Contrast-enhancing Tumor Research Articles

EXTH-09. TUMOR PHARMACOKINETICS, PHARMACODYNAMICS AND RADIATION SENSITIZATION IN PATIENT-DERIVED XENOGRAFT MODELS OF GLIOBLASTOMA TREATED WITH THE AURORA KINASE A INHIBITOR LY3295668

Abstract Cell-cycle deregulation is at the crux of all malignancies, including glioblastoma (GBM). Aurora Kinase A (AURKA) plays a central role in G2/M transition and faithful chromosome segregation. In this study, we evaluated the pharmacokinetics, pharmacodynamics, and radiation sensitization properties of LY3295668, a highly specific AURKA inhibitor, in orthotopic patient-derived xenograft (PDX) models of GBM. Mice with intracranial tumors were randomized to 50 mg/kg LY3295668 PO BID x 4 days vs. placebo. LY3295668 levels in plasma and contrast-enhancing tumor tissue were measured by liquid chromatography tandem mass spectrometry (LC-MS/MS). Unbound fractions were determined by equilibrium dialysis. Immunohistochemistry was performed to assess levels of pAURKA (T288), phospho-Histone H3 (pHH3), and cleaved caspase 3 (CC3). For survival studies, mice with intracranial tumors were randomized to four cohorts – vehicle, radiotherapy, LY3295668 monotherapy, and LY3295668 plus radiotherapy. The median unbound concentration of LY3295668 was 270.88 nmol/L and 22.33 nmol/kg in plasma and tumor tissue, respectively – significantly higher than the biochemical IC50 of LY3295668 for AURKA inhibition (0.8 nM). A decrease in pHH3(+) cells (0.8% vs. 6.4%, p=0.036) indicated drug-induced mitotic arrest and was accompanied by an increase in CC3(+) cells (6.4% vs. 8.0%, p=0.67). Combination of LY3295668 with radiotherapy prolonged survival compared to either therapy alone in orthotopic GBM PDX models. LY3295668 is well tolerated, achieves pharmacologically-relevant unbound concentrations in GBM PDX models, and is associated with significant target modulation. Preclinical combination of LY3295668 with radiation therapy leads to synergistic effects and supports future clinical study of this multimodal strategy in glioblastoma patients.

Artificial Neural Network-Derived Cerebral Metabolic Rate of Oxygen for Differentiating Glioblastoma and Brain Metastasis in MRI: A Feasibility Study

Glioblastoma may appear similar to cerebral metastasis on conventional MRI in some cases, but their therapies differ significantly. This prospective feasibility study was aimed at differentiating them by applying the quantitative susceptibility mapping and quantitative blood-oxygen-level-dependent (QSM + qBOLD) model to these entities for the first time. We prospectively included 15 untreated patients with glioblastoma (n = 7, median age: 68 years, range: 54–84 years) or brain metastasis (n = 8, median age 66 years, range: 50–78 years) who underwent preoperative MRI including multi-gradient echo and arterial spin labeling sequences. Oxygen extraction fraction (OEF), cerebral blood flow (CBF) and cerebral metabolic rate of oxygen (CMRO2) were calculated in the contrast-enhancing tumor (CET) and peritumoral non-enhancing T2 hyperintense region (NET2), using an artificial neural network. We demonstrated that OEF in CET was significantly lower (p = 0.03) for glioblastomas than metastases, all features were significantly higher (p = 0.01) in CET than in NET2 for metastasis patients only, and the ratios of CET/NET2 for CBF (p = 0.04) and CMRO2 (p = 0.01) were significantly higher in metastasis patients than in glioblastoma patients. Discriminative power of a support-vector machine classifier was highest with a combination of two features, yielding an area under the receiver operating characteristic curve of 0.94 with 93% diagnostic accuracy. QSM + qBOLD allows for robust differentiation of glioblastoma and cerebral metastasis while yielding insights into tumor oxygenation.

Evaluating potential of multi-parametric MRI using co-registered histology: Application to a mouse model of glioblastoma

