LesionViewer: a tool for tracking cancer lesions over time
Mia A Levy1, Ankit Garg, Aaron Tam
1Stanford University, Stanford, CA, USA.
AMIA ... Annual Symposium Proceedings. AMIA Symposium
|August 13, 2008
Summary
Oncologists can now better visualize cancer lesion changes using LesionViewer, a software that links radiology reports to images. This tool aids in understanding disease progression and location, improving clinical decision-making for cancer patients.
Area of Science:
- Medical Imaging
- Oncology
- Health Informatics
Background:
- Radiology reports currently lack direct integration with primary image data.
- This disconnect hinders oncologists' ability to visually assess cancer lesion location and behavior over time.
- Effective evaluation of treatment response relies on integrated image and report analysis.
Purpose of the Study:
- To introduce LesionViewer, a prototype software system.
- To assist clinicians in comprehending and reviewing radiology imaging studies.
- To improve the integration of textual radiology reports with primary image data for cancer management.
Main Methods:
- Developed LesionViewer with an Anatomical Summary View for lesion location.
- Incorporated direct navigation to primary image data within the interface.
- Utilized the RECIST (Response Evaluation Criteria in Solid Tumors) guideline for temporal disease behavior analysis in the Disease Summary View.
Main Results:
- A usability study involving nine physicians was conducted.
- Physicians could accurately perform clinical tasks related to radiology report and image data analysis using LesionViewer.
- All participating physicians expressed willingness to use the system if available.
Conclusions:
- LesionViewer effectively integrates radiology reports and image data.
- The system enhances the visualization of cancer lesion location and disease behavior.
- LesionViewer shows promise in supporting oncologists' clinical decision-making processes.
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