Quantitative multi-modal MR imaging as a non-invasive prognostic tool for patients with recurrent low-grade glioma

Congress of neurological surgeons systematic review and evidence-based guidelines for the role of imaging in newly diagnosed WHO grade II diffuse glioma in adults: update

TARGET POPULATION

Adult patients with suspected or histologically proven WHO Grade II diffuse glioma. QUESTION 1: In adult patients with suspected or histologically proven WHO Grade II diffuse glioma, do advanced MRI techniques using magnetic resonance spectroscopy, perfusion weighted imaging or diffusion weighted imaging provide superior assessment of tumor grade, margins, progression, treatment-related effects, and prognosis compared to standard neuroimaging?

RECOMMENDATION

Level II: The use of diffusion imaging and dynamic susceptibility contrast (DSC), dynamic contrast enhancement (DCE) and arterial spin labeling (ASL) sequences are suggested to differentiate WHO Grade II diffuse glioma from higher grade gliomas when this is not accomplished by T2 weighted and pre- and post-gadolinium contrast enhanced T1 weighted imaging.

LEVEL III

The use of diffusion and perfusion is suggested for obtaining information in genomics, prognosis, and post treatment monitoring when this information would be of value to the clinician and is not obtained through other methods.

LEVEL III

The use of MR Spectroscopy is suggested to differentiate WHO Grade II diffuse glioma from higher grade gliomas when this is not accomplished by standard MRI, perfusion and diffusion techniques and when such information would be of value to the clinician. QUESTION 2: In adult patients with suspected or histologically proven WHO Grade II diffuse glioma, does molecular imaging using amino acid PET tracers provide superior assessment of tumor grade, margins, progression, treatment-related effects, and prognosis compared to standard neuroimaging?

RECOMMENDATION

Level III: If not already evident by MRI studies, the addition of amino acid PET with FET and FDOPA as a tracer is suggested to help determine if a brain lesion is a low grade glioma or high grade glioma.

LEVEL III

If the standard clinical prognostic parameters are unclear and novel PET tracers are available, the clinician may consider FET to assist in determination of prognosis in an individual with grade II diffuse glioma.

LEVEL III

Clinicians may use FDOPA PET in addition to MRI if additional information is required for detection of tumor progression.

Congress of Neurological Surgeons systematic review and evidence‑based guidelines on the management of recurrent diffuse low-grade glioma: update

