The Role of DICOM in Artificial Intelligence for Skin Disease - Caffery, Liam J.; Rotemberg, Veronica; Weber, Jochen; Soyer, H. Peter; Malvehy, Josep; Clunie, David (Frontiers in Medicine, 2021)
There is optimism that AI will result in positive clinical outcomes which is driving research and investment in the use of AI for skin disease. At present AI for skin disease is embedded in a research and development and not practised widely in clinical dermatology. Clinical dermatology is also undergoing technological transformation in terms of the development and adoption of standards that optimises the quality use of imaging. Digital Imaging and Communication in Medicine (DICOM) is the international standard for medical imaging. DICOM is a continually evolving standard. There is considerable effort being invested in developing dermatology-specific extensions to the DICOM standard. The ability to encode relevant metadata and afford interoperability with the digital health ecosystem (e.g. image repositories, electronic medical records) has driven the initial impetus in the adoption of DICOM for dermatology. DICOM has a dedicated working group whose role is to develop mechanism to support AI workflows and encode AI artefacts. DICOM can improve AI workflows by encoding derived objects (e.g. secondary images, visual explainabilty maps, AI algorithm output), and the efficient curation of multi-institutional datasets for machine learning training, testing and validation. This can be achieved using DICOM mechanisms such as standardized image formats and metadata, metadata-based image retrieval, and de-identification protocols. DICOM can address a number of important technological and workflow challenges to the implementation of AI. However, many other technological, ethical, regulatory, medico-legal, and workforce barriers will need to be addressed before DICOM and AI can be used effectively in dermatology.