Notice Number: NOT-MH-15-010
Release Date: February 19, 2015
Response Date: March 31, 2015
National Institute of Mental Health (NIMH)
The National Institutes of Mental Health (NIMH) recognizes the increasing demands placed on biomedical researchers to share data they generate through federally-funded research projects. NIMH aims to help the scientific community understand the variety of sources that contribute to the heterogeneity of imaging data and identify solutions for harmonizing and combining data in order to maximize the utility of these valuable resources. In efforts to make these data as valuable as possible for the research community and ultimately, the general public in terms of progress on understanding and treating brain disorders, NIMH is planning a meeting with experts in the field to develop appropriate strategies.
A substantial number of imaging repositories are now accessible to the broader scientific community [e.g., National Database for Autism Research (NDAR), Pediatric MRI Data Repository, 1000 Functional Connectomes Project, the Human Connectome Project (HCP), International Neuroimaging Data Initiative (INDI), Enhancing Neuro Imaging Genetics Through Meta Analysis (ENIGMA) and others] but there remains a large barrier to extracting reliable findings from mining these data. Given that the data are collected at different sites, with different scanners and a variety of acquisition protocols, these multiple sources of variability present challenges for comparing and combining data to reach sound conclusions that could impact public health. The neuroimaging community recognizes these challenges and can serve as a resource for developing solutions.
Given the large investment in acquiring and archiving imaging data, the NIH is motivated to understand how the heterogeneity can be addressed in the analysis of data from diverse sources to yield valid, robust and generalizable findings. The goal is to identify sources of variability and develop approaches to address it when analyzing and combining data from different projects. For example, might processing pipelines be developed to account for variation in hardware, software and various protocol parameters? What image processing and statistical approaches might be used to yield the most impactful results? How might standard protocols being developed in large-scale projects, e.g., the Human Connectome Project, assist in reducing or understanding heterogeneity in imaging data going forward given remaining variations in hardware and software? Can quality control metrics be developed and applied to evaluate the quality of imaging data across projects? What systems might be developed to support large-scale use of such strategies to enable data mining?
A further consideration is whether and how heterogeneity in data acquisition might be reduced or controlled prospectively across research projects. Might a minimal standard protocol, e.g., structural T1 collected in most imaging projects, assist in evaluating and harmonizing data cross projects? Might standard phantoms provide a useful basis of comparison for assessing and reducing heterogeneity of MRI-based imaging data?
The NIMH is planning to host a satellite meeting at the June, 2015 Organization for Human Brain Mapping (OHBM) meeting to foster discussion among the experts. This Request for Information (RFI) solicits input from the community to provide guidance about the priorities of such a meeting. NIMH seeks input related to which problems are perceived to be the most pressing and what potential solutions are tangible.
With this RFI Notice, the NIMH invites interested and knowledgeable persons to inform NIMH about important issues related to quality control methods, workflow designs, metrics and other techniques for assessing and reducing such variation to ensure investments going forward are based on sound justification for maximizing the utility of shared resources. NIMH recognizes that scientific problems related to site and scanner variability may differ across different neuroimaging modalities (e.g. structural MRI, DTI, DSI, functional MRI) and therefore requests that respondents to this RFI identify challenges and best practices for specific neuroimaging modalities.
All responses must be submitted electronically by March 31, 2015, in the form of an email to email@example.com , using the subject 'Neuroimaging”. Responses to this RFI Notice are voluntary. Submitted information will not be considered confidential. Responses are welcome from associations and professional organizations as well as individual stakeholders. This request is for information and planning purposes and should not be construed as a solicitation or as an obligation of the Federal Government or NIMH. No awards will be made based on responses to this RFI. The information submitted will be analyzed and may be used for planning purposes. You will receive an electronic confirmation acknowledging receipt of your response, but will not receive individualized feedback on your submission. No proprietary, classified, confidential and/or sensitive information should be included in your response. The NIH and the government reserve the right to use any non-proprietary technical information in any future solicitation(s).
Please direct all inquiries to:
Michelle Freund, Ph.D.
National Institute of Mental Health (NIMH)