3D Magnetic Resonance Spectroscopic Imaging Research Articles

2D 1H sLASER Long-TE and 3D 31P Chemical Shift Imaging at 3 T for Monitoring Fasting-Induced Changes in Brain Tumor Tissue.

Emerging evidence suggests that fasting could play a key role in cancer treatment. Its metabolic effects on gliomas require further investigation. To design a multi-voxel 1H/31P MR-spectroscopic imaging (MRSI) protocol for noninvasive metabolic monitoring of cerebral, fasting-induced changes on an individual patient/tumor level, and to assess its technical reliability/reproducibility. Prospective. MRS phantom. Twenty-two patients (mean age = 61, 6 female) with suspected WHO grade II-IV glioma examined before and after 72-hour-fasting prior to biopsy/resection. 3-T, 1H decoupled 3D 31P MRSI, 2D 1H sLASER MRSI at an echo time of 144 msec, 2D 1H MRSI (as water reference), T1-weighted, T1-weighted contrast-enhanced, T2-weighted, and FLAIR. sLASER and PRESS sequences were used for phantom measurements. Phantom measurements and spectral simulations were performed with various echo-times for protocol optimization. In vivo spectral analyses were conducted using LCModel and AMARES, obtaining quality/fitting parameters (linewidth, signal-to-noise-ratio, and uncertainty measures of fitting) and metabolite intensities. The volume of glioma sub-regions was calculated and correlated with MRS findings. Ex-vivo spectra of necrotic tumor tissues were obtained using high-resolution magic-angle spinning (HR-MAS) technique. Wilcoxon signed-rank test, Bland-Altman plots, and coefficient of variation were used for repeatability analysis of quality/fitting parameters and metabolite concentrations. Spearman ρ correlation for the concentration of ketone bodies with volumes of glioma sub-regions was determined. A P-value <0.05 was considered statistically significant. 1H and 31P repeatability measures were highly consistent between the two sessions. β-hydroxybutyrate and acetoacetate were detectable (fitting-uncertainty <50%) in glioma sub-regions of all patients who completed the 72-hour-fasting cycle. β-hydroxybutyrate accumulation was significantly correlated with the necrotic/non-enhancing tumor core volume (ρ = 0.81) and validated using ex-vivo 1H HR-MAS. We propose a comprehensive MRS protocol that may be used for monitoring cerebral, fasting-induced changes in patients with glioma. 1 TECHNICAL EFFICACY: Stage 4.

Enhancing Whole-Brain Magnetic Field Homogeneity for 3D-Magnetic Resonance Spectroscopic Imaging with a Novel Unified Coil: A Preliminary Study.

The spectral quality of magnetic resonance spectroscopic imaging (MRSI) can be affected by strong magnetic field inhomogeneities, posing a challenge for 3D-MRSI's widespread clinical use with standard scanner-equipped 2nd-order shim coils. To overcome this, we designed an empirical unified shim-RF head coil (32-ch RF receive and 51-ch shim) for 3D-MRSI improvement. We compared its shimming performance and 3D-MRSI brain coverages against the standard scanner shim (2nd-order spherical harmonic (SH) shim coils) and integrated parallel reception, excitation, and shimming (iPRES) 32-ch AC/DC head coil. We also simulated a theoretical 3rd-, 4th-, and 5th-order SH shim as a benchmark to assess the UNIfied shim-RF coil (UNIC) improvements. In this preliminary study, the whole-brain coverage was simulated by using B0 field maps of twenty-four healthy human subjects (n = 24). Our results demonstrated that UNIC substantially improves brain field homogeneity, reducing whole-brain frequency standard deviations by 27% compared to the standard 2nd-order scanner shim and 17% compared to the iPRES shim. Moreover, UNIC enhances whole-brain coverage of 3D-MRSI by up to 34% compared to the standard 2nd-order scanner shim and up to 13% compared to the iPRES shim. UNIC markedly increases coverage in the prefrontal cortex by 147% and 47% and in the medial temporal lobe and temporal pole by 29% and 13%, respectively, at voxel resolutions of 1.4 cc and 0.09 cc for 3D-MRSI. Furthermore, UNIC effectively reduces variations in shim quality and brain coverage among different subjects compared to scanner shim and iPRES shim. Anticipated advancements in higher-order shimming (beyond 6th order) are expected via optimized designs using dimensionality reduction methods.

