The role of imaging in the management of adults with diffuse low grade glioma: A systematic review and evidence-based clinical practice guideline

Diagnostic accuracy of anti-3-[18F]-FACBC PET/MRI in gliomas

PURPOSE

The primary aim was to evaluate whether anti-3-[18F]FACBC PET combined with conventional MRI correlated better with histomolecular diagnosis (reference standard) than MRI alone in glioma diagnostics. The ability of anti-3-[18F]FACBC to differentiate between molecular and histopathological entities in gliomas was also evaluated.

METHODS

In this prospective study, patients with suspected primary or recurrent gliomas were recruited from two sites in Norway and examined with PET/MRI prior to surgery. Anti-3-[18F]FACBC uptake (TBRpeak) was compared to histomolecular features in 36 patients. PET results were then added to clinical MRI readings (performed by two neuroradiologists, blinded for histomolecular results and PET data) to assess the predicted tumor characteristics with and without PET.

RESULTS

Histomolecular analyses revealed two CNS WHO grade 1, nine grade 2, eight grade 3, and 17 grade 4 gliomas. All tumors were visible on MRI FLAIR. The sensitivity of contrast-enhanced MRI and anti-3-[18F]FACBC PET was 61% (95%CI [45, 77]) and 72% (95%CI [58, 87]), respectively, in the detection of gliomas. Median TBRpeak was 7.1 (range: 1.4-19.2) for PET positive tumors. All CNS WHO grade 1 pilocytic astrocytomas/gangliogliomas, grade 3 oligodendrogliomas, and grade 4 glioblastomas/astrocytomas were PET positive, while 25% of grade 2-3 astrocytomas and 56% of grade 2-3 oligodendrogliomas were PET positive. Generally, TBRpeak increased with malignancy grade for diffuse gliomas. A significant difference in PET uptake between CNS WHO grade 2 and 4 gliomas (p < 0.001) and between grade 3 and 4 gliomas (p = 0.002) was observed. Diffuse IDH wildtype gliomas had significantly higher TBRpeak compared to IDH1/2 mutated gliomas (p < 0.001). Adding anti-3-[18F]FACBC PET to MRI improved the accuracy of predicted glioma grades, types, and IDH status, and yielded 13.9 and 16.7 percentage point improvement in the overall diagnoses for both readers, respectively.

CONCLUSION

Anti-3-[18F]FACBC PET demonstrated high uptake in the majority of gliomas, especially in IDH wildtype gliomas, and improved the accuracy of preoperatively predicted glioma diagnoses.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov ID: NCT04111588, URL: https://clinicaltrials.gov/study/NCT04111588.

Low-Grade Gliomas: Histological Subtypes, Molecular Mechanisms, and Treatment Strategies

Low-Grade Gliomas (LGGs) represent a diverse group of brain tumors originating from glial cells, characterized by their unique histopathological and molecular features. This article offers a comprehensive exploration of LGGs, shedding light on their subtypes, histological and molecular aspects. By delving into the World Health Organization's grading system, 5th edition, various specificities were added due to an in-depth understanding of emerging laboratory techniques, especially genomic analysis. Moreover, treatment modalities are extensively discussed. The degree of surgical resection should always be considered according to postoperative quality of life and cognitive status. Adjuvant therapies focused on chemotherapy and radiotherapy depend on tumor grading and invasiveness. In the current literature, emerging targeted molecular therapies are well discussed due to their succinctly therapeutic effect; in our article, those therapies are summarized based on posttreatment results and possible adverse effects. This review serves as a valuable resource for clinicians, researchers, and medical professionals aiming to deepen their knowledge on LGGs and enhance patient care.

Pre-contrast MAGiC in treated gliomas: a pilot study of quantitative MRI

Quantitative MR imaging is becoming more feasible to be used in clinical work since new approaches have been proposed in order to substantially accelerate the acquisition and due to the possibility of synthetically deriving weighted images from the parametric maps. However, their applicability has to be thoroughly validated in order to be included in clinical practice. In this pilot study, we acquired Magnetic Resonance Image Compilation scans to obtain T1, T2 and PD maps in 14 glioma patients. Abnormal tissue was segmented based on conventional images and using a deep learning segmentation technique to define regions of interest (ROIs). The quantitative T1, T2 and PD values inside ROIs were analyzed using the mean, the standard deviation, the skewness and the kurtosis and compared to the quantitative T1, T2 and PD values found in normal white matter. We found significant differences in pre-contrast T1 and T2 values between abnormal tissue and healthy tissue, as well as between T1w-enhancing and non-enhancing regions. ROC analysis was used to evaluate the potential of quantitative T1 and T2 values for voxel-wise classification of abnormal/normal tissue (AUC = 0.95) and of T1w enhancement/non-enhancement (AUC = 0.85). A cross-validated ROC analysis found high sensitivity (73%) and specificity (73%) with AUCs up to 0.68 on the a priori distinction between abnormal tissue with and without T1w-enhancement. These results suggest that normal tissue, abnormal tissue, and tissue with T1w-enhancement are distinguishable by their pre-contrast quantitative values but further investigation is needed.

The Concept of «Peritumoral Zone» in Diffuse Low-Grade Gliomas: Oncological and Functional Implications for a Connectome-Guided Therapeutic Attitude

Diffuse low-grade gliomas (DLGGs) are heterogeneous and poorly circumscribed neoplasms with isolated tumor cells that extend beyond the margins of the lesion depicted on MRI. Efforts to demarcate the glioma core from the surrounding healthy brain led us to define an intermediate region, the so-called peritumoral zone (PTZ). Although most studies about PTZ have been conducted on high-grade gliomas, the purpose here is to review the cellular, metabolic, and radiological characteristics of PTZ in the specific context of DLGG. A better delineation of PTZ, in which glioma cells and neural tissue strongly interact, may open new therapeutic avenues to optimize both functional and oncological results. First, a connectome-based “supratotal” surgical resection (i.e., with the removal of PTZ in addition to the tumor core) resulted in prolonged survival by limiting the risk of malignant transformation, while improving the quality of life, thanks to a better control of seizures. Second, the timing and order of (neo)adjuvant medical treatments can be modulated according to the pattern of peritumoral infiltration. Third, the development of new drugs specifically targeting the PTZ could be considered from an oncological (such as immunotherapy) and epileptological perspective. Further multimodal investigations of PTZ are needed to maximize long-term outcomes in DLGG patients.

Early Surgery Prolongs Professional Activity in IDH Mutant Low-Grade Glioma Patients: A Policy Change Analysis

Background

Until 2015, Dutch guidelines recommended follow-up and biopsy rather than surgery as initial care for suspected low-grade gliomas (LGG). Given evidence that surgery could extend patient survival, our center stopped following this guideline on January 1, 2010 and opted for early maximal safe resection of LGG. The effects of early surgery on the ability of patients to work remains little documented.

Methods

A total of 104 patients operated on at our center between January 2000 and April 2013 and diagnosed with the WHO 2016 grade 2 astrocytoma, IDH mutant or oligodendroglioma, IDH mutant and deleted 1p19q were included. The clinical characteristics, survival, and work history of patients operated on before or after January 2010 were obtained from the patients' records and compared. The minimal follow-up was 8 years.

Results

As per policy change, the interval between radiological diagnosis and first surgery decreased significantly after 2010. Likewise, before 2010, 25.8% of tumors were initially biopsied, 51.6% were resected under anesthesia, and 22.5% under awake conditions versus 14.3%, 23.8%, and 61.9% after this date (p < 0.001). The severity of permanent postoperative neurological deficits decreased after 2010. In total, 82.5% of the patients returned to work postoperatively before 2010 versus 100% after 2010. The postoperative control of epilepsy increased significantly after 2010 (74.4% vs. 47.9%). The median time from diagnosis to a definitive incapacity to work increased by more than 2 years after 2010 (88.7 vs. 62.2 months).

Conclusion

A policy shift towards early aggressive surgical treatment of IDH mutant LGG is safe and prolongs the patients' ability to work.

Intraoperative MR Imaging during Glioma Resection

One of the major issues in the surgical treatment of gliomas is the concern about maximizing the extent of resection while minimizing neurological impairment. Thus, surgical planning by carefully observing the relationship between the glioma infiltration area and eloquent area of the connecting fibers is crucial. Neurosurgeons usually detect an eloquent area by functional MRI and identify a connecting fiber by diffusion tensor imaging. However, during surgery, the accuracy of neuronavigation can be decreased due to brain shift, but the positional information may be updated by intraoperative MRI and the next steps can be planned accordingly. In addition, various intraoperative modalities may be used to guide surgery, including neurophysiological monitoring that provides real-time information (e.g., awake surgery, motor-evoked potentials, and sensory evoked potential); photodynamic diagnosis, which can identify high-grade glioma cells; and other imaging techniques that provide anatomical information during the surgery. In this review, we present the historical and current context of the intraoperative MRI and some related approaches for an audience active in the technical, clinical, and research areas of radiology, as well as mention important aspects regarding safety and types of devices.

What matters for people with brain cancer? Selecting clinical quality indicators for an Australian Brain Cancer Registry

BACKGROUND

The goal of a clinical quality registry is to deliver immediate gains in survival and quality of life by delivering timely feedback to practitioners, thereby ensuring every patient receives the best existing treatment. We are developing an Australian Brain Cancer Registry (ABCR) to identify, describe, and measure the impact of the variation and gaps in brain cancer care from the time of diagnosis to the end of life.

METHODS

To determine a set of clinical quality indicators (CQIs) for the ABCR, a database and internet search were used to identify relevant guidelines, which were then assessed for quality using the AGREE II Global Rating Scale. Potential indicators were extracted from 21 clinical guidelines, ranked using a modified Delphi process completed in 2 rounds by a panel of experts and other stakeholders, and refined by a multidisciplinary Working Group.

