Assessment of therapeutic response and treatment planning for brain tumors using metabolic and physiological MRI

Imaging Role in Diagnosis, Prognosis, and Treatment Response Prediction Associated with High-grade Glioma

Background

Glioma is one of the most drug and radiation-resistant tumors. Gliomas suffer from inter- and intratumor heterogeneity which makes the outcome of similar treatment protocols vary from patient to patient. This article is aimed to overview the potential imaging markers for individual diagnosis, prognosis, and treatment response prediction in malignant glioma. Furthermore, the correlation between imaging findings and biological and clinical information of glioma patients is reviewed.

Materials and Methods

The search strategy in this study is to select related studies from scientific websites such as PubMed, Scopus, Google Scholar, and Web of Science published until 2022. It comprised a combination of keywords such as Biomarkers, Diagnosis, Prognosis, Imaging techniques, and malignant glioma, according to Medical Subject Headings.

Results

Some imaging parameters that are effective in glioma management include: ADC, FA, Ktrans, regional cerebral blood volume (rCBV), cerebral blood flow (CBF), ve, Cho/NAA and lactate/lipid ratios, intratumoral uptake of 18F-FET (for diagnostic application), RD, ADC, ve, vp, Ktrans, CBFT1, rCBV, tumor blood flow, Cho/NAA, lactate/lipid, MI/Cho, uptakes of 18F-FET, 11C-MET, and 18F-FLT (for prognostic and predictive application). Cerebral blood volume and Ktrans are related to molecular markers such as vascular endothelial growth factor (VEGF). Preoperative ADCmin value of GBM tumors is associated with O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status. 2-hydroxyglutarate metabolite and dynamic 18F-FDOPA positron emission tomography uptake are related to isocitrate dehydrogenase (IDH) mutations.

Conclusion

Parameters including ADC, RD, FA, rCBV, Ktrans, vp, and uptake of 18F-FET are useful for diagnosis, prognosis, and treatment response prediction in glioma. A significant correlation between molecular markers such as VEGF, MGMT, and IDH mutations with some diffusion and perfusion imaging parameters has been identified.

Implantable theranostic device for in vivo real-time NMR evaluation of drug impact in brain tumors

The evaluation of the efficacy of a drug is a fundamental step in the development of new treatments or in personalized therapeutic strategies and patient management. Ideally, this evaluation should be rapid, possibly in real time, easy to perform and reliable. In addition, it should be associated with as few adverse effects as possible for the patient. In this study, we present a device designed to meet these goals for assessing therapeutic response. This theranostic device is based on the use of magnetic resonance imaging and spectroscopy for the diagnostic aspect and on the application of the convection-enhanced delivery technique for the therapeutic aspect. The miniaturized device is implantable and can be used in vivo in a target tissue. In this study, the device was applied to rodent glioma models with local administration of choline kinase inhibitor and acquisition of magnetic resonance images and spectra at 7 Tesla. The variations in the concentration of key metabolites measured by the device during the administration of the molecules demonstrate the relevance of the approach and the potential of the device.

In vivo brain MR spectroscopy in gliomas: clinical and pre-clinical chances

Purpose

Gliomas, the most common primary brain tumours, have recently been re-classified incorporating molecular aspects with important clinical, prognostic, and predictive implications. Concurrently, the reprogramming of metabolism, altering intracellular and extracellular metabolites affecting gene expression, differentiation, and the tumour microenvironment, is increasingly being studied, and alterations in metabolic pathways are becoming hallmarks of cancer. Magnetic resonance spectroscopy (MRS) is a complementary, non-invasive technique capable of quantifying multiple metabolites. The aim of this review focuses on the methodology and analysis techniques in proton MRS (1H MRS), including a brief look at X-nuclei MRS, and on its perspectives for diagnostic and prognostic biomarkers in gliomas in both clinical practice and preclinical research.

Methods

PubMed literature research was performed cross-linking the following key words: glioma, MRS, brain, in-vivo, human, animal model, clinical, pre-clinical, techniques, sequences, 1H, X-nuclei, Artificial Intelligence (AI), hyperpolarization.

Results

We selected clinical works (n = 51), preclinical studies (n = 35) and AI MRS application papers (n = 15) published within the last two decades. The methodological papers (n = 62) were taken into account since the technique first description.

Conclusions

Given the development of treatments targeting specific cancer metabolic pathways, MRS could play a key role in allowing non-invasive assessment for patient diagnosis and stratification, predicting and monitoring treatment responses and prognosis. The characterization of gliomas through MRS will benefit of a wide synergy among scientists and clinicians of different specialties within the context of new translational competences. Head coils, MRI hardware and post-processing analysis progress, advances in research, experts’ consensus recommendations and specific professionalizing programs will make the technique increasingly trustworthy, responsive, accessible.

The Use of Treatment Response Assessment Maps in Discriminating Between Radiation Effect and Persistent Tumoral Lesion in Metastatic Brain Tumors Treated with Gamma Knife Radiosurgery

BACKGROUND

Traditional imaging modalities are not useful in the follow-up of irradiated metastatic brain tumors, because radiation can change imaging characteristics. We aimed to assess the ability of treatment response assessment maps (TRAMs) calculated from delayed-contrast magnetic resonance imaging (MRI) in differentiation between radiation effect and persistent tumoral tissue.

METHODS

TRAMs were calculated by subtracting three-dimensional T1 MRIs acquired 5 minutes after contrast injection from the images acquired 60-105 minutes later. Red areas were regarded as radiation effect and blue areas as persistent tumoral lesion. Thirty-seven patients with 130 metastatic brain tumors who were treated with Gamma Knife radiosurgery and who underwent TRAMs perfusion-weighted MRI were enrolled in this retrospective study.

RESULTS

The median age was 58 years and the most common primary diagnosis was lung cancer (n = 21). The median follow-up period of patients was 12 months. The overall local control rate was 100% at 1 year and 98.9% at 2 years. The median progression-free survival was 12 months. The mean overall survival was 27.3 months. The radiologic and clinical follow-up showed a clinicoradiologic diagnosis of a persistent tumoral lesion in 3 tumors (2.3%) and radiation effect in 127 tumors (97.7%). There was a fair agreement between clinicoradiologic diagnosis and TRAMs analysis (κ = 0.380). The sensitivity and positive predictive value of TRAMs in diagnosing radiation effect were 96.06% and 99.2%, respectively. TRAMs showed comparable results to perfusion-weighted MRI, with a diagnostic odds ratio of 27.4 versus 20.7, respectively.

CONCLUSIONS

The presented results show the ability of TRAMs in differentiating radiation effect and persistent tumoral lesions.

Anti-PD-1 Immunotherapy in Preclinical GL261 Glioblastoma: Influence of Therapeutic Parameters and Non-Invasive Response Biomarker Assessment with MRSI-Based Approaches

Glioblastomas (GBs) are malignant brain tumours with poor prognosis even after aggressive therapy. Programmed cell death-1 (PD-1) immune checkpoint blockade is a promising strategy in many types of cancer, but its therapeutic effects in GB remain low and associated with immune infiltration. Previous work suggests that oscillations of magnetic resonance spectroscopic imaging (MRSI)-based response pattern with chemotherapy could act as a biomarker of efficient immune system attack onto GBs. The presence of such oscillations with other monotherapies such as anti-PD-1 would reinforce its monitoring potential. Here, we confirm that the oscillatory behaviour of the response biomarker is also detected in mice treated with anti PD-1 immunotherapy both in combination with temozolomide and as monotherapy. This indicates that the spectral pattern changes observed during therapy response are shared by different therapeutic strategies, provided the host immune system is elicited and able to productively attack tumour cells. Moreover, the participation of the immune system in response is also supported by the rate of cured animals observed with different therapeutic strategies (in the range of 50–100% depending on the treatment), which also held long-term immune memory against tumour cells re-challenge. Taken together, our findings open the way for a translational use of the MRSI-based biomarker in patient-tailored GB therapy, including immunotherapy, for which reliable non-invasive biomarkers are still missing.

