Discrimination between Glioma Grades II and III Using Dynamic Susceptibility Perfusion MRI: A Meta-Analysis

Beyond conventional imaging: Advancements in MRI for glioma malignancy prediction and molecular profiling

This review examines the advancements in magnetic resonance imaging (MRI) techniques and their pivotal role in diagnosing and managing gliomas, the most prevalent primary brain tumors. The paper underscores the importance of integrating modern MRI modalities, such as diffusion-weighted imaging and perfusion MRI, which are essential for assessing glioma malignancy and predicting tumor behavior. Special attention is given to the 2021 WHO Classification of Tumors of the Central Nervous System, emphasizing the integration of molecular diagnostics in glioma classification, significantly impacting treatment decisions. The review also explores radiogenomics, which correlates imaging features with molecular markers to tailor personalized treatment strategies. Despite technological progress, MRI protocol standardization and result interpretation challenges persist, affecting diagnostic consistency across different settings. Furthermore, the review addresses MRI's capacity to distinguish between tumor recurrence and pseudoprogression, which is vital for patient management. The necessity for greater standardization and collaborative research to harness MRI's full potential in glioma diagnosis and personalized therapy is highlighted, advocating for an enhanced understanding of glioma biology and more effective treatment approaches.

Statistical plots in oncologic imaging, a primer for neuroradiologists

The simplest approach to convey the results of scientific analysis, which can include complex comparisons, is typically through the use of visual items, including figures and plots. These statistical plots play a critical role in scientific studies, making data more accessible, engaging, and informative. A growing number of visual representations have been utilized recently to graphically display the results of oncologic imaging, including radiomic and radiogenomic studies. Here, we review the applications, distinct properties, benefits, and drawbacks of various statistical plots. Furthermore, we provide neuroradiologists with a comprehensive understanding of how to use these plots to effectively communicate analytical results based on imaging data.

Simultaneous quantification of perfusion, permeability, and leakage effects in brain gliomas using dynamic spin-and-gradient-echo echoplanar imaging MRI

OBJECTIVE

To determine the feasibility and biologic correlations of dynamic susceptibility contrast (DSC), dynamic contrast enhanced (DCE), and quantitative maps derived from contrast leakage effects obtained simultaneously in gliomas using dynamic spin-and-gradient-echo echoplanar imaging (dynamic SAGE-EPI) during a single contrast injection.

MATERIALS AND METHODS

Thirty-eight patients with enhancing brain gliomas were prospectively imaged with dynamic SAGE-EPI, which was processed to compute traditional DSC metrics (normalized relative cerebral blood flow [nrCBV], percentage of signal recovery [PSR]), DCE metrics (volume transfer constant [Ktrans], extravascular compartment [ve]), and leakage effect metrics: ΔR2,ss* (reflecting T2*-leakage effects), ΔR1,ss (reflecting T1-leakage effects), and the transverse relaxivity at tracer equilibrium (TRATE, reflecting the balance between ΔR2,ss* and ΔR1,ss). These metrics were compared between patient subgroups (treatment-naïve [TN] vs recurrent [R]) and biological features (IDH status, Ki67 expression).

RESULTS

In IDH wild-type gliomas (IDHwt-i.e., glioblastomas), previous exposure to treatment determined lower TRATE (p = 0.002), as well as higher PSR (p = 0.006), Ktrans (p = 0.17), ΔR1,ss (p = 0.035), ve (p = 0.006), and ADC (p = 0.016). In IDH-mutant gliomas (IDHm), previous treatment determined higher Ktrans and ΔR1,ss (p = 0.026). In TN-gliomas, dynamic SAGE-EPI metrics tended to be influenced by IDH status (p ranging 0.09-0.14). TRATE values above 142 mM-1s-1 were exclusively seen in TN-IDHwt, and, in TN-gliomas, this cutoff had 89% sensitivity and 80% specificity as a predictor of Ki67 > 10%.

CONCLUSIONS

Dynamic SAGE-EPI enables simultaneous quantification of brain tumor perfusion and permeability, as well as mapping of novel metrics related to cytoarchitecture (TRATE) and blood-brain barrier disruption (ΔR1,ss), with a single contrast injection.

CLINICAL RELEVANCE STATEMENT

Simultaneous DSC and DCE analysis with dynamic SAGE-EPI reduces scanning time and contrast dose, respectively alleviating concerns about imaging protocol length and gadolinium adverse effects and accumulation, while providing novel leakage effect metrics reflecting blood-brain barrier disruption and tumor tissue cytoarchitecture.

KEY POINTS

• Traditionally, perfusion and permeability imaging for brain tumors requires two separate contrast injections and acquisitions. • Dynamic spin-and-gradient-echo echoplanar imaging enables simultaneous perfusion and permeability imaging. • Dynamic spin-and-gradient-echo echoplanar imaging provides new image contrasts reflecting blood-brain barrier disruption and cytoarchitecture characteristics.

Multiparametric MRI and T2/FLAIR mismatch complements the World Health Organization 2021 classification for the diagnosis of IDH-mutant 1p/19q non-co-deleted/ATRX-mutant astrocytoma

AIM

To investigate whether T2-weighted imaging-fluid-attenuated inversion recovery (T2/FLAIR) mismatch, T2∗ dynamic susceptibility contrast (DSC) perfusion, and magnetic resonance spectroscopy (MRS) correlated with the histological diagnosis and grading of IDH (isocitrate dehydrogenase)-mutant, 1p/19q non-co-deleted/ATRX (alpha-thalassemia mental retardation X-linked)-mutant astrocytoma.

MATERIALS

Imaging of 101 IDH-mutant diffuse glioma cases of histological grades 2-3 (2019-2021) were analysed retrospectively by two neuroradiologists blinded to the molecular diagnosis. T2/FLAIR mismatch sign is used for radio-phenotyping, and pre-biopsy multiparametric MRI images were assessed for grading purposes. Cut-off values pre-determined for radiologically high-grade lesions were relative cerebral blood volume (rCBV) ≥2, choline/creatine ratio (Cho/Cr) ≥1.5 (30 ms echo time [TE]), Cho/Cr ≥1.8 (135 ms TE).

RESULTS

Sixteen of the 101 cases showed T2/FLAIR mismatch, all of which were histogenetically confirmed IDH-mutant 1p/19q non-co-deleted/ATRX mutant astrocytomas; 50% were grade 3 (8/16) and 50% grade 2 (8/16). None showed contrast enhancement. Nine of the 16 had adequate multiparametric MRI for analysis. Any positive value by combining rCBV ≥2 with Cho/Cr ≥1.5 (30 ms TE) or Cho/Cr ≥1.8 (135 ms TE) predicted grade 3 histology with sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 100%.

CONCLUSION

The T2/FLAIR mismatch sign detected diffuse astrocytomas with 100% specificity. When combined with high Cho/Cr and raised rCBV, this predicted histological grading with high accuracy. The future direction for imaging should explore a similar integrated layered approach of 2021 classification of central nervous system (CNS) tumours combining radio-phenotyping and grading from structural and multiparametric imaging.

Diffusion heterogeneity and vascular perfusion in tumor and peritumoral areas for prediction of overall survival in patients with high-grade glioma

OBJECTIVE

To evaluation of diffusion heterogeneity and vascular perfusion in tumor and peritumoral areas for prognostic prediction in high-grade glioma (HGG, WHO III/IV grade).

