Apparent diffusion coefficients in oligodendroglial tumors characterized by genotype

A metric for quantitative evaluation of glioma margin changes in magnetic resonance imaging

BACKGROUND

Gliomas differ from meningiomas in their margins, most of which are not separated from the surrounding tissue by a distinct interface.

PURPOSE

To characterize the margins of gliomas quantitatively based on the margin sharpness coefficient (MSC) is significant for clinical judgment and invasive analysis of gliomas.

MATERIAL AND METHODS

The data for this study used magnetic resonance image (MRI) data from 67 local patients and 15 open patients to quantify the intensity of changes in the glioma margins of the brain using MSC. The accuracy of MSC was assessed by consistency analysis and Bland-Altman test analysis, as well as invasive correlations using receiver operating characteristic (ROC) and Spearman correlation coefficients for subjects.

RESULTS

In grading the tumors, the mean MSC values were significantly lower for high-grade gliomas (HGG) than for low-grade gliomas (LGG). The concordance correlation between the measured gradient and the actual gradient was high (HGG: 0.981; LGG: 0.993), and the Bland-Altman mean difference at the 95% confidence interval (HGG: -0.576; LGG: 0.254) and the limits of concordance (HGG: 5.580; LGG: 5.436) indicated no statistical difference. The correlation between MSC and invasion based on the margins of gliomas showed an AUC of 0.903 and 0.911 for HGG and LGG, respectively. The mean Spearman correlation coefficient of the MSC versus the actual distance of invasion was -0.631 in gliomas.

CONCLUSION

The relatively low MSC on the blurred margins and irregular shape of gliomas may help in benign-malignant differentiation and invasion prediction of gliomas and has potential application for clinical judgment.

Diffusion Weighted Imaging in Neuro-Oncology: Diagnosis, Post-Treatment Changes, and Advanced Sequences-An Updated Review

DWI is an imaging technique commonly used for the assessment of acute ischemia, inflammatory disorders, and CNS neoplasia. It has several benefits since it is a quick, easily replicable sequence that is widely used on many standard scanners. In addition to its normal clinical purpose, DWI offers crucial functional and physiological information regarding brain neoplasia and the surrounding milieu. A narrative review of the literature was conducted based on the PubMed database with the purpose of investigating the potential role of DWI in the neuro-oncology field. A total of 179 articles were included in the study.

Noninvasive differentiation of molecular subtypes of adult non-enhancing glioma using MRI perfusion and diffusion parameters

Background

Nonenhancing glioma typically have a favorable outcome, but approximately 19–44% have a highly aggressive course due to a glioblastoma genetic profile. The aim of this retrospective study is to use physiological MRI parameters of both perfusion and diffusion to distinguish the molecular profiles of glioma without enhancement at presentation.

Methods

Ninety-nine patients with nonenhancing glioma were included, in whom molecular status (including 1p/19q codeletion status and IDH mutation) and preoperative MRI (T2w/FLAIR, dynamic susceptibility-weighted, and diffusion-weighted imaging) were available. Tumors were segmented semiautomatically using ITK-SNAP to derive whole tumor histograms of relative Cerebral Blood Volume (rCBV) and Apparent Diffusion Coefficient (ADC). Tumors were divided into three clinically relevant molecular profiles: IDH mutation (IDHmt) with (n = 40) or without (n = 41) 1p/19q codeletion, and (n = 18) IDH-wildtype (IDHwt). ANOVA, Kruskal-Wallis, and Chi-Square analyses were performed using SPSS.

Results

rCBV (mean, median, 75^th and 85^th percentile) and ADC (mean, median, 15^th and 25^th percentile) showed significant differences across molecular profiles (P < .01). Posthoc analyses revealed that IDHwt and IDHmt 1p/19q codeleted tumors showed significantly higher rCBV compared to IDHmt 1p/19q intact tumors: mean rCBV (mean, SD) 1.46 (0.59) and 1.35 (0.39) versus 1.08 (0.31), P < .05. Also, IDHwt tumors showed significantly lower ADC compared to IDHmt 1p/19q codeleted and IDHmt 1p/19q intact tumors: mean ADC (mean, SD) 1.13 (0.23) versus 1.27 (0.15) and 1.45 (0.20), P < .001).

Conclusions

A combination of low ADC and high rCBV, reflecting high cellularity and high perfusion respectively, separates IDHwt from in particular IDHmt 1p/19q intact glioma.

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.

Diffusion kurtosis imaging in evaluating gliomas: different region of interest selection methods on time efficiency, measurement repeatability, and diagnostic ability

OBJECTIVES

Comparing the diagnostic efficacy of diffusion kurtosis imaging (DKI) derived from different region of interest (ROI) methods in tumor parenchyma for grading and predicting IDH-1 mutation and 1p19q co-deletion status of glioma patients and correlating with their survival data.

METHODS

Sixty-six patients (29 females; median age, 45 years) with pathologically proved gliomas (low-grade gliomas, 36; high-grade gliomas, 30) were prospectively included, and their clinical data were collected. All patients underwent DKI examination. DKI maps of each metric were derived. Three groups of ROIs (ten spots, ROI-10s; three biggest tumor slices, ROI-3s; and whole-tumor parenchyma, ROI-whole) were manually drawn by two independent radiologists. The interobserver consistency, time spent, diagnostic efficacy, and survival analysis of DKI metrics based on these three ROI methods were analyzed.

RESULTS

The intraexaminer reliability for all parameters among these three ROI methods was good, and the time spent on ROI-10s was significantly less than that of the other two methods (p < 0.001). DKI based on ROI-10s demonstrated a slightly better diagnostic value than the other two ROI methods for grading and predicting the IDH-1 mutation status of glioma, whereas DKI metrics derived from ROI-10s performed much better than those of the ROI-3s and ROI-whole in identifying 1p19q co-deletion. In survival analysis, the model based on ROI-10s that included patient age and mean diffusivity showed the highest prediction value (C-index, 0.81).

CONCLUSIONS

Among the three ROI methods, the ROI-10s method had the least time spent and the best diagnostic value for a comprehensive evaluation of glioma. It is an effective way to process DKI data and has important application value in the clinical evaluation of glioma.

KEY POINTS

• The intraexaminer reliability for all DKI parameters among different ROI methods was good, and the time spent on ROI-10 spots was significantly less than the other two ROI methods. • DKI metrics derived from ROI-10 spots performed the best in ROI selection methods (ROI-10s, ten-spot ROIs; ROI-3s, three biggest tumor slices ROI; and ROI-whole, whole-tumor parenchyma ROI) for a comprehensive evaluation of glioma. • The ROI-10 spots method is an effective way to process DKI data and has important application value in the clinical evaluation of glioma.

