Baseline pretreatment contrast enhancing tumor volume including central necrosis is a prognostic factor in recurrent glioblastoma: evidence from single and multicenter trials

Unlocking Hope: Anti-VEGFR inhibitors and their potential in glioblastoma treatment

PURPOSE

This systematic review summarizes evidence of VEGFR gene mutations and VEGF/VEGFR protein expression in glioblastoma multiforme (GBM) patients, alongside the efficacy and safety of anti-VEGFR tyrosine kinase inhibitors (TKIs) for GBM treatment.

METHODS

A comprehensive literature review was conducted using PubMed up to August 2023. Boolean operators and MeSH term "glioma," along with specific VEGFR-related keywords, were utilized following thorough examination of existing literature.

RESULTS

VEGFR correlates with glioma grade and GBM progression, presenting a viable therapeutic target. Regorafenib and axitinib show promise among studied TKIs. Other multi-targeted TKIs (MTKI) and combination therapies exhibit potential, albeit limited by blood-brain barrier penetration and toxicity. Combining treatments like radiotherapy and enhancing BBB penetration may benefit patients. Further research is warranted in patient quality of life and biomarker-guided selection.

CONCLUSION

While certain therapies hold promise for GBM, future research should prioritize personalized medicine and innovative strategies for improved treatment outcomes.

Quantification of T2-FLAIR Mismatch in Nonenhancing Diffuse Gliomas Using Digital Subtraction

BACKGROUND AND PURPOSE

The T2-FLAIR mismatch sign on MR imaging is a highly specific imaging biomarker of isocitrate dehydrogenase (IDH)-mutant astrocytomas, which lack 1p/19q codeletion. However, most studies using the T2-FLAIR mismatch sign have used visual assessment. This study quantified the degree of T2-FLAIR mismatch using digital subtraction of fluid-nulled T2-weighted FLAIR images from non-fluid-nulled T2-weighted images in human nonenhancing diffuse gliomas and then used this information to assess improvements in diagnostic performance and investigate subregion characteristics within these lesions.

MATERIALS AND METHODS

Two cohorts of treatment-naïve, nonenhancing gliomas with known IDH and 1p/19q status were studied (n = 71 from The Cancer Imaging Archive (TCIA) and n = 34 in the institutional cohort). 3D volumes of interest corresponding to the tumor were segmented, and digital subtraction maps of T2-weighted MR imaging minus T2-weighted FLAIR MR imaging were used to partition each volume of interest into a T2-FLAIR mismatched subregion (T2-FLAIR mismatch, corresponding to voxels with positive values on the subtraction maps) and nonmismatched subregion (T2-FLAIR nonmismatch corresponding to voxels with negative values on the subtraction maps). Tumor subregion volumes, percentage of T2-FLAIR mismatch volume, and T2-FLAIR nonmismatch subregion thickness were calculated, and 2 radiologists assessed the T2-FLAIR mismatch sign with and without the aid of T2-FLAIR subtraction maps.

RESULTS

Thresholds of ≥42% T2-FLAIR mismatch volume classified IDH-mutant astrocytoma with a specificity/sensitivity of 100%/19.6% (TCIA) and 100%/31.6% (institutional); ≥25% T2-FLAIR mismatch volume showed 92.0%/32.6% and 100%/63.2% specificity/sensitivity, and ≥15% T2-FLAIR mismatch volume showed 88.0%/39.1% and 93.3%/79.0% specificity/sensitivity. In IDH-mutant astrocytomas with ≥15% T2-FLAIR mismatch volume, T2-FLAIR nonmismatch subregion thickness was negatively correlated with the percentage T2-FLAIR mismatch volume (P < .0001) across both cohorts. The percentage T2-FLAIR mismatch volume was higher in grades 3-4 compared with grade 2 IDH-mutant astrocytomas (P < .05), and ≥15% T2-FLAIR mismatch volume IDH-mutant astrocytomas were significantly larger than <15% T2-FLAIR mismatch volume IDH-mutant astrocytoma (P < .05) across both cohorts. When evaluated by 2 radiologists, the additional use of T2-FLAIR subtraction maps did not show a significant difference in interreader agreement, sensitivity, or specificity compared with a separate evaluation of T2-FLAIR and T2-weighted MR imaging alone.

CONCLUSIONS

T2-FLAIR digital subtraction maps may be a useful, automated tool to obtain objective segmentations of tumor subregions based on quantitative thresholds for classifying IDH-mutant astrocytomas using the percentage T2 FLAIR mismatch volume with 100% specificity and exploring T2-FLAIR mismatch/T2-FLAIR nonmismatch subregion characteristics. Conversely, the addition of T2-FLAIR subtraction maps did not enhance the sensitivity or specificity of the visual T2-FLAIR mismatch sign assessment by experienced radiologists.

The Prognostic Role of Volumetric MRI Evaluation in the Surgical Treatment of Glioblastoma

Background: Glioblastoma is the most common primary brain neoplasm in adults, with a poor prognosis despite a constant effort to improve patient survival. Some neuroradiological volumetric parameters seem to play a predictive role in overall survival (OS) and progression-free survival (PFS). The aim of this study was to analyze the impact of the volumetric areas of contrast-enhancing tumors and perineoplastic edema on the survival of patients treated for glioblastoma. Methods: A series of 87 patients who underwent surgery was retrospectively analyzed; OS and PFS were considered the end points of the study. For each patient, a multidisciplinary revision was conducted in collaboration with the Neuroradiology and Neuro-Oncology Board. Manual and semiautomatic measurements were adopted to perform the radiological evaluation, and the following quantitative parameters were retrospectively analyzed: contrast enhancement preoperative tumor volume (CE-PTV), contrast enhancement postoperative tumor volume (CE-RTV), edema/infiltration preoperative volume (T2/FLAIR-PV), edema/infiltration postoperative volume (T2/FLAIR-RV), necrosis volume inside the tumor (NV), and total tumor volume including necrosis (TV). Results: The median OS value was 9 months, and the median PFS value was 4 months; the mean values were 12.3 and 6.9 months, respectively. Multivariate analysis showed that the OS-related factors were adjuvant chemoradiotherapy (p < 0.0001), CE-PTV < 15 cm3 (p = 0.03), surgical resection > 95% (p = 0.004), and the presence of a "pseudocapsulated" radiological morphology (p = 0.04). Conclusions: Maximal safe resection is one of the most relevant predictive factors for patient survival. Semiautomatic preoperative MRI evaluation could play a key role in prognostically categorizing these tumors.

pH-Weighted amine chemical exchange saturation transfer echo planar imaging visualizes infiltrating glioblastoma cells

BACKGROUND

Given the invasive nature of glioblastoma, tumor cells exist beyond the contrast-enhancing (CE) region targeted during treatment. However, areas of non-enhancing (NE) tumors are difficult to visualize and delineate from edematous tissue. Amine chemical exchange saturation transfer echo planar imaging (CEST-EPI) is a pH-sensitive molecular magnetic resonance imaging technique that was evaluated in its ability to identify infiltrating NE tumors and prognosticate survival.

METHODS

In this prospective study, CEST-EPI was obtained in 30 patients and areas with elevated CEST contrast ("CEST+" based on the asymmetry in magnetization transfer ratio: MTRasym at 3 ppm) within NE regions were quantitated. Median MTRasym at 3 ppm and volume of CEST + NE regions were correlated with progression-free survival (PFS). In 20 samples from 14 patients, image-guided biopsies of these areas were obtained to correlate MTRasym at 3 ppm to tumor and non-tumor cell burden using immunohistochemistry.

RESULTS

In 15 newly diagnosed and 15 recurrent glioblastoma, higher median MTRasym at 3ppm within CEST + NE regions (P = .007; P = .0326) and higher volumes of CEST + NE tumor (P = .020; P < .001) were associated with decreased PFS. CE recurrence occurred in areas of preoperative CEST + NE regions in 95.4% of patients. MTRasym at 3 ppm was correlated with presence of tumor, cell density, %Ki-67 positivity, and %CD31 positivity (P = .001; P < .001; P < .001; P = .001).

CONCLUSIONS

pH-weighted amine CEST-EPI allows for visualization of NE tumor, likely through surrounding acidification of the tumor microenvironment. The magnitude and volume of CEST + NE tumor correlates with tumor cell density, degree of proliferating or "active" tumor, and PFS.

Fractal-Based Morphometrics of Glioblastoma

Morphometrics have been able to distinguish important features of glioblastoma from magnetic resonance imaging (MRI). Using morphometrics computed on segmentations of various imaging abnormalities, we show that the average and range of lacunarity and fractal dimension values across MRI slices can be prognostic for survival. We look at the repeatability of these metrics to multiple segmentations and how they are impacted by image resolution. We speak to the challenges to overcome before these metrics are included in clinical care, and the insight that they may provide.

Standardized brain tumor imaging protocols for clinical trials: current recommendations and tips for integration

Standardized MRI acquisition protocols are crucial for reducing the measurement and interpretation variability associated with response assessment in brain tumor clinical trials. The main challenge is that standardized protocols should ensure high image quality while maximizing the number of institutions meeting the acquisition requirements. In recent years, extensive effort has been made by consensus groups to propose different "ideal" and "minimum requirements" brain tumor imaging protocols (BTIPs) for gliomas, brain metastases (BM), and primary central nervous system lymphomas (PCSNL). In clinical practice, BTIPs for clinical trials can be easily integrated with additional MRI sequences that may be desired for clinical patient management at individual sites. In this review, we summarize the general concepts behind the choice and timing of sequences included in the current recommended BTIPs, we provide a comparative overview, and discuss tips and caveats to integrate additional clinical or research sequences while preserving the recommended BTIPs. Finally, we also reflect on potential future directions for brain tumor imaging in clinical trials.

