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Objective: This study aimed to evaluate whether arterial input functions (AIFs) obtained from dynamic susceptibility contrast (DSC)-MRI (AIF DSC ) improve the reliability and diagnostic accuracy of dynamic contrast-enhanced (DCE)-derived pharmacokinetic (PK) parameters for differentiating glioblastoma from primary CNS lymphoma (PCNSL) compared with AIFs derived from DCE-MRI (AIF DCE )., Methods: This retrospective study included 172 patients with glioblastoma (n = 147) and PCNSL (n = 25). All patients had undergone preoperative DSC- and DCE-MRI. The volume transfer constant (K trans ), volume of the vascular plasma space (v p ), and volume of the extravascular extracellular space (v e ) were acquired using AIF DSC and AIF DCE . The relative cerebral blood volume (rCBV) was obtained from DSC-MRI. Intraclass correlation coefficients (ICC) and ROC curves were used to assess the reliability and diagnostic accuracy of individual parameters., Results: The mean K trans , v p , and v e values revealed better ICCs with AIF DSC than with AIF DCE (K trans , 0.911 vs 0.355; v p , 0.766 vs 0.503; v e , 0.758 vs 0.657, respectively). For differentiating all glioblastomas from PCNSL, the mean rCBV (AUC = 0.856) was more accurate than the AIF DSC -driven mean K trans , which had the largest AUC (0.711) among the DCE-derived parameters (p = 0.02). However, for glioblastomas with low rCBV (≤ 75th percentile of PCNSL; n = 30), the AIF DSC -driven mean K trans and v p were more accurate than rCBV (AUC: K trans , 0.807 vs rCBV, 0.515, p = 0.004; v p , 0.715 vs rCBV, p = 0.045)., Conclusion: DCE-derived PK parameters using the AIF DSC showed improved reliability and diagnostic accuracy for differentiating glioblastoma with low rCBV from PCNSL., Key Points: • An accurate differential diagnosis of glioblastoma and PCNSL is crucial because of different therapeutic strategies. • In contrast to the rCBV from DSC-MRI, another perfusion imaging technique, the DCE parameters for the differential diagnosis have been limited because of the low reliability of AIFs from DCE-MRI. • When we analyzed DCE-MRI data using AIFs from DSC-MRI (AIF DSC ), AIF DSC -driven DCE parameters showed improved reliability and better diagnostic accuracy than rCBV for differentiating glioblastoma with low rCBV from PCNSL., (© 2021. European Society of Radiology.)

Objective: To develop a radiomics risk score based on dynamic contrast-enhanced (DCE) MRI for prognosis prediction in patients with glioblastoma., Materials and Methods: One hundred and fifty patients (92 male [61.3%]; mean age ± standard deviation, 60.5 ± 13.5 years) with glioblastoma who underwent preoperative MRI were enrolled in the study. Six hundred and forty-two radiomic features were extracted from volume transfer constant (K trans ), fractional volume of vascular plasma space (V p ), and fractional volume of extravascular extracellular space (V e ) maps of DCE MRI, wherein the regions of interest were based on both T1-weighted contrast-enhancing areas and non-enhancing T2 hyperintense areas. Using feature selection algorithms, salient radiomic features were selected from the 642 features. Next, a radiomics risk score was developed using a weighted combination of the selected features in the discovery set (n = 105); the risk score was validated in the validation set (n = 45) by investigating the difference in prognosis between the "radiomics risk score" groups. Finally, multivariable Cox regression analysis for progression-free survival was performed using the radiomics risk score and clinical variables as covariates., Results: 16 radiomic features obtained from non-enhancing T2 hyperintense areas were selected among the 642 features identified. The radiomics risk score was used to stratify high- and low-risk groups in both the discovery and validation sets (both p < 0.001 by the log-rank test). The radiomics risk score and presence of isocitrate dehydrogenase (IDH) mutation showed independent associations with progression-free survival in opposite directions (hazard ratio, 3.56; p = 0.004 and hazard ratio, 0.34; p = 0.022, respectively)., Conclusion: We developed and validated the "radiomics risk score" from the features of DCE MRI based on non-enhancing T2 hyperintense areas for risk stratification of patients with glioblastoma. It was associated with progression-free survival independently of IDH mutation status., Competing Interests: The authors have no potential conflicts of interest to disclose., (Copyright © 2021 The Korean Society of Radiology.)

