Emerging Trends with AI in Radiology in 2023
In a recent video interview, Sonia Gupta, MD discussed a number of ongoing developments with artificial intelligence (AI) in radiology, ranging from market consolidation of AI vendors to maximizing automation and efficiency with patient triage, reporting and follow-up of incidental findings.
One of the ongoing trends with the development of artificial intelligence (AI) modalities in radiology is an increasing emphasis on improving efficiencies with non-interpretative tasks.
In a recent interview, Sonia Gupta, MD said the combination of AI and natural language processing can help retrieve and analyze key historical points from a patient’s electronic medical record (EMR). Dr. Gupta emphasized that this technology could help streamline patient triage, radiology reporting and the management of incidental finding follow-up.
“(With) incidental finding follow-up, AI reads the report and detects the findings that need follow-up … and can also insert the follow-up recommendations for you into the report. Again, this is all non-interpretative and natural language processing-based type of AI. I think that is a really great opportunity we can all utilize,” maintained Dr. Gupta, an abdominal radiologist, a board member of the American Board of Artificial Intelligence in Medicine, and the chief medical officer of Change Healthcare.
(Editor’s note: For related content, see “Emerging Insights on Improving Radiology Workflows,” “Assessing the Value Proposition of AI in Radiology” and “AI in Radiology: Top Five Articles of 2022.”)
Dr. Gupta said the hope is that this emphasis on simplifying non-interpretative tasks could reduce time-consuming elements of radiology workflows and help curtail burnout.
Noting that approximately one-third of radiologists are currently utilizing some form of AI in practice, Dr. Gupta said the combination of cancer screening with AI and appropriate reimbursement could accelerate AI adoption in radiology.
Pointing out there are currently upward of 200 Food and Drug Administration (FDA) 510(k) clearances in radiology, Dr. Gupta said the ongoing consolidation of AI vendors may make it easier for radiologists to choose among relevant systems for their practice. She added that consolidation could be a boon for early adopters, who may gain access to more AI offerings than they originally signed up for.
For more insights from Dr. Gupta, watch the video below.
Possible Real-Time Adaptive Approach to Breast MRI Suggests ‘New Era’ of AI-Directed MRI
June 3rd 2025Assessing the simulated use of AI-generated suspicion scores for determining whether one should continue with full MRI or shift to an abbreviated MRI, the authors of a new study noted comparable sensitivity, specificity, and positive predictive value for biopsies between the MRI approaches.
Mammography AI Platform for Five-Year Breast Cancer Risk Prediction Gets FDA De Novo Authorization
June 2nd 2025Through AI recognition of subtle patterns in breast tissue on screening mammograms, the Clairity Breast software reportedly provides validated risk scoring for predicting one’s five-year risk of breast cancer.
Lunit Unveils Enhanced AI-Powered CXR Software Update
May 28th 2025The Lunit Insight CXR4 update reportedly offers new features such as current-prior comparison of chest X-rays (CXRs), acute bone fracture detection and a 99.5 percent negative predictive value (NPV) for identifying normal CXRs.
Photon-Counting Computed Tomography: Eleven Takeaways from a New Literature Review
May 27th 2025In a review of 155 studies, researchers examined the capabilities of photon-counting computed tomography (PCCT) for enhanced accuracy, tissue characterization, artifact reduction and reduced radiation dosing across thoracic, abdominal, and cardiothoracic imaging applications.
