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Updated: Mar 15, 2026

Measurement of the Pressure-volume Curve in Mouse Lungs
Published on: January 27, 2015
Predicting Lung Volume Reduction after Endobronchial Valve Therapy Is Maximized Using a Combination of Diagnostic
T David Koster1, Eva M van Rikxoort, Ralf-Harto Huebner
1Department of Pulmonary Diseases, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Background:
Bronchoscopic lung volume reduction using one-way endobronchial valves (EBVs) has been proven to be effective in patients with severe emphysema. However, the selection of patients without collateral ventilation prior to treatment is critical for procedural success. Collateral ventilation can be assessed directly with the Chartis system or indirectly using computed tomography (CT) fissure analysis.
Objectives:
We retrospectively evaluated the diagnostic value of a combination of the quantitative CT interlobar fissure completeness score (FCS) and Chartis in predicting responders to EBV therapy.
Methods:
CT data from four prospective studies were pooled and analyzed using semiautomated software to quantify the completeness of interlobar fissures. These FCSs were compared to a reference standard of achieving ≥350 ml of target lobe volume reduction after EBV treatment. Using a receiver operating characteristic curve, optimal thresholds predictive of complete fissures (responders) and incomplete fissures (non-responders) were determined. A subgroup of patients with partially complete fissures was identified, where software had lower accuracy. The complementary value of Chartis was investigated in this group.
Results:
A fissure was defined as complete (FCS >95%), incomplete (FCS <80%), or partially complete (80% < FCS < 95%). The positive predictive value (PPV) of complete fissures is 88.1%, and the negative predictive value (NPV) is 92.9%, with an overall accuracy of 89.2%. Chartis was utilized in patients with partially complete fissures, with a PPV of 82.3%, an NPV of 84.6%, and an accuracy of 83.3%.
Conclusion:
Combining diagnostic tools could reduce the burden on patients and the healthcare system while providing clinicians with a better means for patient selection for EBV therapy.
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