Serial analysis of imaging parameters in patients with newly diagnosed glioblastoma multiforme

Longitudinal MR spectroscopy to detect progression in patients with lower-grade glioma in the surveillance phase

Background

Monitoring lower-grade gliomas (LrGGs) for disease progression is made difficult by the limits of anatomical MRI to distinguish treatment related tissue changes from tumor progression. MR spectroscopic imaging (MRSI) offers additional metabolic information that can help address these challenges. The goal of this study was to compare longitudinal changes in multiparametric MRI, including diffusion weighted imaging, perfusion imaging, and 3D MRSI, for LrGG patients who progressed at the final time-point and those who remained clinically stable.

Methods

Forty-one patients with LrGG who were clinically stable were longitudinally assessed for progression. Changes in anatomical, diffusion, perfusion and MRSI data were acquired and compared between patients who remained clinically stable and those who progressed.

Results

Thirty-one patients remained stable, and 10 patients progressed. Over the study period, progressed patients had a significantly greater increase in normalized choline, choline-to-N-acetylaspartic acid index (CNI), normalized creatine, and creatine-to-N-acetylaspartic acid index (CRNI), than stable patients. CRNI was significantly associated with progression status and WHO type. Progressed astrocytoma patients had greater increases in CRNI than stable astrocytoma patients.

Conclusions

LrGG patients in surveillance with tumors that progressed had significantly increasing choline and creatine metabolite signals on MRSI, with a trend of increasing T2 FLAIR volumes, compared to LrGG patients who remained stable. These data show that MRSI can be used in conjunction with anatomical imaging studies to gain a clearer picture of LrGG progression, especially in the setting of clinical ambiguity.

Perfusion MR prior to radiotherapy is a strong predictor of survival in high-grade gliomas after proton and carbon ion radiotherapy

Background

To assess the survival predictability of perfusion magnetic resonance imaging (MRI) by the normalized cerebral blood volume (nCBV) prior to particle beam radiotherapy (PBRT) in high-grade glioma (HGG) patients underwent particle therapy.

Methods

The study retrieved dynamic susceptibility contrast MRI acquired prior to PBRT between 6/2015 and 3/2019 in 45 patients with HGG. Maximum nCBV (nCBVmax) within or adjacent to surgical/tumor bed was measured using 'hot-spot' method. The predictive values of nCBVmax for progression-free survival (PFS) and overall survival (OS) were assessed in univariate Kaplan-Meier curve and multivariate Cox proportional hazards (CPH) models. Nomograms based on CPH results were constructed to individualize the predicted probability of OS and PFS.

Results

The Kaplan-Meier curves and all CPH models based on nCBVmax as continuous variable (nCBVmax-C), group by cut-off derived from median value and Youden-index method showed that nCBVmax prior to radiotherapy was a strong predictor for both PFS and OS in HGG patients who underwent PBRT. Nomograms built on CPH models showed similar excellent performance in both discrimination and calibration.

Conclusions

Perfusion imaging prior to PBRT is a strong predictor of survival in HGG. Novel perfusion MR-based nomogram with prospective validation could potentially be formally used in future clinical practice to individualize survival probability.

Assessment of higher-order singular value decomposition denoising methods on dynamic hyperpolarized [1-13C]pyruvate MRI data from patients with glioma

BACKGROUND

Real-time metabolic conversion of intravenously-injected hyperpolarized [1-13C]pyruvate to [1-13C]lactate and [13C]bicarbonate in the brain can be measured using dynamic hyperpolarized carbon-13 (HP-13C) MRI. However, voxel-wise evaluation of metabolism in patients with glioma is challenged by the limited signal-to-noise ratio (SNR) of downstream 13C metabolites, especially within lesions. The purpose of this study was to evaluate the ability of higher-order singular value decomposition (HOSVD) denoising methods to enhance dynamic HP [1-13C]pyruvate MRI data acquired from patients with glioma.

METHODS

Dynamic HP-13C MRI were acquired from 14 patients with glioma. The effects of two HOSVD denoising techniques, tensor rank truncation-image enhancement (TRI) and global-local HOSVD (GL-HOSVD), on the SNR and kinetic modeling were analyzed in [1-13C]lactate data with simulated noise that matched the levels of [13C]bicarbonate signals. Both methods were then evaluated in patient data based on their ability to improve [1-13C]pyruvate, [1-13C]lactate and [13C]bicarbonate SNR. The effects of denoising on voxel-wise kinetic modeling of kPL and kPB was also evaluated. The number of voxels with reliable kinetic modeling of pyruvate-to-lactate (kPL) and pyruvate-to-bicarbonate (kPB) conversion rates within regions of interest (ROIs) before and after denoising was then compared.

RESULTS

Both denoising methods improved metabolite SNR and regional signal coverage. In patient data, the average increase in peak dynamic metabolite SNR was 2-fold using TRI and 4-5 folds using GL-HOSVD denoising compared to acquired data. Denoising reduced kPL modeling errors from a native average of 23% to 16% (TRI) and 15% (GL-HOSVD); and kPB error from 42% to 34% (TRI) and 37% (GL-HOSVD) (values were averaged voxelwise over all datasets). In contrast-enhancing lesions, the average number of voxels demonstrating within-tolerance kPL modeling error relative to the total voxels increased from 48% in the original data to 84% (TRI) and 90% (GL-HOSVD), while the number of voxels showing within-tolerance kPB modeling error increased from 0% to 15% (TRI) and 8% (GL-HOSVD).

CONCLUSION

Post-processing denoising methods significantly improved the SNR of dynamic HP-13C imaging data, resulting in a greater number of voxels satisfying minimum SNR criteria and maximum kinetic modeling errors in tumor lesions. This enhancement can aid in the voxel-wise analysis of HP-13C data and thereby improve monitoring of metabolic changes in patients with glioma following treatment.

Intravoxel incoherent motion (IVIM) modeling of diffusion MRI during chemoradiation predicts therapeutic response in IDH wildtype glioblastoma

Background:

Prediction of early progression in glioblastoma may provide an opportunity to personalize treatment. Simplified intravoxel incoherent motion (IVIM) MRI offers quantitative estimates of diffusion and perfusion metrics. We investigated whether these metrics, during chemoradiation, could predict treatment outcome.

Methods:

38 patients with newly diagnosed IDH-wildtype glioblastoma undergoing 6-week/30-fraction chemoradiation had standardized post-operative MRIs at baseline (radiation planning), and at the 10th and 20th fractions. Non-overlapping T1-enhancing (T1C) and non-enhancing T2-FLAIR hyperintense regions were independently segmented. Apparent diffusion coefficient (ADC_T1C, ADC_T2-FLAIR) and perfusion fraction (f_T1C, f_T2-FLAIR) maps were generated with simplified IVIM modelling. Parameters associated with progression before or after 6.9 months (early vs late progression, respectively), overall survival (OS) and progression-free survival (PFS) were investigated.