RESULTS

Nineteen key quality reporting domains were chosen, specified by 57 CQIs detailing the specific inclusion and outcome characteristics to be reported.

CONCLUSION

The selected CQIs will form the basis for the ABCR, provide a framework for achievable data collection, and specify best practices for patients and health care providers, with a view to improving care for brain cancer patients. To our knowledge, the systematic and comprehensive approach we have taken is a world first in selecting the reporting specifications for a brain cancer clinical registry.

Pseudo-insular glioma syndrome: illustrative cases

BACKGROUND

Lower-grade insular gliomas often appear as expansile and infiltrative masses on magnetic resonance imaging (MRI). However, there are nonneoplastic lesions of the insula, such as demyelinating disease and vasculopathies, that can mimic insular gliomas.

OBSERVATIONS

The authors report two patients who presented with headaches and were found to have mass lesions concerning for lower-grade insular glioma based on MRI obtained at initial presentation. However, on the immediate preoperative MRI obtained a few weeks later, both patients had spontaneous and complete resolution of the insular lesions.

LESSONS

Tumor mimics should always be in the differential diagnosis of brain masses, including those involving the insula. The immediate preoperative MRI (within 24–48 hours of surgery) must be compared carefully with the initial presentation MRI to assess interval change that suggests tumor mimics to avoid unnecessary surgical intervention.

Multiple Survival Outcome Prediction of Glioblastoma Patients Based on Multiparametric MRI

PURPOSE

Construction of radiomics models for the individualized estimation of multiple survival stratification in glioblastoma (GBM) patients using the multiregional information extracted from multiparametric MRI that could facilitate clinical decision-making for GBM patients.

MATERIALS AND METHODS

A total of 134 eligible GBM patients were selected from The Cancer Genome Atlas. These patients were separated into the long-term and short-term survival groups according to the median of individual survival indicators: overall survival (OS), progression-free survival (PFS), and disease-specific survival (DSS). Then, the patients were divided into a training set and a validation set in a ratio of 2:1. Radiomics features (n = 5,152) were extracted from multiple regions of the GBM using multiparametric MRI. Then, radiomics signatures that are related to the three survival indicators were respectively constructed using the analysis of variance (ANOVA) and the least absolute shrinkage and selection operator (LASSO) regression for each patient in the training set. Based on a Cox proportional hazards model, the radiomics model was further constructed by combining the signature and clinical risk factors.

RESULTS

The constructed radiomics model showed a promising discrimination ability to differentiate in the training set and validation set of GBM patients with survival indicators of OS, PFS, and DSS. Both the four MRI modalities and five tumor subregions have different effects on the three survival indicators of GBM. The favorable calibration and decision curve analysis indicated the clinical decision value of the radiomics model. The performance of models of the three survival indicators was different but excellent; the best model achieved C indexes of 0.725, 0.677, and 0.724, respectively, in the validation set.

CONCLUSION

Our results show that the proposed radiomics models have favorable predictive accuracy on three survival indicators and can provide individualized probabilities of survival stratification for GBM patients by using multiparametric and multiregional MRI features.

Variations in the management of diffuse low-grade gliomas-A Scandinavian multicenter study

Background

Early extensive surgery is a cornerstone in treatment of diffuse low-grade gliomas (DLGGs), and an additional survival benefit has been demonstrated from early radiochemotherapy in selected “high-risk” patients. Still, there are a number of controversies related to DLGG management. The objective of this multicenter population-based cohort study was to explore potential variations in diagnostic work-up and treatment between treating centers in 2 Scandinavian countries with similar public health care systems.

Methods

Patients screened for inclusion underwent primary surgery of a histopathologically verified diffuse WHO grade II glioma in the time period 2012 through 2017. Clinical and radiological data were collected from medical records and locally conducted research projects, whereupon differences between countries and inter-hospital variations were explored.

Results

A total of 642 patients were included (male:female ratio 1:4), and annual age-standardized incidence rates were 0.9 and 0.8 per 100 000 in Norway and Sweden, respectively. Considerable inter-hospital variations were observed in preoperative work-up, tumor diagnostics, surgical strategies, techniques for intraoperative guidance, as well as choice and timing of adjuvant therapy.

Conclusions

Despite geographical population-based case selection, similar health care organizations, and existing guidelines, there were considerable variations in DLGG management. While some can be attributed to differences in clinical implementation of current scientific knowledge, some of the observed inter-hospital variations reflect controversies related to diagnostics and treatment. Quantification of these disparities renders possible identification of treatment patterns associated with better or worse outcomes and may thus represent a step toward more uniform evidence-based care.

Establishment of an Immune-Related Gene Signature for Risk Stratification for Patients with Glioma

Glioma is a frequently seen primary malignant intracranial tumor, characterized by poor prognosis. The study is aimed at constructing a prognostic model for risk stratification in patients suffering from glioma. Weighted gene coexpression network analysis (WGCNA), integrated transcriptome analysis, and combining immune-related genes (IRGs) were used to identify core differentially expressed IRGs (DE IRGs). Subsequently, univariate and multivariate Cox regression analyses were utilized to establish an immune-related risk score (IRRS) model for risk stratification for glioma patients. Furthermore, a nomogram was developed for predicting glioma patients' overall survival (OS). The turquoise module (cor = 0.67; P < 0.001) and its genes (n = 1092) were significantly pertinent to glioma progression. Ultimately, multivariate Cox regression analysis constructed an IRRS model based on VEGFA, SOCS3, SPP1, and TGFB2 core DE IRGs, with a C-index of 0.811 (95% CI: 0.786-0.836). Then, Kaplan-Meier (KM) survival curves revealed that patients presenting high risk had a dismal outcome (P < 0.0001). Also, this IRRS model was found to be an independent prognostic indicator of gliomas' survival prediction, with HR of 1.89 (95% CI: 1.252-2.85) and 2.17 (95% CI: 1.493-3.14) in the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) datasets, respectively. We established the IRRS prognostic model, capable of effectively stratifying glioma population, convenient for decision-making in clinical practice.

Intraoperative 3 T MRI is more correlative to residual disease extent than early postoperative MRI

PURPOSE

Extent of resection of low grade glioma (LGG) is an important prognostic variable, and may influence decisions regarding adjuvant therapy in certain patient populations. Immediate postoperative magnetic resonance image (MRI) is the mainstay for assessing residual tumor. However, previous studies have suggested that early postoperative MRI fluid-attenuated inversion recovery (FLAIR) (within 48 h) may overestimate residual tumor volume in LGG. Intraoperative magnetic resonance imaging (iMRI) without subsequent resection may more accurately assess residual tumor. Consistency in MRI techniques and utilization of higher magnet strengths may further improve both comparisons between MRI studies performed at different time points as well as the specificity of MRI findings to identify residual tumor. To evaluate the utility of 3 T iMRI in the imaging of LGG, we volumetrically analyzed intraoperative, early, and late (~ 3 months after surgery) postoperative MRIs after resection of LGG.

METHODS

A total of 32 patients with LGG were assessed retrospectively. Residual tumor was defined as hyperintense T2 signal on FLAIR. Volumetric assessment was performed with intraoperative, early, and late postoperative FLAIR via TeraRecon iNtuition.

RESULTS

Perilesional FLAIR parenchymal abnormality volumes were significantly different comparing intraoperative and early postoperative MRI (2.17 ± 0.45 cm³ vs. 5.47 ± 1.07 cm³, respectively (p = 0.0002)). A significant difference of perilesional FLAIR parenchymal abnormality volumes was also found comparing early and late postoperative MRI (5.47 ± 1.07 cm³ vs. 3.22 ± 0.64 cm³, respectively (p = 0.0001)). There was no significant difference between intraoperative and late postoperative Perilesional FLAIR parenchymal abnormality volumes.

CONCLUSIONS

Intraoperative 3 T MRI without further resection appears to better reflect the volume of residual tumor in LGG compared with early postoperative 3 T MRI. Early postoperative MRI may overestimate residual tumor. As such, intraoperative MRI performed after completion of tumor resection may be more useful for making decisions regarding adjuvant therapy.

5-ALA in Suspected Low-Grade Gliomas: Current Role, Limitations, and New Approaches

Radiologically suspected low-grade gliomas (LGG) represent a special challenge for the neurosurgeon during surgery due to their histopathological heterogeneity and indefinite tumor margin. Therefore, new techniques are required to overcome these current surgical drawbacks. Intraoperative visualization of brain tumors with assistance of 5-aminolevulinic acid (5-ALA) induced protoporphyrin IX (PpIX) fluorescence is one of the major advancements in the neurosurgical field in the last decades. Initially, this technique was exclusively applied for fluorescence-guided surgery of high-grade glioma (HGG). In the last years, the use of 5-ALA was also extended to other indications such as radiologically suspected LGG. Here, we discuss the current role of 5-ALA for intraoperative visualization of focal malignant transformation within suspected LGG. Furthermore, we discuss the current limitations of the 5-ALA technology in pure LGG which usually cannot be visualized by visible fluorescence. Finally, we introduce new approaches based on fluorescence technology for improved detection of pure LGG tissue such as spectroscopic PpIX quantification fluorescence lifetime imaging of PpIX and confocal microscopy to optimize surgery.