The T2-FLAIR–mismatch sign as an imaging biomarker for IDH and 1p/19q status in diffuse low-grade gliomas: a systematic review with a Bayesian approach to evaluation of diagnostic test performance

OBJECTIVE

With the revised WHO 2016 classification of brain tumors, there has been increasing interest in imaging biomarkers to predict molecular status and improve the yield of genetic testing for diffuse low-grade gliomas (LGGs). The T2-FLAIR–mismatch sign has been suggested to be a highly specific radiographic marker of isocitrate dehydrogenase (IDH) gene mutation and 1p/19q codeletion status in diffuse LGGs. The presence of T2-FLAIR mismatch indicates a T2-hyperintense lesion that is hypointense on FLAIR with the exception of a hyperintense rim.

METHODS

In accordance with PRISMA guidelines, we performed a systematic review of the Ovid Medline, Embase, Scopus, and Cochrane databases for reports of studies evaluating the diagnostic performance of T2-FLAIR mismatch in predicting the IDH and 1p/19q codeletion status in diffuse LGGs. Results were combined into a 2 × 2 format, and the following diagnostic performance parameters were calculated: sensitivity, specificity, positive predictive value, negative predictive value, and positive (LR+) and negative (LR−) likelihood ratios. In addition, we utilized Bayes theorem to calculate posttest probabilities as a function of known pretest probabilities from previous genome-wide association studies and the calculated LRs. Calculations were performed for 1) IDH mutation with 1p/19q codeletion (IDHmut-Codel), 2) IDH mutation without 1p/19q codeletion (IDHmut-Noncodel), 3) IDH mutation overall, and 4) 1p/19q codeletion overall. The QUADAS-2 (revised Quality Assessment of Diagnostic Accuracy Studies) tool was utilized for critical appraisal of included studies.

RESULTS

A total of 4 studies were included, with inclusion of 2 separate cohorts from a study reporting testing and validation (n = 746). From pooled analysis of all cohorts, the following values were obtained for each molecular profile—IDHmut-Codel: sensitivity 30%, specificity 73%, LR+ 1.1, LR− 1.0; IDHmut-Noncodel: sensitivity 33.7%, specificity 98.5%, LR+ 22.5, LR− 0.7; IDH: sensitivity 32%, specificity 100%, LR+ 32.1, LR− 0.7; 1p/19q codeletion: sensitivity 0%, specificity 54%, LR+ 0.01, LR− 1.9. Bayes theorem was used to calculate the following posttest probabilities after a positive and negative result, respectively—IDHmut-Codel: 32.2% and 29.4%; IDHmut-Noncodel: 95% and 40%; IDH: 99.2% and 73.5%; 1p/19q codeletion: 0.4% and 35.1%.

CONCLUSIONS

The T2-FLAIR–mismatch sign was an insensitive but highly specific marker of IDH mutation and IDHmut-Noncodel profile, although significant exceptions may exist to this finding. Tumors with a positive sign may still be IDHwt or 1p/19q codeleted. These findings support the utility of T2-FLAIR mismatch as an imaging-based biomarker for positive selection of patients with IDH-mutant gliomas.

Advanced imaging parameters improve the prediction of diffuse lower-grade gliomas subtype, IDH mutant with no 1p19q codeletion: added value to the T2/FLAIR mismatch sign

OBJECTIVES

A combination of T2/FLAIR mismatch sign and advanced imaging parameters may improve the determination of molecular subtypes of diffuse lower-grade glioma. We assessed the diagnostic value of adding the apparent diffusion coefficient (ADC) and cerebral blood volume (CBV) to the T2/FLAIR mismatch sign for differentiation of the IDH mutation or 1p/19q codeletion.

MATERIALS AND METHODS

Preoperative conventional, diffusion-weighted, and dynamic susceptibility contrast imaging were performed on 110 patients with diffuse lower-grade gliomas. The study population was classified into three groups using molecular subtype, namely IDH mutation and 1p/19q codeletion (IDHmut-Codel), IDH wild type (IDHwt) and IDH mutation and no 1p/19q codeletion (IDHmut-Noncodel). T2/FLAIR mismatch sign and the histogram parameters of apparent diffusion coefficient (ADC) and normalised cerebral blood volume (nCBV) values were assessed. A multivariate logistic regression model was constructed to distinguish IDHmut-Noncodel from IDHmut-Codel and IDHwt and from IDHwt, and the performance was compared with that of single parameters using the area under the receiver operating characteristics curve (AUC).

RESULTS

Positive visual T2/FLAIR mismatch sign and higher nCBV skewness were significant variables to distinguish IDHmut-Noncodel from the other two groups (AUC, 0.88; 95% CI, 0.81-0.96). A lower ADC10 was a significant variable for distinguishing IDHmut-Noncodel from the IDHwt group (AUC, 0.75; 95% CI, 0.62-0.89). Adding ADC or CBV histogram parameters to T2/FLAIR mismatch sign improved performance in distinguishing IDHmut-Noncodel from the other two groups (AUC 0.882 vs. AUC 0.810) or from IDHwt (AUC 0.923 vs. AUC 0.868).

CONCLUSIONS

The combination of the T2/FLAIR mismatch sign with ADC or CBV histogram parameters can improve the identification of IDHmut-Noncodel diffuse lower-grade gliomas, which can be easily applied in clinical practice.

KEY POINTS

• The combination of the T2/FLAIR mismatch sign with the ADC or CBV histogram parameters can improve the identification of IDHmut-Noncodel diffuse lower-grade gliomas. • The multivariable model showed a significantly better performance for distinguishing the IDHmut-Noncodel group from other diffuse lower-grade gliomas than the T2/FLAIR mismatch sign alone or any single parameter. • The IDHmut-Noncodel type was associated with intermediate treatment outcomes; therefore, the identification of IDHmut-Noncodel diffuse lower-grade gliomas could be helpful for determining the clinical approach.

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.

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.

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.

Perfusion and diffusion MRI signatures in histologic and genetic subtypes of WHO grade II-III diffuse gliomas

The value of perfusion and diffusion-weighted MRI in differentiating histological subtypes according to the 2007 WHO glioma classification scheme (i.e. astrocytoma vs. oligodendroglioma) and genetic subtypes according to the 2016 WHO reclassification (e.g. 1p/19q co-deletion and IDH1 mutation status) in WHO grade II and III diffuse gliomas remains controversial. In the current study, we describe unique perfusion and diffusion MR signatures between histological and genetic glioma subtypes. Sixty-five patients with 2007 histological designations (astrocytomas and oligodendrogliomas), 1p/19q status (+ = intact/- = co-deleted), and IDH1 mutation status (MUT/WT) were included in this study. In all patients, median relative cerebral blood volume (rCBV) and apparent diffusion coefficient (ADC) were estimated within T2 hyperintense lesions. Bootstrap hypothesis testing was used to compare subpopulations of gliomas, separated by WHO grade and 2007 or 2016 glioma classification schemes. A multivariable logistic regression model was also used to differentiate between 1p19q⁺ and 1p19q^- WHO II-III gliomas. Neither rCBV nor ADC differed significantly between histological subtypes of pure astrocytomas and pure oligodendrogliomas. ADC was significantly different between molecular subtypes (p = 0.0016), particularly between IDH^WT and IDH^MUT/1p19q⁺ (p = 0.0013). IDH^MUT/1p19q⁺ grade III gliomas had higher median ADC; IDH^WT grade III gliomas had higher rCBV with lower ADC; and IDH^MUT/1p19q^- had intermediate rCBV and ADC values, similar to their grade II counterparts. A multivariable logistic regression model was able to differentiate between IDH^WT and IDH^MUT WHO II and III gliomas with an AUC of 0.84 (p < 0.0001, 74% sensitivity, 79% specificity). Within IDH^MUT WHO II-III gliomas, a separate multivariable logistic regression model was able to differentiate between 1p19q⁺ and 1p19q^- WHO II-III gliomas with an AUC of 0.80 (p = 0.0015, 64% sensitivity, 82% specificity). ADC better differentiated between genetic subtypes of gliomas according to the 2016 WHO guidelines compared to the classification scheme outlined in the 2007 WHO guidelines based on histological features of the tissue. Results suggest a combination of rCBV, ADC, T2 hyperintense volume, and presence of contrast enhancement together may aid in non-invasively identifying genetic subtypes of diffuse gliomas.