Results:

Higher ADC_T2-FLAIR at baseline [Odds Ratio (OR) = 1.06, 95% CI 1.01–1.15, p = 0.025], lower f_T2-FLAIR at fraction 10 (OR = 2.11, 95% CI 1.04–4.27, p = 0.018), and lack of increase in ADC_T2-FLAIR at fraction 20 compared to baseline (OR = 1.12, 95% CI 1.02–1.22, p = 0.02) were associated with early progression. Combining ADC_T2-FLAIR at baseline, f_T2-FLAIR at fraction 10, ECOG and MGMT promoter methylation status significantly improved AUC to 90.3% compared to a model with only ECOG and MGMT promoter methylation status (p = 0.001). Using multivariable analysis, neither IVIM metrics were associated with OS but higher f_T2-FLAIR at fraction 10 (HR = 0.72, 95% CI 0.56–0.95, p = 0.018) was associated with longer PFS.

Conclusion:

ADC_T2-FLAIR at baseline, its lack of increase from baseline to fraction 20, or f_T2-FLAIR at fraction 10 significantly predicted early progression. f_T2-FLAIR at fraction 10 was associated with PFS.

Predicting Survival in Glioblastoma Patients Using Diffusion MR Imaging Metrics-A Systematic Review

Simple Summary

An accurate survival analysis is crucial for disease management in glioblastoma (GBM) patients. Due to the ability of the diffusion MRI techniques of providing a quantitative assessment of GBM tumours, an ever-growing number of studies aimed at investigating the role of diffusion MRI metrics in survival prediction of GBM patients. Since the role of diffusion MRI in prediction and evaluation of survival outcomes has not been fully addressed and results are often controversial or unsatisfactory, we performed this systematic review in order to collect, summarize and evaluate all studies evaluating the role of diffusion MRI metrics in predicting survival in GBM patients. We found that quantitative diffusion MRI metrics provide useful information for predicting survival outcomes in GBM patients, mainly in combination with other clinical and multimodality imaging parameters.

Abstract

Despite advances in surgical and medical treatment of glioblastoma (GBM), the medium survival is about 15 months and varies significantly, with occasional longer survivors and individuals whose tumours show a significant response to therapy with respect to others. Diffusion MRI can provide a quantitative assessment of the intratumoral heterogeneity of GBM infiltration, which is of clinical significance for targeted surgery and therapy, and aimed at improving GBM patient survival. So, the aim of this systematic review is to assess the role of diffusion MRI metrics in predicting survival of patients with GBM. According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, a systematic literature search was performed to identify original articles since 2010 that evaluated the association of diffusion MRI metrics with overall survival (OS) and progression-free survival (PFS). The quality of the included studies was evaluated using the QUIPS tool. A total of 52 articles were selected. The most examined metrics were associated with the standard Diffusion Weighted Imaging (DWI) (34 studies) and Diffusion Tensor Imaging (DTI) models (17 studies). Our findings showed that quantitative diffusion MRI metrics provide useful information for predicting survival outcomes in GBM patients, mainly in combination with other clinical and multimodality imaging parameters.

Prediction of survival and progression in glioblastoma patients using temporal perfusion changes during radiochemotherapy

BACKGROUND

The aim of this study was to investigate changes in structural magnetic resonance imaging (MRI) according to the RANO criteria and perfusion- and permeability related metrics derived from dynamic contrast-enhanced MRI (DCE) and dynamic susceptibility contrast MRI (DSC) during radiochemotherapy for prediction of progression and survival in glioblastoma.

METHODS

Twenty-three glioblastoma patients underwent biweekly structural and perfusion MRI before, during, and two weeks after a six weeks course of radiochemotherapy. Temporal trends of tumor volume and the perfusion-derived parameters cerebral blood volume (CBV) and blood flow (CBF) from DSC and DCE, in addition to contrast agent capillary transfer constant (K^trans) from DCE, were assessed. The patients were separated in two groups by median survival and differences between the two groups explored. Clinical- and MRI metrics were investigated using univariate and multivariate survival analysis and a predictive survival index was generated.

RESULTS

Median survival was 19.2 months. A significant decrease in contrast-enhancing tumor size and CBV and CBF in both DCE- and DSC-derived parameters was seen during and two weeks past radiochemotherapy (p < 0.05). A 10%/30% increase in K^trans/CBF two weeks after finishing radiochemotherapy resulted in significant shorter survival (13.9/16.8 vs. 31.5/33.1 months; p < 0.05). Multivariate analysis revealed an index using change in K^trans and relative CBV from DSC significantly corresponding with survival time in months (r² = 0.843; p < 0.001).

CONCLUSIONS

Significant temporal changes are evident during radiochemotherapy in tumor size (after two weeks) and perfusion-weighted MRI-derived parameters (after four weeks) in glioblastoma patients. While DCE-based metrics showed most promise for early survival prediction, a multiparametric combination of both DCE- and DSC-derived metrics gave additional information.

Interval brain imaging for adults with cerebral glioma

BACKGROUND

Clinical practice guidelines suggest that magnetic resonance imaging (MRI) of the brain should be performed at certain time points or intervals distant from diagnosis (interval or surveillance imaging) of cerebral glioma, to monitor or follow up the disease; it is not known, however, whether these imaging strategies lead to better outcomes among patients than triggered imaging in response to new or worsening symptoms.

OBJECTIVES

To determine the effect of different imaging strategies (in particular, pre-specified interval or surveillance imaging, and symptomatic or triggered imaging) on health and economic outcomes for adults with glioma (grades 2 to 4) in the brain.

SEARCH METHODS

The Cochrane Gynaecological, Neuro-oncology and Orphan Cancers (CGNOC) Group Information Specialist searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE and Embase up to 18 June 2019 and the NHS Economic Evaluation Database (EED) up to December 2014 (database closure).

SELECTION CRITERIA

We included randomised controlled trials, non-randomised controlled trials, and controlled before-after studies with concurrent comparison groups comparing the effect of different imaging strategies on survival and other health outcomes in adults with cerebral glioma; and full economic evaluations (cost-effectiveness analyses, cost-utility analyses and cost-benefit analyses) conducted alongside any study design, and any model-based economic evaluations on pre- and post-treatment imaging in adults with cerebral glioma.

DATA COLLECTION AND ANALYSIS

We used standard Cochrane review methodology with two authors independently performing study selection and data collection, and resolving disagreements through discussion. We assessed the certainty of the evidence using the GRADE approach.

