Magnetic resonance perfusion-weighted imaging defines angiogenic subtypes of oligodendroglioma according to 1p19q and EGFR status

Advances in diffuse glial tumors diagnosis

In recent decades, there have been significant advances in the diagnosis of diffuse gliomas, driven by the integration of novel technologies. These advancements have deepened our understanding of tumor oncogenesis, enabling a more refined stratification of the biological behavior of these neoplasms. This progress culminated in the fifth edition of the WHO classification of central nervous system (CNS) tumors in 2021. This comprehensive review article aims to elucidate these advances within a multidisciplinary framework, contextualized within the backdrop of the new classification. This article will explore morphologic pathology and molecular/genetics techniques (immunohistochemistry, genetic sequencing, and methylation profiling), which are pivotal in diagnosis, besides the correlation of structural neuroimaging radiophenotypes to pathology and genetics. It briefly reviews the usefulness of tractography and functional neuroimaging in surgical planning. Additionally, the article addresses the value of other functional imaging techniques such as perfusion MRI, spectroscopy, and nuclear medicine in distinguishing tumor progression from treatment-related changes. Furthermore, it discusses the advantages of evolving diagnostic techniques in classifying these tumors, as well as their limitations in terms of availability and utilization. Moreover, the expanding domains of data processing, artificial intelligence, radiomics, and radiogenomics hold great promise and may soon exert a substantial influence on glioma diagnosis. These innovative technologies have the potential to revolutionize our approach to these tumors. Ultimately, this review underscores the fundamental importance of multidisciplinary collaboration in employing recent diagnostic advancements, thereby hoping to translate them into improved quality of life and extended survival for glioma patients.

The value of texture analysis in peritumoral edema of differentiating diagnosis between glioblastoma and primary brain lymphoma

OBJECTIVE

To evaluate the value of texture analysis of routine MRI image in peritumoral edema of differentiating diagnosis between glioblastoma (GBM) and primary brain lymphoma (PBL).

METHODS

The MRI imaging data of 22 patients with glioblastoma and 21 patients with PBL who were hospitalized in our hospital from January 2010 to October 2018 were selected. All the patients were pathologically diagnosed as glioblastoma or PBL, and MRI plain scan and enhanced examination were performed before operation. FireVoxel software was used to delineate the region of interest (ROI) on the most obvious level of peritumoral edema based on T1WI enhancement. Texture parameters were extracted and compared between glioblastoma and PBL.

RESULTS

In the glioblastoma group, the inhomogeneity, kurtosis and entropy texture parameters were statistically different from those in the PBL group. The entropy parameter area under the curve (AUC) (0.903) was significantly better than the kurtosis parameter AUC (0.859) and the inhomogeneity parameter AUC (0.729). When the entropy parameter Cut-off point = 3.883, the sensitivity, specificity and accuracy of glioblastoma and PBL were 85.7, 86.4 and 86.0%, respectively, by differential diagnosis.

CONCLUSION

Texture analysis of tumor peritumoral edema provided quantifiable information, which might be a new method for differentiating glioblastoma from PBL.

Radiomic features from dynamic susceptibility contrast perfusion-weighted imaging improve the three-class prediction of molecular subtypes in patients with adult diffuse gliomas

OBJECTIVES

To investigate whether radiomic features extracted from dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) can improve the prediction of the molecular subtypes of adult diffuse gliomas, and to further develop and validate a multimodal radiomic model by integrating radiomic features from conventional and perfusion MRI.

METHODS

We extracted 1197 radiomic features from each sequence of conventional MRI and DSC-PWI, respectively. The Boruta algorithm was used for feature selection and combination, and a three-class random forest method was applied to construct the models. We also constructed a combined model by integrating radiomic features and clinical metrics. The models' diagnostic performance for discriminating the molecular subtypes (IDH wild type [IDHwt], IDH mutant and 1p/19q-noncodeleted [IDHmut-noncodel], and IDH mutant and 1p/19q-codeleted [IDHmut-codel]) was compared using AUCs in the validation set.

RESULTS

We included 272 patients (training set, n = 166; validation set, n = 106) with grade II-IV gliomas (mean age, 48.7 years; range, 19-77 years). The proportions of the molecular subtypes were 66.2% IDHwt, 15.1% IDHmut-noncodel, and 18.8% IDHmut-codel. Nineteen radiomic features (13 from conventional MRI and 6 from DSC-PWI) were selected to build the multimodal radiomic model. In the validation set, the multimodal radiomic model showed better performance than the conventional radiomic model did in predicting the IDHwt and IDHmut-codel subtypes, which was comparable to the conventional radiomic model in predicting the IDHmut-noncodel subtype. The multimodal radiomic model yielded similar performance as the combined model in predicting the three molecular subtypes.

CONCLUSIONS

Adding DSC-PWI to conventional MRI can improve molecular subtype prediction in patients with diffuse gliomas.

KEY POINTS

• The multimodal radiomic model outperformed conventional MRI when predicting both the IDH wild type and IDH mutant and 1p/19q-codeleted subtypes of gliomas. • The multimodal radiomic model showed comparable performance to the combined model in the prediction of the three molecular subtypes. • Radiomic features from T1-weighted gadolinium contrast-enhanced and relative cerebral blood volume images played an important role in the prediction of molecular subtypes.

A systematic review and meta-analysis on the differentiation of glioma grade and mutational status by use of perfusion-based magnetic resonance imaging

Background

Molecular characterization plays a crucial role in glioma classification which impacts treatment strategy and patient outcome. Dynamic susceptibility contrast (DSC) and dynamic contrast enhanced (DCE) perfusion imaging have been suggested as methods to help characterize glioma in a non-invasive fashion. This study set out to review and meta-analyze the evidence on the accuracy of DSC and/or DCE perfusion MRI in predicting IDH genotype and 1p/19q integrity status.

Methods

After systematic literature search on Medline, EMBASE, Web of Science and the Cochrane Library, a qualitative meta-synthesis and quantitative meta-analysis were conducted. Meta-analysis was carried out on aggregated AUC data for different perfusion metrics.

Results

Of 680 papers, twelve were included for the qualitative meta-synthesis, totaling 1384 patients. It was observed that CBV, ktrans, Ve and Vp values were, in general, significantly higher in IDH wildtype compared to IDH mutated glioma. Meta-analysis comprising of five papers (totaling 316 patients) showed that the AUC of CBV, ktrans, Ve and Vp were 0.85 (95%-CI 0.75–0.93), 0.81 (95%-CI 0.74–0.89), 0.84 (95%-CI 0.71–0.97) and 0.76 (95%-CI 0.61–0.90), respectively. No conclusive data on the prediction of 1p/19q integrity was available from these studies.

