Do Habitat MRI and Fractal Analysis Help Distinguish Triple-Negative Breast Cancer From Non-Triple-Negative Breast Carcinoma

Purpose: To determine whether multiparametric MRI-based spatial habitats and fractal analysis can help distinguish triple-negative breast cancer (TNBC) from non-TNBC. Method: Multiparametric DWI and DCE-MRI at 3T were obtained from 142 biopsy- and surgery-proven breast cancer with 148 breast lesions (TNBC = 26 and non-TNBC = 122). The contrast-enhancing lesions were divided into 3 spatial habitats based on perfusion and diffusion patterns using K-means clustering. The fractal dimension (FD) of the tumour subregions was calculated. The accuracy of the habitat segmentation was measured using the Dice index. Inter- and intra-reader reliability were evaluated with the intraclass correlation coefficient (ICC). The ability to predict TNBC status was assessed using the receiver operating characteristic curve. Results: The Dice index for the whole tumour was 0.81 for inter-reader and 0.88 for intra-reader reliability. The inter- and intra-reader reliability were excellent for all 3 tumour habitats and fractal features (ICC > 0.9). TNBC had a lower hypervascular cellular habitat and higher FD 1 compared to non-TNBC (all P < .001). Multivariate analysis confirmed that hypervascular cellular habitat (OR = 0.88) and FD 1 (OR = 1.35) were independently associated with TNBC (all P < .001) after adjusting for rim enhancement, axillary lymph nodes status, and histological grade. The diagnostic model combining hypervascular cellular habitat and FD 1 showed excellent discriminatory ability for TNBC, with an AUC of 0.951 and an accuracy of 91.9%. Conclusions: The fraction of hypervascular cellular habitat and its FD may serve as useful imaging biomarkers for predicting TNBC status.

The prognostic relevance of a gene expression signature in MRI-defined highly vascularized glioblastoma

Background

The vascular heterogeneity of glioblastomas (GB) remains an important area of research, since tumor progression and patient prognosis are closely tied to this feature. With this study, we aim to identify gene expression profiles associated with MRI-defined tumor vascularity and to investigate its relationship with patient prognosis.

Methods

The study employed MRI parameters calculated with DSC Perfusion Quantification of ONCOhabitats glioma analysis software and RNA-seq data from the TCGA-GBM project dataset. In our study, we had a total of 147 RNA-seq samples, which 15 of them also had MRI parameter information. We analyzed the gene expression profiles associated with MRI-defined tumor vascularity using differential gene expression analysis and performed Log-rank tests to assess the correlation between the identified genes and patient prognosis.

Results

The findings of our research reveal a set of 21 overexpressed genes associated with the high vascularity pattern. Notably, several of these overexpressed genes have been previously implicated in worse prognosis based on existing literature. Our log-rank test further validates that the collective upregulation of these genes is indeed correlated with an unfavorable prognosis. This set of genes includes a variety of molecules, such as cytokines, receptors, ligands, and other molecules with diverse functions.

Conclusions

Our findings suggest that the set of 21 overexpressed genes in the High Vascularity group could potentially serve as prognostic markers for GB patients. These results highlight the importance of further investigating the relationship between the molecules such as cytokines or receptors underlying the vascularity in GB and its observation through MRI and developing targeted therapies for this aggressive disease.

Metabolic habitat imaging with hemodynamic heterogeneity predicts individual progression-free survival in high-grade glioma

AIM

We design a feasibility study to obtain a set of metabolic-hemodynamic habitats for tackling tumor spatial metabolic patterns with hemodynamic information.

MATERIALS AND METHODS

Preoperative data from 69 high-grade gliomas (HGG) patients with subsequent histologic confirmation of HGG were prospectively collected (January 2016 to March 2020) after concurrent chemoradiotherapy (CCRT). Four vascular habitats were automatically segmented by multiparametric magnetic resonance imaging (MRI). The metabolic information, either at enhancing or edema tumor regions, was obtained by two neuroradiologists. The relative habitat volumes were used for weight estimation procedures for computing the coefficients of a linear regression model using weighted least squares (WLS) for metabolite semiquantifications (i.e. the Cho/NAA ratio and the Cho/Cr ratio) at vascular habitats. Multivariate Cox proportional hazard regression analyses are used to obtain the odds ratio (OR) and develop a nomogram using weighted estimators corresponding to each covariate derived from Cox regression coefficients.

RESULTS

There was a strongly correlation between perfusion indexes and the Cho/Cr ratio (rCBV, r=0.71) or Cho/NAA ratio (rCBV, r=0.66) at high-angiogenic enhancing tumor habitats (HAT) habitat. Compared isocitrate dehydrogenase (IDH) mutation to their wild type, the IDH wild type had significantly decreased Cho/Cr ratio (IDH mutation: Cho/Cr ratio = 2.44 ± 0.33, IDH wildtype: Cho/Cr ratio = 2.66 ± 0.36, p=0.02) and Cho/NAA ratio (IDH mutation: Cho/Cr ratio = 4.59 ± 0.61, IDH wildtype: Cho/Cr ratio = 4.99 ± 0.66, p=0.022) at the HAT. The C-index for the median progression-free survival (PFS) prediction was 0.769 for the Cho/NAA nomogram and 0.747 for the Cho/Cr nomogram through 1000 bootstrapping validation.

CONCLUSIONS

Our findings suggest that spatial metabolism combined with hemodynamic heterogeneity is associated with individual PFS to HGG patients post-CCRT.

Transient deoxyhemoglobin formation as a contrast for perfusion MRI studies in patients with brain tumors: a feasibility study

Background: Transient hypoxia-induced deoxyhemoglobin (dOHb) has recently been shown to represent a comparable contrast to gadolinium-based contrast agents for generating resting perfusion measures in healthy subjects. Here, we investigate the feasibility of translating this non-invasive approach to patients with brain tumors. Methods: A computer-controlled gas blender was used to induce transient precise isocapnic lung hypoxia and thereby transient arterial dOHb during echo-planar-imaging acquisition in a cohort of patients with different types of brain tumors (n = 9). We calculated relative cerebral blood volume (rCBV), cerebral blood flow (rCBF), and mean transit time (MTT) using a standard model-based analysis. The transient hypoxia induced-dOHb MRI perfusion maps were compared to available clinical DSC-MRI. Results: Transient hypoxia induced-dOHb based maps of resting perfusion displayed perfusion patterns consistent with underlying tumor histology and showed high spatial coherence to gadolinium-based DSC MR perfusion maps. Conclusion: Non-invasive transient hypoxia induced-dOHb was well-tolerated in patients with different types of brain tumors, and the generated rCBV, rCBF and MTT maps appear in good agreement with perfusion maps generated with gadolinium-based DSC MR perfusion.

Preoperative vascular heterogeneity based on dynamic susceptibility contrast MRI in predicting spatial pattern of locally recurrent high-grade gliomas

OBJECTIVES

To investigate if spatial recurrence pattern is associated with patient prognosis, and whether MRI vascular habitats can predict spatial pattern.

METHODS

In this retrospective study, 69 patients with locally recurrent high-grade gliomas (HGGs) were included. The cohort was divided into intra-resection cavity recurrence (ICR) and extra-resection cavity recurrence (ECR) patterns, according to the distance between the location of the recurrent tumor and the resection cavity or surgical region. Four vascular habitats, high angiogenic tumor, low angiogenic tumor, infiltrated peripheral edema, and vasogenic peripheral edema, were segmented and vascular heterogeneity parameters were analyzed. The survival and diagnostic performance under different spatial recurrence patterns were analyzed by Kaplan-Meier and ROC. A nomogram model was constructed by regression analysis and validated by bootstrapping technique.

RESULTS

Progression-free survival (PFS) and overall survival (OS) were longer for ICR (n = 32) than those for ECR (n = 37) (median PFS: 8 vs. 5 months, median OS: 17 vs. 13 months, p < 0.05). MRI vascular habitat analyses showed ECR had higher median relative cerebral blood volume (rCBVmedian) at each habitat than ICR (all p < 0.01). The rCBVmedian at IPE had good diagnostic performance (AUC: 0.727, 95%CI: 0.607, 0.828). The AUC of the nomogram based on MRI vascular habitats and clinical factors was 0.834 (95%CI: 0.726, 0.913) and was confirmed as 0.833 (95%CI: 0.830, 0.836) by bootstrapping validation.