MAIN RESULTS

We included one retrospective, single-institution study that compared post-operative imaging within 48 hours (early post-operative imaging) with no early post-operative imaging among 125 people who had surgery for glioblastoma (GBM: World Health Organization (WHO) grade 4 glioma). Most patients in the study underwent maximal surgical resection followed by combined radiotherapy and temozolomide treatment. Although patient characteristics in the study arms were comparable, the study was at high risk of bias overall. Evidence from this study suggested little or no difference between early and no early post-operative imaging with respect to overall survival (deaths) at one year after diagnosis of GBM (risk ratio (RR) 0.86, 95% confidence interval (CI) 0.61 to 1.21; 48% vs 55% died, respectively; very low certainty evidence) and little or no difference in overall survival (deaths) at two years after diagnosis of GBM (RR 1.06, 95% CI 0.91 to 1.25; 86% vs 81% died, respectively; very low certainty evidence). No other review outcomes were reported. We found no evidence on the effectiveness of other imaging schedules. In addition, we identified no relevant economic evaluations assessing the efficiency of the different imaging strategies.

AUTHORS' CONCLUSIONS

The effect of different imaging strategies on survival and other health outcomes remains largely unknown. Existing imaging schedules in glioma seem to be pragmatic rather than evidence-based. The limited evidence suggesting that early post-operative brain imaging among GBM patients who will receive combined chemoradiation treatment may make little or no difference to survival needs to be further researched, particularly as early post-operative imaging also serves as a quality control measure that may lead to early re-operation if residual tumour is identified. Mathematical modelling of a large glioma patient database could help to distinguish the optimal timing of surveillance imaging for different types of glioma, with stratification of patients facilitated by assessment of individual tumour growth rates, molecular biomarkers and other prognostic factors. In addition, paediatric glioma study designs could be used to inform future research of imaging strategies among adults with glioma.

[The use of MR perfusion in assessing the efficacy of treatment for malignant brain tumors]

This literature review analyzes the capabilities of magnetic resonance imaging (MRI)-based cerebral perfusion for differentiation between post-radiation changes (e.g., radionecrosis) and continued growth. The technique is compared with other highly informative radiodiagnostic techniques used in neuroradiology. The use of MR perfusion is important in a comprehensive examination protocol. Trends in the technique development are analyzed.

Relationship of In Vivo MR Parameters to Histopathological and Molecular Characteristics of Newly Diagnosed, Nonenhancing Lower-Grade Gliomas

The goal of this research was to elucidate the relationship between WHO 2016 molecular classifications of newly diagnosed, nonenhancing lower grade gliomas (LrGG), tissue sample histopathology, and magnetic resonance (MR) parameters derived from diffusion, perfusion, and ¹H spectroscopic imaging from the tissue sample locations and the entire tumor. A total of 135 patients were scanned prior to initial surgery, with tumor cellularity scores obtained from 88 image-guided tissue samples. MR parameters were obtained from corresponding sample locations, and histograms of normalized MR parameters within the T2 fluid-attenuated inversion recovery lesion were analyzed in order to evaluate differences between subgroups. For tissue samples, higher tumor scores were related to increased normalized apparent diffusion coefficient (nADC), lower fractional anisotropy (nFA), lower cerebral blood volume (nCBV), higher choline (nCho), and lower N-acetylaspartate (nNAA). Within the T2 lesion, higher tumor grade was associated with higher nADC, lower nFA, and higher Cho to NAA index. Pathological analysis confirmed that diffusion and metabolic parameters increased and perfusion decreased with tumor cellularity. This information can be used to select targets for tissue sampling and to aid in making decisions about treating residual disease.

Mono-exponential, diffusion kurtosis and stretched exponential diffusion MR imaging response to chemoradiation in newly diagnosed glioblastoma

PURPOSE

To quantify changes and prognostic value of diffusion MRI measurements obtained using mono-exponential, diffusion kurtosis imaging (DKI) and stretched exponential (SE) models prior and after chemoradiation in newly diagnosed glioblastoma (GBM).

METHODS

Diffusion-weighted images (DWIs) were acquired in twenty-three patients following surgery, prior chemoradiation and within 7 days following completion of treatment, using b-values ranging from 0 to 5000s/mm². Mono-exponential diffusion (apparent diffusion coefficient: ADC), isotropic (non-directional) DKI model with apparent diffusivity (Dapp) and kurtosis (Kapp) estimates as well as SE model with distributed-diffusion coefficient (DDC) and mean intra-voxel heterogeneity (α) were computed for all patients prior and after chemoradiation. Median values were calculated for normal appearing white matter (NAWM) and contrast-enhancing tumor (CET). The magnitudes of diffusion change prior and after chemoradiation were used to predict overall survival (OS).

RESULTS

Diffusivity in NAWM was consistent for all diffusion measures during chemoradiation, while diffusivity measurements (ADC, Dapp and DDC) within CET changed significantly. A strong positive correlation existed between ADC, Dapp, and DDC measurements prior to chemoradiation; however, this association was weak following chemoradiation, suggesting a more complex microstructural environment after cytotoxic therapy. When combined with baseline tumor volume and MGMT status, age and ADC changes added significant prognostic values, whereas more complex diffusion models did not show significant value in predicting OS.

CONCLUSIONS

Despite increased tissue complexity following chemoradiation, advanced diffusion models have longer acquisition times, provide largely comparable measures of diffusivity, and do not appear to provide additional prognostic value compared to mono-exponential ADC maps.

Metabolic Heterogeneity Evidenced by MRS among Patient-Derived Glioblastoma Multiforme Stem-Like Cells Accounts for Cell Clustering and Different Responses to Drugs

Clustering of patient-derived glioma stem-like cells (GSCs) through unsupervised analysis of metabolites detected by magnetic resonance spectroscopy (MRS) evidenced three subgroups, namely clusters 1a and 1b, with high intergroup similarity and neural fingerprints, and cluster 2, with a metabolism typical of commercial tumor lines. In addition, subclones generated by the same GSC line showed different metabolic phenotypes. Aerobic glycolysis prevailed in cluster 2 cells as demonstrated by higher lactate production compared to cluster 1 cells. Oligomycin, a mitochondrial ATPase inhibitor, induced high lactate extrusion only in cluster 1 cells, where it produced neutral lipid accumulation detected as mobile lipid signals by MRS and lipid droplets by confocal microscopy. These results indicate a relevant role of mitochondrial fatty acid oxidation for energy production in GSCs. On the other hand, further metabolic differences, likely accounting for different therapy responsiveness observed after etomoxir treatment, suggest that caution must be used in considering patient treatment with mitochondria FAO blockers. Metabolomics and metabolic profiling may contribute to discover new diagnostic or prognostic biomarkers to be used for personalized therapies.

