Glioblastoma evolution and heterogeneity from a 3D whole-tumor perspective.

Treatment failure for the lethal brain tumor glioblastoma (GBM) is attributed to intratumoral heterogeneity and tumor evolution. We utilized 3D neuronavigation during surgical resection to acquire samples representing the whole tumor mapped by 3D spatial coordinates. Integrative tissue and single-cell analysis revealed sources of genomic, epigenomic, and microenvironmental intratumoral heterogeneity and their spatial patterning. By distinguishing tumor-wide molecular features from those with regional specificity, we inferred GBM evolutionary trajectories from neurodevelopmental lineage origins and initiating events such as chromothripsis to emergence of genetic subclones and spatially restricted activation of differential tumor and microenvironmental programs in the core, periphery, and contrast-enhancing regions. Our work depicts GBM evolution and heterogeneity from a 3D whole-tumor perspective, highlights potential therapeutic targets that might circumvent heterogeneity-related failures, and establishes an interactive platform enabling 360° visualization and analysis of 3D spatial patterns for user-selected genes, programs, and other features across whole GBM tumors.

Quantitative Assessment of Preanalytic Variables on Clinical Evaluation of PI3/AKT/mTOR Signaling Activity in Diffuse Glioma.

Biomarker-driven therapeutic clinical trials require the implementation of standardized, evidence-based practices for sample collection. In diffuse glioma, phosphatidylinositol 3 (PI3)-kinase/AKT/mTOR (PI3/AKT/mTOR) signaling is an attractive therapeutic target for which window-of-opportunity clinical trials could facilitate the identification of promising new agents. Yet, the relevant preanalytic variables and optimal tumor sampling methods necessary to measure pathway activity are unknown. To address this, we used a murine model for isocitrate dehydrogenase (IDH)-wildtype glioblastoma (GBM) and human tumor tissue, including IDH-wildtype GBM and IDH-mutant diffuse glioma. First, we determined the impact of delayed time-to-formalin fixation, or cold ischemia time (CIT), on the quantitative assessment of cellular expression of 6 phosphoproteins that are readouts of PI3K/AK/mTOR activity (phosphorylated-proline-rich Akt substrate of 40 kDa (p-PRAS40, T246), -mechanistic target of rapamycin (p-mTOR; S2448); -AKT (p-AKT, S473); -ribosomal protein S6 (p-RPS6, S240/244 and S235/236), and -eukaryotic initiation factor 4E-binding protein 1 (p-4EBP1, T37/46). With CITs ≥ 2 hours, typical of routine clinical handling, all had reduced or altered expression with p-RPS6 (S240/244) exhibiting relatively greater stability. A similar pattern was observed using patient tumor samples from the operating room with p-4EBP1 more sensitive to delayed fixation than p-RPS6 (S240/244). Many clinical trials utilize unstained slides for biomarker evaluation. Thus, we evaluated the impact of slide storage conditions on the detection of p-RPS6 (S240/244), p-4EBP1, and p-AKT. After 5 months, storage at -80°C was required to preserve the expression of p-4EBP1 and p-AKT, whereas p-RPS6 (240/244) expression was not stable regardless of storage temperature. Biomarker heterogeneity impacts optimal tumor sampling. Quantification of p-RPS6 (240/244) expression in multiple regionally distinct human tumor samples from 8 patients revealed significant intratumoral heterogeneity. Thus, the accurate assessment of PI3K/AKT/mTOR signaling in diffuse glioma must overcome intratumoral heterogeneity and multiple preanalytic factors, including time-to-formalin fixation, slide storage conditions, and phosphoprotein of interest.

Spectroscopic imaging of D-2-hydroxyglutarate and other metabolites in pre-surgical patients with IDH-mutant lower-grade gliomas.

PURPOSE: Prognostically 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). METHODS: Forty-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. RESULTS: Quantifiable 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 < 0.05), all of which exhibited higher proportions of astrocytomas. Compared to NAWM, T2 lesions displayed elevated 2HG+ γ-aminobutyric acid (GABA)/total creatine (tCr) (p < 0.001); reduced glutamate/tCr (p < 0.001); increased myo-inositol/tCr (p < 0.001); and higher tCho/tCr (p < 0.001). Levels of 2HG at sampled tissue locations were significantly associated with tCho (R = 0.62; p = 0.002), total NAA (R = - 0.61; p = 0.002) and cellularity (R = 0.37; p = 0.04) but not MIB-1. Increasing levels of 2HG/tCr (p = 0.0007, HR 5.594) and thresholding (≥ 0.905, median value; p = 0.02) predicted adverse PFS. CONCLUSION: In vivo 2HG detection can reasonably be achieved on clinical scanners and increased levels may signal adverse PFS.

