Cole, Patricia E.

Abstract Determination of therapeutic benefit in intracranial tumors is intimately dependent on serial assessment of radiographic images. The Response Assessment in Neuro-Oncology (RANO) criteria were established in 2010 to provide an updated framework to better characterize tumor response to contemporary treatments. Since this initial update a number of RANO criteria have provided some basic principles for the interpretation of changes on MR images; however, the details of how to operationalize RANO and other criteria for use in clinical trials are ambiguous and not standardized. In this review article designed for the neuro-oncologist or treating clinician, we outline essential steps for performing radiographic assessments by highlighting primary features of the Imaging Charter (referred to as the Charter for the remainder of this article), a document that describes the clinical trial imaging methodology and methods to ensure operationalization of the Charter into the workings of a clinical trial. Lastly, we provide recommendations for specific changes to optimize this methodology for neuro-oncology, including image registration, requirement of growing tumor for eligibility in trials of recurrent tumor, standardized image acquisition guidelines, and hybrid reader paradigms that allow for both unbiased measurements and more comprehensive interpretation.

AbstractBackgroundLow HCV has recently been qualified by the European Medicines Agency as a biomarker for enrichment of clinical trials in predementia stages of Alzheimer's disease. For automated methods to meet the necessary regulatory requirements, it is essential they be standardized and their performance be well characterized.MethodsThe within‐image and between‐field strength reproducibility of automated hippocampal volumetry using the Learning Embeddings for Atlas Propagation (or LEAP) algorithm was assessed on 153 Alzheimer's Disease Neuroimaging Initiative subjects.ResultsTests/retests at 1.5 T and 3 T, and a comparison between 1.5 T and 3 T, yielded average unsigned variabilities in HCVs of 1.51%, 1.52%, and 2.68%. A small bias between field strengths (mean signed difference, 1.17%; standard deviation, 3.07%) was observed.ConclusionsThe measured reproducibility characteristics confirm the suitability of using automated magnetic resonance imaging analyses to assess HCVs quantitatively and to represent a fundamental characterization that is critical to meet the regulatory requirements for using hippocampal volumetry in clinical trials and health care.

AbstractBackgroundRegulatory qualification of a biomarker for a defined context of use provides scientifically robust assurances to sponsors and regulators that accelerate appropriate adoption of biomarkers into drug development.MethodsThe Coalition Against Major Diseases submitted a dossier to the Scientific Advice Working Party of the European Medicines Agency requesting a qualification opinion on the use of hippocampal volume as a biomarker for enriching clinical trials in subjects with mild cognitive impairment, incorporating a scientific rationale, a literature review and a de novo analysis of Alzheimer's Disease Neuroimaging Initiative data.ResultsThe literature review and de novo analysis were consistent with the proposed context of use, and the Committee for Medicinal Products for Human Use released an opinion in November 2011.ConclusionsWe summarize the scientific rationale and the data that supported the first qualification of an imaging biomarker by the European Medicines Agency.

AbstractThe Alzheimer's Disease Neuroimaging Initiative (ADNI) three‐dimensional T1‐weighted magnetic resonance imaging (MRI) acquisitions provide a rich data set for developing and testing analysis techniques for extracting structural endpoints. To promote greater rigor in analysis and meaningful comparison of different algorithms, the ADNI MRI Core has created standardized analysis sets of data comprising scans that met minimum quality control requirements. We encourage researchers to test and report their techniques against these data. Standard analysis sets of volumetric scans from ADNI‐1 have been created, comprising screening visits, 1‐year completers (subjects who all have screening, 6‐ and 12‐month scans), 2‐year annual completers (screening, 1‐year and 2‐year scans), 2‐year completers (screening, 6‐months, 1‐year, 18‐months [mild cognitive impaired (MCI) only], and 2‐year scans), and complete visits (screening, 6‐month, 1‐year, 18‐month [MCI only], 2‐year, and 3‐year [normal and MCI only] scans). As the ADNI‐GO/ADNI‐2 data become available, updated standard analysis sets will be posted regularly.

BackgroundThe promise of Alzheimer's disease biomarkers has led to their incorporation in new diagnostic criteria and in therapeutic trials; however, significant barriers exist to widespread use. Chief among these is the lack of internationally accepted standards for quantitative metrics. Hippocampal volumetry is the most widely studied quantitative magnetic resonance imaging measure in Alzheimer's disease and thus represents the most rational target for an initial effort at standardization.Methods and ResultsThe authors of this position paper propose a path toward this goal. The steps include the following: (1) Establish and empower an oversight board to manage and assess the effort, (2) adopt the standardized definition of anatomic hippocampal boundaries on magnetic resonance imaging arising from the European Alzheimer's Disease Centers–Alzheimer's Disease Neuroimaging Initiative hippocampal harmonization effort as a reference standard, (3) establish a scientifically appropriate, publicly available reference standard data set based on manual delineation of the hippocampus in an appropriate sample of subjects (Alzheimer's Disease Neuroimaging Initiative), and (4) define minimum technical and prognostic performance metrics for validation of new measurement techniques using the reference standard data set as a benchmark.ConclusionsAlthough manual delineation of the hippocampus is the best available reference standard, practical application of hippocampal volumetry will require automated methods. Our intent was to establish a mechanism for credentialing automated software applications to achieve internationally recognized accuracy and prognostic performance standards that lead to the systematic evaluation and then widespread acceptance and use of hippocampal volumetry. The standardization and assay validation process outlined for hippocampal volumetry was envisioned as a template that could be applied to other imaging biomarkers.