BackgroundConventional MRI fails to detect regions of glioblastoma cell infiltration beyond the contrast-enhanced T1 solid tumor region, with infiltrating tumor cells often migrating along host blood vessels. PurposeMRI is capable of generating a range of image contrasts which are commonly assessed individually by qualitative visual inspection. It has long been hypothesized that better diagnoses could be achieved by combining these multiple images, so called multi-parametric or multi-spectral MRI. However, the lack of clinical histology and the difficulties of co-registration, has meant this hypothesis has never been rigorously tested. Here we test this hypothesis, using a previously published multi-dimensional dataset consisting of registered MR images and histology. Study typeAnimal Model. SubjectsMice bearing orthotopic glioblastoma xenografts generated from a patient-derived glioblastoma cell line. Field strength/sequences7 Tesla, T1/T2 weighted, T2 mapping, contrast enhance T1, diffusion-weighted, diffusion tensor imaging. AssessmentImmunohistochemistry sections were stained for Human Leukocyte Antigen (probing human-derived tumor cells). To achieve quantitative MRI-tissue comparison, multiple histological slices cut in the MRI plane were stacked to produce tumor cell density maps acting as ‘ground truth’. Statistical testsSensitivity, specificity, accuracy and Dice similarity indices were calculated. ANOVA, t-test, Bonferroni correction and Pearson coefficients were used for statistical analysis. ResultsCorrelation coefficient analysis with co-registered 'ground truth' histology showed interactive regression maps had higher correlation coefficients and sensitivity values than T2W, ADC, FA, and T2map. Further, the interaction regression maps showed statistical improved detection of tumor volume. Data conclusionVoxel-by-voxel analysis provided quantitative evidence confirming the hypothesis that mpMRI can, potentially, better distinguish between the tumor region and normal tissue.

Deep-learning-based synthesis of post-contrast T1-weighted MRI for tumour response assessment in neuro-oncology: a multicentre, retrospective cohort study

Gadolinium-based contrast agents (GBCAs) are widely used to enhance tissue contrast during MRI scans and play a crucial role in the management of patients with cancer. However, studies have shown gadolinium deposition in the brain after repeated GBCA administration with yet unknown clinical significance. We aimed to assess the feasibility and diagnostic value of synthetic post-contrast T1-weighted MRI generated from pre-contrast MRI sequences through deep convolutional neural networks (dCNN) for tumour response assessment in neuro-oncology. In this multicentre, retrospective cohort study, we used MRI examinations to train and validate a dCNN for synthesising post-contrast T1-weighted sequences from pre-contrast T1-weighted, T2-weighted, and fluid-attenuated inversion recovery sequences. We used MRI scans with availability of these sequences from 775 patients with glioblastoma treated at Heidelberg University Hospital, Heidelberg, Germany (775 MRI examinations); 260 patients who participated in the phase 2 CORE trial (1083 MRI examinations, 59 institutions); and 505 patients who participated in the phase 3 CENTRIC trial (3147 MRI examinations, 149 institutions). Separate training runs to rank the importance of individual sequences and (for a subset) diffusion-weighted imaging were conducted. Independent testing was performed on MRI data from the phase 2 and phase 3 EORTC-26101 trial (521 patients, 1924 MRI examinations, 32 institutions). The similarity between synthetic and true contrast enhancement on post-contrast T1-weighted MRI was quantified using the structural similarity index measure (SSIM). Automated tumour segmentation and volumetric tumour response assessment based on synthetic versus true post-contrast T1-weighted sequences was performed in the EORTC-26101 trial and agreement was assessed with Kaplan-Meier plots. The median SSIM score for predicting contrast enhancement on synthetic post-contrast T1-weighted sequences in the EORTC-26101 test set was 0·818 (95% CI 0·817-0·820). Segmentation of the contrast-enhancing tumour from synthetic post-contrast T1-weighted sequences yielded a median tumour volume of 6·31 cm3 (5·60 to 7·14), thereby underestimating the true tumour volume by a median of -0·48 cm3 (-0·37 to -0·76) with the concordance correlation coefficient suggesting a strong linear association between tumour volumes derived from synthetic versus true post-contrast T1-weighted sequences (0·782, 0·751-0·807, p<0·0001). Volumetric tumour response assessment in the EORTC-26101 trial showed a median time to progression of 4·2 months (95% CI 4·1-5·2) with synthetic post-contrast T1-weighted and 4·3 months (4·1-5·5) with true post-contrast T1-weighted sequences (p=0·33). The strength of the association between the time to progression as a surrogate endpoint for predicting the patients' overall survival in the EORTC-26101 cohort was similar when derived from synthetic post-contrast T1-weighted sequences (hazard ratio of 1·749, 95% CI 1·282-2·387, p=0·0004) and model C-index (0·667, 0·622-0·708) versus true post-contrast T1-weighted MRI (1·799, 95% CI 1·314-2·464, p=0·0003) and model C-index (0·673, 95% CI 0·626-0·711). Generating synthetic post-contrast T1-weighted MRI from pre-contrast MRI using dCNN is feasible and quantification of the contrast-enhancing tumour burden from synthetic post-contrast T1-weighted MRI allows assessment of the patient's response to treatment with no significant difference by comparison with true post-contrast T1-weighted sequences with administration of GBCAs. This finding could guide the application of dCNN in radiology to potentially reduce the necessity of GBCA administration. Deutsche Forschungsgemeinschaft.

A Crowdsourced Consensus on Supratotal Resection Versus Gross Total Resection for Anatomically Distinct Primary Glioblastoma.

