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Related Experiment Video

Updated: Sep 19, 2025

Evaluating Regional Pulmonary Deposition using Patient-Specific 3D Printed Lung Models
07:56

Evaluating Regional Pulmonary Deposition using Patient-Specific 3D Printed Lung Models

Published on: November 11, 2020

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Bronchoscopic lung volume reduction: model for assisted target lobe selection.

Logan Hostetter1, Leah M Brown2, Srinivasan Rajagopalan3

  • 1Department of Internal Medicine, Division of Pulmonary and Critical Care, Mayo Clinic, Rochester, Minnesota, USA.

BMJ Open Respiratory Research
|June 5, 2025
PubMed
Summary

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A new mathematical model aids in selecting patients and target lobes for endobronchial valve (EBV) lung volume reduction, improving outcomes for severe emphysema. This objective approach enhances clinical decision-making for this potent palliative procedure.

Area of Science:

  • Pulmonary Medicine
  • Medical Imaging
  • Biostatistics

Background:

  • Bronchoscopic lung volume reduction using endobronchial valves (EBV) effectively treats severe emphysema, improving lung function and quality of life.
  • Optimal patient and treatment lobe selection are critical for successful EBV outcomes, often relying on multidisciplinary teams and clinical experience.

Purpose of the Study:

  • To develop and validate a mathematical model for objective patient and target lobe selection for EBV procedures.
  • To assist clinicians in making informed decisions for EBV therapy.

Main Methods:

  • Quantitative high-resolution computed tomography (HRCT) analysis from 119 patients was used to develop two logistic regression models for EBV candidacy and target lobe selection.
  • Models were based on normalized HRCT variables: fissure completeness, voxel density (HU < -910, HU < -950), and lobar volumes.
Keywords:
BronchoscopyEmphysemaLung Volume Reduction Surgery

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  • A separate cohort of 50 patients validated the predictive model.
  • Main Results:

    • The training cohort showed high performance with an AUC of 0.91, 81% accuracy, 93% sensitivity, and 78% specificity.
    • The validation cohort demonstrated strong results with an AUC of 0.89, 84% accuracy, 88% sensitivity, and 83% specificity.
    • The model's predictions closely aligned with multidisciplinary team decisions.

    Conclusions:

    • Endobronchial valve lung volume reduction is a powerful palliative treatment for hyperinflated emphysema.
    • The developed mathematical model objectively aids in selecting candidates and target lobes, leveraging multidisciplinary expertise.
    • Future research should explore the model's utility in predicting lobar collapse and functional improvements post-treatment.