Glutamate Is a Noninvasive Metabolic Biomarker of IDH1-Mutant Glioma Response to Temozolomide Treatment

Although lower grade gliomas are driven by mutations in the isocitrate dehydrogenase 1 (IDH1) gene and are less aggressive than primary glioblastoma, they nonetheless generally recur. IDH1-mutant patients are increasingly being treated with temozolomide, but early detection of response remains a challenge and there is a need for complementary imaging methods to assess response to therapy prior to tumor shrinkage. The goal of this study was to determine the value of magnetic resonance spectroscopy (MRS)-based metabolic changes for detection of response to temozolomide in both genetically engineered and patient-derived mutant IDH1 models. Using 1H MRS in combination with chemometrics identified several metabolic alterations in temozolomide-treated cells, including a significant increase in steady-state glutamate levels. This was confirmed in vivo, where the observed 1H MRS increase in glutamate/glutamine occurred prior to tumor shrinkage. Cells labeled with [1-13C]glucose and [3-13C]glutamine, the principal sources of cellular glutamate, showed that flux to glutamate both from glucose via the tricarboxylic acid cycle and from glutamine were increased following temozolomide treatment. In line with these results, hyperpolarized [5-13C]glutamate produced from [2-13C]pyruvate and hyperpolarized [1-13C]glutamate produced from [1-13C]α-ketoglutarate were significantly higher in temozolomide-treated cells compared with controls. Collectively, our findings identify 1H MRS-detectable elevation of glutamate and hyperpolarized 13C MRS-detectable glutamate production from either pyruvate or α-ketoglutarate as potential translatable metabolic biomarkers of response to temozolomide treatment in mutant IDH1 glioma. SIGNIFICANCE: These findings show that glutamate can be used as a noninvasive, imageable metabolic marker for early assessment of tumor response to temozolomide, with the potential to improve treatment strategies for mutant IDH1 patients.

Role of Radiological Intervention in Brain Tumor: A Meta-Analysis

Background

This meta-analysis highlights the diagnostic efficacy of computed tomography (CT), computed tomography angiography (CTA), magnetic resonance image (MRI), as well as magnetic resonance spectroscopy (MRS). This paper assesses the detection of the primary outcome comprising choline/creatine ratio, relative cerebral blood volume (rCBV), as well as choline/N-acetyl aspartate. Cochrane, Medline, ScienceDirect, Google Scholar, and EMBASE databases were searched for extracting the relevant studies.

Methods

A sample of 12 studies on radiologic assessment of brain tumors was selected.

Results

The evidence provides that the heterogeneity exists concerning the CBV of 311.623, I2 = 96.12%, with a significance value of P < 0.001. The pooled difference showed rCBV mean (as 2.18, 95% confidence interval = 0.85 to 3.50) substantially enhances lesion.

Conclusion

The study concluded that radiological interventions, particularly the combination of MRS and MRI, help in the brain patient's precise diagnosis and treatment.

Anti-tumour immune response in GL261 glioblastoma generated by Temozolomide Immune-Enhancing Metronomic Schedule monitored with MRSI-based nosological images

Glioblastomas (GB) are brain tumours with poor prognosis even after aggressive therapy. Improvements in both therapeutic and follow-up strategies are urgently needed. In previous work we described an oscillatory pattern of response to Temozolomide (TMZ) using a standard administration protocol, detected through MRSI-based machine learning approaches. In the present work, we have introduced the Immune-Enhancing Metronomic Schedule (IMS) with an every 6-d TMZ administration at 60 mg/kg and investigated the consistence of such oscillatory behaviour. A total of n = 17 GL261 GB tumour-bearing C57BL/6j mice were studied with MRI/MRSI every 2 d, and the oscillatory behaviour (6.2 ± 1.5 d period from the TMZ administration day) was confirmed during response. Furthermore, IMS-TMZ produced significant improvement in mice survival (22.5 ± 3.0 d for controls vs 135.8 ± 78.2 for TMZ-treated), outperforming standard TMZ treatment. Histopathological correlation was investigated in selected tumour samples (n = 6) analyzing control and responding fields. Significant differences were found for CD3+ cells (lymphocytes, 3.3 ± 2.5 vs 4.8 ± 2.9, respectively) and Iba-1 immunostained area (microglia/macrophages, 16.8% ± 9.7% and 21.9% ± 11.4%, respectively). Unexpectedly, during IMS-TMZ treatment, tumours from some mice (n = 6) fully regressed and remained undetectable without further treatment for 1 mo. These animals were considered "cured" and a GL261 re-challenge experiment performed, with no tumour reappearance in five out of six cases. Heterogeneous therapy response outcomes were detected in tumour-bearing mice, and a selected group was investigated (n = 3 non-responders, n = 6 relapsing tumours, n = 3 controls). PD-L1 content was found ca. 3-fold increased in the relapsing group when comparing with control and non-responding groups, suggesting that increased lymphocyte inhibition could be associated to IMS-TMZ failure. Overall, data suggest that host immune response has a relevant role in therapy response/escape in GL261 tumours under IMS-TMZ therapy. This is associated to changes in the metabolomics pattern, oscillating every 6 d, in agreement with immune cycle length, which is being sampled by MRSI-derived nosological images.

Integration of Three-dimensional Magnetic Resonance Imaging Spectroscopy with the Leksell GammaPlan Radiosurgical Planning Station for the Treatment of Brain Tumors

Introduction

MRI multivoxel spectroscopy mapping is helpful in surgical decision-making. Unfortunately, in daily practice, MRI multivoxel spectroscopy mapping is not always compatible with the current version of Leksell GammaPlan (LGP) (Elekta, Stockholm, Sweden). The aim of this study is to develop a tool to allow the use of this modality in radiosurgical treatments using LGP.

Material and methods

Multivoxel spectroscopy digital imaging and communications in medicine (DICOM) images were analyzed to identify tags to be modified to make the images compatible with LGP. We identify four important tags to be modified for compatibility with LGP. Using Python language, a new software was designed to modify the identified tags and allow the automatic conversion of images to meet LGP requirements.

Results

By modifying the tags of DICOM images, we could use spectroscopic cartography images in radiosurgical planning using LGP. We created a software to reproduce these modifications using a simple and rapid interface. This software executes all the protocols established in the methodology.

Conclusion

The new software, “GP Adapting Solution”, can convert any DICOM image and make it compatible with LGP. The integration of multivoxel spectroscopic images was feasible and could be used for radiosurgical planning. This work is the first step in allowing the potential use of new MRI modalities in radiosurgical planning using LGP. The next steps are to evaluate the impact of these modalities in radiosurgical treatments and to develop methods for integrating other imaging modalities.

Evaluation of the Implementation of the Response Assessment in Neuro-Oncology Criteria in the HERBY Trial of Pediatric Patients with Newly Diagnosed High-Grade Gliomas

BACKGROUND AND PURPOSE

HERBY was a Phase II multicenter trial setup to establish the efficacy and safety of adding bevacizumab to radiation therapy and temozolomide in pediatric patients with newly diagnosed non-brain stem high-grade gliomas. This study evaluates the implementation of the radiologic aspects of HERBY.

MATERIALS AND METHODS

We analyzed multimodal imaging compliance rates and scan quality for participating sites, adjudication rates and reading times for the central review process, the influence of different Response Assessment in Neuro-Oncology criteria in the final response, the incidence of pseudoprogression, and the benefit of incorporating multimodal imaging into the decision process.

RESULTS

Multimodal imaging compliance rates were the following: diffusion, 82%; perfusion, 60%; and spectroscopy, 48%. Neuroradiologists' responses differed for 50% of scans, requiring adjudication, with a total average reading time per patient of approximately 3 hours. Pseudoprogression occurred in 10/116 (9%) cases, 8 in the radiation therapy/temozolomide arm and 2 in the bevacizumab arm (P < .01). Increased target enhancing lesion diameter was a reason for progression in 8/86 cases (9.3%) but never the only radiologic or clinical reason. Event-free survival was predicted earlier in 5/86 (5.8%) patients by multimodal imaging (diffusion, n = 4; perfusion, n = 1).

CONCLUSIONS

The addition of multimodal imaging to the response criteria modified the assessment in a small number of cases, determining progression earlier than structural imaging alone. Increased target lesion diameter, accounting for a large proportion of reading time, was never the only reason to designate disease progression.

A comparison of coil combination strategies in 3D multi-channel MRSI reconstruction for patients with brain tumors

The goal of this study was to find the most robust algorithm for a phase-sensitive coil combination of 3D single-cycle and lactate-edited, multi-channel H-1 point-resolved spectroscopy (PRESS) localized echo planar spectroscopic imaging (EPSI) data for clinical applications in the brain. Data were acquired over 5-10 minutes at 3T using 8- or 32-channel array coils. Peak referencing with residual water and N-acetyl-aspartate, first-point phasing, generalized least squared (GLS) and whitened singular-value decomposition (WSVD) combination algorithms were evaluated relative to unsuppressed water with data from a phantom, six volunteers and 55 patients with brain tumors. Comparison metrics were signal-to-noise ratio, coefficient of variance and percent signal increase. Where residual water was present, using it as a reference peak for phasing and weighting factors from an imaging calibration scan gave the best overall performance. Greater improvement was seen for large selected volumes (>720 cm³ ) and for the 32-channel array (25%) compared with the 8-channel array (19%). Applying voxel-by-voxel phase corrections produced a larger increase in performance for the 32- versus 8-channel coil. We conclude that, for clinically relevant 3D H-1 PRESS localized EPSI studies, the most robust technique employed individual phase maps generated from high residual water and individual amplitude maps generated from calibration scans.