Target population These recommendations apply to adult patients with recurrent WHO grade 2 infiltrative diffuse glioma (oligodendroglioma, astrocytoma).Questions and Recommendations:Imaging Q1: In adult patients with suspected recurrence of histologically proven WHO grade 2 diffuse glioma, do advanced imaging techniques using magnetic resonance spectroscopy, perfusion weighted imaging, diffusion weighted imaging or PET provide superior assessment of tumor recurrence and histologic progression compared to standard MRI neuroimaging?Recommendation Level III: In adult patients with suspected recurrence of histologically proven WHO grade 2 diffuse glioma, advanced imaging techniques using magnetic resonance spectroscopy, perfusion weighted imaging, diffusion weighted imaging or PET are suggested for identification of tumor recurrence or histologic progression.Pathology Q1: In adult patients with suspected recurrence of histologically proven WHO grade 2 diffuse glioma, is molecular testing for IDH-1, IDH-2, and TP53 Mutations and MGMT promotor methylation mutation warranted for predicting survival and formulating treatment recommendations?Recommendation Level III: It is suggested that IDH mutation status be determined for diagnostic purposes. TP53 mutations occur early in WHO grade 2 diffuse glioma pathogenesis, remain stable, and are not suggested as a marker of predisposition to malignant transformation at recurrence or other measures of prognosis. Assessment of MGMT status is suggested as an adjunct to assessing prognosis. Assessment of CDK2NA status is suggested since this is associated with malignant progression of WHO grade 2 diffuse gliomas.Q2: In adult patients with suspected recurrence of histologically proven WHO Grade 2 diffuse glioma, is testing of proliferation indices (MIB-1 and/or BUdR) warranted for predicting survival and formulating treatment recommendations?Recommendation Level III: It is suggested that proliferative indices (MIB-1 or BUdR) be measured in WHO grade 2 diffuse glioma as higher proliferation indices are associated with increased likelihood of recurrence and shorter progression free and overall survival.Chemotherapy Q1: In adult patients with suspected recurrence of histologically proven WHO grade 2 diffuse glioma, does addition of temozolomide (TMZ), other cytotoxic agents or targeted agents to their treatment regimen improve PFS and/or OS?Recommendation Level III: Temozolomide is suggested in the therapy of recurrent WHO grade 2 diffuse glioma as it may improve clinical symptoms. PCV is suggested in the therapy of WHO grade 2 diffuse glioma at recurrence as it may improve clinical symptoms with the strongest evidence being for oligodendrogliomas. TMZ is suggested as the initial choice for recurrent WHO grade 2 diffuse glioma. Carboplatin is not suggested as there is no significant benefit from carboplatin as single agent therapy for recurrent WHO grade 2 diffuse gliomas. There is insufficient evidence to make any recommendations regarding other agents in the management of recurrent WHO grade 2 diffuse glioma.Radiotherapy Q1: In adult patients with suspected recurrence of histologically proven WHO grade 2 diffuse glioma, does addition of radiotherapy to treatment regimen improve PFS and/or OS?Recommendation Level III: Radiation is suggested at recurrence if there was no previous radiation treatment. Q2: In adult patients with suspected recurrence of histologically proven WHO grade 2 diffuse glioma after previous radiotherapy, does addition of re-irradiation or proton therapy to the treatment regimen improve PFS and/or OS?Recommendation Level III: It is suggested that re-irradiation be considered in the setting of WHO grade 2 diffuse glioma recurrence as it may provide benefit in PFS and OS.Surgery Q1: In adult patients with suspected recurrence of histologically proven WHO grade 2 diffuse glioma, does surgical resection improve PFS and/or OS?. There is insufficient evidence to make any new specific recommendations regarding the value of surgery or extent of resection in relationship to survival for recurrent WHO grade 2 diffuse glioma.

An automated approach for predicting glioma grade and survival of LGG patients using CNN and radiomics

Objectives

To develop and validate an efficient and automatically computational approach for stratifying glioma grades and predicting survival of lower-grade glioma (LGG) patients using an integration of state-of-the-art convolutional neural network (CNN) and radiomics.

Method

This retrospective study reviewed 470 preoperative MR images of glioma from BraTs public dataset (n=269) and Jinling hospital (n=201). A fully automated pipeline incorporating tumor segmentation and grading was developed, which can avoid variability and subjectivity of manual segmentations. First, an integrated approach by fusing CNN features and radiomics features was employed to stratify glioma grades. Then, a deep-radiomics signature based on the integrated approach for predicting survival of LGG patients was developed and subsequently validated in an independent cohort.

Results

The performance of tumor segmentation achieved a Dice coefficient of 0.81. The intraclass correlation coefficients (ICCs) of the radiomics features between the segmentation network and physicians were all over 0.75. The performance of glioma grading based on integrated approach achieved the area under the curve (AUC) of 0.958, showing the effectiveness of the integrated approach. The multivariable Cox regression results demonstrated that the deep-radiomics signature remained an independent prognostic factor and the integrated nomogram showed significantly better performance than the clinical nomogram in predicting overall survival of LGG patients (C-index: 0.865 vs. 0.796, P=0.005).

Conclusion

The proposed integrated approach can be noninvasively and efficiently applied in prediction of gliomas grade and survival. Moreover, our fully automated pipeline successfully achieved computerized segmentation instead of manual segmentation, which shows the potential to be a reproducible approach in clinical practice.

Automated Detection of Brain Tumor through Magnetic Resonance Images Using Convolutional Neural Network

