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This study aimed to implement a multimodal 1H/HP-13C imaging protocol to augment the serial monitoring of patients with glioma, while simultaneously pursuing methods for improving the robustness of HP-13C metabolic data. A total of 100 1H/HP [1-13C]-pyruvate MR examinations (104 HP-13C datasets) were acquired from 42 patients according to the comprehensive multimodal glioma imaging protocol. Serial data coverage, accuracy of frequency reference, and acquisition delay were evaluated using a mixed-effects model to account for multiple exams per patient. Serial atlas-based HP-13C MRI demonstrated consistency in volumetric coverage measured by inter-exam dice coefficients (0.977 ± 0.008, mean ± SD; four patients/11 exams). The atlas-derived prescription provided significantly improved data quality compared to manually prescribed acquisitions (n = 26/78; p = 0.04). The water-based method for referencing [1-13C]-pyruvate center frequency significantly reduced off-resonance excitation relative to the coil-embedded [13C]-urea phantom (4.1 ± 3.7 Hz vs. 9.9 ± 10.7 Hz; p = 0.0007). Significantly improved capture of tracer inflow was achieved with the 2-s versus 5-s HP-13C MRI acquisition delay (p = 0.007). This study demonstrated the implementation of a comprehensive multimodal 1H/HP-13C MR protocol emphasizing the monitoring of steady-state/dynamic metabolism in patients with glioma.

PurposeIn patients with diffuse low-grade glioma (LGG), the extent of surgical tumor resection (EOR) has a controversial role, in part because a randomized clinical trial with different levels of EOR is not feasible.MethodsIn a 20-year retrospective cohort of 392 patients with IDH-mutant grade 2 glioma, we analyzed the combined effects of volumetric EOR and molecular and clinical factors on overall survival (OS) and progression-free survival by recursive partitioning analysis. The OS results were validated in two external cohorts (n = 365). Propensity score analysis of the combined cohorts (n = 757) was used to mimic a randomized clinical trial with varying levels of EOR.ResultsRecursive partitioning analysis identified three survival risk groups. Median OS was shortest in two subsets of patients with astrocytoma: those with postoperative tumor volume (TV) > 4.6 mL and those with preoperative TV > 43.1 mL and postoperative TV ≤ 4.6 mL. Intermediate OS was seen in patients with astrocytoma who had chemotherapy with preoperative TV ≤ 43.1 mL and postoperative TV ≤ 4.6 mL in addition to oligodendroglioma patients with either preoperative TV > 43.1 mL and residual TV ≤ 4.6 mL or postoperative residual volume > 4.6 mL. Longest OS was seen in astrocytoma patients with preoperative TV ≤ 43.1 mL and postoperative TV ≤ 4.6 mL who received no chemotherapy and oligodendroglioma patients with preoperative TV ≤ 43.1 mL and postoperative TV ≤ 4.6 mL. EOR ≥ 75% improved survival outcomes, as shown by propensity score analysis.ConclusionAcross both subtypes of LGG, EOR beginning at 75% improves OS while beginning at 80% improves progression-free survival. Nonetheless, maximal resection with preservation of neurological function remains the treatment goal. Our findings have implications for surgical strategies for LGGs, particularly oligodendroglioma.