Conclusions

Future research should aim to predict 1p/19q integrity based on perfusion MRI data. Additionally, correlations with other clinically relevant outcomes should be further investigated, including patient stratification for treatment and overall survival.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13244-022-01230-7.

Preoperative Diagnosis and Molecular Characterization of Gliomas With Liquid Biopsy and Radiogenomics

Gliomas are a heterogenous group of central nervous system tumors with different outcomes and different therapeutic needs. Glioblastoma, the most common subtype in adults, has a very poor prognosis and disabling consequences. The World Health Organization (WHO) classification specifies that the typing and grading of gliomas should include molecular markers. The molecular characterization of gliomas has implications for prognosis, treatment planning, and prediction of treatment response. At present, gliomas are diagnosed via tumor resection or biopsy, which are always invasive and frequently risky methods. In recent years, however, substantial advances have been made in developing different methods for the molecular characterization of tumors through the analysis of products shed in body fluids. Known as liquid biopsies, these analyses can potentially provide diagnostic and prognostic information, guidance on choice of treatment, and real-time information on tumor status. In addition, magnetic resonance imaging (MRI) is another good source of tumor data; radiomics and radiogenomics can link the imaging phenotypes to gene expression patterns and provide insights to tumor biology and underlying molecular signatures. Machine and deep learning and computational techniques can also use quantitative imaging features to non-invasively detect genetic mutations. The key molecular information obtained with liquid biopsies and radiogenomics can be useful not only in the diagnosis of gliomas but can also help predict response to specific treatments and provide guidelines for personalized medicine. In this article, we review the available data on the molecular characterization of gliomas using the non-invasive methods of liquid biopsy and MRI and suggest that these tools could be used in the future for the preoperative diagnosis of gliomas.

Diagnostic and Prognostic Value of pH- and Oxygen-Sensitive Magnetic Resonance Imaging in Glioma: A Retrospective Study

Characterization of hypoxia and tissue acidosis could advance the understanding of glioma biology and improve patient management. In this study, we evaluated the ability of a pH- and oxygen-sensitive magnetic resonance imaging (MRI) technique to differentiate glioma genotypes, including isocitrate dehydrogenase (IDH) mutation, 1p/19q co-deletion, and epidermal growth factor receptor (EGFR) amplification, and investigated its prognostic value. A total of 159 adult glioma patients were scanned with pH- and oxygen-sensitive MRI at 3T. We quantified the pH-sensitive measure of magnetization transfer ratio asymmetry (MTRasym) and oxygen-sensitive measure of R2’ within the tumor region-of-interest. IDH mutant gliomas showed significantly lower MTRasym × R2’ (p < 0.001), which differentiated IDH mutation status with sensitivity and specificity of 90.0% and 71.9%. Within IDH mutants, 1p/19q codeletion was associated with lower tumor acidity (p < 0.0001, sensitivity 76.9%, specificity 91.3%), while IDH wild-type, EGFR-amplified gliomas were more hypoxic (R2’ p = 0.024, sensitivity 66.7%, specificity 76.9%). Both R2’ and MTRasym × R2’ were significantly associated with patient overall survival (R2’: p = 0.045; MTRasym × R2’: p = 0.002) and progression-free survival (R2’: p = 0.010; MTRasym × R2’: p < 0.0001), independent of patient age, treatment status, and IDH status. The pH- and oxygen-sensitive MRI is a clinically feasible and potentially valuable imaging technique for distinguishing glioma subtypes and providing additional prognostic value to clinical practice.

Predicting 1p/19q codeletion status using diffusion-, susceptibility-, perfusion-weighted, and conventional MRI in IDH-mutant lower-grade gliomas

BACKGROUND

Isocitrate dehydrogenase (IDH)-mutant lower-grade gliomas (LGGs) are further classified into two classes: with and without 1p/19q codeletion. IDH-mutant and 1p/19q codeleted LGGs have better prognosis compared with IDH-mutant and 1p/19q non-codeleted LGGs.

PURPOSE

To evaluate conventional magnetic resonance imaging (cMRI), diffusion-weighted imaging (DWI), susceptibility-weighted imaging (SWI), and dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) for predicting 1p/19q codeletion status of IDH-mutant LGGs.

MATERIAL AND METHODS

We retrospectively reviewed cMRI, DWI, SWI, and DSC-PWI in 142 cases of IDH mutant LGGs with known 1p/19q codeletion status. Features of cMRI, relative ADC (rADC), intratumoral susceptibility signals (ITSSs), and the value of relative cerebral blood volume (rCBV) were compared between IDH-mutant LGGs with and without 1p/19q codeletion. Receiver operating characteristic curve and logistic regression were used to determine diagnostic performances.

RESULTS

IDH-mutant and 1p/19q non-codeleted LGGs tended to present with the T2/FLAIR mismatch sign and distinct borders (P < 0.001 and P = 0.038, respectively). Parameters of rADC, ITSSs, and rCBV_max were significantly different between the 1p/19q codeleted and 1p/19q non-codeleted groups (P < 0.001, P = 0.017, and P < 0.001, respectively). A combination of cMRI, SWI, DWI, and DSC-PWI for predicting 1p/19q codeletion status in IDH-mutant LGGs resulted in a sensitivity, specificity, positive predictive value, negative predictive value, and an AUC of 80.36%, 78.57%, 83.30%, 75.00%, and 0.88, respectively.

CONCLUSION

1p/19q codeletion status of IDH-mutant LGGs can be stratified using cMRI and advanced MRI techniques, including DWI, SWI, and DSC-PWI. A combination of cMRI, rADC, ITSSs, and rCBV_max may improve the diagnostic performance for predicting 1p/19q codeletion status.

Joint application of biochemical markers and imaging techniques in the accurate and early detection of glioblastoma

Glioblastoma is a primary brain tumor with the most metastatic effect in adults. Despite the wide range of multidimensional treatments, tumor heterogeneity is one of the main causes of tumor spread and gives great complexity to diagnostic and therapeutic methods. Therefore, featuring noble noninvasive prognostic methods that are focused on glioblastoma heterogeneity is perceived as an urgent need. Imaging neuro-oncological biomarkers including MGMT (O⁶-methylguanine-DNA methyltransferase) promoter methylation status, tumor grade along with other tumor characteristics and demographic features (e.g., age) are commonly referred to during diagnostic, therapeutic and prognostic processes. Therefore, the use of new noninvasive prognostic methods focused on glioblastoma heterogeneity is considered an urgent need. Some neuronal biomarkers, including the promoter methylation status of the promoter MGMT, the characteristics and grade of the tumor, along with the patient's demographics (such as age and sex) are involved in diagnosis, treatment, and prognosis. Among the wide array of imaging techniques, magnetic resonance imaging combined with the more physiologically detailed technique of H-magnetic resonance spectroscopy can be useful in diagnosing neurological cancer patients. In addition, intracranial tumor qualitative analysis and sometimes tumor biopsies help in accurate diagnosis. This review summarizes the evidence for biochemical biomarkers being a reliable biomarker in the early detection and disease management in GBM. Moreover, we highlight the correlation between Imaging techniques and biochemical biomarkers and ask whether they can be combined.

