Pros and cons of current brain tumor imaging

Artificial intelligence in neuro-oncology: advances and challenges in brain tumor diagnosis, prognosis, and precision treatment

This review delves into the most recent advancements in applying artificial intelligence (AI) within neuro-oncology, specifically emphasizing work on gliomas, a class of brain tumors that represent a significant global health issue. AI has brought transformative innovations to brain tumor management, utilizing imaging, histopathological, and genomic tools for efficient detection, categorization, outcome prediction, and treatment planning. Assessing its influence across all facets of malignant brain tumor management- diagnosis, prognosis, and therapy- AI models outperform human evaluations in terms of accuracy and specificity. Their ability to discern molecular aspects from imaging may reduce reliance on invasive diagnostics and may accelerate the time to molecular diagnoses. The review covers AI techniques, from classical machine learning to deep learning, highlighting current applications and challenges. Promising directions for future research include multimodal data integration, generative AI, large medical language models, precise tumor delineation and characterization, and addressing racial and gender disparities. Adaptive personalized treatment strategies are also emphasized for optimizing clinical outcomes. Ethical, legal, and social implications are discussed, advocating for transparency and fairness in AI integration for neuro-oncology and providing a holistic understanding of its transformative impact on patient care.

A clinically relevant computed tomography (CT) radiomics strategy for intracranial rodent brain tumour monitoring

Here, we establish a CT-radiomics based method for application in invasive, orthotopic rodent brain tumour models. Twenty four NOD/SCID mice were implanted with U87R-Luc2 GBM cells and longitudinally imaged via contrast enhanced (CE-CT) imaging. Pyradiomics was employed to extract CT-radiomic features from the tumour-implanted hemisphere and non-tumour-implanted hemisphere of acquired CT-scans. Inter-correlated features were removed (Spearman correlation > 0.85) and remaining features underwent predictive analysis (recursive feature elimination or Boruta algorithm). An area under the curve of the receiver operating characteristic curve was implemented to evaluate radiomic features for their capacity to predict defined outcomes. Firstly, we identified a subset of radiomic features which distinguish the tumour-implanted hemisphere and non- tumour-implanted hemisphere (i.e, tumour presence from normal tissue). Secondly, we successfully translate preclinical CT-radiomic pipelines to GBM patient CT scans (n = 10), identifying similar trends in tumour-specific feature intensities (E.g. 'glszm Zone Entropy'), thereby suggesting a mouse-to-human species conservation (a conservation of radiomic features across species). Thirdly, comparison of features across timepoints identify features which support preclinical tumour detection earlier than is possible by visual assessment of CT scans. This work establishes robust, preclinical CT-radiomic pipelines and describes the application of CE-CT for in-depth orthotopic brain tumour monitoring. Overall we provide evidence for the role of pre-clinical 'discovery' radiomics in the neuro-oncology space.

Preclinical Application of CEST MRI to Detect Early and Regional Tumor Response to Local Brain Tumor Treatment

Treating glioblastoma and monitoring treatment response non-invasively remain challenging. Here, we developed a robust approach using a drug-loaded liposomal hydrogel that is mechanically compatible with the brain, and, simultaneously, we successfully monitored early tumor response using Chemical Exchange Saturation Transfer (CEST) MRI. This CEST-detectable liposomal hydrogel was optimized based on a sustainable drug release and a soft hydrogel for the brain tumor, which is unfavorable for tumor cell proliferation. After injecting the hydrogel next to the tumor, three distinctive CEST contrasts enabled the monitoring of tumor response and drug release longitudinally at 3T. As a result, a continuous tumor volume decrease was observed in the treatment group along with a significant decrease in CEST contrasts relating to the tumor response at 3.5 ppm (Amide Proton Transfer; APT) and at -3.5 ppm (relayed Nuclear Overhauser Effect; rNOE) when compared to the control group (p < 0.05). Interestingly, the molecular change at 3.5 ppm on day 3 (p < 0.05) was found to be prior to the significant decrease in tumor volume on day 5. An APT signal also showed a strong correlation with the number of proliferating cells in the tumors. This demonstrated that APT detected a distinctive decrease in mobile proteins and peptides in tumors before the change in tumor morphology. Moreover, the APT signal showed a regional response to the treatment, associated with proliferating and apoptotic cells, which allowed an in-depth evaluation and prediction of the tumor treatment response. This newly developed liposomal hydrogel allows image-guided brain tumor treatment to address clinical needs using CEST MRI.

Undetected pseudoprogressions in the CeTeG/NOA-09 trial: hints from postprogression survival and MRI analyses

PURPOSE

In the randomized CeTeG/NOA-09 trial, lomustine/temozolomide (CCNU/TMZ) was superior to TMZ therapy regarding overall survival (OS) in MGMT promotor-methylated glioblastoma. Progression-free survival (PFS) and pseudoprogression rates (about 10%) were similar in both arms. Further evaluating this discrepancy, we analyzed patterns of postprogression survival (PPS) and MRI features at first progression according to modified RANO criteria (mRANO).

METHODS

We classified the patients of the CeTeG/NOA-09 trial according to long vs. short PPS employing a cut-off of 18 months and compared baseline characteristics and survival times. In patients with available MRIs and confirmed progression, the increase in T1-enhancing, FLAIR hyperintense lesion volume and the change in ADC mean value of contrast-enhancing tumor upon progression were determined.

RESULTS

Patients with long PPS in the CCNU/TMZ arm had a particularly short PFS (5.6 months). PFS in this subgroup was shorter than in the long PPS subgroup of the TMZ arm (11.1 months, p = 0.01). At mRANO-defined progression, patients of the CCNU/TMZ long PPS subgroup had a significantly higher increase of mean ADC values (p = 0.015) and a tendency to a stronger volumetric increase in T1-enhancement (p = 0.22) as compared to long PPS patients of the TMZ arm.

CONCLUSION

The combination of survival and MRI analyses identified a subgroup of CCNU/TMZ-treated patients with features that sets them apart from other patients in the trial: short first PFS despite long PPS and significant increase in mean ADC values upon mRANO-defined progression. The observed pattern is compatible with the features commonly observed in pseudoprogression suggesting mRANO-undetected pseudoprogressions in the CCNU/TMZ arm of CeTeG/NOA-09.

Taming Glioblastoma in "Real Time": Integrating Multimodal Advanced Neuroimaging/AI Tools Towards Creating a Robust and Therapy Agnostic Model for Response Assessment in Neuro-Oncology

The highly aggressive nature of glioblastoma carries a dismal prognosis despite aggressive multimodal therapy. Alternative treatment regimens, such as immunotherapies, are known to intensify the inflammatory response in the treatment field. Follow-up imaging in these scenarios often mimics disease progression on conventional MRI, making accurate evaluation extremely challenging. To this end, revised criteria for assessment of treatment response in high-grade gliomas were successfully proposed by the RANO Working Group to distinguish pseudoprogression from true progression, with intrinsic constraints related to the postcontrast T1-weighted MRI sequence. To address these existing limitations, our group proposes a more objective and quantifiable "treatment agnostic" model, integrating into the RANO criteria advanced multimodal neuroimaging techniques, such as diffusion tensor imaging (DTI), dynamic susceptibility contrast-perfusion weighted imaging (DSC-PWI), dynamic contrast enhanced (DCE)-MRI, MR spectroscopy, and amino acid-based positron emission tomography (PET) imaging tracers, along with artificial intelligence (AI) tools (radiomics, radiogenomics, and radiopathomics) and molecular information to address this complex issue of treatment-related changes versus tumor progression in "real-time", particularly in the early posttreatment window. Our perspective delineates the potential of incorporating multimodal neuroimaging techniques to improve consistency and automation for the assessment of early treatment response in neuro-oncology.

