- AI
- Molecular Imaging
- CT
- X-Ray
- Ultrasound
- MRI
- Facility Management
- Mammography
FDA Clears AI 'Contouring Assistant' in MRI-Guided Ultrasound Ablation Procedures
The artificial intelligence (AI)-powered module provides a prostate segmentation tool for MRI-guided transurethral ultrasound ablation (TULSA) procedures in patients with prostate cancer.
Reportedly built on over 24 million parameters drawn from nearly 7,500 training images, the artificial intelligence (AI) module Contouring Assistant has garnered 510(k) clearance from the Food and Drug Administration (FDA) for use in MRI-guided transurethral ultrasound ablation (TULSA) procedures in patients with prostate cancer.
Utilized in conjunction with Profound Medical’s TULSA-PRO system, the Contouring Assistant module offers machine learning-based segmentation of the prostate to facilitate targeted ablation of diseased tissue.
Utilized in conjunction with Profound Medical’s TULSA-PRO system (shown above), the recently FDA-cleared Contouring Assistant module provides machine-learning based prostate segmentation, which was found to be non-inferior to contouring done by leading prostate radiologists, according to Profound Medical, the manufacturer of the Contouring Assistant module. (Image courtesy of Profound Medical.)
Profound Medical noted that the Contouring Assistant module was developed with a reference standard that combined contours from leading prostate radiologists Steven Raman, M.D., Robert Princethal, M.D., and Edward Steiner, M.D. Subsequent research evaluating the stand-alone capability of Contouring Assistant in 100 prostate cancer cases found it was non-inferior to the aforementioned reference standard, according to Profound Medical.
The company also noted that additional testing of the Contouring Assistant module by three urologists demonstrated a 32 percent reduction in the time it took to complete prostate segmentation.
“ … (Contouring) Assistant not only allowed my esteemed urologist colleagues and I to approach the accuracy of an expert radiologist reader in our TULSA treatment designs, but also enabled us to reduce overall procedure times by one-third,” noted Preston Sprenkle, M.D., an associate professor of urology at the Yale School of Medicine in New Haven, Ct.
MRI or Ultrasound for Evaluating Pelvic Endometriosis?: Seven Takeaways from a New Literature Review
September 13th 2024While noting the strength of MRI for complete staging of disease and ultrasound’s ability to provide local disease characterization, the authors of a new literature review suggest the two modalities offer comparable results for diagnosing pelvic endometriosis.
Can Radiomics and Autoencoders Enhance Real-Time Ultrasound Detection of Breast Cancer?
September 10th 2024Developed with breast ultrasound data from nearly 1,200 women, a model with mixed radiomic and autoencoder features had a 90 percent AUC for diagnosing breast cancer, according to new research.
Study Assesses Lung CT-Based AI Models for Predicting Interstitial Lung Abnormality
September 6th 2024A machine-learning-based model demonstrated an 87 percent area under the curve and a 90 percent specificity rate for predicting interstitial lung abnormality on CT scans, according to new research.