NIMG-64. IN VIVO METABOLIC PROFILING FOR RECURRENT GLIOMA

Abstract INTRODUCTION The 2021 WHO classification has identified the importance of molecular features in diagnosing adult glioma. The goal of this study was to use short echo MR spectroscopic imaging (MRSI) to evaluate the metabolite profiles at recurrence and characterize in vivo metabolism in relation to pathology by combining it with image-guided tissue samples. METHODS Fifty-one patients with an initial diagnosis of glioma (18 astrocytoma, 14 oligodendroglioma, and 19 glioblastoma) received MR examinations before surgical resection of progressive disease confirmed histologically. The 3D MRSI data were combined, processed, and quantified by LCModel with a simulated basis set. Metabolite levels were compared between contrast-enhancing lesions (CEL), non-enhancing lesions (NEL), and patient groups. Spectra data centered at the tissue target location were correlated to pathological parameters from the samples (0-4 samples/subject). RESULTS 74.5% (38/51) patients had enhancing tumors, with median CEL volume of 4.2 cm3 (min-max: 0.2-28.5 cm3) and median NEL volumes of 50.6 cm3 (4.8-167.2 cm3). The patients with GBM had significantly larger CEL volumes than the others (p=0.009).18/29 (62%) patients with lower-grade glioma had malignant progression to higher grades. Those who progressed from grade 2 to 3 or 4 had higher myo-inositol/choline (mean±SD, 2.62±0.64, N=18) compared to those who recurred as grade 2 (1.88±0.52, N=5, p = 0.015). Of the 51 patients, 40/65 in vivo spectra voxels centered where the tissues were sampled displayed good quality, with 27 having active tumors, 7 having treatment effects, and 6 having mixed tumors/treatment effects. The levels of choline/creatine and myo-inositol+glycline/creatine were significantly correlated with MIB-1 (p&amp;lt; 0.0001, =0.034; r=0.563, 0.349), but no difference was found between the locations with active tumors and treatment effects. DISCUSSION: This study demonstrated metabolite variations at the recurrence. Ongoing studies will further characterize the metabolite profiles for malignant progression and differences between active tumors and treatment effects.

Prediction of Stroke Onset Time With Combined Fast High-Resolution Magnetic Resonance Spectroscopic and Quantitative T2 Mapping.

The purpose of this work is to develop a multispectral imaging approach that combines fast high-resolution 3D magnetic resonance spectroscopic imaging (MRSI) and fast quantitative T2 mapping to capture the multifactorial biochemical changes within stroke lesions and evaluate its potentials for stroke onset time prediction. Special imaging sequences combining fast trajectories and sparse sampling were used to obtain whole-brain maps of both neurometabolites (2.0 × 3.0 × 3.0 mm3) and quantitative T2 values (1.9 × 1.9 × 3.0 mm3) within a 9-minute scan. Participants with ischemic stroke at hyperacute (0-24 h, n = 23) or acute (24 h-7d, n = 33) phase were recruited in this study. Lesion N-acetylaspartate (NAA), lactate, choline, creatine, and T2 signals were compared between groups and correlated with patient symptomatic duration. Bayesian regression analyses were employed to compare the predictive models of symptomatic duration using multispectral signals. In both groups, increased T2 and lactate levels, as well as decreased NAA and choline levels were detected within the lesion (all p < 0.001). Changes in T2, NAA, choline, and creatine signals were correlated with symptomatic duration for all patients (all p < 0.005). Predictive models of stroke onset time combining signals from MRSI and T2 mapping achieved the best performance (hyperacute: R2 = 0.438; all: R2 = 0.548). The proposed multispectral imaging approach provides a combination of biomarkers that index early pathological changes after stroke in a clinical-feasible time and improves the assessment of the duration of cerebral infarction. Developing accurate and efficient neuroimaging techniques to provide sensitive biomarkers for prediction of stroke onset time is of great importance for maximizing the proportion of patients eligible for therapeutic intervention. The proposed method provides a clinically feasible tool for the assessment of symptom onset time post ischemic stroke, which will help guide time-sensitive clinical management.

Evaluation of deep learning models for quality control of MR spectra.