CONCLUSIONS

The spatial pattern of locally recurrent HGGs is associated with prognosis. MRI vascular heterogeneity parameter could be used as a non-invasive imaging marker to predict spatial recurrence pattern.

CLINICAL RELEVANCE STATEMENT

Vascular heterogeneity parameters based on MRI vascular habitat analyses can non-invasively predict the spatial patterns of locally recurrent high-grade gliomas, providing a new diagnostic basis for clinicians to develop the extent of surgical resection and postoperative radiotherapy planning.

KEY POINTS

• Intra-resection cavity pattern was associated with longer progression-free survival and overall survival in locally recurrent high-grade gliomas. • Higher vascular heterogeneities in extra-resection cavity recurrence than in intra-resection cavity recurrence and the vascular heterogeneity parameters had good diagnostic performance in discriminating spatial recurrence pattern. • A nomogram model based on MRI vascular habitats and clinical factors had good performance in predicting spatial recurrence pattern.

Prognostic value of brain perfusion by MRI in the initial study of high grade gliomas

OBJECTIVES

To evaluate if the tumour perfusion at the initial MRI scan is a marker of prognosis for survival in patients diagnosed with High Grade Gliomas (HGG). To analyse the risk factors which influence on the mortality from HGG to quantify the overall survival to be expected in patients.

PATIENTS AND METHODS

The patients diagnosed with HGG through a MRI scan in a third-level hospital between 2017 and 2019 were selected. Clinical and tumour variables were collected. The survival analysis was used to determine the association between the tumour perfusion and the survival time. The relation between the collected variables and the survival period was assessed through Wald's statistical method, measuring the relationship via Cox's regression model. Finally, the type of relationship that exists between the tumour perfusion and the survival was analysed through the Lineal Regression method.Those statistical analysis were carried out using the software SPSS v.17.

RESULTS

38 patients were included (average age: 61.1 years old). The general average survival period was 20.6 months. A relationship between the tumour perfusion at the MRI scan and the overall survival has been identified, in detail, a group with intratumor values of relative cerebral blood volume (rCBV)>3.0 has shown a significant decline in the average survival period with regard to the average survival period of the group with values <3.0 (14.6 months vs. 22.8 months, p = 0.046). It has also been proved that variables like Karnofsky's scale and the response time since the intervention significantly influence on the survival period.

CONCLUSIONS

It has become evident that the tumour perfusion via MRI scan has a prognostic value in the initial analysis of HGG. The average survival period of patients with rCBV less than or equal to 3.0 is significantly higher than those patients whose values are higher, which allows to be more precise with the prognosis of each patient.

A subregion-based RadioFusionOmics model discriminates between grade 4 astrocytoma and glioblastoma on multisequence MRI

PURPOSE

To explore a subregion-based RadioFusionOmics (RFO) model for discrimination between adult-type grade 4 astrocytoma and glioblastoma according to the 2021 WHO CNS5 classification.

METHODS

329 patients (40 grade 4 astrocytomas and 289 glioblastomas) with histologic diagnosis was retrospectively collected from our local institution and The Cancer Imaging Archive (TCIA). The volumes of interests (VOIs) were obtained from four multiparametric MRI sequences (T1WI, T1WI + C, T2WI, T2-FLAIR) using (1) manual segmentation of the non-enhanced tumor (nET), enhanced tumor (ET), and peritumoral edema (pTE), and (2) K-means clustering of four habitats (H1: high T1WI + C, high T2-FLAIR; (2) H2: high T1WI + C, low T2-FLAIR; (3) H3: low T1WI + C, high T2-FLAIR; and (4) H4: low T1WI + C, low T2-FLAIR). The optimal VOI and best MRI sequence combination were determined. The performance of the RFO model was evaluated using the area under the precision-recall curve (AUPRC) and the best signatures were identified.

RESULTS

The two best VOIs were manual VOI3 (putative peritumoral edema) and clustering H34 (low T1WI + C, high T2-FLAIR (H3) combined with low T1WI + C and low T2-FLAIR (H4)). Features fused from four MRI sequences ([Formula: see text]) outperformed those from either a single sequence or other sequence combinations. The RFO model that was trained using fused features [Formula: see text] achieved the AUPRC of 0.972 (VOI3) and 0.976 (H34) in the primary cohort (p = 0.905), and 0.971 (VOI3) and 0.974 (H34) in the testing cohort (p = 0.402).

CONCLUSION

The performance of subregions defined by clustering was comparable to that of subregions that were manually defined. Fusion of features from the edematous subregions of multiple MRI sequences by the RFO model resulted in differentiation between grade 4 astrocytoma and glioblastoma.

Multimodel habitats constructed by perfusion and/or diffusion MRI predict isocitrate dehydrogenase mutation status and prognosis in high-grade gliomas

AIM

To determine whether tumour vascular and cellular heterogeneity of high-grade glioma (HGG) is predictive of isocitrate dehydrogenase (IDH) mutation status and overall survival (OS) by using tumour habitat-based analysis constructed by perfusion and/or diffusion magnetic resonance imaging (MRI).

MATERIALS AND METHODS

Seventy-eight HGG patients that met the 2021 World Health Organization WHO Classification of Tumors of the Central Nervous System, 5th edition (WHO CNS5), were enrolled to predict IDH mutation status, of which 32 grade 4 patients with unmethylated O6-methylguanine-DNA methyltransferase (MGMT) promoter were enrolled for prognostic analysis. The deep-learning-based model nnU-Net and K-means clustering algorithm were applied to construct the Traditional Habitat, Vascular Habitat (VH), Cellular Density Habitat (DH), and their Combined Habitat (CH). Quantitative parameters were extracted and compared between IDH-mutant and IDH-wild-type patients, respectively, and the prediction potential was evaluated by receiver operating characteristic (ROC) curve analysis. OS was analysed using Kaplan-Meier survival analysis and the log-rank test.

RESULTS

Compared with IDH-mutants, median relative cerebral blood volume (rCBVmedian) values in the whole enhancing tumour (WET), VH1, VH3, CH1-4 habitats were significantly increased in IDH-wild-type HGGs (all p<0.05). Additionally, the accuracy of rCBVmedian values in CH1 outperformed other habitats in identifying IDH mutation status (p<0.001) at a cut-off value of 4.83 with AUC of 0.815. Kaplan-Meier survival analysis highlighted significant differences in OS between the populations dichotomised by the median of rCBVmedian in WET, VH1, CH1-3 habitats (all p<0.05).

CONCLUSIONS

The habitat imaging technique may improve the accuracy of predicting IDH mutation status and prognosis, and even provide a new direction for subsequent personalised precision treatment.

Unlocking Bevacizumab's Potential: rCBVmax as a Predictive Biomarker for Enhanced Survival in Glioblastoma IDH-Wildtype Patients

BACKGROUND

Aberrant vascular architecture and angiogenesis are hallmarks of glioblastoma IDH-wildtype, suggesting that these tumors are suitable for antiangiogenic therapy. Bevacizumab was FDA-approved in 2009 following promising results in two clinical trials. However, its use for recurrent glioblastomas remains a subject of debate, as it does not universally improve patient survival.

PURPOSES

In this study, we aimed to analyze the influence of tumor vascularity on the benefit provided by BVZ and propose preoperative rCBVmax at the high angiogenic tumor habitat as a predictive biomarker to select patients who can benefit the most.

METHODS

Clinical and MRI data from 106 patients with glioblastoma IDH-wildtype have been analyzed. Thirty-nine of them received BVZ, and the remaining sixty-seven did not receive a second-line treatment. The ONCOhabitats method was used to automatically calculate rCBV.

RESULTS

We found a median survival from progression of 305 days longer for patients with moderate vascular tumors who received BVZ than those who did not receive any second-line treatment. This contrasts with patients with high-vascular tumors who only presented a median survival of 173 days longer when receiving BVZ. Furthermore, better responses to BVZ were found for the moderate-vascular group with a higher proportion of patients alive at 6, 12, 18, and 24 months after progression.