Objective: Few attempts have been made to investigate the prognostic value of dynamic contrast-enhanced (DCE) MRI or dynamic susceptibility contrast (DSC) MRI of non-enhancing, T2-high-signal-intensity (T2-HSI) lesions of glioblastoma multiforme (GBM) in newly diagnosed patients. This study aimed to investigate the prognostic values of DCE MRI and DSC MRI parameters from non-enhancing, T2-HSI lesions of GBM., Materials and Methods: A total of 76 patients with GBM who underwent preoperative DCE MRI and DSC MRI and standard treatment were retrospectively included. Six months after surgery, the patients were categorized into early progression (n = 15) and non-early progression (n = 61) groups. We extracted and analyzed the permeability and perfusion parameters of both modalities for the non-enhancing, T2-HSI lesions of the tumors. The optimal percentiles of the respective parameters obtained from cumulative histograms were determined using receiver operating characteristic (ROC) curve and univariable Cox regression analyses. The results were compared using multivariable Cox proportional hazards regression analysis of progression-free survival., Results: The 95th percentile value (PV) of Ktrans, mean Ktrans, and median Ve were significant predictors of early progression as identified by the ROC curve analysis (area under the ROC curve [AUC] = 0.704, p = 0.005; AUC = 0.684, p = 0.021; and AUC = 0.670, p = 0.0325, respectively). Univariable Cox regression analysis of the above three parametric values showed that the 95th PV of Ktrans and the mean Ktrans were significant predictors of early progression (hazard ratio [HR] = 1.06, p = 0.009; HR = 1.25, p = 0.017, respectively). Multivariable Cox regression analysis, which also incorporated clinical parameters, revealed that the 95th PV of Ktrans was the sole significant independent predictor of early progression (HR = 1.062, p < 0.009)., Conclusion: The 95th PV of Ktrans from the non-enhancing, T2-HSI lesions of GBM is a potential prognostic marker for disease progression., Competing Interests: The authors have no potential conflicts of interest to disclose., (Copyright © 2021 The Korean Society of Radiology.)

Glioblastoma remains the most devastating brain tumor despite optimal treatment, because of the high rate of recurrence. Distant recurrence has distinct genomic alterations compared to local recurrence, which requires different treatment planning both in clinical practice and trials. To date, perfusion-weighted MRI has revealed that perfusional characteristics of tumor are associated with prognosis. However, not much research has focused on recurrence patterns in glioblastoma: namely, local and distant recurrence. Here, we propose two different neural network models to predict the recurrence patterns in glioblastoma that utilizes high-dimensional radiomic profiles based on perfusion MRI: area under the curve (AUC) (95% confidence interval), 0.969 (0.903-1.000) for local recurrence; 0.864 (0.726-0.976) for distant recurrence for each patient in the validation set. This creates an opportunity to provide personalized medicine in contrast to studies investigating only group differences. Moreover, interpretable deep learning identified that salient radiomic features for each recurrence pattern are related to perfusional intratumoral heterogeneity. We also demonstrated that the combined salient radiomic features, or "radiomic risk score", increased risk of recurrence/progression (hazard ratio, 1.61; p = 0.03) in multivariate Cox regression on progression-free survival.

Objective: To evaluate pharmacokinetic variables from contrast-enhancing lesions (CELs) and non-enhancing T2 high signal intensity lesions (NE-T2HSILs) on dynamic contrast-enhanced (DCE) magnetic resonance (MR) imaging for predicting progression-free survival (PFS) in glioblastoma (GBM) patients., Materials and Methods: Sixty-four GBM patients who had undergone preoperative DCE MR imaging and received standard treatment were retrospectively included. We analyzed the pharmacokinetic variables of the volume transfer constant (Ktrans) and volume fraction of extravascular extracellular space within the CEL and NE-T2HSIL of the entire tumor. Univariate and multivariate Cox regression analyses were performed using preoperative clinical characteristics, pharmacokinetic variables of DCE MR imaging, and postoperative molecular biomarkers to predict PFS., Results: The increased mean Ktrans of the CEL, increased 95th percentile Ktrans of the CELs, and absence of methylated O⁶-methylguanine-DNA methyltransferase promoter were relevant adverse variables for PFS in the univariate analysis ( p = 0.041, p = 0.032, and p = 0.083, respectively). The Kaplan-Meier survival curves demonstrated that PFS was significantly shorter in patients with a mean Ktrans of the CEL > 0.068 and 95th percentile Ktrans of the CEL>0.223 (log-rank p = 0.038 and p = 0.041, respectively). However, only mean Ktrans of the CEL was significantly associated with PFS ( p = 0.024; hazard ratio, 553.08; 95% confidence interval, 2.27-134756.74) in the multivariate Cox proportional hazard analysis. None of the pharmacokinetic variables from NE-T2HSILs were significantly related to PFS., Conclusion: Among the pharmacokinetic variables extracted from CELs and NE-T2HSILs on preoperative DCE MR imaging, the mean Ktrans of CELs exhibits potential as a useful imaging predictor of PFS in GBM patients., Competing Interests: The authors have no potential conflicts of interest to disclose., (Copyright © 2020 The Korean Society of Radiology.)