BackgroundDynamic hyperpolarized (HP)-13C MRI has enabled real-time, non-invasive assessment of Warburg-related metabolic dysregulation in glioma using a [1-13C]pyruvate tracer that undergoes conversion to [1-13C]lactate and [13C]bicarbonate. Using a multi-parametric 1H/HP-13C imaging approach, we investigated dynamic and steady-state metabolism, together with physiological parameters, in high-grade gliomas to characterize active tumor.MethodsMulti-parametric 1H/HP-13C MRI data were acquired from fifteen patients with progressive/treatment-naïve glioblastoma [prog/TN GBM, IDH-wildtype (n = 11)], progressive astrocytoma, IDH-mutant, grade 4 (G4AIDH+, n = 2) and GBM manifesting treatment effects (n = 2). Voxel-wise regional analysis of the cohort with prog/TN GBM assessed imaging heterogeneity across contrast-enhancing/non-enhancing lesions (CEL/NEL) and normal-appearing white matter (NAWM) using a mixed effects model. To enable cross-nucleus parameter association, normalized perfusion, diffusion, and dynamic/steady-state (HP-13C/spectroscopic) metabolic data were collectively examined at the 13C resolution. Prog/TN GBM were similarly compared against progressive G4AIDH+ and treatment effects.ResultsRegional analysis of Prog/TN GBM metabolism revealed statistically significant heterogeneity in 1H choline-to-N-acetylaspartate index (CNI)max, [1-13C]lactate, modified [1-13C]lactate-to-[1-13C]pyruvate ratio (CELval > NELval > NAWMval); [1-13C]lactate-to-[13C]bicarbonate ratio (CELval > NELval/NAWMval); and 1H-lactate (CELval/NELval > NAWMundetected). Significant associations were found between normalized perfusion (cerebral blood volume, nCBV; peak height, nPH) and levels of [1-13C]pyruvate and [1-13C]lactate, as well as between CNImax and levels of [1-13C]pyruvate, [1-13C]lactate and modified ratio. GBM, by comparison to G4AIDH+, displayed lower perfusion %-recovery and modeled rate constants for [1-13C]pyruvate-to-[1-13C]lactate conversion (kPL), and higher 1H-lactate and [1-13C]pyruvate levels, while having higher nCBV, %-recovery, kPL, [1-13C]pyruvate-to-[1-13C]lactate and modified ratios relative to treatment effects.ConclusionsGBM consistently displayed aberrant, Warburg-related metabolism and regional heterogeneity detectable by novel HP-13C/1H imaging techniques.

PurposePrognostically favorable IDH-mutant gliomas are known to produce oncometabolite D-2-hydroxyglutarate (2HG). In this study, we investigated metabolite-based features of patients with grade 2 and 3 glioma using 2HG-specific in vivo MR spectroscopy, to determine their relationship with image-guided tissue pathology and predictive role in progression-free survival (PFS).MethodsForty-five patients received pre-operative MRIs that included 3-D spectroscopy optimized for 2HG detection. Spectral data were reconstructed and quantified to compare metabolite levels according to molecular pathology (IDH1R132H, 1p/19q, and p53); glioma grade; histological subtype; and T2 lesion versus normal-appearing white matter (NAWM) ROIs. Levels of 2HG were correlated with other metabolites and pathological parameters (cellularity, MIB-1) from image-guided tissue samples using Pearson's correlation test. Metabolites predictive of PFS were evaluated with Cox proportional hazards models.ResultsQuantifiable levels of 2HG in 39/42 (93%) IDH+ and 1/3 (33%) IDH- patients indicated a 91.1% apparent detection accuracy. Myo-inositol/total choline (tCho) showed reduced values in astrocytic (1p/19q-wildtype), p53-mutant, and grade 3 (vs. 2) IDH-mutant gliomas (p

BackgroundDiagnostic classification of diffuse gliomas now requires an assessment of molecular features, often including IDH-mutation and 1p19q-codeletion status. Because genetic testing requires an invasive process, an alternative noninvasive approach is attractive, particularly if resection is not recommended. The goal of this study was to evaluate the effects of training strategy and incorporation of biologically relevant images on predicting genetic subtypes with deep learning.MethodsOur dataset consisted of 384 patients with newly diagnosed gliomas who underwent preoperative MRI with standard anatomical and diffusion-weighted imaging, and 147 patients from an external cohort with anatomical imaging. Using tissue samples acquired during surgery, each glioma was classified into IDH-wildtype (IDHwt), IDH-mutant/1p19q-noncodeleted (IDHmut-intact), and IDH-mutant/1p19q-codeleted (IDHmut-codel) subgroups. After optimizing training parameters, top performing convolutional neural network (CNN) classifiers were trained, validated, and tested using combinations of anatomical and diffusion MRI with either a 3-class or tiered structure. Generalization to an external cohort was assessed using anatomical imaging models.ResultsThe best model used a 3-class CNN containing diffusion-weighted imaging as an input, achieving 85.7% (95% CI: [77.1, 100]) overall test accuracy and correctly classifying 95.2%, 88.9%, 60.0% of the IDHwt, IDHmut-intact, and IDHmut-codel tumors. In general, 3-class models outperformed tiered approaches by 13.5%-17.5%, and models that included diffusion-weighted imaging were 5%-8.8% more accurate than those that used only anatomical imaging.ConclusionTraining a classifier to predict both IDH-mutation and 1p19q-codeletion status outperformed a tiered structure that first predicted IDH-mutation, then 1p19q-codeletion. Including apparent diffusion coefficient (ADC), a surrogate marker of cellularity, more accurately captured differences between subgroups.