Interpreting deep learning models for glioma survival classification using visualization and textual explanations

BACKGROUND

Saliency-based algorithms are able to explain the relationship between input image pixels and deep-learning model predictions. However, it may be difficult to assess the clinical value of the most important image features and the model predictions derived from the raw saliency map. This study proposes to enhance the interpretability of saliency-based deep learning model for survival classification of patients with gliomas, by extracting domain knowledge-based information from the raw saliency maps.

MATERIALS AND METHODS

Our study includes presurgical T1-weighted (pre- and post-contrast), T2-weighted and T2-FLAIR MRIs of 147 glioma patients from the BraTs 2020 challenge dataset aligned to the SRI 24 anatomical atlas. Each image exam includes a segmentation mask and the information of overall survival (OS) from time of diagnosis (in days). This dataset was divided into training ([Formula: see text]) and validation ([Formula: see text]) datasets. The extent of surgical resection for all patients was gross total resection. We categorized the data into 42 short (mean [Formula: see text] days), 30 medium ([Formula: see text] days), and 46 long ([Formula: see text] days) survivors. A 3D convolutional neural network (CNN) trained on brain tumour MRI volumes classified all patients based on expected prognosis of either short-term, medium-term, or long-term survival. We extend the popular 2D Gradient-weighted Class Activation Mapping (Grad-CAM), for the generation of saliency map, to 3D and combined it with the anatomical atlas, to extract brain regions, brain volume and probability map that reveal domain knowledge-based information.

RESULTS

For each OS class, a larger tumor volume was associated with a shorter OS. There were 10, 7 and 27 tumor locations in brain regions that uniquely associate with the short-term, medium-term, and long-term survival, respectively. Tumors located in the transverse temporal gyrus, fusiform, and palladium are associated with short, medium and long-term survival, respectively. The visual and textual information displayed during OS prediction highlights tumor location and the contribution of different brain regions to the prediction of OS. This algorithm design feature assists the physician in analyzing and understanding different model prediction stages.

CONCLUSIONS

Domain knowledge-based information extracted from the saliency map can enhance the interpretability of deep learning models. Our findings show that tumors overlapping eloquent brain regions are associated with short patient survival.

Magnetic resonance imaging-derived parameters to predict response to regorafenib in recurrent glioblastoma

PURPOSE

Regorafenib is a multikinase inhibitor, approved as a preferred regimen for recurrent glioblastoma (rGB). Although its effects on prolonging survival could seem modest, it is still unclear whether a subset of patients, potentially identifiable by imaging biomarkers, might experience a more substantial positive effect. Our aim was to evaluate the potential value of magnetic resonance imaging-derived parameters as non-invasive biomarkers to predict response to regorafenib in patients with rGB.

METHODS

20 patients with rGB underwent conventional and advanced MRI at diagnosis (before surgery), at recurrence and at first follow-up (3 months) during regorafenib. Maximum relative cerebral blood volume (rCBVmax) value, intra-tumoral susceptibility signals (ITSS), apparent diffusion coefficient (ADC) values, and contrast-enhancing tumor volumes were tested for correlation with response to treatment, progression-free survival (PFS), and overall survival (OS). Response at first follow-up was assessed according to Response Assessment in Neuro-Oncology (RANO) criteria.

RESULTS

8/20 patients showed stable disease at first follow-up. rCBVmax values of the primary glioblastoma (before surgery) significantly correlated to treatment response; specifically, patients with stable disease displayed higher rCBVmax compared to progressive disease (p = 0.04, 2-group t test). Moreover, patients with stable disease showed longer PFS (p = 0.02, 2-group t test) and OS (p = 0.04, 2-group t test). ITSS, ADC values, and contrast-enhancing tumor volumes showed no correlation with treatment response, PFS nor OS.

CONCLUSION

Our results suggest that rCBVmax of the glioblastoma at diagnosis could serve as a non-invasive biomarker of treatment response to regorafenib in patients with rGB.

Objective response rate targets for recurrent glioblastoma clinical trials based on the historic association between objective response rate and median overall survival

Durable objective response rate (ORR) remains a meaningful endpoint in recurrent cancer; however, the target ORR for single-arm recurrent glioblastoma trials has not been based on historic information or tied to patient outcomes. The current study reviewed 68 treatment arms comprising 4793 patients in past trials in recurrent glioblastoma in order to judiciously define target ORRs for use in recurrent glioblastoma trials. ORR was estimated at 6.1% [95% CI 4.23; 8.76%] for cytotoxic chemothera + pies (ORR = 7.59% for lomustine, 7.57% for temozolomide, 0.64% for irinotecan, and 5.32% for other agents), 3.37% for biologic agents, 7.97% for (select) immunotherapies, and 26.8% for anti-angiogenic agents. ORRs were significantly correlated with median overall survival (mOS) across chemotherapy (R2= 0.4078, P < .0001), biologics (R2= 0.4003, P = .0003), and immunotherapy trials (R2= 0.8994, P < .0001), but not anti-angiogenic agents (R2= 0, P = .8937). Pooling data from chemotherapy, biologics, and immunotherapy trials, a meta-analysis indicated a strong correlation between ORR and mOS (R2= 0.3900, P < .0001; mOS [weeks] = 1.4xORR + 24.8). Assuming an ineffective cytotoxic (control) therapy has ORR = 7.6%, the average ORR for lomustine and temozolomide trials, a sample size of ≥40 patients with target ORR>25% is needed to demonstrate statistical significance compared to control with a high level of confidence (P < .01) and adequate power (>80%). Given this historic data and potential biases in patient selection, we recommend that well-controlled, single-arm phase II studies in recurrent glioblastoma should have a target ORR >25% (which translates to a median OS of approximately 15 months) and a sample size of ≥40 patients, in order to convincingly demonstrate antitumor activity. Crucially, this response needs to have sufficient durability, which was not addressed in the current study.

Multi-nuclear sodium, diffusion, and perfusion MRI in human gliomas

PURPOSE

There is limited knowledge about the associations between sodium and proton MRI measurements in brain tumors. The purpose of this study was to quantify intra- and intertumoral correlations between sodium, diffusion, and perfusion MRI in human gliomas.

METHODS

Twenty glioma patients were prospectively studied on a 3T MRI system with multinuclear capabilities. Three mutually exclusive tumor volumes of interest (VOIs) were segmented: contrast-enhancing tumor (CET), T2/FLAIR hyperintense non-enhancing tumor (NET), and necrosis. Median and voxel-wise associations between apparent diffusion coefficient (ADC), normalized relative cerebral blood volume (nrCBV), and normalized sodium measurements were quantified for each VOI.

RESULTS

Both relative sodium concentration and ADC were significantly higher in areas of necrosis compared to NET (P = 0.003 and P = 0.008, respectively) and CET (P = 0.02 and P = 0.02). Sodium concentration was higher in CET compared to NET (P = 0.04). Sodium and ADC were higher in treated compared to treatment-naïve gliomas within NET (P = 0.006 and P = 0.01, respectively), and ADC was elevated in CET (P = 0.03). Median ADC and sodium concentration were positively correlated across patients in NET (r = 0.77, P < 0.0001) and CET (r = 0.84, P < 0.0001), but not in areas of necrosis (r = 0.45, P = 0.12). Median nrCBV and sodium concentration were negatively correlated across patients in areas of NET (r=-0.63, P = 0.003). Similar associations were observed when examining voxel-wise correlations within VOIs.

CONCLUSION

Sodium MRI is positively correlated with proton diffusion MRI measurements in gliomas, likely reflecting extracellular water. Unique areas of multinuclear MRI contrast may be useful in future studies to understand the chemistry of the tumor microenvironment.

Prognostic and predictive impact of abnormal signal volume evolution early after chemoradiotherapy in glioblastoma

INTRODUCTION

This study was designed to explore the feasibility of semiautomatic measurement of abnormal signal volume (ASV) in glioblastoma (GBM) patients, and the predictive value of ASV evolution for the survival prognosis after chemoradiotherapy (CRT).

METHODS

This retrospective trial included 110 consecutive patients with GBM. MRI metrics, including the orthogonal diameter (OD) of the abnormal signal lesions, the pre-radiation enhancement volume (PRRCE), the volume change rate of enhancement (rCE), and fluid attenuated inversion recovery (rFLAIR) before and after CRT were analyzed. Semi-automatic measurements of ASV were done through the Slicer software.

RESULTS

In logistic regression analysis, age (HR = 2.185, p = 0.012), PRRCE (HR = 0.373, p < 0.001), post CE volume (HR = 4.261, p = 0.001), rCE_1m (HR = 0.519, p = 0.046) were the significant independent predictors of short overall survival (OS) (< 15.43 months). The areas under the receiver operating characteristic curve (AUCs) for predicting short OS with rFLAIR_3m and rCE_1m were 0.646 and 0.771, respectively. The AUCs of Model 1 (clinical), Model 2 (clinical + conventional MRI), Model 3 (volume parameters), Model 4 (volume parameters + conventional MRI), and Model 5 (clinical + conventional MRI + volume parameters) for predicting short OS were 0.690, 0.723, 0.877, 0.879, 0.898, respectively.

CONCLUSION

Semi-automatic measurement of ASV in GBM patients is feasible. The early evolution of ASV after CRT was beneficial in improving the survival evaluation after CRT. The efficacy of rCE_1m was better than that of rFLAIR_3m in this evaluation.

Effectiveness and safety of tumor-treating fields therapy for glioblastoma: A single-center study in a Chinese cohort

Objective

Tumor-treating fields (TTFields) are a new therapeutic modality for patients with glioblastoma (GBM). However, studies on survival outcomes of TTFields are rarely reported in China. This study aimed to examine the clinical efficacy and safety of TTFields therapy for GBM in China.

Methods

A total of 93 patients with newly diagnosed GBM (ndGBM) and recurrent GBM (rGBM) were included in our study retrospectively. They were divided into two groups based on whether they used TTFields. Progression-free survival (PFS), overall survival (OS), and toxicities were assessed.

