Scope of the MIABIS Digital Pathology (individual level)
Motivation
The fields of medicine and pathology are increasingly relying on Digital Pathology and AI algorithms. Digital Pathology involves converting glass slides into digital images that can be analysed using computer algorithms. AI algorithms are being developed to help in diagnose diseases such as cancer and predict patient outcomes, helping to make informed treatment decisions. The generation of large volumes of Whole Slide Imaging (WSI) datasets requires cataloguing at both the resource and the individual patient/case/digital specimen level.
Scope
- SECONDARY USE: Whole Slide Image (WSI) catalogues for research, AI algorithm development.
- DEFINITION OF CORE ATTRIBUTES: A minimal set of essential attributes for both physical specimens (e.g., tissue blocks and slides) and their digitised counterparts (scanned images).
- INTEGRATION WITH BBMRI-ERIC FRAMEWORKS: Embedded in the MIABIS and BBMRI-ERIC IT frameworks for standardised data sharing and interoperability.
Methodology
- Alignment and harmonisation of existing standards such as DICOM DP, LOINC, SNOMED-CT, together with metadata models from various EC-funded projects, including BigPicture, ProCAncer, EUCanImage, INCISIVECDM, CHAIMELEON, and PRIMAGE.
- Incorporate the expertise of different stakeholders.
- Implementation of reference examples within BBMRI-ERIC hosted datasets, such as the BBMRI-ERIC Colorectal Cancer Cohort
Groups of Attributes
- Assay Attributes: Attributes related to the container, hierarchy of mounted specimens and processing details.
- Scan Attributes: Attributes descriptive of the scanning process.
- File Attributes: Attributes descriptive of the file format.
- Donor and Sample Attributes: Attributes related to the patient, study, and series, primarily including elements from the MIABIS sample and donor components.
- Segmentation / Annotation Attributes (planned)
Partners and Liaisons
- ESDIP: Standardization and Interoperability Committee
- EMPAIA International Association: AI APIs and Test Suites
- ISO TC212 - Medical laboratories and in vitro diagnostic systems: ISO/AWI 24051-2: Medical Laboratories — Part 2: Digital Pathology and AI-Based Image Analysis