Gross total resection (GTR) of contrast-enhancing tumor is associated with increased survival in primary glioblastoma. Recently, there has been increasing interest in performing supratotal resections (SpTRs) for glioblastoma. To address the published results, which have varied in part due to lack of consensus on the definition and appropriate use of SpTR. A crowdsourcing approach was used to survey 21 neurosurgical oncologists representing 14 health systems nationwide. Participants were presented with 11 definitions of SpTR and asked to rate the appropriateness of each definition. Participants reviewed T1-weighed postcontrast and fluid-attenuated inversion-recovery magnetic resonance imaging for 22 anatomically distinct glioblastomas. Participants were asked to assess the tumor location's eloquence, the perceived equipoise of enrolling patients in a randomized trial comparing gross total to SpTR, and their personal treatment plans. Most neurosurgeons surveyed (n=18, 85.7%) agree that GTR plus resection of some noncontrast enhancement is an appropriate definition for SpTR. Overall, moderate inter-rater agreement existed regarding eloquence, equipoise, and personal treatment plans. The 4 neurosurgeons who had performed >10 SpTRs for glioblastomas in the past year were more likely to recommend it as their treatment plan (P <.005). Cases were divided into 3 anatomically distinct groups based upon perceived eloquence. Anterior temporal and right frontal glioblastomas were considered the best randomization candidates. We established a consensus definition for SpTR of glioblastoma and identified anatomically distinct locations deemed most amenable to SpTR. These results may be used to plan prospective trials investigating the potential clinical utility of SpTR for glioblastoma.

Metabolic Tumor Microenvironment Characterization of Contrast Enhancing Brain Tumors Using Physiologic MRI.

The tumor microenvironment is a critical regulator of cancer development and progression as well as treatment response and resistance in brain neoplasms. The available techniques for investigation, however, are not well suited for noninvasive in vivo characterization in humans. A total of 120 patients (59 females; 61 males) with newly diagnosed contrast-enhancing brain tumors (64 glioblastoma, 20 brain metastases, 15 primary central nervous system (CNS) lymphomas (PCNSLs), and 21 meningiomas) were examined with a previously established physiological MRI protocol including quantitative blood-oxygen-level-dependent imaging and vascular architecture mapping. Six MRI biomarker maps for oxygen metabolism and neovascularization were fused for classification of five different tumor microenvironments: glycolysis, oxidative phosphorylation (OxPhos), hypoxia with/without neovascularization, and necrosis. Glioblastoma showed the highest metabolic heterogeneity followed by brain metastasis with a glycolysis-to-OxPhos ratio of approximately 2:1 in both tumor entities. In addition, glioblastoma revealed a significant higher percentage of hypoxia (24%) compared to all three other brain tumor entities: brain metastasis (7%; p < 0.001), PCNSL (8%; p = 0.001), and meningioma (8%; p = 0.003). A more aggressive biological brain tumor behavior was associated with a higher percentage of hypoxia and necrosis and a lower percentage of remaining vital tumor tissue and aerobic glycolysis. The proportion of oxidative phosphorylation, however, was rather similar (17–26%) for all four brain tumor entities. Tumor microenvironment (TME) mapping provides insights into neurobiological differences of contrast-enhancing brain tumors and deserves further clinical cancer research attention. Although there is a long roadmap ahead, TME mapping may become useful in order to develop new diagnostic and therapeutic approaches.

Convolutional Neural Networks for Classifying Laterality of Vestibular Schwannomas on Single MRI Slices-A Feasibility Study.

Introduction: Many proposed algorithms for tumor detection rely on 2.5/3D convolutional neural networks (CNNs) and the input of segmentations for training. The purpose of this study is therefore to assess the performance of tumor detection on single MRI slices containing vestibular schwannomas (VS) as a computationally inexpensive alternative that does not require the creation of segmentations. Methods: A total of 2992 T1-weighted contrast-enhanced axial slices containing VS from the MRIs of 633 patients were labeled according to tumor location, of which 2538 slices from 539 patients were used for training a CNN (ResNet-34) to classify them according to the side of the tumor as a surrogate for detection and 454 slices from 94 patients were used for internal validation. The model was then externally validated on contrast-enhanced and non-contrast-enhanced slices from a different institution. Categorical accuracy was noted, and the results of the predictions for the validation set are provided with confusion matrices. Results: The model achieved an accuracy of 0.928 (95% CI: 0.869–0.987) on contrast-enhanced slices and 0.795 (95% CI: 0.702–0.888) on non-contrast-enhanced slices from the external validation cohorts. The implementation of Gradient-weighted Class Activation Mapping (Grad-CAM) revealed that the focus of the model was not limited to the contrast-enhancing tumor but to a larger area of the cerebellum and the cerebellopontine angle. Conclusions: Single-slice predictions might constitute a computationally inexpensive alternative to training 2.5/3D-CNNs for certain detection tasks in medical imaging even without the use of segmentations. Head-to-head comparisons between 2D and more sophisticated architectures could help to determine the difference in accuracy, especially for more difficult tasks.

