Using the Semantic Web and Web Apps to Connect Radiologists and Oncologists

Medical imaging plays an important role in the diagnosis, prognosis and treatment of cancer. Quantitative and qualitative data about medical images are vital components of a radiological report and are very important to the oncologist that requests the radiological exams. However, traditional methods to register these data are inefficient and error prone. The use of unstructured free text in radiology reports makes it impossible to perform even simple calculations, such as changes in lesion dimensions. It also makes the aggregated analysis of many reports difficult. Free text reports lack a reference to the image regions of the finds they refer to and are not machine-computable. This paper proposes a method to provide support for collaborative work among radiologists and oncologists (providing care or taking part in clinical trials) using an imaging web tool, ePAD, to generate structured radiology reports that can be machine-computable. It also shows how ePAD uses Rad Lex ontology terms and the Annotation and Image Markup (AIM) language (and templates) to generate the reports.