Value of dynamic contrast perfusion MRI to predict early response to bevacizumab in newly diagnosed glioblastoma: results from ACRIN 6686 multicenter trial

Expert Panel on Neurological Imaging, Ivanidze J, Shih RY, Utukuri PS, Ajam AA, Auron M, Chang SM, Jordan JT, Kalnins A, Kuo PH, Ledbetter LN, Pannell JS, Pollock JM, Sheehan J, Soares BP, Soderlund KA, Wang LL, Burns J. ACR Appropriateness Criteria® Brain Tumors

Brain tumors represent a complex and clinically diverse disease group, whose management is particularly dependent on neuroimaging given the wide range of differential diagnostic considerations and clinical scenarios. The introduction of advanced brain imaging tools into clinical practice makes it paramount for all treating physicians to recognize the range and understand the appropriate application of various conventional and advanced imaging modalities. The imaging recommendations for neuro-oncologic clinical scenarios involving screening in patients with increased genetic risk, screening in patients with systemic malignancy, pretreatment evaluation in patients with intra- and extraaxial brain tumors, posttreatment-surveillance in patients with known brain tumors after completion of therapy, and subsequent workup in the context of suspected radiographic progression are encompassed by this document. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

Multisite Benchmark Study for Standardized Relative CBV in Untreated Brain Metastases Using the DSC-MRI Consensus Acquisition Protocol

BACKGROUND AND PURPOSE

A national consensus recommendation for the collection of DSC-MRI perfusion data, used to create maps of relative CBV (rCBV), has been recently established for primary and metastatic brain tumors. The goal was to reduce intersite variability and improve ease of comparison across time and sites, fostering widespread use of this informative measure. To translate this goal into practice, the prospective collection of consensus DSC-MRI data and characterization of derived rCBV maps in brain metastases is needed. The purpose of this multisite study was to determine rCBV in untreated brain metastases in comparison to glioblastoma (GBM) and normal-appearing brain by using the national consensus protocol.

MATERIALS AND METHODS

Subjects from 3 sites with untreated enhancing brain metastases underwent DSC-MRI according to a recommended option that uses a midrange flip angle, GRE-EPI acquisition, and the administration of both a preload and second DSC-MRI dose of 0.1 mmol/kg gadolinium-based contrast agent. Quantitative maps of standardized relative CBV (srCBV) were generated and enhancing lesion ROIs determined from postcontrast T1-weighted images alone or calibrated difference maps, termed Δ T1 (dT1) maps. Mean srCBV for metastases were compared with normal-appearing white matter (NAWM) and GBM from a previous study. Comparisons were performed by using either the Wilcoxon signed-rank test for paired comparisons or the Mann-Whitney U nonparametric test for unpaired comparisons.

RESULTS

Forty-nine patients with a primary histology of lung (n = 25), breast (n = 6), squamous cell carcinoma (n = 1), melanoma (n = 5), gastrointestinal (GI) (n = 3), and genitourinary (GU) (n = 9) were included in comparison to GBM (n = 31). The mean srCBV of all metastases (1.83±1.05) were significantly lower (P = .0009) than mean srCBV for GBM (2.67 ± 1.34) with both statistically greater (P < .0001) than NAWM (0.68 ± 0.18). Histologically distinct metastases are each statistically greater than NAWM (P < .0001) with lung (P = .0002) and GU (P = .02) srCBV being significantly different from GBM srCBV.

CONCLUSIONS

Using the consensus DSC-MRI protocol, mean srCBV values were determined for treatment-naïve brain metastases in comparison to normal-appearing white matter and GBM thus setting the benchmark for all subsequent studies adherent to the national consensus recommendation.

