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

A neural tract-inspired conduit for facile, on-demand biopsy of glioblastoma

Background

A major hurdle to effectively treating glioblastoma (GBM) patients is the lack of longitudinal information about tumor progression, evolution, and treatment response.

Methods

In this study, we report the use of a neural tract-inspired conduit containing aligned polymeric nanofibers (i.e., an aligned nanofiber device) to enable on-demand access to GBM tumors in 2 rodent models. Depending on the experiment, a humanized U87MG xenograft and/or F98-GFP+ syngeneic rat tumor model was chosen to test the safety and functionality of the device in providing continuous sampling access to the tumor and its microenvironment.

Results

The aligned nanofiber device was safe and provided a high quantity of quality genomic materials suitable for omics analyses and yielded a sufficient number of live cells for in vitro expansion and screening. Transcriptomic and genomic analyses demonstrated continuity between material extracted from the device and that of the primary, intracortical tumor (in the in vivo model).

Conclusions

The results establish the potential of this neural tract-inspired, aligned nanofiber device as an on-demand, safe, and minimally invasive access point, thus enabling rapid, high-throughput, longitudinal assessment of tumor and its microenvironment, ultimately leading to more informed clinical treatment strategies.

Tracking Therapy Response in Glioblastoma Using 1D Convolutional Neural Networks

BACKGROUND

Glioblastoma (GB) is a malignant brain tumour that is challenging to treat, often relapsing even after aggressive therapy. Evaluating therapy response relies on magnetic resonance imaging (MRI) following the Response Assessment in Neuro-Oncology (RANO) criteria. However, early assessment is hindered by phenomena such as pseudoprogression and pseudoresponse. Magnetic resonance spectroscopy (MRS/MRSI) provides metabolomics information but is underutilised due to a lack of familiarity and standardisation.

METHODS

This study explores the potential of spectroscopic imaging (MRSI) in combination with several machine learning approaches, including one-dimensional convolutional neural networks (1D-CNNs), to improve therapy response assessment. Preclinical GB (GL261-bearing mice) were studied for method optimisation and validation.

RESULTS

The proposed 1D-CNN models successfully identify different regions of tumours sampled by MRSI, i.e., normal brain (N), control/unresponsive tumour (T), and tumour responding to treatment (R). Class activation maps using Grad-CAM enabled the study of the key areas relevant to the models, providing model explainability. The generated colour-coded maps showing the N, T and R regions were highly accurate (according to Dice scores) when compared against ground truth and outperformed our previous method.

CONCLUSIONS

The proposed methodology may provide new and better opportunities for therapy response assessment, potentially providing earlier hints of tumour relapsing stages.

Strategies, considerations, and recent advancements in the development of liquid biopsy for glioblastoma: a step towards individualized medicine in glioblastoma

OBJECTIVE

Glioblastoma (GBM) is a devasting primary brain tumor with less than a 5% 5-year survival. Treatment response assessment can be challenging because of inflammatory pseudoprogression that mimics true tumor progression clinically and on imaging. Developing additional noninvasive assays is critical. In this article, the authors review various biomarkers that could be used in developing liquid biopsies for GBM, along with strengths, limitations, and future applications. In addition, they present a potential liquid biopsy design based on the use of an extracellular vesicle-based liquid biopsy targeting nonneoplastic extracellular vesicles.

METHODS

The authors conducted a current literature review of liquid biopsy in GBM by searching the PubMed, Scopus, and Google Scholar databases. Articles were assessed for type of biomarker, isolation methodology, analytical techniques, and clinical relevance.

RESULTS

Recent work has shown that liquid biopsies of plasma, blood, and/or CSF hold promise as noninvasive clinical tools that can be used to diagnose recurrence, assess treatment response, and predict patient outcomes in GBM. Liquid biopsy in GBM has focused primarily on extracellular vesicles, cell-free tumor nucleic acids, and whole-cell isolates as focal biomarkers. GBM tumor signatures have been generated via analysis of tumor gene mutations, unique RNA expression, and metabolic and proteomic alterations. Liquid biopsies capture tumor heterogeneity, identifying alterations in GBM tumors that may be undetectable via surgical biopsy specimens. Finally, biomarker burden can be used to assess treatment response and recurrence in GBM.

CONCLUSIONS

Liquid biopsy offers a promising avenue for monitoring treatment response and recurrence in GBM without invasive procedures. Although additional steps must be taken to bring liquid biopsy into the clinic, proof-of-principle studies and isolation methodologies are promising. Ultimately, CSF and/or plasma-based liquid biopsy is likely to be a powerful tool in the neurosurgeon's arsenal in the near future for the treatment and management of GBM patients.

A brain tumor reporting and data system to optimize imaging surveillance and prognostication in high-grade gliomas

BACKGROUND AND PURPOSE

High-grade glioma (HGG), including glioblastoma, is the most common primary brain neoplasm and has a dismal prognosis. After initial treatment, follow-up decisions are guided by longitudinal MRI performed at routine intervals. The Brain Tumor Reporting and Data System (BT-RADS) is a proposed structured reporting system for posttreatment brain MRIs. The purpose of this study is to determine the relationship between BT-RADS scores and overall survival in HGG patients.