BackgroundReal-time metabolic conversion of intravenously-injected hyperpolarized [1-13C]pyruvate to [1-13C]lactate and [13C]bicarbonate in the brain can be measured using dynamic hyperpolarized carbon-13 (HP-13C) MRI. However, voxel-wise evaluation of metabolism in patients with glioma is challenged by the limited signal-to-noise ratio (SNR) of downstream 13C metabolites, especially within lesions. The purpose of this study was to evaluate the ability of higher-order singular value decomposition (HOSVD) denoising methods to enhance dynamic HP [1-13C]pyruvate MRI data acquired from patients with glioma.MethodsDynamic HP-13C MRI were acquired from 14 patients with glioma. The effects of two HOSVD denoising techniques, tensor rank truncation-image enhancement (TRI) and global-local HOSVD (GL-HOSVD), on the SNR and kinetic modeling were analyzed in [1-13C]lactate data with simulated noise that matched the levels of [13C]bicarbonate signals. Both methods were then evaluated in patient data based on their ability to improve [1-13C]pyruvate, [1-13C]lactate and [13C]bicarbonate SNR. The effects of denoising on voxel-wise kinetic modeling of kPL and kPB was also evaluated. The number of voxels with reliable kinetic modeling of pyruvate-to-lactate (kPL) and pyruvate-to-bicarbonate (kPB) conversion rates within regions of interest (ROIs) before and after denoising was then compared.ResultsBoth denoising methods improved metabolite SNR and regional signal coverage. In patient data, the average increase in peak dynamic metabolite SNR was 2-fold using TRI and 4-5 folds using GL-HOSVD denoising compared to acquired data. Denoising reduced kPL modeling errors from a native average of 23% to 16% (TRI) and 15% (GL-HOSVD); and kPB error from 42% to 34% (TRI) and 37% (GL-HOSVD) (values were averaged voxelwise over all datasets). In contrast-enhancing lesions, the average number of voxels demonstrating within-tolerance kPL modeling error relative to the total voxels increased from 48% in the original data to 84% (TRI) and 90% (GL-HOSVD), while the number of voxels showing within-tolerance kPB modeling error increased from 0% to 15% (TRI) and 8% (GL-HOSVD).ConclusionPost-processing denoising methods significantly improved the SNR of dynamic HP-13C imaging data, resulting in a greater number of voxels satisfying minimum SNR criteria and maximum kinetic modeling errors in tumor lesions. This enhancement can aid in the voxel-wise analysis of HP-13C data and thereby improve monitoring of metabolic changes in patients with glioma following treatment.

Abstract INTRODUCTION Mutations in isocitrate dehydrogenase (IDH) have been investigated as a prognostic biomarker in glioma. The presence of the IDH mutation (IDHm) is associated with 2-hydroxyglutarate (2HG) production and inhibition of glutamate synthesis (McBrayer, Cell 2018). Hyperpolarized carbon-13 (HP-13C) MRI enables dynamic measurements of in-vivo metabolism using a [2-13C]pyruvate labeled probe that undergoes conversion to [2-13C]lactate and [5-13C]glutamate. Here, we present HP [2-13C]pyruvate data from healthy volunteers and patients with IDHm diffuse glioma. Due to its intrinsic low signal-to-noise ratio (SNR), we demonstrate the ability of post-processing denoising to improve its utility and aid in detection of metabolic changes associated with IDHm. METHODS Dynamic HP 13C data were acquired following intravenous injection of [2-13C]pyruvate from five healthy volunteers and one patient with IDHm grade III astrocytoma. A novel multi-resolution frequency specific multislice EPI sequence was used to obtain [2-13C]pyruvate, [5-13C]glutamate, and downfield and upfield [2-13C]lactate signals (3s temporal resolution, pyruvate/lactate/glutamate spatial resolutions = 0.75x0.75cm2/ 2.25x2.25cm2/ 2.25x2.25cm2, 5 slices 3cm thick). Following phase correction, patch-based tensor decomposition denoising was applied to metabolite images. Metabolite differences between normal-appearing white matter (NAWM) and T2 lesion were examined for the patient data. RESULTS HP [2-13C]pyruvate imaging is able to simultaneously probe glycolytic ([2-13C]lactate) and oxidative ([5-13C]glutamate) metabolism. Denoised pyruvate/lactate/glutamate signals achieved a 4-9/3-6/3-7 fold increase in SNR. T2 lesion exhibited decreased glutamate-to-pyruvate and glutamate-to-lactate AUC ratios versus contralateral NAWM (p< 0.018, p < 1.5e-5), consistent with IDH mutant status. CONCLUSION We successfully demonstrated the feasibility of applying variable resolution HP [2-13C]pyruvate metabolic imaging to detect IDHm specific metabolism. This technique addresses a major hurdle in HP 13C MRI by improving SNR while permitting robust metabolism quantification. Future studies will optimize methods for acquiring and processing data to evaluate further data acquired from IDHm glioma patients. Supported by NIH T32 CA151022, P01 CA118816, and NICO.