A comparison of coil combination strategies in 3D multi-channel MRSI reconstruction for patients with brain tumors

The goal of this study was to find the most robust algorithm for a phase-sensitive coil combination of 3D single-cycle and lactate-edited, multi-channel H-1 point-resolved spectroscopy (PRESS) localized echo planar spectroscopic imaging (EPSI) data for clinical applications in the brain. Data were acquired over 5-10 minutes at 3T using 8- or 32-channel array coils. Peak referencing with residual water and N-acetyl-aspartate, first-point phasing, generalized least squared (GLS) and whitened singular-value decomposition (WSVD) combination algorithms were evaluated relative to unsuppressed water with data from a phantom, six volunteers and 55 patients with brain tumors. Comparison metrics were signal-to-noise ratio, coefficient of variance and percent signal increase. Where residual water was present, using it as a reference peak for phasing and weighting factors from an imaging calibration scan gave the best overall performance. Greater improvement was seen for large selected volumes (>720 cm³ ) and for the 32-channel array (25%) compared with the 8-channel array (19%). Applying voxel-by-voxel phase corrections produced a larger increase in performance for the 32- versus 8-channel coil. We conclude that, for clinically relevant 3D H-1 PRESS localized EPSI studies, the most robust technique employed individual phase maps generated from high residual water and individual amplitude maps generated from calibration scans.

A fuzzy feature fusion method for auto-segmentation of gliomas with multi-modality diffusion and perfusion magnetic resonance images in radiotherapy

The diffusion and perfusion magnetic resonance (MR) images can provide functional information about tumour and enable more sensitive detection of the tumour extent. We aimed to develop a fuzzy feature fusion method for auto-segmentation of gliomas in radiotherapy planning using multi-parametric functional MR images including apparent diffusion coefficient (ADC), fractional anisotropy (FA) and relative cerebral blood volume (rCBV). For each functional modality, one histogram-based fuzzy model was created to transform image volume into a fuzzy feature space. Based on the fuzzy fusion result of the three fuzzy feature spaces, regions with high possibility belonging to tumour were generated automatically. The auto-segmentations of tumour in structural MR images were added in final auto-segmented gross tumour volume (GTV). For evaluation, one radiation oncologist delineated GTVs for nine patients with all modalities. Comparisons between manually delineated and auto-segmented GTVs showed that, the mean volume difference was 8.69% (±5.62%); the mean Dice’s similarity coefficient (DSC) was 0.88 (±0.02); the mean sensitivity and specificity of auto-segmentation was 0.87 (±0.04) and 0.98 (±0.01) respectively. High accuracy and efficiency can be achieved with the new method, which shows potential of utilizing functional multi-parametric MR images for target definition in precision radiation treatment planning for patients with gliomas.

Simultaneous QSM and metabolic imaging of the brain using SPICE

PURPOSE

To map brain metabolites and tissue magnetic susceptibility simultaneously using a single three-dimensional 1 H-MRSI acquisition without water suppression.

METHODS

The proposed technique builds on a subspace imaging method called spectroscopic imaging by exploiting spatiospectral correlation (SPICE), which enables ultrashort echo time (TE)/short pulse repetition time (TR) acquisitions for 1 H-MRSI without water suppression. This data acquisition scheme simultaneously captures both the spectral information of brain metabolites and the phase information of the water signals that is directly related to tissue magnetic susceptibility variations. In extending this scheme for simultaneous QSM and metabolic imaging, we increase k-space coverage by using dual density sparse sampling and ramp sampling to achieve spatial resolution often required by QSM, while maintaining a reasonable signal-to-noise ratio (SNR) for the spatiospectral data used for metabolite mapping. In data processing, we obtain high-quality QSM from the unsuppressed water signals by taking advantage of the larger number of echoes acquired and any available anatomical priors; metabolite spatiospectral distributions are reconstructed using a union-of-subspaces model.

RESULTS

In vivo experimental results demonstrate that the proposed method can produce susceptibility maps at a resolution higher than 1.8 × 1.8 × 2.4 mm3 along with metabolite spatiospectral distributions at a nominal spatial resolution of 2.4 × 2.4 × 2.4 mm3 from a single 7-min MRSI scan. The estimated susceptibility values are consistent with those obtained using the conventional QSM method with 3D multi-echo gradient echo acquisitions.

CONCLUSION

This article reports a new capability for simultaneous susceptibility mapping and metabolic imaging of the brain from a single 1 H-MRSI scan, which has potential for a wide range of applications. Magn Reson Med 79:13-21, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Identifying Voxels at Risk for Progression in Glioblastoma Based on Dosimetry, Physiologic and Metabolic MRI

Despite the longstanding role of radiation in cancer treatment and the presence of advanced, high-resolution imaging techniques, delineation of voxels at-risk for progression remains purely a geometric expansion of anatomic images, missing subclinical disease at risk for recurrence while treating potentially uninvolved tissue and increasing toxicity. This remains despite the modern ability to precisely shape radiation fields. A striking example of this is the treatment of glioblastoma, a highly infiltrative tumor that may benefit from accurate identification of subclinical disease. In this study, we hypothesize that parameters from physiologic and metabolic magnetic resonance imaging (MRI) at diagnosis could predict the likelihood of voxel progression at radiographic recurrence in glioblastoma by identifying voxel characteristics that indicate subclinical disease. Integrating dosimetry can reveal its effect on voxel outcome, enabling risk-adapted voxel dosing. As a system example, 24 patients with glioblastoma treated with radiotherapy, temozolomide and an anti-angiogenic agent were analyzed. Pretreatment median apparent diffusion coefficient (ADC), fractional anisotropy (FA), relative cerebral blood volume (rCBV), vessel leakage (percentage recovery), choline-to-NAA index (CNI) and dose of voxels in the T2 nonenhancing lesion (NEL), T1 post-contrast enhancing lesion (CEL) or normal-appearing volume (NAV) of brain, were calculated for voxels that progressed [NAV→NEL, CEL (N = 8,765)] and compared against those that remained stable [NAV→NAV (N = 98,665)]. Voxels that progressed (NAV→NEL) had significantly different (P < 0.01) ADC (860), FA (0.36) and CNI (0.67) versus stable voxels (804, 0.43 and 0.05, respectively), indicating increased cell turnover, edema and decreased directionality, consistent with subclinical disease. NAV→CEL voxels were more abnormal (1,014, 0.28, 2.67, respectively) and leakier (percentage recovery = 70). A predictive model identified areas of recurrence, demonstrating that elevated CNI potentiates abnormal diffusion, even far (>2 cm) from the tumor and dose escalation >45 Gy has diminishing benefits. Integrating advanced MRI with dosimetry can identify at voxels at risk for progression and may allow voxel-level risk-adapted dose escalation to subclinical disease while sparing normal tissue. When combined with modern planning software, this technique may enable risk-adapted radiotherapy in any disease site with multimodal imaging.

In vitro nuclear magnetic resonance spectroscopy metabolic biomarkers for the combination of temozolomide with PI3K inhibition in paediatric glioblastoma cells

Recent experimental data showed that the PI3K pathway contributes to resistance to temozolomide (TMZ) in paediatric glioblastoma and that this effect is reversed by combination treatment of TMZ with a PI3K inhibitor. Our aim is to assess whether this combination results in metabolic changes that are detectable by nuclear magnetic resonance (NMR) spectroscopy, potentially providing metabolic biomarkers for PI3K inhibition and TMZ combination treatment. Using two genetically distinct paediatric glioblastoma cell lines, SF188 and KNS42, in vitro 1H-NMR analysis following treatment with the dual pan-Class I PI3K/mTOR inhibitor PI-103 resulted in a decrease in lactate and phosphocholine (PC) levels (P<0.02) relative to control. In contrast, treatment with TMZ caused an increase in glycerolphosphocholine (GPC) levels (P≤0.05). Combination of PI-103 with TMZ showed metabolic effects of both agents including a decrease in the levels of lactate and PC (P<0.02) while an increase in GPC (P<0.05). We also report a decrease in the protein expression levels of HK2, LDHA and CHKA providing likely mechanisms for the depletion of lactate and PC, respectively. Our results show that our in vitro NMR-detected changes in lactate and choline metabolites may have potential as non-invasive biomarkers for monitoring response to combination of PI3K/mTOR inhibitors with TMZ during clinical trials in children with glioblastoma, subject to further in vivo validation.