Quantitative radiomic profiling of glioblastoma represents transcriptomic expression

Quantitative imaging biomarkers have increasingly emerged in the field of research utilizing available imaging modalities. We aimed to identify good surrogate radiomic features that can represent genetic changes of tumors, thereby establishing noninvasive means for predicting treatment outcome. From May 2012 to June 2014, we retrospectively identified 65 patients with treatment-naïve glioblastoma with available clinical information from the Samsung Medical Center data registry. Preoperative MR imaging data were obtained for all 65 patients with primary glioblastoma. A total of 82 imaging features including first-order statistics, volume, and size features, were semi-automatically extracted from structural and physiologic images such as apparent diffusion coefficient and perfusion images. Using commercially available software, NordicICE, we performed quantitative imaging analysis and collected the dataset composed of radiophenotypic parameters. Unsupervised clustering methods revealed that the radiophenotypic dataset was composed of three clusters. Each cluster represented a distinct molecular classification of glioblastoma; classical type, proneural and neural types, and mesenchymal type. These clusters also reflected differential clinical outcomes. We found that extracted imaging signatures does not represent copy number variation and somatic mutation. Quantitative radiomic features provide a potential evidence to predict molecular phenotype and treatment outcome. Radiomic profiles represents transcriptomic phenotypes more well.

Association of early changes in 1H MRSI parameters with survival for patients with newly diagnosed glioblastoma receiving a multimodality treatment regimen

Background

The heterogeneous biology of glioblastoma (GBM) emphasizes the need for imaging methods to assess tumor burden and assist in evaluating individual patients. The purpose of this study was to investigate early changes in metrics from 3D 1H magnetic resonance spectroscopic imaging (MRSI) data, compare them with anatomic lesion volumes, and determine whether they were associated with survival for patients with newly diagnosed GBM receiving a multimodality treatment regimen.

Methods

Serial MRI and MRSI scans provided estimates of anatomic lesion volumes and levels of choline, creatine, N-acetylaspartate, lactate, and lipid. The association of metrics derived from these data with survival was assessed using Cox proportional hazards models with adjustments for age, Karnofsky performance score, and extent of resection. Temporal changes in parameters were evaluated using a Wilcoxon signed rank test.

Results

Anatomic lesion volumes at the post-radiotherapy (RT) scan, metabolic lesion volume at mid-RT and post-RT scans, as well as metrics describing levels of choline, lactate, and lipid were associated with overall survival. There was a significant reduction in the enhancing lesion volume, increase in T2 lesion volume from mid-RT to post-RT, and decrease in parameters describing metabolite levels during these early time points.

Conclusion

The MRSI data provided metrics that described the effects of treatment on the metabolic lesion burden and were associated with overall survival. This suggests that adding these parameters to standard assessments of changes in anatomic lesion volumes could contribute to making early decisions about the efficacy of such combination therapies.

Intraoperative serum lactate is not a predictor of survival after glioblastoma surgery

BACKGROUND

Cancer cells can produce lactate in high concentrations. Two previous studies examined the clinical relevance of serum lactate as a biomarker in patients with brain tumors. Patients with high-grade tumors have higher serum concentrations of lactate than those with low-grade tumors. We hypothesized that serum lactic could be used of biomarker to predictor of survival in patients with glioblastoma (GB).

METHODS

This was a retrospective study. Demographic, lactate concentrations and imaging data from 275 adult patients with primary GB was included in the analysis. The progression free survival (PFS) and overall survival (OS) rates were compared in patients who had above and below the median concentrations of lactate. We also investigated the correlation between lactate concentrations and tumor volume. Multivariate analyses were conducted to test the association lactate, tumor volume and demographic variables with PFS and OS.

RESULTS

The median serum concentration of lactate was 2.3mmol/L. A weak correlation was found between lactate concentrations and tumor volume. Kaplan-Meier curves demonstrated similar survival in patients with higher or lower than 2.3mmol/L of lactate. The multivariate analysis indicated that the intraoperative levels of lactate were not independently associated with changes in survival. On another hand, a preoperative T1 volume was an independent predictor PFS (HR 95%CI: 1.41, 1.02-1.82, p=0.006) and OS (HR 95%CI: 1.47, 1.11-1.96, p=0.006).

CONCLUSION

This retrospective study suggests that the serum concentrations of lactate cannot be used as a biomarker to predict survival after GB surgery. To date, there are no clinically available serum biomarkers to determine prognosis in patients with high-grade gliomas. These tumors may produce high levels of lactic acid. We hypothesized that serum lactic could be used of biomarker to predictor of survival in patients with glioblastoma (GB). In this study, we collected perioperative and survival data from 275 adult patients with primary high-grade gliomas to determine whether intraoperative serum acid lactic concentrations can serve as a marker of prognosis. The median serum concentration of lactate was 2.3mmol/L. Our analysis indicated the intraoperative levels of lactate were not independently associated with changes in survival. This retrospective study suggests that the serum concentrations of lactate cannot be used as a biomarker to predict survival after GB surgery.

Restriction Spectrum Imaging Improves Risk Stratification in Patients with Glioblastoma

BACKGROUND AND PURPOSE

ADC as a marker of tumor cellularity has been promising for evaluating the response to therapy in patients with glioblastoma but does not successfully stratify patients according to outcomes, especially in the upfront setting. Here we investigate whether restriction spectrum imaging, an advanced diffusion imaging model, performed after an operation but before radiation therapy, could improve risk stratification in patients with newly diagnosed glioblastoma relative to ADC.

MATERIALS AND METHODS

Pre-radiation therapy diffusion-weighted and structural imaging of 40 patients with glioblastoma were examined retrospectively. Restriction spectrum imaging and ADC-based hypercellularity volume fraction (restriction spectrum imaging-FLAIR volume fraction, restriction spectrum imaging-contrast-enhanced volume fraction, ADC-FLAIR volume fraction, ADC-contrast-enhanced volume fraction) and intensities (restriction spectrum imaging-FLAIR 90th percentile, restriction spectrum imaging-contrast-enhanced 90th percentile, ADC-FLAIR 10th percentile, ADC-contrast-enhanced 10th percentile) within the contrast-enhanced and FLAIR hyperintensity VOIs were calculated. The association of diffusion imaging metrics, contrast-enhanced volume, and FLAIR hyperintensity volume with progression-free survival and overall survival was evaluated by using Cox proportional hazards models.

RESULTS

Among the diffusion metrics, restriction spectrum imaging-FLAIR volume fraction was the strongest prognostic metric of progression-free survival (P = .036) and overall survival (P = .007) in a multivariate Cox proportional hazards analysis, with higher values indicating earlier progression and shorter survival. Restriction spectrum imaging-FLAIR 90th percentile was also associated with overall survival (P = .043), with higher intensities, indicating shorter survival. None of the ADC metrics were associated with progression-free survival/overall survival. Contrast-enhanced volume exhibited a trend toward significance for overall survival (P = .063).