Human IDH mutant 1p/19q co-deleted gliomas have low tumor acidity as evidenced by molecular MRI and PET: a retrospective study

Co-deletion of 1p/19q is a hallmark of oligodendroglioma and predicts better survival. However, little is understood about its metabolic characteristics. In this study, we aimed to explore the extracellular acidity of WHO grade II and III gliomas associated with 1p/19q co-deletion. We included 76 glioma patients who received amine chemical exchange saturation transfer (CEST) imaging at 3 T. Magnetic transfer ratio asymmetry (MTR_asym) at 3.0 ppm was used as the pH-sensitive CEST biomarker, with higher MTR_asym indicating lower pH. To control for the confounder factors, T₂ relaxometry and l-6-¹⁸F-fluoro-3,4-dihydroxyphenylalnine (¹⁸F-FDOPA) PET data were collected in a subset of patients. We found a significantly lower MTR_asym in 1p/19q co-deleted gliomas (co-deleted, 1.17% ± 0.32%; non-co-deleted, 1.72% ± 0.41%, P = 1.13 × 10⁻⁷), while FDOPA (P = 0.92) and T₂ (P = 0.61) were not significantly affected. Receiver operating characteristic analysis confirmed that MTR_asym could discriminate co-deletion status with an area under the curve of 0.85. In analysis of covariance, 1p/19q co-deletion status was the only significant contributor to the variability in MTR_asym when controlling for age and FDOPA (P = 2.91 × 10⁻³) or T₂ (P = 8.03 × 10⁻⁶). In conclusion, 1p/19q co-deleted gliomas were less acidic, which may be related to better prognosis. Amine CEST-MRI may serve as a non-invasive biomarker for identifying 1p/19q co-deletion status.

Updates in the Neuoroimaging and WHO Classification of Primary CNS Gliomas: A Review of Current Terminology, Diagnosis, and Clinical Relevance From a Radiologic Prospective

As new advances in the genomics and imaging of CNS tumors continues to evolve, a standardized system for classification is increasingly essential to diagnosis and management. The molecular markers introduced in the 2016 WHO classification of CNS tumors bring both practical and conceptual advances to the characterization of gliomas, strengthening the prognostic and predictive value of terminology while shedding light on the underlying mechanisms that drive biologic behavior. The purpose of this article is to provide a succinct overview of primary intracranial gliomas from a neuroradiologic prospective and according to the 5th edition WHO classification that was revised in 2016. An update of the molecular markers pertinent to defining the major lineages of brain gliomas will be provided, followed by discussion of the terminology, grading and imaging features associated with individual entities. Neuroradiologists should be aware of the key genomic and radiomic features of common brain gliomas, and familiar with an integrated approach to their diagnosis and grading.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Survival Associations Using Perfusion and Diffusion Magnetic Resonance Imaging in Patients With Histologic and Genetic Defined Diffuse Glioma World Health Organization Grades II and III

OBJECTIVE

According to the new World Health Organization 2016 classification for tumors of the central nervous system, 1p/19q codeletion defines the genetic hallmark that differentiates oligodendrogliomas from diffuse astrocytomas. The aim of our study was to evaluate whether relative cerebral blood volume (rCBV) and apparent diffusion coefficient (ADC) histogram analysis can stratify survival in adult patients with genetic defined diffuse glioma grades II and III.

METHODS

Sixty-seven patients with untreated diffuse gliomas World Health Organization grades II and III and known 1p/19q codeletion status were included retrospectively and analyzed using ADC and rCBV maps based on whole-tumor volume histograms. Overall survival and progression-free survival (PFS) were analyzed by using Kaplan-Meier and Cox survival analyses adjusted for known survival predictors.

RESULTS

Significant longer PFS was associated with homogeneous rCBV distribution-higher rCBVpeak (median, 37 vs 26 months; hazard ratio [HR], 3.2; P = 0.02) in patients with astrocytomas, and heterogeneous rCBV distribution-lower rCBVpeak (median, 46 vs 37 months; HR, 5.3; P < 0.001) and higher rCBVmean (median, 44 vs 39 months; HR, 7.9; P = 0.003) in patients with oligodendrogliomas. Apparent diffusion coefficient parameters (ADCpeak, ADCmean) did not stratify PFS and overall survival.

CONCLUSIONS

Tumors with heterogeneous perfusion signatures and high average values were associated with longer PFS in patients with oligodendrogliomas. On the contrary, heterogeneous perfusion distribution was associated with poor outcome in patients with diffuse astrocytomas.

Differentiation of grade II and III oligodendrogliomas from grade II and III astrocytomas: a histogram analysis of perfusion parameters derived from dynamic contrast-enhanced (DCE) and dynamic susceptibility contrast (DSC) MRI

Background Since oligodendroglial tumors are sensitive to chemotherapy and have a better prognosis, the differentiation of oligodendroglial tumors (OT) from astrocytic tumors (AT) is important. Purpose To investigate the perfusion and permeability parameters that differentiate grade II and III OT from AT, using dynamic contrast-enhanced (DCE) and dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI). Material and Methods We retrospectively reviewed the DCE and DSC MRIs of 39 patients with OT (OTs, n = 19; grade II, n = 12 and grade III, n = 7) and AT (ATs, n = 20; grade II, n = 7 and grade III, n = 13). Glioblastomas were not included. Various histogram parameters of relative cerebral blood volume, volume transfer constant (Ktrans), flux rate constant (Kep), plasma volume fraction (Vp), and extravascular extracellular volume fraction (Ve) from DSC and DCE MRI, were compared between the two groups. Univariable and multivariable logistic regression were used to distinguish OT from AT. Receiver operating characteristic (ROC) curve analysis was performed. Results On the results of DCE MRI, most of the histogram parameters of Ktrans, Kep, and Ve showed tendencies toward higher values in OT than AT. Multivariable logistic regression revealed that the 50th Kep and 95th Ktrans were the most significant parameters predictive of OT, with an odds ratio of 3.7 and 2.5, respectively ( P = 0.004 and 0.03). The area under the curve from the ROC curve analysis for the 50th Kep and the 95th Ktrans were 0.81 and 0.80, respectively. Conclusion The DCE MRI-derived parameters of Ktrans and Kep could facilitate differentiation of OT from AT.