METHODS

Chart review of grade 4 glioma patients who had an MRI at a single institution from November 2018 to November 2019 was performed. BT-RADS scores, tumor characteristics, and overall survival were recorded. Likelihood of improvement, stability, or worsening on the subsequent study was calculated for each score. Survival analysis was performed using Kaplan-Meier method, log-rank test, and a time-dependent cox model. Significance level of .05 was used.

RESULTS

The study identified 91 HGG patients who underwent a total of 538 MRIs. Mean age of patients was 57 years old. Score with the highest likelihood for worsening on the next follow-up was 3b. The risk of death was 53% higher with each incremental increase in BT-RADS scores (hazard ratio, 1.53; 95% confidence interval [CI], 1.07-2.19; p = .019). The risk of death was 167% higher in O-6-methylguanine-DNA-methyltransferase unmethylated tumors (hazard ratio, 2.67; 95% CI, 1.34-5.33; p = .005).

CONCLUSIONS

BT-RADS scores can be used as a reference guide to anticipate whether patients' subsequent MRI will be improved, stable, or worsened. The scoring system can also be used to predict clinical outcomes and prognosis.

Phosphorous Magnetic Resonance Spectroscopy to Detect Regional Differences of Energy and Membrane Metabolism in Naïve Glioblastoma Multiforme

Simple Summary

Glioblastoma multiforme is a highly aggressive brain tumor, tending to infiltrate even larger zones of brain tissue than visible on conventional magnetic resonance imaging. By application of phosphorus magnetic resonance spectroscopy in patients with naïve glioblastoma multiforme, we tried to demonstrate changes in energy and membrane metabolism not only in affected regions but also in distant brain regions, the opposite brain hemisphere, and in comparison to healthy volunteers. We found reduced energetic states and signs of increased cell membrane turnover in regions of visible tumor and differences to and between the “normal-appearing” brains of glioblastoma patients and the brains of healthy volunteers. Our pilot study confirmed the feasibility of the method, so differences between various genetic mutations or clinical applicability for follow-up monitoring can be assessed in larger cohorts.

Abstract

Background: Glioblastoma multiforme (GBM) is a highly malignant primary brain tumor with infiltration of, on conventional imaging, normal-appearing brain parenchyma. Phosphorus magnetic resonance spectroscopy (31P-MRS) enables the investigation of different energy and membrane metabolites. The aim of this study is to investigate regional differences of 31P-metabolites in GBM brains. Methods: In this study, we investigated 32 patients (13 female and 19 male; mean age 63 years) with naïve GBM using 31P-MRS and conventional MRI. Contrast-enhancing (CE), T2-hyperintense, adjacent and distant ipsilateral areas of the contralateral brain and the brains of age- and gender-matched healthy volunteers were assessed. Moreover, the 31P-MRS results were correlated with quantitative diffusion parameters. Results: Several metabolite ratios between the energy-dependent metabolites and/or the membrane metabolites differed significantly between the CE areas, the T2-hyperintense areas, the more distant areas, and even the brains of healthy volunteers. pH values and Mg²⁺ concentrations were highest in visible tumor areas and decreased with distance from them. These results are in accordance with the literature and correlated with quantitative diffusion parameters. Conclusions: This pilot study shows that 31P-MRS is feasible to show regional differences of energy and membrane metabolism in brains with naïve GBM, particularly between the different “normal-appearing” regions and between the contralateral hemisphere and healthy controls. Differences between various genetic mutations or clinical applicability for follow-up monitoring have to be assessed in a larger cohort.

Monocytes carrying GFAP detect glioma, brain metastasis and ischaemic stroke, and predict glioblastoma survival