Results

Among the patients with ndGBM, there were 13 cases with TTFields and 39 cases with no TTFields. The median PFS was 15.3 [95% confidence interval (CI): 6.5-24.1] months and 10.6 (95% CI: 5.4-15.8) months in the two groups, respectively, with P = 0.041. The median OS was 24.8 (95% CI: 6.8-42.8) months and 18.6 (95% CI: 11.4-25.8) months, respectively, with P = 0.368. Patients with subtotal resection (STR) who used TTFields had a better PFS than those who did not (P = 0.003). Among the patients with rGBM, there were 13 cases with TTFields and 28 cases with no TTFields. The median PFS in the two groups was 8.4 (95% CI: 1.7-15.2) months and 8.0 (95% CI: 5.8-10.2) months in the two groups, respectively, with P = 0.265. The median OS was 10.6 (95% CI: 4.8-16.4) months and 13.3 (95% CI: 11.0-15.6) months, respectively, with P = 0.655. A total of 21 patients (21/26, 80.8%) with TTFields developed dermatological adverse events (dAEs). All the dAEs could be resolved or controlled.

Conclusion

TTFields therapy is a safe and effective treatment for ndGBM, especially in patients with STR. However, it may not improve survival in patients with rGBM.

Change in volumetric tumor growth rate after cytotoxic therapy is predictive of overall survival in recurrent glioblastoma

Background

Alterations in tumor growth rate (TGR) in recurrent glioblastoma (rGBM) after treatment may be useful for identifying therapeutic activity. The aim of this study was to assess the impact of volumetric TGR alterations on overall survival (OS) in rGBM treated with chemotherapy with or without radiation therapy (RT).

Methods

Sixty-one rGBM patients treated with chemotherapy with or without concomitant radiation therapy (RT) at 1st or 2nd recurrence were retrospectively examined. Pre- and post-treatment contrast enhancing volumes were computed. Patients were considered "responders" if they reached progression-free survival at 6 months (PFS6) and showed a decrease in TGR after treatment and "non-responders" if they didn't reach PFS6 or if TGR increased.

Results

Stratification by PFS6 and based on TGR resulted in significant differences in OS both for all patients and for patients without RT (P < 0.05). A decrease of TGR (P = 0.009), smaller baseline tumor volume (P = 0.02), O6-methylguanine-DNA methyltransferase promoter methylation (P = 0.048) and fewer number of recurrences (P = 0.048) were significantly associated with longer OS after controlling for age, sex and concomitant RT.

Conclusion

A decrease in TGR in patients with PFS6, along with smaller baseline tumor volume, were associated with a significantly longer OS in rGBM treated with chemotherapy with or without radiation. Importantly, all patients that exhibited PFS6 also showed a measurable decrease in TGR.

Radiographic Response Assessment Strategies for Early-Phase Brain Trials in Complex Tumor Types and Drug Combinations: from Digital "Flipbooks" to Control Systems Theory

There is an urgent need for drug development in brain tumors. While current radiographic response assessment provides instructions for identifying large treatment effects in simple high- and low-grade gliomas, there remains a void of strategies to evaluate complex or difficult to measure tumors or tumors of mixed grade with enhancing and non-enhancing components. Furthermore, most patients exhibit some period of alteration in tumor growth after starting a new therapy, but simple response categorization (e.g., stable disease, progressive disease) fails to provide any meaningful insight into the depth or degree of potential "subclinical" therapeutic response. We propose a creative solution to these issues based on a tiered strategy meant to increase confidence in identifying therapeutic effects even in the most challenging tumor types, while also providing a framework for complex evaluation of combination and sequential treatment schemes. Specifically, we demonstrate the utility of digital "flipbooks" to quickly identify subtle changes in complex tumors. We show how a modified Levin criteria can be used to quantify the degree of visual changes, while establishing estimates of the association between tumor volume and visual inspection. Lastly, we introduce the concept of quantifying therapeutic response using control systems theory. We propose measuring changes in volume (proportional), the area under the volume vs. time curve (integral) and changes in growth rates (derivative) to utilize a "PID" controller model of single or combination therapeutic activity.

Unveiling the Mechanism of the Traditional Korean Medicinal Formula FDY003 on Glioblastoma Through a Computational Network Pharmacology Approach

Glioblastoma (GBM) is the most common type of primary malignant tumor that develops in the brain, with 0.21 million new cases per year globally and a median survival period of less than 2 years after diagnosis. Traditional Korean medicines have been increasingly suggested as effective and safe therapeutic strategies for GBM. However, their pharmacological effects and mechanistic characteristics remain to be studied. In this study, we employed a computational network pharmacological approach to determine the effects and mechanisms of the traditional Korean medicinal formula FDY003 on GBM. We found that FDY003 treatment decreased the viability of human GBM cells and increased their response to chemotherapeutics. We identified 10 potential active pharmacological compounds of FDY003 and 67 potential GBM-related target genes and proteins. The GBM-related targets of FDY003 were signaling components of various crucial GBM-associated pathways, such as PI3K-Akt, focal adhesion, MAPK, HIF-1, FoxO, Ras, and TNF. These pathways are functional regulators for the determination of cell growth and proliferation, survival and death, and cell division cycle of GBM cells. Together, the overall analyses contribute to the pharmacological basis for the anti-GBM roles of FDY003 and its systematic mechanisms.

Hypothetical generalized framework for a new imaging endpoint of therapeutic activity in early phase clinical trials in brain tumors

Imaging response assessment is a cornerstone of patient care and drug development in oncology. Clinicians/clinical researchers rely on tumor imaging to estimate the impact of new treatments and guide decision making for patients and candidate therapies. This is important in brain cancer, where associations between tumor size/growth and emerging neurological deficits are strong. Accurately measuring the impact of a new therapy on tumor growth early in clinical development, where patient numbers are small, would be valuable for decision making regarding late-stage development activation. Current attempts to measure the impact of a new therapy have limited influence on clinical development, as determination of progression, stability or response does not currently account for individual tumor growth kinetics prior to the initiation of experimental therapies. Therefore, we posit that imaging-based response assessment, often used as a tool for estimating clinical effect, is incomplete as it does not adequately account for growth trajectories or biological characteristics of tumors prior to the introduction of an investigational agent. Here, we propose modifications to the existing framework for evaluating imaging assessment in primary brain tumors that will provide a more reliable understanding of treatment effects. Measuring tumor growth trajectories prior to a given intervention may allow us to more confidently conclude whether there is an anti-tumor effect. This updated approach to imaging-based tumor response assessment is intended to improve our ability to select candidate therapies for later-stage development, including those that may not meet currently sought thresholds for "response" and ultimately lead to identification of effective treatments.

Cabozantinib for the treatment of solid tumors: a systematic review

Background:

Cabozantinib is approved, in various settings, for the treatment of renal cell carcinoma, medullary thyroid cancer, and hepatocellular carcinoma, and it has been investigated for the treatment of other cancers. With the available evidence and the real-world performance of cabozantinib compared with clinical trial data, we performed a systematic review of cabozantinib monotherapy as treatment for solid tumors in adults.

Methods:

This study was designed in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses and registered with PROSPERO (CRD42020144680). We searched for clinical and observational studies of cabozantinib monotherapy for solid tumors using Embase, MEDLINE, and Cochrane databases (October 2020), and screened relevant congress abstracts. Eligible studies reported clinical or safety outcomes, or biomarker data. Small studies (n < 25) and studies of cabozantinib combination therapies were excluded. Quality was assessed using National Institute for Health and Care Excellence methodology, and study characteristics were described qualitatively.

Results:

Of 2888 citations, 114 were included (52 randomized studies, 29 observational studies, 32 nonrandomized phase I or II studies or pilot trials, and 1 analysis of data from a randomized study and a nonrandomized study). Beyond approved indications, other tumors studied were castration-resistant prostate cancer, urothelial carcinoma, Ewing sarcoma, osteosarcoma, uveal melanoma, non-small-cell lung cancer, Merkel cell carcinoma, glioblastoma, pheochromocytomas and paragangliomas, cholangiocarcinoma, gastrointestinal stromal tumor, colorectal cancer, salivary gland cancer, carcinoid and pancreatic neuroendocrine tumors, and breast, endometrial and ovarian cancers. The most common adverse events were hypertension, diarrhea, and fatigue.

Conclusion:

The identified evidence demonstrates the positive efficacy/effectiveness of cabozantinib monotherapy in various solid tumor types, with safety findings being consistent with those observed with other VEGFR-targeting tyrosine kinase inhibitors. When available, real-world findings were consistent with the data reported from clinical trials. A limitation of this review is the high proportion of abstracts; however, this allowed us to capture the most up-to-date findings.

Deep Learning-Based 3D MRI Contrast-Enhanced Synthesis From A 2D Non-contrast T2Flair Sequence Deep Learning, MR images Synthesis

PURPOSE

Gadolinium-based contrast agents (GBCAs) have been successfully applied in magnetic resonance (MR) imaging to facilitate better lesion visualization. However, gadolinium deposition in the human brain raised widespread concerns recently. On the other hand, although high-resolution three-dimensional (3D) MR images are more desired for most existing medical image processing algorithms, their long scan duration and high acquiring costs make 2D MR images still much more common clinically. Therefore, developing alternative solutions for 3D contrast-enhanced MR images synthesis to replace GBCAs injection becomes an urgent requirement.

METHODS

This study proposed a deep learning framework that produces 3D isotropic full-contrast T2Flair images from 2D anisotropic non-contrast T2Flair image stacks. The super-resolution (SR) and contrast-enhanced (CE) synthesis tasks are completed in sequence by using an identical generative adversarial network (GAN) with the same techniques. To solve the problem that intra-modality datasets from different scanners have specific combinations of orientations, contrasts and resolutions, we conducted a region-based data augmentation technique on the fly during training to simulate various imaging protocols in the clinic. We further improved our network by introducing atrous spatial pyramid pooling, enhanced residual blocks and deep supervision for better quantitative and qualitative results.

