Sponsored by:
Explore how advanced AI-enabled operational infrastructure can address one of radiology’s most persistent challenges: ensuring incidental findings are tracked, communicated and cared for across the care continuum.
While imaging technology continues to improve detection, data validation and follow up remain time consuming and fragmented processes—creating additional administrative strain and increasing the risk of patients falling through the cracks.
Using breast imaging as a case example, this session examines operational infrastructure designed to advance care across the lifecycle, reduce administrative burden, and improve follow-up adherence and system-wide early detection.
Speakers from Eon and Lifepoint Health demonstrate how unifying breast cancer screening, incidental pathways and embedded care navigation can reshape early detection at scale.
This webinar is sponsored by Eon.
Sponsored by:
Explore how advanced AI-enabled operational infrastructure can address one of radiology’s most persistent challenges: ensuring incidental findings are tracked, communicated and cared for across the care continuum.
While imaging technology continues to improve detection, data validation and follow up remain time consuming and fragmented processes—creating additional administrative strain and increasing the risk of patients falling through the cracks.
Using breast imaging as a case example, this session examines operational infrastructure designed to advance care across the lifecycle, reduce administrative burden, and improve follow-up adherence and system-wide early detection.
Speakers from Eon and Lifepoint Health demonstrate how unifying breast cancer screening, incidental pathways and embedded care navigation can reshape early detection at scale.
This webinar is sponsored by Eon.
Content Areas (Codes):
The following Content Areas will be printed on the certificate for this course:
- Artificial Intelligence
- Leadership & Management
Learning Objectives:
- Describe common enterprise challenges in managing incidental findings.
- Identify operational bottlenecks in current tracking models.
- Identify characteristics of scalable, AI-enabled longitudinal care models.
This non-CME enduring material is estimated to take 1 hour to complete.
Start Date: 05/20/2026
Online Expiration Date: 05/19/2027
This educational activity was originally presented on 05/20/2026 as an interactive online webinar.
Faculty:
- LouAnn Bala, RN, MSN
- Tiffany Dean, RT, BS
Price:
Non-Member/Basic Member Rate: $0.00
Standard Member/Full Access Member Rate: $0.00
Refund / Exchange Policy:
RSNA will not issue any refunds or exchanges for online only versions of educational products or activities purchased online. Please review the entire product or activity description prior to purchase.
RSNA Disclaimer:
The opinions or views expressed in this activity are those of the presenters and do not necessarily reflect the opinions, recommendations or endorsement of the RSNA. Participants should critically appraise the information presented and are encouraged to consult appropriate resources for information surrounding any product or device mentioned. Information presented, as well as publications, technologies, products and/or services discussed, are intended to inform the learner about the knowledge, techniques, and experiences of RSNA faculty who are willing to share such information with colleagues. The RSNA disclaims any and all liability for damages to any individual user for all claims which may result from the use of said information, publications, technologies, products and/or services, and events.