Intracranial meningioma surveillance using volumetrics from T2-weighted MRI.

The gold standard for imaging of meningiomas is MRI with gadolinium-based contrast agent. Due to increased costs, time, and uncertain chronic effects of gadolinium exposure, use of noncontrast T2-weighted imaging (T2WI) in lieu of contrast-enhanced MRI has been an increasing focus of research across various diagnostic scenarios. The purpose of this study was to evaluate the diagnostic accuracy of T2WI in detecting changes in meningioma tumor volume. Imaging and clinical data were reviewed for 82 consecutive patients undergoing MR-surveillance of intracranial meningioma. Using volumetric-T2WI, two neuroradiologists independently calculated tumor volumes. Measurements were compared to a baseline study contrast-enhanced T1 tumor volume. Using contrast-enhanced sequences as the reference standard, statistical analysis was performed to determine the accuracy of T2WI in detecting changes of meningioma volume. Using only T2WI, readers detected meningioma volume change ≥ 20% in 19/82 patients and volume change <20% in 63/82 patients. Reader accuracy for detecting change in tumor volume on T2WI ≥ 20% was 0.85, sensitivity 0.65, specificity 0.93, positive predictive value (PPV) 0.79, and negative predictive value (NPV) 0.87. For meningiomas >1 ml, reader accuracy for detecting change in tumor volume on T2WI ≥20% was 0.90, sensitivity 0.78, specificity 0.95, PPV 0.88, and NPV 0.91. Change in tumor volume on T2WI ≥20% was detected with 100% accuracy for posterior fossa meningiomas. Inter-reader agreement for all meningiomas was moderate (κ = 0.45) improving to substantial agreement (κ = 0.77) with tumor volumes >1 ml. Volumetric-T2WI detects changes in meningioma volume with comparable accuracy to gold standard T1 postcontrast imaging, particularly with higher tumor volumes and posterior fossa locations.

Radiation Therapy for Grade 3 Gliomas: Correlation of MRI Findings With Prognosis.

Background and objectivePostoperative radiotherapy is usually indicated for both grade 3 glioma and grade 4 glioblastoma. However, the treatment results and tumor features of grade 3 glioma clearly differ from those of glioblastoma. There is limited information on outcomes and tumor progression for grade 3 glioma. In this study, we evaluate the result of postoperative radiotherapy for grade 3 glioma and focus on the correlation of MRI findings with prognosis.MethodsIn this study, 99 of 110 patients with grade 3 glioma who received postoperative radiotherapy and were followed up for more than one year were retrospectively analyzed. The total irradiation dose was 60.0 Gy in 30 fractions, and daily temozolomide or two cycles of nimustine (ACNU) was concurrently administered during radiotherapy. The median follow-up period was 46 months (range: 2-151 months).ResultsIn multivariate analysis, pathology [anaplastic oligodendroglioma (AO) vs. anaplastic astrocytoma (AA)], the status of surgical resection (biopsy vs. partial resection or more), and contrast enhancement (enhanced by MRI image or not) were significant factors for overall survival (OS). The five-year OS for AO vs. AA cases were 76.8% vs. 46.1%, total to partial resection vs. biopsy cases were 72.7% vs. 21.0%, and non-enhanced vs. enhanced cases were 82.5% vs. 45.6%, respectively. In multivariate analysis, the status of surgical resection and longer extension of preoperative edema (PE) were significant factors for progression-free survival (PFS). The five-year PFS for the total to partial resection vs. biopsy cases were 52.9% vs. 10.7%, and non-extensive PE vs. extensive PE (EPE) cases were 62.2% vs. 19.1%, respectively.ConclusionOur results suggest that a contrast-enhanced tumor on MRI and a longer PE may also be significantly associated with OS and PFS among grade 3 glioma patients.

Fully automatic brain tumor segmentation for 3D evaluation in augmented reality.

