Differentiation of tumor progression from pseudoprogression in patients with posttreatment glioblastoma using multiparametric histogram analysis

Whole-Tumor Histogram and Texture Analyses of DTI for Evaluation of IDH1-Mutation and 1p/19q-Codeletion Status in World Health Organization Grade II Gliomas

BACKGROUND AND PURPOSE

Prediction of the isocitrate dehydrogenase 1 (IDH1)-mutation and 1p/19q-codeletion status of World Health Organization grade ll gliomas preoperatively may assist in predicting prognosis and planning treatment strategies. Our aim was to characterize the histogram and texture analyses of apparent diffusion coefficient and fractional anisotropy maps to determine IDH1-mutation and 1p/19q-codeletion status in World Health Organization grade II gliomas.

MATERIALS AND METHODS

Ninety-three patients with World Health Organization grade II gliomas with known IDH1-mutation and 1p/19q-codeletion status (18 IDH1 wild-type, 45 IDH1 mutant and no 1p/19q codeletion, 30 IDH1-mutant and 1p/19q codeleted tumors) underwent DTI. ROIs were drawn on every section of the T2-weighted images and transferred to the ADC and the fractional anisotropy maps to derive volume-based data of the entire tumor. Histogram and texture analyses were correlated with the IDH1-mutation and 1p/19q-codeletion status. The predictive powers of imaging features for IDH1 wild-type tumors and 1p/19q-codeletion status in IDH1-mutant subgroups were evaluated using the least absolute shrinkage and selection operator.

RESULTS

Various histogram and texture parameters differed significantly according to IDH1-mutation and 1p/19q-codeletion status. The skewness and energy of ADC, 10th and 25th percentiles, and correlation of fractional anisotropy were independent predictors of an IDH1 wild-type in the least absolute shrinkage and selection operator. The area under the receiver operating curve for the prediction model was 0.853. The skewness and cluster shade of ADC, energy, and correlation of fractional anisotropy were independent predictors of a 1p/19q codeletion in IDH1-mutant tumors in the least absolute shrinkage and selection operator. The area under the receiver operating curve was 0.807.

CONCLUSIONS

Whole-tumor histogram and texture features of the ADC and fractional anisotropy maps are useful for predicting the IDH1-mutation and 1p/19q-codeletion status in World Health Organization grade II gliomas.

Multiparametric MRI as a potential surrogate endpoint for decision-making in early treatment response following concurrent chemoradiotherapy in patients with newly diagnosed glioblastoma: a systematic review and meta-analysis

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.

Diffusion Weighted/Tensor Imaging, Functional MRI and Perfusion Weighted Imaging in Glioblastoma-Foundations and Future

In this article, we review the basics of diffusion tensor imaging and functional MRI, their current utility in preoperative neurosurgical mapping, and their limitations. We also discuss potential future applications, including implementation of resting state functional MRI. We then discuss perfusion and diffusion-weighted imaging and their application in advanced neuro-oncologic practice. We explain how these modalities can be helpful in guiding surgical biopsies and differentiating recurrent tumor from treatment related changes.

Texture analysis of CT images in predicting malignancy risk of gastrointestinal stromal tumours

AIM

To explore the role of texture analysis of computed tomography (CT) images in predicting the malignancy risk of gastrointestinal stromal tumours (GISTs).

MATERIALS AND METHODS

Seventy-eight patients with histopathologically confirmed GISTs underwent preoperative CT. Texture analysis was performed on unenhanced and contrast-enhanced CT images, respectively. Fourteen CT texture parameters were obtained and compared among GISTs at different malignancy risks with one-way analysis of variance or independent-samples Kruskal-Wallis test. Correlations between CT texture parameters and malignancy risk were analysed with Spearman's correlation test. Diagnostic performance of CT texture parameters in differentiating GISTs at low/very low malignancy risk was tested with receiver operating characteristic (ROC) analysis.

RESULTS

Three parameters on unenhanced images (r=-0.268-0.506), four parameters on arterial phase (r=-0.365-0.508), and six parameters on venous phase (r=-0.343-0.481) imaging correlated significantly with malignancy risk of GISTs, respectively (all p<0.05). For identifying GISTs at low/very low malignancy risk, three parameters on unenhanced images (area under ROC curve [AUC], 0.676-0.802), four parameters on arterial phase (AUC, 0.637-0.811), and six parameters on venous phase (AUC, 0.636-0.791) imaging showed significant diagnostic performance, respectively (all p<0.05), especially maximum frequency on both unenhanced and contrast-enhanced images (AUC, 0.791-0.811).

CONCLUSION

Texture analysis of CT images holds great potential to predict the malignancy risk of GISTs preoperatively.

Mean cerebral blood volume is an effective diagnostic index of recurrent and radiation injury in glioma patients: A meta-analysis of diagnostic test

We conducted a meta-analysis to evaluate the diagnostic values of mean cerebral blood volume for recurrent and radiation injury in glioma patients. We performed systematic electronic searches for eligible study up to August 8, 2016. Bivariate mixed effects models were used to estimate the combined sensitivity, specificity, positive likelihood ratios, negative likelihood ratios, diagnostic odds ratios and their 95% confidence intervals (CIs). Fifteen studies with a total number of 576 participants were enrolled. The pooled sensitivity and specificity of diagnostic were 0.88 (95%CI: 0.82-0.92) and 0.85 (95%CI: 0.68-0.93). The pooled positive likelihood ratio is 5.73 (95%CI: 2.56-12.81), negative likelihood ratio is 0.15 (95%CI: 0.10-0.22), and the diagnostic odds ratio is 39.34 (95%CI:13.96-110.84). The summary receiver operator characteristic is 0.91 (95%CI: 0.88-0.93). However, the Deek's plot suggested publication bias may exist (t=2.30, P=0.039). Mean cerebral blood volume measurement methods seems to be very sensitive and highly specific to differentiate recurrent and radiation injury in glioma patients. The results should be interpreted with caution because of the potential bias.