METHODS

Forty patients with HGG underwent diffusion kurtosis imaging (DKI), intravoxel incoherent motion (IVIM), and arterial spin labeling (ASL) MRI before operation. After normalization, the parameters were divided into diffusion heterogeneity parameters (rD, rMD, rMK, rKr, rKa) and vascular perfusion parameters (rD*, rF, rCBF). Univariate and multivariate Cox regression analyses were used to evaluate associations between overall survival (OS) and the above parameters, clinical factors, and IDH1 status. The Mann-Whitney test was used to evaluate differences in the parameters between different IDH1 states.

RESULTS

In the univariate Cox regression analysis, OS was significantly associated with tumor resection range, IDH1 status, tumor heterogeneity parameters (rD, rMD, rMK, rKr, rKa), and rCBF in tumor area(all p < 0.05). In addition, rD and rCBF measured in the peritumoral region were also predictors of poor OS (both p < 0.01). Multivariate Cox regression analysis indicated that rMK in the tumor area and rCBF in the peritumoral area (hazard ratio = 7.900 and 5.466, respectively, for each 0.1 increase in the normalized value) were independent predictors of OS.

CONCLUSION

The rMK of tumor area and rCBF of peritumoral area had independent predictive value for OS in patients with HGG.

ADVANCES IN KNOWLEDGE

This study explored useful imaging biomarkers from the diffusion heterogeneity and vascular perfusion of tumor and peritumoral areas in HGG, which is useful to help clinician to make precise therapeutic plans, and predict the prognostic for glioma patients.

Primary brain tumours in adults

The most frequent adult-type primary CNS tumours are diffuse gliomas, but a large variety of rarer CNS tumour types exists. The classification of these tumours is increasingly based on molecular diagnostics, which is reflected in the extensive molecular foundation of the recent WHO 2021 classification of CNS tumours. Resection as extensive as is safely possible is the cornerstone of treatment in most gliomas, and is now also recommended early in the treatment of patients with radiological evidence of histologically low-grade tumours. For the adult-type diffuse glioma, standard of care is a combination of radiotherapy and chemotherapy. Although treatment with curative intent is not available, combined modality treatment has resulted in long-term survival (>10-20 years) for some patients with isocitrate dehydrogenase (IDH) mutant tumours. Other rarer tumours require tailored approaches, best delivered in specialised centres. Targeted treatments based on molecular alterations still only play a minor role in the treatment landscape of adult-type diffuse glioma, and today are mainly limited to patients with tumours with BRAFV600E (ie, Val600Glu) mutations. Immunotherapy for CNS tumours is still in its infancy, and so far, trials with checkpoint inhibitors and vaccination studies have not shown improvement in patient outcomes in glioblastoma. Current research is focused on improving our understanding of the immunosuppressive tumour environment, the molecular heterogeneity of tumours, and the role of tumour microtube network connections between cells in the tumour microenvironment. These factors all appear to play a role in treatment resistance, and indicate that novel approaches are needed to further improve outcomes of patients with CNS tumours.

Dynamic susceptibility contrast perfusion-weighted and diffusion-weighted magnetic resonance imaging findings in pilocytic astrocytoma and H3.3 and H3.1 variant diffuse midline glioma, H3K27-altered

OBJECTIVE

This study compared the dynamic susceptibility contrast (DSC) magnetic resonance imaging parameters and apparent diffusion coefficient (ADC) between pilocytic astrocytoma (PA) and diffuse midline glioma, H3K27-altered (DMG) variants.

METHODS

The normalized relative cerebral blood volume (nrCBV), normalized relative flow (nrCBF), percentile signal recovery (PSR), and normalized mean ADC (nADCmean) of 23 patients with midline PAs (median age, 13 years [range, 1-71 years]; 13 female patients) and 40 patients with DMG (8.5 years [1-35 years]; 19 female patients), including 35 patients with H3.3- and five patients with H3.1-mutant tumors, treated between January 2016 and May 2022 were statistically compared.

RESULTS

DMG had a significantly lower nADCmean (median: 1.48 vs. 1.96; p = 0.00075) and lower PSR (0.97 vs. 1.23, p = 0.13) but higher nrCBV and nrCBF (1.66 vs. 1.17, p = 0.058, respectively, and 1.87 vs. 1.19, p = 0.028, respectively) than PA. The H3.3 variant had a lower nADCmean than the H3.1 variant (1.46 vs. 1.80, p = 0.10).

CONCLUSION

DMG had lower ADC and PSR and higher rCBV and rCBF than PA. The H3.3 variant had a lower ADC than the H3.1 variant. Recognizing the differences and similarities in the DSC parameters and ADC between these tumors may help presurgical diagnosis.

Differentiation of astrocytoma between grades II and III using a combination of methionine positron emission tomography and magnetic resonance spectroscopy

Objective

This study aimed to establish a method for differentiating between grades II and III astrocytomas using preoperative imaging.

Methods

We retrospectively analyzed astrocytic tumors, including 18 grade II astrocytomas (isocitrate dehydrogenase (IDH)-mutant: IDH-wildtype = 8:10) and 56 grade III anaplastic astrocytomas (37:19). We recorded the maximum methionine (MET) uptake ratios (tumor-to-normal: T/N) on positron emission tomography (PET) and three MRS peak ratios: choline (Cho)/creatine (Cr), N-acetyl aspartate (NAA)/Cr, and Cho/NAA, between June 2015 and June 2020. We then evaluated the cut-off values to differentiate between grades II and III. We compared the grading results between contrast enhancement effects on MR and combinational diagnostic methods (CDM) on a scatter chart using the cutoff values of the T/N ratio and MRS parameters.

Results

The IDH-mutant group showed significant differences in the Cho/NAA ratio between grades II and III using univariate analysis; however, multiple regression analysis results negated this. The IDH-wildtype group showed no significant differences between the groups. Contrast enhancement effects also showed no significant differences in IDH status. Accordingly, regardless of the IDH status, no statistically independent factors differentiated between grades II and III. However, CDMs showed higher sensitivity and negative predictive value in distinguishing them than MRI contrast examinations for both IDH statuses. We demonstrated a significantly higher diagnostic rate of grade III than of grade II with CDM, which was more striking in the IDH-mutant group than in the wild-type group.

Conclusions

CDM could be valuable in differentiating between grade II and III astrocytic tumors.

Arterial input functions in dynamic susceptibility contrast MRI (DSC-MRI) in longitudinal evaluation of brain metastases

BACKGROUND

Dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) could be helpful to separate true disease progression from pseudo-progression in brain metastases when assessing the need for retreatment. However, the selection of arterial input functions (AIFs) is not standardized for analysis, limiting its use for this application.

PURPOSE

To compare population-based AIFs, AIFs specific to each patient, and AIFs specific to every visit in the longitudinal follow-up of brain metastases.

MATERIAL AND METHODS

Longitudinal data were collected from eight patients before treatment (6 of 8 patients) and after treatment (6-17 visits). Imaging was performed using a 1.5-T MRI system. Lesions were segmented by subtracting precontrast images from postcontrast images. Cerebral blood volume (rCBV) and cerebral blood flow (rCBF) were computed, and Pearson's product moment correlation coefficients were calculated to evaluate similarity of DSC parameters dependent on various AIF choices across time. AIF shape characteristics were compared. Parameter differences between white matter (WM) and gray matter (GM) were obtained to determine which AIF choice maximizes tissue differentiation.

