Operational Ontology for Oncology (O3): A Professional Society-Based, Multistakeholder, Consensus-Driven Informatics Standard Supporting Clinical and Research Use of Real-World Data From Patients Treated for Cancer.

PURPOSE: The ongoing lack of data standardization severely undermines the potential for automated learning from the vast amount of information routinely archived in electronic health records (EHRs), radiation oncology information systems, treatment planning systems, and other cancer care and outcomes databases. We sought to create a standardized ontology for clinical data, social determinants of health, and other radiation oncology concepts and interrelationships. METHODS AND MATERIALS: The American Association of Physicists in Medicine's Big Data Science Committee was initiated in July 2019 to explore common ground from the stakeholders' collective experience of issues that typically compromise the formation of large inter- and intra-institutional databases from EHRs. The Big Data Science Committee adopted an iterative, cyclical approach to engaging stakeholders beyond its membership to optimize the integration of diverse perspectives from the community. RESULTS: We developed the Operational Ontology for Oncology (O3), which identified 42 key elements, 359 attributes, 144 value sets, and 155 relationships ranked in relative importance of clinical significance, likelihood of availability in EHRs, and the ability to modify routine clinical processes to permit aggregation. Recommendations are provided for best use and development of the O3 to 4 constituencies: device manufacturers, centers of clinical care, researchers, and professional societies. CONCLUSIONS: O3 is designed to extend and interoperate with existing global infrastructure and data science standards. The implementation of these recommendations will lower the barriers for aggregation of information that could be used to create large, representative, findable, accessible, interoperable, and reusable data sets to support the scientific objectives of grant programs. The construction of comprehensive "real-world" data sets and application of advanced analytical techniques, including artificial intelligence, holds the potential to revolutionize patient management and improve outcomes by leveraging increased access to information derived from larger, more representative data sets.

Systematic errors in respiratory gating due to intrafraction deformations of the liver.

This article shows the limitations of respiratory gating due to intrafraction deformations of the right liver lobe. The variability of organ shape and motion over tens of minutes was taken into account for this evaluation, which closes the gap between short-term analysis of a few regular cycles, as it is possible with 4DCT, and long-term analysis of interfraction motion. Time resolved MR volumes (4D MR sequences) were reconstructed for 12 volunteers and subsequent non-rigid registration provided estimates of the 3D trajectories of points within the liver over time. The full motion during free breathing and its distribution over the liver were quantified and respiratory gating was simulated to determine the gating accuracy for different gating signals, duty cycles, and different intervals between patient setup and treatment. Gating effectively compensated for the respiratory motion within short sequences (3 min), but deformations, mainly in the anterior inferior part (Couinaud segments IVb and V), led to systematic deviations from the setup position of more than 5 mm in 7 of 12 subjects after 20 min. We conclude that measurements over a few breathing cycles should not be used as a proof of accurate reproducibility of motion, not even within the same fraction, if it is longer than a few minutes. Although the diaphragm shows the largest magnitude of motion, it should not be used to assess the gating accuracy over the entire liver because the reproducibility is typically much more limited in inferior parts. Simple gating signals, such as the trajectory of skin motion, can detect the exhalation phase, but do not allow for an absolute localization of the complete liver over longer periods because the drift of these signals does not necessarily correlate with the internal drift.