Non-invasive tumor genotyping using radiogenomic biomarkers, a systematic review and oncology-wide pathway analysis

With targeted treatments playing an increasing role in oncology, the need arises for fast non-invasive genotyping in clinical practice. Radiogenomics is a rapidly evolving field of research aimed at identifying imaging biomarkers useful for non-invasive genotyping. Radiogenomic genotyping has the advantage that it can capture tumor heterogeneity, can be performed repeatedly for treatment monitoring, and can be performed in malignancies for which biopsy is not available. In this systematic review of 187 included articles, we compiled a database of radiogenomic associations and unraveled networks of imaging groups and gene pathways oncology-wide. Results indicated that ill-defined tumor margins and tumor heterogeneity can potentially be used as imaging biomarkers for 1p/19q codeletion in glioma, relevant for prognosis and disease profiling. In non-small cell lung cancer, FDG-PET uptake and CT-ground-glass-opacity features were associated with treatment-informing traits including EGFR-mutations and ALK-rearrangements. Oncology-wide gene pathway analysis revealed an association between contrast enhancement (imaging) and the targetable VEGF-signalling pathway. Although the need of independent validation remains a concern, radiogenomic biomarkers showed potential for prognosis prediction and targeted treatment selection. Quantitative imaging enhanced the potential of multiparametric radiogenomic models. A wealth of data has been compiled for guiding future research towards robust non-invasive genomic profiling.

Grading of oligodendroglial tumors of the brain with apparent diffusion coefficient, magnetic resonance spectroscopy, and dynamic susceptibility contrast imaging

Purpose We explored whether advanced magnetic resonance (MR) imaging techniques could grade oligodendrogliomas. Methods Forty patients (age 9-61 years) with oligodendroglial tumors were selected. There were 23 patients with World Health Organization grade II (group 1) and 17 patients with grade III (group 2) tumors. Apparent diffusion coefficient (ADC) maps were calculated by b values of 0 and 1000 s/mm². Dynamic susceptibility contrast (DSC) images were obtained during the first pass of a bolus of gadolinium-based contrast. These data were post-processed and cerebral blood volume (CBV) maps and permeability (PS) were calculated. MR spectroscopy was acquired after drawing a region of interest on the tumor using two-dimensional chemical shift imaging. Statistical analysis was performed using SPSS software. Results When the rPS_max was combined with the rCBV_max, there was a significant difference between the two groups ( p ≤ 0.03) with area under the curve of 0.742 (95% CI: 0.412-0.904). rCBV, rADC, choline/creatine, and choline/NAA alone were able to differentiate between the two groups; however, they did not show any statistical difference with p values of ≤ 0.121, ≤ 0.722, and ≤ 0.582, respectively. A CBV PS product threshold of 0.53 provided a sensitivity of 80% and a specificity of 83.3% in detection of grade III tumors. Conclusion Combined rCBV_max and rPS_max can be utilized to grade oligodendrogliomas. ADC values, relative cerebral blood volume (rCBV), and MR spectroscopy alone can be utilized to differentiate between the two groups of oligodendrogliomas but without statistical significance.

3D Pseudocontinuous Arterial Spin-Labeling MR Imaging in the Preoperative Evaluation of Gliomas

BACKGROUND AND PURPOSE

Previous studies showed conflicting results concerning the value of CBF maps obtained from arterial spin-labeling MR imaging in grading gliomas. This study was performed to investigate the effectiveness of CBF maps derived from 3D pseudocontinuous arterial spin-labeling in preoperatively assessing the grade, cellular proliferation, and prognosis of gliomas.

MATERIALS AND METHODS

Fifty-eight patients with pathologically confirmed gliomas underwent preoperative 3D pseudocontinuous arterial spin-labeling. The receiver operating characteristic curves for parameters to distinguish high-grade gliomas from low-grade gliomas were generated. Pearson correlation analysis was used to assess the correlation among parameters. Survival analysis was conducted with Cox regression.

RESULTS

Both maximum CBF and maximum relative CBF were significantly higher in high-grade gliomas than in low-grade gliomas (P < .001). The areas under the curve for maximum CBF and maximum relative CBF in distinguishing high-grade gliomas from low-grade gliomas were 0.828 and 0.863, respectively. Both maximum CBF and maximum relative CBF had no correlation with the Ki-67 index in all subjects and had a moderate negative correlation with the Ki-67 index in glioblastomas (r = -0.475, -0.534, respectively). After adjustment for age, a higher maximum CBF (P = .008) and higher maximum relative CBF (P = .005) were associated with worse progression-free survival in gliomas, while a higher maximum relative CBF (P = .033) was associated with better overall survival in glioblastomas.

CONCLUSIONS

3D pseudocontinuous arterial spin-labeling-derived CBF maps are effective in preoperative evaluation of gliomas. Although gliomas with a higher blood flow are more malignant, glioblastomas with a lower blood flow are likely to be more aggressive.

Imaging Correlates of Adult Glioma Genotypes

Primary brain tumors, most commonly gliomas, are histopathologically typed and graded as World Health Organization (WHO) grades I-IV according to increasing degrees of malignancy. These grades provide prognostic information and guidance on treatment such as radiation therapy and chemotherapy after surgery. Despite the confirmed value of the WHO grading system, results of a multitude of studies and prospective interventional trials now indicate that tumors with identical morphologic criteria can have highly different outcomes. Molecular markers can allow subtypes of tumors of the same morphologic type and WHO grade to be distinguished and are, therefore, of great interest in personalization of brain tumor treatment. Recent genomic-wide studies have resulted in a far more comprehensive understanding of the genomic alterations in gliomas and provide suggestions for a new molecularly based classification. Magnetic resonance (MR) imaging phenotypes can serve as noninvasive surrogates for tumor genotypes and can provide important information for diagnosis, prognosis, and, eventually, personalized treatment. The newly emerged field of radiogenomics allows specific MR imaging phenotypes to be linked with gene expression profiles. In this article, the authors review the conventional and advanced imaging features of three tumoral genotypes with prognostic and therapeutic consequences: (a) isocitrate dehydrogenase mutation; (b) the combined loss of the short arm of chromosome 1 and the long arm of chromosome 19, or 1p19q codeletion; and (c) methylguanine methyltransferase promoter methylation. ^© RSNA, 2017.

Differential diagnosis of oligodendroglial and astrocytic tumors using imaging results: the added value of perfusion MR imaging

PURPOSE

The purposes of the present study are to assess whether different characteristics of oligodendrogliomas and astrocytic tumors are visible on MR imaging and to determine the added value of perfusion imaging in conventional MR imaging when differentiating oligodendrogliomas from astrocytic tumors.

