Will this artificial intelligence technology improve diagnostic accuracy and reduce false positive biopsy orders?
Koios DS, an artificial intelligence (AI)-based software platform that reportedly improves the accuracy and efficiency of diagnosing breast and thyroid cancer, recently garnered clearance from the Food and Drug Administration (FDA), according to the software manufacturer Koios Medical.
A recent multicenter retrospective review involving the assessment of 900 breast lesions showed that the addition of Koios DS Breast to ultrasound imaging improved correct BI-RADS classification of sonographic breast lesions by 14 of the 15 physicians participating in the study.
For thyroid cancer, Koios Medical reported a 14 percent increase in detection rates with its Thyroid DS platform and more than a 35 percent reduction in false positive biopsy orders. The company also noted a greater than 50 percent reduction in interpretation variability.
Built with ultrasound data from a worldwide, 48-site network, the AI-generated findings with Koios DS are directly aligned with the BI-RADS and TI-RADS rating systems from the American College of Radiology, according to Koios Medical. The company added that the software is also aligned with the American Thyroid Association’s system for tissue classification and scoring.
“ … This novel software demonstrates that (by) using AI for decision support, physicians can make clinically meaningful shifts in performance, improving interpretation efficacy and diagnostic performance, improving sensitivity and reducing false positives,” noted Lev Barinov, VP of clinical excellence and product management at Koios Medical.
On the reimbursement front, Koios Medical pointed to new CPT Category 3 codes from the American Medical Association that clinicians may employ to bill for use of the Koios DS software in interpreting, classifying and reporting findings from traditional ultrasound examinations.
Meta-Analysis Shows Merits of AI with CTA Detection of Coronary Artery Stenosis and Calcified Plaque
April 16th 2025Artificial intelligence demonstrated higher AUC, sensitivity, and specificity than radiologists for detecting coronary artery stenosis > 50 percent on computed tomography angiography (CTA), according to a new 17-study meta-analysis.
New bpMRI Study Suggests AI Offers Comparable Results to Radiologists for PCa Detection
April 15th 2025Demonstrating no significant difference with radiologist detection of clinically significant prostate cancer (csPCa), a biparametric MRI-based AI model provided an 88.4 percent sensitivity rate in a recent study.
The Reading Room: Artificial Intelligence: What RSNA 2020 Offered, and What 2021 Could Bring
December 5th 2020Nina Kottler, M.D., chief medical officer of AI at Radiology Partners, discusses, during RSNA 2020, what new developments the annual meeting provided about these technologies, sessions to access, and what to expect in the coming year.
Can CT-Based AI Radiomics Enhance Prediction of Recurrence-Free Survival for Non-Metastatic ccRCC?
April 14th 2025In comparison to a model based on clinicopathological risk factors, a CT radiomics-based machine learning model offered greater than a 10 percent higher AUC for predicting five-year recurrence-free survival in patients with non-metastatic clear cell renal cell carcinoma (ccRCC).