Brain tumor is a fatal disease, caused by the growth of abnormal cells in the brain tissues. Therefore, early and accurate detection of this disease can save patient's life. This paper proposes a novel framework for the detection of brain tumor using magnetic resonance (MR) images. The framework is based on the fully convolutional neural network (FCNN) and transfer learning techniques. The proposed framework has five stages which are preprocessing, skull stripping, CNN-based tumor segmentation, postprocessing, and transfer learning-based brain tumor binary classification. In preprocessing, the MR images are filtered to eliminate the noise and are improve the contrast. For segmentation of brain tumor images, the proposed CNN architecture is used, and for postprocessing, the global threshold technique is utilized to eliminate small nontumor regions that enhanced segmentation results. In classification, GoogleNet model is employed on three publicly available datasets. The experimental results depict that the proposed method is achieved average accuracies of 96.50%, 97.50%, and 98% for segmentation and 96.49%, 97.31%, and 98.79% for classification of brain tumor on BRATS2018, BRATS2019, and BRATS2020 datasets, respectively. The outcomes demonstrate that the proposed framework is effective and efficient that attained high performance on BRATS2020 dataset than the other two datasets. According to the experimentation results, the proposed framework outperforms other recent studies in the literature. In addition, this research will uphold doctors and clinicians for automatic diagnosis of brain tumor disease.

Role of Extracellular Vesicles in Glioma Progression: Deciphering Cellular Biological Processes to Clinical Applications

Glioma predominantly targets glial cells in the brain and spinal cord. There are grade I, II, III, and IV gliomas with anaplastic astrocytoma and glioblastoma multiforme as the most severe forms of the disease. Current diagnostic methods are limited in their data acquisition and interpretation, markedly affecting treatment modalities, and patient outcomes. Circulating extracellular vesicles (EVs) or "magic bullets" contain bioactive signature molecules such as DNA, RNA, proteins, lipids, and metabolites. These secretory "smart probes" participate in myriad cellular activities, including glioma progression. EVs are released by all cell populations and may serve as novel diagnostic biomarkers and efficient nano-vehicles in the targeted delivery of encapsulated therapeutics. The present review describes the potential of EV-based biomarkers for glioma management.

MRS as an Aid to Diagnose Malignant Transformation in Low-Grade Gliomas with Increasing Contrast Enhancement

BACKGROUND AND PURPOSE

Increased contrast enhancement has been used as a marker of malignant transformation in low-grade gliomas. This marker has been found to have limited accuracy because many low-grade gliomas with increased contrast enhancement remain grade II. We aimed to investigate whether MR spectroscopy can contribute to the diagnosis of malignant transformation in low-grade gliomas with increased contrast enhancement.

MATERIALS AND METHODS

Patients with low-grade gliomas who had contemporaneous MR spectroscopy and histopathology for tumor regions with increased contrast enhancement between 2004 and 2015 were retrospectively reviewed. Clinical data collected were sex and age, Karnofsky Performance Scale, histologic subtypes, isocitrate dehydrogenase 1 mutation status, disease duration, adjuvant therapy, and post-radiation therapy duration. Imaging data collected were contrast-enhancement size, whole-tumor size, MR spectroscopy metabolite ratios, and tumor grades of regions with increased contrast enhancement. Diagnostic values of these factors on malignant transformation of low-grade gliomas were statistically analyzed.

RESULTS

A total of 86 patients with 96 MR spectroscopy studies were included. Tumor grades associated with increased contrast enhancement were grade II (n = 42), grade III (n = 27), and grade IV (n = 27). On multivariate analysis, the NAA/Cho ratio was the only significant factor (P < .001; OR, 7.1; 95% CI, 3.2-16.1) diagnostic of malignant transformation. With 0.222 as the cutoff value, the sensitivity, specificity, and accuracy of NAA/Cho for diagnosing malignant transformation were 94.4%, 83.3%, and 89.6%, respectively.

CONCLUSIONS

MR spectroscopy complements conventional MR imaging in the diagnosis of malignant transformation in a subgroup of low-grade gliomas with increased contrast enhancement.

MR image phenotypes may add prognostic value to clinical features in IDH wild-type lower-grade gliomas

PURPOSE

To identify significant prognostic magnetic resonance imaging (MRI) features and their prognostic value when added to clinical features in patients with isocitrate dehydrogenase wild-type (IDHwt) lower-grade gliomas.

MATERIALS AND METHODS

Preoperative MR images of 158 patients (discovery set = 112, external validation set = 46) with IDHwt lower-grade gliomas (WHO grade II or III) were retrospectively analyzed using the Visually Accessible Rembrandt Images feature set. Radiologic risk scores (RRSs) for overall survival were derived from the least absolute shrinkage and selection operator and elastic net. Multivariable Cox regression analysis, including age, Karnofsky Performance score, extent of resection, WHO grade, and RRS, was performed. The added prognostic value of RRS was calculated by comparing the integrated area under the receiver operating characteristic curve (iAUC) between models with and without RRS.

