Evidence and context of use for contrast enhancement as a surrogate of disease burden and treatment response in malignant glioma

A novel methodology for mapping interstitial fluid dynamics in murine brain tumors using DCE-MRI

We present a comprehensive methodology for measuring heterogeneous interstitial fluid flow in murine brain tumors using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) coupled with the computational tool, Lymph4D. This four-part protocol encompasses glioma cell preparation, tumor inoculation, MRI imaging protocol, and histological verification using Evans Blue. While conventional DCE-MRI analysis primarily focuses on vascular perfusion, our methods reveal untapped potential to extract crucial information about interstitial fluid dynamics, including directions, velocities, and diffusion coefficients. This methodology extends beyond glioma research, with applicability to conditions routinely imaged with DCE-MRI, thereby offering a versatile tool for investigating interstitial fluid dynamics across a wide range of diseases and conditions. Our methodology holds promise for accelerating discoveries and advancements in biomedical research, ultimately enhancing diagnostic and therapeutic strategies for a wide range of diseases and conditions.

Noninvasive Autopsy-Validated Tumor Probability Maps Identify Glioma Invasion Beyond Contrast Enhancement

BACKGROUND AND OBJECTIVES

This study identified a clinically significant subset of patients with glioma with tumor outside of contrast enhancement present at autopsy and subsequently developed a method for detecting nonenhancing tumor using radio-pathomic mapping. We tested the hypothesis that autopsy-based radio-pathomic tumor probability maps would be able to noninvasively identify areas of infiltrative tumor beyond traditional imaging signatures.

METHODS

A total of 159 tissue samples from 65 subjects were aligned to MRI acquired nearest to death for this retrospective study. Demographic and survival characteristics for patients with and without tumor beyond the contrast-enhancing margin were computed. An ensemble algorithm was used to predict pixelwise tumor presence from pathological annotations using segmented cellularity (Cell), extracellular fluid, and cytoplasm density as input (6 train/3 test subjects). A second level of ensemble algorithms was used to predict voxelwise Cell, extracellular fluid, and cytoplasm on the full data set (43 train/22 test subjects) using 5-by-5 voxel tiles from T1, T1 + C, fluid-attenuated inversion recovery, and apparent diffusion coefficient as input. The models were then combined to generate noninvasive whole brain maps of tumor probability.

RESULTS

Tumor outside of contrast was identified in 41.5% of patients, who showed worse survival outcomes (hazard ratio = 3.90, P < .001). Tumor probability maps reliably tracked nonenhancing tumor on a range of local and external unseen data, identifying tumor outside of contrast in 69% of presurgical cases that also showed reduced survival outcomes (hazard ratio = 1.67, P = .027).

CONCLUSION

This study developed a multistage model for mapping gliomas using autopsy tissue samples as ground truth, which was able to identify regions of tumor beyond traditional imaging signatures.

Cluster-based prognostication in glioblastoma: Unveiling heterogeneity based on diffusion and perfusion similarities

BACKGROUND

While the association between diffusion and perfusion magnetic resonance imaging (MRI) and survival in glioblastoma is established, prognostic models for patients are lacking. This study employed clustering of functional imaging to identify distinct functional phenotypes in untreated glioblastomas, assessing their prognostic significance for overall survival.

METHODS

A total of 289 patients with glioblastoma who underwent preoperative multimodal MR imaging were included. Mean values of apparent diffusion coefficient normalized relative cerebral blood volume and relative cerebral blood flow were calculated for different tumor compartments and the entire tumor. Distinct imaging patterns were identified using partition around medoids (PAM) clustering on the training dataset, and their ability to predict overall survival was assessed. Additionally, tree-based machine-learning models were trained to ascertain the significance of features pertaining to cluster membership.

RESULTS

Using the training dataset (231/289) we identified 2 stable imaging phenotypes through PAM clustering with significantly different overall survival (OS). Validation in an independent test set revealed a high-risk group with a median OS of 10.2 months and a low-risk group with a median OS of 26.6 months (P = 0.012). Patients in the low-risk cluster had high diffusion and low perfusion values throughout, while the high-risk cluster displayed the reverse pattern. Including cluster membership in all multivariate Cox regression analyses improved performance (P ≤ 0.004 each).

CONCLUSIONS

Our research demonstrates that data-driven clustering can identify clinically relevant, distinct imaging phenotypes, highlighting the potential role of diffusion, and perfusion MRI in predicting survival rates of glioblastoma patients.

Isocitrate Dehydrogenase 1/2 Wildtype Adult Astrocytoma with WHO Grade 2/3 Histological Features: Molecular Re-Classification, Prognostic Factors, Clinical Outcomes

BACKGROUND

Isocitrate Dehydrogenase 1/2 (IDH 1/2)-wildtype (WT) astrocytomas constitute a heterogeneous group of tumors and have undergone a series of diagnostic reclassifications over time. This study aimed to investigate molecular markers, clinical, imaging, and treatment factors predictive of outcomes in WHO grade 2/3 IDH-WT astrocytomas ('early glioblastoma').

METHODOLOGY

Patients with WHO grade 2/3 IDH-WT astrocytomas were identified from the hospital archives. They were cross-referenced with the electronic medical records systems, including neuroimaging. The expert neuro-pathology team retrieved data on molecular markers-MGMT, TERT, IDH, and EGFR. Tumors with a TERT mutation and/or EGFR amplification were reclassified as glioblastoma.

RESULTS

Fifty-four patients were identified. Sixty-three percent of the patients could be conclusively reclassified as glioblastoma based on either TERT mutation, EGFR amplification, or both. On imaging, 65% showed gadolinium enhancement on MRI. Thirty-nine patients (72%) received long-course radiotherapy, of whom 64% received concurrent chemotherapy. The median follow-up of the group was 16 months (range: 2-90), and the median overall survival (OS) was 17.3 months. The 2-year OS of the whole cohort was 31%. On univariate analysis, older age, worse performance status (PS), and presence versus absence of contrast enhancement on diagnostic MRI were statistically significant for poorer OS.

CONCLUSION

IDH-WT WHO grade 2/3 astrocytomas are a heterogeneous group of tumors with poor clinical outcomes. The majority can be reclassified as glioblastoma, based on current WHO classification criteria, but further understanding of the underlying biology of these tumors and the discovery of novel targeted agents are needed for better outcomes.

Radio-pathomic maps of glioblastoma identify phenotypes of non-enhancing tumor infiltration associated with bevacizumab treatment response

BACKGROUND

Autopsy-based radio-pathomic maps of glioma pathology have shown substantial promise inidentifying areas of non-enhancing tumor presence, which may be able to differentiate subsets of patients that respond favorably to treatments such as bevacizumab that have shown mixed efficacy evidence. We tested the hypthesis that phenotypes of non-enhancing tumor fronts can distinguish between glioblastoma patients that will respond favorably to bevacizumab and will visually capture treatment response.

METHODS

T1, T1C, FLAIR, and ADC images were used to generate radio-pathomic maps of tumor characteristics for 79 pre-treatment patients with a primary GBM or high-grade IDH1-mutant astrocytoma for this study. Novel phenotyping (hypercellular, hypocellular, hybrid, or well-circumscribed front) of the non-enhancing tumor front was performed on each case. Kaplan Meier analyses were then used to assess differences in survival and bevacizumab efficacy between phenotypes. Phenotype compartment segmentations generated longitudinally for a subset of 26 patients over the course of bevacizumab treatment, where a mixed effect model was used to detect longitudinal changes.