IDH mutant and 1p/19q co-deleted oligodendrogliomas: tumor grade stratification using diffusion-, susceptibility-, and perfusion-weighted MRI

Purpose

Currently, isocitrate dehydrogenase (IDH) mutation and 1p/19q co-deletion are proven diagnostic biomarkers for both grade II and III oligodendrogliomas (ODs). Non-invasive diffusion-weighted imaging (DWI), susceptibility-weighted imaging (SWI), and dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) are widely used to provide physiological information (cellularity, hemorrhage, calcifications, and angiogenesis) of neoplastic histology and tumor grade. However, it is unclear whether DWI, SWI, and DSC-PWI are able to stratify grades of IDH-mutant and 1p/19q co-deleted ODs.

Methods

We retrospectively reviewed the conventional MRI (cMRI), DWI, SWI, and DSC-PWI obtained on 33 patients with IDH-mutated and 1p/19q co-deleted ODs. Features of cMRI, normalized ADC (nADC), intratumoral susceptibility signals (ITSSs), normalized maxim CBV (nCBV), and normalized maximum CBF (nCBF) were compared between low-grade ODs (LGOs) and high-grade ODs (HGOs). Receiver operating characteristic curve and logistic regression were applied to determine diagnostic performances.

Results

HGOs tended to present with prominent edema and enhancement. nADC, ITSSs, nCBV, and nCBF were significantly different between groups (all P < 0.05). The combination of SWI and DSC-PWI for grading resulted in sensitivity and specificity of 100.00 and 93.33%, respectively.

Conclusions

IDH-mutant and 1p/19q co-deleted ODs can be stratified by grades using cMRI and advanced magnetic resonance imaging techniques including DWI, SWI, and DSC-PWI. Combined ITSSs with nCBV appear to be a promising option for grading molecularly defined ODs in clinical practice.

Genetically Defined Oligodendroglioma Is Characterized by Indistinct Tumor Borders at MRI

BACKGROUND AND PURPOSE

In 2016, the World Health Organization revised the brain tumor classification, making IDH mutation and 1p/19q codeletion the defining features of oligodendroglioma. To determine whether imaging characteristics previously associated with oligodendroglial tumors are still applicable, we evaluated the MR imaging features of genetically defined oligodendrogliomas.

MATERIALS AND METHODS

One hundred forty-eight adult patients with untreated World Health Organization grade II and III infiltrating gliomas with histologic oligodendroglial morphology, known 1p/19q status, and at least 1 preoperative MR imaging were retrospectively identified. The association of 1p/19q codeletion with tumor imaging characteristics and ADC values was evaluated.

RESULTS

Ninety of 148 (61%) patients had 1p/19q codeleted tumors, corresponding to genetically defined oligodendroglioma, and 58/148 (39%) did not show 1p/19q codeletion, corresponding to astrocytic tumors. Eighty-three of 90 (92%) genetically defined oligodendrogliomas had noncircumscribed borders, compared with 26/58 (45%) non-1p/19q codeleted tumors with at least partial histologic oligodendroglial morphology (P < .0001). Eighty-nine of 90 (99%) oligodendrogliomas were heterogeneous on T1- and/or T2-weighted imaging. In patients with available ADC values, a lower mean ADC value predicted 1p/19q codeletion (P = .0005).

CONCLUSIONS

Imaging characteristics of World Health Organization 2016 genetically defined oligodendrogliomas differ from the previously considered characteristics of morphologically defined oligodendrogliomas. We found that genetically defined oligodendrogliomas were commonly poorly circumscribed and were almost always heterogeneous in signal intensity.

Unravelling tumour heterogeneity using next-generation imaging: radiomics, radiogenomics, and habitat imaging

Tumour heterogeneity in cancers has been observed at the histological and genetic levels, and increased levels of intra-tumour genetic heterogeneity have been reported to be associated with adverse clinical outcomes. This review provides an overview of radiomics, radiogenomics, and habitat imaging, and examines the use of these newly emergent fields in assessing tumour heterogeneity and its implications. It reviews the potential value of radiomics and radiogenomics in assisting in the diagnosis of cancer disease and determining cancer aggressiveness. This review discusses how radiogenomic analysis can be further used to guide treatment therapy for individual tumours by predicting drug response and potential therapy resistance and examines its role in developing radiomics as biomarkers of oncological outcomes. Lastly, it provides an overview of the obstacles in these emergent fields today including reproducibility, need for validation, imaging analysis standardisation, data sharing and clinical translatability and offers potential solutions to these challenges towards the realisation of precision oncology.

A Bayesian spatial random effects model characterisation of tumour heterogeneity implemented using Markov chain Monte Carlo (MCMC) simulation

The focus of this study is the development of a statistical modelling procedure for characterising intra-tumour heterogeneity, motivated by recent clinical literature indicating that a variety of tumours exhibit a considerable degree of genetic spatial variability. A formal spatial statistical model has been developed and used to characterise the structural heterogeneity of a number of supratentorial primitive neuroectodermal tumours (PNETs), based on diffusion-weighted magnetic resonance imaging. Particular attention is paid to the spatial dependence of diffusion close to the tumour boundary, in order to determine whether the data provide statistical evidence to support the proposition that water diffusivity in the boundary region of some tumours exhibits a deterministic dependence on distance from the boundary, in excess of an underlying random 2D spatial heterogeneity in diffusion. Tumour spatial heterogeneity measures were derived from the diffusion parameter estimates obtained using a Bayesian spatial random effects model. The analyses were implemented using Markov chain Monte Carlo (MCMC) simulation. Posterior predictive simulation was used to assess the adequacy of the statistical model. The main observations are that the previously reported relationship between diffusion and boundary proximity remains observable and achieves statistical significance after adjusting for an underlying random 2D spatial heterogeneity in the diffusion model parameters. A comparison of the magnitude of the boundary-distance effect with the underlying random 2D boundary heterogeneity suggests that both are important sources of variation in the vicinity of the boundary. No consistent pattern emerges from a comparison of the boundary and core spatial heterogeneity, with no indication of a consistently greater level of heterogeneity in one region compared with the other. The results raise the possibility that DWI might provide a surrogate marker of intra-tumour genetic regional heterogeneity, which would provide a powerful tool with applications in both patient management and in cancer research.

