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Incorporation of a computer-aided vessel-suppression system to detect lung nodules in CT images: effect on sensitivity and reading time in routine clinical settings

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Abstract

Purpose

To evaluate whether a computer-aided vessel-suppression system improves lung nodule detection in routine clinical settings.

Materials and methods

We used computer software that automatically suppresses pulmonary vessels on chest CT while preserving pulmonary nodules. Sixty-one chest CT images were included in our study. Three radiologists independently read either standard CT images alone or both computer-aided CT and standard CT images randomly to detect a pulmonary nodule ≥ 4 mm in diameter. After an interval of at least 15 days to avoid recall bias, the three radiologists interpreted the counterpart images of the same patients. The reference standard was decided by an expert panel. The primary endpoint was sensitivity. The secondary endpoint was interpretation time.

Results

The average sensitivity improved with computer-aided CT (72% for standard CT vs. 84% for computer-aided CT, p = 0.02). There was no difference in the false-positive rate (21% for both standard CT and computer-aided CT, p = 0.98). Although the average reading time was 9.5% longer for computer-aided plus standard CT compared with standard CT alone, the difference was not significant (p = 0.11).

Conclusion

Vessel-suppressed CT images helped radiologists to improve the sensitivity of pulmonary nodule detection without compromising the false-positive rate.

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Correspondence to Taku Takaishi.

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The authors declare that they have no conflict of interest.

Ethical approval

This study was approved by the local ethics review board and informed consent was waived due to the retrospective nature of this study.

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Takaishi, T., Ozawa, Y., Bando, Y. et al. Incorporation of a computer-aided vessel-suppression system to detect lung nodules in CT images: effect on sensitivity and reading time in routine clinical settings. Jpn J Radiol 39, 159–164 (2021). https://doi.org/10.1007/s11604-020-01043-y

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  • DOI: https://doi.org/10.1007/s11604-020-01043-y

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