While 3D MR spectroscopic imaging (MRSI) provides valuable spatial metabolic information, one of the hurdles for clinical translation is its interpretation, with voxel-wise quality control (QC) as an essential and the most time-consuming step. This work evaluates the accuracy of machine learning (ML) models for automated QC filtering of individual spectra from 3D healthy control and patient datasets. A total of 53 3D MRSI datasets from prior studies (30 neurological diseases, 13 brain tumors, and 10 healthy controls) were included in the study. Three ML models were evaluated: a random forest classifier (RF), a convolutional neural network (CNN), and an inception CNN (ICNN) along with two hybrid models: CNN + RF, ICNN + RF. QC labels used for training were determined manually through consensus of two MRSI experts. Normalized and cropped real-valued spectra was used as input. A cross-validation approach was used to separate datasets into training/validation/testing sets of aggregated voxels. All models achieved a minimum AUC of 0.964 and accuracy of 0.910. In datasets from neurological disease and controls, the CNN model produced the highest AUC (0.982), while the RF model achieved the highest AUC in patients with brain tumors (0.976). Within tumor lesions, which typically exhibit abnormal metabolism, the CNN AUC was 0.973 while that of the RF was 0.969. Data quality inference times were on the order of seconds for an entire 3D dataset, offering drastic time reduction compared to manual labeling. ML methods accurately and rapidly performed automated QC. Results in tumors highlights the applicability to a variety of metabolic conditions.

Predicting the Onset of Ischemic Stroke With Fast High‐Resolution 3D MR Spectroscopic Imaging

Predicting the Onset of Ischemic Stroke With Fast High‐Resolution 3D MR Spectroscopic Imaging

Pseudoprogression in GBM versus true progression in patients with glioblastoma: A multiapproach analysis

Background and purposeTo investigate the feasibility of using a multiapproach analysis combining clinical data, diffusion- and perfusion-weighted imaging, and 3D magnetic resonance spectroscopic imaging to distinguish true tumor progression (TP) from pseudoprogression (PSP) in patients with glioblastoma. Materials and methodsProgression was suspected within 6 months of radiotherapy in 46 of the 180 patients included in the Phase-III SpectroGlio trial (NCT01507506). Choline/creatine (Cho/Cr), choline/N-acetyl aspartate (Cho/NAA) and lactate/N-acetyl aspartate (Lac/NAA) ratios were extracted. Apparent diffusion coefficient (ADC) and cerebral blood volume (CBV) maps were calculated. ADC, relative CBV values and tumor volume (TV) were collected at relapse. Differences between TP and PSP were evaluated using Mann–Whitney tests, and p values were adjusted with Bonferroni correction. ResultsPatients with suspected progression underwent a new MRI scan 1 month after the first one. Of these, 28 were classified as PSP, and 18 as TP. After a median follow-up of 41 months, median overall survival was higher in PSP than in TP (25.2 vs 20.3 months; p = 0.0092). Lac/NAA and Cho/Cr ratios were higher in TP than in PSP (1.2 vs 0.5; p = 0.006; and 3 vs 2.2; p = 0.021). After multivariate regression analysis, TV was the most significant predictor of TP vs PSP, and the only one retained in the model (p = 0.028). ConclusionThree spectroscopic ratios could be used to differentiate PSP from TP. TV at relapse was the most predictive factor in the multivariate analysis, and overall survival was higher in PSP than in TP.

Predicting the Onset of Ischemic Stroke With Fast High-Resolution 3D MR Spectroscopic Imaging.

Neurometabolite concentrations provide a direct index of infarction progression in stroke. However, their relationship with stroke onset time remains unclear. To assess the temporal dynamics of N-acetylaspartate (NAA), creatine, choline, and lactate and estimate their value in predicting early (<6 hours) vs. late (6-24hours) hyperacute stroke groups. Cross-sectional cohort. A total of 73 ischemic stroke patients scanned at 1.8-302.5 hours after symptom onset, including 25 patients with follow-up scans. A 3 T/magnetization-prepared rapid acquisition gradient echo sequence for anatomical imaging, diffusion-weighted imaging and fluid-attenuated inversion recovery imaging for lesion delineation, and 3D MR spectroscopic imaging (MRSI) for neurometabolic mapping. Patients were divided into hyperacute (0-24hours), acute (24hours to 1 week), and subacute (1-2 weeks) groups, and into early (<6 hours) and late (6-24hours) hyperacute groups. Bayesian logistic regression was used to compare classification performance between early and late hyperacute groups by using different combinations of neurometabolites as inputs. Linear mixed effects modeling was applied for group-wise comparisons between NAA, creatine, choline, and lactate. Pearson's correlation analysis was used for neurometabolites vs. time. P < 0.05 was considered statistically significant. Lesional NAA and creatine were significantly lower in subacute than in acute stroke. The main effects of time were shown on NAA (F=14.321) and creatine (F= 12.261). NAA was significantly lower in late than early hyperacute patients, and was inversely related to time from symptom onset across both groups (r=-0.440). The decrease of NAA and increase of lactate were correlated with lesion volume (NAA: r=-0.472; lactate: r=0.366) in hyperacute stroke. Discrimination was improved by combining NAA, creatine, and choline signals (area under the curve [AUC]=0.90). High-resolution 3D MRSI effectively assessed the neurometabolite changes and discriminated early and late hyperacute stroke lesions. 1. Stage 2.