BackgroundThe mechanistic basis for neurocognitive deficits in central nervous system (CNS) lymphoma and other brain tumors is incompletely understood. We tested the hypothesis that tumor metabolism impairs neurotransmitter pathways and neurocognitive function.MethodsWe performed serial cerebrospinal fluid (CSF) metabolomic analyses using liquid chromatography-electrospray tandem mass spectrometry to evaluate changes in the tumor microenvironment in 14 patients with recurrent CNS lymphoma, focusing on 18 metabolites involved in neurotransmission and bioenergetics. These were paired with serial mini-mental state examination (MMSE) and MRI studies for tumor volumetric analyses. Patients were analyzed in the setting of the phase I trial of lenalidomide/rituximab. Associations were assessed by Pearson and Spearman correlation coefficient. Generalized estimating equation (GEE) models were also established, adjusting for within-subject repeated measures.ResultsOf 18 metabolites, elevated CSF lactate correlated most strongly with lower MMSE score (P < 8E-8, ρ = -0.67). High lactate was associated with lower gamma-aminobutyric acid (GABA), higher glutamate/GABA ratio, and dopamine. Conversely, high succinate correlated with higher MMSE scores. Serial analysis demonstrated a reproducible, time-dependent, reciprocal correlation between changes in lactate and GABA concentrations. While high lactate and low GABA correlated with tumor contrast-enhancing volume, they correlated more significantly with lower MMSE scores than tumor volumes.ConclusionsWe provide evidence that lactate production and Warburg metabolism may impact neurotransmitter dysregulation and neurocognition in CNS lymphomas. We identify novel metabolomic biomarkers that may be applied in future studies of neurocognition in CNS lymphomas. Elucidation of mechanistic interactions between lymphoma metabolism, neurotransmitter imbalance, and neurocognition may promote interventions that preserve cognitive function.

Abstract BACKGROUND The overall prognostic significance of maximal surgical resection in patients with diffuse low-grade glioma has been well established. Nonetheless, prior studies omit the combined importance of molecular subclass, patient characteristics, and chemoradiation. Similar to findings recently published in newly diagnosed glioblastoma, incorporation of these interactive factors may redefine the relative benefit of cytoreductive surgery. METHODS We examine the interactive effects of volumetric extent of resection with molecular and clinical factors to develop a new roadmap for cytoreductive surgery. Based on a 20-year retrospective cohort of 556 patients with WHO II diffuse low-grade glioma treated with surgery at UCSF 444 had complete records for survival modeling and recursive partitioning (RPA) to investigate multivariate relationships of overall and progression free survival. RESULTS Regardless of molecular subtype, patients with tumor volume under 55cm3 and postoperative volume of residual under 1.9cm3 experience the longest OS (median OS: not reached). Patients with volume of residual over 1.9cm3 experience a OS similar to that of patients with large (over 55cm3) oligodendrogliomas (median OS: not reached). Patients faring worst have large (over 55cm3) astrocytic gliomas (median OS: 84.8 months). Patients not treated with chemotherapy and either ATRX wild-type tumors or ATRX-mutant tumors with small (under 1cm3) volume of residual have the longest PFS together with chemotherapy treated patients who receive either no radiation or radiation for p53-mutant tumors under 30cm3 (median PFS 119 months). Patients with the shortest PFS are under 32-years with larger volume of residual (>1cm3), who receive no chemotherapy for ATRX-mutant tumors together with patients who receive both chemoradiation for larger (>30cm3) p53 mutant tumors (median PFS 30.8 months). CONCLUSION This is the first study to combine extent of resection with molecular and clinical information which paves the way for rethinking surgical strategies for individual patients with newly diagnosed low-grade gliomas.