METHODS

We retrospectively studied 22 oligodendroglioma and 54 astrocytic tumor patients, including glioblastoma multiforme (GBM). The morphological tumor characteristics were evaluated using MR imaging. The rCBV, K ^trans, and V _e values were recorded. All imaging and clinical values were compared. The ability to discriminate between the two entities was evaluated using receiver operating characteristic curve analyses. Separate comparison analysis between oligodendroglioma and astrocytic tumors excluding GBM was also performed.

RESULTS

The presence of calcification, higher cortex involvement ratio, and lower V _e value were more representative of oligodendrogliomas than astrocytic tumors (P = <0.001, 0.038, and <0.001, respectively). The area under the curve (AUC) value of a combination of calcification and cortex involvement ratio was 0.796. The combination of all three parameters, including V _e, further increased the diagnostic performance (AUC = 0.881). Comparison test of the two AUC areas revealed significant difference (P = 0.0474). The presence of calcification and higher cortex involvement ratio were the only findings suggestive of oligodendrogliomas than astrocytic tumors with exclusion of GBMs (P = 0.014 and <0.001, respectively).

CONCLUSION

Cortex involvement ratio and the presence of calcification with V _e values were diagnostically accurate in identifying oligodendrogliomas. The V _e value calculated from dynamic contrast-enhanced MR imaging could be a supportive tool for differentiating between oligodendrogliomas and astrocytic tumors including GBMs.

Dynamic contrast-enhanced MRI perfusion for differentiating between melanoma and lung cancer brain metastases

Brain metastases originating from different primary sites overlap in appearance and are difficult to differentiate with conventional MRI. Dynamic contrast-enhanced (DCE)-MRI can assess tumor microvasculature and has demonstrated utility in characterizing primary brain tumors. Our aim was to evaluate the performance of plasma volume (Vp) and volume transfer coefficient (Ktrans ) derived from DCE-MRI in distinguishing between melanoma and nonsmall cell lung cancer (NSCLC) brain metastases. Forty-seven NSCLC and 23 melanoma brain metastases were retrospectively assessed with DCE-MRI. Regions of interest were manually drawn around the metastases to calculate Vpmean and Kmeantrans. The Mann-Whitney U test and receiver operating characteristic analysis (ROC) were performed to compare perfusion parameters between the two groups. The Vpmean of melanoma brain metastases (4.35, standard deviation [SD] = 1.31) was significantly higher (P = 0.03) than Vpmean of NSCLC brain metastases (2.27, SD = 0.96). The Kmeantrans values were higher in melanoma brain metastases, but the difference between the two groups was not significant (P = 0.12). Based on ROC analysis, a cut-off value of 3.02 for Vpmean (area under curve = 0.659 with SD = 0.074) distinguished between melanoma brain metastases and NSCLC brain metastases (P < 0.01) with 72% specificity. Our data show the DCE-MRI parameter Vpmean can differentiate between melanoma and NSCLC brain metastases. The ability to noninvasively predict tumor histology of brain metastases in patients with multiple malignancies can have important clinical implications.

Noninvasively detecting Isocitrate dehydrogenase 1 gene status in astrocytoma by dynamic susceptibility contrast MRI

PURPOSE

To investigate the value of dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI) in the noninvasive evaluation of isocitrate dehydrogenase (IDH) 1 gene status in astrocytoma.

MATERIALS AND METHODS

The preoperative DSC MRI data of 91 lesions with pathologically confirmed astrocytoma were retrospectively analyzed. MR examination was performed on a 3T MRI scanner. The normalized maximum ratios of relative cerebral blood volume (rCBV ratio) of tumor parenchyma were measured. The enrolled astrocytoma patients were divided into six groups according to the World Health Organization (WHO) classification method and IDH1 gene status. The differences in the rCBV ratio of tumor parenchyma between the IDH1 gene mutant and wildtype groups of WHO grade II, III, and IV were compared and plotted receiver operating characteristic (ROC) curves were drawn.

RESULTS

The IDH1 gene mutant and wildtype groups of WHO grade II, III, and IV astrocytoma showed differences in the rCBV ratio (P = 0.005, 0.045, and 0.005, respectively). In WHO grade II, III, and IV astrocytoma, the area under the ROC curve was respectively 0.83, 0.86, and 0.94. The cutoff value of the rCBV ratio was respectively 2.20, 3.14, and 5.63.

CONCLUSION

The rCBV ratio value provided by DSC MRI provides a new potential imaging method for the noninvasive evaluation of the IDH1 status in astrocytoma.

LEVEL OF EVIDENCE

3 J. Magn. Reson. Imaging 2017;45:492-499.

Imaging of oligodendroglioma

Oligodendroglioma are glial tumours, predominantly occurring in adults. Their hallmark molecular feature is codeletion of the 1p and 19q chromosome arms, which is not only of diagnostic but also of prognostic and predictive relevance. On imaging, these tumours characteristically show calcification, and they have a cortical–subcortical location, most commonly in the frontal lobe. Owing to their superficial location, there may be focal thinning or remodelling of the overlying skull. In contrast to other low-grade gliomas, minimal to moderate enhancement is commonly seen and perfusion may be moderately increased. This complicates differentiation from high-grade, anaplastic oligodendroglioma, in which enhancement and increased perfusion are also common. New enhancement in a previously non-enhancing, untreated tumour, however, is suggestive of malignant transformation, as is high growth rate. MR spectroscopy may further aid in the differentiation between low- and high-grade oligodendroglioma. A relatively common feature of recurrent disease is leptomeningeal dissemination, but extraneural spread is rare. Tumours with the 1p/19q codeletion more commonly show heterogeneous signal intensity, particularly on T₂ weighted imaging; calcifications; an indistinct margin; and mildly increased perfusion and metabolism than 1p/19q intact tumours. For the initial diagnosis of oligodendroglioma, MRI and CT are complementary; MRI is superior to CT in assessing tumour extent and cortical involvement, whereas CT is most sensitive to calcification. Advanced and functional imaging techniques may aid in grading and assessing the molecular genotype as well as in differentiating between tumour recurrence and radiation necrosis, but so far no unequivocal method or combination of methods is available.

Dynamic Contrast-Enhanced MRI in Low-Grade Versus Anaplastic Oligodendrogliomas

BACKGROUND AND PURPOSE

Low-grade and anaplastic oligodendrogliomas are often difficult to differentiate on the basis of conventional MR imaging characteristics. Dynamic contrast-enhanced (DCE) MRI can assess tumor microvasculature and has demonstrated utility for predicting glioma grade and prognosis in primary brain tumors. The aim of our study was to evaluate the performance of plasma volume (Vp) and volume transfer coefficient (K(trans) ) derived from DCE MRI in differentiating between grade II and grade III oligodendrogliomas.