Comprehensive Brain Tumour Characterisation with VERDICT-MRI: Evaluation of Cellular and Vascular Measures Validated by Histology

The aim of this work was to extend the VERDICT-MRI framework for modelling brain tumours, enabling comprehensive characterisation of both intra- and peritumoural areas with a particular focus on cellular and vascular features. Diffusion MRI data were acquired with multiple b-values (ranging from 50 to 3500 s/mm2), diffusion times, and echo times in 21 patients with brain tumours of different types and with a wide range of cellular and vascular features. We fitted a selection of diffusion models that resulted from the combination of different types of intracellular, extracellular, and vascular compartments to the signal. We compared the models using criteria for parsimony while aiming at good characterisation of all of the key histological brain tumour components. Finally, we evaluated the parameters of the best-performing model in the differentiation of tumour histotypes, using ADC (Apparent Diffusion Coefficient) as a clinical standard reference, and compared them to histopathology and relevant perfusion MRI metrics. The best-performing model for VERDICT in brain tumours was a three-compartment model accounting for anisotropically hindered and isotropically restricted diffusion and isotropic pseudo-diffusion. VERDICT metrics were compatible with the histological appearance of low-grade gliomas and metastases and reflected differences found by histopathology between multiple biopsy samples within tumours. The comparison between histotypes showed that both the intracellular and vascular fractions tended to be higher in tumours with high cellularity (glioblastoma and metastasis), and quantitative analysis showed a trend toward higher values of the intracellular fraction (fic) within the tumour core with increasing glioma grade. We also observed a trend towards a higher free water fraction in vasogenic oedemas around metastases compared to infiltrative oedemas around glioblastomas and WHO 3 gliomas as well as the periphery of low-grade gliomas. In conclusion, we developed and evaluated a multi-compartment diffusion MRI model for brain tumours based on the VERDICT framework, which showed agreement between non-invasive microstructural estimates and histology and encouraging trends for the differentiation of tumour types and sub-regions.

Assessment and prediction of glioblastoma therapy response: challenges and opportunities

Glioblastoma is the most aggressive type of primary adult brain tumour. The median survival of patients with glioblastoma remains approximately 15 months, and the 5-year survival rate is <10%. Current treatment options are limited, and the standard of care has remained relatively constant since 2011. Over the last decade, a range of different treatment regimens have been investigated with very limited success. Tumour recurrence is almost inevitable with the current treatment strategies, as glioblastoma tumours are highly heterogeneous and invasive. Additionally, another challenging issue facing patients with glioblastoma is how to distinguish between tumour progression and treatment effects, especially when relying on routine diagnostic imaging techniques in the clinic. The specificity of routine imaging for identifying tumour progression early or in a timely manner is poor due to the appearance similarity of post-treatment effects. Here, we concisely describe the current status and challenges in the assessment and early prediction of therapy response and the early detection of tumour progression or recurrence. We also summarize and discuss studies of advanced approaches such as quantitative imaging, liquid biomarker discovery and machine intelligence that hold exceptional potential to aid in the therapy monitoring of this malignancy and early prediction of therapy response, which may decisively transform the conventional detection methods in the era of precision medicine.

Advanced Imaging Techniques for Radiotherapy Planning of Gliomas

The accuracy of target delineation in radiation treatment (RT) planning of cerebral gliomas is crucial to achieve high tumor control, while minimizing treatment-related toxicity. Conventional magnetic resonance imaging (MRI), including contrast-enhanced T1-weighted and fluid-attenuated inversion recovery (FLAIR) sequences, represents the current standard imaging modality for target volume delineation of gliomas. However, conventional sequences have limited capability to discriminate treatment-related changes from viable tumors, owing to the low specificity of increased blood-brain barrier permeability and peritumoral edema. Advanced physiology-based MRI techniques, such as MR spectroscopy, diffusion MRI and perfusion MRI, have been developed for the biological characterization of gliomas and may circumvent these limitations, providing additional metabolic, structural, and hemodynamic information for treatment planning and monitoring. Radionuclide imaging techniques, such as positron emission tomography (PET) with amino acid radiopharmaceuticals, are also increasingly used in the workup of primary brain tumors, and their integration in RT planning is being evaluated in specialized centers. This review focuses on the basic principles and clinical results of advanced MRI and PET imaging techniques that have promise as a complement to RT planning of gliomas.

An Integrated Bioinformatics Study of a Novel Niclosamide Derivative, NSC765689, a Potential GSK3β/β-Catenin/STAT3/CD44 Suppressor with Anti-Glioblastoma Properties

Despite management efforts with standard surgery, radiation, and chemotherapy, glioblastoma multiform (GBM) remains resistant to treatment, which leads to tumor recurrence due to glioma stem cells (GSCs) and therapy resistance. In this study, we used random computer-based prediction and target identification to assess activities of our newly synthesized niclosamide-derived compound, NSC765689, to target GBM oncogenic signaling. Using target prediction analyses, we identified glycogen synthase kinase 3β (GSK3β), β-Catenin, signal transducer and activator of transcription 3 (STAT3), and cluster of differentiation 44 (CD44) as potential druggable candidates of NSC765689. The above-mentioned signaling pathways were also predicted to be overexpressed in GBM tumor samples compared to adjacent normal samples. In addition, using bioinformatics tools, we also identified microRNA (miR)-135b as one of the most suppressed microRNAs in GBM samples, which was reported to be upregulated through inhibition of GSK3β, and subsequently suppresses GBM tumorigenic properties and stemness. We further performed in silico molecular docking of NSC765689 with GBM oncogenes; GSK3β, β-Catenin, and STAT3, and the stem cell marker, CD44, to predict protein-ligand interactions. The results indicated that NSC765689 exhibited stronger binding affinities compared to its predecessor, LCC09, which was recently published by our laboratory, and was proven to inhibit GBM stemness and resistance. Moreover, we used available US National Cancer Institute (NCI) 60 human tumor cell lines to screen in vitro anticancer effects, including the anti-proliferative and cytotoxic activities of NSC765689 against GBM cells, and 50% cell growth inhibition (GI₅₀) values ranged 0.23~5.13 μM. In summary, using computer-based predictions and target identification revealed that NSC765689 may be a potential pharmacological lead compound which can regulate GBM oncogene (GSK3β/β-Catenin/STAT3/CD44) signaling and upregulate the miR-135b tumor suppressor. Therefore, further in vitro and in vivo investigations will be performed to validate the efficacy of NSC765689 as a novel potential GBM therapeutic.

Association of plasma cell-free DNA with survival in patients with IDH wild-type glioblastoma

BACKGROUND

We aimed to determine whether plasma cell-free DNA (cfDNA) concentration is associated with survival in patients with isocitrate dehydrogenase (IDH) wild-type glioblastoma (GBM).

METHODS

Pre-operative and post-chemoradiotherapy blood samples were prospectively collected from patients with newly diagnosed IDH wild-type GBM. Patients underwent surgical resection or biopsy and received adjuvant radiotherapy with concomitant temozolomide. Cell-free DNA (cfDNA) was isolated from plasma and quantified using SYBR Green-based q polymerase chain reaction (qPCR).

