Consensus recommendations for a standardized Brain Tumor Imaging Protocol in clinical trials

Classifying brain metastases by their primary site of origin using a radiomics approach based on texture analysis: a feasibility study

OBJECTIVE

To examine the capability of MRI texture analysis to differentiate the primary site of origin of brain metastases following a radiomics approach.

METHODS

Sixty-seven untreated brain metastases (BM) were found in 3D T1-weighted MRI of 38 patients with cancer: 27 from lung cancer, 23 from melanoma and 17 from breast cancer. These lesions were segmented in 2D and 3D to compare the discriminative power of 2D and 3D texture features. The images were quantized using different number of gray-levels to test the influence of quantization. Forty-three rotation-invariant texture features were examined. Feature selection and random forest classification were implemented within a nested cross-validation structure. Classification was evaluated with the area under receiver operating characteristic curve (AUC) considering two strategies: multiclass and one-versus-one.

RESULTS

In the multiclass approach, 3D texture features were more discriminative than 2D features. The best results were achieved for images quantized with 32 gray-levels (AUC = 0.873 ± 0.064) using the top four features provided by the feature selection method based on the p-value. In the one-versus-one approach, high accuracy was obtained when differentiating lung cancer BM from breast cancer BM (four features, AUC = 0.963 ± 0.054) and melanoma BM (eight features, AUC = 0.936 ± 0.070) using the optimal dataset (3D features, 32 gray-levels). Classification of breast cancer and melanoma BM was unsatisfactory (AUC = 0.607 ± 0.180).

CONCLUSION

Volumetric MRI texture features can be useful to differentiate brain metastases from different primary cancers after quantizing the images with the proper number of gray-levels.

KEY POINTS

• Texture analysis is a promising source of biomarkers for classifying brain neoplasms. • MRI texture features of brain metastases could help identifying the primary cancer. • Volumetric texture features are more discriminative than traditional 2D texture features.

Delay in starting radiotherapy due to neoadjuvant therapy does not worsen survival in unresected glioblastoma patients

PURPOSE

We retrospectively examined the potential effect on overall survival (OS) of delaying radiotherapy to administer neoadjuvant therapy in unresected glioblastoma patients.

PATIENTS AND METHODS

We compared OS in 119 patients receiving neoadjuvant therapy followed by standard treatment (NA group) and 96 patients receiving standard treatment without neoadjuvant therapy (NoNA group). The MaxStat package of R identified the optimal cut-off point for waiting time to radiotherapy.

RESULTS

OS was similar in the NA and NoNA groups. Median waiting time to radiotherapy after surgery was 13 weeks for the NA group and 4.2 weeks for the NoNA group. The longest OS was attained by patients who started radiotherapy after 12 weeks and the shortest by patients who started radiotherapy within 4 weeks (12.3 vs 6.6 months) (P = 0.05). OS was 6.6 months for patients who started radiotherapy before the optimal cutoff of 6.43 weeks and 19.1 months for those who started after this time (P = 0.005). Patients who completed radiotherapy had longer OS than those who did not, in all 215 patients and in the NA and NoNA groups (P = 0.000). In several multivariate analyses, completing radiotherapy was a universally favorable prognostic factor, while neoadjuvant therapy was never identified as a negative prognostic factor.

CONCLUSION

In our series of unresected patients receiving neoadjuvant treatment, in spite of the delay in starting radiotherapy, OS was not inferior to that of a similar group of patients with no delay in starting radiotherapy.

Pseudoprogression of brain tumors

This review describes the definition, incidence, clinical implications, and magnetic resonance imaging (MRI) findings of pseudoprogression of brain tumors, in particular, but not limited to, high-grade glioma. Pseudoprogression is an important clinical problem after brain tumor treatment, interfering not only with day-to-day patient care but also the execution and interpretation of clinical trials. Radiologically, pseudoprogression is defined as a new or enlarging area(s) of contrast agent enhancement, in the absence of true tumor growth, which subsides or stabilizes without a change in therapy. The clinical definitions of pseudoprogression have been quite variable, which may explain some of the differences in reported incidences, which range from 9-30%. Conventional structural MRI is insufficient for distinguishing pseudoprogression from true progressive disease, and advanced imaging is needed to obtain higher levels of diagnostic certainty. Perfusion MRI is the most widely used imaging technique to diagnose pseudoprogression and has high reported diagnostic accuracy. Diagnostic performance of MR spectroscopy (MRS) appears to be somewhat higher, but MRS is less suitable for the routine and universal application in brain tumor follow-up. The combination of MRS and diffusion-weighted imaging and/or perfusion MRI seems to be particularly powerful, with diagnostic accuracy reaching up to or even greater than 90%. While diagnostic performance can be high with appropriate implementation and interpretation, even a combination of techniques, however, does not provide 100% accuracy. It should also be noted that most studies to date are small, heterogeneous, and retrospective in nature. Future improvements in diagnostic accuracy can be expected with harmonization of acquisition and postprocessing, quantitative MRI and computer-aided diagnostic technology, and meticulous evaluation with clinical and pathological data.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.

Conventional and advanced magnetic resonance imaging in patients with high-grade glioma

Magnetic resonance imaging is integral to the care of patients with high-grade gliomas. Anatomic detail can be acquired with conventional structural imaging, but newer approaches also add capabilities to interrogate image-derived physiologic and molecular characteristics of central nervous system neoplasms. These advanced imaging techniques are increasingly employed to generate biomarkers that better reflect tumor burden and therapy response. The following is an overview of current strategies based on advanced magnetic resonance imaging that are used in the assessment of high-grade glioma patients with an emphasis on how novel imaging biomarkers can potentially advance patient care.

Glioma imaging in Europe: A survey of 220 centres and recommendations for best clinical practice

Objectives

At a European Society of Neuroradiology (ESNR) Annual Meeting 2015 workshop, commonalities in practice, current controversies and technical hurdles in glioma MRI were discussed. We aimed to formulate guidance on MRI of glioma and determine its feasibility, by seeking information on glioma imaging practices from the European Neuroradiology community.

Methods

Invitations to a structured survey were emailed to ESNR members (n=1,662) and associates (n=6,400), European national radiologists’ societies and distributed via social media.

Results

Responses were received from 220 institutions (59% academic). Conventional imaging protocols generally include T2w, T2-FLAIR, DWI, and pre- and post-contrast T1w. Perfusion MRI is used widely (85.5%), while spectroscopy seems reserved for specific indications. Reasons for omitting advanced imaging modalities include lack of facility/software, time constraints and no requests. Early postoperative MRI is routinely carried out by 74% within 24–72 h, but only 17% report a percent measure of resection. For follow-up, most sites (60%) issue qualitative reports, while 27% report an assessment according to the RANO criteria. A minority of sites use a reporting template (23%).

Conclusion

Clinical best practice recommendations for glioma imaging assessment are proposed and the current role of advanced MRI modalities in routine use is addressed.

Key Points

• We recommend the EORTC-NBTS protocol as the clinical standard glioma protocol.

• Perfusion MRI is recommended for diagnosis and follow-up of glioma.

• Use of advanced imaging could be promoted with increased education activities.

• Most response assessment is currently performed qualitatively.

• Reporting templates are not widely used, and could facilitate standardisation.

Electronic supplementary material

The online version of this article (10.1007/s00330-018-5314-5) contains supplementary material, which is available to authorized users.

