The ACR Innovation Fund has funded the following grants to date:
- Medical Imaging Machine Learning Competition for Lung and Breast Cancer
This proposal is for hosting a “machine learning competition” to develop algorithms that assist and enable radiologists’ provision of high-value, high-quality patient care.
- New Models for Patient-Centered Care in Radiology: Assessing the Value of Virtual Radiology Consultations with Patients and Referring Providers
In line with the Imaging 3.0 strategy and the establishment of the Commission on Patient- and Family-Centered Care (PFCC), this grant funds a pilot project “implementing synchronous video-based virtual radiology consultations” between radiologists and referring physicians and patients during the patient’s office visit.
- ACR Pipeline for Enrichment of Radiology (PIER): A collaborative pilot program of the ACR Commission for Women and General Diversity with Nth Dimension
Utilizing an existing program, “Nth Dimension,” this grant promotes radiology as a specialty choice to female medical students and those from underrepresented minorities as a means to help our specialty achieve a more diverse composition.
- ACR Ambassador Pilot Program
The funding supports an innovative set of ACR efforts to approach radiology practices, academic departments and health care systems that employ radiologists to demonstrate the value of ACR membership.
- Development of a Peer Learning Tool for Improving Radiologist Performance
This project expands upon the ACR “RADPEER®” program, now in existence for 15 years and being used by over 19,000 radiologists, with the objective being to promote sharing and learning from “near misses and mistakes” that can occur in every day radiology practice. The development of a “multi-component and integrated peer learning platform” will populate a registry of cases promoting all practices to benefit from those occurrences.
- Development of an ACR TI-RADS Multi-Institutional Thyroid Ultrasound Registry
The objective of this project is to develop infrastructure including a multi-institutional registry to track outcomes (biopsy or follow-up) of ultrasound evaluated thyroid nodules in order to validate the ACR TI-RADS™ reporting system. This will also be used for research to assess optimal decision making regarding the need to biopsy the very common thyroid nodules.
- Development and Validation of TBI-RADS: Decreasing Health Care Costs and Standardizing Care Using a Traumatic Brain Injury Reporting and Data System
This project assesses factors that impact outcomes of patients with traumatic brain injuries and determine “threshold values for intracranial hemorrhage, herniation and hydrocephalus that do not lead to increased risk of decomposition or hemorrhage progression.” Using this data, the investigators developed a “new standardized acute management scheme, a Traumatic Brain Imaging Reporting and Data System (TBI-RADS™),” as well as demonstrate the cost effectiveness of clinical protocol.
- Radiologist Accountability for Incidental Findings Management: Impact on Costs at a Large Health System
This project utilizes “a unique informatics engine” at a large U.S. health system, in combination with the recommendations of the ACR Incidental Findings, to evaluate the downstream costs associated with imaging incidental findings reported by radiologists, determining the cost per incidental finding and the cost per detect cancer. This data helps design a Physician Focused Alternative Payment Model that will allow radiologists to confidently contract for the follow-up imaging of those incidental findings.
- Video Advocacy: Patient-Facing Breast Cancer Screening Educational Videos for Web, Broadcast and Social Media
This project created a YouTube channel to house a new series of 2–4 minute, high-definition videos regarding the benefits and challenges of mammography to help patients, working with their referring provider, to determine the best screening strategy for them. This content is available via digital new releases, mammographysaveslives.org and social media.
- RADS-Train: A quality improvement (QI) and training initiative to improve adherence to ACR’s Reporting and Data Systems (RADS)
This project is designed to demonstrate and validate the value of standardized reporting using the ACR “RADS.” It utilizes the liver reporting system (LI-RADS®) as the test case with the goal to “improve reporting of suspicious liver lesions on CT/MRI using I-RADS through the development and implementation of a LI-RADS teaching and case base module.” This will be piloted at one facility with hopes of demonstrating the impact for more widespread use.
- Jumpstarting Development of the ACR Coding and Reimbursement Archive (CORA)
The CORA system will allow the ACR’s Economics Department to create or revise CPT codes for the field of radiology and submit recommendations to the American Medical Association’s (AMA’s), CPT Editorial Panel and the Relative Value Scale Update Committee (RUC). The CORA system will enable users to manage coding information in a seamless, consolidated and collaborative manner. It will also reduce errors, improve request cycle time and make the information readily available to any authorized user.
- Pilot testing, Refinement and Validation of the Infrastructure to Develop RADS-Based Registries
This proposal is to pilot test, refine and validate infrastructure to collect structured data and populate registries based on all current and future ACR Radiology and Data Systems (RADS).
- Info-RADS Patient-Centered Radiology Reporting: Enabling Patients to Take Action. Preparing Patient-Centered Text Modules Added to Radiology Reports for Software Integration
Info-RADS Patient-Centered Radiology Reporting: Enabling patients to take action. Preparing patient centered text modules added to radiology reports for software integration.
- Demonstrating the Value of Assisted Reporting in Radiologist Practice
- From ACR White Papers to National Guidelines: Formalizing the Consensus Process for Algorithm-Based Recommendations
Our goal is to develop a formal consensus process for algorithm-based recommendations in imaging, such as those generated by the ACR Incidental Findings (IF) and Reporting and Data Systems (RADS) Committees.
- Understanding Clinician Resistance to Point of Care Electronic CDS
- Lung Cancer Screening Outreach & PEER
- RadAdjust: A Machine Learning Solution for Imaging Examination RVU Complexity Weighting
- Evaluating AI Applications in Clinical Practice
- Patient Safety Simulation in Root Cause Analysis
- Direct Patient Notification of Non-Urgent Incidental Radiology Findings
- Integrated National Imaging Informatics Course (I3) – Educating the Next Generation of Radiologists and Fostering Interest in Data Science and Imaging Informatics
- Application of Natural Language Processing and Machine Learning to Create an Automated Registry for Interventional Oncology
- Characterization and Targeting of the Main Drivers of Elective Imaging Utilization
- Human Centered Design: Optimizing Patient Experience Through Design Thinking