Advanced Imaging in the Diagnosis and Response Assessment of High-Grade Glioma: AJR Expert Panel Narrative Review

This AJR Expert Panel Narrative Review explores the current status of advanced MRI and PET techniques for the posttherapeutic response assessment of high-grade adult-type gliomas, focusing on ongoing clinical controversies in current practice. Discussed techniques that complement conventional MRI and aid the differentiation of recurrent tumor from posttreatment effects include DWI and diffusion-tensor imaging; perfusion MRI techniques including dynamic susceptibility contrast (DSC), dynamic contrast-enhanced, and arterial spin labeling MRI; MR spectroscopy (MRS) including assessment of 2-hydroxyglutarate (2HG) concentration; glucose- and amino acid (AA)-based PET; and amide proton transfer imaging. Updated criteria for the Response Assessment in Neuro-Oncology are presented. Given the abundant supporting clinical evidence, the panel supports a recommendation that routine response assessment after high-grade glioma treatment should include perfusion MRI, particularly given the development of a consensus recommended DSC-MRI protocol. Although published studies support 2HG MRS and AA PET, these techniques' widespread adoption will likely require increased availability (for 2HG MRS) or increased insurance funding in the United States (for AA PET). The review concludes with a series of consensus opinions from the author panel, centered on the clinical integration of the advanced imaging techniques into posttreatment surveillance protocols.

Current trends in the characterization and monitoring of vascular response to cancer therapy

Tumor vascular physiology is an important determinant of disease progression as well as the therapeutic outcome of cancer treatment. Angiogenesis or the lack of it provides crucial information about the tumor's blood supply and therefore can be used as an index for cancer growth and progression. While standalone anti-angiogenic therapy demonstrated limited therapeutic benefits, its combination with chemotherapeutic agents improved the overall survival of cancer patients. This could be attributed to the effect of vascular normalization, a dynamic process that temporarily reverts abnormal vasculature to the normal phenotype maximizing the delivery and intratumor distribution of chemotherapeutic agents. Longitudinal monitoring of vascular changes following antiangiogenic therapy can indicate an optimal window for drug administration and estimate the potential outcome of treatment. This review primarily focuses on the status of various imaging modalities used for the longitudinal characterization of vascular changes before and after anti-angiogenic therapies and their clinical prospects.

Application of Delta T1 maps for quantitative and objective assessment of extent of resection and survival prediction in glioblastoma

Background and Objectives

Gross-total resection (GTR) and low residual tumor volume (RTV) have been associated with increased survival in glioblastoma. Largely due to the subjectivity involved, the determination of GTR and RTV remains difficult in the postoperative setting. In response, the objective of this study is to evaluate the clinical efficacy of an easy-to-use MRI metric, called delta T1 (dT1), to quantify extent of resection (EOR) and RTV, in comparison to radiologist impression, to predict overall survival (OS) in glioblastoma patients.

Methods

59 patients who underwent resection of glioblastoma were retrospectively identified. Delta T1 (dT1) images, automatically created from the difference between calibrated post- and pre-contrast T1-weighted images, were used to quantify EOR and RTV. Kaplan-Meier survival estimates were determined for EOR categories, an RTV cutoff of 5cm3 and radiologist interpretation of EOR. Multivariate Cox proportional hazard regression analysis was used to evaluate RTV and EOR along with effects related to sex, KPS, MGMT, and age on OS.

Results

Kaplan-Meier analysis revealed a statistically significant difference in median OS for a dT1-determined RTV cutoff of 5 cm3 (P=.0024, HR=2.18 (1.232-3.856)), but not for radiological impression (P=0.666) or dT1-determined EOR (P=0.0803), which was limited to a comparison between partial and subtotal resections. Furthermore, when covariates were accounted for in multivariate Cox regression, significant differences in OS were retained for dT1-determined RTV. Additionally, a significantly strong yet short-term effect of MGMT methylation status on OS was revealed for each RTV and EOR model.

Conclusion

The utility of dT1 maps to quantify EOR and RTV in glioblastoma and predict survival, suggests an emerging role for dT1s with relevance for intraoperative MRI, neuro-navigation and postoperative disease surveillance.