Consensus recommendations on standardized magnetic resonance imaging protocols for multicenter canine brain tumor clinical trials

The National Cancer Institute Comparative Brain Tumor Consortium, Patient Outcomes Working Group, propose a consensus document in support of standardized magnetic resonance imaging protocols for canine brain tumor clinical trials. The intent of this manuscript is to address the widely acknowledged need to ensure canine brain tumor imaging protocols are relevant and have sufficient equivalency to translate to human studies such that: (1) multi-institutional studies can be performed with minimal inter-institutional variation, and (2) imaging protocols are consistent with human consensus recommendations to permit reliable translation of imaging data to human clinical trials. Consensus recommendations include pre- and postcontrast three-dimensional T1-weighted images, T2-weighted turbo spin echo in all three planes, T2*-weighted gradient recalled echo, T2-weighted fluid attenuated inversion recovery, and diffusion weighted imaging/diffusion tensor imaging in transverse plane; field of view of ≤150 mm; slice thickness of ≤2 mm, matrix ≥ 256 for two-dimensional images, and 150 or 256 for three-dimensional images.

Imaging in neuro-oncology

Imaging plays several key roles in managing brain tumors, including diagnosis, prognosis, and treatment response assessment. Ongoing challenges remain as new therapies emerge and there are urgent needs to find accurate and clinically feasible methods to noninvasively evaluate brain tumors before and after treatment. This review aims to provide an overview of several advanced imaging modalities including magnetic resonance imaging and positron emission tomography (PET), including advances in new PET agents, and summarize several key areas of their applications, including improving the accuracy of diagnosis and addressing the challenging clinical problems such as evaluation of pseudoprogression and anti-angiogenic therapy, and rising challenges of imaging with immunotherapy.

Comparison of 2D (RANO) and volumetric methods for assessment of recurrent glioblastoma treated with bevacizumab-a report from the BELOB trial

Background

The current method for assessing progressive disease (PD) in glioblastoma is according to the Response Assessment in Neuro-Oncology (RANO) criteria. Bevacizumab-treated patients may show pseudo-response on postcontrast T1-weighted (T1w) MRI, and a more infiltrative non-enhancing growth pattern on T2w/fluid attenuated inversion recovery (FLAIR) images. We investigated whether the RANO criteria remain the method of choice for assessing bevacizumab-treated recurrent glioblastoma when compared with various volumetric methods.

Methods

Patients with assessable MRI data from the BELOB trial (n = 148) were included. Patients were treated with bevacizumab, lomustine, or both. At first and second radiological follow-up (6 and 12 wk), PD was determined using the 2D RANO criteria and various volumetric methods based on enhancing tumor only and enhancing plus non-enhancing tumor. Differences in overall survival (OS) between PD and non-PD patients were assessed with the log-rank test and a Cox model. Hazard ratios (HRs) and their 95% CIs were determined.

Results

For all patients together, all methods (except subtraction of non-enhancing from enhancing volume at first follow-up) showed significant differences in OS between PD and non-PD patients (P < .001). The largest risk increase for death in case of PD at both first and second follow-up was found with the RANO criteria: HR = 2.81 (95% CI, 1.92-4.10) and HR = 2.80 (95% CI, 1.75-4.49), respectively. In the bevacizumab-treated patients, all methods assessed showed significant differences in OS between PD and non-PD patients. There were no significant differences between methods.

Conclusions

In the first 12 weeks, volumetric methods did not provide significant improvement over the RANO criteria as a posttreatment prognostic marker.

Reconstruction of white matter fibre tracts using diffusion kurtosis tensor imaging at 1.5T: Pre-surgical planning in patients with gliomas

Tractography studies for pre-surgical planning of primary brain tumors is typically done using diffusion tensor imaging (DTI), which cannot resolve crossing, kissing or highly angulated fibres. Tractography based on the estimation of the diffusion kurtosis (DK) tensor was recently demonstrated to enable tackling these limitations. However, its use in the clinical context at low 1.5T field has not yet been reported.

PURPOSE

To evaluate if the estimation of whole-brain tractography using the DK tensor is feasible for pre-surgical investigation of patients with brain tumors at 1.5T.

METHODS

Eight healthy subjects and 3 patients with brain tumors were scanned at 1.5T using a 12-channel head coil. Diffusion-weighted images were acquired with repetition/echo times of 5800/107 ms, 82 × 82 resolution, 3 × 3 × 3 mm3 voxel size, b-values of 0, 1000, 2000 s/mm2 and 64 gradient sensitising directions. Whole-brain tractography was estimated using the DK tensor and corticospinal tracts (CST) were isolated using regions-of-interest placed at the cerebral peduncles and motor gyrus. Tract size, DK metrics and CST deviation index (highest curvature point) were compared between healthy subjects and patients.

RESULTS

Tract sizes did not differ between groups. The CST deviation index was significantly higher in patients compared to healthy subjects. Fractional anisotropy was significantly lower in patients, with higher mean kurtosis asymmetry index at the highest curvature point in patients.

CONCLUSIONS

Corticospinal fibre bundles estimated using DK tensor in a 1.5T scanner presented similar properties in patients with brain gliomas as those reported in the literature using DTI-based tractography.

A comparison of semi-automated volumetric vs linear measurement of small vestibular schwannomas

Objective

Accurate and precise measurement of vestibular schwannoma (VS) size is key to clinical management decisions. Linear measurements are used in routine clinical practice but are prone to measurement error. This study aims to compare a semi-automated volume segmentation tool against standard linear method for measuring small VS. This study also examines whether oblique tumour orientation can contribute to linear measurement error.

Study design

Experimental comparison of observer agreement using two measurement techniques.

Setting

Tertiary skull base unit.

Participants

Twenty-four patients with unilateral sporadic small (< 15 mm maximum intracranial dimension) VS imaged with 1 mm-thickness T1-weighted Gadolinium enhanced MRI.

Main outcome measures

(1) Intra and inter-observer intraclass correlation coefficients (ICC), repeatability coefficients (RC), and relative smallest detectable difference (%SDD). (2) Mean change in maximum linear dimension following reformatting to correct for oblique orientation of VS.

Results

Intra-observer ICC was higher for semi-automated volumetric when compared with linear measurements, 0.998 (95% CI 0.994–0.999) vs 0.936 (95% CI 0.856–0.972), p < 0.0001. Inter-observer ICC was also higher for volumetric vs linear measurements, 0.989 (95% CI 0.975–0.995) vs 0.946 (95% CI 0.880–0.976), p = 0.0045. The intra-observer %SDD was similar for volumetric and linear measurements, 9.9% vs 11.8%. However, the inter-observer %SDD was greater for volumetric than linear measurements, 20.1% vs 10.6%. Following oblique reformatting to correct tumour angulation, the mean increase in size was 1.14 mm (p = 0.04).

Conclusion

Semi-automated volumetric measurements are more repeatable than linear measurements when measuring small VS and should be considered for use in clinical practice. Oblique orientation of VS may contribute to linear measurement error.

MRI features predict p53 status in lower-grade gliomas via a machine-learning approach

Background

P53 mutation status is a pivotal biomarker for gliomas. Here, we developed a machine-learning model to predict p53 status in lower-grade gliomas based on radiomic features extracted from conventional magnetic resonance (MR) images.

Methods

Preoperative MR images were retrospectively obtained from 272 patients with primary grade II/III gliomas. The patients were randomly allocated in a 2:1 ratio to a training (n = 180) or validation (n = 92) set. A total of 431 radiomic features were extracted from each patient. The lest absolute shrinkage and selection operator (LASSO) method was used for feature selection and radiomic signature construction. Subsequently, a machine-learning model to predict p53 status was established using the selected features and a Support Vector Machine classifier. The predictive performance of all individual features and the model was calculated using receiver operating characteristic curves in both the training and validation sets.