Differentiation of Recurrent Glioblastoma from Delayed Radiation Necrosis by Using Voxel-based Multiparametric Analysis of MR Imaging Data

Purpose To assess a volume-weighted voxel-based multiparametric (MP) clustering method as an imaging biomarker to differentiate recurrent glioblastoma from delayed radiation necrosis. Materials and Methods The institutional review board approved this retrospective study and waived the informed consent requirement. Seventy-five patients with pathologic analysis-confirmed recurrent glioblastoma (n = 42) or radiation necrosis (n = 33) who presented with enlarged contrast material-enhanced lesions at magnetic resonance (MR) imaging after they completed concurrent chemotherapy and radiation therapy were enrolled. The diagnostic performance of the total MP cluster score was determined by using the area under the receiver operating characteristic curve (AUC) with cross-validation and compared with those of single parameter measurements (10% histogram cutoffs of apparent diffusion coefficient [ADC10] or 90% histogram cutoffs of normalized cerebral blood volume and initial time-signal intensity AUC). Results Receiver operating characteristic curve analysis showed that an AUC for differentiating recurrent glioblastoma from delayed radiation necrosis was highest in the total MP cluster score and lowest for ADC10 for both readers. The total MP cluster score had significantly better diagnostic accuracy than any single parameter (corrected P = .001-.039 for reader 1; corrected P = .005-.041 for reader 2). The total MP cluster score was the best predictor of recurrent glioblastoma (cross-validated AUCs, 0.942-0.946 for both readers), with a sensitivity of 95.2% for reader 1 and 97.6% for reader 2. Conclusion Quantitative analysis with volume-weighted voxel-based MP clustering appears to be superior to the use of single imaging parameters to differentiate recurrent glioblastoma from delayed radiation necrosis. ^© RSNA, 2017 Online supplemental material is available for this article.

Incidence of Tumour Progression and Pseudoprogression in High-Grade Gliomas: a Systematic Review and Meta-Analysis

Background

High-grade gliomas are the most common primary brain tumours. Pseudoprogression describes the false appearance of radiation-induced progression on MRI. A distinction should be made from true tumour progression to correctly plan treatment. However, there is wide variation of reported pseudoprogression. We thus aimed to establish the incidence of pseudoprogression and tumour progression in high-grade glioma patients with a systematic review and meta-analysis.

Methods

We searched PubMed, Embase and Web of Science on the incidence of pseudoprogression and tumour progression in adult high-grade glioma patients from 2005, the latest on 8 October 2014. Histology or imaging follow-up was used as reference standard. Extracted data included number of patients with worsening of imaging findings on T1 postcontrast or T2/FLAIR, pseudoprogression and tumour progression. Study quality was assessed. Heterogeneity was tested with I². Pooling of the results was done with random models using Metaprop in STATA (StataCorp. Stata Statistical Software. College Station, TX: StataCorp LP).

Results

We identified 73 studies. MRI progression occurred in 2603 patients. Of these, 36% (95% confidence interval [CI] 33–40%) demonstrated pseudoprogression, 60% (95%CI 56–64%) tumour progression and unknown outcome was present in the remaining 4% of the patients (range 1–37%).

Conclusion

This meta-analysis demonstrated for the first time a notably high pooled incidence of pseudoprogression in patients with a form of progression across the available literature. This highlighted the full extent of the problem of the currently conventional MRI-based Response Assessment in Neuro-Oncology (RANO) criteria for treatment evaluation in high-grade gliomas. This underscores the need for more accurate treatment evaluation using advanced imaging to improve diagnostic accuracy and therapeutic approach.

Electronic supplementary material

The online version of this article (doi: 10.1007/s00062-017-0584-x) contains supplementary material, which is available to authorized users. It contains the characteristics of the included studies (supplementary table 1) and a full search strategy (see supplementary search strategy).

Diagnostic accuracy of magnetic resonance imaging techniques for treatment response evaluation in patients with high-grade glioma, a systematic review and meta-analysis

Objective

Treatment response assessment in high-grade gliomas uses contrast enhanced T1-weighted MRI, but is unreliable. Novel advanced MRI techniques have been studied, but the accuracy is not well known. Therefore, we performed a systematic meta-analysis to assess the diagnostic accuracy of anatomical and advanced MRI for treatment response in high-grade gliomas.

Methods

Databases were searched systematically. Study selection and data extraction were done by two authors independently. Meta-analysis was performed using a bivariate random effects model when ≥5 studies were included.

Results

Anatomical MRI (five studies, 166 patients) showed a pooled sensitivity and specificity of 68% (95%CI 51–81) and 77% (45–93), respectively. Pooled apparent diffusion coefficients (seven studies, 204 patients) demonstrated a sensitivity of 71% (60–80) and specificity of 87% (77–93). DSC-perfusion (18 studies, 708 patients) sensitivity was 87% (82–91) with a specificity of 86% (77–91). DCE-perfusion (five studies, 207 patients) sensitivity was 92% (73–98) and specificity was 85% (76–92). The sensitivity of spectroscopy (nine studies, 203 patients) was 91% (79–97) and specificity was 95% (65–99).