The utility of arterial spin labeling imaging for predicting prognosis after a recurrence of high-grade glioma in patients under bevacizumab treatment

BACKGROUND AND PURPOSE

Currently, the antiangiogenic agent bevacizumab (BVZ) is used as a treatment option for high-grade glioma (HGG) patients. However, BVZ restores disruptions of the blood-brain barrier, which leads to the disappearance of contrast enhancement during radiological examinations and therefore complicates evaluations of treatment efficacy. This study aimed to investigate the radio-morphological features of recurrent lesions that newly appeared under BVZ therapy, as well as the utility of arterial spin labeling (ASL) perfusion imaging for evaluating treatment response and prognosis in HGG patients receiving BVZ.

METHODS

Thirty-two patients (20 males, 12 females; age range, 35-84 years) with HGG who experienced a recurrence under BVZ therapy were enrolled. We measured the relative cerebral blood flow (rCBF) values of each recurrent lesion using ASL, and retrospectively investigated the correlation between rCBF values and prognosis.

RESULTS

The optimal rCBF cut-off value for predicting prognosis was defined as 1.67 using receiver operating characteristic curve analysis. The patients in the rCBF < 1.67 group had significantly longer overall survival (OS) and post-progression survival (PPS) than those in the rCBF ≥ 1.67 group (OS: 34.0 months vs. 13.0 months, p = 0.03 and PPS: 13.0 months vs. 6.0 months, p < 0.001, respectively).

CONCLUSION

The ASL-derived rCBF values of recurrent lesions may serve as an effective imaging biomarker for prognosis in HGG patients undergoing BVZ therapy. Low rCBF values may indicate that BVZ efficacy is sustainable, which will influence BVZ treatment strategies in HGG patients.

Standardized brain tumor imaging protocols for clinical trials: current recommendations and tips for integration

Standardized MRI acquisition protocols are crucial for reducing the measurement and interpretation variability associated with response assessment in brain tumor clinical trials. The main challenge is that standardized protocols should ensure high image quality while maximizing the number of institutions meeting the acquisition requirements. In recent years, extensive effort has been made by consensus groups to propose different "ideal" and "minimum requirements" brain tumor imaging protocols (BTIPs) for gliomas, brain metastases (BM), and primary central nervous system lymphomas (PCSNL). In clinical practice, BTIPs for clinical trials can be easily integrated with additional MRI sequences that may be desired for clinical patient management at individual sites. In this review, we summarize the general concepts behind the choice and timing of sequences included in the current recommended BTIPs, we provide a comparative overview, and discuss tips and caveats to integrate additional clinical or research sequences while preserving the recommended BTIPs. Finally, we also reflect on potential future directions for brain tumor imaging in clinical trials.

Advanced MR Techniques for Preoperative Glioma Characterization: Part 1

Preoperative clinical magnetic resonance imaging (MRI) protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation or lack thereof. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this first part, we discuss dynamic susceptibility contrast and dynamic contrast-enhanced MRI, arterial spin labeling, diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting. The second part of this review addresses magnetic resonance spectroscopy, chemical exchange saturation transfer, susceptibility-weighted imaging, MRI-PET, MR elastography, and MR-based radiomics applications. Evidence Level: 3 Technical Efficacy: Stage 2.

What effective technique to differentiate radiation brain necrosis from a tumor progression in patients treated with radiation: A monocentric retrospective study combining the MRI TRAMs technique and the (18F)-dopa PET/CT

PURPOSE

Brain necrosis after radiotherapy is a challenging diagnosis, since it has similar radiological appearance on standard MRI to tumor progression. Consequences on treatment decisions can be important. We compare recent imaging techniques in order to adopt a reliable diagnostic protocol in doubtful situations.

PATIENTS AND METHOD

This is a retrospective study comparing the performance of three imaging techniques after radiotherapy of brain metastasis: Perfusion-MRI, TRAMs technique and F-dopa PET-CT. The evolution of the treated metastasis volume was also analyzed by contouring all patients MRIs. All included patients were suspected of relapse and had the three exams once the volume of treated metastasis increased.