Objectives: Prediction of progression-free survival (PFS) and overall survival (OS) and early identification of molecular biomarkers with prognostic information are clinically important in glioblastoma (GBM) patients. We aimed to explore the utility of arterial spin labeling perfusion-weighted imaging (ASL-PWI) in the prediction of molecular biomarkers and survival in GBM patients., Methods: We retrospectively analyzed 149 consecutive GBM patients, who had undergone maximal surgical resection or biopsy followed by concurrent chemoradiotherapy and adjuvant chemotherapy using temozolomide between November 2010 and June 2016. On preoperative ASL-PWI, cerebral blood flow (CBF) within contrast-enhancing (CE) and nonenhancing (NE) portions were evaluated both qualitatively (perfusion pattern [CE] and perfusion pattern [NE] ) and quantitatively (nCBF CE and nCBF NE ). ASL-PWI findings were correlated with molecular biomarkers, including isocitrate dehydrogenase (IDH) and O6-methylguanine-DNA methyltransferase (MGMT) methylation statuses, and survival, using the Mann-Whitney U-test, Spearman rank correlation, Kaplan-Meier analysis, and receiver operating characteristics analysis., Results: nCBF CE was significantly higher in the IDH wild-type group than in the IDH mutant group (p = .013) and in the MGMT unmethylated group than in the methylated group (p = .047). Areas under the receiver operating characteristic curve were 0.678 for IDH mutation (p = .022) and 0.601 for MGMT promoter methylation (p = .043). Hyperperfusion was associated with the shortest median PFS for both perfusion pattern [CE] (7.6 months) and perfusion pattern [NE] (4.0 months). The perfusion pattern [NE] remained an independent predictor for PFS and OS even after adjusting for clinical and molecular predictors, unlike perfusion pattern [CE] ., Conclusions: ASL-PWI can aid to predict survival and molecular biomarkers including IDH mutation and MGMT promoter methylation statuses in GBM patients., Key Points: • ASL-PWI can aid to predict survival in GBM patients. • ASL-PWI can aid to predict IDH and MGMT promoter methylation statuses in GBM.

Objectives: To assess the association between MR imaging features and major genomic profiles in glioblastoma., Methods: Qualitative and quantitative imaging features such as volumetrics and histogram analysis from normalised CBV (nCBV) and ADC (nADC) were evaluated based on both T2WI and CET1WI. The imaging parameters of different genetic profile groups were compared and regression analyses were used for identifying imaging-molecular associations. Progression-free survival (PFS) was analysed by a Kaplan-Meier test and Cox proportional hazards model., Results: An IDH mutation was observed in 18/176 patients, and ATRX loss was positive in 17/158 of the IDH-wt cases. The IDH-mut group showed a larger volume on T2WI and a higher volume ratio between T2WI and CET1WI than the IDH-wt group (p < 0.05). In the IDH-mut group, higher mean nADC values were observed compared with the IDH-wt tumours (p < 0.05). Among the IDH-wt tumours, IDH-wt, ATRX-loss tumours revealed higher 5th percentile nADC values than the IDH-wt, ATRX-noloss tumours (p = 0.03). PFS was the longest in the IDH-mut group, followed by the IDH-wt, ATRX-loss groups and the IDH-wt, ATRX-noloss groups, consecutively (p < 0.05). We found significant associations of PFS with the genetic profiles and imaging parameters., Conclusion: Major genetic profiles of glioblastoma showed a significant association with MR imaging features, along with some genetic profiles, which are independent prognostic parameters for GBM., Key Points: • Significant correlation exists between radiological parameters such as volumetric and ADC values and major genomic profiles such as IDH mutation and ATRX loss status • Radiological parameters such as the ADC value were feasible predictors of glioblastoma patients' prognosis • Imaging features can predict major genomic profiles of the tumours and the prognosis of glioblastoma patients.

Objectives: To evaluate the diagnostic performance of arterial spin labelling perfusion weighted images (ASL-PWIs) to differentiate primary CNS lymphoma (PCNSL) from glioblastoma (GBM)., Methods: ASL-PWIs of pathologically confirmed PCNSL (n = 21) or GBM (n = 93) were analysed. For qualitative analysis, tumours were visually scored into five categories based on ASL-CBF maps. For quantitative analysis, normalised CBF values were derived by contralateral grey matter (GM) in intra- and peritumoral areas (nCBF intratumoral and nCBF peritumoral , respectively). Visual scoring scales and quantitative parameters from PCNSL and GBM were compared. In addition, the area under the receiver-operating characteristic (ROC) curve was used to determine the diagnostic accuracy of ASL-PWI for differentiating PCNSL from GBM. Weighted kappa or intraclass correlation coefficients (ICCs) were used to assess reliability between two observers., Results: In qualitative analysis, scores 5 (CBF intratumoral >CBF GM , 68.8% [64/93]) and 4 (CBF intratumoral ≈ CBF GM , 47.6% [10/21]) were the most frequently reported scores for GBM and PCNSL, respectively. In quantitative analysis, both nCBF intratumoral and nCBF peritumoral in PCNSL were significantly lower than those in the GBM (nCBF intratumoral , 0.89 ± 0.59 [mean and SD] vs. 2.68 ± 1.89, p < 0.001; nCBF peritumoral , 0.17 ± 0.08 vs. 0.45 ± 0.28, p < 0.001). nCBF peritumoral demonstrated the best diagnostic performance (area under the ROC curve: visual scoring, 0.814; nCBF intratumoral , 0.849; nCBF peritumoral , 0.908; p < 0.001 for all). Interobserver agreements for visual scoring (weighted kappa = 0.869), nCBF intratumoral&#95;GM (ICC = 0.958) and nCBF peritumoral&#95;GM (ICC = 0.947) were all excellent., Conclusions: ASL-PWI performs well in differentiating PCNSL from GBM in both qualitative and quantitative analyses., Key Points: • ASL-PWI performs well (AUC > 0.8) in differentiating PCNSL from GBM. • The visual scoring template demonstrated good diagnostic performance, similar to quantitative analysis. • nCBF peritumoral demonstrated better diagnostic performance than nCBF intratumoral or visual scoring.