RESULTS

Sixty-two patients were enrolled and categorized into high vs. low cfDNA groups relative to the pre-operative median value (25.2 ng/mL, range 5.7-153.0 ng/mL). High pre-operative cfDNA concentration was associated with inferior PFS (median progression-free survival (PFS), 3.4 vs. 7.7 months; log-rank P = .004; hazard ratio [HR], 2.19; 95% CI, 1.26-3.81) and overall survival (OS) (median OS, 8.0 vs. 13.9 months; log-rank P = .01; HR, 2.43; 95% CI, 1.19-4.95). After adjusting for risk factors, including O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status, pre-operative cfDNA remained independently associated with PFS (HR, 2.70; 95% CI, 1.50-4.83; P = .001) and OS (HR, 2.65; 95% CI, 1.25-5.59; P = .01). Post-hoc analysis of change in cfDNA post-chemoradiotherapy compared to pre-surgery (n = 24) showed increasing cfDNA concentration was associated with worse PFS (median, 2.7 vs. 6.0 months; log-rank P = .003; HR, 4.92; 95% CI, 1.53-15.84) and OS (median, 3.9 vs. 19.4 months; log-rank P < .001; HR, 7.77; 95% CI, 2.17-27.76).

CONCLUSIONS

cfDNA concentration is a promising prognostic biomarker for patients with IDH wild-type GBM. Plasma cfDNA can be obtained noninvasively and may enable more accurate estimates of survival and effective clinical trial stratification.

Pseudoprogression versus true progression in glioblastoma patients: A multiapproach literature review: Part 1 - Molecular, morphological and clinical features

With new therapeutic protocols, more patients treated for glioblastoma have experienced a suspicious radiologic image of progression (pseudoprogression) during follow-up. Pseudoprogression should be differentiated from true progression because the disease management is completely different. In the case of pseudoprogression, the follow-up continues, and the patient is considered stable. In the case of true progression, a treatment adjustment is necessary. Presently, a pseudoprogression diagnosis certainly needs to be pathologically confirmed. Some important efforts in the radiological, histopathological, and genomic fields have been made to differentiate pseudoprogression from true progression, and the assessment of response criteria exists but remains limited. The aim of this paper is to highlight clinical and pathological markers to differentiate pseudoprogression from true progression through a literature review.

Liquid Biopsy Strategies to Distinguish Progression from Pseudoprogression and Radiation Necrosis in Glioblastomas

Liquid biopsy for the detection and monitoring of central nervous system tumors is of significant clinical interest. At initial diagnosis, the majority of patients with central nervous system tumors undergo magnetic resonance imaging (MRI), followed by invasive brain biopsy to determine the molecular diagnosis of the WHO 2016 classification paradigm. Despite the importance of MRI for long-term treatment monitoring, in the majority of patients who receive chemoradiation therapy for glioblastoma, it can be challenging to distinguish between radiation treatment effects including pseudoprogression, radiation necrosis, and recurrent/progressive disease based on imaging alone. Tissue biopsy-based monitoring is high risk and not always feasible. However, distinguishing these entities is of critical importance for the management of patients and can significantly affect survival. Liquid biopsy strategies including circulating tumor cells, circulating free DNA, and extracellular vesicles have the potential to afford significant useful molecular information at both the stage of diagnosis and monitoring for these tumors. Here, current liquid biopsy-based approaches in the context of tumor monitoring to differentiate progressive disease from pseudoprogression and radiation necrosis are reviewed.

Advanced magnetic resonance imaging to support clinical drug development for malignant glioma

Even though the treatment options and survival of patients with glioblastoma multiforme (GBM), the most common type of malignant glioma, have improved over the past decade, there is still a high unmet medical need to develop novel therapies. Complexity in pathology and therapy require biomarkers to characterize tumors, to define malignant and active areas, to assess disease prognosis, and to quantify and monitor therapy response. While conventional magnetic resonance imaging (MRI) techniques have improved these assessments, limitations remain. In this review, we evaluate the role of various non-invasive biomarkers based on advanced structural and functional MRI techniques in the context of GBM drug development over the past 5 years.

Predicting Survival in Glioblastoma Patients Using Diffusion MR Imaging Metrics-A Systematic Review

Simple Summary

An accurate survival analysis is crucial for disease management in glioblastoma (GBM) patients. Due to the ability of the diffusion MRI techniques of providing a quantitative assessment of GBM tumours, an ever-growing number of studies aimed at investigating the role of diffusion MRI metrics in survival prediction of GBM patients. Since the role of diffusion MRI in prediction and evaluation of survival outcomes has not been fully addressed and results are often controversial or unsatisfactory, we performed this systematic review in order to collect, summarize and evaluate all studies evaluating the role of diffusion MRI metrics in predicting survival in GBM patients. We found that quantitative diffusion MRI metrics provide useful information for predicting survival outcomes in GBM patients, mainly in combination with other clinical and multimodality imaging parameters.

Abstract

Despite advances in surgical and medical treatment of glioblastoma (GBM), the medium survival is about 15 months and varies significantly, with occasional longer survivors and individuals whose tumours show a significant response to therapy with respect to others. Diffusion MRI can provide a quantitative assessment of the intratumoral heterogeneity of GBM infiltration, which is of clinical significance for targeted surgery and therapy, and aimed at improving GBM patient survival. So, the aim of this systematic review is to assess the role of diffusion MRI metrics in predicting survival of patients with GBM. According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, a systematic literature search was performed to identify original articles since 2010 that evaluated the association of diffusion MRI metrics with overall survival (OS) and progression-free survival (PFS). The quality of the included studies was evaluated using the QUIPS tool. A total of 52 articles were selected. The most examined metrics were associated with the standard Diffusion Weighted Imaging (DWI) (34 studies) and Diffusion Tensor Imaging (DTI) models (17 studies). Our findings showed that quantitative diffusion MRI metrics provide useful information for predicting survival outcomes in GBM patients, mainly in combination with other clinical and multimodality imaging parameters.

Efficiency of High and Standard b Value Diffusion-Weighted Magnetic Resonance Imaging in Grading of Gliomas

Background

Glioma is the most common fatal malignant tumor of the CNS. Early detection of glioma grades based on diffusion-weighted imaging (DWI) properties is considered one of the most recent noninvasive promising tools in the assessment of glioma grade and could be helpful in monitoring patient prognosis and response to therapy.

Aim

This study aimed to investigate the accuracy of DWI at both standard and high b values (b = 1000 s/mm² and b = 3000 s/mm²) to distinguish high-grade glioma (HGG) from low-grade glioma (LGG) in clinical practice based on histopathological results.

Materials and Methods

Twenty-three patients with glioma had DWI at l.5 T MR using two different b values (b = 1000 s/mm² and b = 3000 s/mm²) at Al-Shifa Medical Complex after obtaining ethical and administrative approvals, and data were collected from March 2019 to March 2020. Minimum, maximum, and mean of apparent diffusion coefficient (ADC) values were measured through drawing region of interest (ROI) on a solid part at ADC maps. Data were analyzed by using the MedCalc analysis program, version 19.0.4, receiver operating characteristic (ROC) curve analysis was done, and optimal cutoff values for grading gliomas were determined. Sensitivity and specificity were also calculated.

Results

The obtained results showed the ADC_mean, ADC_ratio, ADC_max, and ADC_min were performed to differentiate between LGG and HGG at both standard and high b values. Moreover, ADC values were inversely proportional to glioma grade, and these differences are more obvious at high b value. Minimum ADC values using standard b value were 1.13 ± 0.17 × 10⁻³ mm²/s, 0.89 ± 0.85 × 10⁻³ mm²/s, and 0.82 ± 0.17 × 10⁻³ mm²/s for grades II, III, and IV, respectively. Concerning high b value, ADC_min values were 0.76 ± 0.07 × 10⁻³ mm²/s, 0.61 ± 0.01 × 10⁻³ mm²/s, and 0.48 ± 0.07 × 10⁻³ mm²/s for grades II, III, and IV, respectively. ADC values were inversely correlated with results of glioma grades, and the correlation was stronger at ADC₃₀₀₀ (r = −0.722, P ≤ 0.001). The ADC₃₀₀₀ achieved the highest diagnostic accuracy with an area under the curve (AUC) of 0.618, 100% sensitivity, 85.7% specificity, and 85.7% accuracy for glioma grading at a cutoff point of ≤0.618 × 10⁻³ mm²/s. The high b value showed stronger agreement with histopathology compared with standard b value results (k = 0.89 and 0.79), respectively.