Conclusion

Advanced techniques showed higher diagnostic accuracy than anatomical MRI, the highest for spectroscopy, supporting the use in treatment response assessment in high-grade gliomas.

Key points

• Treatment response assessment in high-grade gliomas with anatomical MRI is unreliable

• Novel advanced MRI techniques have been studied, but diagnostic accuracy is unknown

• Meta-analysis demonstrates that advanced MRI showed higher diagnostic accuracy than anatomical MRI

• Highest diagnostic accuracy for spectroscopy and perfusion MRI

• Supports the incorporation of advanced MRI in high-grade glioma treatment response assessment

Electronic supplementary material

The online version of this article (doi:10.1007/s00330-017-4789-9) contains supplementary material, which is available to authorized users.

Stratification of pseudoprogression and true progression of glioblastoma multiform based on longitudinal diffusion tensor imaging without segmentation

PURPOSE

Pseudoprogression (PsP) can mimic true tumor progression (TTP) on magnetic resonance imaging in patients with glioblastoma multiform (GBM). The phenotypical similarity between PsP and TTP makes it a challenging task for physicians to distinguish these entities. So far, no approved biomarkers or computer-aided diagnosis systems have been used clinically for this purpose.

METHODS

To address this challenge, the authors developed an objective classification system for PsP and TTP based on longitudinal diffusion tensor imaging. A novel spatio-temporal discriminative dictionary learning scheme was proposed to differentiate PsP and TTP, thereby avoiding segmentation of the region of interest. The authors constructed a novel discriminative sparse matrix with the classification-oriented dictionary learning approach by excluding the shared features of two categories, so that the pooled features captured the subtle difference between PsP and TTP. The most discriminating features were then identified from the pooled features by their feature scoring system. Finally, the authors stratified patients with GBM into PsP and TTP by a support vector machine approach. Tenfold cross-validation (CV) and the area under the receiver operating characteristic (AUC) were used to assess the robustness of the developed system.

RESULTS

The average accuracy and AUC values after ten rounds of tenfold CV were 0.867 and 0.92, respectively. The authors also assessed the effects of different methods and factors (such as data types, pooling techniques, and dimensionality reduction approaches) on the performance of their classification system which obtained the best performance.

CONCLUSIONS

The proposed objective classification system without segmentation achieved a desirable and reliable performance in differentiating PsP from TTP. Thus, the developed approach is expected to advance the clinical research and diagnosis of PsP and TTP.

Amino acid PET and MR perfusion imaging in brain tumours

Purpose

Despite the excellent capacity of the conventional MRI to image brain tumours, problems remain in answering a number of critical diagnostic questions. To overcome these diagnostic shortcomings, PET using radiolabeled amino acids and perfusion-weighted imaging (PWI) are currently under clinical evaluation. The role of amino acid PET and PWI in different diagnostic challenges in brain tumours is controversial.

Methods

Based on the literature and experience of our centres in correlative imaging with PWI and PET using O-(2-[¹⁸F]fluoroethyl)-l-tyrosine or 3,4-dihydroxy-6-[¹⁸F]-fluoro-l-phenylalanine, the current role and shortcomings of amino acid PET and PWI in different diagnostic challenges in brain tumours are reviewed. Literature searches were performed on PubMed, and additional literature was retrieved from the reference lists of identified articles. In particular, all studies in which amino acid PET was directly compared with PWI were included.

Results

PWI is more readily available, but requires substantial expertise and is more sensitive to artifacts than amino acid PET. At initial diagnosis, PWI and amino acid PET can help to define a site for biopsy but amino acid PET appears to be more powerful to define the tumor extent. Both methods are helpful to differentiate progression or recurrence from unspecific posttherapeutic changes. Assessment of therapeutic efficacy can be achieved especially with amino acid PET, while the data with PWI are sparse.

Conclusion

Both PWI and amino acid PET add valuable diagnostic information to the conventional MRI in the assessment of patients with brain tumours, but further studies are necessary to explore the complementary nature of these two methods.

Evaluation of pseudoprogression in patients with glioblastoma

Background

Management of glioblastoma is complicated by pseudoprogression, a radiological phenomenon mimicking progression. This retrospective cohort study investigated the incidence, prognostic implications, and most clinically appropriate definition of pseudoprogression.

Methods

Consecutive glioblastoma patients treated at the Juravinski Hospital and Cancer Centre, Hamilton, Ontario between 2004 and 2012 with temozolomide chemoradiotherapy and with contrast-enhanced MRI at standard imaging intervals were included. At each imaging interval, patient responses as per the RECIST (Response Evaluation Criteria in Solid Tumors), MacDonald, and RANO (Response Assessment in Neuro-Oncology) criteria were reported. Based on each set of criteria, subjects were classified as having disease response, stable disease, pseudoprogression, or true progression. The primary outcome was overall survival.

Results

The incidence of pseudoprogression among 130 glioblastoma patients treated with chemoradiotherapy was 15%, 19%, and 23% as defined by RANO, MacDonald, and RECIST criteria, respectively. Using the RANO definition, median survival for patients with pseudoprogression was 13.0 months compared with 12.5 months for patients with stable disease (hazard ratio [HR]=0.70; 95% confidence interval [CI], 0.35-1.42). Similarly, using the MacDonald definition, median survival for the pseudoprogression group was 11.8 months compared with 12.0 months for the stable disease group (HR=0.86; 95% CI, 0.47-1.58). Furthermore, disease response compared with stable disease was also similar using the RANO (HR=0.52; 95% CI, 0.20-1.35) and MacDonald (HR=0.51: 95% CI, 0.20-1.31) definitions.