RESULTS

Our proposed method achieved superior CE synthesized performance in quantitative metrics and perceptual evaluation. Detailedly, the PSNR, SSIM and AUC are 32.25 dB, 0.932 and 0.991 in the whole brain and 24.93 dB, 0.851 and 0.929 in tumor regions. The radiologists' evaluations confirmed that our proposed method has high confidence in the diagnosis. Analysis of the generalization ability showed that benefiting from the proposed data augmentation technique, our network can be applied to 'unseen' datasets with slight drops in quantitative and qualitative results.

CONCLUSION

Our work demonstrates the clinical potential of synthesizing diagnostic 3D isotropic CE brain MR images from a single 2D anisotropic non-contrast sequence. This article is protected by copyright. All rights reserved.

High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 1: Perfusion and Diffusion Techniques

Objective

Summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and highlight the latest bench-to-bedside developments.

Methods

Experts in advanced MRI techniques applied to high-grade glioma treatment response assessment convened through a European framework. Current evidence regarding the potential for monitoring biomarkers in adult high-grade glioma is reviewed, and individual modalities of perfusion, permeability, and microstructure imaging are discussed (in Part 1 of two). In Part 2, we discuss modalities related to metabolism and/or chemical composition, appraise the clinic readiness of the individual modalities, and consider post-processing methodologies involving the combination of MRI approaches (multiparametric imaging) or machine learning (radiomics).

Results

High-grade glioma vasculature exhibits increased perfusion, blood volume, and permeability compared with normal brain tissue. Measures of cerebral blood volume derived from dynamic susceptibility contrast-enhanced MRI have consistently provided information about brain tumor growth and response to treatment; it is the most clinically validated advanced technique. Clinical studies have proven the potential of dynamic contrast-enhanced MRI for distinguishing post-treatment related effects from recurrence, but the optimal acquisition protocol, mode of analysis, parameter of highest diagnostic value, and optimal cut-off points remain to be established. Arterial spin labeling techniques do not require the injection of a contrast agent, and repeated measurements of cerebral blood flow can be performed. The absence of potential gadolinium deposition effects allows widespread use in pediatric patients and those with impaired renal function. More data are necessary to establish clinical validity as monitoring biomarkers. Diffusion-weighted imaging, apparent diffusion coefficient analysis, diffusion tensor or kurtosis imaging, intravoxel incoherent motion, and other microstructural modeling approaches also allow treatment response assessment; more robust data are required to validate these alone or when applied to post-processing methodologies.

Conclusion

Considerable progress has been made in the development of these monitoring biomarkers. Many techniques are in their infancy, whereas others have generated a larger body of evidence for clinical application.

Imaging Biomarkers of Glioblastoma Treatment Response: A Systematic Review and Meta-Analysis of Recent Machine Learning Studies

OBJECTIVE

Monitoring biomarkers using machine learning (ML) may determine glioblastoma treatment response. We systematically reviewed quality and performance accuracy of recently published studies.

METHODS

Following Preferred Reporting Items for Systematic Reviews and Meta-Analysis: Diagnostic Test Accuracy, we extracted articles from MEDLINE, EMBASE and Cochrane Register between 09/2018-01/2021. Included study participants were adults with glioblastoma having undergone standard treatment (maximal resection, radiotherapy with concomitant and adjuvant temozolomide), and follow-up imaging to determine treatment response status (specifically, distinguishing progression/recurrence from progression/recurrence mimics, the target condition). Using Quality Assessment of Diagnostic Accuracy Studies Two/Checklist for Artificial Intelligence in Medical Imaging, we assessed bias risk and applicability concerns. We determined test set performance accuracy (sensitivity, specificity, precision, F1-score, balanced accuracy). We used a bivariate random-effect model to determine pooled sensitivity, specificity, area-under the receiver operator characteristic curve (ROC-AUC). Pooled measures of balanced accuracy, positive/negative likelihood ratios (PLR/NLR) and diagnostic odds ratio (DOR) were calculated. PROSPERO registered (CRD42021261965).

RESULTS

Eighteen studies were included (1335/384 patients for training/testing respectively). Small patient numbers, high bias risk, applicability concerns (particularly confounding in reference standard and patient selection) and low level of evidence, allow limited conclusions from studies. Ten studies (10/18, 56%) included in meta-analysis gave 0.769 (0.649-0.858) sensitivity [pooled (95% CI)]; 0.648 (0.749-0.532) specificity; 0.706 (0.623-0.779) balanced accuracy; 2.220 (1.560-3.140) PLR; 0.366 (0.213-0.572) NLR; 6.670 (2.800-13.500) DOR; 0.765 ROC-AUC.

CONCLUSION

ML models using MRI features to distinguish between progression and mimics appear to demonstrate good diagnostic performance. However, study quality and design require improvement.

Multiple Survival Outcome Prediction of Glioblastoma Patients Based on Multiparametric MRI

PURPOSE

Construction of radiomics models for the individualized estimation of multiple survival stratification in glioblastoma (GBM) patients using the multiregional information extracted from multiparametric MRI that could facilitate clinical decision-making for GBM patients.

MATERIALS AND METHODS

A total of 134 eligible GBM patients were selected from The Cancer Genome Atlas. These patients were separated into the long-term and short-term survival groups according to the median of individual survival indicators: overall survival (OS), progression-free survival (PFS), and disease-specific survival (DSS). Then, the patients were divided into a training set and a validation set in a ratio of 2:1. Radiomics features (n = 5,152) were extracted from multiple regions of the GBM using multiparametric MRI. Then, radiomics signatures that are related to the three survival indicators were respectively constructed using the analysis of variance (ANOVA) and the least absolute shrinkage and selection operator (LASSO) regression for each patient in the training set. Based on a Cox proportional hazards model, the radiomics model was further constructed by combining the signature and clinical risk factors.

RESULTS

The constructed radiomics model showed a promising discrimination ability to differentiate in the training set and validation set of GBM patients with survival indicators of OS, PFS, and DSS. Both the four MRI modalities and five tumor subregions have different effects on the three survival indicators of GBM. The favorable calibration and decision curve analysis indicated the clinical decision value of the radiomics model. The performance of models of the three survival indicators was different but excellent; the best model achieved C indexes of 0.725, 0.677, and 0.724, respectively, in the validation set.

CONCLUSION

Our results show that the proposed radiomics models have favorable predictive accuracy on three survival indicators and can provide individualized probabilities of survival stratification for GBM patients by using multiparametric and multiregional MRI features.

Systemic coagulation is activated in patients with meningioma and glioblastoma

PURPOSE

Up to 30% of patients with glioblastoma (GBM) develop venous thromboembolism (VTE) over the course of the disease. Although not as high, the risk for VTE is also increased in patients with meningioma. Direct measurement of peak thrombin generation (TG) allows quantitative assessment of systemic coagulation activation in patients with GBM and meningioma. Our aim was to determine the extent of systemic coagulation activation induced by brain tumors, to measure the shift between pre- and post-operative peak TG in patients with GBM, and to assess the relationship between pre-surgical peak TG and pre-operative brain tumor volume on imaging.

METHODS

Pre- and post-surgical plasma samples were obtained from successive patients with GBM and once from patients with meningioma and healthy age- and sex-matched blood donor controls. TG was measured using the calibrated automated thrombogram (CAT) assay, and tumor volumes were measured in pre-surgical MRI scans.

RESULTS

Pre-surgical peak TG was higher in patients with GBM than in controls (288.6 ± 54.1 nM vs 187.1 ± 41.7 nM, respectively, P < 0.001), and, in the nine patients with GBM and paired data available, peak TG was significantly reduced after surgery (323 ± 38 nM vs 265 ± 52 nM, respectively, P = 0.007). Similarly, subjects with meningioma demonstrated higher peak TG compared to controls (242.2 ± 54.9 nM vs 177.7 ± 57.0 nM, respectively, P < 0.001). There was no association between peak TG and pre-operative tumor volume or overall survival.

CONCLUSION

Our results indicate that systemic coagulation activation occurs with both meningioma and GBM, but to a greater degree in the latter. Preoperative peak TG did not correlate with tumor volume, but removal of GBM caused a significant decrease in coagulation activation.

Therapeutic Response Assessment of High-Grade Gliomas During Early-Phase Drug Development in the Era of Molecular and Immunotherapies

ABSTRACT

Several new therapeutic strategies have emerged over the past decades to address unmet clinical needs in high-grade gliomas, including targeted molecular agents and various forms of immunotherapy. Each of these strategies requires addressing fundamental questions, depending on the stage of drug development, including ensuring drug penetration into the brain, engagement of the drug with the desired target, biologic effects downstream from the target including metabolic and/or physiologic changes, and identifying evidence of clinical activity that could be expanded upon to increase the likelihood of a meaningful survival benefit. The current review article highlights these strategies and outlines how imaging technology can be used for therapeutic response evaluation in both targeted and immunotherapies in early phases of drug development in high-grade gliomas.

[Epidemiological, clinical, therapeutic and evolutionary features of patients with glioblastoma: series of cases managed in the Department of Hematology-Oncology at the Mohammed VI University Hospital Center in Marrakech in 2016 and 2017]

Glioblastoma is the most common primary malignant brain tumour. Despite advances in diagnostic and therapeutic treatments, it is still associated with poor outcome The purpose of this study of cases is to describe the epidemiological, clinical, therapeutic and evolutionary features of patients with glioblastoma admitted to the Department of Hematology-Oncology (DHO) in Marrakech in 2016 and 2017. We conducted a literature review of epidemiological, clinical, radiological, anatomopathological, therapeutic and evolutionary data from 40 patients. Glioblastoma accounted for 47.6% of treated intracranial tumours. The average age of patients was 52.4±12.3 years. Functional impotence and signs of intracranial hypertension were the main symptoms. Tumours mainly occurred in the parietal region (44%) and were large (57.5%). Aphasia was related to tumour size (p=0.042). Nine cases had glioblastomas-IDH1-wild and one case had glioblastoma-IDH1-mutant. On admission, patients had poor performance-status. This was due to a prolonged time between surgery and DHO admission (p= 0.034). Patients with sensory impairments were older (62.5±3 years) than those without sensory impairments (51.2±12 years) (p=0,045). In-patient women received chemoradiotherapy (1.5±1 month) earlier than men (2.3±1.2 months) (p=0.03). Survival was 13.6±5.3 months; it was unrelated to the time to surgery (p=0.076), the time to DHO (p=0.058), and the time to chemoradiotherapy (p=0.073). The epidemiological, clinical, radiological and evolutionary features of our sample were comparable to literature data. The molecular profiling was not systematically realized. Despite prolonged treatment times, no link to survival was detected.