Simultaneous multi-slice spin- and gradient-echo dynamic susceptibility-contrast perfusion-weighted MRI of gliomas.

Although combined spin- and gradient-echo (SAGE) dynamic susceptibility-contrast (DSC) MRI can provide perfusion quantification that is sensitive to both macrovessels and microvessels while correcting for T1 -shortening effects, spatial coverage is often limited in order to maintain a high temporal resolution for DSC quantification. In this work, we combined a SAGE echo-planar imaging (EPI) sequence with simultaneous multi-slice (SMS) excitation and blipped controlled aliasing in parallel imaging (blipped CAIPI) at 3 T to achieve both high temporal resolution and whole brain coverage. Two protocols using this sequence with multi-band (MB) acceleration factors of 2 and 3 were evaluated in 20 patients with treated gliomas to determine the optimal scan parameters for clinical use. ΔR2 *(t) and ΔR2 (t) curves were derived to calculate dynamic signal-to-noise ratio (dSNR), ΔR2 *- and ΔR2 -based relative cerebral blood volume (rCBV), and mean vessel diameter (mVD) for each voxel. The resulting SAGE DSC images acquired using MB acceleration of 3 versus 2 appeared visually similar in terms of image distortion and contrast. The difference in the mean dSNR from normal-appearing white matter (NAWM) and that in the mean dSNR between NAWM and normal-appearing gray matter were not statistically significant between the two protocols. ΔR2 *- and ΔR2 -rCBV maps and mVD maps provided unique contrast and spatial heterogeneity within tumors.

Treatment-induced lesions in newly diagnosed glioblastoma patients undergoing chemoradiotherapy and heat-shock protein vaccine therapy.

OBJECTIVES: Treatment-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. METHODS: Twenty-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. RESULTS: Thirty-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. CONCLUSION: Our 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.

Improving the Generalizability of Deep Learning for T2-Lesion Segmentation of Gliomas in the Post-Treatment Setting.

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.

Advanced Hyperpolarized 13C Metabolic Imaging Protocol for Patients with Gliomas: A Comprehensive Multimodal MRI Approach.

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.

Multi-parametric hyperpolarized 13C/1H imaging reveals Warburg-related metabolic dysfunction and associated regional heterogeneity in high-grade human gliomas.

BACKGROUND: Dynamic 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. METHODS: Multi-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. RESULTS: Regional 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. CONCLUSIONS: GBM consistently displayed aberrant, Warburg-related metabolism and regional heterogeneity detectable by novel HP-13C/1H imaging techniques.

Interactive Effects of Molecular, Therapeutic, and Patient Factors on Outcome of Diffuse Low-Grade Glioma.

PURPOSE: In 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. METHODS: In 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. RESULTS: Recursive 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. CONCLUSION: Across 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.

Assessment of higher-order singular value decomposition denoising methods on dynamic hyperpolarized [1-13C]pyruvate MRI data from patients with glioma.

BACKGROUND: Real-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. METHODS: Dynamic 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. RESULTS: Both 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). CONCLUSION: Post-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.

Improving the noninvasive classification of glioma genetic subtype with deep learning and diffusion-weighted imaging.

BACKGROUND: Diagnostic 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. METHODS: Our 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. RESULTS: The 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. CONCLUSION: Training 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.

Tumor metabolism and neurocognition in CNS lymphoma.

BACKGROUND: The 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. METHODS: We 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. RESULTS: Of 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. CONCLUSIONS: We 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.

Recurrent tumor and treatment-induced effects have different MR signatures in contrast enhancing and non-enhancing lesions of high-grade gliomas.