RESULTS

Well-Circumscribed patients showed significant/trending increases in survival compared to Hypercellular Front (HR = 2.0, p = 0.05), Hypocellular Front (HR = 2.02, p = 0.03), and Hybrid Front tumors (HR = 1.75, p = 0.09). Only patients with hypocellular or hybrid fronts showed significant survival benefits from bevacizumab treatment (HR = 2.35, p = 0.02; and HR = 2.45, p = 0.03, respectively). Hypocellular volumes decreased by an average 50.52 mm3 per day of bevacizumab treatment (p = 0.002).

CONCLUSION

Patients with a hypocellular tumor front identified by radio-pathomic maps showed improved treatment efficacy when treated with bevacizumab, and reducing hypocellular volumes over the course of treatment may indicate treatment response.

Radiomic profiling for insular diffuse glioma stratification with distinct biologic pathway activities

Current literature emphasizes surgical complexities and customized resection for managing insular gliomas; however, radiogenomic investigations into prognostic radiomic traits remain limited. We aimed to develop and validate a radiomic model using multiparametric magnetic resonance imaging (MRI) for prognostic prediction and to reveal the underlying biological mechanisms. Radiomic features from preoperative MRI were utilized to develop and validate a radiomic risk signature (RRS) for insular gliomas, validated through paired MRI and RNA-seq data (N = 39), to identify core pathways underlying the RRS and individual prognostic radiomic features. An 18-feature-based RRS was established for overall survival (OS) prediction. Gene set enrichment analysis (GSEA) and weighted gene coexpression network analysis (WGCNA) were used to identify intersectional pathways. In total, 364 patients with insular gliomas (training set, N = 295; validation set, N = 69) were enrolled. RRS was significantly associated with insular glioma OS (log-rank p = 0.00058; HR = 3.595, 95% CI:1.636-7.898) in the validation set. The radiomic-pathological-clinical model (R-P-CM) displayed enhanced reliability and accuracy in prognostic prediction. The radiogenomic analysis revealed 322 intersectional pathways through GSEA and WGCNA fusion; 13 prognostic radiomic features were significantly correlated with these intersectional pathways. The RRS demonstrated independent predictive value for insular glioma prognosis compared with established clinical and pathological profiles. The biological basis for prognostic radiomic indicators includes immune, proliferative, migratory, metabolic, and cellular biological function-related pathways.

Exploring the association of glioma tumor residuals from incongruent [18F]FET PET/MR imaging with tumor proliferation using a multiparametric MRI radiomics nomogram

PURPOSE

The study aimed to using multiparametric MRI radiomics to predict glioma tumor residuals (TRFET over MR) derived from incongruent [18F]fluoroethyl-L-tyrosine ([18F]FET) PET/MR imaging.

METHODS

One hundred ten patients with gliomas who underwent [18F]FET PET/MR scanning were retrospectively analyzed. The TRFET over MR was identified by the discrepancy-PET that the extent of resection (EOR) based on MRI subtracted the biological tumor volume on PET images. The MRI parameters and radiomics features were extracted based on EOR and selected by the least absolute shrinkage and selection operator to construct radiomics score (Rad-score). The correlation network analysis of all features was analyzed by Spearman's correlation tests. The methods for evaluating the clinical usefulness consisted of the receiver operating characteristic curve, the calibration curve, and decision curve analysis.

RESULTS

The Rad-score of the patients with the TRFET over MR was significantly higher than those with the non TRFET over MR (p < 0.001). The Rad-score was significantly correlated with the discrepancy-PET (r = 0.72, p < 0.001), Ki-67 level (r = 0.76, p < 0.001), and epidermal growth factor receptor (EGFR) of gliomas (r = 0.75, p < 0.001), respectively. Moreover, there was a difference of the correlation network analysis between the TRPET over MR group and non TRFET over MR group. The nomogram combing Rad-score and clinical features had the greatest performance in predicting TRFET over MR (AUC = 0.90/0.87, training/testing). There was a significant difference in prognosis (median OS, 17 m vs. 43 m) between patients with TRFET over MR and non TRFET over MR based on nomogram prediction (p < 0.001).

CONCLUSION

The nomogram based on MRI radiomics would predict gliomas tumor residuals caused by the absence of 18F-PET PET examination and adjust EOR to improve prognosis.

Radio-pathomic maps of glioblastoma identify phenotypes of non-enhancing tumor infiltration associated with bevacizumab treatment response

Background

Autopsy-based radio-pathomic maps of glioma pathology have shown substantial promise inidentifying areas of non-enhancing tumor presence, which may be able to differentiate subsets of patients that respond favorably to treatments such as bevacizumab that have shown mixed efficacy evidence. We tested the hypthesis that phenotypes of non-enhancing tumor fronts can distinguish between glioblastoma patients that will respond favorably to bevacizumab and will visually capture treatment response.

Methods

T1, T1C, FLAIR, and ADC images were used to generate radio-pathomic maps of tumor characteristics for 79 pre-treatment patients with a primary GBM or high-grade IDH1-mutant astrocytoma for this study. Novel phenotyping (hypercellular, hypocellular, hybrid, or well-circumscribed front) of the non-enhancing tumor front was performed on each case. Kaplan Meier analyses were then used to assess differences in survival and bevacizumab efficacy between phenotypes. Phenotype compartment segmentations generated longitudinally for a subset of 26 patients over the course of bevacizumab treatment, where a mixed effect model was used to detect longitudinal changes.

Results

Well-Circumscribed patients showed significant/trending increases in survival compared to Hypercellular Front (HR = 2.0, p = 0.05), Hypocellular Front (HR = 2.02, p = 0.03), and Hybrid Front tumors (HR = 1.75, p = 0.09). Only patients with hypocellular or hybrid fronts showed significant survival benefits from bevacizumab treatment (HR = 2.35, p = 0.02; and HR = 2.45, p = 0.03, respectively). Hypocellular volumes decreased by an average 50.52 mm3 per day of bevacizumab treatment (p = 0.002).

Conclusion

Patients with a hypocellular tumor front identified by radio-pathomic maps showed improved treatment efficacy when treated with bevacizumab, and reducing hypocellular volumes over the course of treatment may indicate treatment response.

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.

Quantification of perineural satellitosis in pretreatment glioblastoma with structural MRI and a diffusion tensor imaging template

Background

Survival outcomes for glioblastoma (GBM) patients remain unfavorable, and tumor recurrence is often observed. Understanding the radiological growth patterns of GBM could aid in improving outcomes. This study aimed to examine the relationship between contrast-enhancing tumor growth direction and white matter, using an image registration and deformation strategy.

Methods

In GBM patients 2 pretreatment scans (diagnostic and neuronavigation) were gathered retrospectively, and coregistered to a template and diffusion tensor imaging (DTI) atlas. The GBM lesions were segmented and coregistered to the same space. Growth vectors were derived and divided into vector populations parallel (Φ = 0-20°) and perpendicular (Φ = 70-90°) to white matter. To test for statistical significance between parallel and perpendicular groups, a paired samples Student's t-test was performed. O6-methylguanine-DNA methyltransferase (MGMT) methylation status and its correlation to growth rate were also tested using a one-way ANOVA test.