Conclusion

The ADC values decrease with an increase in tumor cellularity. Meanwhile, high b value provides better tissue contrast by reflecting more tissue diffusivity. Therefore, ADC-derived parameters at high b value are more useful in the grading of glioma than those obtained at standard b value. They might be a better surrogate imaging sequence in the preoperative evaluation of gliomas.

Glioblastoma Recurrence Versus Treatment Effect in a Pathology-Documented Series

OBJECTIVE

Patients diagnosed with glioblastoma (GBM) are treated with surgery followed by fractionated radiotherapy with concurrent and adjuvant temozolomide. Patients are monitored with serial magnetic resonance imaging (MRI). However, treatment-related changes frequently mimic disease progression. We reviewed a series of patients undergoing surgery for presumed first-recurrence GBM, where pathology reports were available for tissue diagnosis, in order to better understand factors associated with a diagnosis of treatment-related changes on final pathology.

METHODS

Patient records at a single institution between 2005 and 2015 were retrospectively reviewed. Pathology reports were reviewed to determine diagnosis of recurrent GBM or treatment effect. Survival analysis was performed interrogating overall survival (OS) and progression-free survival (PFS). Correlation with radiation treatment plans was also examined.

RESULTS

One-hundred-twenty-three patients were identified. One-hundred-sixteen patients (94%) underwent resection and seven underwent biopsy. Treatment-related changes were reported in 20 cases (16%). These patients had longer median OS and PFS from the time of recurrence than patients with true disease progression. However, there was no significant difference in OS from the time of initial diagnosis. Treatment effect was associated with surgery within 90 days of completing radiation. In patients receiving radiation at our institution (n = 53), larger radiation target volume and a higher maximum dose were associated with treatment effect.

CONCLUSION

Treatment effect was associated with surgery nearer to completion of radiation, a larger radiation target volume, and a higher maximum point dose. Treatment effect was associated with longer PFS and OS from the time of recurrence, but not from the time of initial diagnosis.

Isocitrate dehydrogenase 1 mutant glioblastomas demonstrate a decreased rate of pseudoprogression: a multi-institutional experience

BACKGROUND

Pseudoprogression (psPD) represents false radiologic evidence of tumor progression and is observed in some glioblastoma (GBM) patients after postoperative chemoradiation (CRT) with temozolomide (TMZ). The ambiguity of the psPD diagnosis confounds identification of true progression and may lead to unnecessary interventions. The association between psPD and isocitrate dehydrogenase 1 (IDH1) mutational (mut) status is understudied, and its incidence may alter clinical decision making.

METHODS

We retrospectively evaluated 120 patients with IDH1-mut (n = 60) and IDH1-wild-type (IDH-WT; [n = 60]) GBMs who received postoperative CRT with TMZ at 4 academic institutions. Response Assessment in Neuro-Oncology criteria were used to identify psPD rates in routine brain MRIs performed up to 90 days after CRT completion.

RESULTS

Within 90 days of completing CRT, 9 GBM patients (1 [1.7%] IDH1-mut and 8 [13.3%] IDH1-WTs) demonstrated true progression, whereas 17 patients (3 [5%] IDH1-muts and 14 [23.3%] IDH1-WTs) demonstrated psPD (P  =  .004). IDH1-mut GBMs had a lower probability of psPD (hazard ratio: 0.173, 95% CI, 0.047-0.638, P = .008). Among the patients with radiologic signs suggestive of progression (n = 26), psPD was found to be the cause in 3 of 4 (75.0%) of the IDH1-mut GBMs and 14 of 22 (63.6%) of the IDH1-WT GBMs (P = .496). Median overall survival for IDH1-mut and IDH1-WT GBM patients was 40.3 and 23.0 months, respectively (P  < .001).

CONCLUSIONS

IDH1-mut GBM patients demonstrate lower absolute rates of psPD expression. Irrespective of GBM subtype, psPD expression was more likely than true progression within 90 days of completing CRT. Continuing adjuvant treatment for IDH1-mut GBMs is suggested if radiologic progression is suspected during this time interval.

Preparation of Cholera Toxin Subunit B Functionalized Nanoparticles for Targeted Therapy of Glioblastoma

Cholera toxin subunit B (CTB) is the nontoxic moiety of cholera toxin. It can target the glycosphingolipid GM1 expressed in the blood-brain barrier (BBB), neovasculature, and glioblastoma cells. Thus, CTB has been utilized as a multifunctional molecule for targeted therapy of glioblastoma. Here, we describe a detailed method for preparation of CTB functionalized paclitaxel (PTX)-loaded poly (lactic-co-glycolic acid) (PLGA) nanoparticles. This unique modification can guide nanoparticles across the BBB and target glioblastoma cells. The characterization of nanoparticles such as size, zeta potential, morphology, drug loading, and encapsulation efficiency is shown in this chapter.

Post-chemoradiation volumetric response predicts survival in newly diagnosed glioblastoma treated with radiation, temozolomide, and bevacizumab or placebo

Background

In the current study we used contrast-enhanced T1 subtraction maps to test whether early changes in enhancing tumor volume are prognostic for overall survival (OS) in newly diagnosed glioblastoma (GBM) patients treated with chemoradiation with or without bevacizumab (BV).

Methods

Seven hundred ninety-eight patients (404 BV and 394 placebo) with newly diagnosed GBM in the AVAglio trial (NCT00943826) had baseline MRI scans available, while 337 BV-treated and 269 placebo-treated patients had >4 MRI scans for response evaluation. The volume of contrast-enhancing tumor was quantified and used for subsequent analyses.

Results

A decrease in tumor volume during chemoradiation was associated with a longer OS in the placebo group (hazard ratio [HR] = 1.578, P < 0.0001) but not BV-treated group (HR = 1.135, P = 0.4889). Results showed a higher OS in patients on the placebo arm with a sustained decrease in tumor volume using a post-chemoradiation baseline (HR = 1.692, P = 0.0005), and a trend toward longer OS was seen in BV-treated patients (HR = 1.264, P = 0.0724). Multivariable Cox regression confirmed that sustained response or stable disease was prognostic for OS (HR = 0.7509, P = 0.0127) when accounting for age (P = 0.0002), KPS (P = 0.1516), postsurgical tumor volume (P < 0.0001), O6-methylguanine-DNA methyltransferase status (P < 0.0001), and treatment type (P = 0.7637) using the post-chemoradiation baseline.

Conclusions

The post-chemoradiation timepoint is a better baseline for evaluating efficacy in newly diagnosed GBM. Early progression during the maintenance phase is consequential in predicting OS, supporting the use of progression-free survival rates as a meaningful surrogate for GBM.

A study of the focal adhesion kinase inhibitor GSK2256098 in patients with recurrent glioblastoma with evaluation of tumor penetration of [11C]GSK2256098

Background

GSK2256098 is a novel oral focal adhesion kinase (FAK) inhibitor. Preclinical studies demonstrate growth inhibition in glioblastoma cell lines. However, rodent studies indicate limited blood-brain barrier (BBB) penetration. In this expansion cohort within a phase I study, the safety, tolerability, pharmacokinetics (PK), and clinical activity of GSK2256098 were evaluated in patients with recurrent glioblastoma. Biodistribution and kinetics of [11C]GSK2256098 were assessed in a substudy using positron-emission tomography (PET).

Methods

Patients were treated with GSK2256098 until disease progression or withdrawal due to adverse events (AEs). Serial PK samples were collected on day 1. On a single day between days 9 and 20, patients received a microdose of intravenous [11C]GSK2256098 and were scanned with PET over 90 minutes with parallel PK sample collection. Response was assessed by MRI every 6 weeks.