Objective: This study evaluated the possibility of accelerated gadolinium accumulation in irradiated brain parenchyma where the blood-brain barrier was weakened., Methods: From January 2010 to June 2015, 44 patients with supratentorial glioblastoma were retrospectively identified who underwent pre- and post-radiation brain MR imaging, including R1 mapping. The mean dose of administered gadobutrol (Gadovist, Bayer, Germany) was 5.1 vials. Regions of interest (ROIs) were drawn around tumors that were located within 50-100% iso-dose lines of maximum radiation dose. ROIs were also drawn at globus pallidus, thalamus, and cerebral white matter. Averages of R1 values (unit: s-1) before and after radiation and those of R1 ratio (post-radiation R1 / pre-radiation R1) were compared by t-test or rank sum test as appropriate. Multiple linear regression analysis was performed to evaluate independent association factors for R1 value increase at irradiated parenchyma., Results: The mean R1 values in peri-tumoral areas were significantly increased after radiotherapy (0.7901±0.0977 [mean±SD] vs. 0.8146±0.1064; P <.01). The mean R1 ratio of high radiation dose areas was significantly higher than that of low dose areas (1.0055±0.0654 vs. 0.9882±0.0642; P <.01). The mean R1 ratio was lower in those who underwent hypofractionated radiotherapy (mean dose, 45.0 Gy) than those who underwent routine radiotherapy (mean dose, 61.1 Gy) (0.9913±0.0740 vs. 1.0463±0.0633; P = .08). Multiple linear regression analysis revealed that only radiotherapy type was significantly associated with increased R1 (P = .02) around tumors., Conclusions: Radiotherapy can induce R1 value increase in the brain parenchyma, which might suggest accelerated gadolinium accumulation due to damage to the blood-brain barrier.

Objectives: To prospectively explore the value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in predicting the progression of enhancing lesions persisting after standard treatment in patients with surgically resected glioblastoma (GBM)., Methods: Forty-seven GBM patients, who underwent near-total tumorectomy followed by concurrent chemoradiation therapy (CCRT) with temozolomide (TMZ) between May 2014 and February 2016, were enrolled. Twenty-four patients were finally analyzed for measurable enhancing lesions persisting after standard treatment. DCE-MRI parameters were calculated at enhancing lesions. Mann-Whitney U tests and multivariable stepwise logistic regression were used to compare parameters between progression (n = 16) and non-progression (n = 8) groups., Results: Mean K trans and v e were significantly lower in progression than in non-progression (P = 0.037 and P = 0.037, respectively). The 5th percentile of the cumulative K trans histogram was also significantly lower in the progression than in non-progression group (P = 0.017). Mean v e was the only independent predictor of progression (P = 0.007), with a sensitivity of 100%, specificity of 63%, and an overall accuracy of 88% at a cut-off value of 0.873., Conclusions: DCE-MRI may help predict the progression of enhancing lesions persisting after the completion of standard treatment in patients with surgically resected GBM, with mean v e serving as an independent predictor of progression., Key Points: • Enhancing lesions may persist after standard treatment in GBM patients. • DCE-MRI may help predict the progression of the enhancing lesions. • Mean K trans and v e were lower in progression than in non-progression group. • DCE-MRI may help identify patients requiring close follow-up after standard treatment. • DCE-MRI may help plan treatment strategies for GBM patients.

Objectives: To identify candidate imaging biomarkers for early disease progression in glioblastoma multiforme (GBM) patients by analysis of dynamic contrast-enhanced (DCE) MR parameters of non-enhancing T2 high signal intensity (SI) lesions., Methods: Forty-nine GBM patients who had undergone preoperative DCE MR imaging and received standard treatment were retrospectively included. According to the Response Assessment in Neuro-Oncology criteria, patients were classified into progression (n = 21) or non-progression (n = 28) groups. We analysed the pharmacokinetic parameters of Ktrans, Ve and Vp within non-enhancing T2 high SI lesions of each tumour. The best percentiles of each parameter from cumulative histograms were identified by the area under the receiver operating characteristic curve (AUC) and were compared using multivariate stepwise logistic regression., Results: For the differentiation of early disease progression, the highest AUC values were found in the 99th percentile of Ktrans (AUC 0.954), the 97th percentile of Ve (AUC 0.815) and the 94th percentile of Vp (AUC 0.786) (all p < 0.05). The 99th percentile of Ktrans was the only significant independent variable from the multivariate stepwise logistic regression (p = 0.002)., Conclusions: We found that the Ktrans of non-enhancing T2 high SI lesions in GBM patients holds potential as a candidate prognostic marker in future prospective studies., Key Points: • DCE MR imaging provides candidate prognostic marker of GBM after standard treatment. • Cumulative histogram was applied to include entire non-enhancing T2 high SI lesions. • The 99th percentile value of Ktrans was the most likely potential biomarker.

