Harnessing imaging tools to guide immunotherapy trials: summary from the National Cancer Institute Cancer Imaging Steering Committee workshop.

As the immuno-oncology field continues the rapid growth witnessed over the past decade, optimising patient outcomes requires an evolution in the current response-assessment guidelines for phase 2 and 3 immunotherapy clinical trials and clinical care. Additionally, investigational tools-including image analysis of standard-of-care scans (such as CT, magnetic resonance, and PET) with analytics, such as radiomics, functional magnetic resonance agents, and novel molecular-imaging PET agents-offer promising advancements for assessment of immunotherapy. To document current challenges and opportunities and identify next steps in immunotherapy diagnostic imaging, the National Cancer Institute Clinical Imaging Steering Committee convened a meeting with diverse representation among imaging experts and oncologists to generate a comprehensive review of the state of the field.

iRECIST: guidelines for response criteria for use in trials testing immunotherapeutics.

Tumours respond differently to immunotherapies compared with chemotherapeutic drugs, raising questions about the assessment of changes in tumour burden-a mainstay of evaluation of cancer therapeutics that provides key information about objective response and disease progression. A consensus guideline-iRECIST-was developed by the RECIST working group for the use of modified Response Evaluation Criteria in Solid Tumours (RECIST version 1.1) in cancer immunotherapy trials, to ensure consistent design and data collection, facilitate the ongoing collection of trial data, and ultimate validation of the guideline. This guideline describes a standard approach to solid tumour measurements and definitions for objective change in tumour size for use in trials in which an immunotherapy is used. Additionally, it defines the minimum datapoints required from future trials and those currently in development to facilitate the compilation of a data warehouse to use to later validate iRECIST. An unprecedented number of trials have been done, initiated, or are planned to test new immune modulators for cancer therapy using a variety of modified response criteria. This guideline will allow consistent conduct, interpretation, and analysis of trials of immunotherapies.

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.

Resource requirements to accelerate clinical applications of next generation sequencing and radiomics: Workshop commentary and review.

The National Institutes of Health (NIH)/U.S. Food and Drug Administration (FDA) Joint Leadership Council Next-Generation Sequencing (NGS) and Radiomics Working Group (NGS&R WG) was formed by the NIH/FDA Joint Leadership Council to promote the development and validation of innovative NGS tests, radiomic tools, and associated data analysis and interpretation enhanced by artificial intelligence (AI) and machine-learning (ML) technologies. A two-day workshop was held on September 29-30, 2021 to convene members of the scientific community to discuss how to overcome the "ground truth" gap that has frequently been acknowledged as one of the limiting factors impeding high-quality research, development, validation, and regulatory science in these fields. This report provides a summary of the resource gaps identified by the WG and attendees, highlights existing resources and the ways they can potentially be leveraged to accelerate growth in these fields, and presents opportunities to support NGS and radiomic tool development and validation using technologies such as AI and ML.

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.

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.

Criteria for the translation of radiomics into clinically useful tests.

Computer-extracted tumour characteristics have been incorporated into medical imaging computer-aided diagnosis (CAD) algorithms for decades. With the advent of radiomics, an extension of CAD involving high-throughput computer-extracted quantitative characterization of healthy or pathological structures and processes as captured by medical imaging, interest in such computer-extracted measurements has increased substantially. However, despite the thousands of radiomic studies, the number of settings in which radiomics has been successfully translated into a clinically useful tool or has obtained FDA clearance is comparatively small. This relative dearth might be attributable to factors such as the varying imaging and radiomic feature extraction protocols used from study to study, the numerous potential pitfalls in the analysis of radiomic data, and the lack of studies showing that acting upon a radiomic-based tool leads to a favourable benefit-risk balance for the patient. Several guidelines on specific aspects of radiomic data acquisition and analysis are already available, although a similar roadmap for the overall process of translating radiomics into tools that can be used in clinical care is needed. Herein, we provide 16 criteria for the effective execution of this process in the hopes that they will guide the development of more clinically useful radiomic tests in the future.

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.

Considerations on Integrating Prostate-Specific Membrane Antigen Positron Emission Tomography Imaging Into Clinical Prostate Cancer Trials by National Clinical Trials Network Cooperative Groups.