Results

Thirteen patients were treated in 3 dose cohorts (1000 mg, 750 mg, 500 mg; all dosed twice daily). The maximum tolerated dose was 1000 mg twice daily. Dose-limiting toxicities were related to cerebral edema. Treatment-related AEs (>25%) were diarrhea, fatigue, and nausea. Eight patients participated in the PET substudy, with [11C]GSK2256098 VT (volume of distribution) estimates of 0.9 in tumor tissue, 0.5 in surrounding T2 enhancing areas, and 0.4 in normal brain. Best response of stable disease was observed in 3 patients, including 1 patient on treatment for 11.3 months.

Conclusions

GSK2256098 was tolerable in patients with relapsed glioblastoma. GSK2256098 crossed the BBB at low levels into normal brain, but at markedly higher levels into tumor, consistent with tumor-associated BBB disruption. Additional clinical trials of GSK2256098 are ongoing.

Noninvasive O6 Methylguanine-DNA Methyltransferase Status Prediction in Glioblastoma Multiforme Cancer Using Magnetic Resonance Imaging Radiomics Features: Univariate and Multivariate Radiogenomics Analysis

BACKGROUND

This study aimed to predict methylation status of the O₆ methylguanine-DNA methyltransferase (MGMT) gene promoter status by using magnetic resonance imaging radiomics features, as well as univariate and multivariate analysis.

METHODS

Eighty-two patients who had an MGMT methylation status were included in this study. Tumors were manually segmented in the 4 regions of magnetic resonance images, 1) whole tumor, 2) active/enhanced region, 3) necrotic regions, and 4) edema regions. About 7000 radiomics features were extracted for each patient. Feature selection and classifier were used to predict MGMT status through different machine learning algorithms. The area under the curve (AUC) of the receiver operating characteristic curve was used for model evaluations.

RESULTS

Regarding univariate analysis, the Inverse Variance feature From Gray Level Co-occurrence Matrix in whole tumor segment with 4.5 mm Sigma of Laplacian of Gaussian filter with AUC of 0.71 (P value = 0.002) was found to be the best predictor. For multivariate analysis, the Decision Tree classifier with Select from Model feature selector and LOG (Laplacian of Gaussian) filter in edema region had the highest performance (AUC, 0.78), followed by Ada-Boost classifier with Select from Model feature selector and LOG filter in edema region (AUC, 0.74).

CONCLUSIONS

This study showed that radiomics using machine learning algorithms is a feasible noninvasive approach to predict MGMT methylation status in patients with glioblastoma multiforme cancer.

Evaluation of tumor response to antiangiogenic therapy in patients with recurrent gliomas using contrast-enhanced perfusion-weighted magnetic resonance imaging techniques: A meta-analysis

BACKGROUND

It is of vital importance to find radiologic biomarkers that can accurately predict treatment response. Usually, the initiation of antiangiogenic therapy causes a rapid decrease in the contrast enhancing tumor. However, the treatment response is observed only in a fraction of patients due to the partial radiological response secondary to stabilization of abnormal vessels which does not essentially indicate a true antitumor effect. Perfusion-weighted magnetic resonance imaging (PW-MRI) techniques have shown implicitness as a strong imaging biomarker for gliomas since they give hemodynamic information of blood vessels. Hence, there is a rapid expansion of PW-MRI related studies and clinical applications.

AIM

To determine the diagnostic performance of PW-MRI techniques including: (A) dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI); and (B) dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) for evaluating response to antiangiogenic therapy in patients with recurrent gliomas.

METHODS

Databases such as PubMed (MEDLINE included), EMBASE, and Google Scholar were searched for relevant original articles. The included studies were assessed for methodological quality with the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Medical imaging follow-up or histopathological analysis was used as the reference standard. The data were extracted by two reviewers independently, and then the sensitivity, specificity, summary receiver operating characteristic curve, area under the curve (AUC), and heterogeneity were calculated using Meta-Disc 1.4 software.

RESULTS

This study analyzed a total of six articles. The overall sensitivity for DCE-MRI and DSC-MRI was 0.69 [95% confidence interval (CI): 0.53-0.82], and the specificity was 0.99 (95%CI: 0.93-1) by a random effects model (DerSimonianee-Laird model). The likelihood ratio (LR) +, LR-, and diagnostic odds ratio (DOR) were 12.84 (4.54-36.28), 0.35 (0.22-0.53), and 24.44 (7.19-83.06), respectively. The AUC (± SE) was 0.9921 (± 0.0120), and the Q* index (± SE) was 0.9640 (± 0.0323). For DSC-MRI, the sensitivity was 0.73, the specificity was 0.98, the LR+ was 7.82, the LR- was 0.32, the DOR was 31.65, the AUC (± SE) was 0.9925 (± 0.0132), and the Q* index was 0.9649 (± 0.0363). For DCE-MRI, the sensitivity was 0.41, the specificity was 0.97, the LR+ was 5.34, the LR- was 0.71, the DOR was 8.76, the AUC (± SE) was 0.9922 (± 0.2218), and the Q* index was 0.8935 (± 0.3037).

CONCLUSION

This meta-analysis demonstrated a beneficial value of PW-MRI (DSC-MRI and DCE-MRI) in monitoring the response of recurrent gliomas to antiangiogenic therapy, with reasonable sensitivity, specificity, +LR, and -LR.

Enhanced Glioblastoma Targeting Ability of Carfilzomib Enabled by a DA7R-Modified Lipid Nanodisk

The robust proliferation of tumors relies on a rich neovasculature for nutrient supplies. Therefore, a basic strategy of tumor targeting therapy should include not only killing regular cancer cells but also blocking tumor neovasculature. D-peptide ^DA7R, which was previously reported to specifically bind vascular endothelial growth factor receptor 2 (VEGFR2) and neuropilin-1 (NRP-1), could achieve the goal of multitarget recognition. Accordingly, the main purposes of this work were to establish a carfilzomib-loaded lipid nanodisk modified with multifunctional peptide ^DA7R (^DA7R-ND/CFZ) and to evaluate its anti-glioblastoma efficacy in vitro and in vivo. It is testified that the ^DA7R peptide-conjugated lipid nanodisk can be specifically taken up by U87MG cells and HUVECs. Furthermore, ^DA7R-ND demonstrated a more enhanced penetration than that of the nonmodified formulation on the tumor spheroid model in vitro and more tumor region accumulation in vivo on the subcutaneous and intracranial tumor-bearing nude mice model. ^DA7R-ND was shown to co-localize with tumor neovasculature in vivo. When loaded with proteasome inhibitor carfilzomib, the ^DA7R-decorated nanodisk could remarkably suppress tumor proliferation, extend survival time of nude mice bearing an intracranial tumor, and inhibit neovasculature formation with an efficacy higher than that of the nonmodified nanodisk in vitro and in vivo. The present study verified that the heptapeptide ^DA7R-conjugated nanodisk is a promising nanocarrier for glioblastoma targeting therapy.

Analysis of pseudoprogression after proton or photon therapy of 99 patients with low grade and anaplastic glioma

•

No difference in pseudoprogression rate six months after proton or photon therapy.

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Oligodendrogliomas develop pseudoprogression sooner after protons vs. photons.

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Astrocytomas develop pseudoprogression at similar time after protons vs. photons.

Background and purpose

Proton therapy is increasingly used to treat primary brain tumors. There is concern for higher rates of pseudoprogression (PsP) after protons compared to photons. The purposes of this study are to compare the rate of PsP after proton vs. photon therapy for grade II and III gliomas and to identify factors associated with the development of PsP.