RESULTS

The majority of our patients were treated by stereotactic radiotherapy. Suspicion of relapse was on average around 17months after treatment. Four cases of radionecrosis were diagnosed and six cases of real tumor progression. Neurological symptoms were less present in radionecrosis cases. All of our radionecrosis cases had relative cerebral blood volume below 1. F-dopa PET-CT succeeded to set the good diagnosis in eight cases, although we found one false positive and one false negative exam. The TRAMs technique failed in one case of false negative exam.

CONCLUSIONS

Perfusion-MRI showed high performance in the diagnosis of radionecrosis, especially when calculating relative cerebral blood volume rate. The TRAMs technique showed interesting results and deserves application in daily routine combined with the perfusion-MRI. F-dopa CT might induce false results because of different metabolic uptake according to tumor type, medication and brain blood barrier leak.

Molecular and functional imaging in cancer-targeted therapy: current applications and future directions

Targeted anticancer drugs block cancer cell growth by interfering with specific signaling pathways vital to carcinogenesis and tumor growth rather than harming all rapidly dividing cells as in cytotoxic chemotherapy. The Response Evaluation Criteria in Solid Tumor (RECIST) system has been used to assess tumor response to therapy via changes in the size of target lesions as measured by calipers, conventional anatomically based imaging modalities such as computed tomography (CT), and magnetic resonance imaging (MRI), and other imaging methods. However, RECIST is sometimes inaccurate in assessing the efficacy of targeted therapy drugs because of the poor correlation between tumor size and treatment-induced tumor necrosis or shrinkage. This approach might also result in delayed identification of response when the therapy does confer a reduction in tumor size. Innovative molecular imaging techniques have rapidly gained importance in the dawning era of targeted therapy as they can visualize, characterize, and quantify biological processes at the cellular, subcellular, or even molecular level rather than at the anatomical level. This review summarizes different targeted cell signaling pathways, various molecular imaging techniques, and developed probes. Moreover, the application of molecular imaging for evaluating treatment response and related clinical outcome is also systematically outlined. In the future, more attention should be paid to promoting the clinical translation of molecular imaging in evaluating the sensitivity to targeted therapy with biocompatible probes. In particular, multimodal imaging technologies incorporating advanced artificial intelligence should be developed to comprehensively and accurately assess cancer-targeted therapy, in addition to RECIST-based methods.

Early post-bevacizumab change in rCBV from DSC-MRI identifies pseudoresponse in recurrent glioblastoma: Results from ACRIN 6677/RTOG 0625

Background

Progressive enhancement predicted poor survival in ACRIN 6677/RTOG 0625, a multi-center trial of bevacizumab with irinotecan or temozolomide in recurrent glioblastoma, but pseudoresponse likely limited enhancement-based survival prognostication in T1 non-progressors. We aimed to determine whether early change in cerebral blood volume from baseline (ΔCBV) could further stratify the T1 non-progressors according to overall (OS) and progression-free (PFS) survival.

Methods

37/123 enrolled patients had DSC-MRI, including 13, 15, and 8 patients without 2D-T1 progression at 2, 8, and 16 weeks post-treatment initiation, respectively. Mean CBV normalized to white matter (nRCBV) and mean standardized CBV (sRCBV) were extracted from enhancing tumor. ROC curves were derived for ΔCBV using six-month PFS and one-year OS as reference standards. Kaplan-Meier survival estimates and log-rank test compared PFS and OS for both ΔCBV (increase vs. decrease) and T1 response status (stable vs. decreasing enhancement).

Results

PFS and OS were significantly worse for increasing CBV at 2 weeks (p=0.003 and p=0.002 for nRCBV, and p=0.03 and p=0.03 for sRCBV, respectively), but not for 2D-T1 patients with stable vs. decreasing enhancement (p=0.44 and p=0.86, respectively). ΔCBV at week 2 was also a good prognostic marker for OS-1 and PFS-6 using ROC analysis. By contrast, 2D-T1 response status at weeks 2, 8, and 16 was not associated with PFS-6. ΔCBV at 16 weeks (p=0.008 for sRCBV) but not 8 weeks (p=0.74 for nRCBV and p=0.56 for sRCBV) was associated with significant difference in median survival, but no difference in survival was observed for 2D-T1 patients with stable vs. decreasing enhancement at 8 weeks (p=0.69) or 16 weeks (p=0.21). At 16 weeks, OS did not differ significantly between 2D-T1 progressors and 2D-T1 non-progressors with increasing CBV (median survival 3.3 months post week 16 scan vs. 9.2 months, respectively; p=0.13), suggesting that 2D-T1 non-progressors with increasing CBV may have a prognosis like that of 2D-T1 progressors.