Abstract BACKGROUND The prognostic importance of maximal resection of contrast enhancing and non-contrast enhancing disease has been established. Nonetheless, glioblastomas exist within the framework of complex neural circuitry serving cognition, movement, and behavior consequential leading to neurological impairments. The prognostic importance of neurological impairments on survival remains poorly understood. METHODS This is a retrospective, single cohort study from UCSF including 316 eligible patients diagnosed over 20 years with 9.6 years of follow-up. All patients underwent surgical resection for newly diagnosed glioblastoma for whom survival, molecular, preoperative and postoperative MRI images, and clinical data were available. All patients had chemoradiation treated IDH-wild-type glioblastoma with available preoperative and 1-month post-surgical resection neurological outcomes. We employed survival models and recursive partitioning (RPA) to investigate multivariate relationships of overall survival (OS). RESULTS Preoperative neurological impairments were present in 75.6% (n= 239) and new post resection impairments were identified in 37.3% (n=117). Univariate analysis confirmed that new postoperative cognitive impairment [HR 7.91, 95% CI 2.47-25.33] and hemiplegia [HR 3.38, 95% CI 0.83-13.67] (not hemiparesis) impact OS. Risk stratified grouping by RPA demonstrated that gross total resection of contrast enhancing tumor in patients with no new postoperative neurological impairments confers the longest OS (median OS 27.1 months 95%CI 21.5-33.7). Patients with any residual tumor volume after surgery but no new neurological deficits experience a similar survival to younger patients (under 65) with 1 or more new postoperative neurological deficits (median OS 16.6 months 95%CI 15.2-19.2). Shortest OS is identified in patients with any volume of residual tumor plus 1 or more new postoperative neurological deficits and age over 65 (median OS 11.4 months, 95%CI 9.3-13.5). CONCLUSIONS This study confirms that new postoperative neurological impairments impact overall survival in patients with chemoradiation treated IDH-wild-type glioblastoma.

Abstract INTRODUCTION Detecting radiological response or resistance to treatment in patients with GBM is difficult with conventional MRI. In response to this challenge, hyperpolarized carbon-13 (HP-13C) MRI techniques were developed to probe real-time [1-13C]pyruvate metabolism. METHODS Dynamic HP-13C MRI was acquired pre-operatively from 6 patientswith recurrent GBM following intravenous injection of HP [1-13C]pyruvate. Five were confirmed with tumor progression and one had treatment effects without progression. Frequency-selective echo-planar imaging (8 slices, 3s temporal resolution, 3.38 cm3 spatial resolution, 60s acquisition) captured [1-13C]pyruvate metabolism to [1-13C]lactate and [1-13C]bicarbonate in the brain. Proton imaging included 3-D FLAIR, T1-weighted post-Gd IRSPGR, and spectroscopy. Carbon-13 voxels with non-enhancing lesion (NEL) or contrast-enhancing lesion (CEL) were identified for subsequent analysis. Temporally-summed HP-13C metabolite data within the CEL and NEL were evaluated using the pyruvate-to-lactate ratio; a modified ratio that takes into account vascular contributions of pyruvate; and parameter percentile ranks over the entire brain. Proton spectroscopy data were processed to obtain choline-to-NAA index (CNI) maps, which provide z-scores of relative tissue abnormality. RESULTS All of the anatomic lesions displayed abnormal CNI with maximum values of 3.22-6.35. The 5 patients with CEL lesions demonstrated 87th– 98thpercentile levels of pyruvate in the brain; and 95th-100thpercentile levels of lactate in 4 progressed patients and 60thpercentile in the patient presenting with treatment effects. For the patient with an exclusively non-enhancing lesion, percentile levels of pyruvate and lactate were 66thand 88thin the brain, respectively. The mean+/-SD percentile of the lactate-to-pyruvate and modified ratios were 75+/-22, 86+/-23 and 60+/-3, 71+/-12 in the progressed and non-progressed patients, respectively. CONCLUSION These data importantly demonstrate aberrant [1-13C]pyruvate metabolism in patients with GBM in both contrast-enhancing and non-enhancing lesions. Ongoing studies will further characterize the utility of HP imaging markers.

