B and D had similar PIF (median, 0.91 and 0.90, respectively) and DSC (both medians, 0.059), which were all significantly higher than that of Template C. Templates B and C had significantly lower FIF (median, 0.061 and 0.054, respectively) compared to Template D. CONCLUSION: This study demonstrated significant differences between language templates in their inclusiveness of and spatial agreement with the PLAs detected in the presurgical fMRI of the patient cohort. These findings may help guide the selection of language templates tailored to their applications in clinical fMRI studies.

Predicting suicidality in late-life depression by 3D convolutional neural network and cross-sample entropy analysis of resting-state fMRI.

BACKGROUND: Predicting suicide is a pressing issue among older adults; however, predicting its risk is difficult. Capitalizing on the recent development of machine learning, considerable progress has been made in predicting complex behavior such as suicide. As depression remained the strongest risk for suicide, we aimed to apply deep learning algorithms to identify suicidality in a group with late-life depression (LLD). METHODS: We enrolled 83 patients with LLD, 35 of which were non-suicidal and 48 were suicidal, including 26 with only suicidal ideation and 22 with past suicide attempts, for resting-state functional magnetic resonance imaging (MRI). Cross-sample entropy (CSE) analysis was conducted to examine the complexity of MRI signals among brain regions. Three-dimensional (3D) convolutional neural networks (CNNs) were used, and the classification accuracy in each brain region was averaged to predict suicidality after sixfold cross-validation. RESULTS: We found brain regions with a mean accuracy above 75% to predict suicidality located mostly in default mode, fronto-parietal, and cingulo-opercular resting-state networks. The models with right amygdala and left caudate provided the most reliable accuracy in all cross-validation folds, indicating their neurobiological importance in late-life suicide. CONCLUSION: Combining CSE analysis and the 3D CNN, several brain regions were found to be associated with suicidality.