Conclusions

Of all conventional glioblastoma response criteria, the RANO criteria gave the lowest incidence of pseudoprogression. Regardless of criteria, patients with pseudoprogression did not have statistically significant difference in survival compared with patients with stable disease.

Dynamic Susceptibility Contrast MR Imaging in Glioma: Review of Current Clinical Practice

Dynamic susceptibility contrast (DSC) MR imaging, a perfusion-weighted MR imaging technique typically used in neuro-oncologic applications for estimating the relative cerebral blood volume within brain tumors, has demonstrated much potential for determining prognosis, predicting therapeutic response, and assessing early treatment response of gliomas. This review highlights recent developments using DSC-MR imaging and emphasizes the need for technical standardization and validation in prospective studies in order for this technique to become incorporated into standard-of-care imaging for patients with brain tumors.

Arterial spin labeling: Pathologically proven superiority over conventional MRI for detection of high-grade glioma progression after treatment

BACKGROUND

Standard of care for high-grade gliomas (HGGs) includes surgical debulking and adjuvant chemotherapy and radiation. Patients under treatment require frequent clinical and imaging monitoring for therapy modulation. Differentiating tumor progression from treatment-related changes can be challenging on conventional MRI, resulting in delayed recognition of tumor progression. Arterial spin labeling (ASL) may be more sensitive for tumor progression.

MATERIALS AND METHODS

ASL and associated conventional MR images obtained in patients previously treated for HGGs and before biopsy or re-resection were reviewed by three neuroradiologists who were blinded to the histopathologic results. Regions of interest (ROIs) of greatest perfusion were chosen by consensus, and mirror-image contralateral ROIs were also placed. Sensitivity of ASL for tumor progression was compared with those of contrast-enhanced T1-weighted (T1W-CE) and fluid-attenuated inversion recovery (FLAIR) images using McNemar's test. We tested for an association between cerebral blood flow (CBF) and apparent diffusion correlation (ADC) using a Hotelling-Lawley trace. Finally, we used a Pearson's analysis to test for a correlation between CBF and percentage of tumor within each resection.

RESULTS

Twenty-two patients were studied. ASL demonstrated hyperperfusion in all cases with mean CBF ratio 3.37 (±1.71). T1W-CE and FLAIR images were positive in 15 (p = 0.0233) and 16 (p = 0.0412) cases, respectively. There was no association between ADC and CBF (p = 0.687). There was a correlation between CBF and percentage of tumor (p = 0.048).

CONCLUSION

ASL may be more sensitive than conventional MR sequences for the detection of tumor progression in patients treated for HGGs.

Evaluation of pseudoprogression rates and tumor progression patterns in a phase III trial of bevacizumab plus radiotherapy/temozolomide for newly diagnosed glioblastoma

BACKGROUND

Evaluation of glioblastoma disease status may be complicated by treatment-induced changes and discordance between enhancing and nonenhancing MRI. Exploratory analyses are presented (prospectively assessed pseudoprogression and therapy-related tumor pattern changes) from the AVAglio trial (bevacizumab or placebo plus radiotherapy/temozolomide for newly diagnosed glioblastoma).

METHODS

MRI was done every 8 weeks (beginning 4 wk after chemoradiotherapy) using prespecified and standardized T1 and T2 protocols. Progressive disease (PD) at 10 weeks was reconfirmed at 18 weeks to distinguish pseudoprogression. Progression-free survival (PFS), excluding cases of confirmed pseudoprogression, was assessed (post-hoc/exploratory). Tumor progression patterns were determined at each disease assessment/PD (prespecified/exploratory).

RESULTS

Of patients with PD in the bevacizumab and placebo arms, 143/354 (40.4%) and 155/387 (40.1%), respectively, had PD due to contrast-enhancing lesions, and 51/354 (14.4%) and 53/387 (13.7%) had PD due to nonenhancing lesions. Of all patients in the bevacizumab arm (n = 458), 2.2% had confirmed pseudoprogression versus 9.3% in the placebo arm (n = 463). Baseline characteristics did not differ between patients with/without pseudoprogression (including for MGMT status). Excluding confirmed pseudoprogression, PFS (hazard ratio: 0.65, 95% CI: 0.56-0.75; P < .0001, bevacizumab vs placebo) was comparable to the intent-to-treat population. At PD, most patients had the same tumor focus (local/multifocal, >84%) and infiltrative profile (>88%) as at baseline; no shift to a diffuse or multifocal phenotype was observed.

CONCLUSIONS

Pseudoprogression complicated progression assessment in a small but relevant number of patients but had negligible impact on PFS. Bevacizumab did not appear to adversely impact tumor progression patterns.

MR perfusion-weighted imaging in the evaluation of high-grade gliomas after treatment: a systematic review and meta-analysis

BACKGROUND

Distinction between tumor and treatment related changes is crucial for clinical management of patients with high-grade gliomas. Our purpose was to evaluate whether dynamic susceptibility contrast-enhanced (DSC) and dynamic contrast enhanced (DCE) perfusion-weighted imaging (PWI) metrics can effectively differentiate between recurrent tumor and posttreatment changes within the enhancing signal abnormality on conventional MRI.

METHODS

A comprehensive literature search was performed for studies evaluating PWI-based differentiation of recurrent tumor and posttreatment changes in patients with high-grade gliomas (World Health Organization grades III and IV). Only studies published in the "temozolomide era" beginning in 2005 were included. Summary estimates of diagnostic accuracy were obtained by using a random-effects model.