Surgical outcome and molecular pattern characterization of recurrent glioblastoma multiforme: A single-center retrospective series

OBJECTIVE

Despite recent advances in diagnosis and treatment of the disease, the prognosis of patients with glioblastoma multiforme (GBM) remains poor. While the value of molecular pattern profiles at first diagnosis has been demonstrated, only few studies have examined these biomarkers at the time of recurrence. The aim of this study was to explore the impact of extent of resection at repeated craniotomy on overall survival (OS) of patients with recurrent GBM. In addition, we investigated the molecular pattern profiles at first and second surgery to evaluate possible temporal evolution of these patterns and to assess the effect of these modifications on OS.

METHODS

We conducted a retrospective cohort study of 63 patients (mean age 59.2 years) surgically treated at least two times for recurrent GBM between 2006 and 2020.

RESULTS

Median OS and progression-free survival (PFS) were 22 months (range 2-168 months) and 10 months (range 1-96 months), respectively. The OS following gross-total resection (GTR) at recurrence for patients with initial GTR (GTR/GTR) was significantly increased (42.6 months) compared with sub-total resection (STR) at reoperation after initial GTR (GTR/STR) (19 months) and with GTR at reoperation after initial STR (STR/GTR) (17 months) (p = 0.0004). Overall surgical morbidity resulted 12.7% and 11.1% at first and at second surgery, respectively. Changes in genetic profiles between first and second surgery of 1p/19q co-deletion, MGMT promoter methylation and p53 mutations occurred in 5.6%, 1.9% and 9.3% of cases, respectively. MGMT promoter methylation appeared to affect OS in univariate analysis at first (p = 0.038) and second surgery (p = 0.107), whereas p53 mutation appeared to affect OS only at second surgery (p = 0.01). In a multivariate analysis female sex (HR = 0.322, 95% CI 0.147-0.705; p = 0.005), PFS (HR = 0.959, 95% CI 0.934-0.986; p = 0.003), GTR at first and second surgery (HR = 0.195, 95% CI 0.091-0.419; p < 0.0001) and adjuvant chemotherapy at recurrence (HR = 0.407, 95% CI 0.206-0.809; p = 0.01) were associated with longer OS.

CONCLUSIONS

This study confirmed the role of extent of resection (EOR) at first and at recurrence as a significant predictor of outcome in patients with recurrent GBM. In addition, this study highlighted the concept of a dynamic evolution of GBM genome after initial surgical resection, supporting the need of further studies to investigate the clinical and therapeutic implications of the changes in genetic profiles after initial surgery.

A generic deep learning model for reduced gadolinium dose in contrast-enhanced brain MRI

PURPOSE

With rising safety concerns over the use of gadolinium-based contrast agents (GBCAs) in contrast-enhanced MRI, there is a need for dose reduction while maintaining diagnostic capability. This work proposes comprehensive technical solutions for a deep learning (DL) model that predicts contrast-enhanced images of the brain with approximately 10% of the standard dose, across different sites and scanners.

METHODS

The proposed DL model consists of a set of methods that improve the model robustness and generalizability. The steps include multi-planar reconstruction, 2.5D model, enhancement-weighted L1, perceptual, and adversarial losses. The proposed model predicts contrast-enhanced images from corresponding pre-contrast and low-dose images. With IRB approval and informed consent, 640 heterogeneous patient scans (56 train, 13 validation, and 571 test) from 3 institutions consisting of 3D T1-weighted brain images were used. Quantitative metrics were computed and 50 randomly sampled test cases were evaluated by 2 board-certified radiologists. Quantitative tumor segmentation was performed on cases with abnormal enhancements. Ablation study was performed for systematic evaluation of proposed technical solutions.

RESULTS

The average peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) between full-dose and model prediction were 35.07 ± 3.84 dB and 0.92 ± 0.02 , respectively. Radiologists found the same enhancing pattern in 45/50 (90%) cases; discrepancies were minor differences in contrast intensity and artifacts, with no effect on diagnosis. The average segmentation Dice score between full-dose and synthesized images was 0.88 ± 0.06 (median = 0.91).

CONCLUSIONS

We have proposed a DL model with technical solutions for low-dose contrast-enhanced brain MRI with potential generalizability under diverse clinical settings.

A randomized controlled phase III study of VB-111 combined with bevacizumab vs bevacizumab monotherapy in patients with recurrent glioblastoma (GLOBE)

Background

Ofranergene obadenovec (VB-111) is an anticancer viral therapy that demonstrated in a phase II study a survival benefit for patients with recurrent glioblastoma (rGBM) who were primed with VB-111 monotherapy that was continued after progression with concomitant bevacizumab.

Methods

This pivotal phase III randomized, controlled trial compared the efficacy and safety of upfront combination of VB-111 and bevacizumab versus bevacizumab monotherapy. Patients were randomized 1:1 to receive VB-111 10¹³ viral particles every 8 weeks in combination with bevacizumab 10 mg/kg every 2 weeks (combination arm) or bevacizumab monotherapy (control arm). The primary endpoint was overall survival (OS), and secondary endpoints were objective response rate (ORR) by Response Assessment in Neuro-Oncology (RANO) criteria and progression-free survival (PFS).

Results

Enrolled were 256 patients at 57 sites. Median exposure to VB-111 was 4 months. The study did not meet its primary or secondary goals. Median OS was 6.8 versus 7.9 months in the combination versus control arm (hazard ratio, 1.20; 95% CI: 0.91–1.59; P = 0.19) and ORR was 27.3% versus 21.9% (P = 0.26). A higher rate of grades 3–5 adverse events was reported in the combination arm (67% vs 40%), mainly attributed to a higher rate of CNS and flu-like/fever events. Trends for improved survival with combination treatment were seen in the subgroup of patients with smaller tumors and in patients who had a posttreatment febrile reaction.

Conclusions

In this study, upfront concomitant administration of VB-111 and bevacizumab failed to improve outcomes in rGBM. Change of treatment regimen, with the lack of VB-111 monotherapy priming, may explain the differences from the favorable phase II results.

Clinical trials registration

NCT02511405

Bintrafusp alfa (M7824), a bifunctional fusion protein targeting TGF-β and PD-L1: results from a phase I expansion cohort in patients with recurrent glioblastoma

Background

For patients with recurrent glioblastoma (rGBM), there are few options following treatment failure with radiotherapy plus temozolomide. Bintrafusp alfa is a first-in-class bifunctional fusion protein composed of the extracellular domain of the TGF-βRII receptor (a TGF-β “trap”) fused to a human IgG1 antibody blocking PD-L1.

Methods

In this phase I, open-label expansion cohort (NCT02517398), patients with rGBM that progressed after radiotherapy plus temozolomide received bintrafusp alfa 1200 mg Q2W until disease progression, unacceptable toxicity, or trial withdrawal. Response was assessed per RANO criteria. The primary endpoint was disease control rate (DCR); secondary endpoints included safety.

Results

As of August 24, 2018, 35 patients received bintrafusp alfa for a median of 1.8 (range, 0.5–20.7) months. Eight patients (22.9%) experienced disease control as assessed by an independent review committee: 2 had a partial response, 4 had stable disease, and 2 had non-complete response/non-progressive disease. Median progression-free survival (PFS) was 1.4 (95% confidence interval [CI], 1.2–1.6) months; 6- and 12-month PFS rates were 15.1% and 11.3%, respectively. Median overall survival (OS) was 5.3 (95% CI, 2.6–9.4) months; 6- and 12-month OS rates were 44.5% and 30.8%, respectively. The DCR (95% CI) was 66.7% (22.3–95.7%) for patients with IDH-mutant GBM (n = 6) and 13.8% (3.9–31.7%) for patients with IDH–wild-type GBM (n = 29). Disease control was seen regardless of PD-L1 expression. Twenty-five patients (71.4%) experienced treatment-related adverse events (grade ≥3; 17.1% [n = 6]).

Conclusions

The percentage of patients achieving disease control and the manageable safety profile may warrant further investigation of bintrafusp alfa in GBM.

Drug delivery and targeting to brain tumors: considerations for crossing the blood-brain barrier

Introduction: The blood-brain barrier (BBB) selectively impedes the transportation of drug molecules into the brain, which makes the drug delivery and targeting of brain tumors very challenging.Areas covered: Having surveyed the recent literature, comprehensive insights are given into the impacts of the BBB on the advanced drug delivery and targeting modalities for brain tumors.Expert opinion: Brain capillary endothelial cells form the BBB in association with astrocytes, pericytes, neurons, and extracellular matrix. Coop of these forms the complex setting of neurovascular unite. The BBB maintains the brain homeostasis by restrictive controlling of the blood circulating nutrients/substances trafficking. Despite substantial progress on therapy of brain tumors, there is no impeccable strategy to safely deliver chemotherapeutics into the brain. Various strategies have been applied to deliver chemotherapeutics into the brain (e.g. BBB opening, direct delivery by infusion, injection, microdialysis, and implants, and smart nanosystems), which hold different pros and cons. Of note, smart nanoscale multifunctional nanomedicines can serve as targeting, imaging, and treatment modality for brain tumors. Given that aggressive brain tumors (e.g. gliomas) are often unresponsive to any treatments, an in-depth understanding of the molecular/cellular complexity of brain tumors might help the development of smart and effective treatment modalities.