MATERIALS AND METHODS

Twenty-four consecutive patients with pathologically confirmed oligodendroglioma (World Health Organization grade II, n = 14 and grade III, n = 10) were retrospectively assessed. Pretreatment DCE MRI was performed and regions of interest were manually drawn around the entire tumor volume to calculate Vp and K(trans) . The Mann-Whitney U test and receiver operating characteristic (ROC) analysis were performed to compare pharmacokinetic parameters between the 2 groups.

RESULTS

The Vpmean values for grade III oligodendrogliomas were significantly higher (P = .03) than those for grade II oligodendrogliomas. The K(trans) mean values were higher in grade III lesions, but the difference between the 2 groups was not statistically significant (P > .05). Based on ROC analysis, the Vpmean (area under curve = .757, SD = .1) cut-off value that provided the best combination of high sensitivity and specificity to distinguish between grade II and III oligodendrogliomas was 2.35 (P < .03).

CONCLUSION

The results of our study suggest the DCE MRI parameter Vpmean can noninvasively differentiate between grade II and grade III oligodendrogliomas.

Genetics and imaging of oligodendroglial tumors

Oligodendroglial tumors are chemosensitive with a favorable prognosis compared with other histological subtypes. The genetic hallmark of co-deletion of 1p and 19q determines both treatment response and prognosis. While this test now forms part of routine histopathology diagnosis in many laboratories, alternative noninvasive imaging biomarkers of tumor genotype remain an attractive proposition. This review will focus on imaging biomarkers of molecular genetics in oligodendroglial tumors.

Combination of diffusion tensor imaging and conventional MRI correlates with isocitrate dehydrogenase 1/2 mutations but not 1p/19q genotyping in oligodendroglial tumours

OBJECTIVES

To explore the correlations of conventional MRI (cMRI) and diffusion tensor imaging (DTI) values with the 1p/19 codeletion and IDH mutations in oligodendroglial tumours (OTs).

METHODS

Eighty-four patients with OTs who underwent cMRI and DTI were retrospectively reviewed. The maximal fractional anisotropy and minimal apparent diffusion coefficient (ADC) were measured and compared using the Mann-Whitney U test. Receiver operating characteristic curves, logistic regression analysis and four-table statistics analysis were performed to predict genotypings.

RESULTS

OTs with 1p/19q codeletion or IDH mutations were prone to locate in frontal (P = 0.106 and 0.005, respectively) and insular lobes and were associated with absent or blurry contrast enhancement (P = 0.040 and 0.013, respectively). DTI values showed significant differences between OTs with and without IDH mutations (P < 0.05) but not in OTs with and without 1p/19q loss. The Ki-67 index significantly correlated with IDH mutations (P = 0.002) but not with 1p/19q codeletion. A combination of DTI and cMRI for the identification of IDH mutations resulted in sensitivity, specificity, positive and negative predictive values of 92.2 %, 75.8 %, 93.8 % and 71.1 %, respectively.

CONCLUSIONS

Combination of DTI and cMRI correlates with isocitrate dehydrogenase 1/2 mutations but not 1p/19q genotyping in OTs.

KEY POINTS

• OTs with 1p/19q codeletion were associated with absent or blurry contrast enhancement • OTs with IDH mutations were also associated with absent or blurry contrast enhancement • OTs with IDH mutations were prone to locate in frontal and insular lobes • DTI values can provide a non-invasive method for assessing the IDH status of OTs • A combination of DTI and cMRI correlates with isocitrate dehydrogenase 1/2 mutations.

Benefits of dynamic susceptibility-weighted contrast-enhanced perfusion MRI for glioma diagnosis and therapy

Glioma are the most common supra-tentorial brain tumor in the USA with an estimated annual incidence of 17,000 new cases per year. Dynamic susceptibility-weighted contrast-enhanced (DSC) perfusion MRI noninvasively characterizes tumor biology allowing for the diagnosis and therapeutic monitoring of glioma. This MRI technique utilizes the rapid changes in signal intensity caused by a rapid intravascular bolus of paramagnetic contrast agent to calculate physiologic perfusion metrics. DSC perfusion MRI has increasingly become an integrated part of glioma imaging. The specific aim of this article is to review the benefits of DSC perfusion MRI in the therapy of glioma.

Prognostic Value of Dynamic Susceptibility Contrast-Enhanced and Diffusion-Weighted MR Imaging in Patients with Glioblastomas

BACKGROUND AND PURPOSE

Prediction of survival in patients with glioblastomas is important for individualized treatment planning. This study aimed to assess the prognostic utility of presurgical dynamic susceptibility contrast and diffusion-weighted imaging for overall survival in patients with glioblastoma.

MATERIALS AND METHODS

MR imaging data from pathologically proved glioblastomas between June 2006 to December 2013 in 58 patients (mean age, 62.7 years; age range, 22-89 years) were included in this retrospective study. Patients were divided into long survival (≥15 months) and short survival (<15 months) groups, depending on overall survival time. Patients underwent dynamic susceptibility contrast perfusion and DWI before surgery and were treated with chemotherapy and radiation therapy. The maximum relative cerebral blood volume and minimum mean diffusivity values were measured from the enhancing part of the tumor.

RESULTS

Maximum relative cerebral blood volume values in patients with short survival were significantly higher compared with those who demonstrated long survival (P < .05). No significant difference was observed in the minimum mean diffusivity between short and long survivors. Receiver operator curve analysis demonstrated that a maximum relative cerebral blood volume cutoff value of 5.79 differentiated patients with low and high survival with an area under the curve of 0.93, sensitivity of 0.89, and specificity of 0.90 (P < .001), while a minimum mean diffusivity cutoff value of 8.35 × 10(-4)mm(2)/s had an area under the curve of 0.55, sensitivity of 0.71, and specificity of 0.47 (P > .05) in separating the 2 groups.

CONCLUSIONS

Maximum relative cerebral blood volume may be used as a prognostic marker of overall survival in patients with glioblastomas.

Modern brain tumor imaging

The imaging and clinical management of patients with brain tumor continue to evolve over time and now heavily rely on physiologic imaging in addition to high-resolution structural imaging. Imaging remains a powerful noninvasive tool to positively impact the management of patients with brain tumor. This article provides an overview of the current state-of-the art clinical brain tumor imaging. In this review, we discuss general magnetic resonance (MR) imaging methods and their application to the diagnosis of, treatment planning and navigation, and disease monitoring in patients with brain tumor. We review the strengths, limitations, and pitfalls of structural imaging, diffusion-weighted imaging techniques, MR spectroscopy, perfusion imaging, positron emission tomography/MR, and functional imaging. Overall this review provides a basis for understudying the role of modern imaging in the care of brain tumor patients.