CONCLUSIONS

We propose rCBVmax as a potential biomarker to select patients who can benefit more from BVZ after tumor progression. In addition, we propose a threshold of 7.5 to stratify patients into moderate- and high-vascular groups to select the optimal second-line treatment.

Vascular differences between IDH-wildtype glioblastoma and astrocytoma IDH-mutant grade 4 at imaging and transcriptomic levels

Global agreement in central nervous system (CNS) tumor classification is essential for predicting patient prognosis and determining the correct course of treatment, as well as for stratifying patients for clinical trials at international level. The last update by the World Health Organization of CNS tumor classification and grading in 2021 considered, for the first time, IDH-wildtype glioblastoma and astrocytoma IDH-mutant grade 4 as different tumors. Mutations in the genes isocitrate dehydrogenase (IDH) 1 and 2 occur early and, importantly, contribute to gliomagenesis. IDH mutation produces a metabolic reprogramming of tumor cells, thus affecting the processes of hypoxia and vascularity, resulting in a clear advantage for those patients who present with IDH-mutated astrocytomas. Despite the clinical relevance of IDH mutation, current protocols do not include full sequencing for every patient. Alternative biomarkers could be useful and complementary to obtain a more reliable classification. In this sense, magnetic resonance imaging (MRI)-perfusion biomarkers, such as relative cerebral blood volume and flow, could be useful from the moment of presurgery, without incurring additional financial costs or requiring extra effort. The main purpose of this work is to analyze the vascular and hemodynamic differences between IDH-wildtype glioblastoma and IDH-mutant astrocytoma. To achieve this, we evaluate and validate the association between dynamic susceptibility contrast-MRI perfusion biomarkers and IDH mutation status. In addition, to gain a deeper understanding of the vascular differences in astrocytomas depending on the IDH mutation, we analyze the transcriptomic bases of the vascular differences.

Predicting the recurrence of hepatocellular carcinoma (≤ 5 cm) after resection surgery with promising risk factors: habitat fraction of tumor and its peritumoral micro-environment

PURPOSE

Characterizing the composition of hepatocellular carcinoma (HCC) and peritumoral micro-environment may provide sensitive biomarkers. We aimed to predict the recurrence-free survival (RFS) of HCC (≤ 5 cm) with habitat imaging of HCC and its peritumoral micro-environment.

MATERIAL AND METHODS

A total of 264 patients with HCC were included. Taking advantage of the enhancement ratio at the arterial and hepatobiliary phase of contrast-enhanced MRI, all HCCs and their peritumoral tissue of 3 mm and 4 mm were encoded with different habitats. Besides, the quantitative fraction of each habitat of HCC and peritumoral tissue were calculated. Univariable and multivariable Cox regression analysis was performed to select the prognostic factors. The nomogram-based predictor was established. Kaplan-Meier analysis was conducted to stratify the recurrence risk. Fivefold cross-validation was performed to determine the predictive performance with the concordance index (C-Index). Decision curve analysis was used to evaluate the net benefit.

RESULTS

Qualitatively, the spatial distribution of the habitats varied for different survival outcomes. Quantitatively, the fraction of habitat 3 in peritumoral tissue of 4 mm (f3-P4) was selected as independent risk factors (OR = 89.2, 95% CI = 14.5-549.2, p < 0.001) together with other two clinical variables. Integrating both clinical variables and f3-P4, a nomogram was constructed and showed high predictive efficacy (C-Index: 0.735, 95% CI 0.617-0.854) and extra net benefit according to the decision curve. Furthermore, patients with low f3-P4 or risk score given by nomogram have far longer RFS than those with high f3-P4 or risk score (stratification by f3-P4: 131.9 vs 55.0 months and stratification by risk score:131.9 vs 34.1 months).

CONCLUSION

Habitat imaging of HCC and peritumoral microenvironment can be used for effectively and non-invasively estimating the RFS, which holds potential in guiding clinical management and decision making.

Overall survival prediction for high-grade glioma patients using mathematical modeling of tumor cell infiltration

PURPOSE

This study aimed at applying a mathematical framework for the prediction of high-grade gliomas (HGGs) cell invasion into normal tissues for guiding the clinical target delineation, and at investigating the possibility of using tumor infiltration maps for patient overall survival (OS) prediction.

MATERIAL & METHODS

A model describing tumor infiltration into normal tissue was applied to 93 HGG cases. Tumor infiltration maps and corresponding isocontours with different cell densities were produced. ROC curves were used to seek correlations between the patient OS and the volume encompassed by a particular isocontour. Area-Under-the-Curve (AUC) values were used to determine the isocontour having the highest predictive ability. The optimal cut-off volume, having the highest sensitivity and specificity, for each isocontour was used to divide the patients in two groups for a Kaplan-Meier survival analysis.

RESULTS

The highest AUC value was obtained for the isocontour of cell densities 1000 cells/mm3 and 2000 cells/mm3, equal to 0.77 (p < 0.05). Correlation with the GTV yielded an AUC of 0.73 (p < 0.05). The Kaplan-Meier survival analysis using the 1000 cells/mm3 isocontour and the ROC optimal cut-off volume for patient group selection rendered a hazard ratio (HR) of 2.7 (p < 0.05), while the GTV rendered a HR = 1.6 (p < 0.05).

CONCLUSION

The simulated tumor cell invasion is a stronger predictor of overall survival than the segmented GTV, indicating the importance of using mathematical models for cell invasion to assist in the definition of the target for HGG patients.

Spectral Analysis Based on Hemodynamic Habitat Imaging Predicts Isocitrate Dehydrogenase Status and Prognosis in High-Grade Glioma

BACKGROUND

The intratumoral heterogeneity of high-grade gliomas (HGGs) is associated with isocitrate dehydrogenase (IDH) status and prognosis, which can be established by quantitative radioanalysis of spatial tumor habitats. Therefore, we designed a framework for tackling tumors based on spatial metabolism using the hemodynamic tissue signature (HTS), focusing on metabolic changes in tumor habitat to predict IDH status and assess prognosis in patients with HGG.

METHODS

Preoperative data for 121 patients with HGG with subsequent histologic confirmation of HGG were prospectively collected (January 2016 to December 2020). The HTS was mapped from the image data, chemical shift imaging voxels were selected from the HTS habitat as the region of interest, and the metabolic ratio of the HTS was calculated using weighted least square method fitting. The metabolic rate of the tumor enhancement area was used as a control to analyze the efficacy of each HTS metabolic rate in predicting the IDH status and prognosis of HGG.

RESULTS

Total choline (Cho)/total creatine and Cho/N-acetyl-aspartate showed significant differences between IDH-wildtype and IDH-mutant in high- and low-angiogenic enhanced tumor sites (P < 0.05); Cho/total creatine was an independent risk factor for prognosis of HGG patients in high-angiogenic enhanced tumor habitats, with significant differences in survival time between groups (P < 0.05). The metabolic ratio in the tumor enhanced area could not predict IDH status or evaluate prognosis.

CONCLUSIONS

Spectral analysis based on hemodynamic habitat imaging can clearly distinguish IDH mutations and the prognosis assessment is more accurate, rendering it superior to traditional spectral analysis in tumor enhancement areas.

Advanced MR Techniques for Preoperative Glioma Characterization: Part 1

Preoperative clinical magnetic resonance imaging (MRI) protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation or lack thereof. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this first part, we discuss dynamic susceptibility contrast and dynamic contrast-enhanced MRI, arterial spin labeling, diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting. The second part of this review addresses magnetic resonance spectroscopy, chemical exchange saturation transfer, susceptibility-weighted imaging, MRI-PET, MR elastography, and MR-based radiomics applications. Evidence Level: 3 Technical Efficacy: Stage 2.