Results

For 78 GBM patients (mean age 61 years ± 13 SD, 32 men), the included GBM lesions showed a predominant preference for perineural satellitosis (P < .001), with a mean percentile growth of 30.8% (95% CI: 29.6-32.0%) parallel (0° < |Φ| < 20°) to white matter. Perpendicular tumor growth with respect to white matter microstructure (70° < |Φ| < 90°) showed to be 22.7% (95% CI: 21.3-24.1%) of total tumor growth direction.

Conclusions

The presented strategy showed that tumor growth direction in pretreatment GBM patients correlated with white matter architecture. Future studies with patient-specific DTI data are required to verify the accuracy of this method prospectively to identify its usefulness as a clinical metric in pre and posttreatment settings.

RANO 2.0: Update to the Response Assessment in Neuro-Oncology Criteria for High- and Low-Grade Gliomas in Adults

PURPOSE

The Response Assessment in Neuro-Oncology (RANO) criteria for high-grade gliomas (RANO-HGG) and low-grade gliomas (RANO-LGG) were developed to improve reliability of response assessment in glioma trials. Over time, some limitations of these criteria were identified, and challenges emerged regarding integrating features of the modified RANO (mRANO) or the immunotherapy RANO (iRANO) criteria.

METHODS

Informed by data from studies evaluating the different criteria, updates to the RANO criteria are proposed (RANO 2.0).

RESULTS

We recommend a standard set of criteria for both high- and low-grade gliomas, to be used for all trials regardless of the treatment modalities being evaluated. In the newly diagnosed setting, the postradiotherapy magnetic resonance imaging (MRI), rather than the postsurgical MRI, will be used as the baseline for comparison with subsequent scans. Since the incidence of pseudoprogression is high in the 12 weeks after radiotherapy, continuation of treatment and confirmation of progression during this period with a repeat MRI, or histopathologic evidence of unequivocal recurrent tumor, are required to define tumor progression. However, confirmation scans are not mandatory after this period nor for the evaluation of treatment for recurrent tumors. For treatments with a high likelihood of pseudoprogression, mandatory confirmation of progression with a repeat MRI is highly recommended. The primary measurement remains the maximum cross-sectional area of tumor (two-dimensional) but volumetric measurements are an option. For IDH wild-type glioblastoma, the nonenhancing disease will no longer be evaluated except when assessing response to antiangiogenic agents. In IDH-mutated tumors with a significant nonenhancing component, clinical trials may require evaluating both the enhancing and nonenhancing tumor components for response assessment.

CONCLUSION

The revised RANO 2.0 criteria refine response assessment in gliomas.

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.

Imaging biomarkers for clinical applications in neuro-oncology: current status and future perspectives

Biomarker discovery and development are popular for detecting the subtle diseases. However, biomarkers are needed to be validated and approved, and even fewer are ever used clinically. Imaging biomarkers have a crucial role in the treatment of cancer patients because they provide objective information on tumor biology, the tumor's habitat, and the tumor's signature in the environment. Tumor changes in response to an intervention complement molecular and genomic translational diagnosis as well as quantitative information. Neuro-oncology has become more prominent in diagnostics and targeted therapies. The classification of tumors has been actively updated, and drug discovery, and delivery in nanoimmunotherapies are advancing in the field of target therapy research. It is important that biomarkers and diagnostic implements be developed and used to assess the prognosis or late effects of long-term survivors. An improved realization of cancer biology has transformed its management with an increasing emphasis on a personalized approach in precision medicine. In the first part, we discuss the biomarker categories in relation to the courses of a disease and specific clinical contexts, including that patients and specimens should both directly reflect the target population and intended use. In the second part, we present the CT perfusion approach that provides quantitative and qualitative data that has been successfully applied to the clinical diagnosis, treatment and application. Furthermore, the novel and promising multiparametric MR imageing approach will provide deeper insights regarding the tumor microenvironment in the immune response. Additionally, we briefly remark new tactics based on MRI and PET for converging on imaging biomarkers combined with applications of bioinformatics in artificial intelligence. In the third part, we briefly address new approaches based on theranostics in precision medicine. These sophisticated techniques merge achievable standardizations into an applicatory apparatus for primarily a diagnostic implementation and tracking radioactive drugs to identify and to deliver therapies in an individualized medicine paradigm. In this article, we describe the critical principles for imaging biomarker characterization and discuss the current status of CT, MRI and PET in finiding imaging biomarkers of early disease.

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.

Dual-Energy Computed Tomography-Based Iodine Concentration Estimation for Evaluating Choroidal Malignant Melanoma Response to Treatment: Optimization and Primary Validation

Contrast-enhanced imaging for choroidal malignant melanoma (CMM) is mostly limited to detecting metastatic tumors, possibly due to difficulties in fixing the eye position. We aimed to (1) validate the appropriateness of estimating iodine concentration based on dual-energy computed tomography (DECT) for CMM and optimize the calculation parameters for estimation, and (2) perform a primary clinical validation by assessing the ability of this technique to show changes in CMM after charged-particle radiation therapy. The accuracy of the optimized estimate (eIC_optimized) was compared to an estimate obtained by commercial software (eIC_commercial) by determining the difference from the ground truth. Then, eIC_optimized, tumor volume, and CT values (80 kVp, 140 kVp, and synthesized 120 kVp) were measured at pre-treatment and 3 months and 1.5−2 years after treatment. The difference from the ground truth was significantly smaller in eIC_optimized than in eIC_commercial (p < 0.01). Tumor volume, CT values, and eIC_optimized all decreased significantly at 1.5−2 years after treatment, but only eIC_commercial showed a significant reduction at 3 months after treatment (p < 0.01). eIC_optimized can quantify contrast enhancement in primary CMM lesions and has high sensitivity for detecting the response to charged-particle radiation therapy, making it potentially useful for treatment monitoring.

A Head-to-Head Comparison of 18F-Fluorocholine PET/CT and Conventional MRI as Predictors of Outcome in IDH Wild-Type High-Grade Gliomas