Advances in Magnetic Resonance Imaging and Positron Emission Tomography Imaging for Grading and Molecular Characterization of Glioma

In recent years, the management of glioma has evolved significantly, reflecting our better understanding of the underlying mechanisms of tumor development, tumor progression, and treatment response. Glioma grade, along with a number of underlying molecular and genetic biomarkers, has been recognized as an important prognostic and predictive factor that can help guide the management of patients. This article highlights advances in magnetic resonance imaging (MRI), including diffusion-weighted imaging, diffusion tensor imaging, magnetic resonance spectroscopy, dynamic contrast-enhanced imaging, and perfusion MRI, as well as position emission tomography using various tracers including methyl-(11)C-l-methionine and O-(2-(18)F-fluoroethyl)-l-tyrosine. Use of multiparametric imaging data has improved the diagnostic strength of imaging, introduced the potential to noninvasively interrogate underlying molecular features of low-grade glioma and to guide local therapies such as surgery and radiotherapy.

Cerebral blood volume calculated by dynamic susceptibility contrast-enhanced perfusion MR imaging: preliminary correlation study with glioblastoma genetic profiles

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.

Differentiation between oligodendroglioma genotypes using dynamic susceptibility contrast perfusion-weighted imaging and proton MR spectroscopy

BACKGROUND AND PURPOSE

Oligodendrogliomas with 1p/19q chromosome LOH are more sensitive to chemoradiation therapy than those with intact alleles. The usefulness of dynamic susceptibility contrast-PWI-guided ¹H-MRS in differentiating these 2 genotypes was tested in this study.

MATERIALS AND METHODS

Forty patients with oligodendrogliomas, 1p/19q LOH (n = 23) and intact alleles (n = 17), underwent MR imaging and 2D-¹H-MRS. ¹H-MRS VOI was overlaid on FLAIR images to encompass the hyperintense abnormality on the largest cross-section of the neoplasm and then overlaid on CBV maps to coregister CBV maps with ¹H-MRS VOI. rCBVmax values were obtained by measuring the CBV from each of the selected ¹H-MRS voxels in the neoplasm and were normalized with respect to contralateral white matter. Metabolite ratios with respect to ipsilateral Cr were computed from the voxel corresponding to the rCBVmax value. Logistic regression and receiver operating characteristic analyses were performed to ascertain the best model to discriminate the 2 genotypes of oligodendrogliomas. Qualitative evaluation of conventional MR imaging characteristics (patterns of tumor border, signal intensity, contrast enhancement, and paramagnetic susceptibility effect) was also performed to distinguish the 2 groups of oligodendrogliomas.

RESULTS

The incorporation of rCBVmax value and metabolite ratios (NAA/Cr, Cho/Cr, Glx/Cr, myo-inositol/Cr, and lipid + lactate/Cr) into the multivariate logistic regression model provided the best discriminatory classification with sensitivity (82.6%), specificity (64.7%), and accuracy (72%) in distinguishing 2 oligodendroglioma genotypes. Oligodendrogliomas with 1p/19q LOH were also more associated with paramagnetic susceptibility effect (P < .05).

CONCLUSIONS

Our preliminary results indicate the potential of combing PWI and ¹H-MRS to distinguish oligodendroglial genotypes.

Multimodal MR imaging (diffusion, perfusion, and spectroscopy): is it possible to distinguish oligodendroglial tumor grade and 1p/19q codeletion in the pretherapeutic diagnosis?

BACKGROUND AND PURPOSE

Pretherapeutic determination of tumor grade and genotype in grade II and III oligodendroglial tumors is clinically important but is still challenging. Tumor grade and 1p/19q status are currently the 2 most important factors in therapeutic decision making for patients with these tumors. Histopathology and cMRI studies are still limited in some cases. In the present study, we were interested in determining whether the combination of PWI, DWI, and MR spectroscopy could help distinguish oligodendroglial tumors according to their histopathologic grade and genotype.

MATERIALS AND METHODS

We retrospectively reviewed 50 adult patients with grade II and III oligodendrogliomas and oligoastrocytomas who had DWI, PWI, and MR spectroscopy at short and long TE data and known 1p/19q status. Univariate analyses and multivariate random forest models were performed to determine which criteria could differentiate between grades and genotypes.

RESULTS

ADC, rCBV, rCBF, and rK2 were significantly different between grade II and III oligodendroglial tumors. DWI, PWI, and MR spectroscopy showed no significant difference between tumors with and without 1p/19q loss. Separation between tumor grades and genotypes with cMRI alone showed 31% and 48% misclassification rates, respectively. Multimodal MR imaging helps to determine tumor grade and 1p/19q genotype more accurately (misclassification rates of 17% and 40%, respectively).

CONCLUSIONS

Although multimodal investigation of oligodendroglial tumors has a lower contribution to 1p/19q genotyping compared with cMRI alone, it greatly improves the accuracy of grading of these neoplasms. Use of multimodal MR imaging could thus provide valuable information that may assist clinicians in patient preoperative management and treatment decision making.

Biology, genetics and imaging of glial cell tumours

Despite advances in therapy, gliomas remain associated with poor prognosis. Clinical advances will be achieved through molecularly targeted biological therapies, for which knowledge of molecular genetic and gene expression characteristics in relation to histopathology and in vivo imaging are essential. Recent research supports the molecular classification of gliomas based on genetic alterations or gene expression profiles, and imaging data supports the concept that molecular subtypes of glioma may be distinguished through non-invasive anatomical, physiological and metabolic imaging techniques, suggesting differences in the baseline biology of genetic subtypes of infiltrating glioma. Furthermore, MRI signatures are now being associated with complex gene expression profiles and cellular signalling pathways through genome-wide microarray studies using samples obtained by image guidance which may be co-registered with clinical imaging. In this review we describe the pathobiology, molecular pathogenesis, stem cells and imaging characteristics of gliomas with emphasis on astrocytomas and oligodendroglial neoplasms.

11C-methionine uptake correlates with combined 1p and 19q loss of heterozygosity in oligodendroglial tumors

BACKGROUND AND PURPOSE

Oligodendroglial tumors with 1p/19q LOH are known to show longer patient survival than those without 1p/19q LOH, but the reason for this clinical difference has not been elucidated, to our knowledge. This study was designed to clarify whether uptake of MET correlates with 1p/19q LOH of oligodendroglial tumors.

MATERIALS AND METHODS

This study included 102 consecutive patients with supratentorial WHO grade II and III oligodendroglial tumors (39 oligoastrocytic and 63 oligodendroglial tumors) that were resected and diagnosed between January 2008 and August 2011 at Tokyo Women's Medical University Hospital. These patients underwent MET PET T/N ratio measurement before treatment. T/N ratios were calculated by dividing the maximum SUV for the tumor by the mean SUV of the contralateral normal frontal cortex. After surgery, FISH for resected tissues was used to determine 1p/19q LOH.

