Imaging plays a key role in the management of cancer patients, contributing important evidence for treatment response via serial measurements of reference cancer lesions. However, the identification, comparison, measurement, and documentation of oncologic lesions can be inefficient and error prone with the typical methodology used by most institutions, said presenter Dr. Paul Chang from the University of Chicago.
In response, the researchers created an electronic-based workflow. During interpretation of an imaging study, the radiologist identifies and measures cancer lesions using a PACS-integrated tool called Lesion Tracker, which automatically extracts quantitative measurements from the lesion, Chang said.
Next, these measurements are automatically sent to another tool called Lesion Dashboard, which was created for oncology clinical research associates and oncologists. Lesion Dashboard allows the oncologist to immediately view the relevant cancer lesions selected by the radiologist, along with the images that support the radiologist's lesion selection and measurements.
"Our study has found that by using this electronic-based workflow, we can significantly reduce the variability in lesion selection," Chang said. This approach better leverages the radiologist's expertise and relevance in oncology patient management.