Purpose: To evaluate the diagnostic performance of cerebral blood flow (CBF) by using arterial spin labeling (ASL) perfusion magnetic resonance (MR) imaging to differentiate glioblastoma (GBM) from brain metastasis., Materials and Methods: The institutional review board of our hospital approved this retrospective study. The study population consisted of 128 consecutive patients who underwent surgical resection and were diagnosed as either GBM (n = 89) or brain metastasis (n = 39). All participants underwent preoperative MR imaging including ASL. For qualitative analysis, the tumors were visually graded into five categories based on ASL-CBF maps by two blinded reviewers. For quantitative analysis, the reviewers drew regions of interest (ROIs) on ASL-CBF maps upon the most hyperperfused portion within the tumor and upon peritumoral T2 hyperintensity area. Signal intensities of intratumoral and peritumoral ROIs for each subject were normalized by dividing the values by those of contralateral normal gray matter (nCBFintratumoral and nCBFperitumoral, respectively). Visual grading scales and quantitative parameters between GBM and brain metastasis were compared. In addition, the area under the receiver-operating characteristic curve was used to evaluate the diagnostic performance of ASL-driven CBF to differentiate GBM from brain metastasis., Results: For qualitative analysis, GBM group showed significantly higher grade compared to metastasis group (p = 0.001). For quantitative analysis, both nCBFintratumoral and nCBFperitumoral in GBM were significantly higher than those in metastasis (both p < 0.001). The areas under the curve were 0.677, 0.714, and 0.835 for visual grading, nCBFintratumoral, and nCBFperitumoral, respectively (all p < 0.001)., Conclusion: ASL perfusion MR imaging can aid in the differentiation of GBM from brain metastasis., Competing Interests: The authors have declared that no competing interests exist.

Purpose: To analyze the enhancement patterns and apparent diffusion coefficient (ADC) values of non-measurable surgical cavity wall enhancement pattern, newly appearing after completion of standard concurrent chemoradiotherapy (CCRT) with temozolomide in glioblastoma patients for the prognosis prediction., Materials and Methods: From January 2010 to April 2014, among 190 patients with histopathologically confirmed glioblastoma, a total of 33 patients with non-measurable wall enhancement on post-CCRT MR imaging were enrolled and divided into two subgroups: non-progression (n = 18) and progression groups (n = 15). We analyzed the wall enhancement patterns, which were categorized into three patterns: thin, thick and nodular enhancement. ADC values were measured in the enhancing portions of the walls. The progression-free survival (PFS) related to the wall enhancement was analyzed by Kaplan-Meier analysis, and survival curves were compared using the log-rank test., Results: Statistically significant differences in the surgical cavity wall enhancement patterns was shown between the progression and non-progression groups (P = 0.0032). Thin wall enhancement was more frequently observed in the non-progression group, and thick or nodular wall enhancement were observed in the progression group (P = 0.0016). There was no statistically significant difference in the mean ADC values between the progression and non-progression groups. The mean PFS was longer in patients with thin wall enhancement than in those with nodular or thick wall enhancement (35.5 months vs. 15.8 months, P = 0.008)., Conclusion: Pattern analysis of non-measurable surgical cavity wall enhancement on post-CCRT MR imaging might be useful tool for predicting prognosis of GBM patient before clear progression of non-measurable disease., Competing Interests: The authors have declared that no competing interests exist.

Purpose: To explore the role of dynamic contrast material-enhanced magnetic resonance (MR) imaging in the differentiation of true progression from pseudoprogression in patients with glioblastoma on the basis of findings in entirely newly developed or enlarged enhancing lesions after concurrent radiation therapy and chemotherapy with temozolomide and to evaluate the diagnostic performance of the quantitative pharmacokinetic parameters obtained at dynamic contrast-enhanced MR imaging, such as the volume transfer constant (K(trans)), the extravascular extracellular space per unit volume of tissue(ve), and the blood plasma volume per unit volume of tissue(vp)., Materials and Methods: This prospective study had institutional review board approval; written informed consent was obtained from all patients. Thirty-three patients with histopathologically proven glioblastoma who had undergone concurrent radiation therapy and chemotherapy with temozolomide were included. Dynamic contrast-enhanced MR imaging-derived pharmacokinetic parameters, including K(trans), ve, and vp, were calculated for newly developed or enlarged enhancing lesions. Pharmacokinetic parameters were compared between the true progression (n = 17) and pseudoprogression (n = 16) groups by using unpaired t tests and then multivariable analysis., Results: The mean K(trans) and ve were higher in the true progression group than in the pseudoprogression group (mean K(trans), 0.44 min(-1) ± 0.25 [standard deviation] and 0.23 min(-1) ± 0.10 for true progression and pseudoprogression groups, respectively, P = .004; and mean ve, 1.26 ± 0.78 and 0.75 ± 0.49 for true progression and pseudoprogression groups, respectively, P = .034). Multivariable analysis showed that mean K(trans) was the only independently differentiating variable (P = .004)., Conclusion: Dynamic contrast-enhanced MR imaging-derived pharmacokinetic parameters, including K(trans) and ve, in the entire newly developed or enlarged enhancing lesion may be useful objective diagnostic tools in the differentiation of true progression from pseudoprogression in patients with glioblastoma who have undergone concurrent radiation therapy and chemotherapy with temozolomide.

