Aims and objectives
The Institute of Medicine and the American Society of Clinical Oncology both advocate the development of learning health systems to guide real-time treatment decisions for patients with cancer (1,2).
An integral component of these initiatives will be the integration of radiological information to automate tumor staging and outcomes analyses.
We introduce a structured reporting system,
and a set of data mining tools that can facilitate these aims.
Methods and materials
We developed the ViSion multimedia structured reporting system which tags key images with metadata to describe diagnostic findings (3).
ViSion comprises a client-server software arrangement.
The client resides on a computer workstation and runs in parallel with any vendor’s picture archiving and communication system (PACS) or advance 3D imaging system.
As a radiologist analyzes images with the PACS or 3D imaging system,
the radiologist can press a button on a keyboard or speech microphone to...
Data mining of ViSion’s unique disease timelines can be used for numerous oncological applications,
including automated TMN staging of cancer patients and clinical trials analyses.
a search for all the patients whom have undergone a breast biopsy can be performed with the system.
The system will identify all the occurrences of image findings labeled with the anatomical location of “Breast” and the radiological observation/diagnosis of “Biopsy” to yield a cohort of patients.
ViSion structured reporting with its ability to conduct data mining of multidisciplinary disease timelines can support learning health systems and facilitate personalized cancer treatments.
is a Professor of Diagnostic Radiology at the University of Texas MD Anderson Cancer Center in Houston,
where he also serves as the Medical Director of the Image Processing and Visualization Laboratory.
The learning health care system in America. http://www.iom.edu/Activities/Quality/LearningHealthcare.aspx . Accessed January 7,
2014. CancerLinQ: Building a transformation in cancer care. http://www.asco.org/institute-quality/cancerlinq . Accessed January 7,
2014. Sketching a new reality: What will the radiology report of the future look like? http://www.nxtbook.com/nxtbooks/acr/acrbulletin_201203/index.php?startid=14 .
Accessed January 7,