Results

The p53-related radiomic signature was built using the LASSO algorithm; this procedure consisted of four first-order statistics or related wavelet features (including Maximum, Median, Minimum, and Uniformity), a shape and size-based feature (Spherical Disproportion), and ten textural features or related wavelet features (including Correlation, Run Percentage, and Sum Entropy). The prediction accuracies based on the area under the curve were 89.6% in the training set and 76.3% in the validation set, which were better than individual features.

Conclusions

These results demonstrate that MR image texture features are predictive of p53 mutation status in lower-grade gliomas. Thus, our procedure can be conveniently used to facilitate presurgical molecular pathological diagnosis.

•

We established a p53-related radiomic signature in lower-grade gliomas based on LASSO algorithm.

•

We developed a machine-learning model using the radiomic signature and a support vector machine.

•

P53 mutation status of lower-grade gliomas was predicted effectively based on our machine-learning model.

Glioblastoma update: molecular biology, diagnosis, treatment, response assessment, and translational clinical trials

This is an exciting time in neuro-oncology. Discoveries elucidating the molecular mechanisms of oncogenesis and the molecular subtypes of glioblastoma multiforme (GBM) have led to new diagnostic and classification schemes with more prognostic power than histology alone. Molecular profiling has become part of the standard neuropathological evaluation of GBM. Chemoradiation followed by adjuvant temozolomide remains the standard therapy for newly diagnosed GBM, but survival remains unsatisfactory. Patients with recurrent GBM continue to have a dismal prognosis, but neuro-oncology centers with active clinical trial programs are seeing a small but increasing cadre of patients with longer survival. Molecularly targeted therapeutics, personalized therapy based on molecular profiling of individual tumors, and immunotherapeutic strategies are all being evaluated and refined in clinical trials. Understanding of the molecular mechanisms of tumor-mediated immunosuppression, and specifically interactions between tumor cells and immune effector cells in the tumor microenvironment, has led to a new generation of immunotherapies, including vaccine and immunomodulatory strategies as well as T-cell-based treatments. Molecularly targeted therapies, chemoradiation, immunotherapies, and anti-angiogenic therapies have created the need to develop more reliable neuroimaging criteria for differentiating the effects of therapy from tumor progression and changes in blood–brain barrier physiology from treatment response. Translational clinical trials for patients with GBM now incorporate quantitative imaging using both magnetic resonance imaging and positron emission tomography techniques. This update presents a summary of the current standards for therapy for newly diagnosed and recurrent GBM and highlights promising translational research.

SEOM clinical guidelines for anaplastic gliomas (2017)

The SEOM/GEINO clinical guidelines provide recommendations for radiological, and molecular diagnosis, treatment and follow-up of adult patients with anaplastic gliomas (AG). We followed the 2016 WHO classification which specifies the major diagnostic/prognostic and predictive value of IDH1/IDH2 missense mutations and 1p/19q codeletions in AG. The diagnosis of anaplastic oligoastrocytoma is discouraged. Surgery, radiotherapy and chemotherapy with PCV or TMZ are the first-line standard of care for AG with slight modifications according to molecular variables. A multidisciplinary team is highly recommended in the management of these tumors.

Diffusion MRI Phenotypes Predict Overall Survival Benefit from Anti-VEGF Monotherapy in Recurrent Glioblastoma: Converging Evidence from Phase II Trials

Purpose: Anti-VEGF therapies remain controversial in the treatment of recurrent glioblastoma (GBM). In the current study, we demonstrate that recurrent GBM patients with a specific diffusion MR imaging signature have an overall survival (OS) advantage when treated with cediranib, bevacizumab, cabozantinib, or aflibercept monotherapy at first or second recurrence. These findings were validated using a separate trial comparing bevacizumab with lomustine.Experimental Design: Patients with recurrent GBM and diffusion MRI from the monotherapy arms of 5 separate phase II clinical trials were included: (i) cediranib (NCT00035656); (ii) bevacizumab (BRAIN Trial, AVF3708g; NCT00345163); (iii) cabozantinib (XL184-201; NCT00704288); (iv) aflibercept (VEGF Trap; NCT00369590); and (v) bevacizumab or lomustine (BELOB; NTR1929). Apparent diffusion coefficient (ADC) histogram analysis was performed prior to therapy to estimate "ADCL," the mean of the lower ADC distribution. Pretreatment ADCL, enhancing volume, and clinical variables were tested as independent prognostic factors for OS.Results: The coefficient of variance (COV) in double baseline ADCL measurements was 2.5% and did not significantly differ (P = 0.4537). An ADCL threshold of 1.24 μm2/ms produced the largest OS differences between patients (HR ∼ 0.5), and patients with an ADCL > 1.24 μm2/ms had close to double the OS in all anti-VEGF therapeutic scenarios tested. Training and validation data confirmed that baseline ADCL was an independent predictive biomarker for OS in anti-VEGF therapies, but not in lomustine, after accounting for age and baseline enhancing tumor volume.Conclusions: Pretreatment diffusion MRI is a predictive imaging biomarker for OS in patients with recurrent GBM treated with anti-VEGF monotherapy at first or second relapse. Clin Cancer Res; 23(19); 5745-56. ©2017 AACR.

Detection of immune responses after immunotherapy in glioblastoma using PET and MRI

Contrast-enhanced MRI is typically used to follow treatment response and progression in patients with glioblastoma (GBM). However, differentiating tumor progression from pseudoprogression remains a clinical dilemma largely unmitigated by current advances in imaging techniques. Noninvasive imaging techniques capable of distinguishing these two conditions could play an important role in the clinical management of patients with GBM and other brain malignancies. We hypothesized that PET probes for deoxycytidine kinase (dCK) could be used to differentiate immune inflammatory responses from other sources of contrast-enhancement on MRI. Orthotopic malignant gliomas were established in syngeneic immunocompetent mice and then treated with dendritic cell (DC) vaccination and/or PD-1 mAb blockade. Mice were then imaged with [18F]-FAC PET/CT and MRI with i.v. contrast. The ratio of contrast enhancement on MRI to normalized PET probe uptake, which we term the immunotherapeutic response index, delineated specific regions of immune inflammatory activity. On postmortem examination, FACS-based enumeration of intracranial tumor-infiltrating lymphocytes directly correlated with quantitative [18F]-FAC PET probe uptake. Three patients with GBM undergoing treatment with tumor lysate-pulsed DC vaccination and PD-1 mAb blockade were also imaged before and after therapy using MRI and a clinical PET probe for dCK. Unlike in mice, [18F]-FAC is rapidly catabolized in humans; thus, we used another dCK PET probe, [18F]-clofarabine ([18F]-CFA), that may be more clinically relevant. Enhanced [18F]-CFA PET probe accumulation was identified in tumor and secondary lymphoid organs after immunotherapy. Our findings identify a noninvasive modality capable of imaging the host antitumor immune response against intracranial tumors.

Current Clinical Brain Tumor Imaging

Neuroimaging plays an ever evolving role in the diagnosis, treatment planning, and post-therapy assessment of brain tumors. This review provides an overview of current magnetic resonance imaging (MRI) methods routinely employed in the care of the brain tumor patient. Specifically, we focus on advanced techniques including diffusion, perfusion, spectroscopy, tractography, and functional MRI as they pertain to noninvasive characterization of brain tumors and pretreatment evaluation. The utility of both structural and physiological MRI in the post-therapeutic brain evaluation is also reviewed with special attention to the challenges presented by pseudoprogression and pseudoresponse.