Purpose: To assess the prognosis predictability of a measurable enhancing lesion using histogram parameters produced by the normalized cerebral blood volume (nCBV) and normalized apparent diffusion coefficient (nADC) after completion of standard concomitant chemoradiotherapy (CCRT) and adjuvant temozolomide (TMZ) medication in glioblastoma multiforme (GBM) patients., Materials and Methods: This study was approved by the institutional review board (IRB), and the requirement for informed consent was waived. A total of 59 patients with newly diagnosed GBM who received standard CCRT with TMZ and adjuvant TMZ for six cycles underwent perfusion-weighted and diffusion-weighted imaging. Twenty-seven patients had a measurable enhancing lesion and 32 patients lacked a measurable enhancing lesion based on the Response Assessment in Neuro-Oncology (RANO) criteria in the follow-up MRI, which was performed within 3 months after adjuvant TMZ therapy was completed. We measured the nCBV and nADC histogram parameters based on the measurable enhancing lesion. The progression free survival (PFS) was analyzed by the Kaplan-Meier method with the use of the log-rank test., Results: The median PFS of patients lacking measurable enhancing lesion was longer than for those with measurable enhancing lesions (17.6 vs 3.3 months, P<.0001). There was a significant, positive correlation between the 99th percentile nCBV value of a measurable enhancing lesion and the PFS (P= .044, R(2)= .152). In addition, the median PFS was longer in patients with a 99th percentile nCBV value ≧ 4.5 than it was in those with a value <4.5 (4.4 vs 3.1 months, P = .036)., Conclusion: We found that the nCBV value can be used for the prognosis prediction of a measurable enhancing lesion after the completion of standard treatment for GBM, wherein a high 99th percentile nCBV value (≧ 4.5) suggests a better PFS for GBM patients.

A 45-yr-old female patient was admitted with one-month history of headache and progressive left hemiparesis. Brain magnetic resonance imaging (MRI) demonstrated a mass lesion in her right frontal lobe. Her brain tumor was confirmed as a small cell glioblastoma. Her follow-up brain MRI, taken at 8 months after her initial surgery demonstrated tumor recurrence in the right frontal lobe. Contrast-enhanced 7.0T brain magnetic resonance imaging (MRI) was safely performed before surgery and at the time of recurrence. Compared with 1.5T and 3.0T brain MRI, 7.0T MRI showed sharpened images of the brain tumor contexture with detailed anatomical information. The fused images of 7.0T and 1.5T brain MRI taken at the time of recurrence demonstrated no significant discrepancy in the positions of the anterior and the posterior commissures. It is suggested that 7.0T MRI can be safely utilized for better images of the maligant gliomas before and after surgery.

Purpose: To explore the role of histogram analysis of apparent diffusion coefficient (ADC) maps obtained at standard- and high-b-value (1000 and 3000 sec/mm(2), respectively) diffusion-weighted (DW) imaging in the differentiation of true progression from pseudoprogression in glioblastoma treated with radiation therapy and concomitant temozolomide., Materials and Methods: This retrospective study was approved by the institutional review board of Seoul National University Hospital, and informed consent requirement was waived. Thirty patients with histopathologically proved glioblastoma who had undergone concurrent chemotherapy and radiation therapy (CCRT) with temozolomide underwent diffusion-weighted MR imaging with b values of 1000 and 3000 sec/mm(2), and corresponding ADC maps were calculated from entire newly developed or enlarged enhancing lesions after completion of CCRT. Histogram parameters of each ADC map between true progression (n = 15) and pseudoprogression (n = 15) groups were compared by using the unpaired Student t test. Receiver operating characteristic analysis was used to determine the best cutoff values for predictors in the differentiation of true progression from pseudoprogression. Results were validated in an independent test set of nine patients by using the best cutoff value to predict differentiation of true progression from pseudoprogression. The accuracy of the selected best cutoff value in the independent test set was then calculated., Results: In terms of cumulative histograms, the fifth percentile of both ADC at b value of 1000 sec/mm(2) (ADC1000) and the ADC at b value of 3000 sec/mm(2) (ADC3000) were significantly lower in the true progression group than in the pseudoprogression group (P = .049 and P < .001, respectively). In contrast, neither the mean ADC1000 nor the mean ADC3000 was significantly different between the two groups. The diagnostic values of the parameters derived from ADC1000 and ADC3000 were compared, and a significant difference (0.224, P = .016) was found between the area under the receiver operating characteristic curve of the fifth percentile for ADC1000 and that for ADC3000. The accuracies were 66.7% (six of nine patients) and 88.9% (eight of nine patients) based on the fifth percentile of both ADC1000 and ADC3000 in the independent test set, respectively., Conclusion: The fifth percentile of the cumulative ADC histogram obtained at a high b value was the most promising parameter in the differentiation of true progression from pseudoprogression of the newly developed or enlarged enhancing lesions after CCRT with temozolomide for glioblastoma treatment. Online supplemental material is available for this article., (© RSNA, 2013.)