Materials and methods

Ninety-nine patients age >18 years with grade II or III glioma treated with photons or protons were retrospectively reviewed. Demographic data, IDH and 1p19q status, and treatment factors were analyzed for association with PsP, progression free survival (PFS), and overall survival (OS).

Results

Sixty-five patients were treated with photons and 34 with protons. Among those with oligodendroglioma, PsP developed in 6/42 photon-treated patients (14.3%) and 4/25 proton-treated patients (16%, p = 1.00). Among those with astrocytoma, PsP developed in 3/23 photon-treated patients (13%) and 1/9 proton-treated patients (11.1%, p = 1.00). There was no difference in PsP rate based on radiation type, radiation dose, tumor grade, 1p19q codeletion, or IDH status. PsP occurred earlier in oligodendroglioma patients treated with protons compared to photons, 48 days vs. 131 days, p < .01. On multivariate analyses, gross total resection (p = .03, HR = 0.48, 95%CI = 0.25–0.93) and PsP (p = .04, HR = 0.22, 95% CI = 0.05–0.91) were associated with better PFS; IDH mutation was associated with better OS (p < .01, HR = 0.22, 95%CI = 0.08–0.65).

Conclusions

Patients with oligodendroglioma but not astrocytoma develop PsP earlier after protons compared to photons. PsP was associated with better PFS.

Residual Deep Convolutional Neural Network Predicts MGMT Methylation Status

Predicting methylation of the O6-methylguanine methyltransferase (MGMT) gene status utilizing MRI imaging is of high importance since it is a predictor of response and prognosis in brain tumors. In this study, we compare three different residual deep neural network (ResNet) architectures to evaluate their ability in predicting MGMT methylation status without the need for a distinct tumor segmentation step. We found that the ResNet50 (50 layers) architecture was the best performing model, achieving an accuracy of 94.90% (+/- 3.92%) for the test set (classification of a slice as no tumor, methylated MGMT, or non-methylated). ResNet34 (34 layers) achieved 80.72% (+/- 13.61%) while ResNet18 (18 layers) accuracy was 76.75% (+/- 20.67%). ResNet50 performance was statistically significantly better than both ResNet18 and ResNet34 architectures (p < 0.001). We report a method that alleviates the need of extensive preprocessing and acts as a proof of concept that deep neural architectures can be used to predict molecular biomarkers from routine medical images.

Response Assessment in Neuro-Oncology Clinical Trials

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

Bone marrow response as a potential biomarker of outcomes in glioblastoma patients

OBJECTIVE

Glioblastoma (GBM) is a highly aggressive malignancy that requires a multidisciplinary therapeutic approach of surgery, chemotherapy, and radiation therapy, but therapy is frequently limited by side effects. The most common adverse effect of chemotherapy with temozolomide (TMZ) is myelosuppression. It remains unclear whether the degree of bone-marrow suppression might serve as a biomarker for treatment outcome. The aim of the current study was to investigate whether the degree of bone-marrow toxicity in patients treated with TMZ correlates with overall survival (OS) and MRI-based time to progression (progression-free survival [PFS]).

METHODS

Complete blood counts and clinical and imaging information were collected retrospectively from 86 cases involving GBM patients who had completed both radiation therapy and at least 6 monthly cycles of chemotherapy with TMZ.

RESULTS

Using a multivariate Cox proportional hazard model, it was observed that MGMT promoter methylation, wild-type EGFR, younger patient age at diagnosis, and treatment-induced decreases in white blood cell counts were associated with improved OS. The 2-year survival rate was 25% and 58% for patients with increases and decreases, respectively, in white blood cell counts from baseline over 6 months of TMZ treatment. Consistent with the literature, IDH mutation and MGMT promoter methylation were associated with better PFS and OS. IDH mutation and MGMT promoter methylation were not correlated with changes in peripheral red blood cell or white blood cell counts.

CONCLUSIONS

Decreases in white blood cell counts might serve as a potential biomarker for OS and PFS in malignant glioma patients treated with radiation therapy and TMZ. It remains unclear whether treatment-induced changes in white blood cell counts correlate with drug-induced antitumor activity or represent an independent factor of the altered local and systemic tumor environment. Additional studies will be needed to determine dose dependence for chemotherapy based upon peripheral blood counts.

Early changes in glioblastoma metabolism measured by MR spectroscopic imaging during combination of anti-angiogenic cediranib and chemoradiation therapy are associated with survival

Precise assessment of treatment response in glioblastoma during combined anti-angiogenic and chemoradiation remains a challenge. In particular, early detection of treatment response by standard anatomical imaging is confounded by pseudo-response or pseudo-progression. Metabolic changes may be more specific for tumor physiology and less confounded by changes in blood-brain barrier permeability. We hypothesize that metabolic changes probed by magnetic resonance spectroscopic imaging can stratify patient response early during combination therapy. We performed a prospective longitudinal imaging study in newly diagnosed glioblastoma patients enrolled in a phase II clinical trial of the pan-vascular endothelial growth factor receptor inhibitor cediranib in combination with standard fractionated radiation and temozolomide (chemoradiation). Forty patients were imaged weekly during therapy with an imaging protocol that included magnetic resonance spectroscopic imaging, perfusion magnetic resonance imaging, and anatomical magnetic resonance imaging. Data were analyzed using receiver operator characteristics, Cox proportional hazards model, and Kaplan-Meier survival plots. We observed that the ratio of total choline to healthy creatine after 1 month of treatment was significantly associated with overall survival, and provided as single parameter: (1) the largest area under curve (0.859) in receiver operator characteristics, (2) the highest hazard ratio (HR = 85.85, P = 0.006) in Cox proportional hazards model, (3) the largest separation (P = 0.004) in Kaplan-Meier survival plots. An inverse correlation was observed between total choline/healthy creatine and cerebral blood flow, but no significant relation to tumor volumetrics was identified. Our results suggest that in vivo metabolic biomarkers obtained by magnetic resonance spectroscopic imaging may be an early indicator of response to anti-angiogenic therapy combined with standard chemoradiation in newly diagnosed glioblastoma.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Pseudoprogression, radionecrosis, inflammation or true tumor progression? challenges associated with glioblastoma response assessment in an evolving therapeutic landscape

The wide variety of treatment options that exist for glioblastoma, including surgery, ionizing radiation, anti-neoplastic chemotherapies, anti-angiogenic therapies, and active or passive immunotherapies, all may alter aspects of vascular permeability within the tumor and/or normal parenchyma. These alterations manifest as changes in the degree of contrast enhancement or T2-weighted signal hyperintensity on standard anatomic MRI scans, posing a potential challenge for accurate radiographic response assessment for identifying anti-tumor effects. The current review highlights the challenges that remain in differentiating true disease progression from changes due to radiation therapy, including pseudoprogression and radionecrosis, as well as immune or inflammatory changes that may occur as either an undesired result of cytotoxic therapy or as a desired consequence of immunotherapies.

Modified Criteria for Radiographic Response Assessment in Glioblastoma Clinical Trials

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

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

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

MRI texture features as biomarkers to predict MGMT methylation status in glioblastomas

Purpose:

Imaging biomarker research focuses on discovering relationships between radiological features and histological findings. In glioblastoma patients, methylation of the O⁶-methylguanine methyltransferase (MGMT) gene promoter is positively correlated with an increased effectiveness of current standard of care. In this paper, the authors investigate texture features as potential imaging biomarkers for capturing the MGMT methylation status of glioblastoma multiforme (GBM) tumors when combined with supervised classification schemes.

Methods:

A retrospective study of 155 GBM patients with known MGMT methylation status was conducted. Co-occurrence and run length texture features were calculated, and both support vector machines (SVMs) and random forest classifiers were used to predict MGMT methylation status.