Multimodal Disentangled Variational Autoencoder with Game Theoretic Interpretability for Glioma grading

Effective fusion of multimodal magnetic resonance imaging (MRI) is of great significance to boost the accuracy of glioma grading thanks to the complementary information provided by different imaging modalities. However, how to extract the common and distinctive information from MRI to achieve complementarity is still an open problem in information fusion research. In this study, we propose a deep neural network model termed as multimodal disentangled variational autoencoder (MMD-VAE) for glioma grading based on radiomics features extracted from preoperative multimodal MRI images. Specifically, the radiomics features are quantized and extracted from the region of interest for each modality. Then, the latent representations of variational autoencoder for these features are disentangled into common and distinctive representations to obtain the shared and complementary data among modalities. Afterward, cross-modality reconstruction loss and common-distinctive loss are designed to ensure the effectiveness of the disentangled representations. Finally, the disentangled common and distinctive representations are fused to predict the glioma grades, and SHapley Additive exPlanations (SHAP) is adopted to quantitatively interpret and analyze the contribution of the important features to grading. Experimental results on two benchmark datasets demonstrate that the proposed MMD-VAE model achieves encouraging predictive performance (AUC:0.9939) on a public dataset, and good generalization performance (AUC:0.9611) on a cross-institutional private dataset. These quantitative results and interpretations may help radiologists understand gliomas better and make better treatment decisions for improving clinical outcomes.

Accelerated 3D whole-brain T1, T2, and proton density mapping: feasibility for clinical glioma MR imaging

Purpose

Advanced MRI-based biomarkers offer comprehensive and quantitative information for the evaluation and characterization of brain tumors. In this study, we report initial clinical experience in routine glioma imaging with a novel, fully 3D multiparametric quantitative transient-state imaging (QTI) method for tissue characterization based on T1 and T2 values.

Methods

To demonstrate the viability of the proposed 3D QTI technique, nine glioma patients (grade II–IV), with a variety of disease states and treatment histories, were included in this study. First, we investigated the feasibility of 3D QTI (6:25 min scan time) for its use in clinical routine imaging, focusing on image reconstruction, parameter estimation, and contrast-weighted image synthesis. Second, for an initial assessment of 3D QTI-based quantitative MR biomarkers, we performed a ROI-based analysis to characterize T1 and T2 components in tumor and peritumoral tissue.

Results

The 3D acquisition combined with a compressed sensing reconstruction and neural network-based parameter inference produced parametric maps with high isotropic resolution (1.125 × 1.125 × 1.125 mm³ voxel size) and whole-brain coverage (22.5 × 22.5 × 22.5 cm³ FOV), enabling the synthesis of clinically relevant T1-weighted, T2-weighted, and FLAIR contrasts without any extra scan time. Our study revealed increased T1 and T2 values in tumor and peritumoral regions compared to contralateral white matter, good agreement with healthy volunteer data, and high inter-subject consistency.

Conclusion

3D QTI demonstrated comprehensive tissue assessment of tumor substructures captured in T1 and T2 parameters. Aiming for fast acquisition of quantitative MR biomarkers, 3D QTI has potential to improve disease characterization in brain tumor patients under tight clinical time-constraints.

Imaging growth as a predictor of grade of malignancy and aggressiveness of IDH-mutant and 1p/19q-codeleted oligodendrogliomas in adults

BACKGROUND

We quantified the spontaneous imaging growth rate of oligodendrogliomas. We assessed whether (i) it discriminates between World Health Organization (WHO) grade II and grade III oligodendrogliomas, and (ii) grade III oligodendrogliomas with neo-angiogenesis are associated with more fast growth rates (≥8 mm/y).

METHODS

This work employed a retrospective bicentric cohort study (2010-2016) of adult patients harboring a newly diagnosed supratentorial oligodendroglioma, isocitrate dehydrogenase (IDH) mutant and 1p/19q codeleted (WHO 2016 classification), with a minimum of 2 available MRIs before any treatment (minimum 6-week interval) to measure the spontaneous tumor growth rate.

RESULTS

We included 108 patients (age 44.7 ± 14.1 y, 60 males). The tumor growth rate was higher in grade III oligodendrogliomas with neo-angiogenesis (n = 37, median 10.4 mm/y, mean 10.0 ± 6.9) than in grade III oligodendrogliomas with increased mitosis count only (cutoff ≥6 mitoses, n = 18, median 3.9 mm/y, mean 4.5 ± 3.2; P = 0.004), and higher than in grade II oligodendrogliomas (n = 53, median 2.3 mm/y, mean 2.8 ± 2.2; P < 0.001). There was increased prevalence of fast tumor growth rates in grade III oligodendrogliomas with neo-angiogenesis (54.1%) compared with grade III oligodendrogliomas with increased mitosis count only (11.1%; P < 0.001), and in grade II oligodendrogliomas (0.0%; P < 0.001). The tumor growth rate trends did not differ between centers (P = 0.121). Neo-angiogenesis (P < 0.001) and mitosis count at ≥9 (P = 0.013) were independently associated with tumor growth rates ≥8 mm/year. A tumor growth rate ≥8 mm/year was the only predictor independently associated with shorter progression-free survival (P = 0.041).

CONCLUSIONS

The spontaneous tumor growth rate recapitulates oligodendroglioma aggressiveness, permits identification of grade III oligodendrogliomas preoperatively when ≥8 mm/year, and questions the grading by mitosis count.

Guidelines in the management of CNS tumors

INTRODUCTION

Evidence-based, clinical practice guidelines in the management of central nervous system tumors (CNS) continue to be developed and updated through the work of the Joint Section on Tumors of the Congress of Neurological Surgeons (CNS) and the American Association of Neurological Surgeons (AANS).

METHODS

The guidelines are created using the most current and clinically relevant evidence using systematic methodologies, which classify available data and provide recommendations for clinical practice.

CONCLUSION

This update summarizes the Tumor Section Guidelines developed over the last five years for non-functioning pituitary adenomas, low grade gliomas, vestibular schwannomas, and metastatic brain tumors.

IDH-Mutant Low-grade Glioma: Advances in Molecular Diagnosis, Management, and Future Directions

PURPOSE OF REVIEW

IDH-mutant low-grade gliomas (LGG) have emerged as a distinct clinical and molecular entity with unique treatment considerations. Here, we review updates in IDH-mutant LGG diagnosis and classification, imaging biomarkers, therapies, and neurocognitive and patient-reported outcomes.

RECENT FINDINGS

CDKN2A/B homozygous deletion in IDH-mutant astrocytoma is associated with shorter survival, similar to WHO grade 4. The T2-FLAIR mismatch, a highly specific but insensitive sign, is diagnostic of IDH-mutant astrocytoma. Maximal safe resection is currently indicated in all LGG cases. Radiotherapy with subsequent PCV (procarbazine, lomustine, vincristine) provides longer overall survival compared to radiotherapy alone. Temozolomide in place of PCV is reasonable, but high-level evidence is still lacking. LGG adjuvant treatment has important quality of life and neurocognitive side effects that should be considered. Although incurable, IDH-mutant LGG have a favorable survival compared to IDH-WT glioma. Recent advances in molecular-based classification, imaging, and targeted therapies will hopefully improve survival and quality of life.

Assessment of Amide proton transfer weighted (APTw) MRI for pre-surgical prediction of final diagnosis in gliomas

PURPOSE

Radiological assessment of primary brain neoplasms, both high (HGG) and low grade tumors (LGG), based on contrast-enhancement alone can be inaccurate. We evaluated the radiological value of amide proton transfer weighted (APTw) MRI as an imaging complement for pre-surgical radiological diagnosis of brain tumors.

METHODS

Twenty-six patients were evaluated prospectively; (22 males, 4 females, mean age 55 years, range 26-76 years) underwent MRI at 3T using T1-MPRAGE pre- and post-contrast administration, conventional T2w, FLAIR, and APTw imaging pre-surgically for suspected primary/secondary brain tumor. Assessment of the additional value of APTw imaging compared to conventional MRI for correct pre-surgical brain tumor diagnosis. The initial radiological pre-operative diagnosis was based on the conventional contrast-enhanced MR images. The range, minimum, maximum, and mean APTw signals were evaluated. Conventional normality testing was performed; with boxplots/outliers/skewness/kurtosis and a Shapiro-Wilk's test. Mann-Whitney U for analysis of significance for mean/max/min and range APTw signal. A logistic regression model was constructed for mean, max, range and Receiver Operating Characteristic (ROC) curves calculated for individual and combined APTw signals.

RESULTS

Conventional radiological diagnosis prior to surgery/biopsy was HGG (8 patients), LGG (12 patients), and metastasis (6 patients). Using the mean and maximum: APTw signal would have changed the pre-operative evaluation the diagnosis in 8 of 22 patients (two LGGs excluded, two METs excluded). Using a cut off value of >2.0% for mean APTw signal integral, 4 of the 12 radiologically suspected LGG would have been diagnosed as high grade glioma, which was confirmed by histopathological diagnosis. APTw mean of >2.0% and max >2.48% outperformed four separate clinical radiological assessments of tumor type, P-values = .004 and = .002, respectively.

CONCLUSIONS

Using APTw-images as part of the daily clinical pre-operative radiological evaluation may improve diagnostic precision in differentiating LGGs from HGGs, with potential improvement of patient management and treatment.

Clinical Management of Diffuse Low-Grade Gliomas

Diffuse low-grade gliomas (LGG) represent a heterogeneous group of primary brain tumors arising from supporting glial cells and usually affecting young adults. Advances in the knowledge of molecular profile of these tumors, including mutations in the isocitrate dehydrogenase genes, or 1p/19q codeletion, and in neuroradiological techniques have contributed to the diagnosis, prognostic stratification, and follow-up of these tumors. Optimal post-operative management of LGG is still controversial, though radiation therapy and chemotherapy remain the optimal treatments after surgical resection in selected patients. In this review, we report the most important and recent research on clinical and molecular features, new neuroradiological techniques, the different therapeutic modalities, and new opportunities for personalized targeted therapy and supportive care.

