The Diagnostic Imaging AI (artificial intelligence) focus page provides information, videos, podcasts, and the latest news about product developments, trial results, screening guidelines, and protocol guidance that touch on the development and use of AI across the healthcare continuum.
October 13th 2025
A deep learning AI platform, which incorporated radiomic features including CT attenuation metrics, demonstrated a 93.6 percent AUC for detecting invasive adenocarcinoma on chest CT.
Can Deep Learning Provide a CT-Less Alternative for Attenuation Compensation with SPECT MPI?
February 26th 2025In a recent interview, Abhinav K. Jha, Ph.D., discussed key challenges with the use of SPECT MRI and how an emerging deep learning model may facilitate attenuation compensation without the need for an additional computed tomography (CT) scan.
Can CT-Based AI Help Predict Renal Function Decline After Radioligand Therapy for mCRPC?
February 25th 2025In patients who had at least four cycles of 177Lu-PSMA-I&T for mCRPC, new research shows that a 10 percent or greater decrease in total kidney volume on CT at six months has a 90 percent AUC for predicting estimated glomerular filtration rates (eGFRs) of 30 percent or greater at one year.
Study Assesses Potential of Seven-Minute AI-Enhanced 3T MRI of the Shoulder
February 20th 2025Researchers found that the use of seven-minute threefold parallel imaging-accelerated deep learning 3T MRI had 89 percent sensitivity for supraspinatus-infraspinatus tendon tears and 93 percent sensitivity for superior labral tears.
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.
Employing AI in Detecting Subdural Hematomas on Head CTs: An Interview with Jeremy Heit, MD, PhD
February 7th 2025In a video interview from the International Stroke Conference (ISC), Jeremy Heit, M.D., Ph.D., discussed new research revealing over 90 percent sensitivity and specificity rates for AI detection of subdural hematomas on non-contrast-enhanced head CTs.
Comparative AI Study Shows Merits of RapidAI LVO Software in Stroke Detection
February 6th 2025The Rapid LVO AI software detected 33 percent more cases of large vessel occlusion (LVO) on computed tomography angiography (CTA) than Viz LVO AI software, according to a new comparative study presented at the International Stroke Conference (ISC).
Study: Mammography AI Leads to 29 Percent Increase in Breast Cancer Detection
February 5th 2025Use of the mammography AI software had a nearly equivalent false positive rate as unassisted radiologist interpretation and resulted in a 44 percent reduction in screen reading workload, according to findings from a randomized controlled trial involving over 105,000 women.