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Lung nodule CAD software as a second reader: a multicenter study.

Charles S White1, Robert Pugatch, Thomas Koonce

  • 1University of Maryland Medical Center, 22 S. Greene Street, Baltimore, MD 21201, USA. cwhite@umm.edu

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Computed tomography (CT) lung nodule computer-aided detection (CAD) software improved radiologist sensitivity for detecting pulmonary nodules. This second reader tool enhanced diagnostic performance in a multicenter trial.

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Area of Science:

  • Medical Imaging
  • Radiology
  • Artificial Intelligence in Medicine

Background:

  • Pulmonary nodules require accurate detection for timely diagnosis and treatment.
  • Computer-aided detection (CAD) software is increasingly used to assist radiologists.
  • Evaluating CAD software as a supplementary tool is crucial for improving diagnostic accuracy.

Purpose of the Study:

  • To assess the efficacy of computer-aided detection (CAD) software as a second reader for identifying lung nodules on computed tomography (CT) scans.
  • To quantify the impact of CAD software on radiologist performance in a multicenter setting.

Main Methods:

  • A multicenter study involving 109 patients and 10 radiologist readers.
  • Chest CT scans were interpreted by radiologists, first without and then with CAD software assistance.
  • Performance was measured using receiver operating characteristic (ROC) curves to compare detection rates.

Main Results:

  • Computer-aided detection (CAD) software increased the area under the curve (AUC) from 86.7% to 88.7%, indicating improved performance.
  • The average improvement in AUC with CAD software was 1.9%.
  • Enhanced sensitivity was observed in patients with cancer compared to those without.

Conclusions:

  • Computer-aided detection (CAD) software effectively serves as a second reader, enhancing radiologist sensitivity in detecting pulmonary nodules.
  • The study demonstrates the value of integrating CAD software into the diagnostic workflow for lung nodule detection.