Conclusion

After 2 weeks of anti-angiogenic therapy, ΔCBV in 2D-T1 non-progressors significantly prognosticated PFS and OS, whereas 2D-T1 response status did not, identifying a subpopulation that benefits from bevacizumab. Combining 2D-T1 progression and ΔCBV may yield a response assessment paradigm with 3-tiered OS stratification.

Federated learning enables big data for rare cancer boundary detection

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing.

Dynamic Contrast-Enhanced Ultrasound Modeling of an Analog to Pseudo-Diffusivity in Intravoxel Incoherent Motion Magnetic Resonance Imaging

Tumor perfusion and vascular properties are important determinants of cancer response to therapy and thus various approaches for imaging perfusion are being explored. In particular, Intravoxel Incoherent Motion (IVIM) MRI has been actively researched as an alternative to Dynamic-Contrast-Enhanced (DCE) CT and DCE-MRI as it offers non-ionizing, non-contrast-based perfusion imaging. However, for repetitive treatment assessment in a short time period, high cost, limited access, and inability to scan at the bedside remain disadvantages of IVIM MRI. We propose an analysis framework that may enable 3D DCE Ultrasound (DCE-US) - low cost, bedside imaging with excellent safety record - as an alternative modality to IVIM MRI for the generation of DCE-US based pseudo-diffusivity maps in acoustically accessible anatomy and tumors. Modelling intravascular contrast propagation as a convective-diffusive process, we reconstruct parametric maps of pseudo-diffusivity by solving a large-scale fully coupled inverse problem without any assumptions regarding local constancy of the reconstructed parameters. In a mouse tumor model, we demonstrate that the 3D DCE-US pseudo-diffusivity is repeatable, sensitive to treatment with an antiangiogenic agent, and moderately correlated to histological measures of perfusion and angiogenesis.

Hemodynamic Imaging in Cerebral Diffuse Glioma-Part B: Molecular Correlates, Treatment Effect Monitoring, Prognosis, and Future Directions

Gliomas, and glioblastoma in particular, exhibit an extensive intra- and inter-tumoral molecular heterogeneity which represents complex biological features correlating to the efficacy of treatment response and survival. From a neuroimaging point of view, these specific molecular and histopathological features may be used to yield imaging biomarkers as surrogates for distinct tumor genotypes and phenotypes. The development of comprehensive glioma imaging markers has potential for improved glioma characterization that would assist in the clinical work-up of preoperative treatment planning and treatment effect monitoring. In particular, the differentiation of tumor recurrence or true progression from pseudoprogression, pseudoresponse, and radiation-induced necrosis can still not reliably be made through standard neuroimaging only. Given the abundant vascular and hemodynamic alterations present in diffuse glioma, advanced hemodynamic imaging approaches constitute an attractive area of clinical imaging development. In this context, the inclusion of objective measurable glioma imaging features may have the potential to enhance the individualized care of diffuse glioma patients, better informing of standard-of-care treatment efficacy and of novel therapies, such as the immunotherapies that are currently increasingly investigated. In Part B of this two-review series, we assess the available evidence pertaining to hemodynamic imaging for molecular feature prediction, in particular focusing on isocitrate dehydrogenase (IDH) mutation status, MGMT promoter methylation, 1p19q codeletion, and EGFR alterations. The results for the differentiation of tumor progression/recurrence from treatment effects have also been the focus of active research and are presented together with the prognostic correlations identified by advanced hemodynamic imaging studies. Finally, the state-of-the-art concepts and advancements of hemodynamic imaging modalities are reviewed together with the advantages derived from the implementation of radiomics and machine learning analyses pipelines.