RESULTS

The mean T/N ratio of tumors with 1p/19q LOH was significantly greater than that of tumors without 1p/19q LOH (P = .0166). The threshold T/N ratio value of 2.46 was found to correlate significantly with 1p/19q LOH by univariate (P = .0011) and multivariate analyses (P = .0209) in all tumors.

CONCLUSIONS

The T/N ratio on MET PET might be a useful aid to the diagnosis of 1p/19q LOH. Our data add new information on the biology and imaging characteristics of oligodendroglial tumors with 1p/19q LOH.

Use of magnetic perfusion-weighted imaging to determine epidermal growth factor receptor variant III expression in glioblastoma

Identification of the epidermal growth factor receptor variant III (EGFRvIII) mutation in glioblastoma has become increasingly relevant in the optimization of therapy. Traditionally, determination of tumor EGFRvIII-expression has relied on tissue-based diagnostics. Here, we assess the accuracy of magnetic resonance perfusion-weighted imaging (MR-PWI) in discriminating the EGFRvIII-expressing glioblastoma subtype. We analyzed RNA from 132 primary human glioblastoma tissue samples by reverse-transcription polymerase chain reaction (RT-PCR) for the EGFRvIII and EGFR wild-type mutations and by quantitative RT-PCR for expression of vascular endothelial growth factor (VEGF). Concurrently, 3 independent observers reviewed preoperative 1.5-Tesla (T)/SE or 3.0-Tesla (T)/GE MR perfusion images to determine the maximum relative tumor blood volume (rTBV) of each of these tumors. EGFRvIII-expressing glioblastomas showed significantly higher rTBV, compared with those tumors lacking EGFRvIII expression. This association was observed in both the 1.5T/SE (P = .000) and 3.0T/GE (P = .001) cohorts. By logistic regression analysis, combining the 2 MR system cohorts, rTBV was a very strong predictor of EGFRvIII mutation (odds ratio [rTBV] = 2.70; P = .000; McFadden's ρ(2) = 0.23). Furthermore, by receiver-operating characteristic curve analysis, rTBV discriminated EGFRvIII with very high accuracy (A(z) = 0.81). In addition, we found that VEGF upregulation was associated, although without reaching statistical significance, with EGFRvIII expression (P = .16) and with increased rTBV (F-ratio = 2.71; P = .102). These trends suggest that VEGF-mediated angiogenesis may be a potential mediator of angiogenesis to increase perfusion in EGFRvIII-expressing glioblastomas, but there are likely several other contributing factors. This study demonstrates the potential to use rTBV, a MR-PWI-derived parameter, as a noninvasive surrogate of the EGFRvIII mutation.

Absence of IDH mutation identifies a novel radiologic and molecular subtype of WHO grade II gliomas with dismal prognosis

The phenotypic heterogeneity of low-grade gliomas (LGGs) is still inconsistently explained by known molecular abnormalities in patients treated according to the present standards of care. IDH1 codon 132 and IDH2 codon 172 sequencing was performed in a series of 47 LGGs and correlated with clinical presentation, MR imaging characteristics, genomic profile and outcome. A total of 38 IDH1 mutations at codon 132 and 2 IDH2 mutations at codon 172 were found, including 35 R132H (87.5%), 2 R132C (5.0%), 1 R132S (2.5%) and 2 R172 M (5%). The IDH mutations were significantly associated with 1p19q deleted genotype (P = 0.031) and p53 expression (P = 0.014). The presence (vs. absence) of IDH mutations was associated with a better outcome (5-year survival rate, 93% vs. 51%, respectively, P = 0.000001). After adjustment for age, tumor location and size, radiologic infiltration pattern and extent of surgery, multivariate analysis confirmed that IDH mutations was an independent favorable prognostic factor (hazard ratio = 40.9; 95% CI, 2.89-578.49, P = 0.006). Furthermore, we showed that patients with IDH-nonmutated tumors were significantly older (P = 0.020) and that these tumors involved significantly more frequently the insula (P = 0.004), were larger in size (>6 cm, P = 0.047), displayed an infiltrative pattern on MRI (P = 0.007) and were all p53 negative with no 1p19q deletion (P < 10⁻⁶). The absence of IDH mutations in LGGs identifies a novel entity of LGGs with distinctive location, infiltrative behavior, specific molecular alterations, and dismal outcome. These findings could significantly modify the LGG classification and may represent a new tool to guide patient-tailored therapy.

Molecular genetics, imaging and treatment of oligodendroglial tumours

The discovery of a genetic signature of chemosensitivity and prognosis in oligodendroglial tumours prompted a new optimism in glioma management. After more than a decade since the initial reports, where do we stand in the current management of oligodendroglial tumours? This review focuses on the latest molecular genetics, imaging characteristics, and recent trials of treatment paradigms for these tumours.

Clinical impact of integrated physiologic brain tumor imaging

The development of new MRI techniques in the last two decades has provided neuroradiologists and neurosurgeons with additional noninvasive imaging tools for management and treatment of brain tumors. When coupled with standard structural MR sequences in imaging brain tumors, Blood Oxygenation Level Dependent (BOLD) functional MRI (fMRI), Perfusion Weighted Imaging (PWI) and Diffusion Tensor Imaging (DTI) provide additional physiologic information that is very useful for differential diagnosis, presurgical planning and prognosis. In this review after a brief technical description of BOLD fMRI, PWI and DTI, studies are described from the literature that have extensively validated these imaging techniques in comparison with invasive "gold standard" techniques such as intraoperative electrical cortical and subcortical stimulation mapping or biopsy. Additional studies are mentioned that demonstrate the positive impact of BOLD fMRI, PWI and DTI on brain tumor treatment and clinical outcome. In the final section an interesting clinical case treated at our institution is presented that highlights the clinical utility of this integrated physiologic brain tumor imaging approach.

Genetic signature of adult gliomas and correlation with MRI features

In recent years the amount of information concerning the genetics and the biology of gliomas, and particularly of glioblastoma multiforme, increased steadily. Such an increase has been paralleled by the technological progress of MRI. The merging of these scientific areas, as summarized in this review, is helping the stratification of glioma patients for clinical trials and their clinical follow-up. Although available therapeutic options appear limited in number, it is likely that in the next 5 years, both as a consequence of the increased knowledge due to genomic sequencing of hundreds of glioblastoma specimens and to continuous improvements of MRI, new perspectives will be available for these patients, with a sizable impact on their prognosis.