Evaluating metabolites in patients with major depressive disorder who received mindfulness-based cognitive therapy and healthy controls using short echo MRSI at 7 Tesla.

ObjectivesOur aim was to evaluate differences in metabolite levels between unmedicated patients with major depressive disorder (MDD) and healthy controls, to assess changes in metabolites in patients after they completed an 8-week course of mindfulness-based cognitive therapy (MBCT), and to exam the correlation between metabolites and depression severity.Materials and methodsSixteen patients with MDD and ten age- and gender-matched healthy controls were studied using 3D short echo-time (20 ms) magnetic resonance spectroscopic imaging (MRSI) at 7 Tesla. Relative metabolite ratios were estimated in five regions of interest corresponding to insula, anterior cingulate cortex (ACC), caudate, putamen, and thalamus.ResultsIn all cases, MBCT reduced severity of depression. The ratio of total choline-containing compounds/total creatine (tCr) in the right caudate was significantly increased compared to that in healthy controls, while ratios of N-acetyl aspartate (NAA)/tCr in the left ACC, myo-inositol/tCr in the right insula, and glutathione/tCr in the left putamen were significantly decreased. At baseline, the severity of depression was negatively correlated with my-inositol/tCr in the left insula and putamen. The improvement in depression severity was significantly associated with changes in NAA/tCr in the left ACC.ConclusionsThis study has successfully evaluated regional differences in metabolites for patients with MDD who received MBCT treatment and in controls using 7 Tesla MRSI

T2 FLAIR hyperintensity volume Is associated with cognitive function and quality of life in clinically stable patients with lower grade gliomas

Survival outcomes for patients with lower grade gliomas (LrGG) continue to improve. However, damage caused both by tumor growth and by the consequences of treatment often leads to significantly impaired cognitive function and quality of life (QoL). While neuropsychological testing is not routine, serial clinical MRIs are standard of care for patients with LrGG. Thus, having a greater understanding of MRI indicators of cognitive and QoL impairment risk could be beneficial to patients and clinicians. In this work we sought to test the hypothesis that in clinically stable LrGG patients, T2 FLAIR hyperintensity volumes at the time of cognitive assessment are associated with impairments of cognitive function and QoL and could be used to help identify patients for cognitive and QoL assessments and interventions. We performed anatomical MR imaging, cognitive testing and QoL assessments cross-sectionally in 30 clinically stable grade 2 and 3 glioma patients with subjective cognitive concerns who were 6 or more months post-treatment. Larger post-surgical T2 FLAIR volume at testing was significantly associated with lower cognitive performance, while pre-surgical tumor volume was not. Older patients had lower cognitive performance than younger patients, even after accounting for normal age-related declines in performance. Patients with Astrocytoma, IDH mutant LrGGs were more likely to show lower cognitive performance than patients with Oligodendroglioma, IDH mutant 1p19q co-deleted LrGGs. Previous treatment with combined radiation and chemotherapy was associated with poorer self-reported QoL, including self-reported cognitive function. This study demonstrates the importance of appreciating that LrGG patients may experience impairments in cognitive function and QoL over their disease course, including during periods of otherwise sustained clinical stability. Imaging factors can be helpful in identifying vulnerable patients who would benefit from cognitive assessment and rehabilitation

Automatic Relevance Determination for Identifying Thalamic Regions Implicated in Schizophrenia

There have been many theories about and computational models of the schizophrenic disease state. Brain imaging techniques have suggested that abnormalities of the thalamus may contribute to the pathophysiology of schizophrenia. Several studies have found the thalamus to be altered in schizophrenia, and the thalamus has connections with other brain structures implicated in the disorder. This paper describes an experiment examining thalamic levels of the metabolite N-acetylaspartate (NAA), taken from schizophrenics and controls using in vivo proton magnetic resonance spectroscopic imaging. Automatic relevance determination was performed on neural networks trained on this data, identifying NAA group differences in the pulvinar and mediodorsal nucleus, underscoring the importance of examining thalamic subregions in schizophrenia.</p

Automatic Relevance Determination for Identifying Thalamic Regions Implicated in Schizophrenia

There have been many theories about and computational models of the schizophrenic disease state. Brain imaging techniques have suggested that abnormalities of the thalamus may contribute to the pathophysiology of schizophrenia. Several studies have found the thalamus to be altered in schizophrenia, and the thalamus has connections with other brain structures implicated in the disorder. This paper describes an experiment examining thalamic levels of the metabolite N-acetylaspartate (NAA), taken from schizophrenics and controls using in vivo proton magnetic resonance spectroscopic imaging. Automatic relevance determination was performed on neural networks trained on this data, identifying NAA group differences in the pulvinar and mediodorsal nucleus, underscoring the importance of examining thalamic subregions in schizophrenia.</p

QSMGAN: Improved Quantitative Susceptibility Mapping using 3D Generative Adversarial Networks with increased receptive field