(1) Aim: To study the associations between imaging parameters derived from contrast-enhanced MRI (CE-MRI) and 18F-fluorocholine PET/CT and their performance as prognostic predictors in isocitrate dehydrogenase wild-type (IDH-wt) high-grade gliomas. (2) Methods: A prospective, multicenter study (FuMeGA: Functional and Metabolic Glioma Analysis) including patients with baseline CE-MRI and 18F-fluorocholine PET/CT and IDH wild-type high-grade gliomas. Clinical variables such as performance status, extent of surgery and adjuvant treatments (Stupp protocol vs others) were obtained and used to discriminate overall survival (OS) and progression-free survival (PFS) as end points. Multilesionality was assessed on the visual analysis of PET/CT and CE-MRI images. After tumor segmentation, standardized uptake value (SUV)-based variables for PET/CT and volume-based and geometrical variables for PET/CT and CE-MRI were calculated. The relationships among imaging techniques variables and their association with prognosis were evaluated using Pearson’s chi-square test and the t-test. Receiver operator characteristic, Kaplan−Meier and Cox regression were used for the survival analysis. (3) Results: 54 patients were assessed. The median PFS and OS were 5 and 11 months, respectively. Significant strong relationships between volume-dependent variables obtained from PET/CT and CE-MRI were found (r > 0.750, p < 0.05). For OS, significant associations were found with SUVmax, SUVpeak, SUVmean and sphericity (HR: 1.17, p = 0.035; HR: 1.24, p = 0.042; HR: 1.62, p = 0.040 and HR: 0.8, p = 0.022, respectively). Among clinical variables, only Stupp protocol and age showed significant associations with OS and PFS. No CE-MRI derived variables showed significant association with prognosis. In multivariate analysis, age (HR: 1.04, p = 0.002), Stupp protocol (HR: 2.81, p = 0.001), multilesionality (HR: 2.20, p = 0.013) and sphericity (HR: 0.79, p = 0.027) derived from PET/CT showed independent associations with OS. For PFS, only age (HR: 1.03, p = 0.021) and treatment protocol (HR: 2.20, p = 0.008) were significant predictors. (4) Conclusions: 18F-fluorocholine PET/CT metabolic and radiomic variables were robust prognostic predictors in patients with IDH-wt high-grade gliomas, outperforming CE-MRI derived variables.

The relationship between radiomics and pathomics in Glioblastoma patients: Preliminary results from a cross-scale association study

Glioblastoma multiforme (GBM) typically exhibits substantial intratumoral heterogeneity at both microscopic and radiological resolution scales. Diffusion Weighted Imaging (DWI) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) are two functional MRI techniques that are commonly employed in clinic for the assessment of GBM tumor characteristics. This work presents initial results aiming at determining if radiomics features extracted from preoperative ADC maps and post-contrast T1 (T1C) images are associated with pathomic features arising from H&E digitized pathology images. 48 patients from the public available CPTAC-GBM database, for which both radiology and pathology images were available, were involved in the study. 91 radiomics features were extracted from ADC maps and post-contrast T1 images using PyRadiomics. 65 pathomic features were extracted from cell detection measurements from H&E images. Moreover, 91 features were extracted from cell density maps of H&E images at four different resolutions. Radiopathomic associations were evaluated by means of Spearman's correlation (ρ) and factor analysis. p values were adjusted for multiple correlations by using a false discovery rate adjustment. Significant cross-scale associations were identified between pathomics and ADC, both considering features (n = 186, 0.45 < ρ < 0.74 in absolute value) and factors (n = 5, 0.48 < ρ < 0.54 in absolute value). Significant but fewer ρ values were found concerning the association between pathomics and radiomics features (n = 53, 0.5 < ρ < 0.65 in absolute value) and factors (n = 2, ρ = 0.63 and ρ = 0.53 in absolute value). The results of this study suggest that cross-scale associations may exist between digital pathology and ADC and T1C imaging. This can be useful not only to improve the knowledge concerning GBM intratumoral heterogeneity, but also to strengthen the role of radiomics approach and its validation in clinical practice as "virtual biopsy", introducing new insights for omics integration toward a personalized medicine approach.

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.

Prognostic validation of a new classification system for extent of resection in glioblastoma: a report of the RANO resect group

BACKGROUND

Terminology to describe extent of resection in glioblastoma is inconsistent across clinical trials. A surgical classification system was previously proposed based upon residual contrast-enhancing (CE) tumor. We aimed to (I) explore the prognostic utility of the classification system and (II) define how much removed non-CE tumor translates into a survival benefit.

METHODS

The international RANO resect group retrospectively searched previously compiled databases from seven neuro-oncological centers in the USA and Europe for patients with newly diagnosed glioblastoma per WHO 2021 classification. Clinical and volumetric information from pre- and post-operative MRI were collected.

RESULTS

We collected 1008 patients with newly diagnosed IDHwt glioblastoma. 744 IDHwt glioblastomas were treated with radiochemotherapy per EORTC 26981/22981 (TMZ/RT→TMZ) following surgery. Among these homogenously treated patients, lower absolute residual tumor volumes (in cm 3) were favorably associated with outcome: patients with 'maximal CE resection' (class 2) had superior outcome compared to patients with 'submaximal CE resection' (class 3) or 'biopsy' (class 4). Extensive resection of non-CE tumor (≤5 cm 3 residual non-CE tumor) was associated with better survival among patients with complete CE resection, thus defining class 1 ('supramaximal CE resection'). The prognostic value of the resection classes was retained on multivariate analysis when adjusting for molecular and clinical markers.

CONCLUSIONS

The proposed "RANO categories for extent of resection in glioblastoma" are highly prognostic and may serve for stratification within clinical trials. Removal of non-CE tumor beyond the CE tumor borders may translate into additional survival benefit, providing a rationale to explicitly denominate such 'supramaximal CE resection'.

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.

Ellipsoid calculations versus manual tumor delineations for glioblastoma tumor volume evaluation

In glioblastoma, the response to treatment assessment is essentially based on the 2D tumor size evolution but remains disputable. Volumetric approaches were evaluated for a more accurate estimation of tumor size. This study included 57 patients and compared two volume measurement methods to determine the size of different glioblastoma regions of interest: the contrast-enhancing area, the necrotic area, the gross target volume and the volume of the edema area. The two methods, the ellipsoid formula (the calculated method) and the manual delineation (the measured method) showed a high correlation to determine glioblastoma volume and a high agreement to classify patients assessment response to treatment according to RANO criteria. This study revealed that calculated and measured methods could be used in clinical practice to estimate glioblastoma volume size and to evaluate tumor size evolution.

Radio-Pathomic Maps of Cell Density Identify Brain Tumor Invasion beyond Traditional MRI-Defined Margins

BACKGROUND AND PURPOSE

Currently, contrast-enhancing margins on T1WI are used to guide treatment of gliomas, yet tumor invasion beyond the contrast-enhancing region is a known confounding factor. Therefore, this study used postmortem tissue samples aligned with clinically acquired MRIs to quantify the relationship between intensity values and cellularity as well as to develop a radio-pathomic model to predict cellularity using MR imaging data.

MATERIALS AND METHODS

This single-institution study used 93 samples collected at postmortem examination from 44 patients with brain cancer. Tissue samples were processed, stained with H&E, and digitized for nuclei segmentation and cell density calculation. Pre- and postgadolinium contrast T1WI, T2 FLAIR, and ADC images were collected from each patient's final acquisition before death. In-house software was used to align tissue samples to the FLAIR image via manually defined control points. Mixed-effects models were used to assess the relationship between single-image intensity and cellularity for each image. An ensemble learner was trained to predict cellularity using 5 × 5 voxel tiles from each image, with a two-thirds to one-third train-test split for validation.

RESULTS

Single-image analyses found subtle associations between image intensity and cellularity, with a less pronounced relationship in patients with glioblastoma. The radio-pathomic model accurately predicted cellularity in the test set (root mean squared error = 1015 cells/mm²) and identified regions of hypercellularity beyond the contrast-enhancing region.

CONCLUSIONS

A radio-pathomic model for cellularity trained with tissue samples acquired at postmortem examination is able to identify regions of hypercellular tumor beyond traditional imaging signatures.