Multiparametric MRI and [18F]Fluorodeoxyglucose Positron Emission Tomography Imaging Is a Potential Prognostic Imaging Biomarker in Recurrent Glioblastoma

Purpose/objectives

Multiparametric advanced MR and [¹⁸F]fluorodeoxyglucose (FDG)-positron emission tomography (PET) imaging may be important biomarkers for prognosis as well for distinguishing recurrent glioblastoma multiforme (GBM) from treatment-related changes.

Methods/materials

We retrospectively evaluated 30 patients treated with chemoradiation for GBM and underwent advanced MR and FDG-PET for confirmation of tumor progression. Multiparametric MRI and FDG-PET imaging metrics were evaluated for their association with 6-month overall (OS) and progression-free survival (PFS) based on pathological, radiographic, and clinical criteria.

Results

17 males and 13 females were treated between 2001 and 2014, and later underwent FDG-PET at suspected recurrence. Baseline FDG-PET and MRI imaging was obtained at a median of 7.5 months [interquartile range (IQR) 3.7–12.4] following completion of chemoradiation. Median follow-up after FDG-PET imaging was 10 months (IQR 7.2–13.0). Receiver-operator characteristic curve analysis identified that lesions characterized by a ratio of the SUV_max to the normal contralateral brain (SUV_max/NB index) >1.5 and mean apparent diffusion coefficient (ADC) value of ≤1,400 × 10⁻⁶ mm²/s correlated with worse 6-month OS and PFS. We defined three patient groups that predicted the probability of tumor progression: SUV_max/NB index >1.5 and ADC ≤1,400 × 10⁻⁶ mm²/s defined high-risk patients (n = 7), SUV_max/NB index ≤1.5 and ADC >1,400 × 10⁻⁶ mm²/s defined low-risk patients (n = 11), and intermediate-risk (n = 12) defined the remainder of the patients. Median OS following the time of the FDG-PET scan for the low, intermediate, and high-risk groups were 23.5, 10.5, and 3.8 months (p < 0.01). Median PFS were 10.0, 4.4, and 1.9 months (p = 0.03). Rates of progression at 6-months in the low, intermediate, and high-risk groups were 36, 67, and 86% (p = 0.04).

Conclusion

Recurrent GBM in the molecular era is associated with highly variable outcomes. Multiparametric MR and FDG-PET biomarkers may provide a clinically relevant, non-invasive and cost-effective method of predicting prognosis and improving clinical decision making in the treatment of patients with suspected tumor recurrence.

A Population-Based Digital Reference Object (DRO) for Optimizing Dynamic Susceptibility Contrast (DSC)-MRI Methods for Clinical Trials

The standardization and broad-scale integration of dynamic susceptibility contrast (DSC)-magnetic resonance imaging (MRI) have been confounded by a lack of consensus on DSC-MRI methodology for preventing potential relative cerebral blood volume inaccuracies, including the choice of acquisition protocols and postprocessing algorithms. Therefore, we developed a digital reference object (DRO), using physiological and kinetic parameters derived from in vivo data, unique voxel-wise 3-dimensional tissue structures, and a validated MRI signal computational approach, aimed at validating image acquisition and analysis methods for accurately measuring relative cerebral blood volume in glioblastomas. To achieve DSC-MRI signals representative of the temporal characteristics, magnitude, and distribution of contrast agent-induced T₁ and T₂* changes observed across multiple glioblastomas, the DRO's input parameters were trained using DSC-MRI data from 23 glioblastomas (>40 000 voxels). The DRO's ability to produce reliable signals for combinations of pulse sequence parameters and contrast agent dosing schemes unlike those in the training data set was validated by comparison with in vivo dual-echo DSC-MRI data acquired in a separate cohort of patients with glioblastomas. Representative applications of the DRO are presented, including the selection of DSC-MRI acquisition and postprocessing methods that optimize CBV accuracy, determination of the impact of DSC-MRI methodology choices on sample size requirements, and the assessment of treatment response in clinical glioblastoma trials.

Response Assessment in Neuro-Oncology Clinical Trials

Development of novel therapies for CNS tumors requires reliable assessment of response and progression. This requirement has been particularly challenging in neuro-oncology for which contrast enhancement serves as an imperfect surrogate for tumor volume and is influenced by agents that affect vascular permeability, such as antiangiogenic therapies. In addition, most tumors have a nonenhancing component that can be difficult to accurately quantify. To improve the response assessment in neuro-oncology and to standardize the criteria that are used for different CNS tumors, the Response Assessment in Neuro-Oncology (RANO) working group was established. This multidisciplinary international working group consists of neuro-oncologists, medical oncologists, neuroradiologists, neurosurgeons, radiation oncologists, neuropsychologists, and experts in clinical outcomes assessments, working in collaboration with government and industry to enhance the interpretation of clinical trials. The RANO working group was originally created to update response criteria for high- and low-grade gliomas and to address such issues as pseudoresponse and nonenhancing tumor progression from antiangiogenic therapies, and pseudoprogression from radiochemotherapy. RANO has expanded to include working groups that are focused on other tumors, including brain metastases, leptomeningeal metastases, spine tumors, pediatric brain tumors, and meningiomas, as well as other clinical trial end points, such as clinical outcomes assessments, seizures, corticosteroid use, and positron emission tomography imaging. In an effort to standardize the measurement of neurologic function for clinical assessment, the Neurologic Assessment in Neuro-Oncology scale was drafted. Born out of a workshop conducted by the Jumpstarting Brain Tumor Drug Development Coalition and the US Food and Drug Administration, a standardized brain tumor imaging protocol now exists to reduce variability and improve reliability. Efforts by RANO have been widely accepted and are increasingly being used in neuro-oncology trials, although additional refinements will be needed.

Differentiating radiation necrosis from tumor progression in brain metastases treated with stereotactic radiotherapy: utility of intravoxel incoherent motion perfusion MRI and correlation with histopathology

Radiation necrosis is a serious potential adverse event of stereotactic radiosurgery that cannot be reliably differentiated from recurrent tumor using conventional imaging techniques. Intravoxel incoherent motion (IVIM) is a magnetic resonance imaging (MRI) based method that uses a diffusion-weighted sequence to estimate quantitative perfusion and diffusion parameters. This study evaluated the IVIM-derived apparent diffusion coefficient (ADC) and perfusion fraction (f), and compared the results to the gold standard histopathological-defined outcomes of radiation necrosis or recurrent tumor. Nine patients with ten lesions were included in this study; all lesions exhibited radiographic progression after stereotactic radiosurgery for brain metastases that subsequently underwent surgical resection due to uncertainty regarding the presence of radiation necrosis versus recurrent tumor. Pre-surgical IVIM was performed to obtain f and ADC values and the results were compared to histopathology. Five lesions exhibited pathological radiation necrosis and five had predominantly recurrent tumor. The IVIM perfusion fraction reliably differentiated tumor recurrence from radiation necrosis (f_mean = 10.1 ± 0.7 vs. 8.3 ± 1.2, p = 0.02; cutoff value of 9.0 yielding a sensitivity/specificity of 100%/80%) while the ADC did not distinguish between the two (ADC_mean = 1.1 ± 0.2 vs. 1.2 ± 0.4, p = 0.6). IVIM shows promise in differentiating recurrent tumor from radiation necrosis for brain metastases treated with radiosurgery, but needs to be validated in a larger cohort.

Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization

Purpose

Textural measures have been widely explored as imaging biomarkers in cancer. However, their robustness under dynamic range and spatial resolution changes in brain 3D magnetic resonance images (MRI) has not been assessed. The aim of this work was to study potential variations of textural measures due to changes in MRI protocols.

Materials and methods

Twenty patients harboring glioblastoma with pretreatment 3D T1-weighted MRIs were included in the study. Four different spatial resolution combinations and three dynamic ranges were studied for each patient. Sixteen three-dimensional textural heterogeneity measures were computed for each patient and configuration including co-occurrence matrices (CM) features and run-length matrices (RLM) features. The coefficient of variation was used to assess the robustness of the measures in two series of experiments corresponding to (i) changing the dynamic range and (ii) changing the matrix size.

Results

No textural measures were robust under dynamic range changes. Entropy was the only textural feature robust under spatial resolution changes (coefficient of variation under 10% in all cases).

Conclusion

Textural measures of three-dimensional brain tumor images are not robust neither under dynamic range nor under matrix size changes. Standards should be harmonized to use textural features as imaging biomarkers in radiomic-based studies. The implications of this work go beyond the specific tumor type studied here and pose the need for standardization in textural feature calculation of oncological images.

Analysis of heterogeneity in T2-weighted MR images can differentiate pseudoprogression from progression in glioblastoma

PURPOSE

To develop an image analysis technique that distinguishes pseudoprogression from true progression by analyzing tumour heterogeneity in T2-weighted images using topological descriptors of image heterogeneity called Minkowski functionals (MFs).

METHODS

Using a retrospective patient cohort (n = 50), and blinded to treatment response outcome, unsupervised feature estimation was performed to investigate MFs for the presence of outliers, potential confounders, and sensitivity to treatment response. The progression and pseudoprogression groups were then unblinded and supervised feature selection was performed using MFs, size and signal intensity features. A support vector machine model was obtained and evaluated using a prospective test cohort.

RESULTS

The model gave a classification accuracy, using a combination of MFs and size features, of more than 85% in both retrospective and prospective datasets. A different feature selection method (Random Forest) and classifier (Lasso) gave the same results. Although not apparent to the reporting radiologist, the T2-weighted hyperintensity phenotype of those patients with progression was heterogeneous, large and frond-like when compared to those with pseudoprogression.

CONCLUSION

Analysis of heterogeneity, in T2-weighted MR images, which are acquired routinely in the clinic, has the potential to detect an earlier treatment response allowing an early change in treatment strategy. Prospective validation of this technique in larger datasets is required.

Modified Criteria for Radiographic Response Assessment in Glioblastoma Clinical Trials

Radiographic endpoints including response and progression are important for the evaluation of new glioblastoma therapies. The current RANO criteria was developed to overcome many of the challenges identified with previous guidelines for response assessment, however, significant challenges and limitations remain. The current recommendations build on the strengths of the current RANO criteria, while addressing many of these limitations. Modifications to the current RANO criteria include suggestions for volumetric response evaluation, use contrast enhanced T1 subtraction maps to increase lesion conspicuity, removal of qualitative non-enhancing tumor assessment requirements, use of the post-radiation time point as the baseline for newly diagnosed glioblastoma response assessment, and "treatment-agnostic" response assessment rubrics for identifying pseudoprogression, pseudoresponse, and a confirmed durable response in newly diagnosed and recurrent glioblastoma trials.

Advanced MRI Techniques in the Monitoring of Treatment of Gliomas

OPINION STATEMENT

With advances in treatments and survival of patients with glioblastoma (GBM), it has become apparent that conventional imaging sequences have significant limitations both in terms of assessing response to treatment and monitoring disease progression. Both 'pseudoprogression' after chemoradiation for newly diagnosed GBM and 'pseudoresponse' after anti-angiogenesis treatment for relapsed GBM are well-recognised radiological entities. This in turn has led to revision of response criteria away from the standard MacDonald criteria, which depend on the two-dimensional measurement of contrast-enhancing tumour, and which have been the primary measure of radiological response for over three decades. A working party of experts published RANO (Response Assessment in Neuro-oncology Working Group) criteria in 2010 which take into account signal change on T2/FLAIR sequences as well as the contrast-enhancing component of the tumour. These have recently been modified for immune therapies, which are associated with specific issues related to the timing of radiological response. There has been increasing interest in quantification and validation of physiological and metabolic parameters in GBM over the last 10 years utilising the wide range of advanced imaging techniques available on standard MRI platforms. Previously, MRI would provide structural information only on the anatomical location of the tumour and the presence or absence of a disrupted blood-brain barrier. Advanced MRI sequences include proton magnetic resonance spectroscopy (MRS), vascular imaging (perfusion/permeability) and diffusion imaging (diffusion weighted imaging/diffusion tensor imaging) and are now routinely available. They provide biologically relevant functional, haemodynamic, cellular, metabolic and cytoarchitectural information and are being evaluated in clinical trials to determine whether they offer superior biomarkers of early treatment response than conventional imaging, when correlated with hard survival endpoints. Multiparametric imaging, incorporating different combinations of these modalities, improves accuracy over single imaging modalities but has not been widely adopted due to the amount of post-processing analysis required, lack of clinical trial data, lack of radiology training and wide variations in threshold values. New techniques including diffusion kurtosis and radiomics will offer a higher level of quantification but will require validation in clinical trial settings. Given all these considerations, it is clear that there is an urgent need to incorporate advanced techniques into clinical trial design to avoid the problems of under or over assessment of treatment response.

Clinical Applications of Contrast-Enhanced Perfusion MRI Techniques in Gliomas: Recent Advances and Current Challenges

Gliomas possess complex and heterogeneous vasculatures with abnormal hemodynamics. Despite considerable advances in diagnostic and therapeutic techniques for improving tumor management and patient care in recent years, the prognosis of malignant gliomas remains dismal. Perfusion-weighted magnetic resonance imaging techniques that could noninvasively provide superior information on vascular functionality have attracted much attention for evaluating brain tumors. However, nonconsensus imaging protocols and postprocessing analysis among different institutions impede their integration into standard-of-care imaging in clinic. And there have been very few studies providing a comprehensive evidence-based and systematic summary. This review first outlines the status of glioma theranostics and tumor-associated vascular pathology and then presents an overview of the principles of dynamic contrast-enhanced MRI (DCE-MRI) and dynamic susceptibility contrast-MRI (DSC-MRI), with emphasis on their recent clinical applications in gliomas including tumor grading, identification of molecular characteristics, differentiation of glioma from other brain tumors, treatment response assessment, and predicting prognosis. Current challenges and future perspectives are also highlighted.

Amino acid PET and MR perfusion imaging in brain tumours

Purpose

Despite the excellent capacity of the conventional MRI to image brain tumours, problems remain in answering a number of critical diagnostic questions. To overcome these diagnostic shortcomings, PET using radiolabeled amino acids and perfusion-weighted imaging (PWI) are currently under clinical evaluation. The role of amino acid PET and PWI in different diagnostic challenges in brain tumours is controversial.

Methods

Based on the literature and experience of our centres in correlative imaging with PWI and PET using O-(2-[¹⁸F]fluoroethyl)-l-tyrosine or 3,4-dihydroxy-6-[¹⁸F]-fluoro-l-phenylalanine, the current role and shortcomings of amino acid PET and PWI in different diagnostic challenges in brain tumours are reviewed. Literature searches were performed on PubMed, and additional literature was retrieved from the reference lists of identified articles. In particular, all studies in which amino acid PET was directly compared with PWI were included.