NIMG-24. LONGITUDINAL MR SPECTROSCOPY TO DETECT PROGRESSION IN PATIENTS WITH LOWER-GRADE GLIOMA IN THE SURVEILLANCE PHASE

Abstract BACKGROUND Monitoring lower-grade gliomas (LrGGs) for disease progression is made difficult by the limits of anatomical MRI to distinguish treatment-related tissue changes from tumor progression. MR spectroscopic imaging (MRSI) offers additional metabolic information that can help address these challenges. The goal of this study was to compare longitudinal changes in multiparametric MRI, including diffusion-weighted imaging, perfusion imaging, and 3D MRSI, for LrGG patients who progressed at the final time point and those who remained clinically stable. METHODS Forty-one patients with LrGG who were clinically stable were longitudinally assessed for progression. Changes in anatomical, diffusion, perfusion, and MRSI data were acquired and compared between patients who remained clinically stable and those who progressed. RESULTS Thirty-one patients remained stable, and 10 patients progressed. Over the study period, progressed patients had a significantly greater increase in normalized choline, choline-to-N-acetylaspartic acid index (CNI), normalized creatine, and creatine-to-N-acetylaspartic acid index (CRNI), than stable patients. CRNI was significantly associated with progression status and WHO type. Progressed astrocytoma patients had greater increases in CRNI than stable astrocytoma patients. CONCLUSIONS LrGG patients in surveillance with tumors that progressed had significantly increasing choline and creatine metabolite signals on MRSI, with a trend of increasing T2 FLAIR volumes, compared to LrGG patients who remained stable. These data show that MRSI can be used in conjunction with anatomical imaging studies to gain a clearer picture of LrGG progression, especially in the setting of clinical ambiguity.

ATP line splitting in association with reduced intracellular magnesium and pH: a brain 31 P MR spectroscopic imaging (MRSI) study of pediatric patients with myelin oligodendrocyte glycoprotein antibody-associated disorders (MOGADs).

Over the past four decades, ATP, the obligatory energy molecule for keeping all cells alive and functioning, has been thought to contribute only one set of signals in brain 31 P MR spectra. Here we report for the first time the observation of two separate β-ATP peaks in brain spectra acquired from patients with myelin oligodendrocyte glycoprotein antibody-associated disorders (MOGADs) using 3D MRSI at 7 T. In voxel spectra with β-ATP line splitting, these two peaks are separated by 0.46 ± 0.18 ppm (n = 6). Spectral lineshape analysis indicates that the upper field β-ATP peak is smaller in relative intensity (24 ± 11% versus 76 ± 11%), and narrower in linewidth (56.8 ± 10.3 versus 41.2 ± 10.3 Hz) than the downfield one. Data analysis also reveals a similar line splitting for the intracellular inorganic phosphate (Pi ) signal, which is characterized by two components with a smaller separation (0.16 ± 0.09 ppm) and an intensity ratio (26 ± 7%:74 ± 7%) comparable to that of β-ATP. While the major components of Pi and β-ATP correspond to a neutral intracellular pH (6.99 ± 0.01) and a free Mg2+ level (0.18 ± 0.02 mM, by Iotti's conversion formula) as found in healthy subjects, their minor counterparts relate to a slightly acidic pH (6.86 ± 0.07) and a 50% lower [Mg2+ ] (0.09 ± 0.02 mM), respectively. Data correlation between β-ATP and Pi signals appears to suggest an association between an increased [H+ ] and a reduced [Mg2+ ] in MOGAD patients.