Results:

The best classification system (an SVM-based classifier) had a maximum area under the receiver-operating characteristic (ROC) curve of 0.85 (95% CI: 0.78–0.91) using four texture features (correlation, energy, entropy, and local intensity) originating from the T2-weighted images, yielding at the optimal threshold of the ROC curve, a sensitivity of 0.803 and a specificity of 0.813.

Conclusions:

Results show that supervised machine learning of MRI texture features can predict MGMT methylation status in preoperative GBM tumors, thus providing a new noninvasive imaging biomarker.

Glioma-Targeted Drug Delivery Enabled by a Multifunctional Peptide

The rapid proliferation of glioma relies on vigorous angiogenesis for the supply of essential nutrients; thus, a radical method of antiglioma therapy should include blocking tumor neovasculature formation. A phage display selected heptapeptide, the glioma-initiating cell peptide GICP, was previously reported as a ligand of VAV3 protein (a Rho GTPase guanine nucleotide exchange factor), which is overexpressed on glioma cells and tumor neovasculature. Therefore, GICP holds potential for the multifunctional targeting of glioma (tumor cells and neovasculature). We developed GICP-modified micelle-based paclitaxel delivery systems for antiglioma therapy in vitro and in vivo. GICP and GICP-modified PEG-PLA micelles (GICP-PEG-PLA) could be significantly taken up by U87MG cells, a human cell line derived from malignant gliomas and human umbilical vein endothelial cells (HUVECs). Furthermore, GICP-PEG-PLA micelles demonstrated enhanced penetration in a tumor spheroid model in vitro in comparison to unmodified micelles. In vivo, DiR-loaded GICP-PEG-PLA micelles exhibited superior accumulation in the tumor region by targeting neovasculature and glioma cells in nude mice bearing subcutaneous glioma. When loaded with paclitaxel, GICP-PEG-PLA micelles could more effectively suppress tumor growth and neovasculature formation than unmodified micelles in vivo. Our results indicated that GICP could serve as a promising multifunctional ligand for glioma targeting.

Automated Segmentation of Hyperintense Regions in FLAIR MRI Using Deep Learning

We present a deep convolutional neural network application based on autoencoders aimed at segmentation of increased signal regions in fluid-attenuated inversion recovery magnetic resonance imaging images. The convolutional autoencoders were trained on the publicly available Brain Tumor Image Segmentation Benchmark (BRATS) data set, and the accuracy was evaluated on a data set where 3 expert segmentations were available. The simultaneous truth and performance level estimation (STAPLE) algorithm was used to provide the ground truth for comparison, and Dice coefficient, Jaccard coefficient, true positive fraction, and false negative fraction were calculated. The proposed technique was within the interobserver variability with respect to Dice, Jaccard, and true positive fraction. The developed method can be used to produce automatic segmentations of tumor regions corresponding to signal-increased fluid-attenuated inversion recovery regions.

FDG PET/MR Imaging Coregistration Helps Predict Survival in Patients with Glioblastoma and Radiologic Progression after Standard of Care Treatment

Purpose To determine the correlation between metabolic activity at fluorine 18 fluorodeoxyglucose (FDG) positron emission tomography (PET) and survival in patients with glioblastoma and suspected progression at posttherapy magnetic resonance (MR) imaging. Materials and Methods The authors retrospectively examined the relationship between metabolic activity at FDG PET in the residual lesion identified at brain MR imaging and survival time in 56 patients with glioblastoma who were treated with postoperative concurrent radiation and temozolomide therapy and who underwent FDG PET/computed tomography because of radiologic deterioration at follow-up MR imaging between 2006 and 2015. A normalized metric of metabolic activity in the residual lesion (standardized uptake value ratio [SUV_r]) was calculated as the maximum standardized uptake value (SUV_max) in the tumor relative to that in healthy white matter. The primary end point of the study was survival time from PET. Patients were stratified according to SUV_r. Comparisons of risk for death between subgroups were made with the log-hazard ratio of the Cox proportional hazard model. Results There was a significant association between overall survival and SUV_r in the residual lesion (P = .006), and a survival benefit was observed in patients with SUV_r of less than 1.7, who had a median survival time of 23.1 months (95% confidence interval [CI]: 12.7, 38.9), which was significantly longer than that in patients with an SUV_r of 2.0 to less than 2.5 and those with an SUV_r of at least 2.5, who had a median survival time of 10.1 (95% CI: 2.4, 15.9; P = .008) and 7.5 (95% CI: 3.9, 9.7; P < .001) months, respectively. Conclusion Patients with glioblastoma whose posttherapy MR images showed a residual lesion with high relative metabolic activity at FDG PET had a shorter survival time than did those with low activity at FDG PET. ^© RSNA, 2016.

ANG1005 for breast cancer brain metastases: correlation between 18F-FLT-PET after first cycle and MRI in response assessment

PURPOSE

Improved therapies and imaging modalities are needed for the treatment of breast cancer brain metastases (BCBM). ANG1005 is a drug conjugate consisting of paclitaxel covalently linked to Angiopep-2, designed to cross the blood-brain barrier. We conducted a biomarker substudy to evaluate ¹⁸F-FLT-PET for response assessment.

METHODS

Ten patients with measurable BCBM received ANG1005 at a dose of 550 mg/m² IV every 21 days. Before and after cycle 1, patients underwent PET imaging with ¹⁸F-FLT, a thymidine analog, retention of which reflects cellular proliferation, for comparison with gadolinium-contrast magnetic resonance imaging (Gd-MRI) in brain metastases detection and response assessment. A 20 % change in uptake after one cycle of ANG1005 was deemed significant.

RESULTS

Thirty-two target and twenty non-target metastatic brain lesions were analyzed. The median tumor reduction by MRI after cycle 1 was -17.5 % (n = 10 patients, lower, upper quartiles: -25.5, -4.8 %) in target lesion size compared with baseline. Fifteen of twenty-nine target lesions (52 %) and 12/20 nontarget lesions (60 %) showed a ≥20 % decrease post-therapy in FLT-PET SUV change (odds ratio 0.71, 95 % CI: 0.19, 2.61). The median percentage change in SUV_max was -20.9 % (n = 29 lesions; lower, upper quartiles: -42.4, 2.0 %), and the median percentage change in SUV₈₀ was also -20.9 % (n = 29; lower, upper quartiles: -49.0, 0.0 %). Two patients had confirmed partial responses by PET and MRI lasting 6 and 18 cycles, respectively. Seven patients had stable disease, receiving a median of six cycles.

CONCLUSIONS

ANG1005 warrants further study in BCBM. Results demonstrated a moderately strong association between MRI and ¹⁸F-FLT-PET imaging.

Dynamics of circulating hypoxia-mediated miRNAs and tumor response in patients with high-grade glioma treated with bevacizumab

OBJECTIVE Bevacizumab is an antiangiogenic agent under investigation for use in patients with high-grade glioma. It produces a high rate of radiological response; however, this response should be interpreted with caution because it may reflect normalization of the tumor vasculature and not necessarily a true antitumor effect. The authors previously demonstrated that 4 hypoxia-mediated microRNAs (miRNA)-miR-210, miR-21, miR-10b, and miR-196b-are upregulated in glioma as compared with normal brain tissue. The authors hypothesized that the regulation and expression of these miRNAs would be altered in response to bevacizumab treatment. The object of this study was to perform longitudinal monitoring of circulating miRNA levels in patients undergoing bevacizumab treatment and to correlate it with tumor response. METHODS A total of 120 serum samples from 28 patients with high-grade glioma were prospectively collected prior to bevacizumab (n = 15) or temozolomide (TMZ; n = 13) treatment and then longitudinally during treatment. Quantification of the 4 miRNAs was evaluated by real-time polymerase chain reaction using total RNA extracted from the serum. At each time point, tumor response was assessed by Response Assessment in Neuro-Oncology criteria and by performing MRI using fluid attenuated inversion recovery (FLAIR) and contrast-enhanced images. RESULTS As compared with pretreatment levels, high levels of miR-10b and miR-21 were observed in the majority of patients throughout the bevacizumab treatment period. miR-10b and miR-21 levels correlated negatively and significantly with changes in enhancing tumor diameters (r = -0.648, p < 0.0001) in the bevacizumab group but not in the TMZ group. FLAIR images and the RANO assessment did not correlate with the sum quantification of these miRNAs in either group. CONCLUSIONS Circulating levels of miR-10b and miR-21 probably reflect the antiangiogenic effect of therapy, but their role as biomarkers for tumor response remains uncertain and requires further investigation.