Regorafenib in Glioblastoma Recurrence: How to Deal With MR Imaging Treatments Changes

The treatment of recurrent high-grade gliomas remains a major challenge of daily neuro-oncology practice, and imaging findings of new therapies may be challenging. Regorafenib is a multi-kinase inhibitor that has recently been introduced into clinical practice to treat recurrent glioblastoma, bringing with it a novel panel of MRI imaging findings. On the basis of the few data in the literature and on our personal experience, we have identified the main MRI changes during regorafenib therapy, and then, we defined two different patterns, trying to create a simple summary line of the main changes of pathological tissue during therapy. We named these patterns, respectively, pattern A (less frequent, similar to classical progression disease) and pattern B (more frequent, with decreased diffusivity and decrease contrast-enhancement). We have also reported MR changes concerning signal intensity on T1-weighted and T2-weighted images, SWI, and perfusion imaging, derived from the literature (small series or case reports) and from our clinical experience. The clinical implication of these imaging modifications remains to be defined, taking into account that we are still at the dawn in the evaluation of such imaging modifications.

Feasibility of glioblastoma tissue response mapping with physiologic BOLD imaging using precise oxygen and carbon dioxide challenge

OBJECTIVES

Innovative physiologic MRI development focuses on depiction of heterogenous vascular and metabolic features in glioblastoma. For this feasibility study, we employed blood oxygenation level-dependent (BOLD) MRI with standardized and precise carbon dioxide (CO₂) and oxygen (O₂) modulation to investigate specific tumor tissue response patterns in patients with newly diagnosed glioblastoma.

MATERIALS AND METHODS

Seven newly diagnosed untreated patients with suspected glioblastoma were prospectively included to undergo a BOLD study with combined CO₂ and O₂ standardized protocol. %BOLD signal change/mmHg during hypercapnic, hypoxic, and hyperoxic stimulus was calculated in the whole brain, tumor lesion and segmented volumes of interest (VOI) [contrast-enhancing (CE) - tumor, necrosis and edema] to analyze their tissue response patterns.

RESULTS

Quantification of BOLD signal change after gas challenges can be used to identify specific responses to standardized stimuli in glioblastoma patients. Integration of this approach with automatic VOI segmentation grants improved characterization of tumor subzones and edema. Magnitude of BOLD signal change during the 3 stimuli can be visualized at voxel precision through color-coded maps overlayed onto whole brain and identified VOIs.

CONCLUSIONS

Our preliminary investigation shows good feasibility of BOLD with standardized and precise CO₂ and O₂ modulation as an emerging physiologic imaging technique to detail specific glioblastoma characteristics. The unique tissue response patterns generated can be further investigated to better detail glioblastoma lesions and gauge treatment response.

Expression and clinical significance of TIMELESS in glioma

In recent years, studies have shown that TIMELESS, as an oncogene, is involved in progression of cancers. However, its relationship with prognosis in glioma patients is rarely reported. Our purpose was to explore the role of TIMELESS in glioma. Based on 1814 glioma samples from multiple databases such as The Cancer Genome Atlas (TCGA), The Chinese Glioma Genome Atlas (CGGA), and The Gene Expression Omnibus (GEO), we use a variety of bioinformatics methods to verify the mechanism of action of TIMELESS in glioma from mRNA to protein, from appearance to mechanism analysis, from clinical features to prognosis. Then, the connectivity map (CMap) tool was used to predict drugs that inhibit the expression of TIMELESS. First, we found TIMELESS is highly expressed in glioma at mRNA and protein levels. Second, TIMELESS is an independent risk factor in prognosis and has suitable clinical diagnostic value in glioma. It was also positively correlated with World Health Organization (WHO) grade, age, and histology, and negatively correlated with isocitrate dehydrogenase (IDH) 1 mutation and 1p19q codeletion. Third, base excision, cell cycle, and mismatch repair pathway were activated by TIMELESS in glioma. We predict small molecules to inhibit TIMELESS such as 8-azaguanine, gw8510, 6-thioguanosine, and ursodeoxycholic acid. This study is the first comprehensive analysis of TIMELESS, revealing a relationship between this novel oncogene, clinical characteristics of patients with glioma, and a mechanism leading to poor prognosis. It also provides a biomarker for diagnosis and treatment of glioma and reveal the pathologic progress of glioma at the genetic level.

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.

Worse prognosis for IDH wild-type diffuse gliomas with larger residual biological tumor burden

OBJECTIVE

The association of overall survival (OS) with tumor burden, including contrast enhanced (CE) volume on CE T1-weighted images, fluid-attenuated inversion recovery (FLAIR) hyperintense volume, and 3, 4-dihydroxy-6-[18F]-fluoro-L-phenylalanine (FDOPA) hypermetabolic volume, in isocitrate dehydrogenase (IDH) wild-type gliomas remains unclear. This study aimed to assess the association between biological tumor burden in pre- and post-operative status and OS in IDH wild-type gliomas, and evaluated which volume was the best predictor of OS.

METHODS

Thirty-four patients with treatment-naïve IDH wild-type gliomas (WHO grade II 6, III 15, IV 13) were retrospectively included. Three pre-operative tumor regions of interest (ROIs) were segmented based on the CE, FLAIR hyperintense, and FDOPA hypermetabolic regions. Resected ROIs were segmented from the post-operative images. Residual CE, FLAIR hyperintense, and FDOPA hypermetabolic ROIs were created by subtracting resected ROIs from pre-operative ROIs. Cox regression analysis was conducted to investigate the association of OS with the volume of each ROI, and Akaike information criterion was used to assess the fitness.

RESULTS

Residual CE volume had a significant association with OS [hazard ratio (HR) = 1.26, p = 0.039], but this effect disappeared when controlling for tumor grade. Residual FDOPA hypermetabolic volume best fit the regression model and was significantly associated with OS (HR = 1.18, p = 0.008), even when controlling for tumor grade. FLAIR hyperintense volume showed no significant association with OS.

CONCLUSION

Residual FDOPA hypermetabolic burden predicted OS for IDH wild-type gliomas, regardless of the tumor grade. Furthermore, removing hypermetabolic and CE regions may improve the prognosis.

Maximum Uptake and Hypermetabolic Volume of 18F-FDOPA PET Estimate Molecular Status and Overall Survival in Low-Grade Gliomas: A PET and MRI Study

PURPOSE

We evaluated F-FDOPA PET and MRI characteristics in association with the molecular status and overall survival (OS) in a large number of low-grade gliomas (LGGs).

METHODS

Eighty-six patients who underwent F-FDOPA PET and MRI and were diagnosed with new or recurrent LGGs were retrospectively evaluated with respect to their isocitrate dehydrogenase (IDH) and 1p19q status (10 IDH wild type, 57 mutant, 19 unknown; 1p19q status in IDH mutant: 20 noncodeleted, 37 codeleted). After segmentation of the hyperintense area on fluid-attenuated inversion recovery image (FLAIRROI), the following were calculated: normalized SUVmax (nSUVmax) of F-FDOPA relative to the striatum, F-FDOPA hypermetabolic volume (tumor-to-striatum ratios >1), FLAIRROI volume, relative cerebral blood volume, and apparent diffusion coefficient within FLAIRROI. Receiver operating characteristic curve and Cox regression analyses were performed.