RESULTS

Of 1581 abstracts screened, 28 articles were included. The pooled sensitivities and specificities of each study's best performing parameter were 90% and 88% (95% CI: 0.85-0.94; 0.83-0.92) and 89% and 85% (95% CI: 0.78-0.96; 0.77-0.91) for DSC and DCE, respectively. The pooled sensitivities and specificities for detecting tumor recurrence using the 2 most commonly evaluated parameters, mean relative cerebral blood volume (rCBV) (threshold range, 0.9-2.15) and maximum rCBV (threshold range, 1.49-3.1), were 88% and 88% (95% CI: 0.81-0.94; 0.78-0.95) and 93% and 76% (95% CI: 0.86-0.98; 0.66-0.85), respectively.

CONCLUSIONS

PWI-derived thresholds separating viable tumor from treatment changes demonstrate relatively good accuracy in individual studies. However, because of significant variability in optimal reported thresholds and other limitations in the existing body of literature, further investigation and standardization is needed before implementing any particular quantitative PWI strategy across institutions.

Amino Acid PET - An Imaging Option to Identify Treatment Response, Posttherapeutic Effects, and Tumor Recurrence?

Routine diagnostics and treatment monitoring in patients with primary and secondary brain tumors is usually based on contrast-enhanced standard MRI. However, the capacity of standard MRI to differentiate neoplastic tissue from non-specific posttreatment effects may be limited particularly after therapeutic interventions such as radio- and/or chemotherapy or newer treatment options, e.g., immune therapy. Metabolic imaging using PET may provide relevant additional information on tumor metabolism, which allows a more accurate diagnosis especially in clinically equivocal situations, particularly when radiolabeled amino acids are used. Amino acid PET allows a sensitive monitoring of a response to various treatment options, the early detection of tumor recurrence, and an improved differentiation of tumor recurrence from posttherapeutic effects. In the past, this method had only limited availability due to the use of PET tracers with a short half-life, e.g., C-11. In recent years, however, novel amino acid PET tracers labeled with positron emitters with a longer half-life (F-18) have been developed and clinically validated, which allow a more efficient and cost-effective application. These developments and the well-documented diagnostic performance of PET using radiolabeled amino acids suggest that its application continues to spread and that this technique may be available as a routine diagnostic tool for several indications in the field of neuro-oncology.

Incremental Prognostic Value of ADC Histogram Analysis over MGMT Promoter Methylation Status in Patients with Glioblastoma

Purpose To investigate the incremental prognostic value of apparent diffusion coefficient (ADC) histogram analysis over oxygen 6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status in patients with glioblastoma and the correlation between ADC parameters and MGMT status. Materials and Methods This retrospective study was approved by institutional review board, and informed consent was waived. A total of 112 patients with glioblastoma were divided into training (74 patients) and test (38 patients) sets. Overall survival (OS) and progression-free survival (PFS) was analyzed with ADC parameters, MGMT status, and other clinical factors. Multivariate Cox regression models with and without ADC parameters were constructed. Model performance was assessed with c index and receiver operating characteristic curve analyses for 12- and 16-month OS and 12-month PFS in the training set and validated in the test set. ADC parameters were compared according to MGMT status for the entire cohort. Results By using ADC parameters, the c indices and diagnostic accuracies for 12- and 16-month OS and 12-month PFS in the models showed significant improvement, with the exception of c indices in the models for PFS (P < .05 for all) in the training set. In the test set, the diagnostic accuracy was improved by using ADC parameters and was significant, with the 25th and 50th percentiles of ADC for 16-month OS (P = .040 and P = .047) and the 25th percentile of ADC for 12-month PFS (P = .026). No significant correlation was found between ADC parameters and MGMT status. Conclusion ADC histogram analysis had incremental prognostic value over MGMT promoter methylation status in patients with glioblastoma. (©) RSNA, 2016 Online supplemental material is available for this article.

Differentiation of Hemangioblastoma from Metastatic Brain Tumor using Dynamic Contrast-enhanced MR Imaging

PURPOSE

The aim of this study was to differentiate hemangioblastomas from metastatic brain tumors using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and compare the diagnostic performances with diffusion-weighted imaging (DWI) and dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI).

METHODS

We retrospectively reviewed 7 patients with hemangioblastoma and 15 patients with metastatic adenocarcinoma with magnetic resonance imaging (MRI) including DWI, DSC-MRI, and DCE-MRI. Apparent diffusion coefficient (ADC), relative cerebral blood volume (rCBV), and DCE-MRI parameters (K ^trans, k _ep, v _e, and v _p) were compared between the two groups. The diagnostic performance of each parameter was evaluated with receiver operating characteristic (ROC) curve analysis.

RESULTS

v _p, k _ep, and rCBV were significantly different between patients with hemangioblastoma and those with metastatic brain tumor (p < 0.001, p = 0.005, and p = 0.017, respectively). A v _p cutoff value of 0.012 and a rCBV cutoff value of 8.0 showed the highest accuracy for differentiating hemangioblastoma from metastasis. The area under the ROC curve for v _p and rCBV was 0.99 and 0.89, respectively. A v _p > 0.012 showed 100 % sensitivity, 93.3 % specificity, and 95.5 % accuracy and a rCBV > 8.0 showed 85.7 % sensitivity, 93.3 % specificity, and 90.9 % accuracy for differentiating hemangioblastoma from metastatic brain tumor.

CONCLUSION

DCE-MRI was useful for differentiating hemangioblastoma from metastatic brain tumor.