Conventional and Advanced Magnetic Resonance Imaging Assessment of Non-Enhancing Peritumoral Area in Brain Tumor

The non-enhancing peritumoral area (NEPA) is defined as the hyperintense region in T2-weighted and fluid-attenuated inversion recovery (FLAIR) images surrounding a brain tumor. The NEPA corresponds to different pathological processes, including vasogenic edema and infiltrative edema. The analysis of the NEPA with conventional and advanced magnetic resonance imaging (MRI) was proposed in the differential diagnosis of solid brain tumors, showing higher accuracy than MRI evaluation of the enhancing part of the tumor. In particular, MRI assessment of the NEPA was demonstrated to be a promising tool for distinguishing high-grade gliomas from primary lymphoma and brain metastases. Additionally, the MRI characteristics of the NEPA were found to correlate with prognosis and treatment response. The purpose of this narrative review was to describe MRI features of the NEPA obtained with conventional and advanced MRI techniques to better understand their potential in identifying the different characteristics of high-grade gliomas, primary lymphoma and brain metastases and in predicting clinical outcome and response to surgery and chemo-irradiation. Diffusion and perfusion techniques, such as diffusion tensor imaging (DTI), diffusional kurtosis imaging (DKI), dynamic susceptibility contrast-enhanced (DSC) perfusion imaging, dynamic contrast-enhanced (DCE) perfusion imaging, arterial spin labeling (ASL), spectroscopy and amide proton transfer (APT), were the advanced MRI procedures we reviewed.

The promise of metabolic imaging in diffuse midline glioma

Recent insights into histopathological and molecular subgroups of glioma have revolutionized the field of neuro-oncology by refining diagnostic categories. An emblematic example in pediatric neuro-oncology is the newly defined diffuse midline glioma (DMG), H3 K27-altered. DMG represents a rare tumor with a dismal prognosis. The diagnosis of DMG is largely based on clinical presentation and characteristic features on conventional magnetic resonance imaging (MRI), with biopsy limited by its delicate neuroanatomic location. Standard MRI remains limited in its ability to characterize tumor biology. Advanced MRI and positron emission tomography (PET) imaging offer additional value as they enable non-invasive evaluation of molecular and metabolic features of brain tumors. These techniques have been widely used for tumor detection, metabolic characterization and treatment response monitoring of brain tumors. However, their role in the realm of pediatric DMG is nascent. By summarizing DMG metabolic pathways in conjunction with their imaging surrogates, we aim to elucidate the untapped potential of such imaging techniques in this devastating disease.

Deep Learning of Time-Signal Intensity Curves from Dynamic Susceptibility Contrast Imaging Enables Tissue Labeling and Prediction of Survival in Glioblastoma

BACKGROUND AND PURPOSE

An autoencoder can learn representative time-signal intensity patterns to provide tissue heterogeneity measures using dynamic susceptibility contrast MR imaging. The aim of this study was to investigate whether such an autoencoder-based pattern analysis could provide interpretable tissue labeling and prognostic value in isocitrate dehydrogenase (IDH) wild-type glioblastoma.

MATERIALS AND METHODS

Preoperative dynamic susceptibility contrast MR images were obtained from 272 patients with IDH wild-type glioblastoma (training and validation, 183 and 89 patients, respectively). The autoencoder was applied to the dynamic susceptibility contrast MR imaging time-signal intensity curves of tumor and peritumoral areas. Representative perfusion patterns were defined by voxelwise K-means clustering using autoencoder latent features. Perfusion patterns were labeled by comparing parameters with anatomic reference tissues for baseline, signal drop, and percentage recovery. In the validation set (n = 89), a survival model was created from representative patterns and clinical predictors using Cox proportional hazard regression analysis, and its performance was calculated using the Harrell C-index.

RESULTS

Eighty-nine patients were enrolled. Five representative perfusion patterns were used to characterize tissues as high angiogenic tumor, low angiogenic/cellular tumor, perinecrotic lesion, infiltrated edema, and vasogenic edema. Of these, the low angiogenic/cellular tumor (hazard ratio, 2.18; P = .047) and infiltrated edema patterns (hazard ratio, 1.88; P = .009) in peritumoral areas showed significant prognostic value. The combined perfusion patterns and clinical predictors (C-index, 0.72) improved prognostication when added to clinical predictors (C-index, 0.55).

CONCLUSIONS

The autoencoder perfusion pattern analysis enabled tissue characterization of peritumoral areas, providing heterogeneity and dynamic information that may provide useful prognostic information in IDH wild-type glioblastoma.

Visualising spatial heterogeneity in glioblastoma using imaging habitats

Glioblastoma is a high-grade aggressive neoplasm characterised by significant intra-tumoral spatial heterogeneity. Personalising therapy for this tumour requires non-invasive tools to visualise its heterogeneity to monitor treatment response on a regional level. To date, efforts to characterise glioblastoma's imaging features and heterogeneity have focussed on individual imaging biomarkers, or high-throughput radiomic approaches that consider a vast number of imaging variables across the tumour as a whole. Habitat imaging is a novel approach to cancer imaging that identifies tumour regions or 'habitats' based on shared imaging characteristics, usually defined using multiple imaging biomarkers. Habitat imaging reflects the evolution of imaging biomarkers and offers spatially preserved assessment of tumour physiological processes such perfusion and cellularity. This allows for regional assessment of treatment response to facilitate personalised therapy. In this review, we explore different methodologies to derive imaging habitats in glioblastoma, strategies to overcome its technical challenges, contrast experiences to other cancers, and describe potential clinical applications.

Decoding the Heterogeneity of Malignant Gliomas by PET and MRI for Spatial Habitat Analysis of Hypoxia, Perfusion, and Diffusion Imaging: A Preliminary Study

Background

Tumor heterogeneity poses major clinical challenges in high-grade gliomas (HGGs). Quantitative radiomic analysis with spatial tumor habitat clustering represents an innovative, non-invasive approach to represent and quantify tumor microenvironment heterogeneity. To date, habitat imaging has been applied mainly on conventional magnetic resonance imaging (MRI), although virtually extendible to any imaging modality, including advanced MRI techniques such as perfusion and diffusion MRI as well as positron emission tomography (PET) imaging.

Objectives

This study aims to evaluate an innovative PET and MRI approach for assessing hypoxia, perfusion, and tissue diffusion in HGGs and derive a combined map for clustering of intra-tumor heterogeneity.

Materials and Methods

Seventeen patients harboring HGGs underwent a pre-operative acquisition of MR perfusion (PWI), Diffusion (dMRI) and 18F-labeled fluoroazomycinarabinoside (18F-FAZA) PET imaging to evaluate tumor vascularization, cellularity, and hypoxia, respectively. Tumor volumes were segmented on fluid-attenuated inversion recovery (FLAIR) and T1 post-contrast images, and voxel-wise clustering of each quantitative imaging map identified eight combined PET and physiologic MRI habitats. Habitats’ spatial distribution, quantitative features and histopathological characteristics were analyzed.

Results

A highly reproducible distribution pattern of the clusters was observed among different cases, particularly with respect to morphological landmarks as the necrotic core, contrast-enhancing vital tumor, and peritumoral infiltration and edema, providing valuable supplementary information to conventional imaging. A preliminary analysis, performed on stereotactic bioptic samples where exact intracranial coordinates were available, identified a reliable correlation between the expected microenvironment of the different spatial habitats and the actual histopathological features. A trend toward a higher representation of the most aggressive clusters in WHO (World Health Organization) grade IV compared to WHO III was observed.

Conclusion

Preliminary findings demonstrated high reproducibility of the PET and MRI hypoxia, perfusion, and tissue diffusion spatial habitat maps and correlation with disease-specific histopathological features.

Hemodynamic Imaging in Cerebral Diffuse Glioma—Part B: Molecular Correlates, Treatment Effect Monitoring, Prognosis, and Future Directions

Gliomas, and glioblastoma in particular, exhibit an extensive intra- and inter-tumoral molecular heterogeneity which represents complex biological features correlating to the efficacy of treatment response and survival. From a neuroimaging point of view, these specific molecular and histopathological features may be used to yield imaging biomarkers as surrogates for distinct tumor genotypes and phenotypes. The development of comprehensive glioma imaging markers has potential for improved glioma characterization that would assist in the clinical work-up of preoperative treatment planning and treatment effect monitoring. In particular, the differentiation of tumor recurrence or true progression from pseudoprogression, pseudoresponse, and radiation-induced necrosis can still not reliably be made through standard neuroimaging only. Given the abundant vascular and hemodynamic alterations present in diffuse glioma, advanced hemodynamic imaging approaches constitute an attractive area of clinical imaging development. In this context, the inclusion of objective measurable glioma imaging features may have the potential to enhance the individualized care of diffuse glioma patients, better informing of standard-of-care treatment efficacy and of novel therapies, such as the immunotherapies that are currently increasingly investigated. In Part B of this two-review series, we assess the available evidence pertaining to hemodynamic imaging for molecular feature prediction, in particular focusing on isocitrate dehydrogenase (IDH) mutation status, MGMT promoter methylation, 1p19q codeletion, and EGFR alterations. The results for the differentiation of tumor progression/recurrence from treatment effects have also been the focus of active research and are presented together with the prognostic correlations identified by advanced hemodynamic imaging studies. Finally, the state-of-the-art concepts and advancements of hemodynamic imaging modalities are reviewed together with the advantages derived from the implementation of radiomics and machine learning analyses pipelines.

