Editor: What To Know
- Penn and the American College of Radiology CRI will focus on developing and hosting analytic tools that will be made available to the broader community through the ACR Data Analysis and Research Toolkit (DART) or other platforms, as appropriate.
- “Our goal in this collaboration is not only to make these computational tools more publicly available but ultimately to leverage such synergies and the DART to be able to evaluate radiomics biomarkers, such as the ones enabled by CaPTk, in prospective oncologic clinical trials,” said Despina Kontos, Ph.
- “Data and tool-hosting platforms like DART play an important role in data processing and the radiomic, pathomic and genomic analysis used to develop AI algorithms and advance virtual clinical trials,” says Etta D.
October 14, 2020
The American College of Radiology ® Center for Research and Innovation™ (CRI) has announced a new collaborative effort with the Center for Biomedical Image Computing & Analytics (CBICA) in the Perelman School of Medicine at the University of Pennsylvania (Penn). The collaboration will leverage the ACR’s industry-leading research infrastructure and Penn’s scientific expertise in a joint effort to more rapidly advance imaging informatics.
Penn and the American College of Radiology CRI will focus on developing and hosting analytic tools that will be made available to the broader community through the ACR Data Analysis and Research Toolkit (DART) or other platforms, as appropriate. The first example is the Cancer Imaging Phenomics Toolkit (CaPTk), a software platform for the analysis of radiographic cancer images, currently focusing on the brain, breast, and lung cancer. CaPTk aims to facilitate the swift translation of advanced computational algorithms into routine clinical quantification, analysis, decision making, and reporting workflow. Its long-term goal is providing widely used technology that leverages the value of advanced imaging analytics in cancer prediction, diagnosis and prognosis, as well as in better understanding the biological mechanisms of cancer development. Follow-up directions include involvement in the Federated Tumor Segmentation initiative (FeTS), which aims at facilitating privacy-preserving multi-institutional collaborations on computational analyses without sharing patient data.
“Data and tool-hosting platforms like DART play an important role in data processing and the radiomic, pathomic and genomic analysis used to develop AI algorithms and advance virtual clinical trials,” says Etta D. Pisano, MD, FACR, chief research officer of the American College of Radiology. “The ACR is committed to making more tools available in DART that support researchers and data scientists who are working to build these automated capabilities.”
“Our goal in this collaboration is not only to make these computational tools more publicly available but ultimately to leverage such synergies and the DART to be able to evaluate radiomics biomarkers, such as the ones enabled by CaPTk, in prospective oncologic clinical trials,” said Despina Kontos, Ph.D., an associate professor of Radiology at Penn, co-chair of the ECOG-ACRIN Radiomics Working Group and a member of the computational science lab.
Sites interested in participating can learn more about the project by contacting Michael Boss, Ph.D., director of the ACR Imaging Core Laboratory at mboss@acr.org.