Response Assessment and Magnetic Resonance Imaging Issues for Clinical Trials Involving High-Grade Gliomas

There exist multiple challenges associated with the current response assessment criteria for high-grade gliomas, including the uncertain role of changes in nonenhancing T2 hyperintensity, and the phenomena of pseudoresponse and pseudoprogression in the setting of antiangiogenic and chemoradiation therapies, respectively. Advanced physiological magnetic resonance imaging (MRI), including diffusion and perfusion (dynamic susceptibility contrast MRI and dynamic contrast-enhanced MRI) sensitive techniques for overcoming response assessment challenges, has been proposed, with their own potential advantages and inherent shortcomings. Measurement variability exists for conventional and advanced MRI techniques, necessitating the standardization of image acquisition parameters in order to establish the utility of these imaging methods in multicenter trials for high-grade gliomas. This review chapter highlights the important features of MRI in clinical brain tumor trials, focusing on the current state of response assessment in brain tumors, advanced imaging techniques that may provide additional value for determining response, and imaging issues to be considered for multicenter trials.

Recent Application of Advanced MR Imaging to Predict Pseudoprogression in High-grade Glioma Patients

Pseudoprogression is regarded as a subacute form of treatment-related change with a reported incidence of 20-30%, occurring predominantly within the first three months after the completion of concurrent chemoradiotherapy (CCRT) in glioblastoma multiforme (GBM) patients. Occurrence of progressive lesions on conventional contrast-enhanced MR imaging may also accompany clinical deterioration, posing considerable diagnostic challenges to clinicians and radiologists. False interpretation of treatment-related change as true progression may lead to the cessation of effective first-line therapy (i.e., adjuvant temozolomide) and unnecessary surgery. Increasing awareness of the diagnostic challenge of the phenomenon has underscored the need for better imaging techniques that may aid in differentiating the treatment-related change from true progression. In this review, we discuss the recent applications of advanced MR imaging such as diffusion-weighted and perfusion-weighted imaging in the evaluation of treatment response in high-grade glioma patients and highlight their potential role in differentiating pseudoprogression from true progression.

Assessing and monitoring intratumor heterogeneity in glioblastoma: how far has multimodal imaging come?

Glioblastoma demonstrates imaging features of intratumor heterogeneity that result from underlying heterogeneous biological properties. This stems from variations in cellular behavior that result from genetic mutations that either drive, or are driven by, heterogeneous microenvironment conditions. Among all imaging methods available, only T1-weighted contrast-enhancing and T2-weighted fluid-attenuated inversion recovery are used in standard clinical glioblastoma assessment and monitoring. Advanced imaging modalities are still considered emerging techniques as appropriate end points and robust methodologies are missing from clinical trials. Discovering how these images specifically relate to the underlying tumor biology may aid in improving quality of clinical trials and understanding the factors involved in regional responses to treatment, including variable drug uptake and effect of radiotherapy. Upon validation and standardization of emerging MR techniques, providing information based on the underlying tumor biology, these images may allow for clinical decision-making that is tailored to an individual's response to treatment.

Differentiating Tumor Progression from Pseudoprogression in Patients with Glioblastomas Using Diffusion Tensor Imaging and Dynamic Susceptibility Contrast MRI

BACKGROUND AND PURPOSE

Early assessment of treatment response is critical in patients with glioblastomas. A combination of DTI and DSC perfusion imaging parameters was evaluated to distinguish glioblastomas with true progression from mixed response and pseudoprogression.

MATERIALS AND METHODS

Forty-one patients with glioblastomas exhibiting enhancing lesions within 6 months after completion of chemoradiation therapy were retrospectively studied. All patients underwent surgery after MR imaging and were histologically classified as having true progression (>75% tumor), mixed response (25%-75% tumor), or pseudoprogression (<25% tumor). Mean diffusivity, fractional anisotropy, linear anisotropy coefficient, planar anisotropy coefficient, spheric anisotropy coefficient, and maximum relative cerebral blood volume values were measured from the enhancing tissue. A multivariate logistic regression analysis was used to determine the best model for classification of true progression from mixed response or pseudoprogression.

RESULTS

Significantly elevated maximum relative cerebral blood volume, fractional anisotropy, linear anisotropy coefficient, and planar anisotropy coefficient and decreased spheric anisotropy coefficient were observed in true progression compared with pseudoprogression (P < .05). There were also significant differences in maximum relative cerebral blood volume, fractional anisotropy, planar anisotropy coefficient, and spheric anisotropy coefficient measurements between mixed response and true progression groups. The best model to distinguish true progression from non-true progression (pseudoprogression and mixed) consisted of fractional anisotropy, linear anisotropy coefficient, and maximum relative cerebral blood volume, resulting in an area under the curve of 0.905. This model also differentiated true progression from mixed response with an area under the curve of 0.901. A combination of fractional anisotropy and maximum relative cerebral blood volume differentiated pseudoprogression from nonpseudoprogression (true progression and mixed) with an area under the curve of 0.807.

CONCLUSIONS

DTI and DSC perfusion imaging can improve accuracy in assessing treatment response and may aid in individualized treatment of patients with glioblastomas.

Independent Poor Prognostic Factors for True Progression after Radiation Therapy and Concomitant Temozolomide in Patients with Glioblastoma: Subependymal Enhancement and Low ADC Value

BACKGROUND AND PURPOSE

Subependymal enhancement and DWI have been reported to be useful MR imaging markers for identifying true progression. Our aim was to determine whether the subependymal enhancement pattern and ADC can differentiate true progression from pseudoprogression in patients with glioblastoma multiforme treated with concurrent chemoradiotherapy by using temozolomide.

