Regulatory

FDA OKs Latest Version of Thirona’s LungQ Software

LungQ 4 provides enhanced airway segmentation analysis and delivers detailed anatomical context that enhances clinical interpretation.

By: Michael Barbella

Managing Editor

Thirona has nabbed U.S. Food and Drug Administration (FDA) clearance for its LungQ 4 software, which extends the capabilities of its previous versions.

This new clearance builds on the FDA-authorized LungQ 3, which introduced advanced lung segmentation capabilities—a critical foundation for accurate analysis on a regional level.

The artificial intelligence (AI)-powered CT analysis LungQ 4 software extends these capabilities into:

  • Enhanced peripheral airway segmentation.
  • Estimated chronic perfusion defects from CT.
  • Post-treatment detection of endobronchial implants.

Since its inception in 2014, Thirona has remained focused on its mission to translate validated AI technology into practical, clinically reliable tools designed to enhance pulmonary intervention planning and guidance, and to accelerate respiratory clinical trials evaluating treatment efficacy.

Leveraging Thirona’s FDA-cleared and CE-certified segmentation framework, along with advanced deep learning models, LungQ 4 provides enhanced airway segmentation analysis, enabling clinicians to identify distal airways within previously inaccessible peripheral lung regions. By combining this extended analysis with anatomical airway mapping, LungQ 4 delivers detailed anatomical context that enhances clinical interpretation, according to the company.

In navigational bronchoscopy, this can support precise access planning for distal airway targets in bronchoscopic interventions for treating lung cancer, emphysema, and chronic airway diseases. In respiratory disease assessment, it can provide consistent anatomical referencing to visualize airway abnormalities up to the peripheral bronchial branches, enabling physicians to better understand disease patterns within the bronchial tree.

Validated in a recently published study1 comparing automated and manual assessments by expert bronchoscopist, this analysis demonstrated excellent accuracy and reliability with a subcentimeter alignment between AI-identified pathways and expert-marked routes. This indicates that AI is ready to match, and potentially surpass, expert-level manual assessment for pre-procedural planning.

Already part of CE-certified LungQ 3 and now FDA-cleared LungQ 4, chronic perfusion defects from CT (PXT) applies deep learning to estimate approximate chronic perfusion defects directly from computed tomography images, providing quantitative data for anatomical regions to support treatment target selection in lung volume reduction therapy and advancing quantitative imaging in functional lung assessment.

Earlier clinical evaluations confirmed that PXT delivers quantitative information comparable to SPECT-CT,2 which together with Thirona’s segmentation capabilities, enables subsegmental regions analyses.

Available for clinical use in Europe, the United Kingdom, and Australia, the FDA’s clearance of PXT opens new opportunities for future integration of the analysis into precision-driven interventional workflows in U.S. hospitals, Thirona bigwigs said.

The new analysis for detection of endobronchial implants in patients who have undergone lung volume reduction intervention extends LungQ’s FDA-cleared capabilities to the post-treatment setting.

Offering automated detection and localization of endobronchial implants, the analysis provides information for post-treatment evaluation of implant positioning or displacement. This functionality complements LungQ’s established role in pre-procedural planning and patient eligibility assessment, paving the way toward integrated AI-supported treatment pathways, extending into follow-up and longitudinal monitoring.

“Each new FDA clearance is a great confirmation of our uncompromised focus on quality and performance, continuously improving our software to make a real impact in clinical practice,” Thirona CEO Eva van Rikxoort, Ph.D., stated. “With LungQ 4, we’ve come a long way in translating our AI technology into trusted tools that actually work in everyday care, implemented in close collaboration with our partners across advanced clinical systems and solutions used by physicians around the world.”

Thirona is a global company providing high-precision advanced lung image analysis with artificial intelligence through expertise-based services for medtech, pharmaceutical, and CRO companies. Thirona partners with research institutions and medical companies in their innovation programs aimed to enable breakthroughs in precision medicine for personalized pulmonary disease treatment.

Since its inception in 2014, the company has established a proven track record in 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 wide range of high-performance AI-based algorithms trained on disease specific datasets, offering AI analytical capabilities. The scalable AI platform delivers consistent and reproducible results, powering exploratory research studies as well as large multi-site clinical trials.

Founded by van Rikxoort, the company’s mission is to utilize the latest domain knowledge and artificial intelligence technology to create positive impact by making personalized treatments in lung diseases accessible for everyone.

References
1 Heikens. N. et al. 2025. Automated CT based airway segmentation software for navigation bronchoscopy, ERS international congress abstract 2025. The abstract will be published in a supplement of the European Respiratory Journal (ERJ) by November 2025.
2 Koster. D., et al, 2023. High-Resolution Computed Tomography-approximated Perfusion Is Comparable to Nuclear Perfusion Imaging in Severe Chronic Obstructive Pulmonary Disease, American Journal of Respiratory and Critical Care Medicine, High-Resolution Computed Tomography-approximated Perfusion Is Comparable to Nuclear Perfusion Imaging in Severe Chronic Obstructive Pulmonary Disease | American Journal of Respiratory and Critical Care Medicine

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