P15.03.A The value of 7 Tesla MR spectroscopic imaging for improved preoperative determination of the tumor grade and IDH status in gliomas: preliminary data

Abstract Introduction A new generation of MR spectroscopic imaging (MRSI) methods using 7T scanners have demonstrated the capability to resolve more neuro- and oncometabolites at higher resolutions than clinical routine MRSI. In a cohort of glioma patients, we explored the automated preoperative and noninvasive classification of IDH-mutation status and tumor grade based on 7T MRSI. Methods This retrospective study included 36 patients (15 female) with histologically confirmed diffusely infiltrating glioma WHO grade 2-4 (9 grade 2, 9 grade 3 and 18 grade 4) and known IDH status (21 IDH1-mut, 15 IDH-wt) with an available 7T MRSI scan of sufficient data quality. The 3D MRSI scan had a 3.4 mm isotropic resolution and 15 minutes acquisition time. 12 spectral components were classified voxel-wise, including choline, glutamine and glycine. Within a tumor segmentation based on routine 3T imaging, we used a random forest algorithm for the voxel-wise classification of IDH mutation and grade (into low or high grade). Training used the leave-one-out cross validation method (i.e., for every patient data set, the other 35 datasets were used as training set) and feature selection out of the available combinations for metabolite ratios (e.g., glutamine to choline). The resulting voxel classifications were aggregated into a mean probability per patient that was the base for receiver-operator characteristic (ROC) curves both for grade and IDH status. Results The classification algorithm obtained an area under the curve (AUC) for IDH determination of 0.85 (e.g., 75% sensitivity and 95% specificity). For grade determination, the AUC was 0.88 (e.g., 87% sensitivity and 89% specificity). In comparison, the AUC per voxel would have resulted in an AUC of 0.66 for both. Further, classification by individual metabolite ratios resulted in lower AUCs in all cases. Conclusions According to our preliminary data, preoperative 7T MRSI is capable to determine the correct glioma grade and IDH status with high sensitivity and specificity by leveraging the extended metabolic panel width and voxel amount. By increasing this cohort in future, we intend to confirm our initial results and we also plan to extend classification to more molecular-pathological features (e.g., TERT). Thus, even a voxel-wise classification of tumor microenvironments could be attempted. Further improvements in 7T MRSI methodology such as absolute instead of relative quantification would also aid these attempts. In summary, 7T MRSI has shown its potential for improved preoperative characterization of gliomas.

Longitudinal MR spectroscopy to detect progression in patients with lower-grade glioma in the surveillance phase.

Monitoring lower-grade gliomas (LrGGs) for disease progression is made difficult by the limits of anatomical MRI to distinguish treatment related tissue changes from tumor progression. MR spectroscopic imaging (MRSI) offers additional metabolic information that can help address these challenges. The goal of this study was to compare longitudinal changes in multiparametric MRI, including diffusion weighted imaging, perfusion imaging, and 3D MRSI, for LrGG patients who progressed at the final time-point and those who remained clinically stable. Forty-one patients with LrGG who were clinically stable were longitudinally assessed for progression. Changes in anatomical, diffusion, perfusion and MRSI data were acquired and compared between patients who remained clinically stable and those who progressed. Thirty-one patients remained stable, and 10 patients progressed. Over the study period, progressed patients had a significantly greater increase in normalized choline, choline-to-N-acetylaspartic acid index (CNI), normalized creatine, and creatine-to-N-acetylaspartic acid index (CRNI), than stable patients. CRNI was significantly associated with progression status and WHO type. Progressed astrocytoma patients had greater increases in CRNI than stable astrocytoma patients. LrGG patients in surveillance with tumors that progressed had significantly increasing choline and creatine metabolite signals on MRSI, with a trend of increasing T2 FLAIR volumes, compared to LrGG patients who remained stable. These data show that MRSI can be used in conjunction with anatomical imaging studies to gain a clearer picture of LrGG progression, especially in the setting of clinical ambiguity.

In Vivo Absolute Metabolite Quantification Using a Multiplexed ERETIC-RX Array Coil for Whole-Brain MR Spectroscopic Imaging.