Advances in the treatment of newly diagnosed glioblastoma

Glioblastoma is a refractory malignancy with limited treatment options at tumor recurrence. Only a small proportion of patients survive 2 years or longer with the current standard of care. Gene expression profiling can segregate newly diagnosed patients into groups with different prognoses, and these biomarkers are being incorporated into a new generation of personalized clinical trials. Using the experience from recently completed large scale, multi-faceted, randomized glioblastoma clinical trials, a new clinical trial paradigm is being established to move promising therapies forward into the newly diagnosed treatment setting. Upcoming trials using the immune check-point inhibitors are an example of this changing paradigm and these and other immunotherapies have potential as promising new treatment modalities for newly diagnosed GB patients.

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

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

Treating recurrent glioblastoma: an update

Glioblastoma, the most aggressive of the gliomas, has a high recurrence and mortality rate. The nature of this poor prognosis resides in the molecular heterogeneity and phenotypic features of this tumor. Despite research advances in understanding the molecular biology, it has been difficult to translate this knowledge into effective treatment. Nearly all will have tumor recurrence, yet to date very few therapies have established efficacy as salvage regimens. This challenge is further complicated by imaging confounders and to an even greater degree by the ever increasing molecular heterogeneity that is thought to be both sporadic and treatment-induced. The development of novel clinical trial designs to support the development and testing of novel treatment regimens and drug delivery strategies underscore the need for more precise techniques in imaging and better surrogate markers to help determine treatment response. This review summarizes recent approaches to treat patients with recurrent glioblastoma and considers future perspectives.

Assessing and monitoring intratumor heterogeneity in glioblastoma: how far has multimodal imaging come?

Glioblastoma demonstrates imaging features of intratumor heterogeneity that result from underlying heterogeneous biological properties. This stems from variations in cellular behavior that result from genetic mutations that either drive, or are driven by, heterogeneous microenvironment conditions. Among all imaging methods available, only T1-weighted contrast-enhancing and T2-weighted fluid-attenuated inversion recovery are used in standard clinical glioblastoma assessment and monitoring. Advanced imaging modalities are still considered emerging techniques as appropriate end points and robust methodologies are missing from clinical trials. Discovering how these images specifically relate to the underlying tumor biology may aid in improving quality of clinical trials and understanding the factors involved in regional responses to treatment, including variable drug uptake and effect of radiotherapy. Upon validation and standardization of emerging MR techniques, providing information based on the underlying tumor biology, these images may allow for clinical decision-making that is tailored to an individual's response to treatment.

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

A recent joint meeting was held on January 30, 2014, with the US Food and Drug Administration (FDA), National Cancer Institute (NCI), clinical scientists, imaging experts, pharmaceutical and biotech companies, clinical trials cooperative groups, and patient advocate groups to discuss imaging endpoints for clinical trials in glioblastoma. This workshop developed a set of priorities and action items including the creation of a standardized MRI protocol for multicenter studies. The current document outlines consensus recommendations for a standardized Brain Tumor Imaging Protocol (BTIP), along with the scientific and practical justifications for these recommendations, resulting from a series of discussions between various experts involved in aspects of neuro-oncology neuroimaging for clinical trials. The minimum recommended sequences include: (i) parameter-matched precontrast and postcontrast inversion recovery-prepared, isotropic 3D T1-weighted gradient-recalled echo; (ii) axial 2D T2-weighted turbo spin-echo acquired after contrast injection and before postcontrast 3D T1-weighted images to control timing of images after contrast administration; (iii) precontrast, axial 2D T2-weighted fluid-attenuated inversion recovery; and (iv) precontrast, axial 2D, 3-directional diffusion-weighted images. Recommended ranges of sequence parameters are provided for both 1.5 T and 3 T MR systems.

[Towards more precision in the therapy of brain tumors. Possibilities and limits of MRI]

Due to the introduction of advanced functional and spectroscopic magnetic resonance (MR) sequences, MR imaging has gained significant importance in neuro-oncology. In contrast to recent years when neuro-oncological imaging was mostly limited to contrast-enhanced T1-weighted images, advanced MR methods provide direct visualization and assessment of tumor pathophysiology. This article summarizes the most relevant MR methods for neuro-oncological imaging and highlights the pathophysiological background as well as potential clinical applications. Ultimately, this article gives a glimpse into the future and introduces potential applications of ultra-high field MRI.

Quantification of Nonenhancing Tumor Burden in Gliomas Using Effective T2 Maps Derived from Dual-Echo Turbo Spin-Echo MRI

PURPOSE

Evaluation of nonenhancing tumor (NET) burden is an important yet challenging part of brain tumor response assessment. This study focuses on using dual-echo turbo spin-echo MRI as a means of quickly estimating tissue T2, which can be used to objectively define NET burden.

EXPERIMENTAL DESIGN

A series of experiments were performed to establish the use of T2 maps for defining NET burden. First, variation in T2 was determined using the American College of Radiology (ACR) water phantoms in 16 scanners evaluated over 3 years. Next, the sensitivity and specificity of T2 maps for delineating NET from other tissues were examined. Then, T2-defined NET was used to predict survival in separate subsets of patients with glioblastoma treated with radiotherapy, concurrent radiation, and chemotherapy, or bevacizumab at recurrence.

RESULTS

Variability in T2 in the ACR phantom was 3% to 5%. In training data, ROC analysis suggested that 125 ms < T2 < 250 ms could delineate NET with a sensitivity of >90% and specificity of >65%. Using this criterion, NET burden after completion of radiotherapy alone, or concurrent radiotherapy, and chemotherapy was shown to be predictive of survival (Cox, P < 0.05), and the change in NET volume before and after bevacizumab therapy in recurrent glioblastoma was also a predictive of survival (P < 0.05).

CONCLUSIONS

T2 maps using dual-echo data are feasible, stable, and can be used to objectively define NET burden for use in brain tumor characterization, prognosis, and response assessment. The use of effective T2 maps for defining NET burden should be validated in a randomized, clinical trial.

Effects of anti-angiogenesis on glioblastoma growth and migration: model to clinical predictions

Glioblastoma multiforme (GBM) causes significant neurological morbidity and short survival times. Brain invasion by GBM is associated with poor prognosis. Recent clinical trials of bevacizumab in newly-diagnosed GBM found no beneficial effects on overall survival times; however, the baseline health-related quality of life and performance status were maintained longer in the bevacizumab group and the glucocorticoid requirement was lower. Here, we construct a clinical-scale model of GBM whose predictions uncover a new pattern of recurrence in 11/70 bevacizumab-treated patients. The findings support an exception to the Folkman hypothesis: GBM grows in the absence of angiogenesis by a cycle of proliferation and brain invasion that expands necrosis. Furthermore, necrosis is positively correlated with brain invasion in 26 newly-diagnosed GBM. The unintuitive results explain the unusual clinical effects of bevacizumab and suggest new hypotheses on the dynamic clinical effects of migration by active transport, a mechanism of hypoxia-driven brain invasion.