A Neuroradiologist's Guide to Operationalizing the Response Assessment in Neuro-Oncology (RANO) Criteria Version 2.0 for Gliomas in Adults.

Radiographic assessment plays a crucial role in the management of patients with central nervous system (CNS) tumors, aiding in treatment planning and evaluation of therapeutic efficacy by quantifying response. Recently, an updated version of the Response Assessment in Neuro-Oncology (RANO) criteria (RANO 2.0) was developed to improve upon prior criteria and provide an updated, standardized framework for assessing treatment response in clinical trials for gliomas in adults. This article provides an overview of significant updates to the criteria including (1) the use of a unified set of criteria for high and low grade gliomas in adults; (2) the use of the post-radiotherapy MRI scan as the baseline for evaluation in newly diagnosed high-grade gliomas; (3) the option for the trial to mandate a confirmation scan to more reliably distinguish pseudoprogression from tumor progression; (4) the option of using volumetric tumor measurements; and (5) the removal of subjective non-enhancing tumor evaluations in predominantly enhancing gliomas (except for specific therapeutic modalities). Step-by-step pragmatic guidance is hereby provided for the neuroradiologist and imaging core lab involved in operationalization and technical execution of RANO 2.0 in clinical trials, including the display of representative cases and in-depth discussion of challenging scenarios.ABBREVIATIONS: BTIP = Brain Tumor Imaging Protocol; CE = Contrast-Enhancing; CNS = Central Nervous System; CR = Complete Response; ECOG = Eastern Cooperative Oncology Group; HGG = High-Grade Glioma; IDH = Isocitrate Dehydrogenase; IRF = Independent Radiologic Facility; LGG = Low-Grade Glioma; KPS = Karnofsky Performance Status; MR = Minor Response; mRANO = Modified RANO; NANO = Neurological Assessment in Neuro-Oncology; ORR = Objective Response Rate; OS = Overall Survival; PD = Progressive Disease; PFS = Progression-Free Survival; PR = Partial Response; PsP = Pseudoprogression; RANO = Response Assessment in Neuro-Oncology; RECIST = Response Evaluation Criteria In Solid Tumors; RT = Radiation Therapy; SD = Stable Disease; Tx = Treatment.

RANO 2.0: Update to the Response Assessment in Neuro-Oncology Criteria for High- and Low-Grade Gliomas in Adults.

PURPOSE: The Response Assessment in Neuro-Oncology (RANO) criteria for high-grade gliomas (RANO-HGG) and low-grade gliomas (RANO-LGG) were developed to improve reliability of response assessment in glioma trials. Over time, some limitations of these criteria were identified, and challenges emerged regarding integrating features of the modified RANO (mRANO) or the immunotherapy RANO (iRANO) criteria. METHODS: Informed by data from studies evaluating the different criteria, updates to the RANO criteria are proposed (RANO 2.0). RESULTS: We recommend a standard set of criteria for both high- and low-grade gliomas, to be used for all trials regardless of the treatment modalities being evaluated. In the newly diagnosed setting, the postradiotherapy magnetic resonance imaging (MRI), rather than the postsurgical MRI, will be used as the baseline for comparison with subsequent scans. Since the incidence of pseudoprogression is high in the 12 weeks after radiotherapy, continuation of treatment and confirmation of progression during this period with a repeat MRI, or histopathologic evidence of unequivocal recurrent tumor, are required to define tumor progression. However, confirmation scans are not mandatory after this period nor for the evaluation of treatment for recurrent tumors. For treatments with a high likelihood of pseudoprogression, mandatory confirmation of progression with a repeat MRI is highly recommended. The primary measurement remains the maximum cross-sectional area of tumor (two-dimensional) but volumetric measurements are an option. For IDH wild-type glioblastoma, the nonenhancing disease will no longer be evaluated except when assessing response to antiangiogenic agents. In IDH-mutated tumors with a significant nonenhancing component, clinical trials may require evaluating both the enhancing and nonenhancing tumor components for response assessment. CONCLUSION: The revised RANO 2.0 criteria refine response assessment in gliomas.

Meta-Analysis of the Test-Retest Repeatability of [18F]-Fluorodeoxyglucose Standardized Uptake Values: Implications for Assessment of Tumor Response.