Relative ADC and Location Differ between Posterior Fossa Pilocytic Astrocytomas with and without Gangliocytic Differentiation

BACKGROUND AND PURPOSE

Pilocytic astrocytomas, the most common posterior fossa tumors in children, are characterized by KIAA1549-BRAF fusions and shows excellent 5-year survival rates. Pilocytic astrocytoma with gangliocytic differentiation, a recently defined pilocytic astrocytoma variant that includes glial and neuronal elements similar to a ganglioglioma, may be distinguished from a classic ganglioglioma by molecular, radiologic, and histopathologic features. This study investigated whether imaging could distinguish posterior fossa pilocytic astrocytoma with and without gangliocytic differentiation.

MATERIALS AND METHODS

Preoperative MRIs (± CTs) of 41 children (age range, 7 months to 15 years; mean age, 7.3 ± 3.7 years; 58.5% male) with pilocytic astrocytoma with gangliocytic differentiation (n = 7) or pilocytic astrocytoma (n = 34) were evaluated; differences in tumor location, morphology, and minimum relative ADC between tumor types were compared (Wilcoxon rank sum test, Fisher exact test). Histopathology and BRAF fusion/mutation status were reviewed. Associations of progression-free survival with diagnosis, imaging features, and BRAF status were examined by Cox proportional hazards models.

RESULTS

Pilocytic astrocytoma with gangliocytic differentiation appeared similar to pilocytic astrocytoma but had lower minimum relative ADC (mean, 1.01 ± 0.17 compared with 2.01 ± 0.38 for pilocytic astrocytoma; P = .0005) and was more commonly located within midline structures (P = .0034). BRAF status was similar for both groups. Non-total resection (hazard ratio, 52.64; P = .0002), pilocytic astrocytoma with gangliocytic differentiation diagnosis (hazard ratio, 4.66; P = .0104), and midline involvement (hazard ratio, 3.32; P = .0433) were associated with shorter progression-free survival.

CONCLUSIONS

Minimum relative ADC and tumor location may be useful adjuncts to histopathology in differentiating pilocytic astrocytoma with gangliocytic differentiation from pilocytic astrocytoma. Shorter progression-free survival in pilocytic astrocytoma with gangliocytic differentiation is likely due to a propensity for involvement of midline structures and poor resectability.

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.

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.

Magnetic resonance diffusion metrics indexing high focal cellularity and sharp transition at the tumour boundary predict poor outcome in glioblastoma multiforme

AIM

To investigate the prognostic power of intra-tumoural and gradient magnetic resonance imaging (MRI) diffusion metrics in patients with glioblastoma multiforme (GBM).

MATERIALS AND METHODS

Forty-six consecutive patients with histologically confirmed GBM who had undergone preoperative diffusion tensor imaging at 3 T were included. Mean diffusivity (MD) and MD gradient maps were computed. Regions of interest were analysed to determine the minimum MD within the enhancing tumour (minMD). MD gradients were calculated along the enhancing tumour boundary and subjected to histogram analysis. Overall survival (OS) and time to progression (TTP) were derived and survival analysis was undertaken.

RESULTS

There were 31 deaths and 37 patients progressed during the study period. Multivariate survival analysis, controlling for treatment and gender, showed that minMD values<6.1×10(-4) mm(2)/s predicted shorter OS (hazard ratio [HR]=2.82, 1.25-6.34; p=0.012) and TTP (HR=5.43, 1.96-15.05; p=0.001). Higher MD gradient values of the tumour boundary predicted shorter survival: MD gradient values >4.7×10(-5) mm(2)/s (10(th) centile) had a significantly shorter OS with a HR of 0.43 (0.19-0.96; p=0.04). Similarly, a value above 1.4×10(-4) mm(2)/s (75(th) centile) was a significant predictor for shorter OS (HR=0.39, 0.17-0.89; p=0.03).

CONCLUSIONS

Lower minMD and higher MD gradient values for the 10(th) and 75(th) percentile of the tumour boundary demonstrated prognostic value in preoperative GBM. This suggests that MRI diffusion metrics indicative of higher focal cellularity and steeper transition from high cellular tumour edge to low cellular oedema define more aggressive glioblastoma subtypes with a poorer prognosis.

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.

Conventional and advanced (DTI/SWI) neuroimaging findings in pediatric oligodendroglioma

PURPOSE

Oligodendroglioma are rare pediatric brain tumors. The literature about neuroimaging findings is scant. A correct presurgical diagnosis is important to plan the therapeutic approach. Here, we evaluated the conventional and advanced neuroimaging features in our cohort of pediatric oligodendrogliomas and discuss our findings in the context of the current literature.

METHODS

Clinical histories were reviewed for tumor grading, neurologic manifestation, treatment, and clinical status at the last follow-up. Neuroimaging studies were retrospectively evaluated for tumor morphology and characteristics on conventional and advanced magnetic resonance imaging (MRI).

RESULTS

Five children with oligodendroglioma were included in this study. Four children were diagnosed with a low-grade oligodendroglioma. The location of the tumors included the frontal and temporal lobe in two cases each and the fronto-parietal lobe in one. In all oligodendrogliomas, tumor margins appeared sharp. In the high-grade oligodendroglioma, a cystic and partially hemorrhagic component was seen. In all children, the tumor showed a T1-hypointense and T2-hyperintense signal. The signal intensity on fluid attenuation inversion recovery (FLAIR) images was hyperintense in four and mixed hypo-hyperintense in one child. The anaplastic oligodendroglioma showed postcontrast enhancement and decreased diffusion while the low-grade oligodendrogliomas showed increased diffusion. One low-grade oligodendroglioma showed calcifications on susceptibility weighted imaging.

CONCLUSION

Conventional MRI findings of pediatric oligodendrogliomas are nonspecific. Advanced MRI sequences may differentiate (1) low-grade and high-grade pediatric oligodendrogliomas and (2) pediatric oligodendrogliomas and other brain tumors.

Imaging intratumor heterogeneity: role in therapy response, resistance, and clinical outcome

Tumors exhibit genomic and phenotypic heterogeneity, which has prognostic significance and may influence response to therapy. Imaging can quantify the spatial variation in architecture and function of individual tumors through quantifying basic biophysical parameters such as CT density or MRI signal relaxation rate; through measurements of blood flow, hypoxia, metabolism, cell death, and other phenotypic features; and through mapping the spatial distribution of biochemical pathways and cell signaling networks using PET, MRI, and other emerging molecular imaging techniques. These methods can establish whether one tumor is more or less heterogeneous than another and can identify subregions with differing biology. In this article, we review the image analysis methods currently used to quantify spatial heterogeneity within tumors. We discuss how analysis of intratumor heterogeneity can provide benefit over more simple biomarkers such as tumor size and average function. We consider how imaging methods can be integrated with genomic and pathology data, instead of being developed in isolation. Finally, we identify the challenges that must be overcome before measurements of intratumoral heterogeneity can be used routinely to guide patient care.