MATERIALS AND METHODS

Forty-two patients with glioblastoma multiforme with newly developed or enlarged enhancing lesions on the first follow-up MR images obtained within 2 months of concurrent chemoradiotherapy completion were included. Subependymal enhancement was analyzed for the presence, location, and pattern (local or distant relative to enhancing lesions). The mean ADC value and the fifth percentile of the cumulative ADC histogram were determined. A multiple logistic regression analysis was performed to identify independent factors associated with true progression.

RESULTS

Distant subependymal enhancement (ie, extending >1 cm or isolated from the enhancing lesion) was significantly more common in true progression (n = 24) than in pseudoprogression (n = 18) (P = .042). The fifth percentile of the cumulative ADC histogram was significantly lower in true progression than in pseudoprogression (P = .014). Both the distant subependymal enhancement and the fifth percentile of the cumulative ADC histogram were independent factors associated with true progression (P = .041 and P = .033, respectively). Sensitivity and specificity for the diagnosis of true progression were 83% and 67%, respectively, by using both factors.

CONCLUSIONS

Both the distant subependymal enhancement and the fifth percentile of the cumulative ADC histogram were significant independent factors predictive of true progression.

Physiologic MRI for assessment of response to therapy and prognosis in glioblastoma

Aside from bidimensional measurements from conventional contrast-enhanced MRI, there are no validated or FDA-qualified imaging biomarkers for high-grade gliomas. However, advanced functional MRI techniques, including perfusion- and diffusion-weighted MRI, have demonstrated much potential for determining prognosis, predicting therapeutic response, and assessing early treatment response. They may also prove useful for differentiating pseudoprogression from true progression after temozolomide chemoradiation and pseudoresponse from true response after anti-angiogenic therapy. This review will highlight recent developments using these techniques and emphasize the need for technical standardization and validation in prospective studies in order for these methods to become incorporated into standard-of-care imaging for brain tumor patients.

Tumour progression or pseudoprogression? A review of post-treatment radiological appearances of glioblastoma

Glioblastoma (GBM) is a common brain tumour in adults, which, despite multimodality treatment, has a poor median survival. Efficacy of therapy is assessed by clinical examination and magnetic resonance imaging (MRI) features. There is now a recognised subset of treated patients with imaging features that indicate "progressive disease" according to Macdonald's criteria, but subsequently, show stabilisation or resolution without a change in treatment. In these cases of "pseudoprogression", it is believed that non-tumoural causes lead to increased contrast enhancement and conventional MRI is inadequate in distinguishing this from true tumour progression. Incorrect diagnosis is important, as failure to identify pseudoprogression could lead to an inappropriate change of effective therapy. The purpose of this review is to outline the current research into radiological assessment with MRI and molecular imaging of post-treatment GBMs, specifically the differentiation between pseudoprogression and tumour progression.

Post-treatment imaging of high-grade gliomas

Current standard of care for treatment of newly diagnosed high grade gliomas is surgery followed by concomitant radiotherapy (RT) and chemotherapy (CT) with temozolomide (TMZ). Recently, bevacizumab, an anti – angiogenic agent has also been approved for treatment of recurrent gliomas. Baseline imaging after excision is optimally obtained in the first 24 hours. When baseline postoperative imaging is delayed beyond 24 hours, subacute hemorrhage, subacute ischemia and inflammation at the resection margins render differentiation from residual tumor challenging. Radiation necrosis is a well recognized entity and is differentiated from recurrence based on morphology on structural imaging, presence of lipid – lactate complexes with lack of choline on spectroscopy and low normalized cerebral blood volume (CBV) ratios at perfusion imaging. Novel chemotherapies have lead to the occurrence of interesting but sometimes confusing post treatment imaging appearances including the phenomena of ‘pseudoprogression’ and ‘pseudoresponse’. Pseudoprogression refers to transient, self resolving focal enhancement mediated by TMZ-induced increased vascular permeability and local inflammatory response. Pathologically, these lesions do not have viable tumor. The lesions stabilize or regress without further treatment and are usually clinically asymptomatic. Pseudoresponse refers to rapid regression of enhancement, perfusion, mass effect and midline shift caused by the anti – angiogenic effect of bevacizumab. It is termed pseudoresponse since biological tumor persists as non-enhancing altered signal. It is important for radiologists to be aware of these entities seen on post treatment imaging of gliomas, as misinterpretation may lead to inappropriate management decisions and prognostication.

Pseudoprogression in Patients with Glioblastoma: Assessment by Using Volume-weighted Voxel-based Multiparametric Clustering of MR Imaging Data in an Independent Test Set

PURPOSE

To validate a volume-weighted voxel-based multiparametric clustering (VVMC) method for magnetic resonance imaging data that is designed to differentiate between pseudoprogression and early tumor progression (ETP) in patients with glioblastoma in an independent test set.

MATERIALS AND METHODS

This retrospective study was approved by the local institutional review board, with waiver of the need to obtain informed consent. The study patients were grouped chronologically into a training set (108 patients) and a test set (54 patients). The reference standard was pathologic findings or subsequent clinical-radiologic study results. By using the optimal cutoff determined in the training set, the diagnostic performance of VVMC was subsequently tested in the test set and was compared with that of single-parameter measurements (apparent diffusion coefficient [ADC], normalized cerebral blood volume [nCBV], and initial area under the time-signal intensity curve).