Interventions to reduce the time to diagnosis of brain tumours

BACKGROUND

Brain tumours are recognised as one of the most difficult cancers to diagnose because presenting symptoms, such as headache, cognitive symptoms, and seizures, may be more commonly attributable to other, more benign conditions. Interventions to reduce the time to diagnosis of brain tumours include national awareness initiatives, expedited pathways, and protocols to diagnose brain tumours, based on a person's presenting symptoms and signs; and interventions to reduce waiting times for brain imaging pathways. If such interventions reduce the time to diagnosis, it may make it less likely that people experience clinical deterioration, and different treatment options may be available.

OBJECTIVES

To systematically evaluate evidence on the effectiveness of interventions that may influence: symptomatic participants to present early (shortening the patient interval), thresholds for primary care referral (shortening the primary care interval), and time to imaging diagnosis (shortening the secondary care interval and diagnostic interval). To produce a brief economic commentary, summarising the economic evaluations relevant to these interventions.

SEARCH METHODS

For evidence on effectiveness, we searched CENTRAL, MEDLINE, and Embase from January 2000 to January 2020; Clinicaltrials.gov to May 2020, and conference proceedings from 2014 to 2018. For economic evidence, we searched the UK National Health Services Economic Evaluation Database from 2000 to December 2014.

SELECTION CRITERIA

We planned to include studies evaluating any active intervention that may influence the diagnostic pathway, e.g. clinical guidelines, direct access imaging, public health campaigns, educational initiatives, and other interventions that might lead to early identification of primary brain tumours. We planned to include randomised and non-randomised comparative studies. Included studies would include people of any age, with a presentation that might suggest a brain tumour.

DATA COLLECTION AND ANALYSIS

Two review authors independently assessed titles identified by the search strategy, and the full texts of potentially eligible studies. We resolved discrepancies through discussion or, if required, by consulting another review author.

MAIN RESULTS

We did not identify any studies for inclusion in this review. We excluded 115 studies. The main reason for exclusion of potentially eligible intervention studies was their study design, due to a lack of control groups. We found no economic evidence to inform a brief economic commentary on this topic.

AUTHORS' CONCLUSIONS

In this version of the review, we did not identify any studies that met the review inclusion criteria for either effectiveness or cost-effectiveness. Therefore, there is no evidence from good quality studies on the best strategies to reduce the time to diagnosis of brain tumours, despite the prioritisation of research on early diagnosis by the James Lind Alliance in 2015. This review highlights the need for research in this area.

Normative Baseline for Radiomics in Brain MRI: Evaluating the Robustness, Regional Variations, and Reproducibility on FLAIR Images

BACKGROUND

Radiomics in neuroimaging has gained momentum as a noninvasive prediction tool not only to differentiate between types of brain tumors, but also to create phenotypic signatures in neurological and neuropsychiatric disorders. However, there is currently little understating about the robustness and reproducibility of radiomic features in a baseline normative population.

PURPOSE

To investigate the intra- and interscanner reproducibility, spatial robustness, and sensitivity of radiomics on fluid attenuation inversion recovery (FLAIR) images, which are widely used in neuro-oncology investigations.

STUDY TYPE

Retrospective.

POPULATION

Three separate datasets of healthy controls: 1) 87 subjects (age range 12-64 years), 2) intrascanner three timepoints, four subjects, and 3) interscanner, eight subjects at three different sites.

FIELD STRENGTH/SEQUENCE

T₂ -weighted FLAIR at 1.5T and 3.0T.

ASSESSMENT

Spatial variance across lobes, and their relation with age/gender, intra- and inter-scanner reproducibility (with and without site harmonization) of radiomics.

STATISTICAL TESTS

Analysis of variance (ANOVA), interclass correlation (ICC), coefficient of variation (CoV), Bland-Altman analysis.

RESULTS

Analysis of data revealed no differences between genders; however, multiple radiomic features were highly associated with age (P < 0.05). Spatial variability was also evaluated where only 29.04% gray matter and 38.7% white matter features demonstrated an ICC >0.5. Furthermore, the results demonstrated intra-scanner reliability (ICC >0.5); however, inter-scanner reproducibility was poor, with ICC < 0.5 for 82% gray matter and 78.5% white matter features. The inter-scanner reliability improved (ICC < 0.5 for 39.67% gray matter and 38% white matter features) using site-harmonization techniques.

DATA CONCLUSION

These findings suggest that, accounting for age, spatial locations in radiomics-based analysis and use of intersite radiomics harmonization is crucial before interpreting these features for pathological inference. Level of Evidence 3. Technical Efficacy Stage 1. J. MAGN. RESON. IMAGING 2021;53:394-407.

Combination of Magnetic Resonance Spectroscopy and ¹¹C-Methionine Positron Emission Tomography for the Accurate Diagnosis of Non-Enhancing Supratentorial Glioma

OBJECTIVE

To evaluate whether the combination of magnetic resonance spectroscopy (MRS) and ¹¹C-methionine positron emission tomography (¹¹C-MET PET) could increase accurate diagnostic sensitivity for non-enhancing supratentorial gliomas.

MATERIALS AND METHODS

Between February 2012 and December 2017, 109 patients with non-enhanced supratentorial lesions on contrast-enhanced MRI were enrolled. Each patient underwent MRS and ¹¹C-MET PET before treatment. A lesion was considered to be a glioma when either the MRS or ¹¹C-MET PET results reached the diagnostic threshold. The radiological diagnosis was compared with the pathological diagnosis or medical diagnostic criteria.

RESULTS

The sensitivity and specificity were 60.0% and 50.0% for MRS and 75.8% and 50.0% for ¹¹C-MET PET, respectively. Upon combining the two modalities, the sensitivity and specificity of the imaging-based diagnosis prior to surgery reached 89.5% and 42.9%, respectively. Statistically significant differences in the sensitivities were observed between the combined and individual approaches (MRS alone, 89.5% vs. 60.0%, p < 0.001; ¹¹C-MET PET alone, 89.5% vs. 75.8%, p = 0.001). However, no significant differences in specificity were observed between the combined and individual modalities.

CONCLUSION

The combination of MRS and ¹¹C-MET PET findings significantly increases accurate diagnostic sensitivity for non-enhancing supratentorial gliomas without significantly lowering the specificity. This finding suggests the potential of the combined MRS and ¹¹C-MET PET approach in clinical applications.

The biological and clinical basis for early referral of low grade glioma patients to a surgical neuro-oncologist

The discovery of IDH1/2 (isocitrate dehydrogenase) mutation in large scale, genomewide mutational analyses of gliomas has led to profound developments in understanding tumourigenesis, and restructuring of the classification of both high and low grade gliomas. Owing to this progress made in the recognition of molecular markers which predict tumour behavior and treatment response, the increasing importance of adjuvant treatments such as chemo- and radiotherapy, and the tremendous advances in surgical technique and intraoperative monitoring which have facilitated superior extents of resection whilst preserving neurological functioning and quality of life, contemporary management of low grade glioma (LGG) has switched from a passive, observant approach to a more active, interventional one. Furthermore, this has implications for the manner in which patients with incidentally discovered and/or asymptomatic LGG are managed, and this review of the biological behaviour of LGG, as well as its clinical investigation and management, should act as a timely reminder to all clinicians of the importance of referring LGG patients early to a surgical neuro-oncologist who is not only familiar and acquainted with the vagaries of this disease process, but who, in addition, is devoted to delivering care to these patients with the support of a multi-disciplinary clinical decision-making unit, comprising medical neuro-oncologists, radiation oncologists and allied health professionals.

Italian consensus and recommendations on diagnosis and treatment of low-grade gliomas. An intersociety (SINch/AINO/SIN) document

In 2018, the SINch (Italian Society of Neurosurgery) Neuro-Oncology Section, AINO (Italian Association of Neuro-Oncology) and SIN (Italian Association of Neurology) Neuro-Oncology Section formed a collaborative Task Force to look at the diagnosis and treatment of low-grade gliomas (LGGs). The Task Force included neurologists, neurosurgeons, neuro-oncologists, pathologists, radiologists, radiation oncologists, medical oncologists, a neuropsychologist and a methodologist. For operational purposes, the Task Force was divided into five Working Groups: diagnosis, surgical treatment, adjuvant treatments, supportive therapies, and follow-up. The resulting guidance document is based on the available evidence and provides recommendations on diagnosis and treatment of LGG patients, considering all aspects of patient care along their disease trajectory.

Correction to: Advanced imaging in adult diffusely infiltrating low-grade gliomas

The original article [1] contains errors in Table 1 in rows ktrans and Ve; the correct version of Table 1 can be viewed in this Correction article.

MRI Follow-up of Astrocytoma: Automated Coregistration and Color-Coding of FLAIR Sequences Improves Diagnostic Accuracy With Comparable Reading Time

BACKGROUND

MRI follow-up is widely used for longitudinal assessment of astrocytoma, yet reading can be tedious and error-prone, in particular when changes are subtle.

PURPOSE/HYPOTHESIS

To determine the effect of automated, color-coded coregistration (AC) of fluid attenuated inversion recovery (FLAIR) sequences on diagnostic accuracy, certainty, and reading time compared to conventional follow-up MRI assessment of astrocytoma patients.

STUDY TYPE

Retrospective.

POPULATION

In all, 41 patients with neuropathologically confirmed astrocytoma.

FIELD STRENGTH/SEQUENCE

1.0-3.0T/FLAIR ASSESSMENT: The presence or absence of tumor progression was determined based on FLAIR sequences, contrast-enhanced T₁ sequences, and clinical data. Three radiologists assessed 47 MRI study pairs in a conventional reading (CR) and in a second reading supported by AC after 6 weeks. Readers determined the presence/absence of tumor progression and indicated diagnostic certainty on a 5-point Likert scale. Reading time was recorded by an independent assessor.