RESULTS

Although DSC parameters follow similar patterns in time, the various AIF selections cause large parameter variations with relative standard deviations of up to ±60%. AIFs sampled in one patient across sessions more similar in shape than AIFs sampled across patients. Estimates of rCBV based on scan-specific AIFs differentiated better between perfusion in WM and GM than patient-specific or population-based AIFs (P ≤ 0.02).

CONCLUSION

Results indicate that scan-specific AIFs are the best choice for DSC-MRI parameter estimations in the longitudinal follow-up of brain metastases.

A rare, giant, anaplastic oligodendroglioma

Oligodendroglioma, the third most common glioma, accounts for 5% of primary brain tumors and around 20% of all glial neoplasms. They are quite uncommon in children. Here, we aimed to show an unusual case of a 9-year-old boy developing a huge anaplastic oligodendroglioma. A high-grade astrocytoma-like supratentorial tumor was discovered by a sophisticated brain scan employing magnetic resonance imaging. The tumor was identified by histopathology as an anaplastic oligodendroglioma. Anaplastic oligodendroglioma should be considered while making the differential diagnosis of high-grade astrocytoma notwithstanding its rarity.

Telomerase reverse transcriptase promoter mutation and histologic grade in IDH wild-type histological lower-grade gliomas: The value of perfusion-weighted image, diffusion-weighted image, and 18F-FDG-PET

PURPOSE

The telomerase reverse transcriptase promoter (TERTp) mutation is an unfavorable prognostic factor in isocitrate dehydrogenase-wildtype (IDHwt) histologically lower-grade astrocytoma (LGA), which was incorporated as a key component in the WHO 2021 classification of IDHwt LGA, replacing histologic grades in the WHO 2016 classification. The purpose of this study was to identify the imaging characteristics predictive of TERTp mutations in IDHwt LGA.

METHODS

This retrospective study was approved by our institutional review board. This single-center study retrospectively included 59 patients with pathologically confirmed IDHwt LGA with known TERTp mutation status. In addition to clinical information and morphological characteristics, semi-quantitative imaging biomarkers such as the tumor-to-normal ratio (T/N ratio) on ¹⁸F-FDG-PET, normalized apparent diffusion coefficient (nADC), and histogram parameters from normalized relative cerebral blood volume (nrCBV) maps were compared between (a) TERTp-wildtype and TERTp-mutant tumors or (b) grade II and grade III astrocytoma. A p value < 0.05 was considered significant.

RESULTS

There were no significant differences in the conventional imaging findings, T/N ratio on FDG-PET, nrCBV or ADC histogram metrics between IDHwt LGA with TERTp mutations and those without. Grade III IDHwt astrocytomas exhibited significantly higher nrCBV values, T/N ratio and lower ADC parameters than grade II IDHwt astrocytoma.

CONCLUSIONS

In patients with IDHwt LGA, T/N ratio, nrCBV values and nADC may be surrogate markers for predicting histologic grade, but are not useful for predicting TERTp mutations.

Tumor volume and calcifications as indicators for preoperative differentiation of grade II/III diffuse gliomas

PURPOSE

To retrospectively evaluate preoperative clinical factors for their ability to preoperatively differentiate malignancy grades in patients with incipient supratentorial grade II/III diffuse gliomas.

METHODS

This retrospective study included 206 adult patients with incipient supratentorial grade II/III diffuse gliomas according to the 2016 World Health Organization classification of tumors of the central nervous system. The cohort included 136 men and 70 women, with a median age of 41 years. Preoperative factors included age, sex, presence of calcifications on computed tomography scans, and preoperative tumor volume measured using preoperative magnetic resonance imaging.

RESULTS

In patients with oligodendrogliomas (IDH-mutant and 1p/19q-codeleted), calcifications were significantly more frequent (p = 0.0034) and tumor volume was significantly larger (p < 0.001) in patients with grade III tumors than in those with grade II tumors. Moreover, in patients with IDH-mutant astrocytomas, preoperative tumor volume was significantly larger (p = 0.0042) in patients with grade III tumors than in those with grade II tumors. In contrast, none of the evaluated preoperative clinical factors were significantly different between the patients with grade II and III IDH-wildtype astrocytomas.

CONCLUSION

In adult patients with suspicison incipient supratentorial grade II/III diffuse gliomas, presence of calcifications and larger preoperative tumor volume might be used as preoperative indices to differentiate between malignancy grades II and III in oligodendrogliomas (IDH-mutant and 1p/19q-codeleted) and larger preoperative tumor volume might have similar utility in IDH-mutant astrocytomas.

MRI features predict tumor grade in isocitrate dehydrogenase (IDH)-mutant astrocytoma and oligodendroglioma

PURPOSE

Nearly all literature for predicting tumor grade in astrocytoma and oligodendroglioma pre-dates the molecular classification system. We investigated the association between contrast enhancement, ADC, and rCBV with tumor grade separately for IDH-mutant astrocytomas and molecularly-defined oligodendrogliomas.

METHODS

For this retrospective study, 44 patients with IDH-mutant astrocytomas (WHO grades II, III, or IV) and 39 patients with oligodendrogliomas (IDH-mutant and 1p/19q codeleted) (WHO grade II or III) were enrolled. Two readers independently assessed preoperative MRI for contrast enhancement, ADC, and rCBV. Inter-reader agreement was calculated, and statistical associations between MRI metrics and WHO grade were determined per reader.

RESULTS

For IDH-mutant astrocytomas, both readers found a stepwise positive association between contrast enhancement and WHO grade (Reader A: OR 7.79 [1.97, 30.80], p = 0.003; Reader B: OR 6.62 [1.70, 25.82], p = 0.006); both readers found that ADC was negatively associated with WHO grade (Reader A: OR 0.74 [0.61, 0.90], p = 0.002); Reader B: OR 0.80 [0.66, 0.96], p = 0.017), and both readers found that rCBV was positively associated with WHO grade (Reader A: OR 2.33 [1.35, 4.00], p = 0.002; Reader B: OR 2.13 [1.30, 3.57], p = 0.003). For oligodendrogliomas, both readers found a positive association between contrast enhancement and WHO grade (Reader A: OR 15.33 [2.56, 91.95], p = 0.003; Reader B: OR 20.00 [2.19, 182.45], p = 0.008), but neither reader found an association between ADC or rCBV and WHO grade.

CONCLUSIONS

Contrast enhancement predicts WHO grade for IDH-mutant astrocytomas and oligodendrogliomas. ADC and rCBV predict WHO grade for IDH-mutant astrocytomas, but not for oligodendrogliomas.

Efficacy of MR diffusion kurtosis imaging for differentiating low-grade from high-grade glioma before surgery: A systematic review and meta-analysis

BACKGROUND

Accurate discrimination and diagnosis of low-grade glioma (LGG) and high-grade glioma (HGG) before surgery is clinically important because it affects the patient's outcome and guides the clinicians to select appropriate management. The aim of this study was to evaluate the diagnostic performance of diffusion kurtosis imaging (DKI) for differentiating LGG from HGG.

METHODS

A literature search of the PubMed, Web of Science, Cochrane Library and EMBASE databases was conducted up to December 15, 2020. Studies that evaluated the diagnostic performance of DKI for differentiating LGG from HGG were selected. Retrieved hits were evaluated by the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Summary sensitivity and specificity were determined, and the data analysis was performed using Stata 14.0 and Review Manager 5.3.