BACKGROUND: Differentiating treatment-induced injury from recurrent high-grade glioma is an ongoing challenge in neuro-oncology, in part due to lesion heterogeneity. This study aimed to determine whether different MR features were relevant for distinguishing recurrent tumor from the effects of treatment in contrast-enhancing lesions (CEL) and non-enhancing lesions (NEL). METHODS: This prospective study analyzed 291 tissue samples (222 recurrent tumor, 69 treatment-effect) with known coordinates on imaging from 139 patients who underwent preoperative 3T MRI and surgery for a suspected recurrence. 8 MR parameter values were tested from perfusion-weighted, diffusion-weighted, and MR spectroscopic imaging at each tissue sample location for association with histopathological outcome using generalized estimating equation models for CEL and NEL tissue samples. Individual cutoff values were evaluated using receiver operating characteristic curve analysis with 5-fold cross-validation. RESULTS: In tissue samples obtained from CEL, elevated relative cerebral blood volume (rCBV) was associated with the presence of recurrent tumor pathology (P < 0.03), while increases in normalized choline (nCho) and choline-to-NAA index (CNI) were associated with the presence of recurrent tumor pathology in NEL tissue samples (P < 0.008). A mean CNI cutoff value of 2.7 had the highest performance, resulting in mean sensitivity and specificity of 0.61 and 0.81 for distinguishing treatment-effect from recurrent tumor within the NEL. CONCLUSION: Although our results support prior work that underscores the utility of rCBV in distinguishing the effects of treatment from recurrent tumor within the contrast enhancing lesion, we found that metabolic parameters may be better at differentiating recurrent tumor from treatment-related changes in the NEL of high-grade gliomas.

Characterization of serial hyperpolarized 13C metabolic imaging in patients with glioma.

BACKGROUND: Hyperpolarized 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. METHODS: Serial 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). RESULTS: When 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. CONCLUSION: Serial 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.

Association of Maximal Extent of Resection of Contrast-Enhanced and Non-Contrast-Enhanced Tumor With Survival Within Molecular Subgroups of Patients With Newly Diagnosed Glioblastoma.

Importance: Per the World Health Organization 2016 integrative classification, newly diagnosed glioblastomas are separated into isocitrate dehydrogenase gene 1 or 2 (IDH)-wild-type and IDH-mutant subtypes, with median patient survival of 1.2 and 3.6 years, respectively. Although maximal resection of contrast-enhanced (CE) tumor is associated with longer survival, the prognostic importance of maximal resection within molecular subgroups and the potential importance of resection of non-contrast-enhanced (NCE) disease is poorly understood. Objective: To assess the association of resection of CE and NCE tumors in conjunction with molecular and clinical information to develop a new road map for cytoreductive surgery. Design, Setting, and Participants: This retrospective, multicenter cohort study included a development cohort from the University of California, San Francisco (761 patients diagnosed from January 1, 1997, through December 31, 2017, with 9.6 years of follow-up) and validation cohorts from the Mayo Clinic (107 patients diagnosed from January 1, 2004, through December 31, 2014, with 5.7 years of follow-up) and the Ohio Brain Tumor Study (99 patients with data collected from January 1, 2008, through December 31, 2011, with a median follow-up of 10.9 months). Image accessors were blinded to patient groupings. Eligible patients underwent surgical resection for newly diagnosed glioblastoma and had available survival, molecular, and clinical data and preoperative and postoperative magnetic resonance images. Data were analyzed from November 15, 2018, to March 15, 2019. Main Outcomes and Measures: Overall survival. Results: Among the 761 patients included in the development cohort (468 [61.5%] men; median age, 60 [interquartile range, 51.6-67.7] years), younger patients with IDH-wild-type tumors and aggressive resection of CE and NCE tumors had survival similar to that of patients with IDH-mutant tumors (median overall survival [OS], 37.3 [95% CI, 31.6-70.7] months). Younger patients with IDH-wild-type tumors and reduction of CE tumor but residual NCE tumors fared worse (median OS, 16.5 [95% CI, 14.7-18.3] months). Older patients with IDH-wild-type tumors benefited from reduction of CE tumor (median OS, 12.4 [95% CI, 11.4-14.0] months). The results were validated in the 2 external cohorts. The association between aggressive CE and NCE in patients with IDH-wild-type tumors was not attenuated by the methylation status of the promoter region of the DNA repair enzyme O6-methylguanine-DNA methyltransferase. Conclusions and Relevance: This study confirms an association between maximal resection of CE tumor and OS in patients with glioblastoma across all subgroups. In addition, maximal resection of NCE tumor was associated with longer OS in younger patients, regardless of IDH status, and among patients with IDH-wild-type glioblastoma regardless of the methylation status of the promoter region of the DNA repair enzyme O6-methylguanine-DNA methyltransferase. These conclusions may help reassess surgical strategies for individual patients with newly diagnosed glioblastoma.

Comparison between Short and Long Echo Time Magnetic Resonance Spectroscopic Imaging at 3T and 7T for Evaluating Brain Metabolites in Patients with Glioma.

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.