Interrogating Metabolism in Brain Cancer

This article reviews existing and emerging techniques of interrogating metabolism in brain cancer from well-established proton magnetic resonance spectroscopy to the promising hyperpolarized metabolic imaging and chemical exchange saturation transfer and emerging techniques of imaging inflammation. Some of these techniques are at an early stage of development and clinical trials are in progress in patients to establish the clinical efficacy. It is likely that in vivo metabolomics and metabolic imaging is the next frontier in brain cancer diagnosis and assessing therapeutic efficacy; with the combined knowledge of genomics and proteomics a complete understanding of tumorigenesis in brain might be achieved.

Diagnostic accuracy of proton magnetic resonance spectroscopy and perfusion-weighted imaging in brain gliomas follow-up: a single institutional experience

Objectives The objective of this study was to evaluate whether proton magnetic resonance spectroscopy and perfusion magnetic resonance imaging (MRI) are able to increase diagnostic accuracy in the follow-up of brain gliomas, identifying the progression of disease before it becomes evident in the standard MRI; also to evaluate which of the two techniques has the best diagnostic accuracy. Methods Eighty-three patients with cerebral glioma (50 high-grade gliomas (HGGs), 33 low-grade gliomas (LGGs)) were retrospectively enrolled. All patients underwent standard MRI, H spectroscopic and perfusion echo-planar imaging MRI. For spectroscopy variations of choline/creatine, choline/N-acetyl-aspartate ratio, and lipids and lactates peak were considered. For perfusion 2.0 was considered the cerebral blood volume cut-off for progression. The combination of functional parameters gave a multiparametric score (0-2) to predict outcome. Diagnostic performance was determined by the receiver operating characteristic curve, with sensitivity, specificity, positive predictive and negative predictive values. Results In patients with LGGs a combined score of at least 1 was the best predictor for progression (odds ratio (OR) 3.91) with 8.4 months median anticipation of diagnosis compared to standard MRI. The individual advanced magnetic resonance technique did not show a diagnostic accuracy comparable to the combination of the two. Overall diagnostic accuracy area under the curve (AUC) was 0.881. In patients with HGGs the multiparametric score did not improve diagnostic accuracy significantly. Perfusion MRI was the best predictor of progression (OR 3.65), with 6.7 months median anticipation of diagnosis. Overall diagnostic accuracy AUC was 0.897. Then spectroscopy and perfusion MRI are able to identify tumour progression during follow-up earlier than standard MRI. Conclusion In patients with LGGs the combination of the functional parameters seems to be the best method for diagnosis of progression. In patients with HGGs perfusion is the best diagnostic method.

Metabolomics of Therapy Response in Preclinical Glioblastoma: A Multi-Slice MRSI-Based Volumetric Analysis for Noninvasive Assessment of Temozolomide Treatment

Glioblastoma (GBM) is the most common aggressive primary brain tumor in adults, with a short survival time even after aggressive therapy. Non-invasive surrogate biomarkers of therapy response may be relevant for improving patient survival. Previous work produced such biomarkers in preclinical GBM using semi-supervised source extraction and single-slice Magnetic Resonance Spectroscopic Imaging (MRSI). Nevertheless, GBMs are heterogeneous and single-slice studies could prevent obtaining relevant information. The purpose of this work was to evaluate whether a multi-slice MRSI approach, acquiring consecutive grids across the tumor, is feasible for preclinical models and may produce additional insight into therapy response. Nosological images were analyzed pixel-by-pixel and a relative responding volume, the Tumor Responding Index (TRI), was defined to quantify response. Heterogeneous response levels were observed and treated animals were ascribed to three arbitrary predefined groups: high response (HR, n = 2), TRI = 68.2 ± 2.8%, intermediate response (IR, n = 6), TRI = 41.1 ± 4.2% and low response (LR, n = 2), TRI = 13.4 ± 14.3%, producing therapy response categorization which had not been fully registered in single-slice studies. Results agreed with the multi-slice approach being feasible and producing an inverse correlation between TRI and Ki67 immunostaining. Additionally, ca. 7-day oscillations of TRI were observed, suggesting that host immune system activation in response to treatment could contribute to the responding patterns detected.

MRI in Glioma Immunotherapy: Evidence, Pitfalls, and Perspectives

Pseudophenomena, that is, imaging alterations due to therapy rather than tumor evolution, have an important impact on the management of glioma patients and the results of clinical trials. RANO (response assessment in neurooncology) criteria, including conventional MRI (cMRI), addressed the issues of pseudoprogression after radiotherapy and concomitant chemotherapy and pseudoresponse during antiangiogenic therapy of glioblastomas (GBM) and other gliomas. The development of cancer immunotherapy forced the identification of further relevant response criteria, summarized by the iRANO working group in 2015. In spite of this, the unequivocal definition of glioma progression by cMRI remains difficult particularly in the setting of immunotherapy approaches provided by checkpoint inhibitors and dendritic cells. Advanced MRI (aMRI) may in principle address this unmet clinical need. Here, we discuss the potential contribution of different aMRI techniques and their indications and pitfalls in relation to biological and imaging features of glioma and immune system interactions.

Nuclear Overhauser Enhancement-Mediated Magnetization Transfer Imaging in Glioma with Different Progression at 7 T

Glioma is a malignant neoplasm affecting the central nervous system. The conventional approaches to diagnosis, such as T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), and contrast-enhanced T1WI, give an oversimplified representation of anatomic structures. Nuclear Overhauser enhancement (NOE) imaging is a special form of magnetization transfer (MT) that provides a new way to detect small solute pools through indirect measurement of attenuated water signals, and makes it possible to probe semisolid macromolecular protons. In this study, we investigated the correlation between the effect of NOE-mediated imaging and progression of glioma in a rat tumor model. We found that the NOE signal decreased in tumor region, and signal of tumor center and peritumoral normal tissue markedly decreased with growth of the glioma. At the same time, NOE signal in contralateral normal tissue dropped relatively late (at about day 16-20 after implanting the glioma cells). NOE imaging is a new contrast method that may provide helpful insights into the pathophysiology of glioma with regard to mobile proteins, lipids, and other metabolites. Further, NOE images differentiate normal brain tissue from glioma tissue at a molecular level. Our study indicates that NOE-mediated imaging is a new and promising approach for estimation of tumor progression.

Glioma Recurrence Versus Radiation Necrosis: Single-Session Multiparametric Approach Using Simultaneous O-(2-18F-Fluoroethyl)-L-Tyrosine PET/MRI

PURPOSE

This study aimed to investigate the potential of hybrid gadolinium (Gd)-enhanced F-fluoroethyl-L-tyrosine (F-FET) PET/MRI in distinguishing recurrence from radiation necrosis using simultaneously acquired multiple structural and functional parameters.

METHODS

Twenty-six patients (5 female and 21 male patients; mean ± SD age, 51.58 ± 15.97 years) with single or multiple contrast-enhancing brain lesions (n = 32) on MRI after surgery and radiation therapy were evaluated with simultaneously acquired Gd-enhanced F-FET PET/MRI. They were then followed up with resurgery and histopathological diagnosis (n = 9) and/or clinical/MRI- or PET/MRI-based imaging follow-up (n = 17). PET/MR images were analyzed using manually drawn regions of interest over areas of maximal contrast enhancement and/or FET uptake. Maximum target-to-background ratio (TBRmax), mean target-to-background ratio (TBRmean), and choline-to-creatine (Cho/Cr) ratios as well as normalized mean relative cerebral blood volume (rCBVmean) and mean apparent diffusion coefficient (ADCmean) were determined. The accuracy of each parameter individually and in various possible combinations for differentiating recurrence versus radiation necrosis was evaluated using 2-tailed independent samples Student t test, multivariate analysis of variance, and multivariate receiver operating characteristic analysis. Positive histopathological finding and long-term imaging/clinical follow-up suggestive of disease progression served as criterion standard.

RESULTS

Of 26 patients, 19 were classified as recurrence, with 7 patients showing radiation necrosis. Individually, TBRmax, TBRmean, ADCmean, and Cho/Cr ratios as well as normalized rCBVmean was significant in differentiating recurrence from radiation necrosis, with an accuracy of 93.8% for TBRmax, 87.5% for TBRmean, 81.3% for ADCmean, 96.9% for Cho/Cr ratio, and 90.6% for normalized rCBVmean. The accuracy of both normalized rCBVmean and ADCmean was improved in combination with TBRmax or Cho/Cr ratio. However, TBRmax (or TBRmean) with Cho/Cr ratio yielded the highest accuracy, approaching up to 97%. Furthermore, maximum area under the curve is achieved with the combination of TBRmean, CBV, and Cho/Cr values.