RESULTS

PET and MRI metrics combined with age predicted the IDH mutation and 1p19q codeletion statuses with sensitivities of 73% and 76% and specificities of 100% and 94%, respectively. Significant correlations were found between OS and the IDH mutation status (hazard ratio [HR] = 4.939), nSUVmax (HR = 2.827), F-FDOPA hypermetabolic volume (HR = 1.048), and FLAIRROI volume (HR = 1.006). The nSUVmax (HR = 151.6) for newly diagnosed LGGs and the F-FDOPA hypermetabolic volume (HR = 1.038) for recurrent LGGs demonstrated significant association with OS.

CONCLUSIONS

Combining F-FDOPA PET and MRI with age proved useful for predicting the molecular status in patients with LGGs, whereas the nSUVmax and F-FDOPA hypermetabolic volume may be useful for prognostication.

Knockdown of TXNDC9 induces apoptosis and autophagy in glioma and mediates cell differentiation by p53 activation

Glioma is the most common malignant brain tumor. Because of its high degree of malignancy, the effect of surgical treatment, radiotherapy, chemotherapy, or immunotherapy is not ideal. TXNDC9 belongs to thioredoxin domain-containing proteins, which is involved in tumor progression. However, no research associated with TXNDC9 has been reported in glioma. In this study, we found that TXNDC9 was upregulated in glioma. Knockdown of TXNDC9 would prevent proliferation and metastasis, induce the apoptosis rate of glioma cells, and promote the expression Cleaved-caspase3, Cleaved-caspase8, Cleaved-caspase9. Meanwhile, knockdown of TXNDC9 induced autophagy by increasing the level of LC3 and Beclin-1. Cell morphology and expression analysis of GFAP, Vimentin, verified that TXNDC9 could regulate glioma cell differentiation. During this program, the expression of p53 changes dramatically. The apoptosis, autophagy, and cell differentiation program were blocked by p53 inhibitor treatment. In conclusion, the silencing of TXNDC9 induces apoptosis and autophagy in glioma and promotes cell differentiation by controlling p53 and may function as a new mechanism in glioma.

Multiparametric MR-PET Imaging Predicts Pharmacokinetics and Clinical Response to GDC-0084 in Patients with Recurrent High-Grade Glioma

PURPOSE

GDC-0084 is an oral, brain-penetrant small-molecule inhibitor of PI3K and mTOR. Because these two targets alter tumor vascularity and metabolism, respectively, we hypothesized multiparametric MR-PET could be used to quantify the response, estimate pharmacokinetic (PK) parameters, and predict progression-free survival (PFS) in patients with recurrent malignant gliomas.

PATIENTS AND METHODS

Multiparametric advanced MR-PET imaging was performed to evaluate physiologic response in a first-in-man, multicenter, phase I, dose-escalation study of GDC-0084 (NCT01547546) in 47 patients with recurrent malignant glioma.

RESULTS

Measured maximum concentration (C _max) was associated with a decrease in enhancing tumor volume (P = 0.0287) and an increase in fractional anisotropy (FA; P = 0.0418). Posttreatment tumor volume, ¹⁸F-FDG uptake, K^trans, and relative cerebral blood volume (rCBV) were all correlated with C _max. A linear combination of change in ¹⁸F-FDG PET uptake, apparent diffusion coefficient (ADC), FA, K^trans, v_p, and rCBV was able to estimate both C _max (R² = 0.4113; P < 0.0001) and drug exposure (AUC; R² = 0.3481; P < 0.0001). Using this composite multiparametric MR-PET imaging response biomarker to predict PK, patients with an estimated C _max > 0.1 μmol/L and AUC > 1.25 μmol/L*hour demonstrated significantly longer PFS compared with patients with a lower estimated concentration and exposure (P = 0.0039 and P = 0.0296, respectively).

CONCLUSIONS

Results from this study suggest composite biomarkers created from multiparametric MR-PET imaging targeting metabolic and/or physiologic processes specific to the drug mechanism of action may be useful for subsequent evaluation of treatment efficacy for larger phase II-III studies.

A novel cholchicine/gadolinium-loading tubulin self-assembly nanocarrier for MR imaging and chemotherapy of glioma

To enhance the therapeutic efficiency and reduce side effects from drug delivery and chemotherapy, image-guided nanoscale systems have attracted tremendous attention in recent decades. In this study, we developed a novel method to fabricate a colchicine/gadolinium-loaded tubulin self-assembly nanocarrier (Col-Gd@Tub NC) for the image-guided chemotherapy of glioma. The Col-Gd@Tub NCs were spontaneously formed via tubulin self-assembly and were subsequently functionalized by colchicine and gadolinium elements. These resultant Col-Gd@Tub NCs with a diameter of 45 nm exhibited uniform particle size distribution and favorable stability without any leakage of gadolinium in water. Meanwhile, the introduction of gadolinium endowed Col-Gd@Tub NCs with high T ₁-weighted MRI performance in vitro. After tail vein injection, Col-Gd@Tub NCs exhibited excellent MRI contrast capability and relatively long circulation time (∼12 h) and were finally cleared out from the bladder. More significantly, the binding colchicine still exerted an anti-tumor effect after the Col-Gd@Tub NCs were taken up by the tumor cells. These results show that the Col-Gd@Tub NCs may be served as a versatile nanoscale platform for the integration of biomedical imaging probes and therapeutic molecules for tumor therapy.

Proliferation-dominant high-grade astrocytoma: survival benefit associated with extensive resection of FLAIR abnormality region

OBJECTIVE

The aim of this study was to investigate the relationship between extent of resection (EOR) and survival in terms of clinical, molecular, and radiological factors in high-grade astrocytoma (HGA).

METHODS

Clinical and radiological data from 585 cases of molecularly defined HGA were reviewed. In each case, the EOR was evaluated twice: once according to contrast-enhanced T1-weighted images (CE-T1WI) and once according to fluid attenuated inversion recovery (FLAIR) images. The ratio of the volume of the region of abnormality in CE-T1WI to that in FLAIR images (VFLAIR/VCE-T1WI) was calculated and a receiver operating characteristic curve was used to determine the optimal cutoff value for that ratio. Univariate and multivariate analyses were performed to identify the prognostic value of each factor.

RESULTS

Both the EOR evaluated from CE-T1WI and the EOR evaluated from FLAIR could divide the whole cohort into 4 subgroups with different survival outcomes (p < 0.001). Cases were stratified into 2 subtypes based on VFLAIR/VCE-T1WI with a cutoff of 10: a proliferation-dominant subtype and a diffusion-dominant subtype. Kaplan-Meier analysis showed a significant survival advantage for the proliferation-dominant subtype (p < 0.0001). The prognostic implication has been further confirmed in the Cox proportional hazards model (HR 1.105, 95% CI 1.078-1.134, p < 0.0001). The survival of patients with proliferation-dominant HGA was significantly prolonged in association with extensive resection of the FLAIR abnormality region beyond contrast-enhancing tumor (p = 0.03), while no survival benefit was observed in association with the extensive resection in the diffusion-dominant subtype (p = 0.86).