RESULTS

Thirteen studies with 705 patients were included. The individual sensitivity and specificity of the 13 studies varied from 71% to 100% for sensitivity and 73-100% for specificity. The pooled sensitivity of DKI was 88% (95% confidence interval [CI], 83-91%), and the pooled specificity was 91% (95% CI, 86-95%). The area under the summary receiver operating characteristic curve was 0.93 (95% CI, 0.90-0.95). The pooled diagnostic odds ratio of DKI was 64.85 (95% CI 38.52-109.19). The levels of heterogeneity for sensitivity and specificity across the included studies were high (I² =66%) and mild (I² =47.04%), respectively. The multiple subgroup analyses were driven by DKI technique and study region.

CONCLUSIONS

DKI demonstrated a high diagnostic performance for differentiation of LGG from HGG.

The Use of 18F-FET-PET-MRI in Neuro-Oncology: The Best of Both Worlds—A Narrative Review

Gliomas are the most frequent primary tumors of the brain. They can be divided into grade II-IV astrocytomas and grade II-III oligodendrogliomas, based on their histomolecular profile. The prognosis and treatment is highly dependent on grade and well-identified prognostic and/or predictive molecular markers. Multi-parametric MRI, including diffusion weighted imaging, perfusion, and MR spectroscopy, showed increasing value in the non-invasive characterization of specific molecular subsets of gliomas. Radiolabeled amino-acid analogues, such as 18F-FET, have also been proven valuable in glioma imaging. These tracers not only contribute in the diagnostic process by detecting areas of dedifferentiation in diffuse gliomas, but this technique is also valuable in the follow-up of gliomas, as it can differentiate pseudo-progression from real tumor progression. Since multi-parametric MRI and 18F-FET PET are complementary imaging techniques, there may be a synergistic role for PET-MRI imaging in the neuro-oncological imaging of primary brain tumors. This could be of value for both primary staging, as well as during treatment and follow-up.

Hemodynamic Imaging in Cerebral Diffuse Glioma-Part A: Concept, Differential Diagnosis and Tumor Grading

Diffuse gliomas are the most common primary malignant intracranial neoplasms. Aside from the challenges pertaining to their treatment-glioblastomas, in particular, have a dismal prognosis and are currently incurable-their pre-operative assessment using standard neuroimaging has several drawbacks, including broad differentials diagnosis, imprecise characterization of tumor subtype and definition of its infiltration in the surrounding brain parenchyma for accurate resection planning. As the pathophysiological alterations of tumor tissue are tightly linked to an aberrant vascularization, advanced hemodynamic imaging, in addition to other innovative approaches, has attracted considerable interest as a means to improve diffuse glioma characterization. In the present part A of our two-review series, the fundamental concepts, techniques and parameters of hemodynamic imaging are discussed in conjunction with their potential role in the differential diagnosis and grading of diffuse gliomas. In particular, recent evidence on dynamic susceptibility contrast, dynamic contrast-enhanced and arterial spin labeling magnetic resonance imaging are reviewed together with perfusion-computed tomography. While these techniques have provided encouraging results in terms of their sensitivity and specificity, the limitations deriving from a lack of standardized acquisition and processing have prevented their widespread clinical adoption, with current efforts aimed at overcoming the existing barriers.

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

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

Combining 18F-DOPA PET and MRI with perfusion-weighted imaging improves delineation of high-grade subregions in enhancing and non-enhancing gliomas prior treatment: a biopsy-controlled study

PURPOSE

We aimed to compare spatial extent of high-grade subregions detected with combined [¹⁸F]-dihydroxyphenylalanine (¹⁸F-DOPA) PET and MRI to the one provided by advanced multimodal MRI alone including Contrast-enhanced (CE) and Perfusion weighted imaging (PWI). Then, we compared the accuracy between imaging modalities, in a per biopsy analysis.

METHODS

Participants with suspected diffuse glioma were prospectively included between June 2018 and September 2019. Volumes of high-grade subregions were delineated respectively on ¹⁸F-DOPA PET and MRI (CE and PWI). Up to three per-surgical neuronavigation-guided biopsies were performed per patient.

RESULTS

Thirty-eight biopsy samples from sixteen participants were analyzed. Six participants (38%) had grade IV IDH wild-type glioblastoma, six (38%) had grade III IDH-mutated astrocytoma and four (24%) had grade II IDH-mutated gliomas. Three patients had intratumoral heterogeneity with coexisting high- and low-grade tumor subregions. High-grade volumes determined with combined ¹⁸F-DOPA PET/MRI (median of 1.7 [interquartile range (IQR) 0.0, 19.1] mL) were larger than with multimodal MRI alone (median 1.3 [IQR 0.0, 12.8] mL) with low overlap (median Dice's coefficient 0.24 [IQR 0.08, 0.59]). Delineation volumes were substantially increased in five (31%) patients. In a per biopsy analysis, combined ¹⁸F-DOPA PET/MRI detected high-grade subregions with an accuracy of 58% compared to 42% (p = 0.03) with CE MRI alone and 50% (p = 0.25) using multimodal MRI (CE + PWI).

CONCLUSIONS

The addition of ¹⁸F-DOPA PET to multimodal MRI (CE and PWI) enlarged the delineation volumes and enhanced overall accuracy for detection of high-grade subregions. Thus, combining ¹⁸F-DOPA with advanced MRI may improve treatment planning in newly diagnosed gliomas.

Imaging Advances for Central Nervous System Tumors

This article reviews recent advances in the use of standard and advanced imaging techniques for diagnosis and treatment of central nervous system (CNS) tumors, including glioma and brain metastasis. Following the recent transition from a histology-based approach in classifying CNS tumors to one that integrates histology with the molecular information of tumor, the approaches for imaging CNS tumors have also been adapted to this new framework. Some challenges related to the diagnosis and treatment of CNS tumors, such as differentiating tumor from treatment-related imaging changes, require further progress to implement advanced imaging for clinical use.

Impact of 18F-FET PET/MR on clinical management of brain tumor patients

Multiparametric PET/MRI with the amino-acid analog O-(2-¹⁸F-fluoroethyl)-l-tyrosine (¹⁸F-FET) enables the simultaneous assessment of molecular, morphologic, and functional brain tumor characteristics. Although it is considered the most accurate noninvasive approach in brain tumors, its relevance for patient management is still under debate. Here, we report the diagnostic performance of ¹⁸F-FET PET/MRI and its impact on clinical management in a retrospective patient cohort. Methods: We retrospectively analyzed brain tumor patients who underwent ¹⁸F-FET PET/MRI between 2017 and 2018. ¹⁸F-FET PET/MRI examinations were indicated clinically because of equivocal standard imaging results or the clinical course. Histologic confirmation or clinical and standard imaging follow-up served as the reference standard. We evaluated ¹⁸F-FET PET/MRI accuracy in identifying malignancy in untreated suspected lesions (category, new diagnosis) and true progression during adjuvant treatment (category, detection of progression) in a clinical setting. Using multiple regression, we also estimated the contribution of single modalities to produce an optimal PET/MRI outcome. We assessed the recommended and applied therapies before and after ¹⁸F-FET PET/MRI and noted whether the treatment changed on the basis of the ¹⁸F-FET PET/MRI outcome. Results: We included 189 patients in the study. ¹⁸F-FET PET/MRI allowed the identification of malignancy at new diagnosis with an accuracy of 85% and identified true progression with an accuracy of 93%. Contrast enhancement, ¹⁸F-FET PET uptake, and tracer kinetics were the major contributors to an optimal PET/MRI outcome. In the previously equivocal patients, ¹⁸F-FET PET/MRI changed the clinical management in 33% of the untreated lesions and 53% of the cases of tumor progression. Conclusion: Our results suggest that ¹⁸F-FET PET/MRI helps clarify equivocal conditions and profoundly supports the clinical management of brain tumor patients. The optimal modality setting for ¹⁸F-FET PET/MRI and the clinical value of a simultaneous examination need further exploration. At a new diagnosis, multiparametric ¹⁸F-FET PET/MRI might help prevent unnecessary invasive procedures by ruling out malignancy; however, adding static ¹⁸F-FET PET to an already existing MRI examination seems to be of equal value. At detection of progression, multiparametric ¹⁸F-FET PET/MRI may increase therapy effectiveness by distinguishing between tumor progression and therapy-related imaging alterations.