Quantitative susceptibility mapping (QSM) is a powerful MRI technique that has shown great potential in quantifying tissue susceptibility in numerous neurological disorders. However, the intrinsic ill-posed dipole inversion problem greatly affects the accuracy of the susceptibility map. We propose QSMGAN: a 3D deep convolutional neural network approach based on a 3D U-Net architecture with increased receptive field of the input phase compared to the output and further refined the network using the WGAN with gradient penalty training strategy. Our method generates accurate QSM maps from single orientation phase maps efficiently and performs significantly better than traditional non-learning-based dipole inversion algorithms. The generalization capability was verified by applying the algorithm to an unseen pathology--brain tumor patients with radiation-induced cerebral microbleeds

A Fully Automated Method for Segmenting Arteries and Quantifying Vessel Radii on Magnetic Resonance Angiography Images of Varying Projection Thickness.

PurposePrecise quantification of cerebral arteries can help with differentiation and prognostication of cerebrovascular disease. Existing image processing and segmentation algorithms for magnetic resonance angiography (MRA) are limited to the analysis of either 2D maximum intensity projection images or the entire 3D volume. The goal of this study was to develop a fully automated, hybrid 2D-3D method for robust segmentation of arteries and accurate quantification of vessel radii using MRA at varying projection thicknesses.MethodsA novel algorithm that employs an adaptive Frangi filter for segmentation of vessels followed by estimation of vessel radii is presented. The method was evaluated on MRA datasets and corresponding manual segmentations from three healthy subjects for various projection thicknesses. In addition, the vessel metrics were computed in four additional subjects. Three synthetically generated angiographic datasets resembling brain vasculature were also evaluated under different noise levels. Dice similarity coefficient, Jaccard Index, F-score, and concordance correlation coefficient were used to measure the segmentation accuracy of manual versus automatic segmentation.ResultsOur new adaptive filter rendered accurate representations of vessels, maintained accurate vessel radii, and corresponded better to manual segmentation at different projection thicknesses than prior methods. Validation with synthetic datasets under low contrast and noisy conditions revealed accurate quantification of vessels without distortions.ConclusionWe have demonstrated a method for automatic segmentation of vascular trees and the subsequent generation of a vessel radii map. This novel technique can be applied to analyze arterial structures in healthy and diseased populations and improve the characterization of vascular integrity

NIMG-64. THE POTENTIAL OF 7T ANATOMICAL IMAGING FOR CLINICAL ASSESSMENT OF CONTRAST-ENHANCING AND T2-HYPERINTENSE LESIONS IN PATIENTS WITH GLIOMA

Abstract PURPOSE 7 Tesla (7T) MRI scanners can provide novel information to improve the characterization of gliomas. However, patients who receive 7T scans must undergo separate clinical evaluations at lower field strengths due to a lack of clinical validation of 7T anatomical imaging. The purpose of this study was to develop a robust volumetric anatomical imaging protocol for the clinical evaluation of patients with glioma at 7T and compare lesion definition to standard 3T imaging. METHODS 3D T2-weighted, T2 FLAIR, and T1-weighted sequences at 7T were optimized to match the contrast, resolution, and scan time of corresponding clinical sequences at 3T. Ten patients with contrast-enhancing glioma (grades II-IV) were scanned with a protocol consisting of pre-contrast anatomical imaging and post-contrast T1-weighted imaging at both field strengths, with the 7T scan occurring in between the pre- and post-contrast 3T imaging. A&nbsp;half-dose of contrast was used at 7T, with an additional half-dose given immediately afterwards at 3T to provide similar lesion contrast given the 2.3-fold difference in field strength. Metrics for comparison between field strengths included volumes of T2 and contrast-enhancing lesions, and Likert-scale ratings (1-5) of lesion definition by a neuro-radiologist. RESULTS T2 and contrast-enhancing lesion volumes were not significantly different between field strengths, despite the trend in larger enhancing lesion volumes at 3T, which was expected given the protocol design. 7T T2-weighted and post-contrast T1-weighted images received on average half-point higher Likert-scale ratings than corresponding 3T images, whereas the opposite trend was observed with the T2 FLAIR and pre-contrast T1-weighted images. CONCLUSION Our pilot study suggests that clinical assessment of contrast-enhancing and T2-hyperintense lesions in glioma is feasible at 7T, which would obviate the need for two scans, allowing patients to take advantage of the increased sensitivity in metabolic and physiologic imaging available at 7T and ultimately improve patient care

A Fully Automated Method for Segmenting Arteries and Quantifying Vessel Radii on Magnetic Resonance Angiography Images of Varying Projection Thickness.