RESULTS

The presence of cysts, pial invasion, and cortical involvement were favorable prognostic factors, while ependymal extension, multifocal or multicentric distribution, nonlobar location, proportion of necrosis > 33%, satellites, and eloquent cortex involvement were significantly associated with worse prognosis. RRS independently predicted survival and significantly enhanced model performance for survival prediction when integrated to clinical features (iAUC increased to 0.773-0.777 from 0.737), which was successfully validated on the validation set (iAUC increased to 0.805-0.830 from 0.735).

CONCLUSION

MRI features associated with prognosis in patients with IDHwt lower-grade gliomas were identified. RRSs derived from MRI features independently predicted survival and significantly improved performance of survival prediction models when integrated into clinical features.

KEY POINTS

• Comprehensive analysis of MRI features conveys prognostic information in patients with isocitrate dehydrogenase wild-type lower-grade gliomas. • Presence of cysts, pial invasion, and cortical involvement of the tumor were favorable prognostic factors. • Radiological phenotypes derived from MRI independently predict survival and have the potential to improve survival prediction when added to clinical features.

Tissue-type mapping of gliomas

Purpose

To develop a statistical method of combining multimodal MRI (mMRI) of adult glial brain tumours to generate tissue heterogeneity maps that indicate tumour grade and infiltration margins.

Materials and methods

We performed a retrospective analysis of mMRI from patients with histological diagnosis of glioma (n = 25). ¹H Magnetic Resonance Spectroscopic Imaging (MRSI) was used to label regions of “pure” low- or high-grade tumour across image types. Normal brain and oedema characteristics were defined from healthy controls (n = 10) and brain metastasis patients (n = 10) respectively. Probability density distributions (PDD) for each tissue type were extracted from intensity normalised proton density and T₂-weighted images, and p and q diffusion maps. Superpixel segmentation and Bayesian inference was used to produce whole-brain tissue-type maps.

Results

Total lesion volumes derived automatically from tissue-type maps correlated with those from manual delineation (p < 0.001, r = 0.87). Large high-grade volumes were determined in all grade III & IV (n = 16) tumours, in grade II gemistocytic rich astrocytomas (n = 3) and one astrocytoma with a histological diagnosis of grade II. For patients with known outcome (n = 20), patients with survival time < 2 years (3 grade II, 2 grade III and 10 grade IV) had a high-grade volume significantly greater than zero (Wilcoxon signed rank p < 0.0001) and also significantly greater high grade volume than the 5 grade II patients with survival >2 years (Mann Witney p = 0.0001). Regions classified from mMRI as oedema had non-tumour-like ¹H MRS characteristics.

Conclusions

¹H MRSI can label tumour tissue types to enable development of a mMRI tissue type mapping algorithm, with potential to aid management of patients with glial tumours.

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Non-Gaussian multimodal MRI characteristics of high and low grade glioma tissue.

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Bayesian inference of multimodal MRI derives whole brain tumour tissue-type maps.

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Automated segmentation of normal and tumour tissue volumes.

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Visualisation of glioma heterogeneity, infiltration, necrosis and vasogenic oedema.

Survival Associations Using Perfusion and Diffusion Magnetic Resonance Imaging in Patients With Histologic and Genetic Defined Diffuse Glioma World Health Organization Grades II and III

OBJECTIVE

According to the new World Health Organization 2016 classification for tumors of the central nervous system, 1p/19q codeletion defines the genetic hallmark that differentiates oligodendrogliomas from diffuse astrocytomas. The aim of our study was to evaluate whether relative cerebral blood volume (rCBV) and apparent diffusion coefficient (ADC) histogram analysis can stratify survival in adult patients with genetic defined diffuse glioma grades II and III.

METHODS

Sixty-seven patients with untreated diffuse gliomas World Health Organization grades II and III and known 1p/19q codeletion status were included retrospectively and analyzed using ADC and rCBV maps based on whole-tumor volume histograms. Overall survival and progression-free survival (PFS) were analyzed by using Kaplan-Meier and Cox survival analyses adjusted for known survival predictors.

