Value of a computer-Aided detection system based on chest tomosynthesis imaging for the detection of pulmonary nodules

Yoshitake Yamada, Eisuke Shiomi, Masahiro Hashimoto, Takayuki Abe, Masaki Matsusako, Yukihisa Saida, Kenji Ogawa

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

Purpose: To assess the value of a computer-Aided detection (CAD) system for the detection of pulmonary nodules on chest tomosynthesis images. Materials and Methods: Fifty patients with and 50 without pulmonary nodules underwent both chest tomosynthesis and multidetector computed tomography (CT) on the same day. Fifteen observers (five interns and residents, five chest radiologists, and five abdominal radiologists) independently evaluated tomosynthesis images of 100 patients for the presence of pulmonary nodules in a blinded and randomized manner, first without CAD, then with the inclusion of CAD marks. Multidetector CT images served as the reference standard. Free-response receiver operating characteristic analysis was used for the statistical analysis. Results: The pooled diagnostic performance of 15 observers was significantly better with CAD than without CAD (figure of merit [FOM], 0.74 vs 0.71, respectively; P = .02). The average true-positive fraction and false-positive rate per all cases with CAD were 0.56 and 0.26, respectively, whereas those without CAD were 0.47 and 0.20, respectively. Subanalysis showed that the diagnostic performance of interns and residents was significantly better with CAD than without CAD (FOM, 0.70 vs 0.62, respectively; P = .001), whereas for chest radiologists and abdominal radiologists, the FOM with CAD values were greater but not significantly: 0.80 versus 0.78 (P = .38) and 0.74 versus 0.73 (P = .65), respectively. Conclusion: CAD significantly improved diagnostic performance in the detection of pulmonary nodules on chest tomosynthesis images for interns and residents, but provided minimal benefit for chest radiologists and abdominal radiologists.

Original languageEnglish
Pages (from-to)333-339
Number of pages7
JournalRadiology
Volume287
Issue number1
DOIs
Publication statusPublished - 2018 Apr

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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