Purpose:Precise quantification of cerebral arteries can help with differentiation and prognostication of cerebrovascular disease. Existing image processing and segmentation algorithms for magnetic resonance angiography (MRA) are limited to the analysis of either 2D maximum intensity projection images or the entire 3D volume. The goal of this study was to develop a fully automated, hybrid 2D-3D method for robust segmentation of arteries and accurate quantification of vessel radii using MRA at varying projection thicknesses. Methods:A novel algorithm that employs an adaptive Frangi filter for segmentation of vessels followed by estimation of vessel radii is presented. The method was evaluated on MRA datasets and corresponding manual segmentations from three healthy subjects for various projection thicknesses. In addition, the vessel metrics were computed in four additional subjects. Three synthetically generated angiographic datasets resembling brain vasculature were also evaluated under different noise levels. Dice similarity coefficient, Jaccard Index, F-score, and concordance correlation coefficient were used to measure the segmentation accuracy of manual versus automatic segmentation. Results:Our new adaptive filter rendered accurate representations of vessels, maintained accurate vessel radii, and corresponded better to manual segmentation at different projection thicknesses than prior methods. Validation with synthetic datasets under low contrast and noisy conditions revealed accurate quantification of vessels without distortions. Conclusion:We have demonstrated a method for automatic segmentation of vascular trees and the subsequent generation of a vessel radii map. This novel technique can be applied to analyze arterial structures in healthy and diseased populations and improve the characterization of vascular integrity

NCOG-14. NEUROCOGNITIVE FUNCTION AND QUALITY OF LIFE IN STABLE GRADE II AND III GLIOMA PATIENTS

Abstract Neurocognitive function and quality of life are important clinical outcome measures for patients with lower grade glioma. Here, we performed neurocognitive testing and quality of life assessments in radiologically and clinically stable grade 2 and 3 glioma patients who are not receiving active treatment. METHODS Patients completed a computerized battery of standardized neurocognitive tests in the NIH Toolbox and quality of life assessments with the FACT-BR. We acquired patient demographic information, current performance status, current anti-epileptic therapy, treatment history, extent of resection at diagnosis and recurrence, tumor location, and histologic and molecular tumor characteristics. Tumor volumes were measured on T2 FLAIR MRIs. RESULTS We have enrolled 15 patients. All patients had previous resection (10 partial, 5 gross total), 11 received chemotherapy, and 6 prior radiation. Median age at testing was 41&nbsp;years old (range 26&nbsp;– 65). As a group, patients were impaired on processing speed and fluid cognition. Two patients were impaired on picture vocabulary, 6 on list sorting, 11 on processing speed, 6 on sequence memory, 4 on inhibitory control, 2 on dimensional change, 7 on fluid cognition, and 0 on crystallized cognition. Higher age was significantly associated with poorer age-corrected oral-reading, and sequence memory. Insula and parietal lesions were associated with slower processing speed. Previous chemotherapy treatment was associated with poorer dimensional change. On imaging, larger tumor volumes were associated with poorer list sorting, processing speed, and sequence memory. On the FACT-BR, older patients, patients with prior radiation or those with higher grade were associated with poorer social/family well-being. CONCLUSION The NIH Toolbox and FACT-BR are effective, accessible tools to assess neurocognitive function and quality of life in glioma patients. By correlating these assessments with patient and tumor characteristics, it may be possible to identify patients at risk for specific deficits and provide opportunity for intervention

NCOG-11. FEASIBILITY AND EFFICACY OF AN IPAD-BASED COGNITIVE REHABILITATION PROGRAM IN BRAIN TUMOR PATIENTS

Abstract OBJECTIVE To assess feasibility and effect on cognitive function and Health-Related Quality of Life (HRQoL) of an iPad-based intervention in grade 2 and 3 glioma patients stable off treatment. Patients with lower grade glioma suffer significant cognitive dysfunctions that impact their HRQoL. Formal cognitive rehabilitation is a limited resource that may be more available if deployed with a mobile device such as an iPad. METHODS Stable, grade 2 and 3 glioma patients with subjective cognitive complaints, complete a baseline computerized battery of standardized cognitive tests using the NIH Toolbox and HRQOL assessment with the FACT-BR. Patients then completed a novel, evidence-based, iPad based, brain tumor specific, cognitive rehabilitation program called ReMind over the next 3 months (~3 hours per week). NIH Toolbox and HRQOL assessments were repeated after completion of the rehabilitation, and again 9 months after baseline. Primary endpoint was feasibility with secondary endpoints of changes in cognitive scores and HRQOL assessments. RESULTS To date, 10 patients have enrolled and completed baseline testing, of whom 5 have completed ReMind rehabilitation. Median age is 56 years. Median disease duration is 7.6 years. 5 patients have Oligodendrogliomas (IDH mutated and 1p19q deleted), 3 patients have Astrocytomas, IDH mutated, and 2 patients have Astrocytomas NOS. 5 are grade II and 5 are grade III. 5 had left hemisphere tumors, 4 had right hemisphere tumors, and 1 was bilateral. 10 had prior chemotherapy and 8 prior radiation. We anticipate enrolling another 5 – 10 patients and will present the updated feasibility data as well as changes in cognitive and HRQOL scores. CONCLUSION As patients with lower grade tumors live longer, it is important to increase availability of cognitive interventions to improve HRQOL and outcomes. This iPad based approach provides in-home access to cognitive training and compensation strategies for patients with brain tumors