Results

PWI is more readily available, but requires substantial expertise and is more sensitive to artifacts than amino acid PET. At initial diagnosis, PWI and amino acid PET can help to define a site for biopsy but amino acid PET appears to be more powerful to define the tumor extent. Both methods are helpful to differentiate progression or recurrence from unspecific posttherapeutic changes. Assessment of therapeutic efficacy can be achieved especially with amino acid PET, while the data with PWI are sparse.

Conclusion

Both PWI and amino acid PET add valuable diagnostic information to the conventional MRI in the assessment of patients with brain tumours, but further studies are necessary to explore the complementary nature of these two methods.

Progressive disease in glioblastoma: Benefits and limitations of semi-automated volumetry

Purpose

Unambiguous evaluation of glioblastoma (GB) progression is crucial, both for clinical trials as well as day by day routine management of GB patients. 3D-volumetry in the follow-up of GB provides quantitative data on tumor extent and growth, and therefore has the potential to facilitate objective disease assessment. The present study investigated the utility of absolute changes in volume (delta) or regional, segmentation-based subtractions for detecting disease progression in longitudinal MRI follow-ups.

Methods

165 high resolution 3-Tesla MRIs of 30 GB patients (23m, mean age 60.2y) were retrospectively included in this single center study. Contrast enhancement (CV) and tumor-related signal alterations in FLAIR images (FV) were semi-automatically segmented. Delta volume (dCV, dFV) and regional subtractions (sCV, sFV) were calculated. Disease progression was classified for every follow-up according to histopathologic results, decisions of the local multidisciplinary CNS tumor board and a consensus rating of the neuro-radiologic report.

Results

A generalized logistic mixed model for disease progression (yes / no) with dCV, dFV, sCV and sFV as input variables revealed that only dCV was significantly associated with prediction of disease progression (P = .005). Delta volume had a better accuracy than regional, segmentation-based subtractions (79% versus 72%) and a higher area under the curve by trend in ROC curves (.83 versus .75).

Conclusion

Absolute volume changes of the contrast enhancing tumor part were the most accurate volumetric determinant to detect progressive disease in assessment of GB and outweighed FLAIR changes as well as regional, segmentation-based image subtractions. This parameter might be useful in upcoming objective response criteria for glioblastoma.

High-resolution whole-brain DCE-MRI using constrained reconstruction: Prospective clinical evaluation in brain tumor patients

PURPOSE

To clinically evaluate a highly accelerated T1-weighted dynamic contrast-enhanced (DCE) MRI technique that provides high spatial resolution and whole-brain coverage via undersampling and constrained reconstruction with multiple sparsity constraints.

METHODS

Conventional (rate-2 SENSE) and experimental DCE-MRI (rate-30) scans were performed 20 minutes apart in 15 brain tumor patients. The conventional clinical DCE-MRI had voxel dimensions 0.9 × 1.3 × 7.0 mm(3), FOV 22 × 22 × 4.2 cm(3), and the experimental DCE-MRI had voxel dimensions 0.9 × 0.9 × 1.9 mm(3), and broader coverage 22 × 22 × 19 cm(3). Temporal resolution was 5 s for both protocols. Time-resolved images and blood-brain barrier permeability maps were qualitatively evaluated by two radiologists.

RESULTS

The experimental DCE-MRI scans showed no loss of qualitative information in any of the cases, while achieving substantially higher spatial resolution and whole-brain spatial coverage. Average qualitative scores (from 0 to 3) were 2.1 for the experimental scans and 1.1 for the conventional clinical scans.

CONCLUSIONS

The proposed DCE-MRI approach provides clinically superior image quality with higher spatial resolution and coverage than currently available approaches. These advantages may allow comprehensive permeability mapping in the brain, which is especially valuable in the setting of large lesions or multiple lesions spread throughout the brain.

Determining priority signs and symptoms for use as clinical outcomes assessments in trials including patients with malignant gliomas: Panel 1 Report

Patients with primary brain tumors such as malignant gliomas are highly symptomatic, often from the time of diagnosis. Signs and symptoms (signs/symptoms) can cause functional limitations that often worsen over the disease trajectory and may impact patient quality of life. It is recognized that standard measurements of tumor response do not adequately measure this impact or the impact that a therapy may have to mitigate these signs/symptoms and potentially have clinical benefit. Identifying a core set of signs/symptoms and functional limitations is important for understanding their clinical impact and is the first step to including clinical outcomes assessment in primary brain tumor clinical trials.

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.

Clinical PET/MRI in neurooncology: opportunities and challenges from a single-institution perspective

Purpose

Magnetic resonance imaging (MRI) plays a key role in neurooncology, i.e., for diagnosis, treatment evaluation and detection of recurrence. However, standard MRI cannot always separate malignant tissue from other pathologies or treatment-induced changes. Advanced MRI techniques such as diffusion-weighted imaging, perfusion imaging and spectroscopy show promising results in discriminating malignant from benign lesions. Further, supplemental imaging with amino acid positron emission tomography (PET) has been shown to increase accuracy significantly and is used routinely at an increasing number of sites. Several centers are now implementing hybrid PET/MRI systems allowing for multiparametric imaging, combining conventional MRI with advanced MRI and amino acid PET imaging. Neurooncology is an obvious focus area for PET/MR imaging.

Methods

Based on the literature and our experience from more than 300 PET/MRI examinations of brain tumors with ¹⁸F-fluoro-ethyl-tyrosine, the clinical use of PET/MRI in adult and pediatric neurooncology is critically reviewed.

Results

Although the results are increasingly promising, the added value and range of indications for multiparametric imaging with PET/MRI are yet to be established. Robust solutions to overcome the number of issues when using a PET/MRI scanner are being developed, which is promising for a more routine use in the future.

Conclusions

In a clinical setting, a PET/MRI scan may increase accuracy in discriminating recurrence from treatment changes, although sequential same-day imaging on separate systems will often constitute a reliable and cost-effective alternative. Pediatric patients who require general anesthesia will benefit the most from simultaneous PET and MR imaging.

MRI Evaluation of Non-Necrotic T2-Hyperintense Foci in Pediatric Diffuse Intrinsic Pontine Glioma

BACKGROUND AND PURPOSE

The conventional MR imaging appearance of diffuse intrinsic pontine glioma suggests intralesional histopathologic heterogeneity, and various distinct lesion components, including T2-hypointense foci, have been described. Here we report the prevalence, conventional MR imaging semiology, and advanced MR imaging features of non-necrotic T2-hyperintense foci in diffuse intrinsic pontine glioma.

MATERIALS AND METHODS

Twenty-five patients with diffuse intrinsic pontine gliomas were included in this study. MR imaging was performed at 3T by using conventional and advanced MR imaging sequences. Perfusion (CBV), vascular permeability (v_e, K^trans), and diffusion (ADC) metrics were calculated and used to characterize non-necrotic T2-hyperintense foci in comparison with other lesion components, namely necrotic T2-hyperintense foci, T2-hypointense foci, peritumoral edema, and normal brain stem. Statistical analysis was performed by using Kruskal-Wallis and Wilcoxon rank sum tests.

RESULTS

Sixteen non-necrotic T2-hyperintense foci were found in 12 tumors. In these foci, ADC values were significantly higher than those in either T2-hypointense foci (P = .002) or normal parenchyma (P = .0002), and relative CBV values were significantly lower than those in either T2-hypointense (P = .0002) or necrotic T2-hyperintense (P = .006) foci. Volume transfer coefficient values in T2-hyperintense foci were lower than those in T2-hypointense (P = .0005) or necrotic T2-hyperintense (P = .0348) foci.