STATISTICAL TESTS

The Wilcoxon test was used to assess reading time and diagnostic certainty. Differences in diagnostic accuracy, sensitivity, and specificity were analyzed with the McNemar mid-p test.

RESULTS

Readers attained significantly higher overall sensitivity (0.86 vs. 0.75; P < 0.05) and diagnostic accuracy (0.84 vs. 0.73; P < 0.05) for detection of progressive nonenhancing tumor burden when using AC compared to CR. There was a strong trend towards higher specificity within the AC-augmented reading, yet without statistical significance (0.83 vs. 0.71; P = 0.08). Sensitivity for unequivocal disease progression was similarly high in both approaches (AC: 0.94, CR: 0.92), while for marginal disease progressions, it was significantly higher in AC (AC: 0.78, CR: 0.58; P < 0.05). Reading time including application loading time was comparable (AC: 38.1 ± 16.8 sec, CR: 36.0 ± 18.9 s; P = 0.25).

DATA CONCLUSION

Compared to CR, AC improves comparison of FLAIR signal hyperintensity at MRI follow-up of astrocytoma patients, allowing for a significantly higher diagnostic accuracy, particularly for subtle disease progression at a comparable reading time.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY STAGE: 6 J. Magn. Reson. Imaging 2020;52:1197-1206.

One-day protocol for 18F-FDG and 13N-ammonia PET/CT with uptake decoupling score in differentiating untreated low-grade glioma from inflammation

PURPOSE

Accurate identification of low-grade gliomas (LGGs; World Health Organization grades I and II) and their differentiation from brain inflammation lesions (BILs) remains difficult; however, it is essential for treatment. This study assessed whether a one-day protocol for voxel-wise ¹⁸F-FDG and ¹³N-ammonia PET/CT with uptake decoupling analysis could differentiate LGGs from BILs.

MATERIALS AND METHODS

Twenty-eight patients with LGGs and 16 patients with BILs underwent ¹⁸F-FDG and ¹³N-ammonia PET/CT on the same day before any type of therapy. The decoupling score and tumor-to-normal tissue (T/N) ratio of ¹⁸F-FDG and ¹³N-ammonia were calculated at each location. Student's t-test was used to compare values, and ROC curve analysis was used to establish a cut-off value for the T/N ratio and decoupling score. Area under the curve (AUC) was calculated to evaluate differential efficacy.

RESULTS

Significant differences were observed in ¹³N-ammonia T/N ratio (p=0.018) and decoupling score (p=0.003) between LGGs and BILs; however, the ¹⁸F-FDG T/N ratio did not show any differences (p=0.413). Optimal cut-off values for ¹⁸F-FDG T/N ratio, ¹³N-ammonia T/N ratio, and decoupling score were 0.73, 0.97, and 2.31, respectively, with corresponding AUCs of 0.48, 0.68, and 0.77. The respective sensitivity, specificity, and accuracy parameters using these cut-off values were 53.6%, 62.5%, and 56.8%, respectively, for ¹⁸F-FDG; 50.0%, 75.0%, and 59.1%, respectively, for ¹³N-ammonia; and 60.7%, 93.8%, and 72.7%, respectively, for decoupling score.

CONCLUSIONS

¹⁸F-FDG/¹³N-ammonia uptake decoupling score can be used to discriminate between LGGs and BILs. Use of a decoupling map of these two tracers can improve visual analysis and diagnostic accuracy.

High-order radiomics features based on T2 FLAIR MRI predict multiple glioma immunohistochemical features: A more precise and personalized gliomas management

Objective

To investigate the performance of high-order radiomics features and models based on T2-weighted fluid-attenuated inversion recovery (T2 FLAIR) in predicting the immunohistochemical biomarkers of glioma, in order to execute a non-invasive, more precise and personalized glioma disease management.

Methods

51 pathologically confirmed gliomas patients committed in our hospital from March 2015 to June 2018 were retrospective analysis, and Ki-67, vimentin, S-100 and CD34 immunohistochemical data were collected. The volumes of interest (VOIs) were manually sketched and the radiomics features were extracted. Feature reduction was performed by ANOVA+ Mann-Whiney, spearman correlation analysis, least absolute shrinkage and selection operator (LASSO) and Gradient descent algorithm (GBDT). SMOTE technique was used to solve the data bias between two groups. Comprehensive binary logistic regression models were established. Area under the ROC curves (AUC), sensitivity, specificity and accuracy were used to evaluate the predict performance of models. Models reliability were decided according to the standard net benefit of the decision curves.

Results

Four clusters of significant features were screened out and four predicting models were constructed. AUC of Ki-67, S-100, vimentin and CD34 models were 0.713, 0.923, 0.854 and 0.745, respectively. The sensitivities were 0.692, 0.893, 0.875 and 0.556, respectively. The specificities were: 0.667, 0.905, 0.722, and 0.875, with accuracy of 0.660, 0.898, 0.738, and 0.667, respectively. According to the decision curves, the Ki-67, S-100 and vimentin models had reference values.

Conclusion

The radiomics features based on T2 FLAIR can potentially predict the Ki-67, S-100, vimentin and CD34 expression. Radiomics model were expected to be a computer-intelligent, non-invasive, accurate and personalized management method for gliomas.

Interval brain imaging for adults with cerebral glioma

BACKGROUND

Clinical practice guidelines suggest that magnetic resonance imaging (MRI) of the brain should be performed at certain time points or intervals distant from diagnosis (interval or surveillance imaging) of cerebral glioma, to monitor or follow up the disease; it is not known, however, whether these imaging strategies lead to better outcomes among patients than triggered imaging in response to new or worsening symptoms.

OBJECTIVES

To determine the effect of different imaging strategies (in particular, pre-specified interval or surveillance imaging, and symptomatic or triggered imaging) on health and economic outcomes for adults with glioma (grades 2 to 4) in the brain.

SEARCH METHODS

The Cochrane Gynaecological, Neuro-oncology and Orphan Cancers (CGNOC) Group Information Specialist searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE and Embase up to 18 June 2019 and the NHS Economic Evaluation Database (EED) up to December 2014 (database closure).

SELECTION CRITERIA

We included randomised controlled trials, non-randomised controlled trials, and controlled before-after studies with concurrent comparison groups comparing the effect of different imaging strategies on survival and other health outcomes in adults with cerebral glioma; and full economic evaluations (cost-effectiveness analyses, cost-utility analyses and cost-benefit analyses) conducted alongside any study design, and any model-based economic evaluations on pre- and post-treatment imaging in adults with cerebral glioma.

DATA COLLECTION AND ANALYSIS

We used standard Cochrane review methodology with two authors independently performing study selection and data collection, and resolving disagreements through discussion. We assessed the certainty of the evidence using the GRADE approach.

MAIN RESULTS

We included one retrospective, single-institution study that compared post-operative imaging within 48 hours (early post-operative imaging) with no early post-operative imaging among 125 people who had surgery for glioblastoma (GBM: World Health Organization (WHO) grade 4 glioma). Most patients in the study underwent maximal surgical resection followed by combined radiotherapy and temozolomide treatment. Although patient characteristics in the study arms were comparable, the study was at high risk of bias overall. Evidence from this study suggested little or no difference between early and no early post-operative imaging with respect to overall survival (deaths) at one year after diagnosis of GBM (risk ratio (RR) 0.86, 95% confidence interval (CI) 0.61 to 1.21; 48% vs 55% died, respectively; very low certainty evidence) and little or no difference in overall survival (deaths) at two years after diagnosis of GBM (RR 1.06, 95% CI 0.91 to 1.25; 86% vs 81% died, respectively; very low certainty evidence). No other review outcomes were reported. We found no evidence on the effectiveness of other imaging schedules. In addition, we identified no relevant economic evaluations assessing the efficiency of the different imaging strategies.

AUTHORS' CONCLUSIONS

The effect of different imaging strategies on survival and other health outcomes remains largely unknown. Existing imaging schedules in glioma seem to be pragmatic rather than evidence-based. The limited evidence suggesting that early post-operative brain imaging among GBM patients who will receive combined chemoradiation treatment may make little or no difference to survival needs to be further researched, particularly as early post-operative imaging also serves as a quality control measure that may lead to early re-operation if residual tumour is identified. Mathematical modelling of a large glioma patient database could help to distinguish the optimal timing of surveillance imaging for different types of glioma, with stratification of patients facilitated by assessment of individual tumour growth rates, molecular biomarkers and other prognostic factors. In addition, paediatric glioma study designs could be used to inform future research of imaging strategies among adults with glioma.

Advanced imaging in adult diffusely infiltrating low-grade gliomas

The adult diffusely infiltrating low-grade gliomas (LGGs) are typically IDH mutant and slow-growing gliomas having moderately increased cellularity generally without mitosis, necrosis, and microvascular proliferation. Supra-total resection of LGG significantly increases the overall survival by delaying malignant transformation compared with a simple debulking so accurate MR diagnosis is crucial for treatment planning. Data from meta-analysis support the addition of diffusion and perfusion-weighted MR imaging and MR spectroscopy in the diagnosis of suspected LGG. Typically, LGG has lower cellularity (ADCmin), angiogenesis (rCBVmax), capillary permeability (Ktrans), and mitotic activity (Cho/Cr ratio) compared to high-grade glioma. The identification of 2-hydroxyglutarate by MR spectroscopy can reflect the IDH status of the tumor. The initial low ADCmin, high rCBVmax, and Ktrans values are consistent with the poor prognosis. The gradual increase in intratumoral Cho/Cr ratio and rCBVmax values are well correlated with tumor progression. Besides MR-based technical artifacts, which are minimized by the voxel-based assessment of data obtained by histogram analysis, the problems derived from the diversity and the analysis of imaging data should be solved by using artificial intelligence techniques. The quantitative multiparametric MR imaging of LGG can either improve the diagnostic accuracy of their differential diagnosis or assess their prognosis.