Local detection of microvessels in IDH-wildtype glioblastoma using relative cerebral blood volume: an imaging marker useful for astrocytoma grade 4 classification

BACKGROUND

The microvessels area (MVA), derived from microvascular proliferation, is a biomarker useful for high-grade glioma classification. Nevertheless, its measurement is costly, labor-intense, and invasive. Finding radiologic correlations with MVA could provide a complementary non-invasive approach without an extra cost and labor intensity and from the first stage. This study aims to correlate imaging markers, such as relative cerebral blood volume (rCBV), and local MVA in IDH-wildtype glioblastoma, and to propose this imaging marker as useful for astrocytoma grade 4 classification.

METHODS

Data from 73 tissue blocks belonging to 17 IDH-wildtype glioblastomas and 7 blocks from 2 IDH-mutant astrocytomas were compiled from the Ivy GAP database. MRI processing and rCBV quantification were carried out using ONCOhabitats methodology. Histologic and MRI co-registration was done manually with experts' supervision, achieving an accuracy of 88.8% of overlay. Spearman's correlation was used to analyze the association between rCBV and microvessel area. Mann-Whitney test was used to study differences of rCBV between blocks with presence or absence of microvessels in IDH-wildtype glioblastoma, as well as to find differences with IDH-mutant astrocytoma samples.

RESULTS

Significant positive correlations were found between rCBV and microvessel area in the IDH-wildtype blocks (p < 0.001), as well as significant differences in rCBV were found between blocks with microvascular proliferation and blocks without it (p < 0.0001). In addition, significant differences in rCBV were found between IDH-wildtype glioblastoma and IDH-mutant astrocytoma samples, being 2-2.5 times higher rCBV values in IDH-wildtype glioblastoma samples.

CONCLUSIONS

The proposed rCBV marker, calculated from diagnostic MRIs, can detect in IDH-wildtype glioblastoma those regions with microvessels from those without it, and it is significantly correlated with local microvessels area. In addition, the proposed rCBV marker can differentiate the IDH mutation status, providing a complementary non-invasive method for high-grade glioma classification.

Lack of Benefit of Extending Temozolomide Treatment in Patients with High Vascular Glioblastoma with Methylated MGMT

In this study, we evaluated the benefit on survival of the combination of methylation of O6-methylguanine-DNA methyltransferase (MGMT) promotor gene and moderate vascularity in glioblastoma using a retrospective dataset of 123 patients from a multicenter cohort. MRI processing and calculation of relative cerebral blood volume (rCBV), used to define moderate- and high-vascular groups, were performed with the automatic ONCOhabitats method. We assessed the previously proposed rCBV threshold (10.7) and the new calculated ones (9.1 and 9.8) to analyze the association with survival for different populations according to vascularity and MGMT methylation status. We found that patients included in the moderate-vascular group had longer survival when MGMT is methylated (significant median survival difference of 174 days, p = 0.0129*). However, we did not find significant differences depending on the MGMT methylation status for the high-vascular group (p = 0.9119). In addition, we investigated the combined correlation of MGMT methylation status and rCBV with the prognostic effect of the number of temozolomide cycles, and only significant results were found for the moderate-vascular group. In conclusion, there is a lack of benefit of extending temozolomide treatment for patients with high vascular glioblastomas, even presenting MGMT methylation. Preliminary results suggest that patients with moderate vascularity and methylated MGMT glioblastomas would benefit more from prolonged adjuvant chemotherapy.

Electrotherapies for Glioblastoma

Non-thermal, intermediate frequency (100-500 kHz) electrotherapies present a unique therapeutic strategy to treat malignant neoplasms. Here, pulsed electric fields (PEFs) which induce reversible or irreversible electroporation (IRE) and tumour-treating fields (TTFs) are reviewed highlighting the foundations, advances, and considerations of each method when applied to glioblastoma (GBM). Several biological aspects of GBM that contribute to treatment complexity (heterogeneity, recurrence, resistance, and blood-brain barrier(BBB)) and electrophysiological traits which are suggested to promote glioma progression are described. Particularly, the biological responses at the cellular and molecular level to specific parameters of the electrical stimuli are discussed offering ways to compare these parameters despite the lack of a universally adopted physical description. Reviewing the literature, a disconnect is found between electrotherapy techniques and how they target the biological complexities of GBM that make treatment difficult in the first place. An attempt is made to bridge the interdisciplinary gap by mapping biological characteristics to different methods of electrotherapy, suggesting important future research topics and directions in both understanding and treating GBM. To the authors' knowledge, this is the first paper that attempts an in-tandem assessment of the biological effects of different aspects of intermediate frequency electrotherapy methods, thus offering possible strategies toward GBM treatment.

Prognostic Prediction Based on Dynamic Contrast-Enhanced MRI and Dynamic Susceptibility Contrast-Enhanced MRI Parameters from Non-Enhancing, T2-High-Signal-Intensity Lesions in Patients with Glioblastoma

Objective

Few attempts have been made to investigate the prognostic value of dynamic contrast-enhanced (DCE) MRI or dynamic susceptibility contrast (DSC) MRI of non-enhancing, T2-high-signal-intensity (T2-HSI) lesions of glioblastoma multiforme (GBM) in newly diagnosed patients. This study aimed to investigate the prognostic values of DCE MRI and DSC MRI parameters from non-enhancing, T2-HSI lesions of GBM.

Materials and Methods

A total of 76 patients with GBM who underwent preoperative DCE MRI and DSC MRI and standard treatment were retrospectively included. Six months after surgery, the patients were categorized into early progression (n = 15) and non-early progression (n = 61) groups. We extracted and analyzed the permeability and perfusion parameters of both modalities for the non-enhancing, T2-HSI lesions of the tumors. The optimal percentiles of the respective parameters obtained from cumulative histograms were determined using receiver operating characteristic (ROC) curve and univariable Cox regression analyses. The results were compared using multivariable Cox proportional hazards regression analysis of progression-free survival.

Results

The 95th percentile value (PV) of Ktrans, mean Ktrans, and median Ve were significant predictors of early progression as identified by the ROC curve analysis (area under the ROC curve [AUC] = 0.704, p = 0.005; AUC = 0.684, p = 0.021; and AUC = 0.670, p = 0.0325, respectively). Univariable Cox regression analysis of the above three parametric values showed that the 95th PV of Ktrans and the mean Ktrans were significant predictors of early progression (hazard ratio [HR] = 1.06, p = 0.009; HR = 1.25, p = 0.017, respectively). Multivariable Cox regression analysis, which also incorporated clinical parameters, revealed that the 95th PV of Ktrans was the sole significant independent predictor of early progression (HR = 1.062, p < 0.009).

Conclusion

The 95th PV of Ktrans from the non-enhancing, T2-HSI lesions of GBM is a potential prognostic marker for disease progression.

DCE-MRI in Glioma, Infiltration Zone and Healthy Brain to Assess Angiogenesis: A Biopsy Study

Purpose

To explore the focal predictability of vascular growth factor expression and neovascularization using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in glioma.

