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Quantifying emphysema in lung screening computed tomography with robust automated lobe segmentation.

Thomas Z Li1,2, Ho Hin Lee1, Kaiwen Xu3

  • 1Vanderbilt University, Department of Biomedical Engineering, Nashville, Tennessee, United States.

Journal of Medical Imaging (Bellingham, Wash.)
|July 20, 2023
PubMed
Summary

A new automated algorithm accurately segments lung lobes for emphysema quantification, improving lung cancer risk prediction. Regional emphysema in the right upper lobe is linked to higher lung cancer incidence.

Keywords:
Lobar emphysemalevel set methodlung cancer risklung screeningpulmonary lobe segmentation

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Area of Science:

  • Medical imaging analysis
  • Pulmonary medicine
  • Radiology

Background:

  • Anatomy-based emphysema quantification in lung screening computed tomography (CT) can enhance lung cancer risk assessment.
  • Accurate lung lobe segmentation is crucial for this analysis, but existing algorithms lack validation for lung screening CT data.

Purpose of the Study:

  • To develop and validate an automated lobe segmentation algorithm for robust emphysema quantification in lung screening CT.
  • To investigate the association between lobar emphysema and lung cancer incidence.

Main Methods:

  • Developed an automated lobe segmentation approach using self-supervised training, level set regularization, and radiologist-annotated finetuning.
  • Validated the algorithm on three datasets, achieving an external validation Dice score of 0.93.
  • Quantified lobar emphysema in a National Lung Screening Trial cohort and analyzed its association with lung cancer incidence.

Main Results:

  • The developed algorithm achieved a Dice score of 0.93, outperforming a leading algorithm (0.90).
  • Increased low attenuation volume in the right upper lobe was significantly associated with higher lung cancer incidence (OR: 1.97; 95% CI: [1.06, 3.66]), independent of other risk factors.
  • Quantitative lobar emphysema improved the model's fit for predicting lung cancer incidence.

Conclusions:

  • This study presents the first automated lobe segmentation algorithm validated for robustness in lung screening CT with smoking-related pathology.
  • Regional emphysema is identified as a quantitative risk factor independently associated with increased lung cancer incidence.
  • The algorithm is publicly available for research use.