MRI biomarkers in neuro-oncology

The central role of MRI in neuro-oncology is undisputed. The technique is used, both in clinical practice and in clinical trials, to diagnose and monitor disease activity, support treatment decision-making, guide the use of focused treatments and determine response to treatment. Despite recent substantial advances in imaging technology and image analysis techniques, clinical MRI is still primarily used for the qualitative subjective interpretation of macrostructural features, as opposed to quantitative analyses that take into consideration multiple pathophysiological features. However, the field of quantitative imaging and imaging biomarker development is maturing. The European Imaging Biomarkers Alliance (EIBALL) and Quantitative Imaging Biomarkers Alliance (QIBA) are setting standards for biomarker development, validation and implementation, as well as promoting the use of quantitative imaging and imaging biomarkers by demonstrating their clinical value. In parallel, advanced imaging techniques are reaching the clinical arena, providing quantitative, commonly physiological imaging parameters that are driving the discovery, validation and implementation of quantitative imaging and imaging biomarkers in the clinical routine. Additionally, computational analysis techniques are increasingly being used in the research setting to convert medical images into objective high-dimensional data and define radiomic signatures of disease states. Here, I review the definition and current state of MRI biomarkers in neuro-oncology, and discuss the clinical potential of quantitative image analysis techniques.

Exploring diagnostic performance of T2 mapping in diffuse glioma grading

Background

To evaluate the diagnostic performance of T2 mapping in differentiating WHO grade II glioma from high-grade glioma (HGG).

Methods

We conducted a single-center, retrospective diagnostic study. Confirmed diffuse glioma (WHO grade II-IV) patients who underwent post-contrast T1-weighted imaging, T2-weighted imaging, and T2 mapping were included. All diagnoses were based on histological and molecular tests. Seventy-five percent of cases were subsampled to generate receiver operating characteristic (ROC) curves and areas under the curve (AUC), while the remaining cases were used to test the accuracy of T2 mapping. Subsampling was repeated four times. Age, T2 relaxation time, and contrast-enhancement status were used to generate a multivariable ROC curve. T2 relaxation time was also used to generate ROC curves to predict the isocitrate dehydrogenase (IDH) status.

Results

A total of 159 patients were included in the study. After four repeats of subsampling, the AUCs of the T2 mapping ROC curve were 0.801 (95% CI: 0.724-0.879), 0.795 (95% CI: 0.714-0.875), 0.803 (95% CI: 0.723-0.884), and 0.801 (95% CI: 0.716-0.886), with an average sensitivity of 0.753 and an average specificity of 0.767. When applied to the remaining 25% of cases, the accuracy was 75%, 93.75%, 82.50%, and 71.74%. The AUC of the multivariable ROC was 0.927 (95% CI: 0.882-0.971). IDH-mutant and IDH-wildtype gliomas have significantly different T2 relaxation times (146.28 and 124.10 ms, respectively; P=0.001), and the AUC of IDH-mutant prediction was 0.687 (95% CI: 0.585-0.789).

Conclusions

Quantitative T2 mapping differentiated WHO grade II glioma from HGG with moderate sensitivity and specificity. Given the advantages of short acquisition times and the absence of a contrast agent, our study suggests the application of T2 mapping in pre-operative glioma grading is feasible.

Identification of Tumor-Specific MRI Biomarkers Using Machine Learning (ML)

The identification of reliable and non-invasive oncology biomarkers remains a main priority in healthcare. There are only a few biomarkers that have been approved as diagnostic for cancer. The most frequently used cancer biomarkers are derived from either biological materials or imaging data. Most cancer biomarkers suffer from a lack of high specificity. However, the latest advancements in machine learning (ML) and artificial intelligence (AI) have enabled the identification of highly predictive, disease-specific biomarkers. Such biomarkers can be used to diagnose cancer patients, to predict cancer prognosis, or even to predict treatment efficacy. Herein, we provide a summary of the current status of developing and applying Magnetic resonance imaging (MRI) biomarkers in cancer care. We focus on all aspects of MRI biomarkers, starting from MRI data collection, preprocessing and machine learning methods, and ending with summarizing the types of existing biomarkers and their clinical applications in different cancer types.

DSC and DCE Histogram Analyses of Glioma Biomarkers, Including IDH, MGMT, and TERT, on Differentiation and Survival

RATIONALE AND OBJECTIVES

The World Health Organization 2016 classification of central nervous system tumors added the molecular classification of gliomas and has guiding significance for the operation and prognosis of glioma patients. At present, the perfusion technique plays an important role in judging the malignant degree of glioma. To evaluate the performance of dynamic susceptibility contrast (DSC)- and dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) histogram analyses in discriminating the states of molecular biomarkers and survival in glioma patients.

MATERIALS AND METHODS

Forty-three glioma patients who underwent DCE- and DSC-MRI were enrolled. Relevant molecular test results, including those on isocitrate dehydrogenase (IDH), O6-methylguanine-DNA methyltransferase (MGMT) and telomere reverse transcriptase (TERT), were collected. The mean relative cerebral blood volume of DSC-MRI and histogram parameters derived from DCE-MRI (volume transfer coefficient (K^trans), fractional volume of the extravascular extracellular space (V_e), fractional blood plasma volume (V_p), rate constant between the extravascular extracellular space and blood plasma (K_ep) and area under the curve (AUC)) were calculated. Differences in each parameter between gliomas with different expression states (IDH, MGMT, and TERT) were evaluated. The diagnostic efficiency of each parameter was analyzed. The overall survival of all patients was assessed.

RESULTS

The 10th percentile AUC (AUC = 0.830, sensitivity = 0.78, specificity = 0.80), the 90th percentile V_e (AUC = 0.816, sensitivity = 0.84, specificity = 0.79), and the mean K_ep (AUC = 0.818, sensitivity = 0.76, specificity = 0.78) provided the highest differential efficiency for IDH, MGMT, and TERT, respectively. Kaplan-Meier curves showed a significant difference between subjects with a 10th percentile AUC higher or lower than 0.028 (log-rank = 7.535; p = 0.006) for IDH and between subjects with different 90th percentile V_e values (log-rank = 6.532; p = 0.011) for MGMT.

CONCLUSION

Histogram DCE-MRI demonstrates good diagnostic performance in identifying different molecular types and for the prognostic assessment of glioma.

Prognostic Value of Preoperative MRI Metrics for Diffuse Lower-Grade Glioma Molecular Subtypes

BACKGROUND AND PURPOSE

Despite the improved prognostic relevance of the 2016 WHO molecular-based classification of lower-grade gliomas, variability in clinical outcome persists within existing molecular subtypes. Our aim was to determine prognostically significant metrics on preoperative MR imaging for lower-grade gliomas within currently defined molecular categories.