ObjectivesTreatment-induced lesions represent a great challenge in neuro-oncology. The aims of this study were (i) to characterize treatment induced lesions in glioblastoma patients treated with chemoradiotherapy and heat-shock protein (HSP) vaccine and (ii) to evaluate the diagnostic accuracy of diffusion weighted imaging for differentiation between treatment-induced lesions and tumor progression.MethodsTwenty-seven patients with newly diagnosed glioblastoma treated with HSP vaccine and chemoradiotherapy were included. Serial magnetic resonance imaging evaluation was performed to detect treatment-induced lesions and assess their growth. Quantitative analysis of the apparent diffusion coefficient (ADC) was performed to discriminate treatment-induced lesions from tumor progression. Mann-Whitney U-test and receiver operating characteristic (ROC) curves were used for analysis.ResultsThirty-three percent of patients developed treatment-induced lesions. Five treatment-related lesions appeared between end of radiotherapy and the first vaccine administration; 4 lesions within the first 4 months from vaccine initiation and 1 at 3.5 years. Three patients with pathology proven treatment-induced lesions showed a biphasic growth pattern progressed shortly after. ADC ratio between the peripheral enhancing rim and central necrosis showed an accuracy of 0.84 (95% CI 0.63-1) for differentiation between progression and treatment-induced lesions.ConclusionOur findings do not support the iRANO recommendation of a 6-month time window in which progressive disease should not be declared after immunotherapy initiation. A biphasic growth pattern of pathologically proven treatment-induced lesions was associated with a dismal prognosis. The presence of lower ADC values in the central necrotic portion of the lesions compared to the enhancing rim shows high specificity for detection of treatment-induced lesions.

BackgroundHyperpolarized carbon-13 (HP-13C) MRI is a non-invasive imaging technique for probing brain metabolism, which may improve clinical cancer surveillance. This work aimed to characterize the consistency of serial HP-13C imaging in patients undergoing treatment for brain tumors and determine whether there is evidence of aberrant metabolism in the tumor lesion compared to normal-appearing tissue.MethodsSerial dynamic HP [1-13C]pyruvate MRI was performed on 3 healthy volunteers (6 total examinations) and 5 patients (21 total examinations) with diffuse infiltrating glioma during their course of treatment, using a frequency-selective echo-planar imaging (EPI) sequence. HP-13C imaging at routine clinical timepoints overlapped treatment, including radiotherapy (RT), temozolomide (TMZ) chemotherapy, and anti-angiogenic/investigational agents. Apparent rate constants for [1-13C]pyruvate conversion to [1-13C]lactate (kPL) and [13C]bicarbonate (kPB) were simultaneously quantified based on an inputless kinetic model within normal-appearing white matter (NAWM) and anatomic lesions defined from 1H MRI. The inter/intra-subject consistency of kPL-NAWM and kPB-NAWM was measured in terms of the coefficient of variation (CV).ResultsWhen excluding scans following anti-angiogenic therapy, patient values of kPL-NAWM and kPB-NAWM were 0.020 s-1 ± 23.8% and 0.0058 s-1 ± 27.7% (mean ± CV) across 17 HP-13C MRIs, with intra-patient serial kPL-NAWM/kPB-NAWM CVs ranging 6.8-16.6%/10.6-40.7%. In 4/5 patients, these values (0.018 s-1 ± 13.4% and 0.0058 s-1 ± 24.4%; n = 13) were more similar to those from healthy volunteers (0.018 s-1 ± 5.0% and 0.0043 s-1 ± 12.6%; n = 6) (mean ± CV). The anti-angiogenic agent bevacizumab was associated with global elevations in apparent rate constants, with maximum kPL-NAWM in 2 patients reaching 0.047 ± 0.001 and 0.047 ± 0.003 s-1 (±model error). In 3 patients with progressive disease, anatomic lesions showed elevated kPL relative to kPL-NAWM of 0.024 ± 0.001 s-1 (±model error) in the absence of gadolinium enhancement, and 0.032 ± 0.008, 0.040 ± 0.003 and 0.041 ± 0.009 s-1 with gadolinium enhancement. The lesion kPB in patients was reduced to unquantifiable values compared to kPB-NAWM.ConclusionSerial measures of HP [1-13C]pyruvate metabolism displayed consistency in the NAWM of healthy volunteers and patients. Both kPL and kPB were globally elevated following bevacizumab treatment, while progressive disease demonstrated elevated kPL in gadolinium-enhancing and non-enhancing lesions. Larger prospective studies with homogeneous patient populations are planned to evaluate metabolic changes following treatment.