Absolute quantification of metabolites in MR spectroscopic imaging (MRSI) requires a stable reference signal of known concentration. The Electronic REference To access In vivo Concentrations (ERETIC) has shown great promise but has not been applied in patients and 3D MRSI. ERETIC hardware has not been integrated with receive arrays due to technical challenges, such as coil combination and unwanted coupling between multiple ERETIC and receive channels, for which we developed mitigation strategies. To develop absolute quantification for whole-brain MRSI in glioma patients. Prospective. Five healthy volunteers and three patients with isocitrate dehydrogenase mutant glioma (27% female). Calibration and coil loading phantoms. A 3 T; Adiabatic spin-echo spiral 3D MRSI with real-time motion correction, Fluid Attenuated Inversion Recovery (FLAIR), Gradient Recalled Echo (GRE), Multi-echo Magnetization Prepared Rapid Acquisition of Gradient Echo (MEMPRAGE). Absolute quantification was performed for five brain metabolites (total N-acetyl-aspartate [NAA]/creatine/choline, glutamine + glutamate, myo-inositol) and the oncometabolite 2-hydroxyglutarate using a custom-built 4x-ERETIC/8x-receive array coil. Metabolite quantification was performed with both EREIC and internal water reference methods. ERETIC signal was transmitted via optical link and used to correct coil loading. Inductive and radiative coupling between ERETIC and receive channels were measured. ERETIC and internal water methods for metabolite quantification were compared using Bland-Altman (BA) analysis and the nonparametric Mann-Whitney test. P < 0.05 was considered statistically significant. ERETIC could be integrated in receive arrays and inductive coupling dominated (5-886 times) radiative coupling. Phantoms show proportional scaling of the ERETIC signal with coil loading. The BA analysis demonstrated very good agreement (3.3% ± 1.6%) in healthy volunteers, while there was a large difference (36.1% ± 3.8%) in glioma tumors between metabolite concentrations by ERETIC and internal water quantification. Our results indicate that ERETIC integrated with receive arrays and whole-brain MRSI is feasible for brain metabolites quantification. Further validation is required to probe that ERETIC provides more accurate metabolite concentration in glioma patients. 2 TECHNICAL EFFICACY: Stage 1.

Achieving high-resolution 1H-MRSI of the human brain with compressed-sensing and low-rank reconstruction at 7 Tesla

Low sensitivity MR techniques such as magnetic resonance spectroscopic imaging (MRSI) greatly benefit from the gain in signal-to-noise provided by ultra-high field MR. High-resolution and whole-slab brain MRSI remains however very challenging due to lengthy acquisition, low signal, lipid contamination and field inhomogeneity. In this study, we propose an acquisition-reconstruction scheme that combines 1H free-induction-decay (FID)-MRSI sequence, short TR acquisition, compressed sensing acceleration and low-rank modeling with total-generalized-variation constraint to achieve metabolite imaging in two and three dimensions at 7 Tesla. The resulting images and volumes reveal highly detailed distributions that are specific to each metabolite and follow the underlying brain anatomy. The MRSI method was validated in a high-resolution phantom containing fine metabolite structures, and in five healthy volunteers. This new application of compressed sensing acceleration paves the way for high-resolution MRSI in clinical setting with acquisition times of 5 min for 2D MRSI at 2.5 mm and of 20 min for 3D MRSI at 3.3 mm isotropic.

3D magnetic resonance spectroscopic imaging reveals links between brain metabolites and multidimensional pain features in fibromyalgia.

Fibromyalgia is a centralized multidimensional chronic pain syndrome, but its pathophysiology is not fully understood. We applied 3D magnetic resonance spectroscopic imaging (MRSI), covering multiple cortical and subcortical brain regions, to investigate the association between neuro-metabolite (e.g. combined glutamate and glutamine, Glx; myo-inositol, mIno; and combined (total) N-acetylaspartate and N-acetylaspartylglutamate, tNAA) levels and multidimensional clinical/behavioural variables (e.g. pain catastrophizing, clinical pain severity and evoked pain sensitivity) in women with fibromyalgia (N=87). Pain catastrophizing scores were positively correlated with Glx and tNAA levels in insular cortex, and negatively correlated with mIno levels in posterior cingulate cortex (PCC). Clinical pain severity was positively correlated with Glx levels in insula and PCC, and with tNAA levels in anterior midcingulate cortex (aMCC), but negatively correlated with mIno levels in aMCC and thalamus. Evoked pain sensitivity was negatively correlated with levels of tNAA in insular cortex, MCC, PCC and thalamus. These findings support single voxel placement targeting nociceptive processing areas in prior 1 H-MRS studies, but also highlight other areas not as commonly targeted, such as PCC, as important for chronic pain pathophysiology. Identifying target brain regions linked to multidimensional symptoms of fibromyalgia (e.g. negative cognitive/affective response to pain, clinical pain, evoked pain sensitivity) may aid the development of neuromodulatory and individualized therapies. Furthermore, efficient multi-region sampling with 3D MRSI could reduce the burden of lengthy scan time for clinical research applications of molecular brain-based mechanisms supporting multidimensional aspects of fibromyalgia. This large N study linked brain metabolites and pain features in fibromyalgia patients, with a better spatial resolution and brain coverage, to understand a molecular mechanism underlying pain catastrophizing and other aspects of pain transmission. Metabolite levels in self-referential cognitive processing area as well as pain-processing regions were associated with pain outcomes. These results could help the understanding of its pathophysiology and treatment strategies for clinicians.