CONCLUSIONS

Non-necrotic T2-hyperintense foci are common, distinct lesion components within diffuse intrinsic pontine gliomas. Advanced MR imaging data suggest low cellularity and an early stage of angioneogenesis with leaky vessels resulting in expansion of the extracellular space. Because of the lack of biopsy validation, the underlying histoarchitectural and pathophysiologic changes remain unclear; therefore, these foci may correspond to a poorly understood biologic event in tumor evolution.

Creation of an NCI comparative brain tumor consortium: informing the translation of new knowledge from canine to human brain tumor patients

On September 14-15, 2015, a meeting of clinicians and investigators in the fields of veterinary and human neuro-oncology, clinical trials, neuropathology, and drug development was convened at the National Institutes of Health campus in Bethesda, Maryland. This meeting served as the inaugural event launching a new consortium focused on improving the knowledge, development of, and access to naturally occurring canine brain cancer, specifically glioma, as a model for human disease. Within the meeting, a SWOT (strengths, weaknesses, opportunities, and threats) assessment was undertaken to critically evaluate the role that naturally occurring canine brain tumors could have in advancing this aspect of comparative oncology aimed at improving outcomes for dogs and human beings. A summary of this meeting and subsequent discussion are provided to inform the scientific and clinical community of the potential for this initiative. Canine and human comparisons represent an unprecedented opportunity to complement conventional brain tumor research paradigms, addressing a devastating disease for which innovative diagnostic and treatment strategies are clearly needed.

Geometrical Measures Obtained from Pretreatment Postcontrast T1 Weighted MRIs Predict Survival Benefits from Bevacizumab in Glioblastoma Patients

Background

Antiangiogenic therapies for glioblastoma (GBM) such as bevacizumab (BVZ), have been unable to extend survival in large patient cohorts. However, a subset of patients having angiogenesis-dependent tumors might benefit from these therapies. Currently, there are no biomarkers allowing to discriminate responders from non-responders before the start of the therapy.

Methods

40 patients from the randomized GENOM009 study complied the inclusion criteria (quality of images, clinical data available). Of those, 23 patients received first line temozolomide (TMZ) for eight weeks and then concomitant radiotherapy and TMZ. 17 patients received BVZ+TMZ for seven weeks and then added radiotherapy to the treatment. Clinical variables were collected, tumors segmented and several geometrical measures computed including: Contrast enhancing (CE), necrotic, and total volumes; equivalent spherical CE width; several geometric measures of the CE ‘rim’ geometry and a set of image texture measures. The significance of the results was studied using Kaplan-Meier and Cox proportional hazards analysis. Correlations were assessed using Spearman correlation coefficients.

Results

Kaplan-Meier and Cox proportional hazards analysis showed that total, CE and inner volume (p = 0.019, HR = 4.258) and geometric heterogeneity of the CE areas (p = 0.011, HR = 3.931) were significant parameters identifying response to BVZ. The group of patients with either regular CE areas (small geometric heterogeneity, median difference survival 15.88 months, p = 0.011) or those with small necrotic volume (median survival difference 14.50 months, p = 0.047) benefited substantially from BVZ.

Conclusion

Imaging biomarkers related to the irregularity of contrast enhancing areas and the necrotic volume were able to discriminate GBM patients with a substantial survival benefit from BVZ. A prospective study is needed to validate our results.

Updates in the management of brain metastases

The clinical management/understanding of brain metastases (BM) has changed substantially in the last 5 years, with key advances and clinical trials highlighted in this review. Several of these changes stem from improvements in systemic therapy, which have led to better systemic control and longer overall patient survival, associated with increased time at risk for developing BM. Development of systemic therapies capable of preventing BM and controlling both intracranial and extracranial disease once BM are diagnosed is paramount. The increase in use of stereotactic radiosurgery alone for many patients with multiple BM is an outgrowth of the desire to employ treatments focused on local control while minimizing cognitive effects associated with whole brain radiotherapy. Complications from BM and their treatment must be considered in comprehensive patient management, especially with greater awareness that the majority of patients do not die from their BM. Being aware of significant heterogeneity in prognosis and therapeutic options for patients with BM is crucial for appropriate management, with greater attention to developing individual patient treatment plans based on predicted outcomes; in this context, recent prognostic models of survival have been extensively revised to incorporate molecular markers unique to different primary cancers.

A longitudinal magnetic resonance elastography study of murine brain tumors following radiation therapy

An accurate and noninvasive method for assessing treatment response following radiotherapy is needed for both treatment monitoring and planning. Measurement of solid tumor volume alone is not sufficient for reliable early detection of therapeutic response, since changes in physiological and/or biomechanical properties can precede tumor volume change following therapy. In this study, we use magnetic resonance elastography to evaluate the treatment effect after radiotherapy in a murine brain tumor model. Shear modulus was calculated and compared between the delineated tumor region of interest (ROI) and its contralateral, mirrored counterpart. We also compared the shear modulus from both the irradiated and non-irradiated tumor and mirror ROIs longitudinally, sampling four time points spanning 9-19 d post tumor implant. Results showed that the tumor ROI had a lower shear modulus than that of the mirror ROI, independent of radiation. The shear modulus of the tumor ROI decreased over time for both the treated and untreated groups. By contrast, the shear modulus of the mirror ROI appeared to be relatively constant for the treated group, while an increasing trend was observed for the untreated group. The results provide insights into the tumor properties after radiation treatment and demonstrate the potential of using the mechanical properties of the tumor as a biomarker. In future studies, more closely spaced time points will be employed for detailed analysis of the radiation effect.

Glioblastoma: does the pre-treatment geometry matter? A postcontrast T1 MRI-based study

BACKGROUND

The potential of a tumour's volumetric measures obtained from pretreatment MRI sequences of glioblastoma (GBM) patients as predictors of clinical outcome has been controversial. Mathematical models of GBM growth have suggested a relation between a tumour's geometry and its aggressiveness.

METHODS

A multicenter retrospective clinical study was designed to study volumetric and geometrical measures on pretreatment postcontrast T1 MRIs of 117 GBM patients. Clinical variables were collected, tumours segmented, and measures computed including: contrast enhancing (CE), necrotic, and total volumes; maximal tumour diameter; equivalent spherical CE width and several geometric measures of the CE "rim". The significance of the measures was studied using proportional hazards analysis and Kaplan-Meier curves.

RESULTS

Kaplan-Meier and univariate Cox survival analysis showed that total volume [p = 0.034, Hazard ratio (HR) = 1.574], CE volume (p = 0.017, HR = 1.659), spherical rim width (p = 0.007, HR = 1.749), and geometric heterogeneity (p = 0.015, HR = 1.646) were significant parameters in terms of overall survival (OS). Multivariable Cox analysis for OS provided the later two parameters as age-adjusted predictors of OS (p = 0.043, HR = 1.536 and p = 0.032, HR = 1.570, respectively).

CONCLUSION

Patients with tumours having small geometric heterogeneity and/or spherical rim widths had significantly better prognosis. These novel imaging biomarkers have a strong individual and combined prognostic value for GBM patients.

KEY POINTS

• Three-dimensional segmentation on magnetic resonance images allows the study of geometric measures. • Patients with small width of contrast enhancing areas have better prognosis. • The irregularity of contrast enhancing areas predicts survival in glioblastoma patients.

