AI-Rad Companion (Pulmonary) is advanced software designed to analyze CT images of the lungs. It helps clinicians by segmenting lung regions, measuring lung volumes, identifying areas with abnormal tissue density, and detecting lung lesions including solid pulmonary nodules. This enables efficient and precise assessment of lung disease from existing CT scans, supporting better diagnosis and treatment decisions in emergency and specialty care.
AI-Rad Companion (Pulmonary) is image processing software that provides quantitative and qualitative analysis from previously acquired Computed Tomography DICOM images to support radiologists and physicians from emergency medicine, specialty care, urgent care, and general practice in the evaluation and assessment of disease of the lungs. It provides segmentation and measurement of complete lung and lung lobes, identification of areas with lower Hounsfield values, interface to syngo.CT Lung CAD, and segmentation and measurements of found lung lesions with lobe dedication.
The software is a CT image processing application that uses deep learning algorithms for segmentation of lung lobes and lesions, identifies lung parenchyma areas below -950 HU, and measures volumes and lesion parameters. It integrates with external CAD systems (syngo.CT Lung CAD) and supports data from multiple CT vendors including Siemens, GE, and Philips. Visualization is provided via color overlays on multiplanar reconstructions and volume rendered images.
The device underwent software validation, bench testing, and clinical data-based software validations demonstrating substantial equivalence to predicate devices. A large retrospective study (>4500 CT data sets) validated lung lobe segmentation with high Dice coefficients (0.95-0.98), low mean surface distances, and small volume errors. All performance results exceeded those of predicate devices. Risk management, cybersecurity, and usability validations were also conducted.
No predicate devices specified
Submission
11/23/2018
FDA Approval
7/26/2019
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