Brain metabolite concentration in pain processing regions is linked with multidimensional morbidity in fibromyalgia - a voxel-wise 3D MR Spectroscopic Imaging study

Fibromyalgia is a multidimensional chronic pain syndrome. It is thought to result mainly from central nervous system dysfunction, but its working mechanism is not fully understood. In this study, we applied multi-slice magnetic resonance spectroscopy imaging (MRSI) to investigate the relationship between brain metabolite (e.g., combined glutamate and glutamine, Glx; myo-inositol, mIno; and combined N-acetylaspartate and N-acetylaspartylglutamate; tNAA) levels and the severity of multidimensional clinical/behavioral metrics (e.g., pain catastrophizing, clinical pain severity, and evoked pain sensitivity) in fibromyalgia patients (N=87). Fibromyalgia patients showed greater pain catastrophizing and hyperalgesia compared with age-matched healthy controls (N=40). In fibromyalgia patients, pain catastrophizing scale scores were positively correlated with Glx and tNAA levels in the insular cortex, and were negatively correlated with mIno levels in the posterior cingulate cortex (PCC). Clinical pain severity showed positive correlations with Glx levels in the insular and PCC, and with tNAA levels in the anterior middle cingulate cortex (aMCC), but negatively with mIno levels in the aMCC and thalamus. The level of tNAA in the insular cortex, MCC, PCC, and thalamus, were negatively correlated with evoked pain sensitivity. These results highlight the utility of MRSI in the understanding of molecular mechanisms underlying multidimensional aspects of fibromyalgia. This work was supported by the NIH (National Institute of Arthritis and Musculoskeletal and Skin Diseases grant R01-AR064367, National Center for Complementary and Integrative Health grants R01-AT007550, R61-AT009306, and P01-AT AT009965, and National Center for Research Resources grants P41-RR14075, S10-RR021110, and S10-RR023043). Development of MRSI pulse sequence and processing was funded by NIH/NCI grants K22CA178269 and R01CA211080.

A large fixed bed reactor for MRI operando experiments at elevated temperature and pressure.

Recently, in situ studies using nuclear magnetic resonance (NMR) have shown the possibility to monitor local transport phenomena of gas-phase reactions inside opaque structures. Their application to heterogeneously catalyzed reactions remains challenging due to inherent temperature and pressure constraints. In this work, an NMR-compatible reactor was designed, manufactured, and tested, which can endure high temperatures and increased pressure. In temperature and pressure tests, the reactor withstood pressures up to 28 bars at room temperature and temperatures over 400 °C and exhibited only little magnetic shielding. Its applicability was demonstrated by performing the CO2 methanation reaction, which was measured operando for the first time by using a 3D magnetic resonance spectroscopic imaging sequence. The reactor design is described in detail, allowing its easy adaptation for different chemical reactions and other NMR measurements under challenging conditions.

BIMG-04. MAPPING HETEROGENEITY OF HIGH-GRADE GLIOMA METABOLISM USING HIGH RESOLUTION 7T MRSI

OBJECTIVESNeurosurgical resection in gliomas depends on the precise preoperative definition of the tumor and its margins to realize a safe maximum resection that translates into a better patient outcome. New metabolic imaging techniques could improve this delineation as well as designate targets for biopsies. We validated the performance of our fast high-resolution whole-brain 3D-magnetic resonance spectroscopic imaging (MRSI) method at 7T in high-grade gliomas (HGGs) as first step to this regard.METHODSWe measured 23 patients with HGGs at 7T with MRSI covering the whole cerebrum with 3.4mm isotropic resolution in 15 min. Quantification used a basis-set of 17 neurochemical components. They were evaluated for their reliability/quality and compared to neuroradiologically segmented tumor regions-of-interest (necrosis, contrast-enhanced, non-contrast-enhanced+edema, peritumoral) and histopathology (e.g., grade, IDH-status).RESULTSWe found 18/23 measurements to be usable and ten neurochemicals quantified with acceptable quality. The most common denominators were increases of glutamine, glycine, and total choline as well as decreases of N-acetyl-aspartate and total creatine over most tumor regions. Other metabolites like taurine and serine showed mixed behavior. We further found that heterogeneity in the metabolic images often continued into the peritumoral region. While 2-hydroxy-glutarate could not be satisfyingly quantified, we found a tendency for a decrease of glutamate in IDH1-mutant HGGs.DISCUSSIONOur findings corresponded well to clinical tumor segmentation but were more heterogeneous and often extended into the peritumoral region. Our results corresponded to previous knowledge, but with previously not feasible resolution. Apart from glycine/glutamine and their role in glioma progression, more research on the connection of glutamate and others to specific mutations is necessary. The addition of low-grade gliomas and statistical ROI analysis in a larger cohort will be the next important steps to define the benefits of our 7T MRSI approach for the definition of spatial metabolic tumor profiles.

