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Objectives: A combination of T2/FLAIR mismatch sign and advanced imaging parameters may improve the determination of molecular subtypes of diffuse lower-grade glioma. We assessed the diagnostic value of adding the apparent diffusion coefficient (ADC) and cerebral blood volume (CBV) to the T2/FLAIR mismatch sign for differentiation of the IDH mutation or 1p/19q codeletion.Materials and Methods: Preoperative conventional, diffusion-weighted, and dynamic susceptibility contrast imaging were performed on 110 patients with diffuse lower-grade gliomas. The study population was classified into three groups using molecular subtype, namely IDH mutation and 1p/19q codeletion (IDHmut-Codel), IDH wild type (IDHwt) and IDH mutation and no 1p/19q codeletion (IDHmut-Noncodel). T2/FLAIR mismatch sign and the histogram parameters of apparent diffusion coefficient (ADC) and normalised cerebral blood volume (nCBV) values were assessed. A multivariate logistic regression model was constructed to distinguish IDHmut-Noncodel from IDHmut-Codel and IDHwt and from IDHwt, and the performance was compared with that of single parameters using the area under the receiver operating characteristics curve (AUC).Results: Positive visual T2/FLAIR mismatch sign and higher nCBV skewness were significant variables to distinguish IDHmut-Noncodel from the other two groups (AUC, 0.88; 95% CI, 0.81-0.96). A lower ADC10 was a significant variable for distinguishing IDHmut-Noncodel from the IDHwt group (AUC, 0.75; 95% CI, 0.62-0.89). Adding ADC or CBV histogram parameters to T2/FLAIR mismatch sign improved performance in distinguishing IDHmut-Noncodel from the other two groups (AUC 0.882 vs. AUC 0.810) or from IDHwt (AUC 0.923 vs. AUC 0.868).Conclusions: The combination of the T2/FLAIR mismatch sign with ADC or CBV histogram parameters can improve the identification of IDHmut-Noncodel diffuse lower-grade gliomas, which can be easily applied in clinical practice.Key Points: • The combination of the T2/FLAIR mismatch sign with the ADC or CBV histogram parameters can improve the identification of IDHmut-Noncodel diffuse lower-grade gliomas. • The multivariable model showed a significantly better performance for distinguishing the IDHmut-Noncodel group from other diffuse lower-grade gliomas than the T2/FLAIR mismatch sign alone or any single parameter. • The IDHmut-Noncodel type was associated with intermediate treatment outcomes; therefore, the identification of IDHmut-Noncodel diffuse lower-grade gliomas could be helpful for determining the clinical approach. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate the imaging features of isocitrate dehydrogenase (IDH) mutant glioma and to assess the diagnostic performance of magnetic resonance imaging (MRI) for prediction of IDH mutation in patients with glioma.Methods: A systematic search of Ovid-MEDLINE and EMBASE up to 10 October 2017 was conducted to find relevant studies. The search terms combined synonyms for 'glioma', 'IDH mutation' and 'MRI'. Studies evaluating the imaging features of IDH mutant glioma and the diagnostic performance of MRI for prediction of IDH mutation in patients with glioma were selected. The pooled summary estimates of sensitivity and specificity and their 95% confidence intervals (CIs) were calculated using a bivariate random-effects model. The results of multiple subgroup analyses are reported.Results: Twenty-eight original articles in a total of 2,146 patients with glioma were included. IDH mutant glioma showed frontal lobe predominance, less contrast enhancement, well-defined border, high apparent diffusion coefficient (ADC) value and low relative cerebral blood volume (rCBV) value. For the meta-analysis that included 18 original articles, the summary sensitivity was 86% (95% CI, 79%-91%) and the summary specificity was 87% (95% CI, 78-92%). In a subgroup analysis, the summary sensitivity of 2-hydroxyglutarate magnetic resonance spectroscopy (MRS) [96% (95% CI, 91-100%)] was higher than the summary sensitivities of other imaging modalities.Conclusions: IDH mutant glioma consistently demonstrated less aggressive imaging features than IDH wild-type glioma. Despite the variety of different MRI techniques used, MRI showed the potential to non-invasively predict IDH mutation in patients with glioma. 2-Hydroxyglutarate MRS shows higher pooled sensitivity than other imaging modalities.Key Points: • IDH mutant glioma showed frontal lobe predominance, less contrast enhancement, well-defined border, high ADC value, and low rCBV value. • The diagnostic performance of MRI for prediction of IDH mutation in patients with glioma is within a clinically acceptable range, the summary sensitivity was 86% (95% CI, 79-91%) and the summary specificity was 87% (95% CI, 78-92%). • In a subgroup analysis, the summary sensitivity of 2-hydroxyglutarate MRS [96% (95% CI, 91-100%)] was higher than the summary sensitivities of other imaging modalities. [ABSTRACT FROM AUTHOR]

