
REMOD, a new AI model, detects pancreatic cancer on CT scans much earlier and more accurately than radiologists.
Key Details
- 1The AI model, REDMOD, was trained to identify radiomic signatures of pre-diagnostic pancreatic ductal adenocarcinoma (PDAC) on CT scans.
- 2It was trained with imaging data from multiple institutions and developed a 40-feature radiomic signature.
- 3Tested on over 200 abdominal CT scans from patients later diagnosed with PDAC despite no initial radiologist findings.
- 4REMOD detected pancreatic cancer on average 475 days before clinical diagnosis.
- 5The model achieved nearly 75% sensitivity, about twice as high as radiologists' sensitivity.
- 6At a 24-month prediction window, REDMOD's sensitivity was triple that of radiologists.
Why It Matters
Early detection of pancreatic cancer is vital due to its poor prognosis when caught late. AI advancements like REDMOD could revolutionize detection efficacy, potentially improving survival rates and demonstrating the impact of imaging AI in clinical practice.

Source
Radiology Business
Related News

•Radiology Business
RadNet AI Tool Reduces Unnecessary Prostate Biopsies by 19%
RadNet's DeepHealth AI tool can help avoid nearly 1 in 5 prostate biopsies while maintaining high cancer detection sensitivity.

•Radiology Business
FDA Clears MRI2CT AI for 3D Bone Visualization from MRI
MRI2CT's NextMR receives FDA clearance to generate 3D bone images from standard spine MRIs, reducing reliance on CT scans.

•Radiology Business
Multi-Vendor AI Adoption Delivers Efficiency Gains in Private Radiology
A large-scale European study shows that adopting multiple AI tools in private radiology practices leads to significant efficiency improvements.