Artificial intelligence tool designed to improve radiologist cancer detection performance.
Therapixel captured 510(k) clearance from the U.S. Food and Drug Administration this week for MammoScreen™, an explainable, actionable artificial intelligence (AI) tool designed to help with mammography interpretation.
The clearance comes after the release of findings from a multi-case study, company officials said, that showed radiologists had better cancer detection performance on mammograms when they used MammoScreen versus when they analyzed images solo.
“We believe MammoScreen will provide quick and reliable confirmation of radiologists’ suspicions as they read,” said Matthieu Leclerc-Chavlet, Therapixel chief executive officer. “This AI solution will ensure a more certain assessment by radiologists and a speedier reassurance of women having breast cancer screening exams, resulting in a more efficient workflow and reduced costs for the healthcare system.”
According to company information, MammoScreen can automatically detect and characterize suspicious soft tissue lesions and calcifications on mammography images while simultaneously assessing their likelihood of malignancy. Radiologists receive a summary report that categorizes each lesion’s suspiciousness on a scale of 1-to-10 with 10 being the most likely to indicate malignancy.
Can Emerging AI Software Offer Detection of CAD on CCTA on Par with Radiologists?
May 14th 2025In a study involving over 1,000 patients who had coronary computed tomography angiography (CCTA) exams, AI software demonstrated a 90 percent AUC for assessments of cases > CAD-RADS 3 and 4A and had a 98 percent NPV for obstructive coronary artery disease.
Contrast-Enhanced Mammography Study Reveals 24 Percent Lower Sensitivity with Moderate/Marked BPE
April 30th 2025In comparison to minimal or mild background parenchymal enhancement on contrast-enhanced mammography (CEM), researchers found that moderate or marked BPE was associated with a 12 percent lower AUC for breast cancer detection.
Could AI-Powered Abbreviated MRI Reinvent Detection for Structural Abnormalities of the Knee?
April 24th 2025Employing deep learning image reconstruction, parallel imaging and multi-slice acceleration in a sub-five-minute 3T knee MRI, researchers noted 100 percent sensitivity and 99 percent specificity for anterior cruciate ligament (ACL) tears.