Imaging of brain tumors

Neuroimaging plays a crucial role in diagnosis of brain tumors and in the decision-making process for therapy. Functional imaging techniques can reflect cellular density (diffusion imaging), capillary density (perfusion techniques), and tissue biochemistry (magnetic resonance [MR] spectroscopy). In addition, cortical activation imaging (functional MR imaging) can identify various loci of eloquent cerebral cortical function. Combining these new tools can increase diagnostic specificity and confidence. Familiarity with conventional and advanced imaging findings facilitates accurate diagnosis, differentiation from other processes, and optimal patient treatment. This article is a practical synopsis of pathologic, clinical, and imaging spectra of most common brain tumors.

Diffusion-weighted MRI characteristics of the cerebral metastasis to brain boundary predicts patient outcomes

Background

Diffusion-weighted MRI (DWI) has been used in neurosurgical practice mainly to distinguish cerebral metastases from abscess and glioma. There is evidence from other solid organ cancers and metastases that DWI may be used as a biomarker of prognosis and treatment response. We therefore investigated DWI characteristics of cerebral metastases and their peritumoral region recorded pre-operatively and related these to patient outcomes.

Methods

Retrospective analysis of 76 cases operated upon at a single institution with DWI performed pre-operatively at 1.5T. Maps of apparent diffusion coefficient (ADC) were generated using standard protocols. Readings were taken from the tumor, peritumoral region and across the brain-tumor interface. Patient outcomes were overall survival and time to local recurrence.

Results

A minimum ADC greater than 919.4 × 10^-6 mm²/s within a metastasis predicted longer overall survival regardless of adjuvant therapies. This was not simply due to differences between the types of primary cancer because the effect was observed even in a subgroup of 36 patients with the same primary, non-small cell lung cancer. The change in diffusion across the tumor border and into peritumoral brain was measured by the “ADC transition coefficient” or ATC and this was more strongly predictive than ADC readings alone. Metastases with a sharp change in diffusion across their border (ATC >0.279) showed shorter overall survival compared to those with a more diffuse edge. The ATC was the only imaging measurement which independently predicted overall survival in multivariate analysis (hazard ratio 0.54, 95% CI 0.3 – 0.97, p = 0.04).

Conclusions

DWI demonstrates changes in the tumor, across the tumor edge and in the peritumoral region which may not be visible on conventional MRI and this may be useful in predicting patient outcomes for operated cerebral metastases.

Isocitrate dehydrogenase mutation is associated with tumor location and magnetic resonance imaging characteristics in astrocytic neoplasms

The molecular subsets of glioma behave in biologically distinct ways. The present study detected isocitrate dehydrogenase (IDH) 1 and IDH2 mutations in glioma to analyze whether IDH-mutated gliomas are situated in certain preferential areas and to investigate their correlation with magnetic resonance imaging (MRI) characteristics. A series of 193 patients with astrocytic neoplasms (111 diffuse and 82 anaplastic astrocytomas), grouped according to prelabeled anatomical structures and the risk of surgery, were retrospectively reviewed for IDH1 and IDH2 mutations to compare the tumor location and MRI features. A total of 111 IDH1 mutations at codon 132 (57.5%) and six IDH2 mutations at codon 172 (3.1%) were detected. The IDH1/2 mutations were found to predict longer survival, independent of the histological type in this series of patients. The IDH-mutated gliomas were predominantly located in a single lobe, such as the frontal lobe, temporal lobe or cerebellum and rarely in the diencephalon or brain stem. Furthermore, according to the risk of surgery, the IDH-mutated tumors were rarely located in the high-risk regions of the brain, where surgery exhibits a high mortality rate intraoperatively and postoperatively. In addition, gliomas with IDH mutations were significantly more likely to exhibit a unilateral pattern of growth, sharp tumor margins, homogeneous signal intensity and less contrast enhancement on MRI. The results of the current study suggested that the prolonged survival of patients with IDH-mutated gliomas is primarily due to a less aggressive biological behavior according to tumor site and MRI features.

Can diffusion tensor imaging noninvasively detect IDH1 gene mutations in astrogliomas? A retrospective study of 112 cases

BACKGROUND AND PURPOSE

IDH1 mutational status probably plays an important role in the predictive response for patients with astroglioma. This study explores whether DTI metrics are able to noninvasively detect IDH1 status in astrogliomas.

MATERIALS AND METHODS

The DTI data of 112 patients with pathologically proven astroglioma (including 25, 12, and 10 cases with IDH1 mutation and 11, 11, and 43 cases without mutation in grades II, III, and IV, respectively) were retrospectively reviewed. The maximal fractional anisotropy, minimal ADC, ratio of maximal fractional anisotropy, and ratio of minimal ADC in the tumor body were measured. In the same World Health Organization grading, the imaging parameters of patients with and without IDH1 R132H mutation were compared by means of optimal metrics for detecting mutations. Receiver operating characteristic curve analysis was performed.

RESULTS

The maximal fractional anisotropy and ratio of maximal fractional anisotropy values had statistical significance between patients with IDH1 R132H mutation and those without mutation in astrogliomas of grades II and III. The areas under the curve for maximal fractional anisotropy and ratio of maximal fractional anisotropy were both 0.92 in grade II and 0.80 and 0.82 in grade III. The minimal ADC value and ratio of minimal ADC value also demonstrated statistical significance between patients with mutation and those without mutation in all astroglioma grades. The areas under the curve for minimal ADC were 0.94 (II), 0.76 (III), and 0.66 (IV), and the areas under the curve for ratio of minimal ADC were 0.93 (II), 0.83 (III), and 0.70 (IV).

CONCLUSIONS

Fractional anisotropy and ADC from DTI can noninvasively detect IDH1 R132H mutation in astrogliomas.

The reliability of routine clinical post-processing software in assessing potential diffusion-weighted MRI "biomarkers" in brain metastases

BACKGROUND AND PURPOSE

Diffusion MRI characteristics have been used as biomarkers to guide prognosis in cerebral pathologies including brain metastases. The measurement of ADC is often described poorly in clinical and research studies with little detail given to the practical considerations of where to place ROIs, which post processing software package to use and how reproducible the resulting metrics will be.

METHOD

We investigated a series of 12 patients with brain metastases and preoperative DWI. Three post processing platforms were used. ROI were placed over the tumour, peritumoural region and across the brain-tumour interface. These recordings were made by a neurosurgeon and a neuroradiologist. Inter-intra-observer variability was assessed using Bland-Altman analysis. An exploratory analysis of DWI with overall survival and tumour type was made.

RESULTS

There was excellent correlation between the software packages used for all measures including assessing the whole tumour, selective regions with lowest ADC, the change of ADC across the brain-tumour interface and the relation of the tumour ADC to peritumoural regions and the normal white matter. There was no significant inter- or intra-observer variability for repeated readings. There were significant differences in the mean values obtained using different methodologies and different metrics had differing relationships to overall survival and primary tumour of origin.