Diffusion Magnetic Resonance Imaging Phenotypes Predict Overall Survival Benefit From Bevacizumab or Surgery in Recurrent Glioblastoma With Large Tumor Burden

BACKGROUND

Diffusion magnetic resonance (MR) characteristics are a predictive imaging biomarker for survival benefit in recurrent glioblastoma treated with anti-vascular endothelial growth factor (VEGF) therapy; however, its use in large volume recurrence has not been evaluated.

OBJECTIVE

To determine if diffusion MR characteristics can predict survival outcomes in patients with large volume recurrent glioblastoma treated with bevacizumab or repeat resection.

METHODS

A total of 32 patients with large volume (>20 cc or > 3.4 cm diameter) recurrent glioblastoma treated with bevacizumab and 35 patients treated with repeat surgery were included. Pretreatment tumor volume and apparent diffusion coefficient (ADC) histogram analysis were used to phenotype patients as having high (>1.24 μm2/ms) or low (<1.24 μm2/ms) ADCL, the mean value of the lower peak in a double Gaussian model of the ADC histogram within the contrast enhancing tumor.

RESULTS

In bevacizumab and surgical cohorts, volume was correlated with overall survival (Bevacizumab: P = .009, HR = 1.02; Surgical: P = .006, HR = 0.96). ADCL was an independent predictor of survival in the bevacizumab cohort (P = .049, HR = 0.44), but not the surgical cohort (P = .273, HR = 0.67). There was a survival advantage of surgery over bevacizumab in patients with low ADCL (P = .036, HR = 0.43) but not in patients with high ADCL (P = .284, HR = 0.69).

CONCLUSION

Pretreatment diffusion MR imaging is an independent predictive biomarker for overall survival in recurrent glioblastoma with a large tumor burden. Large tumors with low ADCL have a survival benefit when treated with surgical resection, whereas large tumors with high ADCL may be best managed with bevacizumab.

A mesoscopic simulator to uncover heterogeneity and evolutionary dynamics in tumors

Increasingly complex in silico modeling approaches offer a way to simultaneously access cancerous processes at different spatio-temporal scales. High-level models, such as those based on partial differential equations, are computationally affordable and allow large tumor sizes and long temporal windows to be studied, but miss the discrete nature of many key underlying cellular processes. Individual-based approaches provide a much more detailed description of tumors, but have difficulties when trying to handle full-sized real cancers. Thus, there exists a trade-off between the integration of macroscopic and microscopic information, now widely available, and the ability to attain clinical tumor sizes. In this paper we put forward a stochastic mesoscopic simulation framework that incorporates key cellular processes during tumor progression while keeping computational costs to a minimum. Our framework captures a physical scale that allows both the incorporation of microscopic information, tracking the spatio-temporal emergence of tumor heterogeneity and the underlying evolutionary dynamics, and the reconstruction of clinically sized tumors from high-resolution medical imaging data, with the additional benefit of low computational cost. We illustrate the functionality of our modeling approach for the case of glioblastoma, a paradigm of tumor heterogeneity that remains extremely challenging in the clinical setting.

A Position Statement on the Utility of Interval Imaging in Standard of Care Brain Tumour Management: Defining the Evidence Gap and Opportunities for Future Research

Objectiv e

To summarise current evidence for the utility of interval imaging in monitoring disease in adult brain tumours, and to develop a position for future evidence gathering while incorporating the application of data science and health economics.

Methods

Experts in 'interval imaging' (imaging at pre-planned time-points to assess tumour status); data science; health economics, trial management of adult brain tumours, and patient representatives convened in London, UK. The current evidence on the use of interval imaging for monitoring brain tumours was reviewed. To improve the evidence that interval imaging has a role in disease management, we discussed specific themes of data science, health economics, statistical considerations, patient and carer perspectives, and multi-centre study design. Suggestions for future studies aimed at filling knowledge gaps were discussed.

Results

Meningioma and glioma were identified as priorities for interval imaging utility analysis. The "monitoring biomarkers" most commonly used in adult brain tumour patients were standard structural MRI features. Interval imaging was commonly scheduled to provide reported imaging prior to planned, regular clinic visits. There is limited evidence relating interval imaging in the absence of clinical deterioration to management change that alters morbidity, mortality, quality of life, or resource use. Progression-free survival is confounded as an outcome measure when using structural MRI in glioma. Uncertainty from imaging causes distress for some patients and their caregivers, while for others it provides an important indicator of disease activity. Any study design that changes imaging regimens should consider the potential for influencing current or planned therapeutic trials, ensure that opportunity costs are measured, and capture indirect benefits and added value.

Conclusion

Evidence for the value, and therefore utility, of regular interval imaging is currently lacking. Ongoing collaborative efforts will improve trial design and generate the evidence to optimise monitoring imaging biomarkers in standard of care brain tumour management.

Relative oxygen extraction fraction (rOEF) MR imaging reveals higher hypoxia in human epidermal growth factor receptor (EGFR) amplified compared with non-amplified gliomas

PURPOSE

Epidermal growth factor receptor (EGFR) amplification promotes gliomagenesis and is linked to lack of oxygen within the tumor microenvironment. Using hypoxia-sensitive spin-and-gradient echo echo-planar imaging and perfusion MRI, we investigated the influence of EGFR amplification on tissue oxygen availability and utilization in human gliomas.

METHODS

This study included 72 histologically confirmed EGFR-amplified and non-amplified glioma patients. Reversible transverse relaxation rate (R₂'), relative cerebral blood volume (rCBV), and relative oxygen extraction fraction (rOEF) were calculated for the contrast-enhancing and non-enhancing tumor regions. Using Student t test or Wilcoxon rank-sum test, median R₂', rCBV, and rOEF were compared between EGFR-amplified and non-amplified gliomas. ROC analysis was performed to assess the ability of imaging characteristics to discriminate EGFR amplification status. Overall survival (OS) was determined using univariate and multivariate cox models. Kaplan-Meier survival curves were plotted and compared using the log-rank test.

RESULTS

EGFR amplified gliomas exhibited significantly higher median R₂' and rOEF than non-amplified gliomas. ROC analysis suggested that R₂' (AUC = 0.7190; P = 0.0048) and rOEF (AUC = 0.6959; P = 0.0156) could separate EGFR status. Patients with EGFR-amplified gliomas had a significantly shorter OS than non-amplified patients. Univariate cox regression analysis determined both R₂' and rOEF significantly influence OS. No significant difference was observed in rCBV between patient cohorts nor was rCBV found to be an effective differentiator of EGFR status.

CONCLUSION

Imaging of tumor oxygen characteristics revealed EGFR-amplified gliomas to be more hypoxic and contribute to shorter patient survival than EGFR non-amplified gliomas.

Noninvasive Characterization of Tumor Angiogenesis and Oxygenation in Bevacizumab-treated Recurrent Glioblastoma by Using Dynamic Susceptibility MRI: Secondary Analysis of the European Organization for Research and Treatment of Cancer 26101 Trial

Background Relevance of antiangiogenic treatment with bevacizumab in patients with glioblastoma is controversial because progression-free survival benefit did not translate into an overall survival (OS) benefit in randomized phase III trials. Purpose To perform longitudinal characterization of intratumoral angiogenesis and oxygenation by using dynamic susceptibility contrast agent-enhanced (DSC) MRI and evaluate its potential for predicting outcome from administration of bevacizumab. Materials and Methods In this secondary analysis of the prospective randomized phase II/III European Organization for Research and Treatment of Cancer 26101 trial conducted between October 2011 and December 2015 in 596 patients with first recurrence of glioblastoma, the subset of patients with availability of anatomic MRI and DSC MRI at baseline and first follow-up was analyzed. Patients were allocated into those administered bevacizumab (hereafter, the BEV group; either bevacizumab monotherapy or bevacizumab with lomustine) and those not administered bevacizumab (hereafter, the non-BEV group with lomustine monotherapy). Contrast-enhanced tumor volume, noncontrast-enhanced T2 fluid-attenuated inversion recovery (FLAIR) signal abnormality volume, Gaussian-normalized relative cerebral blood volume (nrCBV), Gaussian-normalized relative blood flow (nrCBF), and tumor metabolic rate of oxygen (nTMRO₂) was quantified. The predictive ability of these imaging parameters was assessed with multivariable Cox regression and formal interaction testing. Results A total of 254 of 596 patients were evaluated (mean age, 57 years ± 11; 155 men; 161 in the BEV group and 93 in non-BEV group). Progression-free survival was longer in the BEV group (3.7 months; 95% confidence interval [CI]: 3.0, 4.2) compared with the non-BEV group (2.5 months; 95% CI: 1.5, 2.9; P = .01), whereas OS was not different (P = .15). The nrCBV decreased for the BEV group (-16.3%; interquartile range [IQR], -39.5% to 12.0%; P = .01), but not for the non-BEV group (1.2%; IQR, -17.9% to 23.3%; P = .19) between baseline and first follow-up. An identical pattern was observed for both nrCBF and nTMRO₂ values. Contrast-enhanced tumor and noncontrast-enhanced T2 FLAIR signal abnormality volumes decreased for the BEV group (-66% [IQR, -83% to -35%] and -33% [IQR, -71% to -5%], respectively; P < .001 for both), whereas they increased for the non-BEV group (30% [IQR, -17% to 98%], P = .001; and 10% [IQR, -13% to 82%], P = .02, respectively) between baseline and first follow-up. None of the assessed MRI parameters were predictive for OS in the BEV group. Conclusion Bevacizumab treatment decreased tumor volumes, angiogenesis, and oxygenation, thereby reflecting its effectiveness for extending progression-free survival; however, these parameters were not predictive of overall survival (OS), which highlighted the challenges of identifying patients that derive an OS benefit from bevacizumab. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Dillon in this issue.