CONCLUSIONS

VFLAIR/VCE-T1WI is an important classifier that could divide the HGA into 2 subtypes with distinct invasive features. Patients with proliferation-dominant HGA can benefit from extensive resection of the FLAIR abnormality region, which provides the theoretical basis for a personalized resection strategy.

Personalized image-based tumor growth prediction in a convection-diffusion-reaction model

Inter-individual heterogeneity of tumors leads to non-effectiveness of unique therapy plans. This issue has caused a growing interest in the field of personalized medicine and its application in tumor growth evaluation. Accordingly, in this paper, a framework of personalized medicine is presented for growth prediction of brain glioma tumors. A convection-diffusion-reaction model is used as the patient-specific tumor growth model which is associated with multimodal magnetic resonance images (MRIs). Two parameters of intracellular area fraction (ICAF) and metabolic rate have been used to incorporate the physiological data obtained from medical images into the model. The framework is tested on the data of two cases of glioma tumors to document the approach; parameter estimation is made using particle swarm optimization (PSO) and genetic algorithm (GA) and the model is evaluated by comparing the predicted tumors with the observed tumors in terms of root mean square error of the ICAF maps (IRMSE), relative area difference (RAD) and Dice's coefficient (DC). Results show the differences of IRMSE, RAD and DC in 4.1 ∓ 1.15%, 0.099 ∓ 0.041 and 85.5 ∓ 7.5%, respectively. Survival times are estimated by assuming the tumor radius of 35 mm as the fatal burden. Results confirm that less-diffusive tumors lead to higher survival times. The represented framework makes it possible to personally predict the growth behavior of glioma tumors only based on patients' routine MRIs and provides a basis for modeling the personalized therapy and walking in the path of personalized medicine.

Simultaneous FET-PET and contrast-enhanced MRI based on hybrid PET/MR improves delineation of tumor spatial biodistribution in gliomas: a biopsy validation study

Purpose

Glioma treatment planning requires precise tumor delineation, which is typically performed with contrast-enhanced (CE) MRI. However, CE MRI fails to reflect the entire extent of glioma. O-(2-¹⁸F-fluoroethyl)-L-tyrosine (¹⁸F-FET) PET may detect tumor volumes missed by CE MRI. We investigated the clinical value of simultaneous FET-PET and CE MRI in delineating tumor extent before treatment planning. Guided stereotactic biopsy was used to validate the findings.

Methods

Conventional MRI and ¹⁸F-FET PET were performed simultaneously on a hybrid PET/MR in 33 patients with histopathologically confirmed glioma. Tumor volumes were quantified using a tumor-to-brain ratio ≥ 1.6 (V_PET) and a visual threshold (V_CE). We visually assessed abnormal areas on FLAIR images and calculated Dice’s coefficient (DSC), overlap volume (OV), discrepancy-PET, and discrepancy-CE. Additionally, several stereotactic biopsy samples were taken from “matched” or “mismatched” FET-PET and CE MRI regions.

Results

Among 31 patients (93.94%), FET-PET delineated significantly larger tumor volumes than CE MRI (77.84 ± 51.74 cm³ vs. 34.59 ± 27.07 cm³, P < 0.05). Of the 21 biopsy samples obtained from regions with increased FET uptake, all were histopathologically confirmed as glioma tissue or tumor infiltration, whereas only 13 showed enhancement on CE MRI. Among all patients, the spatial similarity between V_PET and V_CE was low (average DSC 0.56 ± 0.22), while the overlap was high (average OV 0.95 ± 0.08). The discrepancy-CE and discrepancy-PET were lower than 10% in 28 and 0 patients, respectively. Eleven patients showed V_PET partially beyond abnormal signal areas on FLAIR images.

Conclusion

The metabolically active biodistribution of gliomas delineated with FET-PET significantly exceeds tumor volume on CE MRI, and histopathology confirms these findings. Our preliminary results indicate that combining the anatomic and molecular information obtained from conventional MRI and FET-PET would reveal a more accurate glioma extent, which is critical for individualized treatment planning.

Electronic supplementary material

The online version of this article (10.1007/s00259-019-04656-2) contains supplementary material, which is available to authorized users.

Recurrent or Refractory High-Grade Gliomas Treated by Convection-Enhanced Delivery of a TGFβ2-Targeting RNA Therapeutic: A Post-Hoc Analysis with Long-Term Follow-Up

Background. OT101 is a first-in-class RNA therapeutic designed to abrogate the immunosuppressive actions of transforming growth factor beta 2 (TGFβ2). Here, we report our post-hoc analysis of the single-agent activity of OT101 in adult patients with recurrent and/or refractory (R/R) high-grade gliomas. Methods. In a Phase 2 clinical trial (ClinicalTrials.gov, NCT00431561), OT101 was administered to 89 R/R high-grade glioma (HGG) (anaplastic astrocytoma/AA: 27; glioblastoma multiforme/GBM: 62) patients with an intratumoral catheter using a convection enhanced delivery (CED) system. Seventy-seven patients (efficacy population; GBM: 51; AA: 26) received at least the intended minimum number of four OT101 treatment cycles. Response determinations were based on central review of magnetic resonance imaging (MRI) scans according to the McDonald criteria. Standard statistical methods were applied for the analysis of data. Findings. Nineteen patients had a complete response (CR) or partial response (PR) following a slow but robust size reduction of their target lesions (median time for 90% reduction of the baseline tumor volume = 11.7 months, range: 4.9-57.7 months). The mean log reduction of the tumor volume was 2.2 ± 0.4 (median = 1.4: range: 0.4-4.5) logs. In addition, seven patients had a stable disease (SD) lasting ≥6 months. For the combined group of 26 AA/GBM patients with favorable responses, the median progression-free survival (PFS) of 1109 days and overall survival (OS) of 1280 days were significantly better than the median PFS (p < 0.00001) and OS (p < 0.00001) of the non-responders among the 89 patients or the 77-patient efficacy population. Conclusion. Intratumorally administered OT101 exhibits clinically meaningful single-agent activity and induces durable CR/PR/SD in R/R HGG patients.

Reliability of intraoperative ultrasound in detecting tumor residual after brain diffuse glioma surgery: a systematic review and meta-analysis

Intraoperative ultrasonography (iUS) is considered an accurate, safe, and cost-effective tool to estimate the extent of resection of both high-grade (HGG) and low-grade (DLGG) diffuse gliomas (DGs). However, it is currently missing an evidence-based assessment of iUS diagnostic accuracy in DGs surgery. The objective of review is to perform a systematic review and meta-analysis of the diagnostic performance of iUS in detecting tumor residue after DGs resection. A comprehensive literature search for studies published through October 2018 was performed according to PRISMA-DTA and STARD 2015 guidelines, using the following algorithm: ("ultrasound" OR "ultrasonography" OR "ultra-so*" OR "echo*" OR "eco*") AND ("brain" OR "nervous") AND ("tumor" OR "tumour" OR "lesion" OR "mass" OR "glio*" OR "GBM") AND ("surgery" OR "surgical" OR "microsurg*" OR "neurosurg*"). Pooled sensitivity, specificity, positive and negative likelihood ratios (LR+ and LR-), and diagnostic odds ratio (DOR) of iUS in DGs were calculated. A subgroup analysis for HGGs and DLGGs was also conducted. Thirteen studies were included in the systematic review (665 DGs). Ten articles (409 DGs) were selected for the meta-analysis with the following results: sensitivity 72.2%, specificity 93.5%, LR- 0.29, LR+ 3, and DOR 9.67. Heterogeneity among studies was non-significant. Subgroup analysis demonstrates a better diagnostic performance of iUS for DLGGs compared with HGGs. iUS is an effective technique in assessing DGs resection. No significant differences are seen regarding iUS modality and transducer characteristics. Its diagnostic performance is higher in DLGGs than HGGs and could be worsened by previous treatments, surgical artifacts, and small tumor residue volumes.