CONCLUSION

Diffusion weighted MRI metrics offer promise as potential non-invasive biomarkers in brain metastases and a variety of metrics have been shown to be reliably measured using differing platforms and observers.

Contrast enhancement in 1p/19q-codeleted anaplastic oligodendrogliomas is associated with 9p loss, genomic instability, and angiogenic gene expression

BACKGROUND

The aim of this study was to correlate MRI features and molecular characteristics in anaplastic oligodendrogliomas (AOs).

METHODS

The MRI characteristics of 50 AO patients enrolled in the French national network for high-grade oligodendroglial tumors were analyzed. The genomic profiles and IDH mutational statuses were assessed using high-resolution single-nucleotide polymorphism arrays and direct sequencing, respectively. The gene expression profiles of 25 1p/19q-codeleted AOs were studied on Affymetrix expression arrays.

RESULTS

Most of the cases were frontal lobe contrast-enhanced tumors (52%), but the radiological presentations of these cases were heterogeneous, ranging from low-grade glioma-like aspects (26%) to glioblastoma-like aspects (22%). The 1p/19q codeletion (n = 39) was associated with locations in the frontal lobe (P = .001), with heterogeneous intratumoral signal intensities (P = .003) and with no or nonmeasurable contrast enhancements (P = .01). The IDH wild-type AOs (n = 7) more frequently displayed ringlike contrast enhancements (P = .03) and were more frequently located outside of the frontal lobe (P = .01). However, no specific imaging pattern could be identified for the 1p/19q-codeleted AO or the IDH-mutated AO. Within the 1p/19q-codeleted AO, the contrast enhancement was associated with larger tumor volumes (P = .001), chromosome 9p loss and CDKN2A loss (P = .006), genomic instability (P = .03), and angiogenesis-related gene expression (P < .001), particularly for vascular endothelial growth factor A and angiopoietin 2.

CONCLUSION

In AOs, the 1p/19q codeletion and the IDH mutation are associated with preferential (but not with specific) imaging characteristics. Within 1p/19q-codeleted AO, imaging heterogeneity is related to additional molecular alterations, especially chromosome 9p loss, which is associated with contrast enhancement and larger tumor volume.

Metrics and textural features of MRI diffusion to improve classification of pediatric posterior fossa tumors

BACKGROUND AND PURPOSE

Qualitative radiologic MR imaging review affords limited differentiation among types of pediatric posterior fossa brain tumors and cannot detect histologic or molecular subtypes, which could help to stratify treatment. This study aimed to improve current posterior fossa discrimination of histologic tumor type by using support vector machine classifiers on quantitative MR imaging features.

MATERIALS AND METHODS

This retrospective study included preoperative MRI in 40 children with posterior fossa tumors (17 medulloblastomas, 16 pilocytic astrocytomas, and 7 ependymomas). Shape, histogram, and textural features were computed from contrast-enhanced T2WI and T1WI and diffusivity (ADC) maps. Combinations of features were used to train tumor-type-specific classifiers for medulloblastoma, pilocytic astrocytoma, and ependymoma types in separation and as a joint posterior fossa classifier. A tumor-subtype classifier was also produced for classic medulloblastoma. The performance of different classifiers was assessed and compared by using randomly selected subsets of training and test data.

RESULTS

ADC histogram features (25th and 75th percentiles and skewness) yielded the best classification of tumor type (on average >95.8% of medulloblastomas, >96.9% of pilocytic astrocytomas, and >94.3% of ependymomas by using 8 training samples). The resulting joint posterior fossa classifier correctly assigned >91.4% of the posterior fossa tumors. For subtype classification, 89.4% of classic medulloblastomas were correctly classified on the basis of ADC texture features extracted from the Gray-Level Co-Occurence Matrix.

CONCLUSIONS

Support vector machine-based classifiers using ADC histogram features yielded very good discrimination among pediatric posterior fossa tumor types, and ADC textural features show promise for further subtype discrimination. These findings suggest an added diagnostic value of quantitative feature analysis of diffusion MR imaging in pediatric neuro-oncology.

Imaging in sepsis-associated encephalopathy--insights and opportunities

Sepsis-associated encephalopathy (SAE) refers to a clinical spectrum of acute neurological dysfunction that arises in the context of sepsis. Although the pathophysiology of SAE is incompletely understood, it is thought to involve endothelial activation, blood-brain barrier leakage, inflammatory cell migration, and neuronal loss with neurotransmitter imbalance. SAE is associated with a high risk of mortality. Imaging studies using MRI and CT have demonstrated changes in the brains of patients with SAE that are also seen in disorders such as stroke. Next-generation imaging techniques such as magnetic resonance spectroscopy, diffusion tensor imaging and PET, as well as experimental imaging modalities, provide options for early identification of patients with SAE, and could aid in identification of pathophysiological processes that represent possible therapeutic targets. In this Review, we explore the recent literature on imaging in SAE, relating the findings of these studies to pathological data and experimental studies to obtain insights into the pathophysiology of sepsis-associated neurological dysfunction. Furthermore, we suggest how novel imaging technologies can be used for early-stage proof-of-concept and proof-of-mechanism translational studies, which may help to improve diagnosis in SAE.

Common pediatric cerebellar tumors: correlation between cell densities and apparent diffusion coefficient metrics

PURPOSE

To test whether there is correlation between cell densities and apparent diffusion coefficient (ADC) metrics of common pediatric cerebellar tumors.

MATERIALS AND METHODS

This study was reviewed for issues of patient safety and confidentiality and was approved by the Institutional Review Board of the University of Texas Southwestern Medical Center and was compliant with HIPAA. The need for informed consent was waived. Ninety-five patients who had preoperative magnetic resonance imaging and surgical pathologic findings available between January 2003 and June 2011 were included. There were 37 pilocytic astrocytomas, 34 medulloblastomas (23 classic, eight desmoplastic-nodular, two large cell, one anaplastic), 17 ependymomas (13 World Health Organization [WHO] grade II, four WHO grade III), and seven atypical teratoid rhabdoid tumors. ADCs of solid tumor components and normal cerebellum were measured. Tumor-to-normal brain ADC ratios (hereafter, ADC ratio) were calculated. The medulloblastomas and ependymomas were subcategorized according to the latest WHO classification, and tumor cellularity was calculated. Correlation was sought between cell densities and mean tumor ADCs, minimum tumor ADCs, and ADC ratio.

RESULTS

When all tumors were considered together, negative correlation was found between cellularity and mean tumor ADCs (ρ = -0.737, P < .05) and minimum tumor ADCs (ρ = -0.736, P < .05) of common pediatric cerebellar tumors. There was no correlation between cellularity and ADC ratio. Negative correlation was found between cellularity and minimum tumor ADC in atypical teratoid rhabdoid tumors (ρ = -0.786, P < .05). In atypical teratoid rhabdoid tumors, no correlation was found between cellularity and mean tumor ADC and ADC ratio. There was no correlation between the ADC metrics and cellularity of the pilocytic astrocytomas, medulloblastomas, and ependymomas.

