The Cancer Imaging Archive (TCIA) is intended to be a resource to the research community. As such, an Advisory Group was formed to ensure that every dataset in the archive is one that would be of value to our target audiences. When researchers submit applications to the Advisory Group for consideration the following questions are used to help determine their value to the research community:
- How important is this data set to facilitating research reproducibility in this topic area?
- Does this dataset address a data gap for critical current research for a clinical need?
- Is this a novel/unique dataset compared to what’s already in TCIA?
- Is the dataset of a sufficient size/scale to support scientific conclusions or hypothesis development?
- Does the dataset contain sufficient supporting data and documentation?
- If the dataset consists of an analysis of image based data, is it based on a biological hypothesis or other proposed discovery about the patho-physiological basis of cancer?
The TCIA Advisory Group reviews each candidate collection based on the criteria above and the availability of resources, and decides whether to accept, reject, or ask for clarifications for each candidate collection. Preference is given to data sets which can be fully public and do not require any application process or data use agreements. Proposals which contain supporting non-image data (e.g. patient outcomes, training classifiers/labels, tumor segmentations) are highly preferred to those which lack these characteristics. The Advisory Group is composed of staff from the National Cancer Institute (NCI) and Frederick National Laboratory for Cancer Research (FNLCR) who are experts in cancer imaging, informatics and related technologies. The current membership includes:
- Janet Eary, Associate Director, NCI Cancer Imaging Program
- Lalitha Shankar, Branch Chief, NCI Cancer Imaging Program
- Irina A. Lubensky, Chief, NCI Cancer Diagnosis Program
- Krishnan Patel, Assistant Research Physician, Radiation Oncology Branch, Center for Cancer Research