CONCLUSIONS

Our findings suggest that FET uptake with Cho/Cr ratio and normalized rCBVmean could be most useful to distinguish primary glioma recurrence from radiation necrosis. Hybrid simultaneous multiparametric F-FET PET/MRI might play a significant role in the evaluation of patients with suspected glioma recurrence.

Quantitative T1-mapping detects cloudy-enhancing tumor compartments predicting outcome of patients with glioblastoma

Contrast enhancement of glioblastomas (GBM) is caused by the decrease in relaxation time, T1. Here, we demonstrate that the quantitative measurement of T1 (qT1) discovers a subtle enhancement in GBM patients that is invisible in standard MRI. We assessed the volume change of this “cloudy” enhancement during radio‐chemotherapy and its impact on patients’ progression‐free survival (PFS). We enrolled 18 GBM patients in this observational, prospective cohort study and measured 3T‐MRI pre‐ and post contrast agent with standard T1‐weighted (T1w) and with sequences to quantify T1 before radiation, and at 6‐week intervals during radio‐chemotherapy. We measured contrast enhancement by subtracting pre from post contrast contrast images, yielding relative signal increase ∆T1w and relative T1 shortening ∆qT1. On ∆qT1, we identified a solid and a cloudy‐enhancing compartment and evaluated the impact of their therapy‐related volume change upon PFS. In ∆qT1 maps cloudy‐enhancing compartments were found in all but two patients at baseline and in all patients during therapy. The qT1 decrease in the cloudy‐enhancing compartment post contrast was 21.64% versus 1.96% in the contralateral control tissue (P < 0.001). It was located at the margin of solid enhancement which was also seen on T1w. In contrast, the cloudy‐enhancing compartment was visually undetectable on ∆T1w. A volume decrease of more than 21.4% of the cloudy‐enhancing compartment at first follow‐up predicted longer PFS (P = 0.038). Cloudy‐enhancing compartment outside the solid contrast‐enhancing area of GBM is a new observation which is only visually detectable with qT1‐mapping and may represent tumor infiltration. Its early volume decrease predicts a longer PFS in GBM patients during standard radio‐chemotherapy.

Serial analysis of 3D H-1 MRSI for patients with newly diagnosed GBM treated with combination therapy that includes bevacizumab

Interpretation of changes in the T1- and T2-weighted MR images from patients with newly diagnosed glioblastoma (GBM) treated with standard of care in conjunction with anti-angiogenic agents is complicated by pseudoprogression and pseudoresponse. The hypothesis being tested in this study was that 3D H-1 magnetic resonance spectroscopic imaging (MRSI) provides estimates of levels of choline, creatine, N-acetylaspartate (NAA), lactate and lipid that change in response to treatment and that metrics describing these characteristics are associated with survival. Thirty-one patients with newly diagnosed GBM and being treated with radiation therapy (RT), temozolomide, erlotinib and bevacizumab were recruited to receive serial MR scans that included 3-D lactate edited MRSI at baseline, mid-RT, post-RT and at specific follow-up time points. The data were processed to provide estimates of metrics representing changes in metabolite levels relative to normal appearing brain. Cox proportional hazards analysis was applied to examine the relationship of these parameters with progression free survival (PFS) and overall survival (OS). There were significant reductions in parameters that describe relative levels of choline to NAA and creatine, indicating that the treatment caused a decrease in tumor cellularity. Changes in the levels of lactate and lipid relative to the NAA from contralateral brain were consistent with vascular normalization. Metabolic parameters from the first serial follow-up scan were associated with PFS and OS, when accounting for age and extent of resection. Integrating metabolic parameters into the assessment of patients with newly diagnosed GBM receiving therapies that include anti-angiogenic agents may be helpful for tracking changes in tumor burden, resolving ambiguities in anatomic images caused by non-specific treatment effects and for predicting outcome.

Diffusion and perfusion weighted magnetic resonance imaging for tumor volume definition in radiotherapy of brain tumors

Accurate target volume delineation is crucial for the radiotherapy of tumors. Diffusion and perfusion magnetic resonance imaging (MRI) can provide functional information about brain tumors, and they are able to detect tumor volume and physiological changes beyond the lesions shown on conventional MRI. This review examines recent studies that utilized diffusion and perfusion MRI for tumor volume definition in radiotherapy of brain tumors, and it presents the opportunities and challenges in the integration of multimodal functional MRI into clinical practice. The results indicate that specialized and robust post-processing algorithms and tools are needed for the precise alignment of targets on the images, and comprehensive validations with more clinical data are important for the improvement of the correlation between histopathologic results and MRI parameter images.

Therapy Monitoring with Functional and Molecular MR Imaging

Cancer therapy is mainly based on different combinations of surgery, radiotherapy, and chemotherapy. Additionally, targeted therapies (designed to disrupt specific tumor hallmarks, such as angiogenesis, metabolism, proliferation, invasiveness, and immune evasion), hormonotherapy, immunotherapy, and interventional techniques have emerged as alternative oncologic treatments. Conventional imaging techniques and current response criteria do not always provide the necessary information regarding therapy success particularly to targeted therapies. In this setting, MR imaging offers an attractive combination of anatomic, physiologic, and molecular information, which may surpass these limitations, and is being increasingly used for therapy response assessment.

MRSI-based molecular imaging of therapy response to temozolomide in preclinical glioblastoma using source analysis

Characterization of glioblastoma (GB) response to treatment is a key factor for improving patients' survival and prognosis. MRI and magnetic resonance spectroscopic imaging (MRSI) provide morphologic and metabolic profiles of GB but usually fail to produce unequivocal biomarkers of response. The purpose of this work is to provide proof of concept of the ability of a semi-supervised signal source extraction methodology to produce images with robust recognition of response to temozolomide (TMZ) in a preclinical GB model. A total of 38 female C57BL/6 mice were used in this study. The semi-supervised methodology extracted the required sources from a training set consisting of MRSI grids from eight GL261 GBs treated with TMZ, and six control untreated GBs. Three different sources (normal brain parenchyma, actively proliferating GB and GB responding to treatment) were extracted and used for calculating nosologic maps representing the spatial response to treatment. These results were validated with an independent test set (7 control and 17 treated cases) and correlated with histopathology. Major differences between the responder and non-responder sources were mainly related to the resonances of mobile lipids (MLs) and polyunsaturated fatty acids in MLs (0.9, 1.3 and 2.8 ppm). Responding tumors showed significantly lower mitotic (3.3 ± 2.9 versus 14.1 ± 4.2 mitoses/field) and proliferation rates (29.8 ± 10.3 versus 57.8 ± 5.4%) than control untreated cases. The methodology described in this work is able to produce nosological images of response to TMZ in GL261 preclinical GBs and suitably correlates with the histopathological analysis of tumors. A similar strategy could be devised for monitoring response to treatment in patients. Copyright © 2016 John Wiley & Sons, Ltd.

Advanced neuroimaging in the clinic: critical appraisal of the evidence base

The shortage of high-quality systematic reviews in the field of radiology limits evidence-based integration of imaging methods into clinical practice and may perpetuate misconceptions regarding the efficacy and appropriateness of imaging techniques for specific applications. Diffusion tensor imaging for patients with mild traumatic brain injury (DTI-mTBI) and dynamic susceptibility contrast MRI for patients with glioma (DSC-glioma) are applications of quantitative neuroimaging, which similarly detect manifestations of disease where conventional neuroimaging techniques cannot. We performed a critical appraisal of reviews, based on the current evidence-based medicine methodology, addressing the ability of DTI-mTBI and DSC-glioma to (a) detect brain abnormalities and/or (b) predict clinical outcomes. 23 reviews of DTI-mTBI and 26 reviews of DSC-glioma met criteria for inclusion. All reviews addressed detection of brain abnormalities, whereas 12 DTI-mTBI reviews and 22 DSC-glioma reviews addressed prediction of a clinical outcome. All reviews were assessed using a critical appraisal worksheet consisting of 19 yes/no questions. Reviews were graded according to the total number of positive responses and the 2011 Oxford Centre for evidence-based medicine levels of evidence criteria. Reviews addressing DTI-mTBI detection had moderate quality, while those addressing DSC-glioma were of low quality. Reviews addressing prediction of outcomes for both applications were of low quality. Five DTI-mTBI reviews, but only one review of DSC-glioma met criteria for classification as a meta-analysis/systematic/quantitative review.

Characterization of the serum metabolome following radiation treatment in patients with high-grade gliomas

Background

Glioblastomas progress rapidly making response evaluation using MRI insufficient since treatment effects are not detectable until months after initiation of treatment. Thus, there is a strong need for supplementary biomarkers that could provide reliable and early assessment of treatment efficacy. Analysis of alterations in the metabolome may be a source for identification of new biomarker patterns harboring predictive information. Ideally, the biomarkers should be found within an easily accessible compartment such as the blood.