CONCLUSIONS

Restriction spectrum imaging-derived cellularity in FLAIR hyperintensity regions may be a more robust prognostic marker than ADC and conventional imaging for early progression and poorer survival in patients with glioblastoma. However, future studies with larger samples are needed to explore its predictive ability.

Patterns of failure for patients with glioblastoma following O-(2-[18F]fluoroethyl)-L-tyrosine PET- and MRI-guided radiotherapy

BACKGROUND AND PURPOSE

To evaluate the patterns of failure following clinical introduction of amino-acid O-(2-[¹⁸F]fluoroethyl)-L-tyrosine (FET)-PET-guided target definition for radiotherapy (RT) of glioblastoma patients.

MATERIALS AND METHODS

The first 66 consecutive patients with confirmed histology, scanned using FET-PET/CT and MRI were selected for evaluation. Chemo-radiotherapy was delivered to a volume based on both MRI and FET-PET (PET_vol). The volume of recurrence (RV) was defined on MRI data collected at the time of progression according to RANO criteria.

RESULTS

Fifty patients were evaluable, with median follow-up of 45months. Central, in-field, marginal and distant recurrences were observed for 82%, 10%, 2%, and 6% of the patients, respectively. We found a volumetric overlap of 26%, 31% and 39% of the RV with the contrast-enhancing MR volume, PET_vol and the composite MRPET_vol, respectively. MGMT-methylation (p=0.03), larger PET_vol (p<0.001), and less extensive surgery (p<0.001), were associated with larger PET_vol overlap.

CONCLUSION

The combined MRPET_vol had a stronger association with the recurrence volume than either of the modalities alone. Larger overlap of PET_vol and RV was observed for patients with MGMT-methylation, less extensive surgery, and large PET_vol on the RT-planning scans.

Early postoperative tumor progression predicts clinical outcome in glioblastoma-implication for clinical trials

Molecular markers define the diagnosis of glioblastoma in the new WHO classification of 2016, challenging neuro-oncology centers to provide timely treatment initiation. The aim of this study was to determine whether a time delay to treatment initiation was accompanied by signs of early tumor progression in an MRI before the start of radiotherapy, and, if so, whether this influences the survival of glioblastoma patients. Images from 61 patients with early post-surgery MRI and a second MRI just before the start of radiotherapy were examined retrospectively for signs of early tumor progression. Survival information was analyzed using the Kaplan–Meier method, and a Cox multivariate analysis was performed to identify independent variables for survival prediction. 59 percent of patients showed signs of early tumor progression after a mean time of 24.1 days from the early post-surgery MRI to the start of radiotherapy. Compared to the group without signs of early tumor progression, which had a mean time of 23.3 days (p = 0.685, Student’s t test), progression free survival was reduced from 320 to 185 days (HR 2.3; CI 95% 1.3–4.0; p = 0.0042, log-rank test) and overall survival from 778 to 329 days (HR 2.9; CI 95% 1.6–5.1; p = 0.0005). A multivariate Cox regression analysis revealed that the Karnofsky performance score, O-6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation, and signs of early tumor progression are prognostic markers of overall survival. Early tumor progression at the start of radiotherapy is associated with a worse prognosis for glioblastoma patients. A standardized baseline MRI might allow for better patient stratification.

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

BACKGROUND

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSION

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

Quantitative Perfusion and Permeability Biomarkers in Brain Cancer from Tomographic CT and MR Images

Dynamic contrast-enhanced perfusion and permeability imaging, using computed tomography and magnetic resonance systems, are important techniques for assessing the vascular supply and hemodynamics of healthy brain parenchyma and tumors. These techniques can measure blood flow, blood volume, and blood-brain barrier permeability surface area product and, thus, may provide information complementary to clinical and pathological assessments. These have been used as biomarkers to enhance the treatment planning process, to optimize treatment decision-making, and to enable monitoring of the treatment noninvasively. In this review, the principles of magnetic resonance and computed tomography dynamic contrast-enhanced perfusion and permeability imaging are described (with an emphasis on their commonalities), and the potential values of these techniques for differentiating high-grade gliomas from other brain lesions, distinguishing true progression from posttreatment effects, and predicting survival after radiotherapy, chemotherapy, and antiangiogenic treatments are presented.

Imaging patterns predict patient survival and molecular subtype in glioblastoma via machine learning techniques

BACKGROUND

MRI characteristics of brain gliomas have been used to predict clinical outcome and molecular tumor characteristics. However, previously reported imaging biomarkers have not been sufficiently accurate or reproducible to enter routine clinical practice and often rely on relatively simple MRI measures. The current study leverages advanced image analysis and machine learning algorithms to identify complex and reproducible imaging patterns predictive of overall survival and molecular subtype in glioblastoma (GB).

METHODS

One hundred five patients with GB were first used to extract approximately 60 diverse features from preoperative multiparametric MRIs. These imaging features were used by a machine learning algorithm to derive imaging predictors of patient survival and molecular subtype. Cross-validation ensured generalizability of these predictors to new patients. Subsequently, the predictors were evaluated in a prospective cohort of 29 new patients.

RESULTS

Survival curves yielded a hazard ratio of 10.64 for predicted long versus short survivors. The overall, 3-way (long/medium/short survival) accuracy in the prospective cohort approached 80%. Classification of patients into the 4 molecular subtypes of GB achieved 76% accuracy.

CONCLUSIONS

By employing machine learning techniques, we were able to demonstrate that imaging patterns are highly predictive of patient survival. Additionally, we found that GB subtypes have distinctive imaging phenotypes. These results reveal that when imaging markers related to infiltration, cell density, microvascularity, and blood-brain barrier compromise are integrated via advanced pattern analysis methods, they form very accurate predictive biomarkers. These predictive markers used solely preoperative images, hence they can significantly augment diagnosis and treatment of GB patients.

Evaluation of pre-radiotherapy apparent diffusion coefficient (ADC): patterns of recurrence and survival outcomes analysis in patients treated for glioblastoma multiforme

PURPOSE

To investigate the association of pre-radiotherapy apparent diffusion coefficient (ADC) abnormalities with patterns of recurrence and outcomes in patients with glioblastoma multiforme (GBM).

MATERIALS AND METHODS

Fifty-two patients with recurrent GBM were retrospectively evaluated. Diffusion MRI images were acquired for all patients postoperatively prior to radiotherapy. ADC images were evaluated for geographic regions of diffusion restriction (hypointensity) within the FLAIR volume. If identified, the ADC map and the T1+C MRI at the time of recurrence were registered to the original plan to determine the pattern of recurrence and the coverage of the ADC abnormality by the 60 Gy isodose line (IDL). Progression-free and overall survival was determined for patients with and without an ADC hypointensity.

