Technological developments and greater rigor in the quantitative measurement of biological features in medical images have given rise to an increased interest in using quantitative imaging biomarkers (QIBs) to measure changes in these features. Critical to the performance of a QIB in preclinical or clinical settings are three primary metrology areas of interest: measurement linearity and bias, repeatability, and the ability to consistently reproduce equivalent results when conditions change, as would be expected in any clinical trial. Unfortunately, performance studies to date differ greatly in designs, analysis method and metrics used to assess a QIB for clinical use. It is therefore, difficult or not possible to integrate results from different studies or to use reported results to design studies. The Radiological Society of North America (RSNA) and the Quantitative Imaging Biomarker Alliance (QIBA) with technical, radiological and statistical experts developed a set of technical performance analysis methods, metrics and study designs that provide terminology, metrics and methods consistent with widely accepted metrological standards. This document provides a consistent framework for the conduct and evaluation of QIB performance studies so that results from multiple studies can be compared, contrasted or combined.

Since 1990, the primary criteria used for assessing response to therapy in high-grade gliomas were those developed by Macdonald and colleagues, which incorporated 2-dimensional area measurements of contrast-enhancing tumor regions, corticosteroid dosing, and clinical assessment to arrive at a designation of response, stable disease, or progression. Recent advances in imaging technology and targeted therapeutics, however, have exposed limitations of the Macdonald criteria and have highlighted the need for reevaluation of response assessment criteria. In 2010, the Response Assessment in Neuro-Oncology (RANO) Working Group published updated criteria to address this need and to standardize response assessment for high-grade gliomas. In 2009, prior to the publication of the RANO criteria, the randomized, placebo-controlled, multicenter, phase 3 AVAglio trial was designed and initiated to investigate the effectiveness of radiotherapy and temozolomide with or without bevacizumab in newly diagnosed glioblastoma. The AVAglio protocol enacted specific measures to adapt the Macdonald criteria to the frontline treatment setting and to antiangiogenic agent evaluation, including the incorporation of a T2/fluid-attenuated inversion recovery component, qualitative assessment of irregularly shaped contrast-enhancing lesions, and a decision tree for confirming or ruling out pseudoprogression. Moreover, the protocol outlines practical means by which these adapted response criteria can be implemented in the clinic. This article describes the evolution of radiographic response criteria for high-grade gliomas and highlights the similarities and differences between those implemented in the AVAglio study and those subsequently published by RANO.

Medical imaging serves many roles in patient care and the drug approval process, including assessing treatment response and guiding treatment decisions. These roles often involve a quantitative imaging biomarker, an objectively measured characteristic of the underlying anatomic structure or biochemical process derived from medical images. Before a quantitative imaging biomarker is accepted for use in such roles, the imaging procedure to acquire it must undergo evaluation of its technical performance, which entails assessment of performance metrics such as repeatability and reproducibility of the quantitative imaging biomarker. Ideally, this evaluation will involve quantitative summaries of results from multiple studies to overcome limitations due to the typically small sample sizes of technical performance studies and/or to include a broader range of clinical settings and patient populations. This paper is a review of meta-analysis procedures for such an evaluation, including identification of suitable studies, statistical methodology to evaluate and summarize the performance metrics, and complete and transparent reporting of the results. This review addresses challenges typical of meta-analyses of technical performance, particularly small study sizes, which often causes violations of assumptions underlying standard meta-analysis techniques. Alternative approaches to address these difficulties are also presented; simulation studies indicate that they outperform standard techniques when some studies are small. The meta-analysis procedures presented are also applied to actual [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) test–retest repeatability data for illustrative purposes.

In this paper, we review the results of BIOINFOMED, a study funded by the European Commission (EC) with the purpose to analyse the different issues and challenges in the area where Medical Informatics and Bioinformatics meet. Traditionally, Medical Informatics has been focused on the intersection between computer science and clinical medicine, whereas Bioinformatics have been predominantly centered on the intersection between computer science and biological research. Although researchers from both areas have occasionally collaborated, their training, objectives and interests have been quite different. The results of the Human Genome and related projects have attracted the interest of many professionals, and introduced new challenges that will transform biomedical research and health care. A characteristic of the 'post genomic' era will be to correlate essential genotypic information with expressed phenotypic information. In this context, Biomedical Informatics (BMI) has emerged to describe the technology that brings both disciplines (BI and MI) together to support genomic medicine. In recognition of the dynamic nature of BMI, institutions such as the EC have launched several initiatives in support of a research agenda, including the BIOINFOMED study.

Determination of tumor response to treatment in neuro-oncology is challenging, particularly when antiangiogenic agents are considered. Nontumoral factors (eg, blood-brain barrier disruption, edema, and necrosis) can alter contrast enhancement independent of true tumor response/progression. Furthermore, gliomas are often infiltrative, with nonenhancing components. In adults, the Response Assessment in Neuro-Oncology (RANO) criteria attempted to address these issues. No such guidelines exist yet for children. The ongoing randomized phase II trial, A Study of Avastin (bevacizumab) in Combination With Temolozomide (TMZ) and Radiotherapy in Paediatric and Adolescent Patients With High-Grade Glioma (HERBY), will establish the efficacy and safety of the antiangiogenic agent bevacizumab for the first-line treatment of newly diagnosed high-grade glioma in children (n = 121 patients, enrollment complete). The primary end point is event-free survival (tumor progression/recurrence by central review, second primary malignancy, or death). Determination of progression or response is based on predefined clinical and radiographic criteria, modeled on the RANO criteria and supported by expert pseudoprogression review and the use of standardized imaging protocols. The HERBY trial will also compare conventional MR imaging (T1-weighted and T2/fluid-attenuated inversion recovery sequences) with conventional MR imaging plus diffusion/perfusion imaging for response assessment. It is anticipated that HERBY will provide new insights into antiangiogenic-treated pediatric brain tumors. HERBY will also investigate the practicality of obtaining adequate quality diffusion/perfusion scans in a trial setting, and the feasibility of implementing standard imaging protocols across multiple sites. To date, 61/73 (83.6%) patients with available data have completed diffusion-weighted imaging (uptake of other nonconventional techniques has been limited). Harmonization of imaging protocols and techniques may improve the robustness of pediatric neuro-oncology studies and aid future trial comparability.