Contrahemispheric Cortex Predicts Survival and Molecular Markers in Patients With Unilateral High-Grade Gliomas

Background: Malignant high-grade gliomas are characterized by infiltration and destruction of surrounding brain tissue. Alterations in the contrahemispheric brain structure and their roles that may offer prognostically valuable information have not been investigated in high-grade gliomas. Methods: In total, 153 patients with unilateral glioma (low-grade, n = 77; high-grade, n = 76) and 115 healthy controls (HCs) were recruited and scanned with 3-D T1 imaging. The gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) volume in the contrahemisphere were examined. Partial correlation, logistic regression, and multivariate Cox's regression analyses were performed. Results: The contrahemispheric GM volume (CHGMV) in the high-grade glioma patients was significantly decreased compared to that in the HCs/low-grade gliomas (one-way ANOVA, Bonferroni corrected, p < 0.05). The CHGMV is significantly correlated with the WHO grade (r = -0.22, p < 0.05) and contrast-enhanced volume (r = -0.33, p < 0.01). In the high-grade gliomas, the binary logistic regression revealed that the CHGMV can independently predict isocitrate dehydrogenase 1 (IDH1) and P53 mutations. The survival curves revealed that the patients with a low CHGMV had a shorter overall survival (OS) than the patients with a high CHGMV (p = 0.001). The multivariate Cox's regression analysis showed that a low CHGMV can independently predict unfavorable OS with a hazard ratio of 2.883 (p = 0.035). Conclusions: Volume of the contrahemispheric cortex can be potentially used in clinical practice as an imaging biomarker to predict survival and molecular markers in patients with unilateral high-grade gliomas.

Monopolar Spindle 1 Kinase (MPS1/TTK) mRNA Expression is Associated with Earlier Development of Clinical Symptoms, Tumor Aggressiveness and Survival of Glioma Patients

Inhibition of the protein kinase MPS1, a mitotic spindle-checkpoint regulator, reinforces the effects of multiple therapies against glioblastoma multiforme (GBM) in experimental settings. We analyzed MPS1 mRNA-expression in gliomas WHO grade II, III and in clinical subgroups of GBM. Data were obtained by qPCR analysis of tumor and healthy brain specimens and correlated with the patients’ clinical data. MPS1 was overexpressed in all gliomas on an mRNA level (ANOVA, p < 0.01) and correlated with tumor aggressiveness. We explain previously published conflicting results on survival: high MPS1 was associated with poorer long term survival when all gliomas were analyzed combined in one group (Cox regression: t < 24 months, p = 0.009, Hazard ratio: 8.0, 95% CI: 1.7–38.4), with poorer survival solely in low-grade gliomas (LogRank: p = 0.02, Cox regression: p = 0.06, Hazard-Ratio: 8.0, 95% CI: 0.9–66.7), but not in GBM (LogRank: p > 0.05). This might be due to their lower tumor volume at the therapy start. GBM patients with high MPS1 mRNA-expression developed clinical symptoms at an earlier stage. This, however, did not benefit their overall survival, most likely due to the more aggressive tumor growth. Since MPS1 mRNA-expression in gliomas was enhanced with increasing tumor aggressiveness, patients with the worst outcome might benefit best from a treatment directed against MPS1.

Structural plasticity of the bilateral hippocampus in glioma patients

This study investigates the structural plasticity and neuronal reaction of the hippocampus in glioma patient pre-surgery. Ninety-nine glioma patients without bilateral hippocampus involvement (low-grade, n=52; high-grade, n=47) and 80 healthy controls with 3D T1 images and resting-fMRI were included. Hippocampal volume and dynamic amplitude of low-frequency fluctuation (dALFF) were analyzed among groups. Relationships between hippocampal volume and clinical characteristics were assessed. We observed remote hippocampal volume increases in low- and high-grade glioma and a greater response of the ipsilateral hippocampus than the contralesional hippocampus. The bilateral hippocampal dALFF was significantly increased in high-grade glioma. Tumor-associated epilepsy and the IDH-1 mutation did not affect hippocampal volume in glioma patients. No significant relationship between hippocampal volume and age was observed in high-grade glioma. The Kaplan-Meier curve and log-rank test revealed that large hippocampal volume was associated with shorter overall survival (OS) compared with small hippocampal volume (p=0.007). Multivariate Cox regression analysis revealed that large hippocampal volume was an independent predictor of unfavorable OS (HR=3.597, 95% CI: 1.160-11.153, p=0.027) in high-grade glioma. Our findings suggest that the hippocampus has a remarkable degree of plasticity in response to pathological stimulation of glioma and that the hippocampal reaction to glioma may be related to tumor malignancy.

Safety and efficacy of VB-111, an anticancer gene therapy, in patients with recurrent glioblastoma: results of a phase I/II study

BACKGROUND

VB-111 is a non-replicating adenovirus carrying a Fas-chimera transgene, leading to targeted apoptosis of tumor vascular endothelium and induction of a tumor-specific immune response. This phase I/II study evaluated the safety, tolerability, and efficacy of VB-111 with and without bevacizumab in recurrent glioblastoma (rGBM).

METHODS

Patients with rGBM (n = 72) received VB-111 in 4 treatment groups: subtherapeutic (VB-111 dose escalation), limited exposure (LE; VB-111 monotherapy until progression), primed combination (VB-111 monotherapy continued upon progression with combination of bevacizumab), and unprimed combination (upfront combination of VB-111 and bevacizumab). The primary endpoint was median overall survival (OS). Secondary endpoints were safety, overall response rate, and progression-free survival (PFS).

RESULTS

VB-111 was well tolerated. The most common adverse event was transient mild-moderate fever. Median OS time was significantly longer in the primed combination group compared with both LE (414 vs 223 days; hazard ratio [HR], 0.48; P = 0.043) and unprimed combination (414 vs 141.5 days; HR, 0.24; P = 0.0056). Patients in the combination phase of the primed combination group had a median PFS time of 90 days compared with 60 in the LE group (HR, 0.36; P = 0.032), and 63 in the unprimed combination group (P = 0.72). Radiographic responders to VB-111 exhibited characteristic, expansive areas of necrosis in the areas of initial enhancing disease.

CONCLUSIONS

Patients with rGBM who were primed with VB-111 monotherapy that continued after progression with the addition of bevacizumab showed significant survival and PFS advantage, as well as specific imaging characteristics related to VB-111 mechanism of action. These results warrant further assessment in a randomized controlled study.

Rate of change in maximum 18F-FDOPA PET uptake and non-enhancing tumor volume predict malignant transformation and overall survival in low-grade gliomas

PURPOSE

To examine whether the rate of change in maximum ¹⁸F-FDOPA PET uptake and the rate of change in non-enhancing tumor volume could predict malignant transformation and residual overall survival (OS) in low grade glioma (LGG) patients who received serial ¹⁸F-FDOPA PET and MRI scans.

METHODS

27 LGG patients with ≥ 2 ¹⁸F-FDOPA PET and MRI scans between 2003 and 2016 were included. The rate of change in FLAIR volume (uL/day) and maximum normalized ¹⁸F-FDOPA specific uptake value (nSUV_max/month), were compared between histological and molecular subtypes. General linear models (GLMs) were used to integrate clinical information with MR-PET measurements to predict malignant transformation. Cox univariate and multivariable regression analyses were performed to identify imaging and clinical risk factors related to OS.

RESULTS

A GLM using patient age, treatment, the rate of change in FLAIR and ¹⁸F-FDOPA nSUV_max could predict malignant transformation with > 67% sensitivity and specificity (AUC = 0.7556, P = 0.0248). A significant association was observed between OS and continuous rates of change in PET uptake (HR = 1.0212, P = 0.0034). Cox multivariable analysis confirmed that continuous measures of the rate of change in PET uptake was an independent predictor of OS (HR = 1.0242, P = 0.0033); however, stratification of patients based on increasing or decreasing rate of change in FLAIR (HR = 2.220, P = 0.025), PET uptake (HR = 2.148, P = 0.0311), or both FLAIR and PET (HR = 2.354, P = 0.0135) predicted OS.

CONCLUSIONS

The change in maximum normalized ¹⁸F-FDOPA PET uptake, with or without clinical information and rate of change in tumor volume, may be useful for predicting the risk of malignant transformation and estimating residual survival in patients with LGG.

Advanced MRI Assessment during Dendritic Cell Immunotherapy Added to Standard Treatment Against Glioblastoma

Evaluating changes induced by immunotherapies (IT) on conventional magnetic resonance imaging (MRI) is difficult because those treatments may produce inflammatory responses. To explore the potential contribution of advanced MRI to distinguish pseudoprogression (PsP) and true tumor progression (TTP), and to identify patients obtaining therapeutic benefit from IT, we examined aMRI findings in newly diagnosed glioblastoma treated with dendritic cell IT added to standard treatment. We analyzed longitudinal MRIs obtained in 22 patients enrolled in the EUDRACT N° 2008-005035-15 trial. According to RANO criteria, we observed 18 TTP and 8 PsP. Comparing MRI performed at the time of TTP/PsP with the previous exam performed two months before, a difference in cerebral blood volume ΔrCBV_max ≥ 0.47 distinguished TTP from PsP with a sensitivity of 67% and specificity of 75% (p = 0.004). A decrease in minimal apparent diffusion coefficient rADC_min (1.15 vs. 1.01, p = 0.003) was observed after four vaccinations only in patients with a persistent increase of natural killer cells (response effectors during IT) in peripheral blood. Basal rADC_min > 1 was independent predictor of longer progression free (16.1 vs. 9 months, p = 0.0001) and overall survival (32.8 vs. 17.5 months, p = 0.0005). In conclusion, rADC predicted response to immunotherapy and survival; Apparent Diffusion Coefficient (ADC) and Cerebral Blood Volume (CBV) modifications over time help differentiating PsP from TTP at onset.