RESULTS

Significant longer PFS was associated with homogeneous rCBV distribution-higher rCBVpeak (median, 37 vs 26 months; hazard ratio [HR], 3.2; P = 0.02) in patients with astrocytomas, and heterogeneous rCBV distribution-lower rCBVpeak (median, 46 vs 37 months; HR, 5.3; P < 0.001) and higher rCBVmean (median, 44 vs 39 months; HR, 7.9; P = 0.003) in patients with oligodendrogliomas. Apparent diffusion coefficient parameters (ADCpeak, ADCmean) did not stratify PFS and overall survival.

CONCLUSIONS

Tumors with heterogeneous perfusion signatures and high average values were associated with longer PFS in patients with oligodendrogliomas. On the contrary, heterogeneous perfusion distribution was associated with poor outcome in patients with diffuse astrocytomas.

Relationship of In Vivo MR Parameters to Histopathological and Molecular Characteristics of Newly Diagnosed, Nonenhancing Lower-Grade Gliomas

The goal of this research was to elucidate the relationship between WHO 2016 molecular classifications of newly diagnosed, nonenhancing lower grade gliomas (LrGG), tissue sample histopathology, and magnetic resonance (MR) parameters derived from diffusion, perfusion, and ¹H spectroscopic imaging from the tissue sample locations and the entire tumor. A total of 135 patients were scanned prior to initial surgery, with tumor cellularity scores obtained from 88 image-guided tissue samples. MR parameters were obtained from corresponding sample locations, and histograms of normalized MR parameters within the T2 fluid-attenuated inversion recovery lesion were analyzed in order to evaluate differences between subgroups. For tissue samples, higher tumor scores were related to increased normalized apparent diffusion coefficient (nADC), lower fractional anisotropy (nFA), lower cerebral blood volume (nCBV), higher choline (nCho), and lower N-acetylaspartate (nNAA). Within the T2 lesion, higher tumor grade was associated with higher nADC, lower nFA, and higher Cho to NAA index. Pathological analysis confirmed that diffusion and metabolic parameters increased and perfusion decreased with tumor cellularity. This information can be used to select targets for tissue sampling and to aid in making decisions about treating residual disease.

Integrating Genomics Into Neuro-Oncology Clinical Trials and Practice

Important advances in our understanding of the molecular biology of brain tumors have resulted in a rapid evolution in the taxonomy of central nervous system (CNS) tumors, which culminated in the revised 2016 World Health Organization classification of CNS tumors that incorporates an integrated molecular/histologic diagnostic approach. Our expanding understanding of brain tumor genomics and molecular evolution during the disease course has started to impact clinical management. Furthermore, incorporation of genomic information in ongoing and planned neuro-oncology clinical trials is expected to lead to improved outcomes and result in personalized treatment options for patients with CNS malignancies.

Glioma-Targeted Delivery of a Theranostic Liposome Integrated with Quantum Dots, Superparamagnetic Iron Oxide, and Cilengitide for Dual-Imaging Guiding Cancer Surgery

Herein, a theranostic liposome (QSC-Lip) integrated with superparamagnetic iron oxide nanoparticles (SPIONs) and quantum dots (QDs) and cilengitide (CGT) into one platform is constructed to target glioma under magnetic targeting (MT) for guiding surgical resection of glioma. Transmission electron microscopy and X-ray photoelectron spectroscopy confirm the complete coencapsulation of SPIONs and QDs in liposome. Besides, CGT is also effectively encapsulated into the liposome with an encapsulation efficiency of ∼88.9%. QSC-Lip exhibits a diameter of 100 ± 1.24 nm, zeta potential of -17.10 ± 0.11 mV, and good stability in several mediums. Moreover, each cargo shows a biphasic release pattern from QSC-Lip, a rapid initial release within initial 10 h followed by a sustained release. Cellular uptake of QSC-Lip is significantly enhanced by C₆ cells under MT. In vivo dual-imaging studies show that QSC-Lip not only produces an obvious negative-contrast enhancement effect on glioma by magnetic resonance imaging but also makes tumor emitting fluorescence under MT. The dual-imaging of QSC-Lip guides the accurate resection of glioma by surgery. Besides, CGT is also specifically distributed to glioma after administration of QSC-Lip under MT, resulting in an effective inhibition of tumors. The integrated liposome may be a potential carrier for theranostics of tumor.