Methods

120 brain biopsies were taken in vital tumor, infiltration zone and normal brain tissue of 30 glioma patients: 17 IDH(isocitrate dehydrogenase)-wildtype glioblastoma (GBM), 1 IDH-wildtype astrocytoma °III (together prognostic group 1), 3 IDH-mutated GBM (group 2), 3 anaplastic astrocytomas IDH-mutated (group 3), 4 anaplastic oligodendrogliomas and 2 low-grade oligodendrogliomas (together prognostic group 4). A mixed linear model evaluated the predictabilities of microvessel density (MVD), vascular area ratio (VAR), mean vessel size (MVS), vascular endothelial growth factor and receptors (VEGF-A, VEGFR‑2) and vascular endothelial-protein tyrosine phosphatase (VE-PTP) expression from Tofts model kinetic and model-free curve parameters.

Results

All kinetic parameters were associated with VEGF‑A (all p < 0.001) expression. K^trans, k_ep and v_e were associated with VAR (p = 0.006, 0.004 and 0.01, respectively) and MVS (p = 0.0001, 0.02 and 0.003, respectively) but not MVD (p = 0.84, 0.74 and 0.73, respectively). Prognostic groups differed in K^trans (p = 0.007) and v_e (p = 0.004) values measured in the infiltration zone. Despite significant differences of VAR, MVS, VEGF‑A, VEGFR‑2, and VE-PTP in vital tumor tissue and the infiltration zone (p = 0.0001 for all), there was no significant difference between kinetic parameters measured in these zones.

Conclusion

The DCE-MRI kinetic parameters show correlations with microvascular parameters in vital tissue and also reveal blood-brain barrier abnormalities in the infiltration zones adequate to differentiate glioma prognostic groups.

Supplementary Information

The online version of this article (10.1007/s00062-021-01015-3) contains supplementary material, which is available to authorized users.

Differential effect of vascularity between long- and short-term survivors with IDH1/2 wild-type glioblastoma

INTRODUCTION

IDH1/2 wt glioblastoma (GB) represents the most lethal tumour of the central nervous system. Tumour vascularity is associated with overall survival (OS), and the clinical relevance of vascular markers, such as rCBV, has already been validated. Nevertheless, molecular and clinical factors may have different influences on the beneficial effect of a favourable vascular signature.

PURPOSE

To evaluate the association between the rCBV and OS of IDH1/2 wt GB patients for long-term survivors (LTSs) and short-term survivors (STSs). Given that initial high rCBV may affect the patient's OS in follow-up stages, we will assess whether a moderate vascularity is beneficial for OS in both groups of patients.

MATERIALS AND METHODS

Ninety-nine IDH1/2 wt GB patients were divided into LTSs (OS ≥ 400 days) and STSs (OS < 400 days). Mann-Whitney and Fisher, uni- and multiparametric Cox, Aalen's additive regression and Kaplan-Meier tests were carried out. Tumour vascularity was represented by the mean rCBV of the high angiogenic tumour (HAT) habitat computed through the haemodynamic tissue signature methodology (available on the ONCOhabitats platform).

RESULTS

For LTSs, we found a significant association between a moderate value of rCBV_mean and higher OS (uni- and multiparametric Cox and Aalen's regression) (p = 0.0140, HR = 1.19; p = 0.0085, HR = 1.22) and significant stratification capability (p = 0.0343). For the STS group, no association between rCBV_mean and survival was observed. Moreover, no significant differences (p > 0.05) in gender, age, resection status, chemoradiation, or MGMT methylation were observed between LTSs and STSs.

CONCLUSION

We have found different prognostic and stratification effects of the vascular marker for the LTS and STS groups. We propose the use of rCBV_mean at HAT as a vascular marker clinically relevant for LTSs with IDH1/2 wt GB and maybe as a potential target for randomized clinical trials focused on this group of patients.

Spatiotemporal habitats from multiparametric physiologic MRI distinguish tumor progression from treatment-related change in post-treatment glioblastoma

OBJECTIVES

We aimed to develop multiparametric physiologic MRI-based spatial habitats and to evaluate whether temporal changes in these habitats help to distinguish tumor progression from treatment-related change in post-treatment glioblastoma.

METHODS

This retrospective, single-institution study included patients with glioblastoma treated by concurrent chemoradiotherapy who had newly developed or enlarging, measurable contrast-enhancing mass. Contrast-enhancing mass was divided into three spatial habitats by K-means clustering of voxel-wise ADC and CBV values. Temporal changes of these habitats between two consecutive examinations prior to the diagnosis of tumor progression or treatment-related change were assessed. Predictors were selected using logistic regression and the performance was measured with an area under the receiver operating characteristics curve (AUC). Spatiotemporal habitats were further analyzed for correlation with the site of tumor progression.

RESULTS

There were 75 patients (mean, 58 years; range, 26-81 years; 43 men) with 48 cases of tumor progression and 39 cases of treatment-related change including 12 patient overlaps at different time points. Three spatial habitats of hypervascular cellular, hypovascular cellular, and nonviable tissue were identified. Increase in the hypervascular cellular (OR 4.55, p = .002) and hypovascular cellular habitat (OR 1.22, p < .001) was predictive of tumor progression. Combination of spatiotemporal habitats yielded a high diagnostic performance with an AUC of 0.89 (95% CI, 0.87-0.92). An increase in hypovascular cellular habitat predicted the site of tumor progression in 84% [21/25] of cases with tumor progression.

CONCLUSIONS

Temporal changes in spatial habitats derived from multiparametric physiologic MRI provided diagnostic value in distinguishing tumor progression from treatment-related change and predicted site of tumor progression in post-treatment glioblastoma.

KEY POINTS

• In post-treatment glioblastoma, three spatial habitats of hypervascular cellular, hypovascular cellular, and nonviable tissue were identified, and an increase in the hypervascular cellular (OR 4.55, p = .002) and hypovascular cellular habitat (OR 1.22, p < .001) was predictive of tumor progression. • Combination of spatiotemporal habitats yielded a high diagnostic performance with an AUC of 0.89 (95% CI, 0.87-0.92). • An increase in hypovascular cellular habitat predicted the site of tumor progression in 84% (21/25) of cases with tumor progression.

Congress of neurological surgeons systematic review and evidence-based guidelines update on the role of emerging developments in the management of newly diagnosed glioblastoma

TARGET POPULATION

These recommendations apply to adult patients with newly diagnosed or suspected glioblastoma.

IMAGING

Question What imaging modalities are in development that may be able to provide improvements in diagnosis, and therapeutic guidance for individuals with newly diagnosed glioblastoma?

RECOMMENDATION

Level III: It is suggested that techniques utilizing magnetic resonance imaging for diffusion weighted imaging, and to measure cerebral blood and magnetic spectroscopic resonance imaging of N-acetyl aspartate, choline and the choline to N-acetyl aspartate index to assist in diagnosis and treatment planning in patients with newly diagnosed or suspected glioblastoma.

SURGERY

Question What new surgical techniques can be used to provide improved tumor definition and resectability to yield better tumor control and prognosis for individuals with newly diagnosed glioblastoma?

RECOMMENDATIONS

Level II: The use of 5-aminolevulinic acid is recommended to improve extent of tumor resection in patients with newly diagnosed glioblastoma. Level II: The use of 5-aminolevulinic acid is recommended to improve median survival and 2 year survival in newly diagnosed glioblastoma patients with clinical characteristics suggesting poor prognosis. Level III: It is suggested that, when available, patients be enrolled in properly designed clinical trials assessing the value of diffusion tensor imaging in improving the safety of patients with newly diagnosed glioblastoma undergoing surgery.

NEUROPATHOLOGY

Question What new pathology techniques and measurement of biomarkers in tumor tissue can be used to provide improved diagnostic ability, and determination of therapeutic responsiveness and prognosis for patients with newly diagnosed glioblastomas?

RECOMMENDATIONS

Level II: Assessment of tumor MGMT promoter methylation status is recommended as a significant predictor of a longer progression free survival and overall survival in patients with newly diagnosed with glioblastoma. Level II: Measurement of tumor expression of neuron-glia-2, neurofilament protein, glutamine synthetase and phosphorylated STAT3 is recommended as a predictor of overall survival in patients with newly diagnosed with glioblastoma. Level III: Assessment of tumor IDH1 mutation status is suggested as a predictor of longer progression free survival and overall survival in patients with newly diagnosed with glioblastoma. Level III: Evaluation of tumor expression of Phosphorylated Mitogen-Activated Protein Kinase protein, EGFR protein, and Insulin-like Growth Factor-Binding Protein-3 is suggested as a predictor of overall survival in patients with newly diagnosed with glioblastoma.

