Performance of Deep Learning Model in Detecting Operable Lung Cancer With Chest Radiographs

Journal of Thoracic Imaging
Min Jae ChaKyung Soo Lee

Abstract

The aim of this study was to evaluate the diagnostic performance of a trained deep convolutional neural network (DCNN) model for detecting operable lung cancer with chest radiographs (CXRs). The institutional review board approved this study. A deep learning model (DLM) based on DCNN was trained with 17,211 CXRs (5700 CT-confirmed lung nodules in 3500 CXRs and 13,711 normal CXRs), finally augmented to 600,000 images. For validation, a trained DLM was tested with 1483 CXRs with surgically resected lung cancer, marked and scored by 2 radiologists. Furthermore, diagnostic performances of DLM and 6 human observers were compared with 500 cases (200 visible T1 lung cancer on CXR and 300 normal CXRs) and analyzed using free-response receiver-operating characteristics curve (FROC) analysis. The overall detection rate of DLM for resected lung cancers (27.2±14.6 mm) was a sensitivity of 76.8% (1139/1483) with a false positive per image (FPPI) of 0.3 and area under the FROC curve (AUC) of 0.732. In the comparison with human readers, DLM demonstrated a sensitivity of 86.5% at 0.1 FPPI and a sensitivity of 92% at 0.3 FPPI with AUC of 0.899 at an FPPI range of 0.03 to 0.44 for detecting visible T1 lung cancers, which were superior to the ave...Continue Reading

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Citations

Dec 25, 2019·Journal of Ultrasound in Medicine : Official Journal of the American Institute of Ultrasound in Medicine·Michael Blaivas, Laura Blaivas
Nov 26, 2019·Expert Review of Respiratory Medicine·Tae Jung KimKyung Soo Lee
Apr 24, 2020·Korean Journal of Radiology : Official Journal of the Korean Radiological Society·Eui Jin Hwang, Chang Min Park
Aug 25, 2020·Machine Vision and Applications·Hanan FarhatRima Kilany
Oct 2, 2020·Journal of the American College of Emergency Physicians Open·Michael BlaivasMatthew White
Dec 3, 2020·Journal of Clinical Medicine·J Luis Espinoza, Le Thanh Dong
Jun 26, 2021·Medical Image Analysis·Erdi ÇallıKeelin Murphy
Jul 8, 2021·Journal of Medical Imaging and Radiation Oncology·Daniel A Moses
Aug 3, 2021·Computational and Mathematical Methods in Medicine·Wu DengJia Xu
Sep 1, 2021·Radiology·Eui Jin HwangChang Min Park

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