FDA Clears Modules of AI-Rad Companion Chest CT From Siemens Healthineers
Summary
The algorithms in AI-Rad Companion Chest CT were trained on extensive datasets and annotated by qualified clinical specialists to provide segmentation, measurement, and highlighting of key anatomical structures, to support quantitative and qualitative analysis. It supports a variety of tasks, including: automated detection of lesions, localization of abnormalities, and measurement of lung lesions; quantification of per-lobe low-attenuation parenchyma; enhanced visualization of lung lesions; automated segmentation of lung lobes and enhanced visualization of low-attenuation parenchyma; segmentation and measurement of maximum diameters of the thoracic aorta; quantification of the total calcium volume in the coronary arteries; and detection of nine anatomical landmarks as identified by American Heart Association (AHA) guidelines. Based on the AI-supported analysis, AI-Rad Companion Chest CT automatically generates standardized, reproducible, and quantitative reports in Digital Imaging and Communications in Medicine (DICOM) SC format. In addition to reducing time spent on manual results documentation, these reports can be accessed by radiologists on the picture archiving and communication system (PACS) in the clinical routine. “AI-Rad Companion Chest CT builds on our decades-long expertise in AI and machine learning, digitalizing healthcare and helping providers perform multi-organ image interpretation of the chest with enhanced detection, accuracy, and precision, which can potentially improve outcomes,” said David Pacitti, President and Head of the Americas at Siemens Healthineers.