Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3400 Spruce Street, 1 Silverstein, Philadelphia, PA 19104, USA, Tel: +1 215-662-3032, Fax: +1 215-662-7011
J Am Med Inform Assoc. 2015 Nov;22(6):1164-8. doi: 10.1093/jamia/ocv020. Epub 2015 Mar 31.
The author sought to integrate an ontology of rare diseases with a large ontological model of radiological diagnosis.
The Orphanet Rare Disease Ontology (ORDO) comprised 6794 rare diseases. The Radiology Gamuts Ontology (RGO) incorporated 16 197 terms and 53,425 causal relations linking disorders to imaging manifestations. Semi-automated string-matching was used to match ORDO terms to RGO terms.
Of 6794 ORDO terms, 1587 (23.3%) were matched to RGO terms. An additional 700 ORDO terms whose names were hyphenated lists of phenotypic features were added to RGO with causal links from the disease name to the various features. Matched terms were more likely to have higher disease prevalence.
Integrating these ontologies expanded the set of terms and scope of knowledge available for radiological differential diagnosis, and can support translational rare-disease research by linking knowledge of genetics and imaging phenotypes.
作者试图将罕见病本体与大型放射学诊断本体模型相结合。
孤儿疾病本体（Orphanet Rare Disease Ontology，ORDO）包含 6794 种罕见疾病。放射学范围本体（Radiology Gamuts Ontology，RGO）纳入了 16197 个术语和 53425 个因果关系，将疾病与影像学表现联系起来。采用半自动字符串匹配方法将 ORDO 术语与 RGO 术语相匹配。
在 6794 个 ORDO 术语中，有 1587 个（23.3%）与 RGO 术语相匹配。另外还有 700 个 ORDO 术语，其名称是表型特征的连字符列表，通过疾病名称与各种特征之间的因果关系添加到 RGO 中。匹配的术语更有可能具有更高的疾病流行率。
整合这些本体扩展了放射学鉴别诊断中可用的术语集和知识范围，并通过将遗传学和影像学表型知识联系起来，支持罕见病的转化研究。