Intraoperative MRI and FLAIR Analysis: Implications for low-grade glioma surgery

PURPOSE

Intraoperative MRI (iMRI) offers the possibility of acquiring intraoperatively real-time images that will guide neurosurgeons when removing brain tumors. The objective of this study was to report the existence of FLAIR abnormalities on iMRI that may occur on the margin of a brain resection and may lead to misdiagnosis of residual tumor.

METHODS

We retrospectively analyzed intraoperative MRI (iMRI) in 21 consecutive patients who underwent surgery for a low-grade glioma. Two readers independently reviewed iMRI images to search for the presence of a FLAIR hyperintensity surrounding the surgical cavity. For each patient, they were instructed to characterize FLAIR abnormalities on the margins of the resected area as (1) no FLAIR abnormality; (2) "linear FLAIR hyperintensity (LFH)", when a<5mm linear FLAIR hyperintensity was present; or (3) "nodular FLAIR hyperintensity (NFH)", in the case of a thick and nodular FLAIR hyperintensity.

RESULTS

LFH were present on at least one surgical margin of one third of the patients analyzed with iMRI, and vanished on follow-up MRI, confirming its transient condition; whereas NFH were linked to persistence of pre-surgical abnormalities, such as residual tumor as confirmed or by histopathological analysis of a second surgery or by its remnant on follow-up MRI.

CONCLUSION

Linear FLAIR hyperintensities can be present on surgical margins analyzed by iMRI and should not be mistaken for residual tumor.

Diagnostic accuracy of flat-panel computed tomography in assessing cerebral perfusion in comparison with perfusion computed tomography and perfusion magnetic resonance: a systematic review

Purpose

Flat-panel computed tomography (FP-CT) is increasingly available in angiographic rooms and hybrid OR’s. Considering its easy access, cerebral imaging using FP-CT is an appealing modality for intra-procedural applications. The purpose of this systematic review is to assess the diagnostic accuracy of FP-CT compared with perfusion computed tomography (CTP) and perfusion magnetic resonance (MRP) in cerebral perfusion imaging.

Methods

We performed a systematic literature search in the Cochrane Library, MEDLINE, Embase, and Web of Science up to June 2019 for studies directly comparing FP-CT with either CTP or MRP in vivo. Methodological quality was assessed using the QUADAS-2 tool. Data on diagnostic accuracy was extracted and pooled if possible.

Results

We found 11 studies comparing FP-CT with CTP and 5 studies comparing FP-CT with MRP. Most articles were pilot or feasibility studies, focusing on scanning and contrast protocols. All patients studied showed signs of cerebrovascular disease. Half of the studies were animal trials. Quality assessment showed unclear to high risks of bias and low concerns regarding applicability. Five studies reported on diagnostic accuracy; FP-CT shows good sensitivity (range 0.84–1.00) and moderate specificity (range 0.63–0.88) in detecting cerebral blood volume (CBV) lesions.

Conclusions

Even though FP-CT provides similar CBV values and reconstructed blood volume maps as CTP in cerebrovascular disease, additional studies are required in order to reliably compare its diagnostic accuracy with cerebral perfusion imaging.

Electronic supplementary material

The online version of this article (10.1007/s00234-019-02285-y) contains supplementary material, which is available to authorized users.

Automatic glioma segmentation based on adaptive superpixel

Background

The automatic glioma segmentation is of great significance for clinical practice. This study aims to propose an automatic method based on superpixel for glioma segmentation from the T2 weighted Magnetic Resonance Imaging.

Methods

The proposed method mainly includes three steps. First, we propose an adaptive superpixel generation algorithm based on simple linear iterative clustering version with 0 parameter (ASLIC0). This algorithm can acquire a superpixel image with fewer superpixels and better fit the boundary of region of interest (ROI) by automatically selecting the optimal number of superpixels. Second, we compose a training set by calculating the statistical, texture, curvature and fractal features for each superpixel. Third, Support Vector Machine (SVM) is used to train classification model based on the features of the second step.

Results

The experimental results on Multimodal Brain Tumor Image Segmentation Benchmark 2017 (BraTS2017) show that the proposed method has good segmentation performance. The average Dice, Hausdorff distance, sensitivity, and specificity for the segmented tumor against the ground truth are 0.8492, 3.4697 pixels, 81.47, and 99.64%, respectively. The proposed method shows good stability on high- and low-grade glioma samples. Comparative experimental results show that the proposed method has superior performance.

Conclusions

This provides a close match to expert delineation across all grades of glioma, leading to a fast and reproducible method of glioma segmentation.

A Critical Appraisal of the Quality of Glioma Imaging Guidelines Using the AGREE II Tool: A EuroAIM Initiative

Background: Following the EuroAIM initiative to assess the quality of medical imaging guidelines by using the Appraisal of Guidelines for Research and Evaluation (AGREE) II instrument, we aimed to evaluate the quality of the current imaging guidelines in patients with gliomas.

Methods: A literature search was conducted to identify eligible imaging guidelines considered in the management of adult patients with gliomas. The selected guidelines were evaluated using the AGREE II instrument by four independent appraisers. The agreement among the four appraisers was estimated using the intraclass correlation coefficient (ICC) analysis.

Results: Seven guidelines were selected for the appraisal. Six out of the seven guidelines showed an average level of quality with only one showing a low quality. The highest scores were found in Domain 1 “Scope and purpose” (mean score = 81.2%) and Domain 4 “Clarity of presentation” (mean score = 77.6%). The remaining domains showed a low level of quality and, in particular, Domain 5 “Applicability” was the most critical with a mean score of 41.7%, mainly related to a minor attention to barriers and facilitators as well as costs and resources implications of applying the guidelines. The ICC analysis showed a very good agreement among the four appraisers with ICC values ranging from 0.907 to 0.993.

Conclusions: The available guidelines on glioma imaging emerged as of average quality according to the AGREE II tool analysis. Based on these results, further efforts should be made in order to involve different professional bodies and stakeholders and increase patient and public involvement in any future guideline drafting as well as to improve the applicability of these guidelines into the clinical practice.

MRI combined with PET-CT of different tracers to improve the accuracy of glioma diagnosis: a systematic review and meta-analysis

Based on studies focusing on positron emission tomography (PET)-computed tomography (CT) combined with magnetic resonance imaging (MRI) in the diagnosis of glioma, we conducted a systematic review and meta-analysis evaluating the pros and cons and the accuracy of different examinations. PubMed and Cochrane Library were searched. The search was conducted until April 2017. Two reviewers independently conducted the literature search according to the criteria set initially. Based on the exclusion criteria, 15 articles are included in this study. Of all studies that used MRI examination, there are five involving 18F-fluorodeoxyglucose-PET, five involving 11C-methionine-PET, five involving 18F-fluoro-ethyl-tyrosine-PET, and three involving 18F-fluorothymidine-PET. Due to the limitations such as lack of data, small sample size, and unrepresentative studies, we use a non-quantitative methodology. MRI examination can provide the anatomy information of glioma more clearly. PET-CT examinations based on tumor metabolism using different tracers have more advantages in determining the degree of glioma malignancy and boundaries. However, information provided by PET-CT of different tracers is not the same. With respect to the novel hybrid MRI/PET examination equipment proposed in recent years, the combination of MRI and PET-CT can definitively improve the diagnostic accuracy of glioma.

A quantitative SVM approach potentially improves the accuracy of magnetic resonance spectroscopy in the preoperative evaluation of the grades of diffuse gliomas

Objectives

To investigate the association between proton magnetic resonance spectroscopy (¹H-MRS) metabolic features and the grade of gliomas, and to establish a machine-learning model to predict the glioma grade.

Methods

This study included 112 glioma patients who were divided into the training (n = 74) and validation (n = 38) sets based on the time of hospitalization. Twenty-six metabolic features were extracted from the preoperative ¹H-MRS image. The Student's t-test was conducted to screen for differentially expressed features between low- and high-grade gliomas (WHO grades II and III/IV, respectively). Next, the minimum Redundancy Maximum Relevance (mRMR) algorithm was performed to further select features for a support vector machine (SVM) classifier building. Performance of the predictive model was evaluated both in the training and validation sets using ROC curve analysis.

Results

Among the extracted ¹H-MRS metabolic features, thirteen features were differentially expressed. Four features were further selected as grade-predictive imaging signatures using the mRMR algorithm. The predictive performance of the machine-learning model measured by the AUC was 0.825 and 0.820 in the training and validation sets, respectively. This was better than the predictive performances of individual metabolic features, the best of which was 0.812.

Conclusions

¹H-MRS metabolic features could help in predicting the grade of gliomas. The machine-learning model achieved a better prediction performance in grading gliomas than individual features, indicating that it could complement the traditionally used metabolic features.

•

¹H-MRS metabolic features could help in predicting the grades of gliomas.

•

The machine-learning model performed better than individual metabolic features.

•

The use of machine-learning model can complement the metabolic features.

A radiomics nomogram based on multiparametric MRI might stratify glioblastoma patients according to survival

OBJECTIVES

To construct a radiomics nomogram for the individualized estimation of the survival stratification in glioblastoma (GBM) patients using the multiregional information extracted from multiparametric MRI, which could facilitate the clinical decision-making for GBM patients.