The FDA NIH Biomarkers, EndpointS, and other Tools (BEST) resource in neuro-oncology

In early 2016, the FDA and the National Institutes of Health (NIH) published the first version of the glossary included in the Biomarkers, EndpointS, and other Tools (BEST) resource.1 The BEST glossary was constructed to harmonize and clarify terms used in translational science and medical product development and to provide a common language used for communication by those agencies. It is considered a "living" document that will be updated in the future. This review will discuss the main biomarker and clinical outcome categories contained in the BEST glossary as they apply to neuro-oncology, as well as the overlapping and hierarchical relationships among them.

Validation of postoperative residual contrast-enhancing tumor volume as an independent prognostic factor for overall survival in newly diagnosed glioblastoma

Background

In the current study, we pooled imaging data in newly diagnosed glioblastoma (GBM) patients from international multicenter clinical trials, single institution databases, and multicenter clinical trial consortiums to identify the relationship between postoperative residual enhancing tumor volume and overall survival (OS).

Methods

Data from 1511 newly diagnosed GBM patients from 5 data sources were included in the current study: (i) a single institution database from UCLA (N = 398; Discovery); (ii) patients from the Ben and Cathy Ivy Foundation for Early Phase Clinical Trials Network Radiogenomics Database (N = 262 from 8 centers; Confirmation); (iii) the chemoradiation placebo arm from an international phase III trial (AVAglio; N = 394 from 120 locations in 23 countries; Validation); (iv) the experimental arm from AVAglio examining chemoradiation plus bevacizumab (N = 404 from 120 locations in 23 countries; Exploratory Set 1); and (v) an Alliance (N0874) phase I/II trial of vorinostat plus chemoradiation (N = 53; Exploratory Set 2). Postsurgical, residual enhancing disease was quantified using T1 subtraction maps. Multivariate Cox regression models were used to determine influence of clinical variables, O6-methylguanine-DNA methyltransferase (MGMT) status, and residual tumor volume on OS.

Results

A log-linear relationship was observed between postoperative, residual enhancing tumor volume and OS in newly diagnosed GBM treated with standard chemoradiation. Postoperative tumor volume is a prognostic factor for OS (P < 0.01), regardless of therapy, age, and MGMT promoter methylation status.

Conclusion

Postsurgical, residual contrast-enhancing disease significantly negatively influences survival in patients with newly diagnosed GBM treated with chemoradiation with or without concomitant experimental therapy.

Radiomics and MGMT promoter methylation for prognostication of newly diagnosed glioblastoma

We attempted to establish a magnetic resonance imaging (MRI)-based radiomic model for stratifying prognostic subgroups of newly diagnosed glioblastoma (GBM) patients and predicting O (6)-methylguanine-DNA methyltransferase promotor methylation (pMGMT-met) status of the tumor. Preoperative MRI scans from 201 newly diagnosed GBM patients were included in this study. A total of 489 texture features including the first-order feature, second-order features from 162 datasets, and location data from 182 datasets were collected. Supervised principal component analysis was used for prognostication and predictive modeling for pMGMT-met status was performed based on least absolute shrinkage and selection operator regression. 22 radiomic features that were correlated with prognosis were used to successfully stratify patients into high-risk and low-risk groups (p = 0.004, Log-rank test). The radiomic high- and low-risk stratification and pMGMT status were independent prognostic factors. As a matter of fact, predictive accuracy of the pMGMT methylation status was 67% when modeled by two significant radiomic features. A significant survival difference was observed among the combined high-risk group, combined intermediate-risk group (this group consists of radiomic low risk and pMGMT-unmet or radiomic high risk and pMGMT-met), and combined low-risk group (p = 0.0003, Log-rank test). Radiomics can be used to build a prognostic score for stratifying high- and low-risk GBM, which was an independent prognostic factor from pMGMT methylation status. On the other hand, predictive accuracy of the pMGMT methylation status by radiomic analysis was insufficient for practical use.

Volumetric response quantified using T1 subtraction predicts long-term survival benefit from cabozantinib monotherapy in recurrent glioblastoma

Background

To overcome challenges with traditional response assessment in anti-angiogenic agents, the current study uses T1 subtraction maps to quantify volumetric radiographic response in monotherapy with cabozantinib, an orally bioavailable tyrosine kinase inhibitor with activity against vascular endothelial growth factor receptor 2 (VEGFR2), hepatocyte growth factor receptor (MET), and AXL, in an open-label, phase II trial in patients with recurrent glioblastoma (GBM) (NCT00704288).

Methods

A total of 108 patients with adequate imaging data and confirmed recurrent GBM were included in this retrospective study from a phase II multicenter trial of cabozantinib monotherapy (XL184-201) at either 100 mg (N = 87) or 140 mg (N = 21) per day. Contrast enhanced T1-weighted digital subtraction maps were used to define volume of contrast-enhancing tumor at baseline and subsequent follow-up time points. Volumetric radiographic response (>65% reduction in contrast-enhancing tumor volume from pretreatment baseline tumor volume sustained for more than 4 wk) was tested as an independent predictor of overall survival (OS).

Results

Volumetric response rate for all therapeutic doses was 38.9% (41.4% and 28.6% for 100 mg and 140 mg doses, respectively). A log-linear association between baseline tumor volume and OS (P = 0.0006) and a linear correlation between initial change in tumor volume and OS (P = 0.0256) were observed. A significant difference in OS was observed between responders (median OS = 20.6 mo) and nonresponders (median OS = 8.0 mo) (hazard ratio [HR] = 0.3050, P < 0.0001). Multivariable analyses showed that continuous measures of baseline tumor volume (HR = 1.0233, P < 0.0001) and volumetric response (HR = 0.2240, P < 0.0001) were independent predictors of OS.

Conclusions

T1 subtraction maps provide value in determining response in recurrent GBM treated with cabozantinib and correlated with survival benefit.

Localized Blood-Brain Barrier Opening in Ovine Model Using Image-Guided Transcranial Focused Ultrasound

Transcranial application of focused ultrasound (FUS) combined with vascular introduction of microbubble contrast agents (MBs) has emerged as a non-invasive technique that can temporarily create a localized opening in the blood-brain barrier (BBB). Under image-guidance, we administered FUS to sheep brain after intravenous injection of microbubbles. BBB opening was confirmed by performing dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to detect the extravasated gadolinium-based magnetic resonance contrast agents. Through pharmacokinetic analysis as well as independent component analysis of the DCE-MRI data, we observed localized enhancement in BBB permeability at the area that subjected to acoustic pressure of 0.48 MPa (mechanical index = 0.96). On the other hand, application of a higher pressure at 0.58 MPa resulted in localized, minor cerebral hemorrhage. No animals exhibited abnormal behavior during the post-FUS survival periods up to 2 mo. Our data suggest that monitoring for excessive BBB disruption is important for safe translation of the method to humans.

A radiomics nomogram based on multiparametric MRI might stratify glioblastoma patients according to survival

OBJECTIVES

To construct a radiomics nomogram for the individualized estimation of the survival stratification in glioblastoma (GBM) patients using the multiregional information extracted from multiparametric MRI, which could facilitate the clinical decision-making for GBM patients.

MATERIALS AND METHODS

A total of 105 eligible GBM patients (57 in the long-term and 48 in the short-term survival groups, separated by an overall survival of 12 months) were selected from the Cancer Genome Atlas. These patients were divided into a training set (n = 70) and a validation set (n = 35). Radiomics features (n = 4000) were extracted from multiple regions of the GBM using multiparametric MRI. Then, a radiomics signature was constructed using least absolute shrinkage and selection operator regression for each patient in the training set. Combined with clinical risk factors, a radiomics nomogram was constructed based on a multivariate logistic regression model. The performance of this radiomics nomogram was assessed by calibration, discrimination, and clinical usefulness.

RESULTS

The radiomics signature consisted of 25 selected features and performed better than clinical risk factors (i.e., age, Karnofsky performance status, and treatment strategy) in survival stratification. When the radiomics signature and clinical risk factors were combined, the radiomics nomogram exhibited promising discrimination in the training (C-index, 0.971) and validation (C-index, 0.974) sets. The favorable calibration and decision curve analysis indicated the clinical usefulness of the radiomics nomogram.

CONCLUSIONS

The presented radiomics nomogram, as a non-invasive prediction tool, could exhibit a favorable predictive accuracy and provide individualized probabilities of survival stratification for GBM patients.

KEY POINTS

• Non-invasive survival stratification of GBM patients can be obtained with a radiomics nomogram. • The proposed nomogram constructed by radiomics signature selected from 4000 radiomics features, combined with independent clinical risk factors such as age, Karnofsky performance status, and treatment strategy. • The proposed radiomics nomogram exhibited good calibration and discrimination for survival stratification of GBM patients in both training (C-index, 0.971) and validation (C-index, 0.974) sets.

Neoadjuvant anti-PD-1 immunotherapy promotes a survival benefit with intratumoral and systemic immune responses in recurrent glioblastoma

Glioblastoma is the most common primary malignant brain tumor in adults and is associated with poor survival. The Ivy Foundation Early Phase Clinical Trials Consortium conducted a randomized, multi-institution clinical trial to evaluate immune responses and survival following neoadjuvant and/or adjuvant therapy with pembrolizumab in 35 patients with recurrent, surgically resectable glioblastoma. Patients who were randomized to receive neoadjuvant pembrolizumab, with continued adjuvant therapy following surgery, had significantly extended overall survival compared to patients that were randomized to receive adjuvant, post-surgical programmed cell death protein 1 (PD-1) blockade alone. Neoadjuvant PD-1 blockade was associated with upregulation of T cell- and interferon-γ-related gene expression, but downregulation of cell-cycle-related gene expression within the tumor, which was not seen in patients that received adjuvant therapy alone. Focal induction of programmed death-ligand 1 in the tumor microenvironment, enhanced clonal expansion of T cells, decreased PD-1 expression on peripheral blood T cells and a decreasing monocytic population was observed more frequently in the neoadjuvant group than in patients treated only in the adjuvant setting. These findings suggest that the neoadjuvant administration of PD-1 blockade enhances both the local and systemic antitumor immune response and may represent a more efficacious approach to the treatment of this uniformly lethal brain tumor.