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Clinical Validation of Computer-Aided Diagnosis Software for Preventing Retained Surgical Sponges

Journal of the American College of Surgeons, vol. 238, pp. 856–860

Abstract

BACKGROUND: We previously reported the successful development of a computer-aided diagnosis (CAD) system for preventing retained surgical sponges with deep learning using training data, including composite and simulated radiographs. In this study, we evaluated the efficacy of the CAD system in a clinical setting. STUDY DESIGN: A total of 1,053 postoperative radiographs obtained from patients 20 years of age or older who underwent surgery were evaluated. We implemented a foreign object detection application software on the portable radiographic device used in the operating room to detect retained surgical sponges. The results of the CAD system diagnosis were prospectively collected. RESULTS: Among the 1,053 images, the CAD system detected possible retained surgical items in 150 images. Specificity was 85.8%, which is similar to the data obtained during the development of the software. CONCLUSIONS: The validation of a CAD system using deep learning in a clinical setting showed similar efficacy as during the development of the system. These results suggest that the CAD system can contribute to the establishment of a more effective protocol than the current standard practice for preventing the retention of surgical items.

Authors 9

  1. Nagasaki University

    Affiliation as printed

    From the Department of Surgery, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki City, Japan (Kurisaki, Soyama, Yamaguchi, Matsuguma, Eguchi)

  2. Nagasaki University

    Affiliation as printed

    From the Department of Surgery, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki City, Japan (Kurisaki, Soyama, Yamaguchi, Matsuguma, Eguchi)

  3. Fujifilm (Japan)

    Affiliation as printed

    Imaging Technology Center, Research and Development Management Headquarters, FUJIFILM Corporation, Tokyo, Japan (Hamauzu, Yamada)

  4. Fujifilm (Japan)

    Affiliation as printed

    Imaging Technology Center, Research and Development Management Headquarters, FUJIFILM Corporation, Tokyo, Japan (Hamauzu, Yamada)

  5. Nagasaki University

    Affiliation as printed

    From the Department of Surgery, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki City, Japan (Kurisaki, Soyama, Yamaguchi, Matsuguma, Eguchi)

  6. Leiden University Medical Center · Erasmus MC · Delft University of Technology

    Affiliation as printed

    Educational Program Technical Medicine, Leiden University Medical Center, Delft University of Technology and Erasmus MC Rotterdam, Rotterdam, The Netherlands (Kerkhof)

  7. Leiden University Medical Center · Erasmus MC · Fujifilm (Japan) · Nagasaki University Hospital · Nagasaki University · Delft University of Technology

    Affiliation as printed

    Department of Radiology, Nagasaki University Hospital, Nagasaki City, Japan (Toya)

    Educational Program Technical Medicine, Leiden University Medical Center, Delft University of Technology and Erasmus MC Rotterdam, Rotterdam, The Netherlands (Kerkhof)

    From the Department of Surgery, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki City, Japan (Kurisaki, Soyama, Yamaguchi, Matsuguma, Eguchi)

    Imaging Technology Center, Research and Development Management Headquarters, FUJIFILM Corporation, Tokyo, Japan (Hamauzu, Yamada)

    Department of Radiology, Nagasaki University Hospital

  8. Nagasaki University Hospital

    Affiliation as printed

    Department of Radiology, Nagasaki University Hospital, Nagasaki City, Japan (Toya)

  9. Nagasaki University

    Affiliation as printed

    From the Department of Surgery, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki City, Japan (Kurisaki, Soyama, Yamaguchi, Matsuguma, Eguchi)

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