High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 1: Perfusion and Diffusion Techniques

Objective

Summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and highlight the latest bench-to-bedside developments.

Methods

Experts in advanced MRI techniques applied to high-grade glioma treatment response assessment convened through a European framework. Current evidence regarding the potential for monitoring biomarkers in adult high-grade glioma is reviewed, and individual modalities of perfusion, permeability, and microstructure imaging are discussed (in Part 1 of two). In Part 2, we discuss modalities related to metabolism and/or chemical composition, appraise the clinic readiness of the individual modalities, and consider post-processing methodologies involving the combination of MRI approaches (multiparametric imaging) or machine learning (radiomics).

Results

High-grade glioma vasculature exhibits increased perfusion, blood volume, and permeability compared with normal brain tissue. Measures of cerebral blood volume derived from dynamic susceptibility contrast-enhanced MRI have consistently provided information about brain tumor growth and response to treatment; it is the most clinically validated advanced technique. Clinical studies have proven the potential of dynamic contrast-enhanced MRI for distinguishing post-treatment related effects from recurrence, but the optimal acquisition protocol, mode of analysis, parameter of highest diagnostic value, and optimal cut-off points remain to be established. Arterial spin labeling techniques do not require the injection of a contrast agent, and repeated measurements of cerebral blood flow can be performed. The absence of potential gadolinium deposition effects allows widespread use in pediatric patients and those with impaired renal function. More data are necessary to establish clinical validity as monitoring biomarkers. Diffusion-weighted imaging, apparent diffusion coefficient analysis, diffusion tensor or kurtosis imaging, intravoxel incoherent motion, and other microstructural modeling approaches also allow treatment response assessment; more robust data are required to validate these alone or when applied to post-processing methodologies.

Conclusion

Considerable progress has been made in the development of these monitoring biomarkers. Many techniques are in their infancy, whereas others have generated a larger body of evidence for clinical application.

High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 2: Spectroscopy, Chemical Exchange Saturation, Multiparametric Imaging, and Radiomics

Objective

To summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and to highlight the latest bench-to-bedside developments.

Methods

The current evidence regarding the potential for monitoring biomarkers was reviewed and individual modalities of metabolism and/or chemical composition imaging discussed. Perfusion, permeability, and microstructure imaging were similarly analyzed in Part 1 of this two-part review article and are valuable reading as background to this article. We appraise the clinic readiness of all the individual modalities and consider methodologies involving machine learning (radiomics) and the combination of MRI approaches (multiparametric imaging).

Results

The biochemical composition of high-grade gliomas is markedly different from healthy brain tissue. Magnetic resonance spectroscopy allows the simultaneous acquisition of an array of metabolic alterations, with choline-based ratios appearing to be consistently discriminatory in treatment response assessment, although challenges remain despite this being a mature technique. Promising directions relate to ultra-high field strengths, 2-hydroxyglutarate analysis, and the use of non-proton nuclei. Labile protons on endogenous proteins can be selectively targeted with chemical exchange saturation transfer to give high resolution images. The body of evidence for clinical application of amide proton transfer imaging has been building for a decade, but more evidence is required to confirm chemical exchange saturation transfer use as a monitoring biomarker. Multiparametric methodologies, including the incorporation of nuclear medicine techniques, combine probes measuring different tumor properties. Although potentially synergistic, the limitations of each individual modality also can be compounded, particularly in the absence of standardization. Machine learning requires large datasets with high-quality annotation; there is currently low-level evidence for monitoring biomarker clinical application.

Conclusion

Advanced MRI techniques show huge promise in treatment response assessment. The clinical readiness analysis highlights that most monitoring biomarkers require standardized international consensus guidelines, with more facilitation regarding technique implementation and reporting in the clinic.

Repeatability of tumor perfusion kinetics from dynamic contrast-enhanced MRI in glioblastoma

Background

Dynamic contrast-enhanced MRI (DCE-MRI) parameters have been shown to be biomarkers for treatment response in glioblastoma (GBM). However, variations in analysis and measurement methodology complicate determination of biological changes measured via DCE. The aim of this study is to quantify DCE-MRI variations attributable to analysis methodology and image quality in GBM patients.

