LungQ 3.0.0 builds on 10 years of clinical trials and 200+ publications to deliver advanced segmentation of pulmonary segments and subsegments
NIJMEGEN, Netherlands–(BUSINESS WIRE)–Thirona, a global company specializing in advanced analysis of thoracic CT images with artificial intelligence, announced that it has received U.S. Food and Drug Administration (FDA) 510(k) clearance for the latest update of its AI-based clinical software LungQ™ (v3.0.0), making its new features widely available for use in hospitals in the United States.
LungQ 3.0.0 is one of the only FDA-cleared solutions that is capable of using AI to automatically segment the pulmonary segments and subsegments found in the internal anatomy of the lung. Based on this analysis, which includes the identification of structures such as lobes, segments, subsegments, airways, and fissures, the technology performs an analysis of the lung tissue and the fissure completeness, supporting physicians in the diagnosis and documentation of pulmonary tissue images from CT thoracic datasets for each individual patient.
“A clearer understanding of lung anatomy helps enable broader adoption of minimally invasive treatments for lung diseases such as COPD and lung cancer, helping save more healthy lung tissue and lung function capacity. Acting as a map for lung anatomy, LungQ helps guide bronchoscopic navigation, leveraging AI to significantly enhance the precision, accuracy, and efficiency of bronchoscopic and surgical lung interventions,” said Eva van Rikxoort, Founder and CEO of Thirona. “Solutions like LungQ are helping usher in a new era of personalized treatment for lung patients, enabling clinicians all over the world to conduct more advanced, easier-to-perform and less invasive procedures with full confidence.”
Based on deep-learning technology, the LungQ software first received 510(k) clearance for version 1.1.0 in 2018. With new enhancements, v.3.0.0 helps guide pulmonologists through the best approach to access various and most peripheral locations within the lungs by delineating pulmonary structures and providing highly accurate CT values for pulmonary tissue. These insights provide essential, non-invasive quantitative support for diagnosis, treatment planning and follow up examination of lung patients.
Rita Priori, CTO at Thirona: “Our AI-based image analysis software LungQ is already used by interventional pulmonologist in Europe and Australia, aiding clinicians through procedures like bronchoscopic lung volume reduction and other interventions. We’re excited to build on the value we’re already seeing in the clinic, helping accelerate innovation in and adoption of a multitude of pulmonary interventions that require high precision on a subsegmental and segmental level, such as lung cancer biopsies, surgical lung volume reduction, lung segmentectomy, ablation procedures, and more.”
The LungQ AI-powered software is approved for clinical use in Europe, the UK and Australia. It is currently used by more than 600 hospitals and has been validated in more than 200 publications globally. The FDA 510(k) cleared LungQ opens tremendous new opportunities for planning and performing localized treatments with maximum precision and accuracy.
To learn more about the LungQ software, please visit our website.
To help make personalized treatment in lung diseases accessible for everyone, Thirona leverages artificial intelligence to deliver high-precision advanced lung image analysis and expertise-based services for MedTech, pharmaceutical and CRO companies. Thirona also partners with research institutions and medical companies to enable breakthroughs in precision medicine for the personalized treatment of pulmonary diseases. Founded by female scientist and entrepreneur Eva van Rikxoort in 2014, the Company has established a proven track record of translating technology into certified clinical end-products through co-innovation with leading MedTech companies.
Thirona’s state-of-the-art lung quantification platform LungQ™ consists of a comprehensive portfolio of robust high-performance AI-based algorithms trained on a wide range of disease-specific datasets, delivering consistent and reproducible results. The unique, scalable platform powers exploratory research studies as well as large multi-site clinical trials and has been cited in over 200 publications.
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