Purpose: To evaluate the usefulness of pseudo-continuous arterial spin labeling (pCASL) imaging in differentiating high-grade gliomas from lymphomas and in noninvasively predicting genetic biomarkers in high-grade gliomas., Materials and Methods: Twelve glioblastoma multiforme (GBM), 3 anaplastic astrocytoma (AA), 5 recurred GBM, and 9 lymphoma patients underwent conventional MR and pCASL imaging. On pCASL perfusion map, mean absolute tumor blood flow (mTBF) was calculated from five regions of interest (ROIs) within the enhancing portion of the tumor. Relative TBF (rTBF = mTBF/mBFgm × 100) was also calculated. mTBF and rTBF of high-grade gliomas and lymphomas were compared using unpaired Student's t-test and receiver operating characteristic (ROC) analysis. Additionally, the association of TBF and six immunohistochemically confirmed genetic biomarkers was analyzed by Pearson correlation analysis in the group of high-grade gliomas., Results: Both mTBF and rTBF of the high-grade gliomas were significantly higher than those of the lymphomas: 92.1 ± 34.7 versus 53.6 ± 30.5 mL/min/100 mg (P = 0.008) and 182.3 ± 69.5 versus 92.5 ± 44.9 (P = 0.002), respectively. Only epidermal growth factor receptor (EGFR) expression status showed a significant positive correlation with mTBF(P = 0.015) and rTBF(P = 0.007)., Conclusion: pCASL imaging may facilitate differentiation of high-grade gliomas from lymphomas and prediction of EGFR expression status in high-grade gliomas., (Copyright © 2013 Wiley Periodicals, Inc.)

Purpose: To evaluate the usefulness of dynamic susceptibility contrast (DSC) enhanced perfusion MR imaging in predicting major genetic alterations in glioblastomas., Materials and Methods: Twenty-five patients (M:F = 13∶12, mean age: 52.1±15.2 years) with pathologically proven glioblastoma who underwent DSC MR imaging before surgery were included. On DSC MR imaging, the normalized relative tumor blood volume (nTBV) of the enhancing solid portion of each tumor was calculated by using dedicated software (Nordic TumorEX, NordicNeuroLab, Bergen, Norway) that enabled semi-automatic segmentation for each tumor. Five major glioblastoma genetic alterations (epidermal growth factor receptor (EGFR), phosphatase and tensin homologue (PTEN), Ki-67, O6-methylguanine-DNA methyltransferase (MGMT) and p53) were confirmed by immunohistochemistry and analyzed for correlation with the nTBV of each tumor. Statistical analysis was performed using the unpaired Student t test, ROC (receiver operating characteristic) curve analysis and Pearson correlation analysis., Results: The nTBVs of the MGMT methylation-negative group (mean 9.5±7.5) were significantly higher than those of the MGMT methylation-positive group (mean 5.4±1.8) (p = .046). In the analysis of EGFR expression-positive group, the nTBVs of the subgroup with loss of PTEN gene expression (mean: 10.3±8.1) were also significantly higher than those of the subgroup without loss of PTEN gene expression (mean: 5.6±2.3) (p = .046). Ki-67 labeling index indicated significant positive correlation with the nTBV of the tumor (p = .01)., Conclusion: We found that glioblastomas with aggressive genetic alterations tended to have a high nTBV in the present study. Thus, we believe that DSC-enhanced perfusion MR imaging could be helpful in predicting genetic alterations that are crucial in predicting the prognosis of and selecting tailored treatment for glioblastoma patients.