MATERIALS AND METHODS

We undertook a retrospective analysis of 306 patients with lower-grade gliomas accrued from an institutional data base and The Cancer Genome Atlas. Two neuroradiologists in consensus analyzed preoperative MRIs of each lower-grade glioma to determine the following: tumor size, tumor location, number of involved lobes, corpus callosum involvement, hydrocephalus, midline shift, eloquent cortex involvement, ependymal extension, margins, contrast enhancement, and necrosis. Adjusted hazard ratios determined the association between MR imaging metrics and overall survival per molecular subtype, after adjustment for patient age, patient sex, World Health Organization grade, and surgical resection status.

RESULTS

For isocitrate dehydrogenase (IDH) wild-type lower-grade gliomas, tumor size (hazard ratio, 3.82; 95% CI, 1.94-7.75; P < .001), number of involved lobes (hazard ratio, 1.70; 95% CI, 1.28-2.27; P < .001), hydrocephalus (hazard ratio, 4.43; 95% CI, 1.12-17.54; P = .034), midline shift (hazard ratio, 1.16; 95% CI, 1.03-1.30; P = .013), margins (P = .031), and contrast enhancement (hazard ratio, 0.34; 95% CI, 0.13-0.90; P = .030) were associated with overall survival. For IDH-mutant 1p/19q-codeleted lower-grade gliomas, tumor size (hazard ratio, 2.85; 95% CI, 1.06-7.70; P = .039) and ependymal extension (hazard ratio, 6.34; 95% CI, 1.07-37.59; P = .042) were associated with overall survival.

CONCLUSIONS

MR imaging metrics offers prognostic information for patients with lower-grade gliomas within molecularly defined classes, with the greatest prognostic value for IDH wild-type lower-grade gliomas.

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.

FAP-specific PET signaling shows a moderately positive correlation with relative CBV and no correlation with ADC in 13 IDH wildtype glioblastomas

OBJECTIVES

Targeting Fibroblast Activation Protein (FAP) is a new approach for glioblastoma imaging. In a recent pilot study glioblastomas showed elevated tracer uptake with high intratumoral heterogeneity in projection on the corresponding T2w/FLAIR and contrast enhanced MRI lesions. In this study, we correlated FAP-specific signaling with apparent diffusion coefficient (ADC) and relative cerebral blood volume (rCBV) signals in MRI to further characterize the significance of FAP uptake.

METHODS

Clinical PET/CT scans of 13 glioblastoma patients were performed post i. v. administration of ⁶⁸Ga-labelled-FAP-specific tracer molecules. PET- and corresponding MRI-scans were co-registrated. 3d volumetric segmentations were performed of T2w/FLAIR lesions and contrast enhancing lesions within co-registrated MRI slides. Signal intensity values of FAP-specific PET signaling, ADC and rCBV were analyzed for their pixel wise correlation in each patient. Pooled estimates of the correlation coefficients were calculated by using the Fisher z-transformation.

RESULTS

FAP-specific PET signals showed a moderately positive correlation with rCBV values which is more pronounced within the T2w/FLAIR lesion (pooled correlation 0,229) than in the contrast enhancing tumor region (pooled correlation 0.09). FAP-specific PET signals showed no correlation with ADC values.

CONCLUSIONS

The moderately positive correlation of FAP-specific signals with rCBV values in MRI indicates that FAP-signaling is not independent from perfusion, but also does not only reflect intratumoral perfusion differences. The missing correlation of FAP-specific signals with ADC indicates that FAP-specific imaging does not reflect cell density, but the spot-like expression of FAP in glioblastomas. The clinical value of FAP-specific imaging needs further investigation.

Hemodynamic investigation of peritumoral impaired blood oxygenation-level dependent cerebrovascular reactivity in patients with diffuse glioma

INTRODUCTION

The presence of peritumorally impaired blood oxygenation-level dependent cerebrovascular reactivity (BOLD-CVR) has been unequivocally demonstrated in patients with diffuse glioma, and may have value to better identify tumor infiltration zone. Since BOLD-CVR does not measure hemodynamic changes directly, we performed additional MR perfusion studies to better characterize the peritumoral hemodynamic environment.

METHODS

Seventeen patients with WHO grade III and IV diffuse glioma underwent high resolution advanced hemodynamic MR imaging including BOLD-CVR and MR perfusion. The obtained multiparametric hemodynamic factors (i.e., regional cerebral blood flow (rCBF), relative cerebral blood volume (rCBV), mean transit time (MTT), time-to-peak (TTP) and BOLD-CVR, were analyzed within 10 concentric expanding 3 mm volumes of interest (VOIs) up to 30 mm from the tumor tissue mask.

RESULTS

BOLD-CVR impairment was found within the tumor tissue mask and the peritumoral VOIs up to 21 mm as compared to the contralateral flipped CVR analysis (p<0.05). In the affected hemisphere, we observed positive spatial correlations including all VOIs between BOLD-CVR and rCBV values (r=0.27; p<0.001), rCBF (r=0.42; p<0.001) and a negative correlation between BOLD-CVR and TTP (r=-0.47; p<0.001).

CONCLUSIONS

Peritumorally impaired BOLD-CVR is associated with concomitant hemodynamic alterations with severity correlating to tumor volume. The distribution of these multiparametric hemodynamic MRI patterns may be considered for future studies characterizing the hemodynamic peritumoral environment, thereby better identifying the extent of tumor infiltration.

Multi-parametric arterial spin labelling and diffusion-weighted magnetic resonance imaging in differentiation of grade II and grade III gliomas

Purpose

To assess arterial spin labelling (ASL) perfusion and diffusion MR imaging (DWI) in the differentiation of grade II from grade III gliomas.

Material and methods

A prospective cohort study was done on 36 patients (20 male and 16 female) with diffuse gliomas, who underwent ASL and DWI. Diffuse gliomas were classified into grade II and grade III. Calculation of tumoural blood flow (TBF) and apparent diffusion coefficient (ADC) of the tumoral and peritumoural regions was made. The ROC curve was drawn to differentiate grade II from grade III gliomas.

Results

There was a significant difference in TBF of tumoural and peritumoural regions of grade II and III gliomas (p = 0.02 and p =0.001, respectively). Selection of 26.1 and 14.8 ml/100 g/min as the cut-off for TBF of tumoural and peritumoural regions differentiated between both groups with area under curve (AUC) of 0.69 and 0.957, and accuracy of 77.8% and 88.9%, respectively. There was small but significant difference in the ADC of tumoural and peritumoural regions between grade II and III gliomas (p = 0.02 for both). The selection of 1.06 and 1.36 × 10^-3 mm²/s as the cut-off of ADC of tumoural and peritumoural regions was made, to differentiate grade II from III with AUC of 0.701 and 0.748, and accuracy of 80.6% and 80.6%, respectively. Combined TBF and ADC of tumoural regions revealed an AUC of 0.808 and accuracy of 72.7%. Combined TBF and ADC for peritumoural regions revealed an AUC of 0.96 and accuracy of 94.4%.

Conclusion

TBF and ADC of tumoural and peritumoural regions are accurate non-invasive methods of differentiation of grade II from grade III gliomas.

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.