CONCLUSION

Negative correlation was found between cellularity and ADC metrics of common pediatric cerebellar tumors. Although ADC metrics are useful in the preoperative diagnosis of common pediatric cerebellar tumors and this utility is generally attributed to differences in cellularity of tumors, tumor cellularity may not be the sole determinant of the differences in diffusivity.

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.

Survival analysis for apparent diffusion coefficient measures in children with embryonal brain tumours

Embryonal brain tumors constitute a large and important subgroup of pediatric brain tumors. Apparent diffusion coefficient (ADC) measures have been previously used in the analysis of these tumors. We investigated a newly described ADC-derived parameter, the apparent transient coefficient in tumor (ATCT), a measure of the gradient change of ADC from the peri-tumoral edema into the tumor core, to study whether ATCT correlates with survival outcome. Sixty-one patients with histologically proven embryonal brain tumors and who had diffusion-weighted imaging (DWI) as part of their clinical imaging were enrolled in a retrospective study correlating ADC measures with survival. Kaplan-Meier survival curves were constructed for extent of surgical resection, age <3 years at diagnosis, tumor type, and metastasis at presentation. A multivariate survival analysis was performed that took into consideration ATCT and variables found to be significant in the Kaplan-Meier analysis as covariates. Results from the multivariate analysis showed that ATCT was the only significant covariate (P < .001). Survival analysis using Kaplan-Meier curves, dividing the patients into 4 groups of increasing values of ATCT, showed that more negative values of ATCT were significantly associated with a poorer prognosis (P < .001). A statistically significant difference was observed for survival data with respect to the change in ADC from edema into the tumor volume. Results show that more negative ATCT values are significantly associated with a poorer survival among children with embryonal brain tumors, irrespective of tumor type, extent of resection, age <3 years at diagnosis, and metastasis at presentation.

Utility of apparent diffusion coefficient ratios in distinguishing common pediatric cerebellar tumors

RATIONALE AND OBJECTIVES

The aim of this study was to identify clinically useful tumor/normal brain apparent diffusion coefficient (ADC) ratios for distinguishing common pediatric cerebellar tumors.

MATERIALS AND METHODS

Review of medical records revealed 79 patients with cerebellar tumors who underwent preoperative magnetic resonance imaging, including diffusion-weighted imaging sequences, and surgery. There were 31 pilocytic astrocytomas, 27 medulloblastomas, 14 ependymomas, and seven atypical teratoid/rhabdoid tumors. ADC values were measured by placing regions of interest on the solid tumor and normal brain parenchyma by two reviewers. Tumor/normal brain ADC ratios were calculated.

RESULTS

Mean ADC values of the pilocytic astrocytomas were greater than those of ependymomas, whose mean ADC values were greater than those of medulloblastomas and atypical teratoid/rhabdoid tumors. Using a tumor/normal brain ADC ratio threshold of 1.70 to distinguish pilocytic astrocytomas from ependymomas, sensitivity of 92% and specificity of 79% were achieved. A tumor/normal brain ADC ratio threshold of 1.20 enabled the sorting of ependymomas from medulloblastomas with sensitivity of 93% and specificity of 88%.

CONCLUSIONS

Tumor/normal brain ADC ratios allow the distinguishing of common pediatric cerebellar tumors.

Multiparametric characterization of grade 2 glioma subtypes using magnetic resonance spectroscopic, perfusion, and diffusion imaging

BACKGROUND AND PURPOSE

The purpose of this study was to derive quantitative parameters from magnetic resonance (MR) spectroscopic, perfusion, and diffusion imaging of grade 2 gliomas according to the World Health Organization and to investigate how these multiple imaging modalities can contribute to evaluating their histologic subtypes and spatial characteristics.

MATERIALS AND METHODS

MR spectroscopic, perfusion, and diffusion images from 56 patients with newly diagnosed grade 2 glioma (24 oligodendrogliomas, 18 astrocytomas, and 14 oligoastrocytomas) were retrospectively studied. Metabolite intensities, relative cerebral blood volume (rCBV), and apparent diffusion coefficient (ADC) were statistically evaluated.

RESULTS

The 75th percentile rCBV and median ADC were significantly different between oligodendrogliomas and astrocytomas (P < .0001) and between oligodendrogliomas and oligoastrocytomas (P < .001). Logistic regression analysis identified both 75th percentile rCBV and median ADC as significant variables in the differentiation of oligodendrogliomas from astrocytomas and oligoastrocytomas. Group differences in metabolite intensities were not significant, but there was a much larger variation in the volumes and maximum values of metabolic abnormalities for patients with oligodendroglioma compared with the other tumor subtypes.

CONCLUSIONS

Perfusion and diffusion imaging provide quantitative MR parameters that can help to differentiate grade 2 oligodendrogliomas from grade 2 astrocytomas and oligoastrocytomas. The large variations in the magnitude and spatial extent of the metabolic lesions between patients and the fact that their values are not correlated with the other imaging parameters indicate that MR spectroscopic imaging may provide complementary information that is helpful in targeting therapy, evaluating residual disease, and assessing response to 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.

MR imaging characteristics of oligodendroglial tumors with assessment of 1p/19q deletion status

PURPOSE

Patients with oligodendrogliomas with allelic loss of chromosomal arm 1p and 19q have been shown, especially with anaplastic oligodendrogliomas, to have both a better initial and long-term response to chemotherapy as well as an improved overall survival. Effective treatment of patients with brain tumors requires accurate diagnostic techniques. MR imaging can be used to help differentiate between low- and high-grade tumors. We hypothesize that certain MR imaging characteristics can be used to differentiate between patients with and without 1p and 19q deletion.

METHODS

Using the clinical database at the University of Virginia Neuro-Oncology Center, we identified adult patients with grade II and III oligodendroglial tumors who underwent treatment from 2002 to 2007. Age at diagnosis, gender, tumor grade, chromosomal deletion status, duration of follow-up, and MR imaging characteristics were analyzed; the latter was read by a blinded neuroradiologist.

RESULTS

One hundred and four patients met the inclusion criteria. Of these patients, 44 manifested 1p/19q co-deletion and 60 patients lacked this deletion. The greatest cross-sectional area (mean) of the tumor measured 23.4 cm(2) for patients with the co-deletion and 31.7 cm(2) for patients with intact alleles (p = 0.008). In addition, inner table thinning was noted directly adjacent to seven tumors with intact 1p and 19q alleles and in no tumors with the 1p/19q co-deletion (p = 0.020). Amongst patients with pure oligodendrogliomas, those with 1p/19q co-deletion had tumors more often confined to a single lobe as compared with those patients without the co-deletion (p = 0.023). Finally, tumors with intact alleles were more often found in the temporal lobe (45.0%) as compared with co-deleted tumors (22.7%) (p = 0.011).

CONCLUSION

MR imaging is a valuable imaging modality for differentiating between oligodendrogliomas with or without the 1p/19q deletion. While imaging will never replace definitive tissue diagnosis, imaging characteristics such as tumor size, location, and overlying skull thinning can assist clinicians in assessing patients with oligodendroglial tumors prior to surgical or medical intervention.