Purpose: To compare the reproducibilities of manual and semiautomatic segmentation method for the measurement of normalized cerebral blood volume (nCBV) using dynamic susceptibility contrast-enhanced (DSC) perfusion MR imaging in glioblastomas., Materials and Methods: Twenty-two patients (11 male, 11 female; 27 tumors) with histologically confirmed glioblastoma (WHO grade IV) were examined with conventional MR imaging and DSC imaging at 3T before surgery or biopsy. Then nCBV (means and standard deviations) in each mass was measured using two DSC MR perfusion analysis methods including manual and semiautomatic segmentation method, in which contrast-enhanced (CE)-T1WI and T2WI were used as structural imaging. Intraobserver and interobserver reproducibility were assessed according to each perfusion analysis method or each structural imaging. Interclass correlation coefficient (ICC), Bland-Altman plot, and coefficient of variation (CV) were used to evaluate reproducibility., Results: Intraobserver reproducibilities on CE-T1WI and T2WI were ICC of 0.74-0.89 and CV of 20.39-36.83% in manual segmentation method, and ICC of 0.95-0.99 and CV of 8.53-16.19% in semiautomatic segmentation method, repectively. Interobserver reproducibilites on CE-T1WI and T2WI were ICC of 0.86-0.94 and CV of 19.67-35.15% in manual segmentation method, and ICC of 0.74-1.0 and CV of 5.48-49.38% in semiautomatic segmentation method, respectively. Bland-Altman plots showed a good correlation with ICC or CV in each method. The semiautomatic segmentation method showed higher intraobserver and interobserver reproducibilities at CE-T1WI-based study than other methods., Conclusion: The best reproducibility was found using the semiautomatic segmentation method based on CE-T1WI for structural imaging in the measurement of the nCBV of glioblastomas.

Objective: The purpose of this study was to differentiate true progression from pseudoprogression of glioblastomas treated with concurrent chemoradiotherapy (CCRT) with temozolomide (TMZ) by using histogram analysis of apparent diffusion coefficient (ADC) and normalized cerebral blood volume (nCBV) maps., Materials and Methods: Twenty patients with histopathologically proven glioblastoma who had received CCRT with TMZ underwent perfusion-weighted imaging and diffusion-weighted imaging (b = 0, 1000 sec/mm(2)). The corresponding nCBV and ADC maps for the newly visible, entirely enhancing lesions were calculated after the completion of CCRT with TMZ. Two observers independently measured the histogram parameters of the nCBV and ADC maps. The histogram parameters between the true progression group (n = 10) and the pseudoprogression group (n = 10) were compared by use of an unpaired Student's t test and subsequent multivariable stepwise logistic regression analysis to determine the best predictors for the differential diagnosis between the two groups. Receiver operating characteristic analysis was employed to determine the best cutoff values for the histogram parameters that proved to be significant predictors for differentiating true progression from pseudoprogression. Intraclass correlation coefficient was used to determine the level of inter-observer reliability for the histogram parameters., Results: The 5th percentile value (C5) of the cumulative ADC histograms was a significant predictor for the differential diagnosis between true progression and pseudoprogression (p = 0.044 for observer 1; p = 0.011 for observer 2). Optimal cutoff values of 892 × 10(-6) mm(2)/sec for observer 1 and 907 × 10(-6) mm(2)/sec for observer 2 could help differentiate between the two groups with a sensitivity of 90% and 80%, respectively, a specificity of 90% and 80%, respectively, and an area under the curve of 0.880 and 0.840, respectively. There was no other significant differentiating parameter on the nCBV histograms. Inter-observer reliability was excellent or good for all histogram parameters (intraclass correlation coefficient range: 0.70-0.99)., Conclusion: The C5 of the cumulative ADC histogram can be a promising parameter for the differentiation of true progression from pseudoprogression of newly visible, entirely enhancing lesions after CCRT with TMZ for glioblastomas.

Purpose: To retrospectively determine whether the apparent diffusion coefficient (ADC) values correlate with O(6)-methylguanine DNA methyltransferase (MGMT) promoter methylation semiquantitatively analyzed by methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) in patients with glioblastoma., Materials and Methods: The study was approved by the Institutional Review Board and was Health Insurance Portability and Accountability Act (HIPAA) compliant. Newly diagnosed patients with glioblastoma (n = 26) were analyzed with an ADC histogram approach based on enhancing solid portion. The methylation status of MGMT promoter was assessed by methylation-specific polymerase chain reaction (MSP) and by MS-MLPA. MS-MLPA is a semiquantitative method that determines the methylation ratio. The Ki-67 labeling index was also analyzed. The mean and 5th percentile ADC values were correlated with MGMT promoter methylation status and Ki-67 labeling index using a linear regression model. Progression-free survival (PFS) was also correlated with the ADC values using Kaplan-Meier survival analysis., Results: The mean methylation ratio was 0.21 ± 0.20. By MSP, there were 5 methylated and 21 unmethylated tumors. The mean ADC revealed a positive relationship with MGMT promoter methylation ratio (P = 0.015) and was also significantly different according to MSP-determined methylation status (P = 0.011). Median PFS was significantly related with methylation ratio (P = 0.017) and MSP-derived methylation status (P = 0.025). A positive relationship was demonstrated between PFS and the mean ADC value (P = 0.001). The 5th percentile ADC values showed a significant negative relationship with Ki-67 labeling index (P = 0.036)., Conclusion: We found that ADC values were significantly correlated with PFS as well as with MGMT promoter methylation status. We believe that ADC values may merit further investigation as a noninvasive biomarker for predicting treatment response., (Copyright © 2012 Wiley Periodicals, Inc.)