The new partnership aims to mitigate the risk associated with missed findings in CT medical imaging studies. The collaboration will combine Oxipit's ChestEye Quality and contextflow's SEARCH Lung CT products to identify missed findings in CT scans in near-real time. ECR 2022 will offer the first preview of the combined solution, and the first installation will be deployed at Leiden University Medical Center.
ChestEye Quality analyzes medical images and corresponding radiologist reports. Acting as a virtual safety net, the software sends a notification to the radiologist if it detects a mismatch or a missed finding not identified in the radiologist report.
ChestEye Quality can operate in retrospective and prospective settings, providing quality audit notifications in near-real time. The product is already deployed in more than 10 medical institutions worldwide.
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Out of nearly 200,000 analyzed chest X-ray images, an average of 1 in 552 (0.18%) chest X-ray studies feature clinically-significant missed findings. The result varies from 0.08% to 0.92% depending on the type of medical institution. 78% of the missed findings relate to pulmonary nodules, aiding earlier detection of lung cancer and significantly improving patient treatment prognosis.
The contextflow partnership will expand ChestEye Quality capabilities into the CT modality.
contextflow SEARCH Lung CT is a clinical decision support system that automatically detects, quantifies and visualizes key disease patterns and lung nodules in CTs of the lungs over time, displaying relevant information directly in the radiologist's PACS viewer. The tool is relevant for the analysis of many suspected diseases, including interstitial lung disease (ILD), chronic pulmonary obstructive disease (COPD), and lung cancer.
In a clinical impact study at the Medical University of Vienna (MUW), an earlier version of SEARCH Lung CT showed an average reading time savings of 31% when contextflow SEARCH Lung CT is available for use with a trend towards improved diagnostic accuracy. The study was recently published in European Radiology.
"We are excited to partner with experts in CT AI medical imaging. The ChestEye Quality AI double reading approach has already proven itself in the CXR modality, helping radiologists to spot more clinically-relevant nodules and improving early diagnostics of lung cancer. Collaboration with contextflow highlights the robustness of the ChestEye Quality framework, showcasing how the AI double reader approach can be easily expanded into other medical imaging modalities," says Oxipit CEO Gediminas Peksys.