RadRx

🧠📸 AI in Radiology Is Getting Its Own Accreditation Program

The American College of Radiology (ACR) is laying the groundwork for a first-of-its-kind accreditation program for artificial intelligence in imaging, aiming for a formal launch by 2027. As AI adoption grows, ACR leaders say it’s clear that real-world AI performance can diverge from premarket testing—and radiology needs quality oversight just like traditional modalities.

🔍 Modeled after decades of ACR accreditation standards in areas like mammography and radiation oncology, the new AI program will evaluate:

AI governance

Model selection & validation

Acceptance testing

Ongoing performance monitoring

In the meantime, ACR has rolled out ARCH-AI, a recognition program to help practices prepare for full accreditation and shape best practices.

This initiative marks a critical step toward ensuring safe, effective, and trusted AI implementation in clinical imaging.

📅 Stay tuned—full program expected by 2027!

American College of Radiology to launch AI accreditation program As the use of AI in imaging continues to grow, it’s “become clear" that real world performance of these products can defer from premarket testing, experts note.

It's Q & A Thursday!

❓ Which branch does the middle hepatic artery arise from in the liver?

🅰️ The middle hepatic artery (MHA) is a variant artery that typically supplies segment IV of the liver.

🔍 The MHA may arise from the following arteries--

➡️ Proper hepatic artery (most common)
➡️ Right or left hepatic artery (less common)
➡️ Gastroduodenal or common hepatic artery (rare)

💡 It is important that the physician provides detailed information regarding the origin of the MHA to ensure that catheterization codes are captured correctly as it may be its own branch, or it may be a more distal branch of the another artery.

🧭 Patients & AI in Healthcare: Hope Meets Hesitation 🤖💬

A new review published in the International Journal of Medical Informatics sheds light on how patients perceive the growing presence of AI in healthcare—and the findings are anything but black and white.

🔍 Key takeaways from the review of 38 studies across 13 countries:

✅ 75% of patients recognize the benefits of AI—like improved accuracy and efficiency
⚠️ 50–70% still express concerns, particularly about:
➡️ Losing the human touch in care
➡️ Trusting AI’s safety and reliability
➡️ Data privacy and security

🧠 Acceptance of AI is shaped not just by performance, but by:

✳️ Individual perceptions
✳️Provider relationships
✳️Healthcare system context
✳️Societal trust and transparency

📢 Lead author Dr. Osnat Bashkin emphasizes that successful AI integration requires more than good tech—it demands transparency, human oversight, and patient engagement at every step.

Healthcare AI isn't just a tech challenge—it's a human one.

https://aiin.healthcare/topics/patient-care/digital-transformation/research-review-patients-have-understandably-mixed-feelings-about-ai-healthcare?utm_source=newsletter&utm_medium=rb_news

Research review: Patients have understandably mixed feelings about AI in healthcare A new review of the relevant scientific literature suggests many if not most patients are aware that healthcare AI’s emerging benefits exist side-by-side with its persistent uncertainties.