Diagnosis and monitoring of primary brain tumours, brain metastasis and acute ischaemic stroke all require invasive, burdensome and costly diagnostics, frequently lacking adequate sensitivity, particularly during disease monitoring. Monocytes are known to migrate to damaged tissues, where they act as tissue macrophages, continuously scavenging, phagocytizing and digesting apoptotic cells and other tissue debris. We hypothesize that upon completion of their tissue-cleaning task, these tissue macrophages might migrate via the lymph system to the bloodstream, where they can be detected and evaluated for their phagolysosomal contents. We discovered a blood monocyte subpopulation carrying the brain-specific glial fibrillary acidic protein in glioma patients and in patients with brain metastasis and evaluated the diagnostic potential of this finding. Blood samples were collected in a cross-sectional study before or during surgery from adult patients with brain lesions suspected of glioma. Together with blood samples from healthy controls, these samples were flowing cytometrically evaluated for intracellular glial fibrillary acidic protein in monocyte subsets. Acute ischaemic stroke patients were tested at multiple time points after onset to evaluate the presence of glial fibrillary acidic protein-carrying monocytes in other forms of brain tissue damage. Clinical data were collected retrospectively. High-grade gliomas (N = 145), brain metastasis (N = 21) and large stroke patients (>100 cm³) (N = 3 versus 6; multiple time points) had significantly increased frequencies of glial fibrillary acidic protein+CD16+ monocytes compared to healthy controls. Based on both a training and validation set, a cut-off value of 0.6% glial fibrillary acidic protein+CD16+ monocytes was established, with 81% sensitivity (95% CI 75–87%) and 85% specificity (95% CI 80–90%) for brain lesion detection. Acute ischaemic strokes of >100 cm³ reached >0.6% of glial fibrillary acidic protein+CD16+ monocytes within the first 2–8 h after hospitalization and subsided within 48 h. Glioblastoma patients with >20% glial fibrillary acidic protein+CD16+ non-classical monocytes had a significantly shorter median overall survival (8.1 versus 12.1 months). Our results and the available literature, support the hypothesis of a tissue-origin of these glial fibrillary acidic protein-carrying monocytes. Blood monocytes carrying glial fibrillary acidic protein have a high sensitivity and specificity for the detection of brain lesions and for glioblastoma patients with a decreased overall survival. Furthermore, their very rapid response to acute tissue damage identifies large areas of ischaemic tissue damage within 8 h after an ischaemic event. These studies are the first to report the clinical applicability for brain tissue damage detection through a minimally invasive diagnostic method, based on blood monocytes and not serum markers, with direct consequences for disease monitoring in future (therapeutic) studies and clinical decision making in glioma and acute ischaemic stroke patients.

Semi-automated construction of patient individualised clinical target volumes for radiotherapy treatment of glioblastoma utilising diffusion tensor decomposition maps

OBJECTIVES

Glioblastoma multiforme (GBM) is a highly infiltrative primary brain tumour with an aggressive clinical course. Diffusion tensor imaging (DT-MRI or DTI) is a recently developed technique capable of visualising subclinical tumour spread into adjacent brain tissue. Tensor decomposition through p and q maps can be used for planning of treatment. Our objective was to develop a tool to automate the segmentation of DTI decomposed p and q maps in GBM patients in order to inform construction of radiotherapy target volumes.

METHODS

Chan-Vese level set model is applied to segment the p map using the q map as its initial starting point. The reason of choosing this model is because of the robustness of this model on either conventional MRI or only DTI. The method was applied on a data set consisting of 50 patients having their gross tumour volume delineated on their q map and Chan-Vese level set model uses these superimposed masks to incorporate the infiltrative edges.

RESULTS

The expansion of tumour boundary from q map to p map is clearly visible in all cases and the Dice coefficient (DC) showed a mean similarity of 74% across all 50 patients between the manually segmented ground truth p map and the level set automatic segmentation.

CONCLUSION

Automated segmentation of the tumour infiltration boundary using DTI and tensor decomposition is possible using Chan-Vese level set methods to expand q map to p map. We have provided initial validation of this technique against manual contours performed by experienced clinicians.

ADVANCES IN KNOWLEDGE

This novel automated technique to generate p maps has the potential to individualise radiation treatment volumes and act as a decision support tool for the treating oncologist.

A radiomics-based biomarker for cytokeratin 19 status of hepatocellular carcinoma with gadoxetic acid-enhanced MRI

OBJECTIVES

We aimed to develop a radiomics-based model derived from gadoxetic acid-enhanced MR images to preoperatively identify cytokeratin (CK) 19 status of hepatocellular carcinoma (HCC).

METHODS

A cohort of 227 patients with single HCC was classified into a training set (n = 159) and a time-independent validated set (n = 68). A total of 647 radiomic features were extracted from multi-sequence MR images. The least absolute shrinkage and selection operator regression and decision tree methods were utilized for feature selection and radiomics signature construction. A multivariable logistic regression model incorporating clinico-radiological features and the fusion radiomics signature was built for prediction of CK19 status by evaluating area under curve (AUC).

RESULTS

In the whole cohort, 57 patients were CK19 positive and 170 patients were CK19 negative. By combining 11 and 6 radiomic features extracted in arterial phase and hepatobiliary phase images, respectively, a fusion radiomics signature achieved AUCs of 0.951 and 0.822 in training and validation datasets. The final combined model integrated a-fetoprotein levels, arterial rim enhancement pattern, irregular tumor margin, and the fusion radiomics signature, with a sensitivity of 0.818 and specificity of 0.974 in the training cohort and that of 0.769 and 0.818 in the validated cohort. The nomogram based on the combined model showed satisfactory prediction performance in training (C-index 0.959) and validation (C-index 0.846) dataset.

CONCLUSIONS

The combined model based on a fusion radiomics signature derived from arterial and hepatobiliary phase images of gadoxetic acid-enhanced MRI can be a reliable biomarker for CK19 status of HCC.

KEY POINTS

• Arterial rim enhancement pattern and irregular tumor margin on hepatobiliary phase on gadoxetic acid-enhanced MRI can be useful for evaluating CK19 status of HCC. • A radiomics-based model performed better than the clinico-radiological model both in training and validation datasets for predicting CK19 status of HCC. • The nomogram based on the fusion radiomics signature can be easily used for CK19 stratification of HCC.