Validated imaging biomarkers as decision-making tools in clinical trials and routine practice: current status and recommendations from the EIBALL* subcommittee of the European Society of Radiology (ESR)

Observer-driven pattern recognition is the standard for interpretation of medical images. To achieve global parity in interpretation, semi-quantitative scoring systems have been developed based on observer assessments; these are widely used in scoring coronary artery disease, the arthritides and neurological conditions and for indicating the likelihood of malignancy. However, in an era of machine learning and artificial intelligence, it is increasingly desirable that we extract quantitative biomarkers from medical images that inform on disease detection, characterisation, monitoring and assessment of response to treatment. Quantitation has the potential to provide objective decision-support tools in the management pathway of patients. Despite this, the quantitative potential of imaging remains under-exploited because of variability of the measurement, lack of harmonised systems for data acquisition and analysis, and crucially, a paucity of evidence on how such quantitation potentially affects clinical decision-making and patient outcome. This article reviews the current evidence for the use of semi-quantitative and quantitative biomarkers in clinical settings at various stages of the disease pathway including diagnosis, staging and prognosis, as well as predicting and detecting treatment response. It critically appraises current practice and sets out recommendations for using imaging objectively to drive patient management decisions.

Dynamic susceptibility contrast and diffusion MR imaging identify oligodendroglioma as defined by the 2016 WHO classification for brain tumors: histogram analysis approach

PURPOSE

According to the revised World Health Organization (WHO) Classification of Tumors of the Central Nervous System (CNS) of 2016, oligodendrogliomas are now defined primarily by a specific molecular signature (presence of IDH mutation and 1p19q codeletion). The purpose of our study was to assess the value of dynamic susceptibility contrast MR imaging (DSC-MRI) and diffusion-weighted imaging (DWI) to characterize oligodendrogliomas and to distinguish them from astrocytomas.

METHODS

Seventy-one adult patients with untreated WHO grade II and grade III diffuse infiltrating gliomas and known 1p/19q codeletion status were retrospectively identified and analyzed using relative cerebral blood volume (rCBV) and apparent diffusion coefficient (ADC) maps based on whole-tumor volume histograms. The Mann-Whitney U test and logistic regression were used to assess the ability of rCBV and ADC to differentiate between oligodendrogliomas and astrocytomas both independently, but also related to the WHO grade. Prediction performance was evaluated in leave-one-out cross-validation (LOOCV).

RESULTS

Oligodendrogliomas showed significantly higher microvascularity (higher rCBV_Mean ≥ 0.80, p = 0.013) and higher vascular heterogeneity (lower rCBV_Peak ≤ 0.044, p = 0.015) than astrocytomas. Diffuse gliomas with higher cellular density (lower ADC_Mean ≤ 1094 × 10^-6 mm²/s, p = 0.009) were more likely to be oligodendrogliomas than astrocytomas. Histogram analysis of rCBV and ADC was able to differentiate between diffuse astrocytomas (WHO grade II) and anaplastic astrocytomas (WHO grade III).

CONCLUSION

Histogram-derived rCBV and ADC parameter may be used as biomarkers for identification of oligodendrogliomas and may help characterize diffuse gliomas based upon their genetic characteristics.

Amide proton transfer-weighted MRI in distinguishing high- and low-grade gliomas: a systematic review and meta-analysis

PURPOSE

Grading of brain gliomas is of clinical importance, and noninvasive molecular imaging may help differentiate low- and high-grade gliomas. We aimed to evaluate the diagnostic performance of amide proton transfer-weighted (APTw) MRI for differentiating low- and high-grade gliomas on 3-T scanners.

METHODS

A systematic literature search of Ovid-MEDLINE and EMBASE was performed up to March 28, 2018. Original articles evaluating the diagnostic performance of APTw MRI for differentiating low- and high-grade gliomas were selected. The pooled sensitivity and specificity were calculated using a bivariate random-effects model. A coupled forest plot and a hierarchical summary receiver operating characteristic curve were obtained. Heterogeneity was investigated using Higgins inconsistency index (I²) test. Meta-regression was performed.

RESULTS

Ten original articles with a total of 353 patients were included. High-grade gliomas showed significantly higher APT signal intensity than low-grade gliomas. The pooled sensitivity and specificity for the diagnostic performance of APTw MRI for differentiating low-grade and high-grade gliomas were 88% (95% CI, 77-94%) and 91% (95% CI, 82-96%), respectively. Higgins I² statistic demonstrated heterogeneity in the sensitivity (I² = 68.17%), whereas no heterogeneity was noted in the specificity (I² = 44.84%). In meta-regression, RF saturation power was associated with study heterogeneity. Correlation coefficients between APT signal intensity and Ki-67 cellular proliferation index ranged from 0.430 to 0.597, indicating moderate correlation. All studies showed excellent interobserver agreement.

CONCLUSIONS

Although heterogeneous protocols were used, APTw MRI demonstrated excellent diagnostic performance for differentiating low- and high-grade gliomas. APTw MRI could be a reliable technique for glioma grading in clinical practice.

Arterial spin labeling MR imaging for differentiation between high- and low-grade glioma-a meta-analysis

Background

Arterial spin labeling is an MR imaging technique that measures cerebral blood flow (CBF) non-invasively. The aim of the study is to assess the diagnostic performance of arterial spin labeling (ASL) MR imaging for differentiation between high-grade glioma and low-grade glioma.

Methods

Cochrane Library, Embase, Medline, and Web of Science Core Collection were searched. Study selection ended November 2017. This study was prospectively registered in PROSPERO (CRD42017080885). Two authors screened all titles and abstracts for possible inclusion. Data were extracted independently by 2 authors. Bivariate random effects meta-analysis was used to describe summary receiver operating characteristics. Trial sequential analysis (TSA) was performed.

Results

In total, 15 studies with 505 patients were included. The diagnostic performance of ASL CBF for glioma grading was 0.90 with summary sensitivity 0.89 (0.79-0.90) and specificity 0.80 (0.72-0.89). The diagnostic performance was similar between pulsed ASL (AUC 0.90) with a sensitivity 0.85 (0.71-0.91) and specificity 0.83 (0.69-0.92) and pseudocontinuous ASL (AUC 0.88) with a sensitivity 0.86 (0.79-0.91) and specificity 0.80 (0.65-0.87). In astrocytomas, the diagnostic performance was 0.89 with sensitivity 0.86 (0.79 to 0.91) and specificity 0.79 (0.63 to 0.89). Sensitivity analysis confirmed the robustness of the findings. TSA revealed that the meta-analysis was adequately powered.

Conclusion

Arterial spin labeling MR imaging had an excellent diagnostic accuracy for differentiation between high-grade and low-grade glioma. Given its low cost, non-invasiveness, and efficacy, ASL MR imaging should be considered for implementation in the routine workup of patients with glioma.

MR Imaging Features of Anaplastic Pleomorphic Xanthoastrocytoma Mimicking High-Grade Astrocytoma

BACKGROUND AND PURPOSE

Anaplastic pleomorphic xanthoastrocytoma, which has been recently defined as a distinct entity in the 2016 World Health Organization classification, may exhibit aggressive clinical behavior and relatively worse prognosis than pleomorphic xanthoastrocytoma. This study aimed to investigate whether there were any differences in MR imaging characteristics between these 2 tumors.

MATERIALS AND METHODS

This retrospective study included 9 patients with anaplastic pleomorphic xanthoastrocytoma and 10 patients with pleomorphic xanthoastrocytoma who underwent MR imaging before an operation. DWI was performed in 17 patients (8 with anaplastic pleomorphic xanthoastrocytoma, 9 with pleomorphic xanthoastrocytoma); and DSC-PWI, in 9 patients (5 with anaplastic pleomorphic xanthoastrocytoma, 4 with pleomorphic xanthoastrocytoma). Demographics, conventional imaging characteristics (location, size, cystic degeneration, enhancement, peritumoral edema, and leptomeningeal contact), minimum relative ADC ratio, and maximum relative CBV ratio were evaluated between the anaplastic pleomorphic xanthoastrocytoma and pleomorphic xanthoastrocytoma groups.