PURPOSE: As prostate-specific membrane antigen (PSMA) positron emission tomography (PET) becomes increasingly available in the United States, the greater sensitivity of the technology in comparison to conventional imaging poses challenges for clinical trials. The NCI Clinical Imaging Steering Committee (CISC) PSMA PET Working Group was convened to coordinate the identification of these challenges in various clinical scenarios and to develop consensus recommendations on how best to integrate PSMA PET into ongoing and upcoming National Clinical Trials Network (NCTN) trials. METHODS: NCI CISC and NCI Genitourinary Steering Committee members and leadership nominated clinicians, biostatisticians, patient advocates, and other imaging experts for inclusion in the PSMA PET Working Group. From April to July 2021, the working group met independently and in conjunction with the CISC to frame challenges, including stage migration, response assessment, trial logistics, and statistical challenges, and to discuss proposed solutions. An anonymous, open-ended survey was distributed to members to collect feedback on challenges faced. Representatives from each NCTN group were invited to present an overview of affected trials. From these discussions, the consensus document was developed and circulated for the inclusion of multiple rounds of feedback from both the Working Group and CISC. RESULTS: The current consensus document outlines the key challenges for clinical prostate cancer trials resulting from the increasing availability of PSMA PET. We discuss implications for patient selection and definition of end points and provide guidance and potential solutions for different clinical scenarios, particularly with regard to best practices in defining eligibility criteria and outcome measures. RECOMMENDATIONS: This article provides guidance regarding clinical trial design and conduct, and the interpretation of trial results.

Considerations for the use of imaging tools for phase II treatment trials in oncology.

In the context of assessing tumor response, imaging tools have the potential to play a vital role in phase II and III treatment trials. If the imaging test is able to predict potential phase III success in a reliable fashion, it would be a useful tool in phase II trial design as it may provide for a more rapid and timely response assessment. The benefits and challenges of using anatomic imaging measures as well as the promising molecular imaging measures, primarily fluorodeoxyglucose-positron emission tomography, are discussed here. The general issues related to successful implementation of advanced imaging in the context of phase II treatment trials are discussed.

Correction to: a Phase 2 Study of 16α-[18F]-Fluoro-17ß-Estradiol Positron Emission Tomography (FES-PET) as a Marker of Hormone Sensitivity in Metastatic Breast Cancer (MBC).

Two data points from Table 1. (continued) were published in error. The corrected data in Table 1. (continued) are shown, in italic, below.

Immune Modulation Therapy and Imaging: Workshop Report.

A workshop at the National Cancer Institute on May 2, 2016, considered the current state of imaging in assessment of immunotherapy. Immunotherapy has shown some remarkable and prolonged responses in the treatment of tumors. However, responses are variable and frequently delayed, complicating the evaluation of new immunotherapy agents and customizing treatment for individual patients. Early anatomic imaging may show that a tumor has increased in size, but this could represent pseudoprogression. On the basis of imaging, clinicians must decide if they should stop, pause, or continue treatment. Other imaging technologies and approaches are being developed to improve the measurement of response in patients receiving immunotherapy. Imaging methods that are being evaluated include radiomic methods using CT, MRI, and 18F-FDG PET, as well as new radiolabeled small molecules, antibodies, and antibody fragments to image the tumor microenvironment, immune status, and changes over the course of therapy. Current studies of immunotherapy can take advantage of these available imaging options to explore and validate their use. Collection of CT, PET, and MR images along with outcomes from trials is critical to develop improved methods of assessment.

FDG-PET lymphoma demonstration project invitational workshop.

The proceedings of a workshop focusing on a project to evaluate the use of fluorodeoxyglucose-positron emission tomography (FDG-PET) as a tool to measure treatment response in non-Hodgkin lymphoma (NHL) are described. Sponsored by the Leukemia & Lymphoma Society, the Foundation of the National Institutes of Health, and the National Cancer Institute, and attended by representatives of the Food and Drug Administration, the Centers for Medicare and Medicaid Services, and scientists and clinical researchers from academia and the pharmaceutical and medical imaging industries, the workshop reviewed the etiology and current standards of care for NHL and proposed the development of a clinical trial to validate FDG-PET imaging techniques as a predictive biomarker for cancer therapy response. As organized under the auspices of the Oncology Biomarker Qualification Initiative, the three federal health agencies and their private sector and nonprofit/advocacy group partners believe that FDG-PET not only demonstrates the potential to be used for the diagnosis and staging of many cancers but in particular can provide an early indication of therapeutic response that is well correlated with clinical outcomes for chemotherapy for this common form of lymphoma. The development of standardized criteria for FDG-PET imaging and establishment of procedures for transmission, storage, quality assurance, and analysis of PET images afforded by this demonstration project could streamline clinical trials of new treatments for more intractable forms of lymphoma and other cancers and, hence, accelerate new drug approvals.

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.

Beyond Correlations, Sensitivities, and Specificities: A Roadmap for Demonstrating Utility of Advanced Imaging in Oncology Treatment and Clinical Trial Design.