Method

Using gas-chromatographic- time-of-flight-mass spectroscopy we have analyzed serum samples from 11 patients with glioblastoma during the initial phase of radiotherapy. Fasting serum samples were collected at admittance, on the same day as, but before first treatment and in the morning after the second and fifth dose of radiation. The acquired data was analyzed and evaluated by chemometrics based bioinformatics methods. Our findings were compared and discussed in relation to previous data from microdialysis in tumor tissue, i.e. the extracellular compartment, from the same patients.

Results

We found a significant change in metabolite pattern in serum comparing samples taken before radiotherapy to samples taken during early radiotherapy. In all, 68 metabolites were lowered in concentration following treatment while 16 metabolites were elevated in concentration. All detected and identified amino acids and fatty acids together with myo-inositol, creatinine, and urea were among the metabolites that decreased in concentration during treatment, while citric acid was among the metabolites that increased in concentration. Furthermore, when comparing results from the serum analysis with findings in tumor extracellular fluid we found a common change in metabolite patterns in both compartments on an individual patient level. On an individual metabolite level similar changes in ornithine, tyrosine and urea were detected. However, in serum, glutamine and glutamate were lowered after treatment while being elevated in the tumor extracellular fluid.

Conclusion

Cross-validated multivariate statistical models verified that the serum metabolome was significantly changed in relation to radiation in a similar pattern to earlier findings in tumor tissue. However, all individual changes in tissue did not translate into changes in serum. Our study indicates that serum metabolomics could be of value to investigate as a potential marker for assessing early response to radiotherapy in malignant glioma.

Electronic supplementary material

The online version of this article (doi:10.1186/s13014-016-0626-6) contains supplementary material, which is available to authorized users.

Differentiating Radiation-Induced Necrosis from Recurrent Brain Tumor Using MR Perfusion and Spectroscopy: A Meta-Analysis

Purpose

This meta-analysis examined roles of several metabolites in differentiating recurrent tumor from necrosis in patients with brain tumors using MR perfusion and spectroscopy.

Methods

Medline, Cochrane, EMBASE, and Google Scholar were searched for studies using perfusion MRI and/or MR spectroscopy published up to March 4, 2015 which differentiated between recurrent tumor vs. necrosis in patients with primary brain tumors or brain metastasis. Only two-armed, prospective or retrospective studies were included. A meta-analysis was performed on the difference in relative cerebral blood volume (rCBV), ratios of choline/creatine (Cho/Cr) and/or choline/N-acetyl aspartate (Cho/NAA) between participants undergoing MRI evaluation. A χ²-based test of homogeneity was performed using Cochran’s Q statistic and I².

Results

Of 397 patients in 13 studies who were analyzed, the majority had tumor recurrence. As there was evidence of heterogeneity among 10 of the studies which used rCBV for evaluation (Q statistic = 31.634, I² = 97.11%, P < 0.0001) a random-effects analysis was applied. The pooled difference in means (2.18, 95%CI = 0.85 to 3.50) indicated that the average rCBV in a contrast-enhancing lesion was significantly higher in tumor recurrence compared with radiation injury (P = 0.001). Based on a fixed-effect model of analysis encompassing the six studies which used Cho/Cr ratios for evaluation (Q statistic = 8.388, I² = 40.39%, P = 0.137), the pooled difference in means (0.77, 95%CI = 0.57 to 0.98) of the average Cho/Cr ratio was significantly higher in tumor recurrence than in tumor necrosis (P = 0.001). There was significant difference in ratios of Cho to NAA between recurrent tumor and necrosis (1.02, 95%CI = 0.03 to 2.00, P = 0.044).

Conclusions

MR spectroscopy and MR perfusion using Cho/NAA and Cho/Cr ratios and rCBV may increase the accuracy of differentiating necrosis from recurrent tumor in patients with primary brain tumors or metastases.

Magnetic Resonance (MR) Metabolic Imaging in Glioma

This review is focused on describing the use of magnetic resonance (MR) spectroscopy for metabolic imaging of brain tumors. We will first review the MR metabolic imaging findings generated from preclinical models, focusing primarily on in vivo studies, and will then describe the use of metabolic imaging in the clinical setting. We will address relatively well-established (1) H MRS approaches, as well as (31) P MRS, (13) C MRS and emerging hyperpolarized (13) C MRS methodologies, and will describe the use of metabolic imaging for understanding the basic biology of glioma as well as for improving the characterization and monitoring of brain tumors in the clinic.

Comparison between magnetic resonance spectroscopy and diffusion weighted imaging in the evaluation of gliomas response after treatment

PURPOSE

To compare magnetic resonance spectroscopy (MRS) and diffusion weighted imaging (DWI) in the assessment of progression and regression of brain tumors in order to assess whether there is correlation between MRS and DWI in the monitoring of patients with primary tumors after therapy.

METHODS

Magnetic resonance imaging (MRI) has been performed in 80 patients, 48 affected by high grade gliomas (HGG) and 32 affected by low grade gliomas (LGG). The variation of apparent diffusion coefficient (ADC) value and metabolite ratios before and after treatment has been used to test DWI sequences and MRS as predictor to response to therapy. Comparison between post contrast-enhancement sequences, MRS and DWI has been done in terms of accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). Moreover statistical correlation of ADC deviations with MRS metabolites variations before and after therapy have been studied.

RESULTS

In the case of HGG, MRS shows better sensitivity, specificity, PPV, NPV and accuracy compared to DWI, especially when considering the Choline/N-acetylaspartate (Cho/NAA) ratio. Regarding the LGG, the technique that better evaluates the response to treatment appears to be the DWI. A moderate correlation between ADC deviations and Cho, Lipide (Lip) and Lactate (Lac) has been found in LGG; while NAA revealed to be weakly correlated to ADC variation. Considering HGG, a weak correlation has been found between ADC deviations and MRS metabolites.

CONCLUSION

Combination of DWI and MRS can help to characterize different changes related to treatment and to evaluate brain tumor response to treatment.

Prognostic Value of Dynamic Susceptibility Contrast-Enhanced and Diffusion-Weighted MR Imaging in Patients with Glioblastomas

BACKGROUND AND PURPOSE

Prediction of survival in patients with glioblastomas is important for individualized treatment planning. This study aimed to assess the prognostic utility of presurgical dynamic susceptibility contrast and diffusion-weighted imaging for overall survival in patients with glioblastoma.

MATERIALS AND METHODS

MR imaging data from pathologically proved glioblastomas between June 2006 to December 2013 in 58 patients (mean age, 62.7 years; age range, 22-89 years) were included in this retrospective study. Patients were divided into long survival (≥15 months) and short survival (<15 months) groups, depending on overall survival time. Patients underwent dynamic susceptibility contrast perfusion and DWI before surgery and were treated with chemotherapy and radiation therapy. The maximum relative cerebral blood volume and minimum mean diffusivity values were measured from the enhancing part of the tumor.

RESULTS

Maximum relative cerebral blood volume values in patients with short survival were significantly higher compared with those who demonstrated long survival (P < .05). No significant difference was observed in the minimum mean diffusivity between short and long survivors. Receiver operator curve analysis demonstrated that a maximum relative cerebral blood volume cutoff value of 5.79 differentiated patients with low and high survival with an area under the curve of 0.93, sensitivity of 0.89, and specificity of 0.90 (P < .001), while a minimum mean diffusivity cutoff value of 8.35 × 10(-4)mm(2)/s had an area under the curve of 0.55, sensitivity of 0.71, and specificity of 0.47 (P > .05) in separating the 2 groups.

CONCLUSIONS

Maximum relative cerebral blood volume may be used as a prognostic marker of overall survival in patients with glioblastomas.