RESULTS

An ADC hypointensity was identified in 32 (62%) of cases. The recurrence pattern in these cases was central in 27/32 (84%), marginal in 4/32 (13%) and distant in 1/32 (3%). The recurrence overlapped with the ADC hypointensity in 28 (88%) patients. The ADC hypointensity was covered by 95% of the 60 Gy IDL in all cases. Kaplan-Meier analysis revealed inferior progression free survival and overall survival in patients with an ADC hypointensity compared to those without, despite similarities between the groups in terms of age, RT dose, performance status, and extent of resection.

CONCLUSIONS

The presence of an ADC hypointensity on pre-radiotherapy diffusion-weighted imaging is associated with the location of tumor recurrence as demonstrated by frequent overlap in this series, and is associated with a trend toward inferior outcomes. This abnormality may reflect a high risk region of hypercellularity and warrants consideration with respect to radiotherapy planning.

Survival prediction in high-grade gliomas using CT perfusion imaging

Patients with high-grade gliomas usually have heterogeneous response to surgery and chemoirradiation. The objectives of this study were (1) to evaluate serial changes in tumor volume and perfusion imaging parameters and (2) to determine the value of these data in predicting overall survival (OS). Twenty-nine patients with World Health Organization grades III and IV gliomas underwent magnetic resonance (MR) and computed tomography (CT) perfusion examinations before surgery, and 1, 3, 6, 9, and 12 months after radiotherapy. Serial measurements of tumor volumes and perfusion parameters were evaluated by receiver operating characteristic analysis, Cox proportional hazards regression, and Kaplan-Meier survival analysis to determine their values in predicting OS. Higher trends in blood flow (BF), blood volume (BV), and permeability-surface area product in the contrast-enhancing lesions (CEL) and the non-enhancing lesions (NEL) were found in patients with OS < 18 months compared to those with OS ≥ 18 months, and these values were significant at selected time points (P < 0.05). Only CT perfusion parameters yielded sensitivities and specificities of ≥ 70% in predicting 18 and 24 months OS. Pre-surgery BF in the NEL and BV in the CEL and NEL 3 months after radiotherapy had sensitivities and specificities >80% in predicting 24 months OS in patients with grade IV gliomas. Our study indicated that CT perfusion parameters were predictive of survival and could be useful in assessing early response and in selecting adjuvant treatment to prolong survival if verified in a larger cohort of patients.

Comparison of ADC metrics and their association with outcome for patients with newly diagnosed glioblastoma being treated with radiation therapy, temozolomide, erlotinib and bevacizumab

To evaluate metrics that describe changes in apparent diffusion coefficient (ADC) and to examine their association with clinical outcome for patients with newly diagnosed GBM who were participating in a Phase II clinical trial of treatment with radiation (RT), temozolomide, erlatonib and bevacizumab. Thirty six patients were imaged after surgery but prior to therapy and at regular follow-up time points. The following ADC metrics were evaluated: (1) histogram percentiles within the T2-hyperintense lesion (T2L) at serial follow-ups; (2) parameters obtained by fitting a two-mixture normal distribution to the histogram within the contrast-enhancing lesion (CEL) at baseline; (3) parameters obtained using both traditional and graded functional diffusion maps within the CEL and T2L. Cox Proportional Hazards models were employed to assess the association of the ADC parameters with overall survival (OS) and progression-free survival (PFS). A lower ADC percentile value within the T2L at early follow-up time points was associated with worse outcome. Of particular interest is that, even when adjusting for clinical prognostic factors, the ADC_10% within the T2L at 2 months was strongly associated with OS (p < 0.001) and PFS (p < 0.007). fDM metrics showed an association with OS and PFS within the CEL when considered by univariate analysis, but not in the T2L. Our study emphasizes the value of ADC metrics obtained from the T2L at the post-RT time point as non-invasive biomarkers for assessing residual tumor in patients with newly diagnosed GBM being treated with combination therapy that includes the anti-angiogenic agent bevacizumab.

Association of overall survival in patients with newly diagnosed glioblastoma with contrast-enhanced perfusion MRI: Comparison of intraindividually matched T1 - and T2 (*) -based bolus techniques

BACKGROUND

To compare intraindividual dynamic susceptibility contrast (DSC) and dynamic contrast enhanced (DCE) MR perfusion parameters and determine the association of DCE parameters with overall survival (OS) with the established predictive DSC parameter cerebral blood volume (CBV) in patients with newly diagnosed glioblastoma.

METHODS

Perfusion data were analyzed retrospectively, and included scans performed preoperatively at 3.0 Tesla in 37 patients (25 males, 12 females, 39-83 years, median 65) later diagnosed with glioblastoma. All patients received standard treatment consisting of surgery and radiochemotherapy. Images were spatially coregistered and maximum region of interest-based DCE and DSC parameter measurements compared and thresholds identified using multivariate linear regression, Pearson's correlation coefficients and using receiver operating characteristic analysis. Survival analysis was performed using Kaplan-Meier curves.

RESULTS

While both, elevated volume transfer constant (K(trans) ) (>0.29 min(-1) ; P = 0.041) and CBV (>23.7 mL/100 mL; P < 0.001) were significantly associated with OS, elevated CBV was associated with worse OS compared with elevated K(trans) . K(trans) was significantly correlated with the leakage correction factor K2 but not with CBV.

CONCLUSION

The combined use of DSC and DCE MR perfusion may provide additional information of prognostic value for glioblastoma patient survival prediction. As K(trans) was not tightly coupled to CBV, both parameters may reflect different stages in the pathogenetic sequence of glioblastoma growth.

Advanced magnetic resonance imaging methods for planning and monitoring radiation therapy in patients with high-grade glioma

This review explores how the integration of advanced imaging methods with high-quality anatomical images significantly improves the characterization, target definition, assessment of response to therapy, and overall management of patients with high-grade glioma. Metrics derived from diffusion-, perfusion-, and susceptibility-weighted magnetic resonance imaging in conjunction with magnetic resonance spectroscopic imaging, allows us to characterize regions of edema, hypoxia, increased cellularity, and necrosis within heterogeneous tumor and surrounding brain tissue. Quantification of such measures may provide a more reliable initial representation of tumor delineation and response to therapy than changes in the contrast-enhancing or T2 lesion alone and have a significant effect on targeting resection, planning radiation, and assessing treatment effectiveness. In the long term, implementation of these imaging methodologies can also aid in the identification of recurrent tumor and its differentiation from treatment-related confounds and facilitate the detection of radiationinduced vascular injury in otherwise normal-appearing brain tissue.