Despite the widespread belief that advanced imaging should be very helpful in guiding oncology treatment decision and improving efficiency and success rates in treatment clinical trials, its acceptance has been slow. Part of this is likely attributable to gaps in study design and statistical methodology for these imaging studies. Also, results supporting the performance of the imaging in these roles have largely been insufficient to justify their use within the design of a clinical trial or in treatment decision making. Statistically significant correlations between the imaging results and clinical outcomes are often incorrectly taken as evidence of adequate performance. Assessments of whether the imaging can outperform standard techniques or meaningfully supplement them are also frequently neglected. This paper provides guidance on study designs and statistical analyses for evaluating the performance of advanced imaging in the various roles in treatment decision guidance and clinical trial conduct. Relevant methodology from the imaging literature is reviewed; gaps in the literature are addressed using related concepts from the more extensive genomic and in vitro biomarker literature.

Beyond Correlations, Sensitivities, and Specificities: Case Examples of the Evaluation of Advanced Imaging in Oncology Clinical Trials and Cancer Treatment.

Although advanced imaging is an important component of oncology clinical trials, there has not been a lot of success in advancing its use from a research perspective. One likely reason is the lack of consensus on the methodology used to study advanced imaging in trials, which results in a disconcerted research effort and produces data that are difficult to collate for use in validating the imaging components being studied. Imaging is used in cancer clinical trials for various indications, and the study design needed to evaluate the imaging in a particular indication will vary. Through case examples, this paper will discuss how advanced imaging is currently being investigated in oncology clinical trials, categorized by the potential clinical indication for the imaging tool and offer suggestions on how development should proceed to further evaluate imaging in the given indication. Available National Cancer Institute resources that can assist in this process will also be discussed.

Guidelines for quality control of PET/CT scans in a multicenter clinical study.

To date, there is no published detailed checklist with parameters referencing the DICOM tag information with respect to the quality control (QC) of PET/CT scans. The aims of these guidelines are to provide the know-how for effectively controlling the quality of PET/CT scans in multicenter studies, to standardize the QC, to give sponsors and regulatory agencies a basis for justification of the data quality when using standardized uptake values as an imaging biomarker, to document the compliance with the imaging guidelines, to verify the per protocol population versus intent to treat population, and to safeguard the validity of multicenter study conclusions employing standardized uptake value (SUV) as an imaging biomarker which is paramount to the scientific community. Following the proposed guidelines will ensure standardized prospective imaging QC of scans applicable to most studies where SUVs are used as an imaging biomarker. The multitude of factors affecting SUV measurements when not controlled inflicts noise on the data. Decisions on patient management with substantial noise would be devastating to patients, ultimately undermine treatment outcome, and invalidate the utility of SUV as an imaging biomarker usefulness. Strict control of the data quality used for the validation of SUV as an imaging biomarker would ensure trust and reliability of the data.

Qualification of National Cancer Institute-Designated Cancer Centers for Quantitative PET/CT Imaging in Clinical Trials.

The National Cancer Institute developed the Centers for Quantitative Imaging Excellence (CQIE) initiative in 2010 to prequalify imaging facilities at all of the National Cancer Institute-designated comprehensive and clinical cancer centers for oncology trials using advanced imaging techniques, including PET. Here we review the CQIE PET/CT scanner qualification process and results in detail. Methods: Over a period of approximately 5 y, sites were requested to submit a variety of phantoms, including uniform and American College of Radiology-approved phantoms, PET/CT images, and examples of clinical images. Submissions were divided into 3 distinct time periods: initial submission (T0) and 2 requalification submissions (T1 and T2). Images were analyzed using standardized procedures, and scanners received a pass or fail designation. Sites had the opportunity to submit new data for scanners that failed. Quantitative results were compared across scanners within a given time period and across time periods for a given scanner. Results: Data from 65 unique PET/CT scanners across 56 sites were submitted for CQIE T0 qualification; 64 scanners passed the qualification. Data from 44 (68%) of those 65 scanners were submitted for T2. From T0 to T2, the percentage of scanners passing the CQIE qualification on the first attempt rose from 38% for T1 to 67% for T2. The most common reasons for failure were SUV outside specifications, incomplete submission, and uniformity issues. Uniform phantom and American College of Radiology-approved phantom results between scanner manufacturers were similar. Conclusion: The results of the CQIE process showed that periodic requalification may decrease the frequency of deficient data submissions. The CQIE project also highlighted the concern within imaging facilities about the burden of maintaining different qualifications and accreditations. Finally, for quantitative imaging-based trials, further evaluation of the relationships between the level of the qualification (e.g., bias or precision) and the quality of the image data, accrual rates, and study power is needed.