Objectives: Differentiation of glioma from brain metastasis is clinically crucial because it affects the clinical outcome of patients and alters patient management. Here, we present a systematic review and meta-analysis of the currently available data on perfusion magnetic resonance imaging (MRI) for differentiating glioma from brain metastasis, assessing MRI protocols and parameters.Methods: A computerised search of Ovid-MEDLINE and EMBASE databases was performed up to 3 October 2017, to find studies on the diagnostic performance of perfusion MRI for differentiating glioma from brain metastasis. Pooled summary estimates of sensitivity and specificity were obtained using hierarchical logistic regression modelling. We conducted meta-regression and subgroup analyses to explain the effects of the study heterogeneity.Results: Eighteen studies with 900 patients were included. The pooled sensitivity and specificity were 90% (95% CI, 84-94%) and 91% (95% CI, 84-95%), respectively. The area under the hierarchical summary receiver operating characteristic curve was 0.96 (95% CI, 0.94-0.98). The meta-regression showed that the percentage of glioma in the study population and the study design were significant factors affecting study heterogeneity. In a subgroup analysis including patients with glioblastoma only, the pooled sensitivity was 92% (95% CI, 84-97%) and the pooled specificity was 94% (95% CI, 85-98%).Conclusions: Although various perfusion MRI techniques were used, the current evidence supports the use of perfusion MRI to differentiate glioma from brain metastasis. In particular, perfusion MRI showed excellent diagnostic performance for differentiating glioblastoma from brain metastasis.Key Points: • Perfusion MRI shows high diagnostic performance for differentiating glioma from brain metastasis. • The pooled sensitivity was 90% and pooled specificity was 91%. • Peritumoral rCBV derived from DSC is a relatively well-validated. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the value of multiparametric MRI for determination of early treatment response following concurrent chemoradiotherapy in patients with newly diagnosed glioblastoma.Methods: A computerized search of Ovid-MEDLINE and EMBASE up to 1 October 2017 was performed to find studies on the diagnostic performance of multiparametric MRI for differentiating true progression from pseudoprogression. The beginning search date was not specified. Pooled estimates of sensitivity and specificity were obtained using hierarchical logistic regression modeling. We performed meta-regression and sensitivity analyses to explain the effects of the study heterogeneity.Results: Nine studies including 456 patients were included. Pooled sensitivity and specificity were 84 % (95 % CI 74-91) and 95 % (95 % CI 83-99), respectively. Area under the hierarchical summary receiver operating characteristic curve was 0.95 (95 % CI 0.92-0.96). Meta-regression showed true progression in the study population, the mean age and the reference standard were significant factors affecting heterogeneity.Conclusion: Multiparametric MRI may be used as a potential surrogate endpoint for assessment of early treatment response, especially in the differentiation of true progression from pseudoprogression. However, based on the current evidence, monoparametric and multiparametric MRI perform equally in the clinical context. Further evaluation will be needed.Key Points: • Multiparametric MRI shows high diagnostic performance for early treatment response in glioblastoma. • Multiparametric MRI could differentiate true progression from pseudoprogression in newly diagnosed glioblastoma. • The normalized rCBV derived from DSC was the most commonly used parameter. [ABSTRACT FROM AUTHOR]

Objectives: To determine if gemistocytic grade II astrocytoma (GemA) and its MR imaging characteristics are associated with a shorter time-to-progression (TTP) compared with non-gemistocytic grade II astrocytoma (non-GemA).Materials and Methods: We enrolled 78 patients who were followed up more than 5 years (29 pathologically proven GemA and 49 non-GemA) during a 10-year period. Contrast-enhanced T1-weighted, diffusion-weighted imaging (DWI), dynamic susceptibility contrast (DSC), and MR spectroscopy (MRS) and clinical data were retrospectively reviewed. Clinical and MR imaging features were analyzed as possible prognostic factors of high-grade transformation, and multivariate analysis of TTP was performed using Cox proportional modeling.Results: GemA showed more frequent high-grade features than non-GemA, including diffusion restriction (P < .001), increased choline/creatine (P = .02), and increased choline/NAA ratio (P = .015). Patients with GemA had a significantly shorter median TTP (53.1 vs 68 months; P < .001). A gemistocytic histopathology (hazard ratio = 3.42; P = .015) and low ADC (hazard ratio = 3.61; P = .001) were independently associated with a shorter TTP.Conclusions: GemA can present with MR imaging findings mimicking high-grade glioma at initial diagnosis and transforms to high-grade disease earlier than non-GemA. Low ADC on DWI might be useful in stratifying the risk of progression in patients with grade II astrocytoma.Key Points: • Gemistocytic grade II astrocytoma (GemA) showed more frequent high-grade features than non-GemA. • Patients with GemA had a significantly shorter median TTP than non-GemA. • Gemistocytic histopathology and low ADC were independently associated with shorter TTP. [ABSTRACT FROM AUTHOR]