For currently available augmented reality workflows, 3D models need to be created with manual or semiautomatic segmentation, which is a time-consuming process. The authors created an automatic segmentation algorithm that generates 3D models of skin, brain, ventricles, and contrast-enhancing tumor from a single T1-weighted MR sequence and embedded this model into an automatic workflow for 3D evaluation of anatomical structures with augmented reality in a cloud environment. In this study, the authors validate the accuracy and efficiency of this automatic segmentation algorithm for brain tumors and compared it with a manually segmented ground truth set. Fifty contrast-enhanced T1-weighted sequences of patients with contrast-enhancing lesions measuring at least 5 cm3 were included. All slices of the ground truth set were manually segmented. The same scans were subsequently run in the cloud environment for automatic segmentation. Segmentation times were recorded. The accuracy of the algorithm was compared with that of manual segmentation and evaluated in terms of Sørensen-Dice similarity coefficient (DSC), average symmetric surface distance (ASSD), and 95th percentile of Hausdorff distance (HD95). The mean ± SD computation time of the automatic segmentation algorithm was 753 ± 128 seconds. The mean ± SD DSC was 0.868 ± 0.07, ASSD was 1.31 ± 0.63 mm, and HD95 was 4.80 ± 3.18 mm. Meningioma (mean 0.89 and median 0.92) showed greater DSC than metastasis (mean 0.84 and median 0.85). Automatic segmentation had greater accuracy for measuring DSC (mean 0.86 and median 0.87) and HD95 (mean 3.62 mm and median 3.11 mm) of supratentorial metastasis than those of infratentorial metastasis (mean 0.82 and median 0.81 for DSC; mean 5.26 mm and median 4.72 mm for HD95). The automatic cloud-based segmentation algorithm is reliable, accurate, and fast enough to aid neurosurgeons in everyday clinical practice by providing 3D augmented reality visualization of contrast-enhancing intracranial lesions measuring at least 5 cm3. The next steps involve incorporation of other sequences and improving accuracy with 3D fine-tuning in order to expand the scope of augmented reality workflow.

Case Report: End-Stage Recurrent Glioblastoma Treated With a New Noninvasive Non-Contact Oncomagnetic Device.

Alternating electric field therapy has been approved for glioblastoma (GBM). We have preclinical evidence for anticancer effects in GBM cell cultures and mouse xenografts with an oscillating magnetic field (OMF) generating device. Here we report OMF treatment of end-stage recurrent glioblastoma in a 53-year-old man who had undergone radical surgical excision and chemoradiotherapy, and experimental gene therapy for a left frontal tumor. He experienced tumor recurrence and progressive enlargement with leptomeningeal involvement. OMF for 5 weeks was well tolerated, with 31% reduction of contrast-enhanced tumor volume and reduction in abnormal T2-weighted Fluid-Attenuated Inversion Recovery volume. Tumor shrinkage appeared to correlate with treatment dose. These findings suggest a powerful new noninvasive therapy for glioblastoma.

OTEH-2. High-dimensional analysis of spatial immune cell heterogeneity in glioblastoma reveals differences between contrast-enhancing and non-contrast-enhancing tumor rims

BackgroundGlioblastoma (GBM) is the most common primary malignant brain tumor in adults. GBM remains an incurable disease, with a median survival ~20 months. Complex intercellular interactions within the tumor microenvironment and spatial heterogeneity have challenged and impeded therapeutic efficacy. The non-contrast-enhancing (by T1-weighted MRI) rim of GBM is not always safely resectable and represents a major source of recurrence. We hypothesized that differential immune infiltration is an underlying factor of spatial heterogeneity in GBM, particularly in the non-contrast-enhancing tumor rim.MethodsFive patients with newly diagnosed GBM (ages 53–84) were recruited to a device feasibility study (NCT04545177) utilizing an intraoperative high-resolution MRI-based navigation system coupled with the NICO Myriad (a non-ablative semi-automated resection tool) and a coupled automated biological Tissue Preservation System (NICO APS) to sample spatially mapped regions of tumors in a reproducible and minimally destructive manner. We obtained brain tumor tissue from: (a) tumor core, (b) contrast-enhancing tumor rim and (c) non-contrast-enhancing tumor rim. Downstream processing consisted of digestion of tumor tissue (Miltenyi human tumor digestion kit) for subsequent single-cell isolation, viability assessment and immediate staining for multiparametric flow cytometry for immune profiling.ResultsViability varied across sampled regions (median 85%, range 52–100%). With the exception of 1 sample, viability was >70% in all specimens. High-dimensional analysis with 26 marker flow cytometry revealed spatial heterogeneity in the frequency of myeloid-derived suppressor cell subsets, regulatory T cells, CD8+ T cells, as well as expression of T cell activation and exhaustion markers.ConclusionsSemi-automated, spatially mapped intraoperative sampling of GBM with high viability of specimens is feasible and reproducible with the NICO Myriad and APS devices. High-dimensional analysis of immune cells in the GBM microenvironment captured the spatial heterogeneity of GBM. Future studies will expand on these observations by analyzing more patient specimens in combination with multiple omics assays.