Advances in diagnostic and treatment modalities for intracranial tumors

Intracranial neoplasia is a common clinical condition in domestic companion animals, particularly in dogs. Application of advances in standard diagnostic and therapeutic modalities together with a broad interest in the development of novel translational therapeutic strategies in dogs has resulted in clinically relevant improvements in outcome for many canine patients. This review highlights the status of current diagnostic and therapeutic approaches to intracranial neoplasia and areas of novel treatment currently in development.

Spin-echo echo-planar perfusion prior to chemoradiation is a strong independent predictor of progression-free and overall survival in newly diagnosed glioblastoma

Spin-echo echo planar (EP) perfusion weighted imaging (SE-PWI) has been demonstrated to be more selective than gradient-echo EP PWI for blood volume in microvessels the size of glioma neocapillaries, but it has not been comprehensively studied in human clinical use. We assessed whether SE-PWI before and after initiating chemoradiation can stratify patients with respect to progression free survival (PFS) and overall survival (OS). Sixty-eight patients with newly diagnosed glioblastoma (mean age 58.3, 36 males) were included in analysis. SE EP cerebral blood volumes (SE-CBVs) in enhancing and nonenhancing tumor, normalized to contralateral normal appearing white matter (SE-nCBV), were assessed at baseline and after initial chemoradiation. SE-nCBV parameters predictive of PFS and OS were identified in univariate and multivariate Cox proportional hazards models. Multivariate analysis demonstrated that baseline tumor mean SE-nCBV was predictive of PFS (p = 0.038) and OS (p = 0.004). Within the patient sample, baseline tumor mean SE-nCBV <2.0 predicted longer patient PFS (median 47.0 weeks, p < 0.001) and OS (median 98.6 weeks, p = 0.003) compared with baseline mean SE-nCBV >2.0 (median PFS 25.3, median OS 56.0 weeks). Exploratory multi-group stratification demonstrated that very high (>4.0) tumor SE-nCBV was associated with worse patient OS than intermediate high (>2.0, <4.0) SE-nCBV (p = 0.025). Baseline mean SE-nCBV can stratify patients for PFS and OS prior to initiation of chemoradiation, which may help select patients who require closer surveillance. Our exploratory analysis indicates a magnitude-dependent relationship between baseline SE-nCBV and OS.

Correlation between progression free survival and dynamic susceptibility contrast MRI perfusion in WHO grade III glioma subtypes

The purpose of this study was to determine whether dynamic susceptibility contrast MR perfusion relative cerebral blood volume (rCBV) correlates with prognosis of World Health Organization (WHO) grade III glial tumors and their different subtypes. Retrospective evaluation of pre-treatment tumor rCBV derived from dynamic susceptibility contrast MR perfusion was performed in 34 patients with histopathologically diagnosed WHO grade III glial tumors (anaplastic astrocytomas (n = 20), oligodendrogliomas (n = 4), and oligoastrocytomas (n = 10)). Progression free survival was correlated with rCBV using Spearman rank analysis. ROC curve analysis was performed to determine the operating point for rCBV in patients with anaplastic astrocytomas dichotomized at the median progression free survival time. For all grade III tumors (n = 34) the mean rCBV was 2.51 with a progression free survival of 705.5 days. The mean rCBV of anaplastic astrocytomas was 2.47 with progression free survival 495.2 days. In contrast, the mean rCBV for oligodendroglial tumors was 2.56 with a progression free survival of 1005.6 days. Although there was no significant correlation between rCBV and progression free survival among all types of grade III gliomas (P = 0.12), among anaplastic astrocytomas there was a significant correlation between pretreatment rCBV and progression free survival with correlation coefficient of -0.51 (P = 0.02). The operating point for rCBV in patients with anaplastic astrocytomas dichotomized at the median progression free survival time (446.5 days) was 2.86 with 78 % accuracy and there was a significant difference between the survival of patients with anaplastic astrocytomas in the dichotomized groups (P = 0.0009). Pre-treatment rCBV may serve as a prognostic imaging biomarker for anaplastic astrocytomas, but not grade III oligodendroglioma tumors.

Serial MR diffusion to predict treatment response in high-grade pediatric brain tumors: a comparison of regional and voxel-based diffusion change metrics

BACKGROUND

Assessment of treatment response by measuring tumor size is known to be a late and potentially confounded response index. Serial diffusion MRI has shown potential for allowing earlier and possibly more reliable response assessment in adult patients, with limited experience in clinical settings and in pediatric brain cancer. We present a retrospective study of clinical MRI data in children with high-grade brain tumors to assess and compare the values of several diffusion change metrics to predict treatment response.

METHODS

Eighteen patients (age range, 1.9-20.6 years) with high-grade brain tumors and serial diffusion MRI (pre- and posttreatment interval range, 1-16 weeks posttreatment) were identified after obtaining parental consent. The following diffusion change metrics were compared with the clinical response status assessed at 6 months: (1) regional change in absolute and normalized apparent diffusivity coefficient (ADC), (2) voxel-based fractional volume of increased (fiADC) and decreased ADC (fdADC), and (3) a new metric based on the slope of the first principal component of functional diffusion maps (fDM).

RESULTS

Responders (n = 12) differed significantly from nonresponders (n = 6) in all 3 diffusional change metrics demonstrating higher regional ADC increase, larger fiADC, and steeper slopes (P < .05). The slope method allowed the best response prediction (P < .01, η(2) = 0.78) with a classification accuracy of 83% for a slope of 58° using receiver operating characteristic (ROC) analysis.

CONCLUSIONS

We demonstrate that diffusion change metrics are suitable response predictors for high-grade pediatric tumors, even in the presence of variable clinical diffusion imaging protocols.

Survival analysis in patients with newly diagnosed glioblastoma using pre- and postradiotherapy MR spectroscopic imaging

BACKGROUND

The objective of this study was to examine the predictive value of parameters of 3D (1)H magnetic resonance spectroscopic imaging (MRSI) prior to treatment with radiation/chemotherapy (baseline) and at a postradiation 2-month follow-up (F2mo) in relationship to 6-month progression-free survival (PFS6) and overall survival (OS).

METHODS

Sixty-four patients with newly diagnosed glioblastoma multiforme (GBM) being treated with radiation and concurrent chemotherapy were involved in this study. Evaluated were metabolite indices and metabolite ratios. Logistic linear regression and Cox proportional hazards models were utilized to evaluate PFS6 and OS, respectively. These analyses were adjusted by age and MR scanner field strength (1.5 T or 3 T). Stepwise regression was performed to determine a subset of the most relevant variables.

RESULTS

Associated with shorter PFS6 were a decrease in the ratio of N-acetyl aspartate to choline-containing compounds (NAA/Cho) in the region with a Cho-to-NAA index (CNI) >3 at baseline and an increase of the CNI within elevated CNI regions (>2) at F2mo. Patients with higher normalized lipid and lactate at either time point had significantly worse OS. Patients who had larger volumes with abnormal CNI at F2mo had worse PFS6 and OS.