IDH1 Mutation Induces Reprogramming of Pyruvate Metabolism

Mutant isocitrate dehydrogenase 1 (IDH1) catalyzes the production of 2-hydroxyglutarate but also elicits additional metabolic changes. Levels of both glutamate and pyruvate dehydrogenase (PDH) activity have been shown to be affected in U87 glioblastoma cells or normal human astrocyte (NHA) cells expressing mutant IDH1, as compared with cells expressing wild-type IDH1. In this study, we show how these phenomena are linked through the effects of IDH1 mutation, which also reprograms pyruvate metabolism. Reduced PDH activity in U87 glioblastoma and NHA IDH1 mutant cells was associated with relative increases in PDH inhibitory phosphorylation, expression of pyruvate dehydrogenase kinase-3, and levels of hypoxia inducible factor-1α. PDH activity was monitored in these cells by hyperpolarized (13)C-magnetic resonance spectroscopy ((13)C-MRS), which revealed a reduction in metabolism of hyperpolarized 2-(13)C-pyruvate to 5-(13)C-glutamate, relative to cells expressing wild-type IDH1. (13)C-MRS also revealed a reduction in glucose flux to glutamate in IDH1 mutant cells. Notably, pharmacological activation of PDH by cell exposure to dichloroacetate (DCA) increased production of hyperpolarized 5-(13)C-glutamate in IDH1 mutant cells. Furthermore, DCA treatment also abrogated the clonogenic advantage conferred by IDH1 mutation. Using patient-derived mutant IDH1 neurosphere models, we showed that PDH activity was essential for cell proliferation. Taken together, our results established that the IDH1 mutation induces an MRS-detectable reprogramming of pyruvate metabolism, which is essential for cell proliferation and clonogenicity, with immediate therapeutic implications.

Imaging metabolism with hyperpolarized (13)C-labeled cell substrates

Non-invasive (13)C magnetic resonance spectroscopy measurements of the uptake and subsequent metabolism of (13)C-labeled substrates is a powerful method for studying metabolic fluxes in vivo. However, the technique has been hampered by a lack of sensitivity, which has limited both the spatial and temporal resolution. The introduction of dissolution dynamic nuclear polarization in 2003, which by radically enhancing the nuclear spin polarization of (13)C nuclei in solution can increase their sensitivity to detection by more than 10(4)-fold, revolutionized the study of metabolism using magnetic resonance, with temporal and spatial resolutions in the seconds and millimeter ranges, respectively. The principal limitation of the technique is the short half-life of the polarization, which at ∼20-30 s in vivo limits studies to relatively fast metabolic reactions. Nevertheless, pre-clinical studies with a variety of different substrates have demonstrated the potential of the method to provide new insights into tissue metabolism and have paved the way for the first clinical trial of the technique in prostate cancer. The technique now stands on the threshold of more general clinical translation. I consider here what the clinical applications might be, which are the substrates that most likely will be used, how will we analyze the resulting kinetic data, and how we might further increase the levels of polarization and extend polarization lifetime.

Advanced magnetic resonance imaging of the physical processes in human glioblastoma

The most common malignant primary brain tumor, glioblastoma multiforme (GBM) is a devastating disease with a grim prognosis. Patient survival is typically less than two years and fewer than 10% of patients survive more than five years. Magnetic resonance imaging (MRI) can have great utility in the diagnosis, grading, and management of patients with GBM as many of the physical manifestations of the pathologic processes in GBM can be visualized and quantified using MRI. Newer MRI techniques such as dynamic contrast enhanced and dynamic susceptibility contrast MRI provide functional information about the tumor hemodynamic status. Diffusion MRI can shed light on tumor cellularity and the disruption of white matter tracts in the proximity of tumors. MR spectroscopy can be used to study new tumor tissue markers such as IDH mutations. MRI is helping to noninvasively explore the link between the molecular basis of gliomas and the imaging characteristics of their physical processes. We, here, review several approaches to MR-based imaging and discuss the potential for these techniques to quantify the physical processes in glioblastoma, including tumor cellularity and vascularity, metabolite expression, and patterns of tumor growth and recurrence. We conclude with challenges and opportunities for further research in applying physical principles to better understand the biologic process in this deadly disease. See all articles in this Cancer Research section, "Physics in Cancer Research."

Relaxation-compensated CEST-MRI of the human brain at 7T: Unbiased insight into NOE and amide signal changes in human glioblastoma

Endogenous chemical exchange saturation transfer (CEST) effects of protons resonating near to water protons are always diluted by competing effects such as direct water saturation and semi-solid magnetization transfer (MT). This leads to unwanted T2 and MT signal contributions that contaminate the observed CEST signal. Furthermore, all CEST effects appear to be scaled by the T1 relaxation time of the mediating water pool. As MT, T1 and T2 are also altered in tumor regions, a recently published correction algorithm yielding the apparent exchange-dependent relaxation AREX, is used to evaluate in vivo CEST effects. This study focuses on CEST effects of amides (3.5ppm) and Nuclear-Overhauser-mediated saturation transfer (NOE, -3.5ppm) that can be properly isolated at 7T. These were obtained in 10 glioblastoma patients, and this is the first comprehensive study where AREX is applied in human brain as well as in human glioblastoma. The correction of CEST effects alters the contrast significantly: after correction, the CEST effect of amides does not show significant contrast between contrast enhancing tumor regions and normal tissue, whereas NOE drops significantly in the tumor area. In addition, new features in the AREX contrasts are visible. This suggests that previous CEST approaches might not have shown pure CEST effects, but rather water relaxation shine-through effects. Our insights help to improve understanding of the CEST effect changes in tumors and correlations on a cellular and molecular level.

Current standards and new concepts in MRI and PET response assessment of antiangiogenic therapies in high-grade glioma patients

Despite multimodal treatment, the prognosis of high-grade gliomas is grim. As tumor growth is critically dependent on new blood vessel formation, antiangiogenic treatment approaches offer an innovative treatment strategy. Bevacizumab, a humanized monoclonal antibody, has been in the spotlight of antiangiogenic approaches for several years. Currently, MRI including contrast-enhanced T1-weighted and T2/fluid-attenuated inversion recovery (FLAIR) images is routinely used to evaluate antiangiogenic treatment response (Response Assessment in Neuro-Oncology criteria). However, by restoring the blood-brain barrier, bevacizumab may reduce T1 contrast enhancement and T2/FLAIR hyperintensity, thereby obscuring the imaging-based detection of progression. The aim of this review is to highlight the recent role of imaging biomarkers from MR and PET imaging on measurement of disease progression and treatment effectiveness in antiangiogenic therapies. Based on the reviewed studies, multimodal imaging combining standard MRI with new physiological MRI techniques and metabolic PET imaging, in particular amino acid tracers, may have the ability to detect antiangiogenic drug susceptibility or resistance prior to morphological changes. As advances occur in the development of therapies that target specific biochemical or molecular pathways and alter tumor physiology in potentially predictable ways, the validation of physiological and metabolic imaging biomarkers will become increasingly important in the near future.

Delayed contrast extravasation MRI: a new paradigm in neuro-oncology

BACKGROUND

Conventional magnetic resonance imaging (MRI) is unable to differentiate tumor/nontumor enhancing tissues. We have applied delayed-contrast MRI for calculating high resolution treatment response assessment maps (TRAMs) clearly differentiating tumor/nontumor tissues in brain tumor patients.

METHODS

One hundred and fifty patients with primary/metastatic tumors were recruited and scanned by delayed-contrast MRI and perfusion MRI. Of those, 47 patients underwent resection during their participation in the study. Region of interest/threshold analysis was performed on the TRAMs and on relative cerebral blood volume maps, and correlation with histology was studied. Relative cerebral blood volume was also assessed by the study neuroradiologist.

RESULTS

Histological validation confirmed that regions of contrast agent clearance in the TRAMs >1 h post contrast injection represent active tumor, while regions of contrast accumulation represent nontumor tissues with 100% sensitivity and 92% positive predictive value to active tumor. Significant correlation was found between tumor burden in the TRAMs and histology in a subgroup of lesions resected en bloc (r(2) = 0.90, P < .0001). Relative cerebral blood volume yielded sensitivity/positive predictive values of 51%/96% and there was no correlation with tumor burden. The feasibility of applying the TRAMs for differentiating progression from treatment effects, depicting tumor within hemorrhages, and detecting residual tumor postsurgery is demonstrated.

CONCLUSIONS

The TRAMs present a novel model-independent approach providing efficient separation between tumor/nontumor tissues by adding a short MRI scan >1 h post contrast injection. The methodology uses robust acquisition sequences, providing high resolution and easy to interpret maps with minimal sensitivity to susceptibility artifacts. The presented results provide histological validation of the TRAMs and demonstrate their potential contribution to the management of brain tumor patients.

Molecular imaging coupled to pattern recognition distinguishes response to temozolomide in preclinical glioblastoma

Non-invasive monitoring of response to treatment of glioblastoma (GB) is nowadays carried out using MRI. MRS and MR spectroscopic imaging (MRSI) constitute promising tools for this undertaking. A temozolomide (TMZ) protocol was optimized for GL261 GB. Sixty-three mice were studied by MRI/MRS/MRSI. The spectroscopic information was used for the classification of control brain and untreated and responding GB, and validated against post-mortem immunostainings in selected animals. A classification system was developed, based on the MRSI-sampled metabolome of normal brain parenchyma, untreated and responding GB, with a 93% accuracy. Classification of an independent test set yielded a balanced error rate of 6% or less. Classifications correlated well both with tumor volume changes detected by MRI after two TMZ cycles and with the histopathological data: a significant decrease (p < 0.05) in the proliferation and mitotic rates and a 4.6-fold increase in the apoptotic rate. A surrogate response biomarker based on the linear combination of 12 spectral features has been found in the MRS/MRSI pattern of treated tumors, allowing the non-invasive classification of growing and responding GL261 GB. The methodology described can be applied to preclinical treatment efficacy studies to test new antitumoral drugs, and begets translational potential for early response detection in clinical studies.