Meningioma in shape

Objective: The aim of this study was to evaluate the possible relationship between the appearance of tumour margins of atypical meningiomas and the risk of tumour recurrence, as well as progression-free survival. We also evaluated the correlations between the tumour margins and the neuroimaging characteristics (e.g. brain oedema and contrast enhancement) along with pathological features (e.g. brain invasion and mean value of Ki-67 LI).&#x0D; Material and methods: In our study, we included 81 patients diagnosed with atypical meningioma (grade II meningioma), who have undergone surgery at the "Prof. Dr N. Oblu" Emergency Clinical Hospital Iasi, between January 1, 2010, and December 31, 2019. We followed the MRI imaging characteristics (e.g. tumour margins patterns, contrast enhancement, oedema grading and tumour volume), but also the pathological characteristics such as brain invasion and the mean value of the Ki-67 labelling index. The assessment of tumour recurrence was made using MRI imaging (T1+ contrast), over a follow-up period of 5 years after the surgery.&#x0D; Results: In our study, we observed that 59.3% (n=48) of meningiomas had an irregular appearance. The irregular margins predominated in the male population (65.1%) and were statistically significantly correlated with brain oedema (p&lt;0.001), contrast enhancement (p&lt;0.01), anatomical location (p&lt;0.014) and the mean value of the Ki-67 labelling index (p&lt;0.01). The tumour margins were not correlated with brain invasion or volume of meningiomas.&#x0D; Conclusion: In our series of patients we found that the irregular margin was not a prognostic factor for tumour recurrence over a period of 5 years or for progression-free survival.

Influence of supramarginal resection on survival outcomes after gross-total resection of IDH-wild-type glioblastoma.

The authors' goal was to use a multicenter, observational cohort study to determine whether supramarginal resection (SMR) of FLAIR-hyperintense tumor beyond the contrast-enhanced (CE) area influences the overall survival (OS) of patients with isocitrate dehydrogenase-wild-type (IDH-wt) glioblastoma after gross-total resection (GTR). The medical records of 888 patients aged ≥ 18 years who underwent resection of GBM between January 2011 and December 2017 were reviewed. Volumetric measurements of the CE tumor and surrounding FLAIR-hyperintense tumor were performed, clinical variables were obtained, and associations with OS were analyzed. In total, 101 patients with newly diagnosed IDH-wt GBM who underwent GTR of the CE tumor met the inclusion criteria. In multivariate analysis, age ≥ 65 years (HR 1.97; 95% CI 1.01-2.56; p < 0.001) and contact with the lateral ventricles (HR 1.59; 95% CI 1.13-1.78; p = 0.025) were associated with shorter OS, but preoperative Karnofsky Performance Status ≥ 70 (HR 0.47; 95% CI 0.27-0.89; p = 0.006), MGMT promotor methylation (HR 0.63; 95% CI 0.52-0.99; p = 0.044), and increased percentage of SMR (HR 0.99; 95% CI 0.98-0.99; p = 0.02) were associated with longer OS. Finally, 20% SMR was the minimum percentage associated with beneficial OS (HR 0.56; 95% CI 0.35-0.89; p = 0.01), but > 60% SMR had no significant influence (HR 0.74; 95% CI 0.45-1.21; p = 0.234). SMR is associated with improved OS in patients with IDH-wt GBM who undergo GTR of CE tumor. At least 20% SMR of the CE tumor was associated with beneficial OS, but greater than 60% SMR had no significant influence on OS.

Rationale and Clinical Implications of Fluorescein-Guided Supramarginal Resection in Newly Diagnosed High-Grade Glioma.

Current standard of care for glioblastoma is surgical resection followed by temozolomide chemotherapy and radiation. Recent studies have demonstrated that >95% extent of resection is associated with better outcomes, including prolonged progression-free and overall survival. The diffusely infiltrative pattern of growth in gliomas results in microscopic extension of tumor cells into surrounding brain parenchyma that makes complete resection unattainable. The historical goal of surgical management has therefore been maximal safe resection, traditionally guided by MRI and defined as removal of all contrast-enhancing tumor. Optimization of surgical resection has led to the concept of supramarginal resection, or removal beyond the contrast-enhancing region on MRI. This strategy of extending the cytoreductive goal targets a tumor region thought to be important in the recurrence or progression of disease as well as resistance to systemic and local treatment. This approach must be balanced against the risk of impacting eloquent regions of brain and causing permanent neurologic deficit, an important factor affecting overall survival. Over the years, fluorescent agents such as fluorescein sodium have been explored as a means of more reliably delineating the boundary between tumor core, tumor-infiltrated brain, and surrounding cortex. Here we examine the rationale behind extending resection into the infiltrative tumor margins, review the current literature surrounding the use of fluorescein in supramarginal resection of gliomas, discuss the experience of our own institution in utilizing fluorescein to maximize glioma extent of resection, and assess the clinical implications of this treatment strategy.

A multisite clinical trial of spectroscopic MRI-guided radiation dose escalation for newly-diagnosed glioblastomas.