RADIATION

Question What radiation therapy techniques are in development that may be used to provide improved tumor control and prognosis for individuals with newly diagnosed glioblastomas?

RECOMMENDATIONS

Level III: It is suggested that patients with newly diagnosed glioblastoma undergo pretreatment radio-labeled amino acid tracer positron emission tomography to assess areas at risk for tumor recurrence to assist in radiation treatment planning. Level III: It is suggested that, when available, patients be with newly diagnosed glioblastomas be enrolled in properly designed clinical trials of radiation dose escalation, altered fractionation, or new radiation delivery techniques.

CHEMOTHERAPY

Question What emerging chemotherapeutic agents or techniques are available to provide better tumor control and prognosis for patients with newly diagnosed glioblastomas?

RECOMMENDATION

Level III: As no emerging chemotherapeutic agents or techniques were identified in this review that improved tumor control and prognosis it is suggested that, when available, patients with newly diagnosed glioblastomas be enrolled in properly designed clinical trials of chemotherapy.

MOLECULAR AND TARGETED THERAPY

Question What new targeted therapy agents are available to provide better tumor control and prognosis for individuals with newly diagnosed glioblastomas?

RECOMMENDATION

Level III: As no new molecular and targeted therapies have clearly provided better tumor control and prognosis it is suggested that, when available, patients with newly diagnosed glioblastomas be enrolled in properly designed clinical trials of molecular and targeted therapies IMMUNOTHERAPY: Question What emerging immunotherapeutic agents or techniques are available to provide better tumor control and prognosis for patients with newly diagnosed glioblastomas?

RECOMMENDATION

Level III: As no immunotherapeutic agents have clearly provided better tumor control and prognosis it is suggested that, when available, patients with newly diagnosed glioblastomas be enrolled in properly designed clinical trials of immunologically-based therapies.

NOVEL THERAPIES

Question What novel therapies or techniques are in development to provide better tumor control and prognosis for individuals with newly diagnosed glioblastomas?

RECOMMENDATIONS

Level II: The use of tumor-treating fields is recommended for patients with newly diagnosed glioblastoma who have undergone surgical debulking and completed concurrent chemoradiation without progression of disease at the time of tumor-treating field therapy initiation. Level II: It is suggested that, when available, enrollment in properly designed studies of vector containing herpes simplex thymidine kinase gene and prodrug therapies be considered in patients with newly diagnosed glioblastoma.

Higher vascularity at infiltrated peripheral edema differentiates proneural glioblastoma subtype

BACKGROUND AND PURPOSE

Genetic classifications are crucial for understanding the heterogeneity of glioblastoma. Recently, perfusion MRI techniques have demonstrated associations molecular alterations. In this work, we investigated whether perfusion markers within infiltrated peripheral edema were associated with proneural, mesenchymal, classical and neural subtypes.

MATERIALS AND METHODS

ONCOhabitats open web services were used to obtain the cerebral blood volume at the infiltrated peripheral edema for MRI studies of 50 glioblastoma patients from The Cancer Imaging Archive: TCGA-GBM. ANOVA and Kruskal-Wallis tests were carried out in order to assess the association between vascular features and the Verhaak subtypes. For assessing specific differences, Mann-Whitney U-test was conducted. Finally, the association of overall survival with molecular and vascular features was assessed using univariate and multivariate Cox models.

RESULTS

ANOVA and Kruskal-Wallis tests for the maximum cerebral blood volume at the infiltrated peripheral edema between the four subclasses yielded false discovery rate corrected p-values of <0.001 and 0.02, respectively. This vascular feature was significantly higher (p = 0.0043) in proneural patients compared to the rest of the subtypes while conducting Mann-Whitney U-test. The multivariate Cox model pointed to redundant information provided by vascular features at the peripheral edema and proneural subtype when analyzing overall survival.

CONCLUSIONS

Higher relative cerebral blood volume at infiltrated peripheral edema is associated with proneural glioblastoma subtype suggesting underlying vascular behavior related to molecular composition in that area.

A practical method for multimodal registration and assessment of whole-brain disease burden using PET, MRI, and optical imaging

Many neurological diseases present with substantial genetic and phenotypic heterogeneity, making assessment of these diseases challenging. This has led to ineffective treatments, significant morbidity, and high mortality rates for patients with neurological diseases, including brain cancers and neurodegenerative disorders. Improved understanding of this heterogeneity is necessary if more effective treatments are to be developed. We describe a new method to measure phenotypic heterogeneity across the whole rodent brain at multiple spatial scales. The method involves co-registration and localized comparison of in vivo radiologic images (e.g. MRI, PET) with ex vivo optical reporter images (e.g. labeled cells, molecular targets, microvasculature) of optically cleared tissue slices. Ex vivo fluorescent images of optically cleared pathology slices are acquired with a preclinical in vivo optical imaging system across the entire rodent brain in under five minutes, making this methodology practical and feasible for most preclinical imaging labs. The methodology is applied in various examples demonstrating how it might be used to cross-validate and compare in vivo radiologic imaging with ex vivo optical imaging techniques for assessing hypoxia, microvasculature, and tumor growth.

MGMT methylation may benefit overall survival in patients with moderately vascularized glioblastomas

Objectives

To assess the combined role of tumor vascularity, estimated from perfusion MRI, and MGMT methylation status on overall survival (OS) in patients with glioblastoma.

Methods

A multicentric international dataset including 96 patients from NCT03439332 clinical study were used to study the prognostic relationships between MGMT and perfusion markers. Relative cerebral blood volume (rCBV) in the most vascularized tumor regions was automatically obtained from preoperative MRIs using ONCOhabitats online analysis service. Cox survival regression models and stratification strategies were conducted to define a subpopulation that is particularly favored by MGMT methylation in terms of OS.

Results

rCBV distributions did not differ significantly (p > 0.05) in the methylated and the non-methylated subpopulations. In patients with moderately vascularized tumors (rCBV < 10.73), MGMT methylation was a positive predictive factor for OS (HR = 2.73, p = 0.003, AUC = 0.70). In patients with highly vascularized tumors (rCBV > 10.73), however, there was no significant effect of MGMT methylation (HR = 1.72, p = 0.10, AUC = 0.56).

Conclusions

Our results indicate the existence of complementary prognostic information provided by MGMT methylation and rCBV. Perfusion markers could identify a subpopulation of patients who will benefit the most from MGMT methylation. Not considering this information may lead to bias in the interpretation of clinical studies.

Key Points

• MRI perfusion provides complementary prognostic information to MGMT methylation.

• MGMT methylation improves prognosis in glioblastoma patients with moderate vascular profile.

• Failure to consider these relations may lead to bias in the interpretation of clinical studies.

Electronic supplementary material

The online version of this article (10.1007/s00330-020-07297-4) contains supplementary material, which is available to authorized users.

Vascular habitat analysis based on dynamic susceptibility contrast perfusion MRI predicts IDH mutation status and prognosis in high-grade gliomas

OBJECTIVE

The current study aimed to evaluate the clinical practice for hemodynamic tissue signature (HTS) method in IDH genotype prediction in three groups derived from high-grade gliomas.

METHODS

Preoperative MRI examinations of 44 patients with known grade and IDH genotype were assigned into three study groups: glioblastoma multiforme, grade III, and high-grade gliomas. Perfusion parameters were analyzed and were used to automatically draw the four reproducible habitats (high-angiogenic enhancing tumor habitats, low-angiogenic enhancing tumor habitats, infiltrated peripheral edema habitats, vasogenic peripheral edema habitats) related to vascular heterogeneity. These four habitats were then compared between inter-patient with IDH mutation and their wild-type counterparts at these three groups, respectively. The discriminating potential for HTS in assessing IDH mutation status prediction was assessed by ROC curves.