Objectives: The aim of this study was to determine whether diffusion and perfusion imaging parameters demonstrate different diagnostic values for predicting pseudoprogression between glioblastoma subgroups stratified by O6-mythylguanine-DNA methyltransferase (MGMT) promoter methylation status.Methods: We enrolled seventy-five glioblastoma patients that had presented with enlarged contrast-enhanced lesions on magnetic resonance imaging (MRI) one month after completing concurrent chemoradiotherapy and undergoing MGMT promoter methylation testing. The imaging parameters included 10 or 90 % histogram cutoffs of apparent diffusion coefficient (ADC10), normalized cerebral blood volume (nCBV90), and initial area under the time signal-intensity curve (IAUC90). The results of the areas under the receiver operating characteristic curve (AUCs) with cross-validation were compared between MGMT methylation and unmethylation groups.Results: MR imaging parameters demonstrated a trend toward higher accuracy in the MGMT promoter methylation group than in the unmethylation group (cross-validated AUCs = 0.70-0.95 and 0.56-0.87, respectively). The combination of MGMT methylation status with imaging parameters improved the AUCs from 0.70 to 0.75-0.90 for both readers in comparison with MGMT methylation status alone. The probability of pseudoprogression was highest (95.7 %) when nCBV90 was below 4.02 in the MGMT promoter methylation group.Conclusions: MR imaging parameters could be stronger predictors of pseudoprogression in glioblastoma patients with the methylated MGMT promoter than in patients with the unmethylated MGMT promoter.Key Points: • The glioblastoma subgroup was stratified according to MGMT promoter methylation status. • Diagnostic values of diffusion and perfusion parameters for predicting pseudoprogression were compared. • Imaging parameters showed higher diagnostic accuracy in the MGMT promoter methylation group. • Imaging parameters were independent to MGMT promoter methylation status for predicting pseudoprogression. • Imaging biomarkers might demonstrate different diagnostic values according to MGMT promoter methylation. [ABSTRACT FROM AUTHOR]

Objectives: To determine the added value of amide proton transfer (APT) imaging to conventional and perfusion MRI for differentiating tumour progression (TP) from the treatment-related effect (TE) in patients with post-treatment glioblastomas.Methods: Sixty-five consecutive patients with enlarging contrast-enhancing lesions following concurrent chemoradiotherapy were assessed using contrast-enhanced T1-weighted MRI (CE-T1WI), 90th percentile histogram parameters of normalized cerebral blood volume (nCBV90) and APT asymmetry value (APT90). Diagnostic performance was determined using the area under the receiver operating characteristic curve (AUC) and cross validations.Results: There were statistically significant differences in the mean APT90 between the TP and the TE groups (3.87-4.01 % vs. 1.38-1.41 %; P < .001). Compared with CE-T1WI alone, the addition of APT90 to CE-T1WI significantly improved cross-validated AUC from 0.58-0.74 to 0.89-0.91 for differentiating TP from TE. The combination of CE-T1WI, nCBV90 and APT90 resulted in greater diagnostic accuracy for differentiating TP from TE than the combination of CE-T1WI and nCBV90 (cross-validated AUC, 0.95-0.97 vs. 0.84-0.91). The inter-reader agreement between the expert and trainee was excellent for the measurements of APT90 (intraclass correlation coefficient, 0.94).Conclusion: Adding APT imaging to conventional and perfusion MRI improves the diagnostic performance for differentiating TP from TE.Key Points: • APT imaging could provide a reliable distinction between TP and TE • Adding APT imaging to CE-T1WI improved the diagnostic accuracy versus CE-T1WI alone • Multimodal imaging using CE-T1WI, perfusion and APT imaging led to accurate diagnosis • The inter-reader agreement of APT histogram parameters was excellent. [ABSTRACT FROM AUTHOR]

Objectives: To determine the diagnostic superiority of parametric response mapping of apparent diffusion coefficient (ADCPR) for predicting glioblastoma treatment response, compared to single time point measurement.Methods: Fifty post-treatment glioblastoma patients were enrolled. ADCPR was calculated from serial apparent diffusion coefficient (ADC) maps acquired before and at the time of first detection of an enlarged contrast-enhancing lesion on voxel-by-voxel basis. The percentage-decrease in ADCPR and tenth percentile histogram cutoff value of ADC (ADC10) were compared at subsequent 3-month and 1-year follow-ups.Results: The percentage-decrease in ADCPR was significantly higher in the progression group (mean = 33.2-38.3 %) than in the stable-response group (mean = 9.7 %) at 3 months follow-up (corrected p < 0.001 for both readers). ADCPR significantly improved area under the receiver operating characteristic curve from 0.67 to 0.88 (corrected p = 0.037) and from 0.70 to 0.92 (corrected p = 0.020) for both readers, respectively, compared to ADC10 at 3-month follow-up, but did not significantly improve at 1-year follow-up. The inter-reader agreement was higher for ADCPR than ADC10 (intraclass correlation coefficient, 0.93 versus 0.86).Conclusion: Voxel-based ADCPR appears to be a superior imaging biomarker than ADC, particularly for predicting early tumour progression in patients with glioblastoma.Key Points: • Treatment response pattern of glioblastoma was evaluated using voxel-based ADCPR and ADC10. • Voxel-based ADCPR was more accurate in predicting treatment response pattern than ADC10. • Inter-reader agreement was higher in ADCPR calculation than in ADC10 calculation. • Voxel-based ADCPR can be a predictor of early treatment response pattern for glioblastoma. [ABSTRACT FROM AUTHOR]