2018 Background: Glioblastoma (GBM) is the most common adult primary malignant brain tumor. These pts have poor outcomes [median overall survival (OS) ̃ 16 months] despite radiation therapy (RT) to 60 Gy and temozolomide (TMZ). Magnetic resonance spectroscopy (MRS) measures levels of specific metabolites in the brain including choline (Cho) and N-acetyl aspartate (NAA). Previously, we found that high Cho/NAA ratios can aid in localizing regions of brain at high risk for GBM recurrence that may not be appreciated on standard contrast-enhanced (CE) MRI. Based on this finding, we conducted a clinical trial to assess the feasibility and safety of using an advanced volumetric MRS technique termed spectroscopic MRI (sMRI) to guide RT dose escalation for newly-diagnosed GBMs. Methods: Our clinical trial (NCT03137888) funded by the NCI (RO1CA214557) enrolled pts at 3 institutions (Emory U, U Miami, Johns Hopkins U) from 5/2017 to 4/2019. This study was approved by the IRB at each respective institution. Eligibility criteria included newly-diagnosed GBM pts ≥ 18 years of age with a tumor site that could be adequately imaged by sMRI. Cho/NAA ratio was normalized to the contralateral normal appearing white matter (NAWM). For RT planning, standard gross tumor volumes (GTV1 &amp; 2) were defined based on T2-FLAIR and T1 CE MRIs and 5 mm margins were added to generate clinical tumor volumes (CTV1 &amp; 2). GTV3 ( = CTV3, sMRI-defined) was generated by the union of residual CE tumor and Cho/NAA ≥ 2x NAWM. To remain eligible, CTV3 was required to be ≤ 65 cc. Planning target volumes (PTVs) were generated by applying a 3 mm margin around CTVs. 50.1, 60 and 75 Gy in 30 fractions were prescribed to PTV1, PTV2 and PTV3, respectively. All pts received standard concurrent/adjuvant TMZ. Survival curves were generated by the Kaplan-Meier method. Toxicities were assessed according to CTCAE v4.0. Results: 30 pts met eligibility and were treated on study. Mean/median ages were 56.4/58.9 years. 9 pts (30%) were MGMT methylated; 2 pts (6.7%) harbored an IDH1 mutation. With median followup of 21.4 months in censored pts, median OS was 23.0 months. 11 of 30 pts were documented to have experienced grade 3 or greater toxicities that were at least possibly due to their treatment. Of the 7 pts who experienced these by 9 months post-RT, most were attributable to TMZ (thrombocytopenia x 4, thrombocytopenia/neutropenia x 1, transaminitis x 1) and only one case (headaches/fatigue x 1) could potentially be ascribed to RT. Increased risk of pseudoprogression or radiation necrosis, especially beyond 3 months post-RT, was noted but these were clinically manageable and did not result in toxicity ≥ grade 3. Conclusions: Dose-escalated RT to 75 Gy guided by sMRI appears feasible and safe for pts with newly-diagnosed GBMs. OS outcome is also quite promising and warrants additional testing. Based on these results, a phase II randomized trial is planned at ECOG-ACRIN (EAF211). Clinical trial information: NCT03137888.

Intraoperative B-Mode Ultrasound Guided Surgery and the Extent of Glioblastoma Resection: A Randomized Controlled Trial.

BackgroundIntraoperative MRI and 5-aminolaevulinic acid guided surgery are useful to maximize the extent of glioblastoma resection. Intraoperative ultrasound is used as a time-and cost-effective alternative, but its value has never been assessed in a trial. The goal of this randomized controlled trial was to assess the value of intraoperative B-mode ultrasound guided surgery on the extent of glioblastoma resection.Materials and MethodsIn this randomized controlled trial, patients of 18 years or older with a newly diagnosed presumed glioblastoma, deemed totally resectable, presenting at the Erasmus MC (Rotterdam, The Netherlands) were enrolled and randomized (1:1) into intraoperative B-mode ultrasound guided surgery or resection under standard neuronavigation. The primary outcome of this study was complete contrast-enhancing tumor resection, assessed quantitatively by a blinded neuroradiologist on pre- and post-operative MRI scans. This trial was registered with ClinicalTrials.gov (NCT03531333).ResultsWe enrolled 50 patients between November 1, 2016 and October 30, 2019. Analysis was done in 23 of 25 (92%) patients in the intraoperative B-mode ultrasound group and 24 of 25 (96%) patients in the standard surgery group. Eight (35%) of 23 patients in the intraoperative B-mode ultrasound group and two (8%) of 24 patients in the standard surgery group underwent complete resection (p=0.036). Baseline characteristics, neurological outcome, functional performance, quality of life, complication rates, overall survival and progression-free survival did not differ between treatment groups (p>0.05).ConclusionsIntraoperative B-mode ultrasound enables complete resection more often than standard surgery without harming patients and can be considered to maximize the extent of glioblastoma resection during surgery.

