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A Challenge for Emphysema Quantification Using a Deep Learning Algorithm With Low-dose Chest Computed Tomography.

Hyewon Choi1, Hyungjin Kim2, Kwang Nam Jin3

  • 1Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine.

Journal of Thoracic Imaging
|June 24, 2022
PubMed
Summary

Deep learning algorithms can accurately quantify emphysema using low-dose chest computed tomography (LDCT) by converting it to simulate standard-dose CT (SDCT). This study identified clinically relevant AI models for improved emphysema assessment.

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Area of Science:

  • Radiology
  • Artificial Intelligence
  • Medical Imaging

Background:

  • Emphysema quantification is crucial for diagnosing and managing chronic obstructive pulmonary disease (COPD).
  • Low-dose chest computed tomography (LDCT) is preferred for lung screening but may have limitations in emphysema quantification compared to standard-dose CT (SDCT).
  • Deep learning (DL) offers potential for image enhancement and quantitative analysis.

Purpose of the Study:

  • To identify clinically relevant deep learning algorithms for emphysema quantification using LDCT.
  • To evaluate the performance of DL models in converting LDCT to simulate SDCT for accurate emphysema assessment.

Main Methods:

  • A competition was organized for emphysema quantification using LDCT.
  • Seven research teams developed DL algorithms to convert LDCT into simulated SDCT.
  • Performance was evaluated using intraclass correlation coefficient (ICC), categorical agreement, and cosine similarity on a test set of 90 CT scans.

Main Results:

  • The top 3 DL algorithms achieved converted LDCT values for LAA-950HU that closely matched SDCT.
  • The first-place algorithm demonstrated high agreement with SDCT (ICC: 0.94, categorical agreement: 0.71, cosine similarity: 0.97).
  • Converted LDCT showed significantly improved emphysema quantification compared to unconverted LDCT.

Conclusions:

  • Deep learning-based CT conversion strategies enable feasible and accurate emphysema quantification using LDCT.
  • This approach holds promise for improving emphysema assessment in clinical practice.