Comparison of ADC metrics and their association with outcome for patients with newly diagnosed glioblastoma being treated with radiation therapy, temozolomide, erlotinib and bevacizumab

To evaluate metrics that describe changes in apparent diffusion coefficient (ADC) and to examine their association with clinical outcome for patients with newly diagnosed GBM who were participating in a Phase II clinical trial of treatment with radiation (RT), temozolomide, erlatonib and bevacizumab. Thirty six patients were imaged after surgery but prior to therapy and at regular follow-up time points. The following ADC metrics were evaluated: (1) histogram percentiles within the T2-hyperintense lesion (T2L) at serial follow-ups; (2) parameters obtained by fitting a two-mixture normal distribution to the histogram within the contrast-enhancing lesion (CEL) at baseline; (3) parameters obtained using both traditional and graded functional diffusion maps within the CEL and T2L. Cox Proportional Hazards models were employed to assess the association of the ADC parameters with overall survival (OS) and progression-free survival (PFS). A lower ADC percentile value within the T2L at early follow-up time points was associated with worse outcome. Of particular interest is that, even when adjusting for clinical prognostic factors, the ADC_10% within the T2L at 2 months was strongly associated with OS (p < 0.001) and PFS (p < 0.007). fDM metrics showed an association with OS and PFS within the CEL when considered by univariate analysis, but not in the T2L. Our study emphasizes the value of ADC metrics obtained from the T2L at the post-RT time point as non-invasive biomarkers for assessing residual tumor in patients with newly diagnosed GBM being treated with combination therapy that includes the anti-angiogenic agent bevacizumab.

The comprehensive neuro-oncology data repository (CONDR): a research infrastructure to develop and validate imaging biomarkers

BACKGROUND

Advanced imaging methods have the potential to serve as quantitative biomarkers in neuro-oncology research. However, a lack of standardization of image acquisition, processing, and analysis limits their application in clinical research. Standardization of these methods and an organized archival platform are required to better validate and apply these markers in research settings and, ultimately, in clinical practice.

OBJECTIVE

The primary objective of the Comprehensive Neuro-oncology Data Repository (CONDR) is to develop a data set for assessing and validating advanced imaging methods in patients diagnosed with brain tumors. As a secondary objective, informatics resources will be developed to facilitate the integrated collection, processing, and analysis of imaging, tissue, and clinical data in multicenter clinical trials. Finally, CONDR data and informatics resources will be shared with the research community for further analysis.

METHODS

CONDR will enroll 200 patients diagnosed with primary brain tumors. Clinical, imaging, and tissue-based data are obtained from patients serially, beginning with diagnosis and continuing over the course of their treatment. The CONDR imaging protocol includes structural and functional sequences, including diffusion- and perfusion-weighted imaging. All data are managed within an XNAT-based informatics platform. Imaging markers are assessed by correlating image and spatially aligned pathological markers and a variety of clinical markers.

EXPECTED OUTCOMES

CONDR will generate data for developing and validating imaging markers of primary brain tumors, including multispectral and probabilistic maps.

DISCUSSION

CONDR implements a novel, open-research model that will provide the research community with both open-access data and open-source informatics resources.

Nuclear overhauser enhancement mediated chemical exchange saturation transfer imaging at 7 Tesla in glioblastoma patients

Background and Purpose

Nuclear Overhauser Enhancement (NOE) mediated chemical exchange saturation transfer (CEST) is a novel magnetic resonance imaging (MRI) technique on the basis of saturation transfer between exchanging protons of tissue proteins and bulk water. The purpose of this study was to evaluate and compare the information provided by three dimensional NOE mediated CEST at 7 Tesla (7T) and standard MRI in glioblastoma patients.

Patients and Methods

Twelve patients with newly diagnosed histologically proven glioblastoma were enrolled in this prospective ethics committee–approved study. NOE mediated CEST contrast was acquired with a modified three-dimensional gradient-echo sequence and asymmetry analysis was conducted at 3.3ppm (B1 = 0.7 µT) to calculate the magnetization transfer ratio asymmetry (MTR_asym). Contrast enhanced T1 (CE-T1) and T2-weighted images were acquired at 3T and used for data co-registration and comparison.

Results

Mean NOE mediated CEST signal based on MTR_asym values over all patients was significantly increased (p<0.001) in CE-T1 tumor (−1.99±1.22%), tumor necrosis (−1.36±1.30%) and peritumoral CEST hyperintensities (PTCH) within T2 edema margins (−3.56±1.24%) compared to contralateral normal appearing white matter (−8.38±1.19%). In CE-T1 tumor (p = 0.015) and tumor necrosis (p<0.001) mean MTR_asym values were significantly higher than in PTCH. Extent of the surrounding tumor hyperintensity was smaller in eight out of 12 patients on CEST than on T2-weighted images, while four displayed at equal size. In all patients, isolated high intensity regions (0.40±2.21%) displayed on CEST within the CE-T1 tumor that were not discernible on CE-T1 or T2-weighted images.

Conclusion

NOE mediated CEST Imaging at 7T provides additional information on the structure of peritumoral hyperintensities in glioblastoma and displays isolated high intensity regions within the CE-T1 tumor that cannot be acquired on CE-T1 or T2-weighted images. Further research is needed to determine the origin of NOE mediated CEST and possible clinical applications such as therapy assessment or biopsy planning.

Lactate and choline metabolites detected in vitro by nuclear magnetic resonance spectroscopy are potential metabolic biomarkers for PI3K inhibition in pediatric glioblastoma

The phosphoinositide 3-kinase (PI3K) pathway is believed to be of key importance in pediatric glioblastoma. Novel inhibitors of the PI3K pathway are being developed and are entering clinical trials. Our aim is to identify potential non-invasive biomarkers of PI3K signaling pathway inhibition in pediatric glioblastoma using in vitro nuclear magnetic resonance (NMR) spectroscopy, to aid identification of target inhibition and therapeutic response in early phase clinical trials of PI3K inhibitors in childhood cancer. Treatment of SF188 and KNS42 human pediatric glioblastoma cell lines with the dual pan-Class I PI3K/mTOR inhibitor PI-103, inhibited the PI3K signaling pathway and resulted in a decrease in phosphocholine (PC), total choline (tCho) and lactate levels (p<0.02) as detected by phosphorus (31P)- and proton (1H)-NMR. Similar changes were also detected using the pan-Class I PI3K inhibitor GDC-0941 which lacks significant mTOR activity and is entering Phase II clinical trials. In contrast, the DNA damaging agent temozolomide (TMZ), which is used as current frontline therapy in the treatment of glioblastoma postoperatively (in combination with radiotherapy), increased PC, glycerophosphocholine (GPC) and tCho levels (p<0.04). PI-103-induced NMR changes were associated with alterations in protein expression levels of regulatory enzymes involved in glucose and choline metabolism including GLUT1, HK2, LDHA and CHKA. Our results show that by using NMR we can detect distinct biomarkers following PI3K pathway inhibition compared to treatment with the DNA-damaging anti-cancer agent TMZ. This is the first study reporting that lactate and choline metabolites are potential non-invasive biomarkers for monitoring response to PI3K pathway inhibitors in pediatric glioblastoma.

Advanced magnetic resonance imaging methods for planning and monitoring radiation therapy in patients with high-grade glioma

This review explores how the integration of advanced imaging methods with high-quality anatomical images significantly improves the characterization, target definition, assessment of response to therapy, and overall management of patients with high-grade glioma. Metrics derived from diffusion-, perfusion-, and susceptibility-weighted magnetic resonance imaging in conjunction with magnetic resonance spectroscopic imaging, allows us to characterize regions of edema, hypoxia, increased cellularity, and necrosis within heterogeneous tumor and surrounding brain tissue. Quantification of such measures may provide a more reliable initial representation of tumor delineation and response to therapy than changes in the contrast-enhancing or T2 lesion alone and have a significant effect on targeting resection, planning radiation, and assessing treatment effectiveness. In the long term, implementation of these imaging methodologies can also aid in the identification of recurrent tumor and its differentiation from treatment-related confounds and facilitate the detection of radiationinduced vascular injury in otherwise normal-appearing brain tissue.