MATERIALS AND METHODS

A total of 105 eligible GBM patients (57 in the long-term and 48 in the short-term survival groups, separated by an overall survival of 12 months) were selected from the Cancer Genome Atlas. These patients were divided into a training set (n = 70) and a validation set (n = 35). Radiomics features (n = 4000) were extracted from multiple regions of the GBM using multiparametric MRI. Then, a radiomics signature was constructed using least absolute shrinkage and selection operator regression for each patient in the training set. Combined with clinical risk factors, a radiomics nomogram was constructed based on a multivariate logistic regression model. The performance of this radiomics nomogram was assessed by calibration, discrimination, and clinical usefulness.

RESULTS

The radiomics signature consisted of 25 selected features and performed better than clinical risk factors (i.e., age, Karnofsky performance status, and treatment strategy) in survival stratification. When the radiomics signature and clinical risk factors were combined, the radiomics nomogram exhibited promising discrimination in the training (C-index, 0.971) and validation (C-index, 0.974) sets. The favorable calibration and decision curve analysis indicated the clinical usefulness of the radiomics nomogram.

CONCLUSIONS

The presented radiomics nomogram, as a non-invasive prediction tool, could exhibit a favorable predictive accuracy and provide individualized probabilities of survival stratification for GBM patients.

KEY POINTS

• Non-invasive survival stratification of GBM patients can be obtained with a radiomics nomogram. • The proposed nomogram constructed by radiomics signature selected from 4000 radiomics features, combined with independent clinical risk factors such as age, Karnofsky performance status, and treatment strategy. • The proposed radiomics nomogram exhibited good calibration and discrimination for survival stratification of GBM patients in both training (C-index, 0.971) and validation (C-index, 0.974) sets.

Diffuse Low-Grade Glioma - Changing Concepts in Diagnosis and Management: A Review

Though diffuse low-grade gliomas (dLGGs) represent only 15% of gliomas, they have been receiving increasing attention in the past decade. Significant advances in knowledge of the natural history and clinical diversity have been documented, and an improved pathological classification of gliomas that integrates histological features with molecular markers has been issued by the WHO. Advances in the radiological assessment of dLGG, particularly new magnetic resonance imaging scanning sequences, allow improved diagnostic and prognostic information. The management paradigms are evolving from “wait and watch” of the past to more active interventional therapy to obviate the risk of malignant transformation. New surgical technologies allow more aggressive surgical resections with a reduction of morbidity. Many reports suggest the association of gross total resection with longer overall survival and progression-free survival in addition to better seizure control. The literature also shows the use of chemotherapeutics and radiation therapy as important adjuncts to surgery. The goals of management have has been increasing survival with increasing stress on quality of life. Our review highlights the recent advances in the molecular diagnosis and management of dLGG with trends toward multidisciplinary and multimodality management of dLGG with an aim to surgically resect the primary disease, followed by chemoradiation in cases of progressive or recurrent disease.

Evidence-based Treatment for Low-grade Glioma

OBJECTIVES

To identify the tumors included in the WHO classification of low-grade gliomas, and review the importance of molecular biomarkers and their implication for treatment, prognosis, and outcomes.

DATA SOURCES

Published research, clinical guidelines, educational articles in oncology journals, and Web-based resources.

CONCLUSION

Molecular neuropathology has influenced the reclassification of low-grade gliomas and, as such, has provided patient-specific treatments with improving outcomes.

IMPLICATIONS FOR NURSING PRACTICE

Nurses play a key role in patient education and communication with the patient's interdisciplinary care team. Understanding the molecular neuropathology that determine treatment recommendations and in turn recognizing and identifying complications provides improved patient/caregiver satisfaction and outcomes.

The effect of glioblastoma heterogeneity on survival stratification: a multimodal MR imaging texture analysis

Background Quantitative evaluation of the effect of glioblastoma (GBM) heterogeneity on survival stratification would be critical for the diagnosis, treatment decision, and follow-up management. Purpose To evaluate the effect of GBM heterogeneity on survival stratification, using texture analysis on multimodal magnetic resonance (MR) imaging. Material and Methods A total of 119 GBM patients (65 in long-term and 54 in short-term survival group, separated by overall survival of 12 months) were selected from the Cancer Genome Atlas, who underwent the T1-weighted (T1W) contrast-enhanced (CE), T1W, T2-weighted (T2W), and FLAIR sequences. For each sequence, the co-occurrence matrix, run-length matrix, and histogram features were extracted to reflect GBM heterogeneity on different scale. The recursive feature elimination based support vector machine was adopted to find an optimal subset. Then the stratification performance of four MR sequences was evaluated, both alone and in combination. Results When each sequence used alone, the T1W-CE sequence performed best, with an area under the receiver operating characteristic curve, accuracy, sensitivity, and specificity of 0.7915, 80.67%, 78.45%, and 83.33%, respectively. When the four sequences combined, the stratification performance was basically equal to that of T1W-CE sequence. In the optimal subset of features extracted from multimodality, those from the T2W sequence weighted the most. Conclusion All the four sequences could reflect heterogeneous distribution of GBM and thereby affect the survival stratification, especially T1W-CE and T2W sequences. However, the stratification performance using only the T1W-CE sequence can be preserved with omission of other three sequences, when investigating the effect of GBM heterogeneity on survival stratification.

Voxel-wise analysis of dynamic 18F-FET PET: a novel approach for non-invasive glioma characterisation

BACKGROUND

Glioma grading with dynamic ¹⁸F-FET PET (0-40 min p.i.) is typically performed by analysing the mean time-activity curve of the entire tumour or a suspicious area within a heterogeneous tumour. This work aimed to ensure a reader-independent glioma characterisation and identification of aggressive sub-volumes by performing a voxel-based analysis with diagnostically relevant kinetic and static ¹⁸F-FET PET parameters. One hundred sixty-two patients with a newly diagnosed glioma classified according to histologic and molecular genetic properties were evaluated. The biological tumour volume (BTV) was segmented in static 20-40 min p.i. ¹⁸F-FET PET images using the established threshold of 1.6 × background activity. For each enclosed voxel, the time-to-peak (TTP), the late slope (Slope_15-40), and the tumour-to-background ratios (TBR_5-15, TBR_20-40) obtained from 5 to 15 min p.i. and 20 to 40 min p.i. images were determined. The percentage portion of these values within the BTV was evaluated with percentage volume fractions (PVFs) and cumulated percentage volume histograms (PVHs). The ability to differentiate histologic and molecular genetic classes was assessed and compared to volume-of-interest (VOI)-based parameters.

RESULTS

Aggressive WHO grades III and IV and IDH-wildtype gliomas were dominated by a high proportion of voxels with an early peak, negative slope, and high TBR, whereby the PVHs with TTP < 20 min p.i., Slope_15-40 < 0 SUV/h, and TBR_5-15 and TBR_20-40 > 2 yielded the most significant differences between glioma grades. We found significant differences of the parameters between WHO grades and IDH mutation status, where the effect size was predominantly higher for voxel-based PVHs compared to the corresponding VOI-based parameters. A low overlap of BTV sub-volumes defined by TTP < 20 min p.i. and negative Slope_15-40 with TBR_5-15 > 2- and TBR_{20-40 > 2}-defined hotspots was observed.

CONCLUSIONS

The presented approach applying voxel-wise analysis of dynamic ¹⁸F-FET PET enables an enhanced characterisation of gliomas and might potentially provide a fast identification of aggressive sub-volumes within the BTV. Parametric 3D ¹⁸F-FET PET information as investigated in this study has the potential to guide individual therapy instrumentation and may be included in future biopsy studies.

Imaging practice in low-grade gliomas among European specialized centers and proposal for a minimum core of imaging

OBJECTIVE

Imaging studies in diffuse low-grade gliomas (DLGG) vary across centers. In order to establish a minimal core of imaging necessary for further investigations and clinical trials in the field of DLGG, we aimed to establish the status quo within specialized European centers.

METHODS

An online survey composed of 46 items was sent out to members of the European Low-Grade Glioma Network, the European Association of Neurosurgical Societies, the German Society of Neurosurgery and the Austrian Society of Neurosurgery.

RESULTS

A total of 128 fully completed surveys were received and analyzed. Most centers (n = 96, 75%) were academic and half of the centers (n = 64, 50%) adhered to a dedicated treatment program for DLGG. There were national differences regarding the sequences enclosed in MRI imaging and use of PET, however most included T1 (without and with contrast, 100%), T2 (100%) and TIRM or FLAIR (20, 98%). DWI is performed by 80% of centers and 61% of centers regularly performed PWI.

CONCLUSION

A minimal core of imaging composed of T1 (w/wo contrast), T2, TIRM/FLAIR, PWI and DWI could be identified. All morphologic images should be obtained in a slice thickness of ≤ 3 mm. No common standard could be obtained regarding advanced MRI protocols and PET.

IMPORTANCE OF THE STUDY

We believe that our study makes a significant contribution to the literature because we were able to determine similarities in numerous aspects of LGG imaging. Using the proposed "minimal core of imaging" in clinical routine will facilitate future cooperative studies.

Low-grade Gliomas

PURPOSE OF REVIEW

Low-grade gliomas present vexing management issues for neuro-oncologists. The relatively long survival compared to other brain tumors makes consideration of treatment toxicity, and thus timing of potentially damaging interventions such as surgery, radiation, and chemotherapy, crucial. Moreover, the rarity of these tumors makes clinical trials to ascertain optimal care challenging.

RECENT FINDINGS

The discovery that most low-grade gliomas harbor isocitrate dehydrogenase (IDH) mutations that confer a favorable prognosis has improved diagnosis and risk stratification of these tumors. Although Level 1 evidence is still lacking, increasing data support the concept of maximal safe tumor debulking as a first step in tumor management. Preliminary results from a large randomized trial suggest chemotherapy is of comparable effectiveness to radiation therapy for one molecular subtype of low-grade glioma. Importantly, however, the final results of a phase 3 trial comparing radiation with or without procarbazine, CCNU (lomustine), and vincristine (PCV) chemotherapy indicate a large survival advantage to combined chemotherapy and radiation, raising questions about using chemotherapy alone as an initial treatment strategy.

