In the first part of a two-part interview, Nina Kottler, M.D. offers insights and perspective on the recently issued guidance from the FDA on AI-enabled devices and how it may impact developers in the radiology field.
The recently issued draft guidance from the Food and Drug Administration (FDA) on submissions for AI-enabled software reflects more of an emphasis on the total product life cycle for AI products, according to Nina Kottler, M.D., the Associate Chief Medical Officer of Clinical AI for Radiology Partners.
Accordingly, in a recent interview, Dr. Kottler noted that a key cornerstone of the FDA guidance is continuous monitoring of AI software, which may be challenging for smaller AI developers in radiology. She suggested that perhaps an independent group could assist with continuous monitoring of AI software.
“ … What if we had a separate group that could not only help out the AI vendors that maybe couldn't afford to do it, or don't have access to all the data, or (are) not mature enough yet to be there?” posited Dr. Kottler, the Associate Chief Medical Officer of Clinical AI for Radiology Partners.
While Dr. Kottler said the FDA guidance’s increased emphasis on transparency of the training and development of AI software is an important priority, the resulting information needs to be conveyed in a practical way for end-user radiologists.
“Now as an end user, as I'm going through my day looking at 100 cases or 200 cases, many of which are using AI, am I going to that document to look and say, ‘Is this patient and is this exam something that (the AI software) was very specifically trained on? No, that's not realistic. So how do you translate these guidelines into something that's more realistic for the end user? That's going to be the important component. That's the part that I really care about,” maintained Dr. Kottler.
(Editor’s note: For related content, see “Current and Emerging Insights on AI in Breast Imaging: An Interview with Mark Traill, MD, Part 3,” “Diagnostic Imaging’s Top Five AI Content of 2024” and “Nina Kottler, MD, MS on Adoption and Impact of AI in Radiology.”)
For more insights from Dr. Kottler, watch the video below.
Study Explores Impact of Insurance on Treatment and Referrals for Patients with Uterine Fibroids
February 19th 2025Women with uterine fibroids and Medicaid coverage are significantly more likely to be treated with uterine artery embolization than those with commercial insurance, according to newly published research.
Study: AI Boosts Ultrasound AUC for Predicting Thyroid Malignancy Risk by 34 Percent Over TI-RADS
February 17th 2025In a study involving assessment of over 1,000 thyroid nodules, researchers found the machine learning model led to substantial increases in sensitivity and specificity for estimating the risk of thyroid malignancy over traditional TI-RADS and guidelines from the American Thyroid Association.
Can CT-Based AI Provide Automated Detection of Colorectal Cancer?
February 14th 2025For the assessment of contrast-enhanced abdominopelvic CT exams, an artificial intelligence model demonstrated equivalent or better sensitivity than radiologist readers, and greater than 90 percent specificity for the diagnosis of colorectal cancer.