PURPOSE: Currently, guidelines for PET with 18F-fluorodeoxyglucose (FDG-PET) interpretation for assessment of therapy response in oncology primarily involve visual evaluation of FDG-PET/CT scans. However, quantitative measurements of the metabolic activity in tumors may be even more useful in evaluating response to treatment. Guidelines based on such measurements, including the European Organization for Research and Treatment of Cancer Criteria and PET Response Criteria in Solid Tumors, have been proposed. However, more rigorous analysis of response criteria based on FDG-PET measurements is needed to adopt regular use in practice. EXPERIMENTAL DESIGN: Well-defined boundaries of repeatability and reproducibility of quantitative measurements to discriminate noise from true signal changes are a needed initial step. An extension of the meta-analysis from de Langen and colleagues (2012) of the test-retest repeatability of quantitative FDG-PET measurements, including mean, maximum, and peak standardized uptake values (SUVmax, SUVmean, and SUVpeak, respectively), was performed. Data from 11 studies in the literature were used to estimate the relationship between the variance in test-retest measurements with uptake level and various study-level, patient-level, and lesion-level characteristics. RESULTS: Test-retest repeatability of percentage fluctuations for all three types of SUV measurement (max, mean, and peak) improved with higher FDG uptake levels. Repeatability in all three SUV measurements varied for different lesion locations. Worse repeatability in SUVmean was also associated with higher tumor volumes. CONCLUSIONS: On the basis of these results, recommendations regarding SUV measurements for assessing minimal detectable changes based on repeatability and reproducibility are proposed. These should be applied to differentiate between response categories for a future set of FDG-PET-based criteria that assess clinically significant changes in tumor response.

A comparison of FLT to FDG PET/CT in the early assessment of chemotherapy response in stages IB-IIIA resectable NSCLC.

BACKGROUND: The aim of this study was to compare the percentage change in 18F-fluorothymidine (FLT) standard uptake value (SUV) between baseline and after one cycle of chemotherapy in patients categorized by RECIST 1.1 computed tomography (CT) as responders or non-responders after two cycles of therapy. Change in 18F-fluorodeoxyglucose (FDG) uptake was also compared between these time points. Nine patients with newly diagnosed, operable, non-small cell lung cancer (NSCLC) were imaged with FDG positron emission tomography/CT (PET), FLT PET/CT, and CT at baseline, following one cycle of neoadjuvant therapy (75 mg/m2 docetaxel + 75 mg/m2 cisplatin), and again after the second cycle of therapy. All patients had a biopsy prior to enrollment and underwent surgical resection within 4 weeks of post-cycle 2 imaging. RESULTS: Between baseline and post-cycle 1, non-responders had mean SULmax (maximum standard uptake value adjusted for lean body mass) increases of 7.0 and 3.4% for FDG and FLT, respectively. Responders had mean decreases of 44.8 and 32.0% in FDG and FLT SULmax, respectively, between baseline and post-cycle 1 imaging. On post-cycle 1 imaging, primary tumor FDG SUL values were significantly lower in responders than in non-responders (P = 0.016). Primary tumor FLT SUL values did not differ significantly between these groups. Using the change from baseline to post-cycle 1, receiver-operating characteristic (ROC) analysis showed an area under the curve (AUC) of 0.94 for FDG and 0.78 for FLT in predicting anatomic tumor response after the second cycle of therapy. CONCLUSIONS: Fractional decrease in FDG SULmax from baseline to post-cycle 1 imaging was significantly different between anatomic responders and non-responders, while percentage changes in FLT SULmax were not significantly different between these groups over the same period of time.

Clinical Translation of the National Institutes of Health's Investments in Nanodrug Products and Devices.

The National Institutes of Health (NIH), a part of the U.S. Department of Health and Human Services, is the primary Federal agency for conducting and supporting biomedical research. The NIH's mission is to seek fundamental knowledge about the nature and behavior of living systems and to apply that knowledge to enhance health, lengthen life, and reduce illness and disability. In support of this mission, NIH has invested about $4.4 billion since 2001 in nanotechnology (NT) research. This investment is leading to fundamental changes in understanding biological processes in health and disease, as well as enabling novel diagnostics and interventions for treating disease. NIH scientists are developing molecular agents and methods for earlier and more accurate diagnosis and therapies aimed directly and selectively at diseased cells, and are exploring root causes of common and rare diseases at the nanoscale. Work is also underway to move these research tools and devices into clinical practice. This particular investigative review examines the NIH NT portfolio linked to clinical trials from FY2008 to FY2015 to assess the progress of clinical translation. Among the subset of trials identified, 70% target drug or combination drug-device products used in treating cancer, AIDS, and other various diseases. The review also provides insight into trends observed from studying the clinical research portfolio.

A risk management approach for imaging biomarker-driven clinical trials in oncology.

Imaging has steadily evolved in clinical cancer research as a result of improved conventional imaging methods and the innovation of new functional and molecular imaging techniques. Despite this evolution, the design and data quality derived from imaging within clinical trials are not ideal and gaps exist with paucity of optimised methods, constraints of trial operational support, and scarce resources. Difficulties associated with integrating imaging biomarkers into trials have been neglected compared with inclusion of tissue and blood biomarkers, largely because of inherent challenges in the complexity of imaging technologies, safety issues related to new imaging contrast media, standardisation of image acquisition across multivendor platforms, and various postprocessing options available with advanced software. Ignorance of these pitfalls directly affects the quality of the imaging read-out, leading to trial failure, particularly when imaging is a primary endpoint. Therefore, we propose a practical risk-based framework and recommendations for trials driven by imaging biomarkers, which allow identification of risks at trial initiation to better allocate resources and prioritise key tasks.