Association between Tumor Acidity and Hypervascularity in Human Gliomas Using pH-Weighted Amine Chemical Exchange Saturation Transfer Echo-Planar Imaging and Dynamic Susceptibility Contrast Perfusion MRI at 3T

BACKGROUND AND PURPOSE

Acidification of the tumor microenvironment from abnormal metabolism along with angiogenesis to meet metabolic demands are both hallmarks of malignant brain tumors; however, the interdependency of tumor acidity and vascularity has not been explored. Therefore, our aim was to investigate the association between pH-sensitive amine chemical exchange saturation transfer echoplanar imaging (CEST-EPI) and relative cerebral blood volume (CBV) measurements obtained from dynamic susceptibility contrast (DSC) perfusion MRI in patients with gliomas.

MATERIALS AND METHODS

In this retrospective study, 90 patients with histologically confirmed gliomas were scanned between 2015 and 2018 (median age, 50.3 years; male/female ratio = 59:31). pH-weighting was obtained using chemical exchange saturation transfer echo-planar imaging estimation of the magnetization transfer ratio asymmetry at 3 ppm, and CBV was estimated using DSC-MR imaging. The voxelwise correlation and patient-wise median value correlation between the magnetization transfer ratio asymmetry at 3 ppm and CBV within T2-hyperintense lesions and contrast-enhancing lesions were evaluated using the Pearson correlation analysis.

RESULTS

General colocalization of elevated perfusion and high acidity was observed in tumors, with local intratumor heterogeneity. For patient-wise analysis, median CBV and magnetization transfer ratio asymmetry at 3 ppm within T2-hyperintense lesions were significantly correlated (R = 0.3180, P = .002), but not in areas of contrast enhancement (P = .52). The positive correlation in T2-hyperintense lesions remained within high-grade gliomas (R = 0.4128, P = .001) and in isocitrate dehydrogenase wild-type gliomas (R = 0.4300, P = .002), but not in World Health Organization II or in isocitrate dehydrogenase mutant tumors. Both magnetization transfer ratio asymmetry at 3 ppm and the voxelwise correlation between magnetization transfer ratio asymmetry and CBV were higher in high-grade gliomas compared with low-grade gliomas in T2-hyperintense tumors (magnetization transfer ratio asymmetry, P = .02; Pearson correlation, P = .01). The same trend held when comparing isocitrate dehydrogenase wild-type gliomas and isocitrate dehydrogenase mutant gliomas (magnetization transfer ratio asymmetry, P = .04; Pearson correlation, P = .01).

CONCLUSIONS

A positive linear correlation between CBV and acidity in areas of T2-hyperintense, nonenhancing tumor, but not enhancing tumor, was observed across patients. Local heterogeneity was observed within individual tumors.

Simultaneous pH-sensitive and oxygen-sensitive MRI of human gliomas at 3 T using multi-echo amine proton chemical exchange saturation transfer spin-and-gradient echo echo-planar imaging (CEST-SAGE-EPI)

PURPOSE

To introduce a new pH-sensitive and oxygen-sensitive MRI technique using amine proton CEST echo spin-and-gradient echo (SAGE) EPI (CEST-SAGE-EPI).

METHODS

pH-weighting was obtained using CEST estimations of magnetization transfer ratio asymmetry (MTRasym ) at 3 ppm, and oxygen-weighting was obtained using R2' measurements. Glutamine concentration, pH, and relaxation rates were varied in phantoms to validate simulations and estimate relaxation rates. The values of MTRasym and R2' in normal-appearing white matter, T2 hyperintensity, contrast enhancement, and macroscopic necrosis were measured in 47 gliomas.

RESULTS

Simulation and phantom results confirmed an increase in MTRasym with decreasing pH. The CEST-SAGE-EPI estimates of R2 , R2*, and R2' varied linearly with gadolinium diethylenetriamine penta-acetic acid concentration (R2  = 6.2 mM-1 ·sec-1 and R2* = 6.9 mM-1 ·sec-1 ). The CEST-SAGE-EPI and Carr-Purcell-Meiboom-Gill estimates of R2 (R2  = 0.9943) and multi-echo gradient-echo estimates of R2* (R2  = 0.9727) were highly correlated. T2 lesions had lower R2' and higher MTRasym compared with normal-appearing white matter, suggesting lower hypoxia and high acidity, whereas contrast-enhancement tumor regions had elevated R2' and MTRasym , indicating high hypoxia and acidity.

CONCLUSION

The CEST-SAGE-EPI technique provides simultaneous pH-sensitive and oxygen-sensitive image contrasts for evaluation of the brain tumor microenvironment. Advantages include fast whole-brain acquisition, in-line B0 correction, and simultaneous estimation of CEST effects, R2 , R2*, and R2' at 3 T.

18F-FDOPA PET and MRI characteristics correlate with degree of malignancy and predict survival in treatment-naïve gliomas: a cross-sectional study

INTRODUCTION

To report the potential value of pre-operative 18F-FDOPA PET and anatomic MRI in diagnosis and prognosis of glioma patients.

METHODS

Forty-five patients with a pathological diagnosis of glioma with pre-operative 18F-FDOPA PET and anatomic MRI were retrospectively examined. The volume of contrast enhancement and T2 hyperintensity on MRI images along with the ratio of maximum 18F-FDOPA SUV in tumor to normal tissue (T/N SUVmax) were measured and used to predict tumor grade, molecular status, and overall survival (OS).

RESULTS

A significant correlation was observed between WHO grade and: the volume of contrast enhancement (r = 0.67), volume of T2 hyperintensity (r = 0.42), and 18F-FDOPA uptake (r = 0.60) (P < 0.01 for each correlation). The volume of contrast enhancement and 18F-FDOPA T/N SUVmax were significantly higher in glioblastoma (WHO IV) compared with lower grade gliomas (WHO I-III), as well as for high-grade gliomas (WHO III-IV) compared with low-grade gliomas (WHO I-II). Receiver-operator characteristic (ROC) analyses confirmed the volume of contrast enhancement and 18F-FDOPA T/N SUVmax could each differentiate patient groups. No significant differences in 18F-FDOPA uptake were observed by IDH or MGMT status. Multivariable Cox regression suggested age (HR 1.16, P = 0.0001) and continuous measures of 18F-FDOPA PET T/N SUVmax (HR 4.43, P = 0.016) were significant prognostic factors for OS in WHO I-IV gliomas.

CONCLUSIONS

Current findings suggest a potential role for the use of pre-operative 18F-FDOPA PET in suspected glioma. Increased 18F-FDOPA uptake may not only predict higher glioma grade, but also worse OS.