Methods

The Extended Tofts model (eTM) and Leaky Tracer Kinetic Model (LTKM), with manually and automatically segmented vascular input functions (VIFs), were used to calculate perfusion kinetic parameters from 29 GBM patients with double-baseline DCE-MRI data. DCE-MRI images were acquired 2-5 days apart with no change in treatment. Repeatability of kinetic parameters was quantified with Bland-Altman and percent repeatability coefficient (%RC) analysis.

Results

The perfusion parameter with the least RC was the plasma volume fraction (v _p ), with a %RC of 53%. The extra-cellular extra-vascular volume fraction (v _e ) %RC was 82% and 81%, for extended Tofts-Kety Model (eTM) and LTKM respectively. The %RC of the volume transfer rate constant (K ^trans ) was 72% for the eTM, and 82% for the LTKM, respectively. Using an automatic VIF resulted in smaller %RCs for all model parameters, as compared to manual VIF.

Conclusions

As much as 72% change in K ^trans (eTM, autoVIF) can be attributable to non-biological changes in the 2-5 days between double-baseline imaging. Poor K ^trans repeatability may result from inferior temporal resolution and short image acquisition time. This variation suggests DCE-MRI repeatability studies should be performed institutionally, using an automatic VIF method and following quantitative imaging biomarkers alliance guidelines.

Imaging Advances for Central Nervous System Tumors

This article reviews recent advances in the use of standard and advanced imaging techniques for diagnosis and treatment of central nervous system (CNS) tumors, including glioma and brain metastasis. Following the recent transition from a histology-based approach in classifying CNS tumors to one that integrates histology with the molecular information of tumor, the approaches for imaging CNS tumors have also been adapted to this new framework. Some challenges related to the diagnosis and treatment of CNS tumors, such as differentiating tumor from treatment-related imaging changes, require further progress to implement advanced imaging for clinical use.

Volumetric study reveals the relationship between outcome and early radiographic response during bevacizumab-containing chemoradiotherapy for unresectable glioblastoma

PURPOSE

Although we have shown the clinical benefit of bevacizumab (BEV) in the treatment of unresectable newly diagnosed glioblastomas (nd-GBM), the relationship between early radiographic response and survival outcome remains unclear. We performed a volumetric study of early radiographic responses in nd-GBM treated with BEV.

METHODS

Twenty-two patients with unresectable nd-GBM treated with BEV during concurrent temozolomide radiotherapy were analyzed. An experienced neuroradiologist interpreted early responses on fluid-attenuated inversion recovery (FLAIR) and gadolinium-enhanced T1-weighted images (GdT1WI). Volumetric changes were evaluated using diffusion-weighted imaging (DWI) and GdT1WI according to the Response Assessment in Neuro-Oncology (RANO) criteria. The results were categorized into improved (complete response [CR] or partial response [PR]) or non-improved (stable disease [SD] or progressive disease [PD]) groups; outcomes were compared using Kaplan-Meier analysis.

RESULTS

The volumetric GdT1WI improvement was a significant predictive factor for overall survival (OS) prolongation (p = 0.0093, median OS: 24.7 vs. 13.6 months); however, FLAIR and DWI images were not predictive. The threshold for the neuroradiologist's interpretation of improvement in GdT1WI was nearly 20% of volume reduction, which was lesser than 50%, the definition of PR applied in the RANO criteria. However, even less stringent neuroradiologist interpretation could successfully predict OS prolongation (improved vs. non-improved: p = 0.0067, median OS: 17.6 vs. 8.3 months). Significant impact of OS on the early response in volumetric GdT1WI was observed within the cut-off range of 20-50% (20%, p = 0.0315; 30%, p = 0.087; 40%, p = 0.0456).

CONCLUSIONS

Early response during BEV-containing chemoradiation can be a predictive indicator of patient outcome in unresectable nd-GBM.