SUMMARY

While the combination of radiation and PCV provides the best proven overall survival with low-grade gliomas, important questions remain. These include whether the better-tolerated temozolomide is as effective as PCV in conjunction with radiation therapy and whether the use of initial chemotherapy as a strategy to defer the potential delayed cognitive toxicity associated with radiation will yield acceptable survival results with a favorable toxicity profile.

Sequential Apparent Diffusion Coefficient for Assessment of Tumor Progression in Patients with Low-Grade Glioma

BACKGROUND AND PURPOSE

Early and accurate identification of tumor progression in patients with low-grade gliomas is challenging. We aimed to assess the role of quantitative ADC analysis in the sequential follow-up of patients with low-grade gliomas as a potential imaging marker of tumor stability or progression.

MATERIALS AND METHODS

In this retrospective study, patients with a diagnosis of low-grade glioma with at least 12 months of imaging follow-up were retrospectively reviewed. Two neuroradiologists independently reviewed sequential MR imaging in each patient to determine tumor progression using the Response Assessment in Neuro-Oncology criteria. Normalized mean ADC (ADC_mean) and 10th percentile ADC (ADC₁₀) values from FLAIR hyperintense tumor volume were calculated for each MR image and compared between patients with stable disease versus tumor progression using univariate analysis. The interval change of ADC values between sequential scans was used to differentiate stable disease from progression using the Fisher exact test.

RESULTS

Twenty-eight of 69 patients who were evaluated met our inclusion criteria. Fifteen patients were classified as stable versus 13 patients as having progression based on consensus reads of MRIs and the Response Assessment in Neuro-Oncology criteria. The interval change of ADC values showed greater concordance with ultimate lesion disposition than quantitative ADC values at a single time point. The interval change in ADC₁₀ matched the expected pattern in 12/13 patients with tumor progression (overall diagnostic accuracy of 86%, P <.001). On average, the ADC₁₀ interval change predicted progression 8 months before conventional MR imaging.

CONCLUSIONS

The interval change of ADC₁₀ values can be used to identify progression versus stability of low-grade gliomas with a diagnostic accuracy of 86% and before apparent radiologic progression on conventional MR imaging.

Radiomics strategy for glioma grading using texture features from multiparametric MRI

BACKGROUND

Accurate glioma grading plays an important role in the clinical management of patients and is also the basis of molecular stratification nowadays.

PURPOSE/HYPOTHESIS

To verify the superiority of radiomics features extracted from multiparametric MRI to glioma grading and evaluate the grading potential of different MRI sequences or parametric maps.

STUDY TYPE

Retrospective; radiomics.

POPULATION

A total of 153 patients including 42, 33, and 78 patients with Grades II, III, and IV gliomas, respectively.

FIELD STRENGTH/SEQUENCE

3.0T MRI/T₁ -weighted images before and after contrast-enhanced, T₂ -weighted, multi-b-value diffusion-weighted and 3D arterial spin labeling images.

ASSESSMENT

After multiparametric MRI preprocessing, high-throughput features were derived from patients' volumes of interests (VOIs). The support vector machine-based recursive feature elimination was adopted to find the optimal features for low-grade glioma (LGG) vs. high-grade glioma (HGG), and Grade III vs. IV glioma classification tasks. Then support vector machine (SVM) classifiers were established using the optimal features. The accuracy and area under the curve (AUC) was used to assess the grading efficiency.

STATISTICAL TESTS

Student's t-test or a chi-square test were applied on different clinical characteristics to confirm whether intergroup significant differences exist.

RESULTS

Patients' ages between LGG and HGG groups were significantly different (P < 0.01). For each patient, 420 texture and 90 histogram parameters were derived from 10 VOIs of multiparametric MRI. SVM models were established using 30 and 28 optimal features for classifying LGGs from HGGs and grades III from IV, respectively. The accuracies/AUCs were 96.8%/0.987 for classifying LGGs from HGGs, and 98.1%/0.992 for classifying grades III from IV, which were more promising than using histogram parameters or using the single sequence MRI.

DATA CONCLUSION

Texture features were more effective for noninvasively grading gliomas than histogram parameters. The combined application of multiparametric MRI provided a higher grading efficiency. The proposed radiomic strategy could facilitate clinical decision-making for patients with varied glioma grades.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;48:1518-1528.

Glioma imaging in Europe: A survey of 220 centres and recommendations for best clinical practice

Objectives

At a European Society of Neuroradiology (ESNR) Annual Meeting 2015 workshop, commonalities in practice, current controversies and technical hurdles in glioma MRI were discussed. We aimed to formulate guidance on MRI of glioma and determine its feasibility, by seeking information on glioma imaging practices from the European Neuroradiology community.

Methods

Invitations to a structured survey were emailed to ESNR members (n=1,662) and associates (n=6,400), European national radiologists’ societies and distributed via social media.

Results

Responses were received from 220 institutions (59% academic). Conventional imaging protocols generally include T2w, T2-FLAIR, DWI, and pre- and post-contrast T1w. Perfusion MRI is used widely (85.5%), while spectroscopy seems reserved for specific indications. Reasons for omitting advanced imaging modalities include lack of facility/software, time constraints and no requests. Early postoperative MRI is routinely carried out by 74% within 24–72 h, but only 17% report a percent measure of resection. For follow-up, most sites (60%) issue qualitative reports, while 27% report an assessment according to the RANO criteria. A minority of sites use a reporting template (23%).

Conclusion

Clinical best practice recommendations for glioma imaging assessment are proposed and the current role of advanced MRI modalities in routine use is addressed.

Key Points

• We recommend the EORTC-NBTS protocol as the clinical standard glioma protocol.

• Perfusion MRI is recommended for diagnosis and follow-up of glioma.

• Use of advanced imaging could be promoted with increased education activities.

• Most response assessment is currently performed qualitatively.

• Reporting templates are not widely used, and could facilitate standardisation.

Electronic supplementary material

The online version of this article (10.1007/s00330-018-5314-5) contains supplementary material, which is available to authorized users.

Brain Tumor Characterization Using Multibiometric Evaluation of MRI

The aim was to evaluate volume, diffusion, and perfusion metrics for better presurgical differentiation between high-grade gliomas (HGG), low-grade gliomas (LGG), and metastases (MET). For this retrospective study, 43 patients with histologically verified intracranial HGG (n = 18), LGG (n = 10), and MET (n = 15) were chosen. Preoperative magnetic resonance data included pre- and post-gadolinium contrast-enhanced T1-weighted fluid-attenuated inversion recover, cerebral blood flow (CBF), cerebral blood volume (CBV), fractional anisotropy, and apparent diffusion coefficient maps used for quantification of magnetic resonance biometrics by manual delineation of regions of interest. A binary logistic regression model was applied for multiparametric analysis and receiver operating characteristic (ROC) analysis. Statistically significant differences were found for normalized-ADC-tumor (nADC-T), normalized-CBF-tumor (nCBF-T), normalized-CBV-tumor (nCBV-T), and normalized-CBF-edema (nCBF-E) between LGG and HGG, and when these metrics were combined, HGG could be distinguished from LGG with a sensitivity and specificity of 100%. The only metric to distinguish HGG from MET was the normalized-ADC-E with a sensitivity of 68.8% and a specificity of 80%. LGG can be distinguished from MET by combining edema volume (Vol-E), Vol-E/tumor volume (Vol-T), nADC-T, nCBF-T, nCBV-T, and nADC-E with a sensitivity of 93.3% and a specificity of 100%. The present study confirms the usability of a multibiometric approach including volume, perfusion, and diffusion metrics in differentially diagnosing brain tumors in preoperative patients and adds to the growing body of evidence in the clinical field in need of validation and standardization.

Visual and semiquantitative 11C-methionine PET: an independent prognostic factor for survival of newly diagnosed and treatment-naïve gliomas

Background

Few data exist regarding the prognostic value of L-[S-methyl-11C]methionine (MET) PET for treatment-naïve gliomas.

Methods

A total of 160 glioma patients (89 men, 71 women; mean age: 45, range 18-84 y) underwent a MET PET prior to any therapy. The PET scans were evaluated visually and semiquantitatively by tumor-to-background (T/N) ratio thresholds chosen by analysis of receiver operating characteristics. Additionally, isocitrate dehydrogenase 1-R132H (IDH1-R132H) immunohistochemistry was performed. Survival analysis was done using Kaplan-Meier estimates and the Cox proportional hazards model.

Results

Significantly shorter mean survival times (7.2 vs 8.6 y; P = 0.024) were seen in patients with amino acid avid gliomas (n = 137) compared with visually negative tumors (n = 33) in MET PET. T/N ratio thresholds of 2.1 and 3.5 were significantly associated with survival (10.3 vs 7 vs 4.3 y; P < 0.001). Mean survival differed significantly using the median T/N ratio of 2.4 as cutoff, independent of histopathology (P < 0.01; mean survival: 10.2 ± 0.8 y vs 5.5 ± 0.6 y). In the subgroup of 142 glioma patients characterized by IDH1-R132H status, METT/N ratio demonstrated a significant prognostic impact in IDH1-R132H wildtype astrocytomas and glioblastoma (P = 0.001). Additionally, multivariate testing revealed semiquantitative MET PET as an independent prognostic parameter for treatment-naïve glioma patients without (P = 0.031) and with IDH1-R132H characterization of gliomas (P = 0.024; odds ratio 1.57).

Conclusion

This retrospective analysis demonstrates the value of MET PET as a prognostic parameter on survival in treatment-naïve glioma patients.