Advances in imaging low-grade gliomas

Imaging plays a key role in the management of low-grade gliomas. The traditional view of these tumours as non-enhancing areas of increased signal on T2-weighted imaging is now accepted as being incorrect. Using new MR and PET techniques that can probe the pathological changes with in these tumours by assessing vascularity (perfusion MR), cellularity and infiltration (diffusion weighted and diffusion tensor MR), metabolism (MR spectroscopy and FDG PET) and proliferation (MR spectroscopy, methionine PET and 18F-fluorothymidine FLT PET). These tools will allow improvements in tumour grading, biopsy/therapy guidance and earlier assessment of the response to therapy.

Cellularity and apparent diffusion coefficient in oligodendroglial tumours characterized by genotype

PURPOSE

Apparent diffusion coefficient (ADC) describes water diffusion within tissues. Previous studies report a negative linear correlation between minimum ADC and tumour cellularity in different types of gliomas, but there are no studies in oligodendroglial tumours. This study evaluated the relationship between ADC and tumour cellularity in oligodendroglial tumours characterized by genotype.

METHODS

ADC was assessed in 17 patients with known 1p/19q status: 3 grade II oligodendrogliomas (OII), 9 grade II oligoastrocytomas (OAII), 5 grade III oligoastrocytomas (OAIII). Regions of interest were placed on ADC maps around tumour margins to generate mean tumour ADC, and over minimum and maximum tumour ADC. Histopathology assessment of tumour cellularity determined minimum, maximum and mean cell density in serial stereotactic biopsies.

RESULTS

1p/19q loss was present in 2/3 OII, 5/9 OAII, 2/5 OAIII. Grade III tumours had higher maximum cell density than grade II tumours (17.2 vs. 10.57%: Mann Whitney U; P = 0.20). Oligoastrocytoma were more likely to have a lower minimum cell density than oligodendrogliomas (Mann Whitney U; P = 0.032). There was no relationship between cell density and genotype. There was no linear correlation between mean ADC and mean cell density (Spearman's rho; r = 0.486: P = 0.438), minimum ADC and maximum cell density (Spearman's rho; r = 0.158: P = 0.660), and maximum ADC and minimum cell density (Spearman's rho; r = 0.039: P = 0.985).

CONCLUSIONS

In oligodendroglial tumours there is no relationship between quantitative assessment of cellularity and ADC. This may reflect differences in oligodendroglial tumour biology compared to other gliomas, although the composition of the extracellular matrix may influence ADC more than cellularity.

Integration of preoperative anatomic and metabolic physiologic imaging of newly diagnosed glioma

PURPOSE

To integrate standard anatomic magnetic resonance imaging in conjunction with uniformly acquired physiologic imaging biomarkers of untreated glioma with different histological grades with the goal of generating an algorithm that can be applied for patient management.

METHODS

A total of 143 patients with previously untreated glioma were scanned immediately before surgical resection using conventional anatomical MR imaging, and with uniform acquisition of perfusion-weighted imaging, diffusion-weighted imaging, and proton MR spectroscopic imaging. Regions of interest corresponding to anatomic and metabolic lesions were identified to assess tumor burden. MR parameters that had been found to be predictive of survival in patients with grade IV glioma were evaluated as a function of tumor grade and histological sub-type. Based on these finding both anatomic and physiologic imaging parameters were then integrated to generate an algorithm for management of patients with newly diagnosed presumed glioma.

RESULTS

Histological analysis indicated that the population comprised 56 patients with grade II, 31 with grade III, and 56 with grade IV glioma. Based on standard anatomic imaging, the presence of hypointense necrotic regions in post-Gadolinium T1-weighted images and the percentage of the T2 hyperintense lesion that was either enhancing or necrotic were effective in identifying patients with grade IV glioma. The individual parameters of diffusion and perfusion parameters were significantly different for patients with grade II astrocytoma versus oligodendroglioma sub-types. All tumors had regions with elevated choline to N-acetylasparate index (CNI). Lactate was higher for grade III and grade IV glioma and lipid was significantly elevated for grade IV glioma. These results were integrated into a proposed management algorithm for newly diagnosed glioma that will need to be prospectively tested in future studies.

CONCLUSION

Metabolic and physiologic imaging characteristics provide information about tumor heterogeneity that may be important for assisting the surgeon to ensure acquisition of representative histology. Correlation of these integrated MR parameters with clinical features will need to be assessed with respect to their role in predicting outcome and stratifying patients into risk groups for clinical trials. Future studies will use image directed tissue sampling to confirm the biological interpretation of these parameters and to assess how they change in response to therapy.

Malignant glioblastomatous transformation of a low-grade glioma in a child

BACKGROUND

The term of low-grade glioma addresses a favorable clinical outcome with indolent histological features in general consideration; however, recent studies underline the inconsistency, which originates from the accumulation of different histologic subtypes in this terminology. The malignant transformation of a low-grade glioma is unusual but presents a poor prognosis.

CASE HISTORY

We report a case of a 12-year-old boy, who was referred for complaints of recurrent seizures. His physical examination was unremarkable, but it was learned that a peripheral mass lesion located on the left posterior parietal lobe--which had been thought to be a low-grade glioma--had been detected on a magnetic resonance imaging 2 years ago at a different hospital. The patient was then treated with valproate and carbamazepine for the seizures and advised to be followed up without any additional diagnostic and therapeutic studies for his suspected low-grade glioma. A recent magnetic resonance imaging study showed enlargements of the mass and surrounding edema with additional necrosis. Surgical excision of the tumor was performed. After the diagnosis of glioblastoma multiforme, the patient received radiation therapy and chemotherapy with a good clinical recovery without any evidence of residue or recurrence at 12-month follow-up.

CONCLUSION

The first line treatment modality in the management of low-grade glioma--especially in suitable patients--is clearly surgery. The gross total resection guarantees the distinguishing of the histological types of the low-grade gliomas and reflects the biologic behavior of these tumors. Observation without surgery must be reserved for selected inoperable cases.

The use of magnetic resonance imaging to noninvasively detect genetic signatures in oligodendroglioma

BACKGROUND

Some patients with low-grade glioma have extraordinarily long survival times; current, early treatment does not prolong their lives. For this reason, therapies that sometimes have neurologic side effects are often deferred intentionally.

METHODS

In a study of oligodendrogliomas, we used a quantitative method of MR analysis based on the S-transform to investigate whether codeletion of chromosomes 1p and 19q, a marker of good prognosis, could be predicted accurately by measuring image texture.

RESULTS

Differences in texture were seen between tumors with codeletion of chromosomes 1p and 19q and those with intact 1p and 19q alleles on contrast-enhanced T1-weighted and T2-weighted MR images. Quantitative MR texture on T2 images predicted codeletion of chromosomes 1p and 19q with high sensitivity and specificity.

CONCLUSIONS

This new method of MR image interpretation may have the potential to augment the diagnostic assessment of patients with suspected low-grade glioma.