RESULTS

Interreader agreement was highest for VVMC (intraclass correlation coefficient, 0.87-0.89). Receiver operating characteristic curve analysis revealed that VVMC performed the best as a classifier, although statistical significance was not demonstrated with respect to the nCBV in the training set. In the test set, the diagnostic accuracy of VVMC was higher than that of any single-parameter measurements, but this trend reached significance only for the ADC. When the entire population was considered, VVMC had significantly better diagnostic accuracy than did any single parameter (P = .003-.046 for reader 1; P = .002-.016 for reader 2). Results of fivefold cross validation confirmed the trends in both the training set and the test set.

CONCLUSION

VVMC is a superior and more reproducible imaging biomarker than single-parameter measurements for differentiating between pseudoprogression and ETP in patients with glioblastoma. Online supplemental material is available for this article.

Diffusion and perfusion MRI to differentiate treatment-related changes including pseudoprogression from recurrent tumors in high-grade gliomas with histopathologic evidence

BACKGROUND AND PURPOSE

Treatment-related changes and recurrent tumors often have overlapping features on conventional MR imaging. The purpose of this study was to assess the utility of DWI and DSC perfusion imaging alone and in combination to differentiate treatment-related effects and recurrent high-grade gliomas.

MATERIALS AND METHODS

We retrospectively identified 68 consecutive patients with high-grade gliomas treated by surgical resection followed by radiation therapy and temozolomide, who then developed increasing enhancing mass lesions indeterminate for treatment-related changes versus recurrent tumor. All lesions were diagnosed by histopathology at repeat surgical resection. ROI analysis was performed of the enhancing lesion on the ADC and DSC maps. Measurements made by a 2D ROI of the enhancing lesion on a single slice were recorded as ADCLesion and rCBVLesion, and measurements made by the most abnormal small fixed diameter ROI as ADCROI and rCBVROI. Statistical analysis was performed with Wilcoxon rank sum tests with P = .05.

RESULTS

Ten of the 68 patients (14.7%) had treatment-related changes, while 58 patients (85.3%) had recurrent tumor only (n = 19) or recurrent tumor mixed with treatment effect (n = 39). DWI analysis showed higher ADCLesion in treatment-related changes than in recurrent tumor (P = .003). DSC analysis revealed lower relative cerebral blood volume (rCBV)Lesion and rCBVROI in treatment-related changes (P = .003 and P = .011, respectively). Subanalysis of patients with suspected pseudoprogression also revealed higher ADCLesion (P = .001) and lower rCBVLesion (P = .028) and rCBVROI (P = .032) in treatment-related changes. Applying a combined ADCLesion and rCBVLesion model did not outperform either the ADC or rCBV metric alone.

CONCLUSIONS

Treatment-related changes showed higher diffusion and lower perfusion than recurrent tumor. Similar correlations were found for patients with suspected pseudoprogression.

Neuroimaging and genetic influence in treating brain neoplasms

The current treatment of glioblastoma patients based on surgery, radiation, and chemotherapy has achieved modest improvement in progression-free survival. In this direction, personalized treatment is the next achievement for better patient management and increased overall survival. Genetic characterization of high-grade gliomas by MR imaging is the goal in neuroimaging. The main genetic alterations described in these neoplasms, implications in patient treatment, and prognosis are reviewed. MR imaging features and novel techniques are correlated with the main genetic aspects of such tumors. Posttreatment phenomena, such as pseudoprogression and pseudoresponse, are analyzed in association with the genetic expression of these tumors.

Diagnosis of pseudoprogression in patients with glioblastoma using O-(2-[18F]fluoroethyl)-L-tyrosine PET

PURPOSE

The follow-up of glioblastoma patients after radiochemotherapy with conventional MRI can be difficult since reactive alterations to the blood-brain barrier with contrast enhancement may mimic tumour progression (i.e. pseudoprogression, PsP). The aim of this study was to assess the clinical value of O-(2-(18)F-fluoroethyl)-L-tyrosine ((18)F-FET) PET in the differentiation of PsP and early tumour progression (EP) after radiochemotherapy of glioblastoma.

METHODS

A group of 22 glioblastoma patients with new contrast-enhancing lesions or lesions showing increased enhancement (>25 %) on standard MRI within the first 12 weeks after completion of radiochemotherapy with concomitant temozolomide (median 7 weeks) were additionally examined using amino acid PET with (18)F-FET. Maximum and mean tumour-to-brain ratios (TBRmax, TBRmean) were determined. (18)F-FET uptake kinetic parameters (i.e. patterns of time-activity curves, TAC) were also evaluated. Classification as PsP or EP was based on the clinical course (no treatment change at least for 6 months), follow-up MR imaging and/or histopathological findings. Imaging results were also related to overall survival (OS).

RESULTS

PsP was confirmed in 11 of the 22 patients. In patients with PsP, (18)F-FET uptake was significantly lower than in patients with EP (TBRmax 1.9 ± 0.4 vs. 2.8 ± 0.5, TBRmean 1.8 ± 0.2 vs. 2.3 ± 0.3; both P < 0.001) and presence of MGMT promoter methylation was significantly more frequent (P = 0.05). Furthermore, a TAC type II or III was more frequently present in patients with EP (P = 0.04). Receiver operating characteristic analysis showed that the optimal (18)F-FET TBRmax cut-off value for identifying PsP was 2.3 (sensitivity 100 %, specificity 91 %, accuracy 96 %, AUC 0.94 ± 0.06; P < 0.001). Univariate survival analysis showed that a TBRmax <2.3 predicted a significantly longer OS (median OS 23 vs. 12 months; P = 0.046).

CONCLUSION

(18)F-FET PET may facilitate the diagnosis of PsP following radiochemotherapy of glioblastoma.