Prediction of disease severity in COPD: a deep learning approach for anomaly-based quantitative assessment of chest CT.

Journal: European radiology
Published Date: Dec 27, 2023

Abstract

OBJECTIVES: To quantify regional manifestations related to COPD as anomalies from a modeled distribution of normal-appearing lung on chest CT using a deep learning (DL) approach, and to assess its potential to predict disease severity.

Authors

  • Silvia D Almeida
    Division of Medical Image Computing, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany. silvia.diasalmeida@dkfz-heidelberg.de.
  • Tobias Norajitra
    Division of Medical Image Computing, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany.
  • Carsten T Lüth
    Interactive Machine Learning Group (IML), German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Tassilo Wald
    Division of Medical Image Computing, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany.
  • Vivienn Weru
    Division of Biostatistics, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Marco Nolden
    Medical Imaging Components, Division Medical Image Computing, DKFZ Heidelberg, Germany.
  • Paul F Jäger
    Interactive Machine Learning Group (IML), German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Oyunbileg von Stackelberg
    Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany; Translational Lung Research Center, Member of the German Lung Research Center, Heidelberg, Germany; Department of Diagnostic and Interventional Radiology With Nuclear Medicine, Thoraxklinik, Heidelberg University Hospital, Heidelberg, Germany. Electronic address: Oyunbileg.Stackelberg@med.uni-heidelberg.de.
  • Claus Peter Heussel
    Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany; Translational Lung Research Center, Member of the German Lung Research Center, Heidelberg, Germany; Department of Diagnostic and Interventional Radiology With Nuclear Medicine, Thoraxklinik, Heidelberg University Hospital, Heidelberg, Germany. Electronic address: heussel_elsevier2019@contbay.com.
  • Oliver Weinheimer
    Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany.
  • Jürgen Biederer
    Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany.
  • Hans-Ulrich Kauczor
    Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital, Im Neuenheimer Feld 110, 69120, Heidelberg, Germany.
  • Klaus Maier-Hein
    Medical Image Analysis, Division Medical Image Computing, DKFZ Heidelberg, Germany.

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