Asynchrony in Peritumoral Resting-State Blood Oxygen Level-Dependent fMRI Predicts Meningioma Grade and Invasion.

Meningioma grade is determined by histologic analysis, with detectable brain invasion resulting in a diagnosis of grade II or III tumor. However, tissue undersampling is a common problem, and invasive parts of the tumor can be missed, resulting in the incorrect assignment of a lower grade. Radiographic biomarkers may be able to improve the diagnosis of grade and identify targets for biopsy. Prior work in patients with gliomas has shown that the resting-state blood oxygen level-dependent fMRI signal within these tumors is not synchronous with normal brain. We hypothesized that blood oxygen level-dependent asynchrony, a functional marker of vascular dysregulation, could predict meningioma grade. We identified 25 patients with grade I and 11 patients with grade II or III meningiomas. Blood oxygen level-dependent time-series were extracted from the tumor and the radiographically normal control hemisphere and were included as predictors in a multiple linear regression to generate a blood oxygen level-dependent asynchrony map, in which negative values signify synchronous and positive values signify asynchronous activity relative to healthy brain. Masks of blood oxygen level-dependent asynchrony were created for each patient, and the fraction of the mask that extended beyond the contrast-enhancing tumor was computed. The spatial extent of blood oxygen level-dependent asynchrony was greater in high (grades II and III) than in low (I) grade tumors (P < 0.001) and could discriminate grade with high accuracy (area under the curve = 0.88). Blood oxygen level-dependent asynchrony radiographically discriminates meningioma grade and may provide targets for biopsy collection to aid in histologic diagnosis.

Changing Enhancement Pattern and Tumor Volume of Vestibular Schwannomas After Subtotal Resection

Surgical strategy in vestibular schwannomas may require subtotal resection to preserve neurologic function. Residual tumor growth pattern and contrast enhancement in the immediate postresection period remain uncertain. We sought to evaluate changes in the enhancement pattern and volume of vestibular schwannomas after subtotal resection in the immediate postoperative period. Volumetric analysis of tumor size and enhancement patterns of vestibular schwannomas were measured on magnetic resonance imaging (MRI) scans obtained within 3 days of surgery, 3 months after surgery, and 1 year after surgery. Nineteen patients were eligible for inclusion in the study (9 male and 10 female) with an average age of 47 years. Contrast enhancement was absent in 6 of 19 (32%) of cases on the immediate postresection MRI with return of expected enhancement on subsequent studies. Volumetric analysis identified that tumors decreased in size by an average of 35% in the first 3 months (P= 0.025) after resection and 46% in the first year after resection (P < 0.01). Vestibular schwannomas that undergo subtotal resection tend to decrease in size over the first 3 months after resection. Residual tumor volume may fail to enhance on the immediate postresection MRI. Both of these findings could lead surgeons to misinterpret degree of resection after surgery and have implications for clinical decision making and research reporting in the scientific literature for vestibular schwannomas after subtotal resection.

Radiomic Analysis to Predict Outcome in Recurrent Glioblastoma Based on Multi-Center MR Imaging From the Prospective DIRECTOR Trial

BackgroundBased on promising results from radiomic approaches to predict O6-methylguanine DNA methyltransferase promoter methylation status (MGMT status) and clinical outcome in patients with newly diagnosed glioblastoma, the current study aimed to evaluate radiomics in recurrent glioblastoma patients.MethodsPre-treatment MR-imaging data of 69 patients enrolled into the DIRECTOR trial in recurrent glioblastoma served as a training cohort, and 49 independent patients formed an external validation cohort. Contrast-enhancing tumor and peritumoral volumes were segmented on MR images. 180 radiomic features were extracted after application of two MR intensity normalization techniques: fixed number of bins and linear rescaling. Radiomic feature selection was performed via principal component analysis, and multivariable models were trained to predict MGMT status, progression-free survival from first salvage therapy, referred to herein as PFS2, and overall survival (OS). The prognostic power of models was quantified with concordance index (CI) for survival data and area under receiver operating characteristic curve (AUC) for the MGMT status.ResultsWe established and validated a radiomic model to predict MGMT status using linear intensity interpolation and considering features extracted from gadolinium-enhanced T1-weighted MRI (training AUC = 0.670, validation AUC = 0.673). Additionally, models predicting PFS2 and OS were found for the training cohort but were not confirmed in our validation cohort.ConclusionsA radiomic model for prediction of MGMT promoter methylation status from tumor texture features in patients with recurrent glioblastoma was successfully established, providing a non-invasive approach to anticipate patient’s response to chemotherapy if biopsy cannot be performed. The radiomic approach to predict PFS2 and OS failed.