Abstract Although the overall prognostic significance of maximal surgical resection of contrast-enhancing tumor in glioblastoma patients is well established, prior studies have not evaluated the combined importance of resection, molecular markers, patient characteristics, and chemoradiation. Incorporation of these factors may redefine the relative benefit of cytoreductive surgery and establish differing thresholds for extent of resection in varying clinical presentations. In the first study of its kind, we examine the interactive effects of volumetric extent of resection with molecular and clinical factors to develop a new roadmap for cytoreductive surgery. Based on a 20-year retrospective cohort of 850 glioblastoma patients who had initial surgery at UCSF, we employed survival models and recursive partitioning (RPA) to investigate multivariate relationships of overall survival (OS), both in the entire cohort as well as a subset diagnosed since 2005 (Stupp-era) with IDH1 mutation status available (n=470). For the entire cohort and the Stupp-era subset, the RPAs elucidate the combinatorial consequence of treatment, age, IDH1 status (in the subset), and resection of both enhancing and non-enhancing tumor. In the Stupp-era, temozolomide-treated patients that are IDH-wildtype and >65 clearly benefit from a reduction of the enhancing tumor (median OS: 10.1 vs 15.8 months). IDH-wildtype, temozolomide-treated patients under 65 benefit from reduction of both enhancing and non-enhancing tumor with a median survival similar to that of IDH-mutant, temozolomide-treated patients (combined median OS: 33.7 months). The patients faring worst are those that did not receive temozolomide that are >65 and/or have ≥0.3 cm3 residual enhancing tumor (median OS: 4 months). These risk models outperform all published prognostic models. This is the first study to combine resection of contrast-enhancing and non-enhancing tumor in conjunction with molecular and clinical information in a large single-institution study, and paves the way for rethinking surgical strategies for individual patients with newly diagnosed glioblastoma.

Abstract INTRODUCTION: The safety and efficacy of a heat shock protein peptide complex- 96 vaccine (HSPPC-96, Prophage) has been previously studied in phase II single-arm trials for the treatment of newly diagnosed and recurrent glioblastoma (GBM). These studies demonstrated modest improvements in survival compared with historical standards. PTEN loss has been recently associated with immunoresistance in GBM patients, mediated in part by B7-H1. PTEN status has not shown clear prognostic value in GBM patients treated with standard of care therapies. The aim of this study is to evaluate the prognostic significance of PTEN status in newly diagnosed GBM patients treated with autologous HSP vaccine and standard chemoradiation. METHODS Our institutional cohort of patients enrolled in a single arm, phase II study of adult GBM patients treated with autologous HSP vaccine and standard chemoradiation (n=27) was analyzed. Differences in overall survival (OS) by PTEN status were evaluated via Kaplan-Meier curves and Log-rank test. RESULTS Median overall survival (n=27) was 26 months. 23 patients had PTEN status available. PTEN loss was found in 16 patients (69.6%) whereas retained PTEN was present in 7 patients (30.4%). Median OS was 59 months (95% CI, 0–120 months) in patients with retained PTEN and 23 months (95% CI, 15–30 months) in patients with PTEN loss. The difference in OS was statistically significant (p=0.037). CONCLUSION: Retained PTEN expression was associated with extended survival in GBM patients treated with HSP vaccine. This finding suggests that PTEN loss may be associated with resistance to vaccine treatment and emphasizes the need for subgroup analysis in further immunotherapy studies.