RESULTS

Anaplastic pleomorphic xanthoastrocytoma was more likely to demonstrate high-grade features than pleomorphic xanthoastrocytoma, including greater maximum tumor diameter (4.7 ± 0.6 cm versus 3.1 ± 1.1 cm, P = .001), more frequent heterogeneous contrast enhancement of solid portions (88.9% versus 20.0%, P = .01), more obvious peritumoral edema (2.3 ± 0.9 cm versus 1.0 ± 0.9 cm, P = .008), lower minimum relative ADC on DWI (1.0 ± 0.2 versus 1.5 ± 0.4, P = .008), and higher maximum relative CBV on DSC-PWI (2.6 ± 0.8 versus 1.6 ± 0.2, P = .036).

CONCLUSIONS

Anaplastic pleomorphic xanthoastrocytomas often have more aggressive MR imaging features mimicking high-grade astrocytomas than pleomorphic xanthoastrocytomas. DWI and DSC-PWI might be useful in the characterization and differentiation of anaplastic pleomorphic xanthoastrocytoma and pleomorphic xanthoastrocytoma.

Preoperative and intraoperative perfusion magnetic resonance imaging in a RELA fusion-positive anaplastic ependymoma: A case report

Background

Ependymomas are rare neuroepithelial tumors thought to arise from radial glial precursor cells lining the walls of the ventricles and central canal of the brain and spinal cord, respectively. Histopathological classification, according to World Health Organization criteria, has only recently defined the RELA-fusion positive ependymoma. These tumors may account for 70% of supratentorial ependymomas in children and represent an aggressive entity distinct from other ependymomas.

Case Description

Here we present the case of a patient with RELA-fusion positive ependymoma of the frontal lobe in whom we used preoperative and intraoperative magnetic resonance (MR) perfusion imaging. In this first demonstrated intraoperative evaluation of MR perfusion in ependymoma, increased peripheral perfusion of the lesion in a ring-like manner with a discrete cutoff around the surgical margin correlated with intraoperative findings of a clear border between the tumor and brain, as well as pathological findings of increased MIB index and hypercellularity-specifically within solid tumor components. An abnormal perfusion pattern also suggested an aggressive lesion, which was later confirmed on pathological analysis. In addition, intraoperative MR perfusion improved detection of tumor tissue in combination with traditional T1-weighted contrast-enhanced methods, which increased extent of resection.

Conclusions

MR perfusion imaging may be a useful method for delineating tumor aggressiveness and borders, which can be prognostic.

The diagnostic accuracy of detecting malignant transformation of low-grade glioma using O-(2-[18F]fluoroethyl)-l-tyrosine positron emission tomography: a retrospective study

OBJECTIVE

The diagnostic accuracy of O-(2-[18F]fluoroethyl)-l-tyrosine (FET) PET scanning in detecting the malignant transformation of low-grade gliomas (LGGs) is controversial. In this study, the authors retrospectively assessed the diagnostic potential of FET PET in patients with MRI-suspected malignant progression of LGGs that had previously been treated and the relationship between FET uptake and MRI and molecular biomarkers.

METHODS

Forty-two patients who had previously undergone surgical or multimodal treatment for a histologically verified LGG were referred for FET PET assessment because of clinical signs and/or MRI findings suggestive of tumor progression. Maximal and mean tumor-to-brain ratios (TBRmax and TBRmean, respectively) on FET PET as well as kinetic FET PET parameters (time to peak [TTP] and time-activity curve [TAC]) were determined. Final diagnoses were confirmed histologically. The diagnostic accuracy of FET parameters, separately and combined, for the detection of malignant progression was evaluated using receiver operating characteristic (ROC) curve analysis. Possible predictors that might influence the diagnostic accuracy of FET PET were assessed using multiple linear regression analysis. Spearman’s rank correlation r method was applied to determine the correlation between TBRmax and TAC, and molecular biomarkers from tumor tissues.

RESULTS

A total of 47 FET PET scans were obtained and showed no significant association between FET parameters and contrast enhancement on MRI. ROC curve analyses overall were unable to demonstrate any significant differentiation between nontransformed LGGs and LGGs that had transformed to high-grade gliomas when evaluating FET parameters separately or combined. After excluding the oligodendroglial subgroup, a significant difference was observed between nontransformed and transformed LGGs when combining FET parameters (i.e., TBRmax > 1.6, TAC describing a plateau or decreasing pattern, and TTP < 25 minutes), with the best result yielded by a combined analysis of TBRmax > 1.6 and TAC with a plateau or decreasing pattern (sensitivity 75% and specificity 83%, p = 0.003). The difference was even greater when patients who had previously undergone oncological treatment were also excluded (sensitivity 93% and specificity 100%, p = 0.001). Multiple linear regression analysis revealed that the presence of an oligodendroglial component (p = 0.029), previous oncological treatment (p = 0.039), and the combined FET parameters (p = 0.027) were significant confounding factors in the detection of malignant progression. TBRmax was positively correlated with increasing cell density (p = 0.040) and inversely correlated with IDH1 mutation (p = 0.006).

CONCLUSIONS

A single FET PET scan obtained at the time of radiological and/or clinical progression seems to be of limited value in distinguishing transformed from nontransformed LGGs, especially if knowledge of the primary tumor histopathology is not known. Therefore, FET PET imaging alone is not adequate to replace histological confirmation, but it may provide valuable information on the location and delineation of active tumor tissue, as well as an assessment of tumor biology in a subgroup of LGGs.

Discrimination between primary low-grade and high-grade glioma with 11C-methionine PET: a bivariate diagnostic test accuracy meta-analysis

OBJECTIVE

To perform a meta-analysis evaluating the diagnostic accuracy of 11C-methionine (MET) positron emission tomography (PET) to discriminate between primary low-grade glioma (LGG) and high-grade glioma (HGG).

METHODS

A systematic database search was performed by a librarian in relevant databases with the latest search on 07 November 2016. Hits were assessed for inclusion independently by two authors. Individual patient data on relative MET uptake was extracted on patients examined pre-operatively with MET PET and subsequent neuropathological diagnosis of astrocytoma or oligodendroglioma. Individual patient data were analysed for diagnostic accuracy using a bivariate diagnostic random-effects meta-analysis model with restricted maximum likelihood estimation method. Bivariate meta-regression and subgroup analyses assessed study heterogeneity and validity. This study is registered with PROSPERO, number CRD42016050747.

RESULTS

Out of 1828 hits, 13 studies comprising of 241 individuals were included in the quantitative and qualitative analysis. MET PET had an area under the bivariate summary receiver operating characteristics curve of 0.78 to discriminate between LGG and HGG and a summary sensitivity of 0.80 with 95% confidence interval (CI) (0.66-0.88) and a summary false positive rate of 0.28, 95% CI (0.19-0.38). Heterogeneity was described by; bias in patient inclusion, study quality, and ratio method. Optimal cutoff for relative MET uptake was 2.21.

CONCLUSION

MET PET had a moderately high diagnostic accuracy for the discrimination between primary LGG and HGG. Advances in knowledge: MET PET can be used as a clinical tool for the non-invasive discrimination between LGG and HGG with a moderately high accuracy at cut-off 2.21.