Differentiating Radiation Necrosis from Brain Tumor Using Hyperpolarized Carbon-13 MR Metabolic Imaging.

Differentiation between radiation-induced necrosis and tumor recurrence is crucial to determine proper management strategies but continues to be one of the central challenges in neuro-oncology. We hypothesized that hyperpolarized 13C MRI, a unique technique to measure real-time in vivo metabolism, would distinguish radiation necrosis from tumor on the basis of cell-intrinsic metabolic differences. The purpose of this study was to explore the feasibility of using hyperpolarized [1-13C]pyruvate for differentiating radiation necrosis from brain tumors. Radiation necrosis was initiated by employing a CT-guided 80-Gy single-dose irradiation of a half cerebrum in mice (n = 7). Intracerebral tumor was modeled with two orthotopic mouse models: GL261 glioma (n = 6) and Lewis lung carcinoma (LLC) metastasis (n = 7). 13C 3D MR spectroscopic imaging data were acquired following hyperpolarized [1-13C]pyruvate injection approximately 89 and 14days after treatment for irradiated and tumor-bearing mice, respectively. The ratio of lactate to pyruvate (Lac/Pyr), normalized lactate, and pyruvate in contrast-enhancing lesion was compared between the radiation-induced necrosis and brain tumors. Histopathological analysis was performed from resected brains. Conventional MRI exhibited typical radiographic features of radiation necrosis and brain tumor with large areas of contrast enhancement and T2 hyperintensity in all animals. Normalized lactate in radiation necrosis (0.10) was significantly lower than that in glioma (0.26, P =.004) and LLC metastatic tissue (0.25, P =.00007). Similarly, Lac/Pyr in radiation necrosis (0.18) was significantly lower than that in glioma (0.55, P =.00008) and LLC metastasis (0.46, P =.000008). These results were consistent with histological findings where tumor-bearing brains were highly cellular, while irradiated brains exhibited pathological markers consistent with reparative changes from radiation necrosis. Hyperpolarized 13C MR metabolic imaging of pyruvate is a noninvasive imaging method that differentiates between radiation necrosis and brain tumors, providing a groundwork for further clinical investigation and translation for the improved management of patients with brain tumors.

Imaging Neurochemistry and Brain Structure Tracks Clinical Decline and Mechanisms of ALS in Patients.

Background: Oxidative stress and protein aggregation are key mechanisms in amyotrophic lateral sclerosis (ALS) disease. Reduced glutathione (GSH) is the most important intracellular antioxidant that protects neurons from reactive oxygen species. We hypothesized that levels of GSH measured by MR spectroscopic imaging (MRSI) in the motor cortex and corticospinal tract are linked to clinical trajectory of ALS patients.Objectives: Investigate the value of GSH imaging to probe clinical decline of ALS patients in combination with other neurochemical and structural parameters.Methods: Twenty-four ALS patients were imaged at 3 T with an advanced MR protocol. Mapping GSH levels in the brain is challenging, and for this purpose, we used an optimized spectral-edited 3D MRSI sequence with real-time motion and field correction to image glutathione and other brain metabolites. In addition, our imaging protocol included (i) an adiabatic T1ρ sequence to image macromolecular fraction of brain parenchyma, (ii) diffusion tensor imaging (DTI) for white matter tractography, and (iii) high-resolution anatomical imaging.Results: We found GSH in motor cortex (r = −0.431, p = 0.04) and corticospinal tract (r = −0.497, p = 0.016) inversely correlated with time between diagnosis and imaging. N-Acetyl-aspartate (NAA) in motor cortex inversely correlated (r = −0.416, p = 0.049), while mean water diffusivity (r = 0.437, p = 0.033) and T1ρ (r = 0.482, p = 0.019) positively correlated with disease progression measured by imputed change in revised ALS Functional Rating Scale. There is more decrease in the motor cortex than in the white matter for GSH compared to NAA, glutamate, and glutamine.Conclusions: Our study suggests that a panel of biochemical and structural imaging biomarkers defines a brain endophenotype, which can be used to time biological events and clinical progression in ALS patients. Such a quantitative brain endophenotype may stratify ALS patients into more homogeneous groups for therapeutic interventions compared to clinical criteria.