Three-dimensional proton magnetic resonance spectroscopic imaging (MRSI) is a powerful non-invasive tool for characterizing spatial variations in metabolic profiles for patients with glioma. Metabolic parameters obtained using this technique have been shown to predict treatment response, disease progression, and transformation to a more malignant phenotype. The availability of ultra-high-field MR systems has the potential to improve the characterization of metabolites. The purpose of this study was to compare the metabolite profiles acquired with conventional long echo time (TE) MRSI at 3T with those obtained with short TE MRSI at 3T and 7T in patients with glioma. The data acquisition parameters were optimized separately for each echo time and field strength to obtain volumetric coverage within clinically feasible data acquisition times of 5-10 min. While a higher field strength did provide better detection of metabolites with overlapping peaks, spatial coverage was reduced and the use of inversion recovery to reduce lipid precluded the detection of lipid in regions of necrosis. For serial evaluation of large, heterogeneous lesions, the use of 3T short TE MRSI may thus be preferred. Despite the limited number of metabolites that it is able to detect, the use of 3T long TE MRSI gives the best contrast in choline/N-acetyl aspartate between normal appearing brain and tumor and also allows the separate detection of lactate and lipid. It may therefore be preferred for serial evaluation of patients with high-grade glioma and for detection of malignant transformation in patients with low-grade 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 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.

Although fully automated volumetric approaches for monitoring brain tumor response have many advantages, most available deep learning models are optimized for highly curated, multi-contrast MRI from newly diagnosed gliomas, which are not representative of post-treatment cases in the clinic. Improving segmentation for treated patients is critical to accurately tracking changes in response to therapy. We investigated mixing data from newly diagnosed (n = 208) and treated (n = 221) gliomas in training, applying transfer learning (TL) from pre- to post-treatment imaging domains, and incorporating spatial regularization for T2-lesion segmentation using only T2 FLAIR images as input to improve generalization post-treatment. These approaches were evaluated on 24 patients suspected of progression who had received prior treatment. Including 26% of treated patients in training improved performance by 13.9%, and including more treated and untreated patients resulted in minimal changes. Fine-tuning with treated glioma improved sensitivity compared to data mixing by 2.5% (p < 0.05), and spatial regularization further improved performance when used with TL by 95th HD, Dice, and sensitivity (6.8%, 0.8%, 2.2%; p < 0.05). While training with ≥60 treated patients yielded the majority of performance gain, TL and spatial regularization further improved T2-lesion segmentation to treated gliomas using a single MR contrast and minimal processing, demonstrating clinical utility in response assessment. [ABSTRACT FROM AUTHOR]

Simple Summary: Dynamic hyperpolarized carbon-13 (HP-13C) MRI is a novel molecular imaging technique that allows for real-time in vivo imaging of glycolysis and oxidative phosphorylation using [1-13C]pyruvate as a non-radioactive and non-toxic metabolic probe. While HP-13C MRI has recently demonstrated the potential to capture Warburg-related metabolic dysregulation in patients with progressive/treatment-naïve high-grade gliomas, further improvement in methodologies is still necessary to help monitor disease status and evaluate early predictors of therapeutic response. To this end, a multimodal 1H/HP-13C MRI protocol was implemented in this study, which incorporated advanced brain tumor MR acquisitions and improved HP-13C metabolic imaging methodologies for the serial monitoring of patients with glioma over the course of clinical treatment. This study aimed to implement a multimodal 1H/HP-13C imaging protocol to augment the serial monitoring of patients with glioma, while simultaneously pursuing methods for improving the robustness of HP-13C metabolic data. A total of 100 1H/HP [1-13C]-pyruvate MR examinations (104 HP-13C datasets) were acquired from 42 patients according to the comprehensive multimodal glioma imaging protocol. Serial data coverage, accuracy of frequency reference, and acquisition delay were evaluated using a mixed-effects model to account for multiple exams per patient. Serial atlas-based HP-13C MRI demonstrated consistency in volumetric coverage measured by inter-exam dice coefficients (0.977 ± 0.008, mean ± SD; four patients/11 exams). The atlas-derived prescription provided significantly improved data quality compared to manually prescribed acquisitions (n = 26/78; p = 0.04). The water-based method for referencing [1-13C]-pyruvate center frequency significantly reduced off-resonance excitation relative to the coil-embedded [13C]-urea phantom (4.1 ± 3.7 Hz vs. 9.9 ± 10.7 Hz; p = 0.0007). Significantly improved capture of tracer inflow was achieved with the 2-s versus 5-s HP-13C MRI acquisition delay (p = 0.007). This study demonstrated the implementation of a comprehensive multimodal 1H/HP-13C MR protocol emphasizing the monitoring of steady-state/dynamic metabolism in patients with glioma. [ABSTRACT FROM AUTHOR]