RESULTS

Compared with IDH wild type, IDH mutation had significantly decreased relative cerebral blood volume (rCBV) at the high-angiogenic enhancing tumor habitats and low-angiogenic enhancing tumor habitats. ROC analysis revealed that the rCBVs in habitats had great ability to discriminate IDH mutation from their wild type in all groups. In addition, the Kaplan-Meier survival analysis yielded significant differences for the survival times observed from the populations dichotomized by low (< 4.31) and high (> 4.31) rCBV in the low-angiogenic enhancing tumor habitat.

CONCLUSIONS

The HTS method has been proven to have high prediction capabilities for IDH mutation status in high-grade glioma patients, providing a set of quantifiable habitats associated with tumor vascular heterogeneity.

KEY POINTS

• The HTS method has a high accuracy for molecular stratification prediction for all subsets of HGG. • The HTS method can give IDH mutation-related hemodynamic information of tumor-infiltrated and vasogenic edema. • IDH-relevant rCBV difference in habitats will be a great prognosis factor in HGG.

Multiparameter MRI Predictors of Long-Term Survival in Glioblastoma Multiforme

Standard-of-care multiparameter magnetic resonance imaging (MRI) scans of the brain were used to objectively subdivide glioblastoma multiforme (GBM) tumors into regions that correspond to variations in blood flow, interstitial edema, and cellular density. We hypothesized that the distribution of these distinct tumor ecological "habitats" at the time of presentation will impact the course of the disease. We retrospectively analyzed initial MRI scans in 2 groups of patients diagnosed with GBM, a long-term survival group comprising subjects who survived >36 month postdiagnosis, and a short-term survival group comprising subjects who survived ≤19 month postdiagnosis. The single-institution discovery cohort contained 22 subjects in each group, while the multi-institution validation cohort contained 15 subjects per group. MRI voxel intensities were calibrated, and tumor voxels clustered on contrast-enhanced T1-weighted and fluid-attenuated inversion-recovery (FLAIR) images into 6 distinct "habitats" based on low- to medium- to high-contrast enhancement and low-high signal on FLAIR scans. Habitat 6 (high signal on calibrated contrast-enhanced T1-weighted and FLAIR sequences) comprised a significantly higher volume fraction of tumors in the long-term survival group (discovery cohort, 35% ± 6.5%; validation cohort, 34% ± 4.8%) compared with tumors in the short-term survival group (discovery cohort, 17% ± 4.5%, P < .03; validation cohort, 16 ± 4.0%, P < .007). Of the 6 distinct MRI-defined habitats, the fractional tumor volume of habitat 6 at diagnosis was significantly predictive of long- or short-term survival. We discuss a possible mechanistic basis for this association and implications for habitat-driven adaptive therapy of GBM.

The wavelet power spectrum of perfusion weighted MRI correlates with tumor vascularity in biopsy-proven glioblastoma samples

Background

Wavelet transformed reconstructions of dynamic susceptibility contrast (DSC) MR perfusion (wavelet-MRP) are a new and elegant way of visualizing vascularization. Wavelet-MRP maps yield a clear depiction of hypervascular tumor regions, as recently shown.

Objective

The aim of this study was to elucidate a possible connection of the wavelet-MRP power spectrum in glioblastoma (GBM) with local vascularity and cell proliferation.

Methods

For this IRB-approved study 12 patients (63.0+/-14.9y; 7m) with histologically confirmed IDH-wildtype GBM were included. Target regions for biopsies were prospectively marked on tumor regions as seen on preoperative 3T MRI. During subsequent neurosurgical tumor resection 43 targeted biopsies were taken from these target regions, of which all 27 matching samples were analyzed. All specimens were immunohistochemically analyzed for endothelial cell marker CD31 and proliferation marker Ki67 and correlated to the wavelet-MRP power spectrum as derived from DSC perfusion weighted imaging.

Results

There was a strong correlation between wavelet-MRP power spectrum (median = 4.41) and conventional relative cerebral blood volume (median = 5.97 ml/100g) in Spearman's rank-order correlation (κ = .83, p < .05). In a logistic regression model, the wavelet-MRP power spectrum showed a significant correlation to CD31 dichotomized to no or present staining (p = .04), while rCBV did not show a significant correlation to CD31 (p = .30). No significant association between Ki67 and rCBV or wavelet-MRP was found (p = .62 and p = .70, respectively).

Conclusion

The wavelet-MRP power spectrum derived from existing DSC-MRI data might be a promising new surrogate for tumor vascularity in GBM.

The Impact of MRI Features and Observer Confidence on the Treatment Decision-Making for Patients with Untreated Glioma

In a blind, dual-center, multi-observer setting, we here identify the pre-treatment radiologic features by Magnetic Resonance Imaging (MRI) associated with subsequent treatment options in patients with glioma. Study included 220 previously untreated adult patients from two institutions (94 + 126 patients) with a histopathologically confirmed diagnosis of glioma after surgery. Using a blind, cross-institutional and randomized setup, four expert neuroradiologists recorded radiologic features, suggested glioma grade and corresponding confidence. The radiologic features were scored using the Visually AcceSAble Rembrandt Images (VASARI) standard. Results were retrospectively compared to patient treatment outcomes. Our findings show that patients receiving a biopsy or a subtotal resection were more likely to have a tumor with pathological MRI-signal (by T2-weighted Fluid-Attenuated Inversion Recovery) crossing the midline (Hazard Ratio; HR = 1.30 [1.21–1.87], P < 0.001), and those receiving a biopsy sampling more often had multifocal lesions (HR = 1.30 [1.16–1.64], P < 0.001). For low-grade gliomas (N = 50), low observer confidence in the radiographic readings was associated with less chance of a total resection (P = 0.002) and correlated with the use of a more comprehensive adjuvant treatment protocol (Spearman = 0.48, P < 0.001). This study may serve as a guide to the treating physician by identifying the key radiologic determinants most likely to influence the treatment decision-making process.

Impact on survival of early tumor growth between surgery and radiotherapy in patients with de novo glioblastoma

PURPOSE

Systematic pre-radiotherapy MRI in patients with newly resected glioblastoma (OMS 2016) sometimes reveals tumor growth in the period between surgery and radiotherapy. We evaluated the relation between early tumor growth and overall survival (OS) with the aim of finding predictors of regrowth.

METHODS

Seventy-five patients from 25 to 84 years old (Median age 62 years) with preoperative, immediate postoperative, and preradiotherapy MRI were included. Volumetric measurements were made on each of the three MRI scans and clinical and molecular parameters were collected for each case.

RESULTS

Fifty-four patients (72%) had an early regrowth with a median contrast enhancement volume of 3.61 cm³-range 0.12-71.93 cm³. The median OS was 24 months in patients with no early tumor growth and 17.1 months in those with early tumor regrowth (p = 0.0024). In the population with initial complete resection (27 patients), the median OS was 25.3 months (19 patients) in those with no early tumor growth between surgery and radiotherapy compared to 16.3 months (8 patients) in those with tumor regrowth. In multivariate analysis, the initial extent of resection (p < 0.001) and the delay between postoperative MRI and preradiotherapy MRI (p < 0.001) were significant independent prognostic factors of regrowth and of poorer outcome.

CONCLUSIONS

We demonstrated that, in addition to the well known issue of incomplete resection, longer delays between surgery and adjuvant treatment is an independent factors of tumor regrowth and a risk factor of poorer outcomes for the patients. To overcome the delay factor, we suggest shortening the usual time between surgery and radiotherapy.

Improving the estimation of prognosis for glioblastoma patients by MR based hemodynamic tissue signatures

Advanced MRI and molecular markers have been raised as crucial to improve prognostic models for patients having glioblastoma (GBM) lesions. In particular, different MR perfusion based markers describing vascular intrapatient heterogeneity have been correlated with tumor aggressiveness, and represent key information to understand tumor resistance against effective therapies of these neoplasms. Recently, hemodynamic tissue signature (HTS) markers based on MR perfusion images have been demonstrated to be useful for describing the heterogeneity of GBM at the voxel level, as well as demonstrating significant correlations with the patient's overall survival. In this work, we analyze the abilities of these markers to improve the conventional prognostic models based on clinical, morphological, and demographic features. Our results, in both the regression and classification tests, show that inclusion of the HTS markers improves the reliability of prognostic models. The HTS method is fully automatic and it is available for research use at http://www.oncohabitats.upv.es.