Clinical parameters outweigh diffusion- and perfusion-derived MRI parameters in predicting survival in newly diagnosed glioblastoma

BACKGROUND

The purpose of this study was to determine the relevance of clinical data, apparent diffusion coefficient (ADC), and relative cerebral blood volume (rCBV) from dynamic susceptibility contrast (DSC) perfusion and the volume transfer constant (k^trans) from dynamic contrast-enhanced (DCE) perfusion for predicting overall survival (OS) and progression-free survival (PFS) in newly diagnosed treatment-naïve glioblastoma patients.

METHODS

Preoperative MR scans including standardized contrast-enhanced T1 (cT1), T2 - fluid-attenuated inversion recovery (FLAIR), ADC, DSC, and DCE of 125 patients with subsequent histopathologically confirmed glioblastoma were performed on a 3 Tesla MRI scanner. ADC, DSC, and DCE parameters were analyzed in semiautomatically segmented tumor volumes on contrast-enhanced (CE) cT1 and hyperintense signal changes on T2 FLAIR (ED). Univariate and multivariable Cox regression analyses including age, sex, extent of resection (EOR), and KPS were performed to assess the influence of each parameter on OS and PFS.

RESULTS

Univariate Cox regression analysis demonstrated a significant association of age, KPS, and EOR with PFS and age, KPS, EOR, lower ADC, and higher rCBV with OS. Multivariable analysis showed independent significance of male sex, KPS, EOR, and increased rCBV_CE for PFS, and age, sex, KPS, and EOR for OS.

CONCLUSIONS

MRI parameters help to predict OS in a univariate Cox regression analysis, and increased rCBV_CE is associated with shorter PFS in the multivariable model. In summary, however, our findings suggest that the relevance of MRI parameters is outperformed by clinical parameters in a multivariable analysis, which limits their prognostic value for survival prediction at the time of initial diagnosis.

Response Assessment in Pediatric Neuro-Oncology: Implementation and Expansion of the RANO Criteria in a Randomized Phase II Trial of Pediatric Patients with Newly Diagnosed High-Grade Gliomas

Determination of tumor response to treatment in neuro-oncology is challenging, particularly when antiangiogenic agents are considered. Nontumoral factors (eg, blood-brain barrier disruption, edema, and necrosis) can alter contrast enhancement independent of true tumor response/progression. Furthermore, gliomas are often infiltrative, with nonenhancing components. In adults, the Response Assessment in Neuro-Oncology (RANO) criteria attempted to address these issues. No such guidelines exist yet for children. The ongoing randomized phase II trial, A Study of Avastin (bevacizumab) in Combination With Temolozomide (TMZ) and Radiotherapy in Paediatric and Adolescent Patients With High-Grade Glioma (HERBY), will establish the efficacy and safety of the antiangiogenic agent bevacizumab for the first-line treatment of newly diagnosed high-grade glioma in children (n = 121 patients, enrollment complete). The primary end point is event-free survival (tumor progression/recurrence by central review, second primary malignancy, or death). Determination of progression or response is based on predefined clinical and radiographic criteria, modeled on the RANO criteria and supported by expert pseudoprogression review and the use of standardized imaging protocols. The HERBY trial will also compare conventional MR imaging (T1-weighted and T2/fluid-attenuated inversion recovery sequences) with conventional MR imaging plus diffusion/perfusion imaging for response assessment. It is anticipated that HERBY will provide new insights into antiangiogenic-treated pediatric brain tumors. HERBY will also investigate the practicality of obtaining adequate quality diffusion/perfusion scans in a trial setting, and the feasibility of implementing standard imaging protocols across multiple sites. To date, 61/73 (83.6%) patients with available data have completed diffusion-weighted imaging (uptake of other nonconventional techniques has been limited). Harmonization of imaging protocols and techniques may improve the robustness of pediatric neuro-oncology studies and aid future trial comparability.

Report of the Jumpstarting Brain Tumor Drug Development Coalition and FDA clinical trials clinical outcome assessment endpoints workshop (October 15, 2014, Bethesda MD)

On October 15, 2014, a workshop was held on the use of clinical outcome assessments in clinical trials for high-grade glioma of the brain. This workshop was sponsored by the Jumpstarting Brain Tumor Drug Development Coalition, consisting of the National Brain Tumor Society, the Society for Neuro-Oncology, the Musella Foundation for Brain Tumor Research and Information, and Accelerate Brain Cancer Cure. It was planned and carried out with participation from the US Food and Drug Administration. The workshop also included stakeholders from all aspects of the brain tumor community, including clinicians, researchers, industry, clinical research organizations, patients and patient advocates, and the National Cancer Institute. This report summarizes the presentations and discussions of that workshop and the proposals that emerged to move the field forward and toward greater inclusion of these endpoints in future clinical trials for high-grade gliomas.

Advanced MRI increases the diagnostic accuracy of recurrent glioblastoma: Single institution thresholds and validation of MR spectroscopy and diffusion weighted MR imaging

The accurate identification of glioblastoma progression remains an unmet clinical need. The aim of this prospective single-institutional study is to determine and validate thresholds for the main metabolite concentrations obtained by MR spectroscopy (MRS) and the values of the apparent diffusion coefficient (ADC) to enable distinguishing tumor recurrence from pseudoprogression. Thirty-nine patients after the standard treatment of a glioblastoma underwent advanced imaging by MRS and ADC at the time of suspected recurrence — median time to progression was 6.7 months. The highest significant sensitivity and specificity to call the glioblastoma recurrence was observed for the total choline (tCho) to total N-acetylaspartate (tNAA) concentration ratio with the threshold ≥ 1.3 (sensitivity 100.0% and specificity 94.7%). The ADCmean value higher than 1313 × 10^− 6 mm²/s was associated with the pseudoprogression (sensitivity 98.3%, specificity 100.0%). The combination of MRS focused on the tCho/tNAA concentration ratio and the ADCmean value represents imaging methods applicable to early non-invasive differentiation between a glioblastoma recurrence and a pseudoprogression. However, the institutional definition and validation of thresholds for differential diagnostics is needed for the elimination of setup errors before implementation of these multimodal imaging techniques into clinical practice, as well as into clinical trials.

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For an effective salvage treatment, an accurate diagnosis of GBM recurrence is essential.

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The standard structural MRI has limited sensitivity and specificity to distinguish GBM progression.

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GBM recurrence is characterized by the ADCmean value ≤ 1313 × 10^− 6 mm²/s and the tCho/tNAA ratio ≥ 1.3.

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An institutional definition of thresholds is needed, if advanced imaging should be used accurately in clinical practice.

Response Assessment in Neuro-Oncology (RANO): more than imaging criteria for malignant glioma

The introduction of antiangiogenic therapies for the treatment of malignant glioma and the effect of these agents on standard imaging studies were the stimuli for forming a small group of investigators to critically evaluate the limitations of the Macdonald criteria in assessing response to treatment. The initial goal of this group was to highlight the challenges in accurately determining the efficacy of therapeutic interventions for malignant glioma and to develop new criteria that could be implemented in clinical care as well as in the design and conduct of clinical trials. This initial Response Assessment in Neuro-Oncology (RANO) effort started in 2008 and over the last 7 years, it has expanded to include a critical review of response assessment across several tumor types as well as endpoint selection and trial design to improve outcome criteria for neuro-oncological trials. In this paper, we review the overarching principles of the RANO initiative and the efforts to date. We also highlight the diverse and expanding efforts of the multidisciplinary groups of investigators who have volunteered their time as part of this endeavor.