CONCLUSIONS

Our study found more 3D MRSI parameters that predicted PFS6 and OS for patients with GBM than did anatomic, diffusion, or perfusion imaging, which were previously evaluated in the same population of patients.

Immediate post-operative MRI suggestive of the site and timing of glioblastoma recurrence after gross total resection: a retrospective longitudinal preliminary study

OBJECTIVES

To retrospectively identify morphological and physiological post-operative magnetic resonance imaging (MRI) characteristics predictive of glioblastoma recurrences after gross total resection (gross-TR).

METHODS

Resection margins of 24 glioblastoma were analysed immediately post-operatively (MRI ≤ 2 h) and early post-operatively (24 h ≤ MRI ≤ 48 h), and subdivided into areas with and without subtle contrast enhancement previously considered non-specific. On follow-up MRI, tumour regrowth areas were subdivided according to recurrence extent (focally/extended) and delay (≤6 and ≥12 months). Co-registration of pre-operative, immediately post-operative and early post-operative MRI with the first follow-up MRI demonstrating recurrence authorised their morphological (contrast enhancements) and physiological (rCBV) characterisation.

RESULTS

Morphologically, on immediately post-operative MRI, micro-nodular and frayed enhancements correlate significantly with early recurrences (≤6 months). After gross-TR the absence of these enhancements is associated with a significant increase in progression-free survival (61 vs 15 weeks respectively) and overall survival (125 vs 51 weeks respectively). Physiologically, areas with a future focal recurrence have a trend toward higher rCBV than other areas.

CONCLUSION

Immediately post-operative topography of micro-nodular and frayed enhancements is suggestive of recurrence location and delay. Absence of such enhancements is associated with a fourfold increase in progression-free survival and a 2.5-fold increase in overall survival.

KEY POINTS

• Immediately post-operative MRI reveals contrast enhancement after glioblastoma gross total resection. • Immediately post-operative micro-nodular and frayed enhancement correlate with early recurrence. • Absence of micro-nodular/frayed enhancement is associated with 61 weeks' progression-free survival. • Absence of micro-nodular/frayed enhancement is associated with 125 weeks' overall survival.

Advances in ultra-high field MRI for the clinical management of patients with brain tumors

PURPOSE OF REVIEW

The last 5 years have seen the number of ultra-high field (UHF; 7 T and beyond) MRI scanners nearly double. Benefits include improved specificity, better sensitivity for signal-starved compounds, and the ability to detect, quantify, and monitor tumor activity and treatment effects. This is especially important in the current climate in which new treatments alter established markers of tumor and the surrounding environment, confounding traditional response criteria.

RECENT FINDINGS

Intra-tumoral heterogeneity and dramatic improvement in spatial localization have been observed with 7 and 8 T high-resolution T2-weighted and T2*-weighted imaging. This depiction of lesions that were not readily detected at lower field improved the classification of glioma. Sub-millimeter visualization of microvasculature has facilitated the detection of microbleeds associated with long-term effects of radiation. New metabolic markers seen at UHF may also assist in distinguishing tumor progression from treatment effect.

SUMMARY

Although progress has been limited by technical challenges, initial experience has demonstrated the promise of 7-T MRI in advancing existing paradigms for diagnosing, monitoring, and managing patients with brain tumors. The success of these systems will depend upon what new information can be gained by UHF, rather than simply improving the quality of the current lower field standard.

Is apparent diffusion coefficient reliable and accurate for monitoring effects of antiangiogenic treatment in a longitudinal study?

PURPOSE

To evaluate the reliability and accuracy of the apparent diffusion coefficient (ADC) for monitoring antiangiogenic treatment in a longitudinal study.

MATERIALS AND METHODS

Tumor volume and ADC were monitored by T2-weighted magnetic resonance imaging (MRI) and diffusion-weighted MRI, respectively, in 18 mice with angiogenesis-dependent tumors (U118MG) before (day 0) and after 2, 7, 14, and 21 days of administration of the antiangiogenic agent sunitinib maleate (n = 12) or vehicle (n = 6). Percent changes in tumor volume and ADC were calculated and correlations between tumor volume and ADC were evaluated.

RESULTS

Tumor volume and ADC showed a negative correlation at 69 of the 72 (96%) follow-up measurements. In the 13 mice with tumor regrowth, ADC started to decrease before (27%) or at the same time (73%) as tumor regrowth. Pretreatment ADC and percent change in ADC change on days 0-2 were similar in mice with positive and negative responses to treatment (0.851 vs. 0.999, 24% vs. 16%). Percent change of ADC showed significant negative correlation with percent change in tumor volume in both the control (r = -0.69) and treated (r = -0.65) groups.

CONCLUSION

Percent change in ADC is a reliable and accurate marker for monitoring the effects of antiangiogenic treatment, whereas pretreatment ADC and early changes in ADC (ie, days 0-2) are limited in predicting treatment outcome.

Assessment of therapeutic response and treatment planning for brain tumors using metabolic and physiological MRI

MRI is routinely used for diagnosis, treatment planning and assessment of response to therapy for patients with glioma. Gliomas are spatially heterogeneous and infiltrative lesions that are quite variable in terms of their response to therapy. Patients classified as having low-grade histology have a median overall survival of 7 years or more, but need to be monitored carefully to make sure that their tumor does not upgrade to a more malignant phenotype. Patients with the most aggressive grade IV histology have a median overall survival of 12-15 months and often undergo multiple surgeries and adjuvant therapies in an attempt to control their disease. Despite improvements in the spatial resolution and sensitivity of anatomic images, there remain considerable ambiguities in the interpretation of changes in the size of the gadolinium-enhancing lesion on T(1) -weighted images as a measure of treatment response, and in differentiating between treatment effects and infiltrating tumor within the larger T(2) lesion. The planning of focal therapies, such as surgery, radiation and targeted drug delivery, as well as a more reliable assessment of the response to therapy, would benefit considerably from the integration of metabolic and physiological imaging techniques into routine clinical MR examinations. Advanced methods that have been shown to provide valuable data for patients with glioma are diffusion, perfusion and spectroscopic imaging. Multiparametric examinations that include the acquisition of such data are able to assess tumor cellularity, hypoxia, disruption of normal tissue architecture, changes in vascular density and vessel permeability, in addition to the standard measures of changes in the volume of enhancing and nonenhancing anatomic lesions. This is particularly critical for the interpretation of the results of Phase I and Phase II clinical trials of novel therapies, which are increasingly including agents that are designed to have anti-angiogenic and anti-proliferative properties as opposed to having a direct effect on tumor cell viability.