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The efficacy of low-dose CT with deep learning image reconstruction in the surveillance of incidentally detected pancreatic cystic lesions

  • Pancreas
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Abstract

Purpose

To evaluate the efficacy of low-dose CT (LDCT) with deep learning image reconstruction (DLIR) for the surveillance of pancreatic cystic lesions (PCLs) compared with standard-dose CT (SDCT) with adaptive statistical iterative reconstruction (ASIR-V).

Methods

The study enrolled 103 patients who underwent pancreatic CT for follow-up of incidentally detected PCLs. The CT protocol included LDCT in the pancreatic phase with 40% ASIR-V, DLIR at medium (DLIR-M) and high levels (DLIR-H), and SDCT in the portal-venous phase with 40% ASIR-V. The overall image quality and conspicuity of PCLs were qualitatively assessed using five-point scales by two radiologists. The size of PCLs, presence of thickened/enhancing walls, enhancing mural nodules, and main pancreatic duct dilatation were reviewed. CT noise and cyst-to-pancreas contrast-to-noise ratio (CNR) were measured. Qualitative and quantitative parameters were analyzed using the chi-squared test, one-way ANOVA, and t-test. Additionally, interobserver agreement was analyzed using the kappa and weighted-kappa statistics.

Results

The volume CT dose-indexes in LDCT and SDCT were 3.0 ± 0.6 mGy and 8.4 ± 2.9 mGy, respectively. LDCT with DLIR-H showed the highest overall image quality, the lowest noise, and the highest CNR. The PCL conspicuity in LDCT with either DLIR-M or DLIR-H was not significantly different from that in SDCT with ASIR-V. Other findings depicting PCLs also revealed no significant differences between LDCT with DLIR and SDCT with ASIR-V. Moreover, the results revealed good or excellent interobserver agreement.

Conclusion

LDCT with DLIR has a comparable performance with SDCT for the follow-up of incidentally detected PCLs.

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Authors and Affiliations

  1. Department of Radiology, Biomedical Research Institute, Pusan National University Hospital, and Pusan National University School of Medicine, Pusan National University, #179, Gudeok-Ro, Seo-Gu, Busan, 49241, Republic of Korea

    Sungho Koh, Nam Kyung Lee, Suk Kim & Seung Baek Hong

  2. Department of Internal Medicine, Biomedical Research Institute, Pusan National University Hospital, and Pusan National University School of Medicine, Pusan National University, Busan, Republic of Korea

    Dong Uk Kim & Sung Yong Han

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  1. Sungho Koh
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Correspondence to Nam Kyung Lee.

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Koh, S., Lee, N.K., Kim, S. et al. The efficacy of low-dose CT with deep learning image reconstruction in the surveillance of incidentally detected pancreatic cystic lesions. Abdom Radiol 48, 2585–2595 (2023). https://doi.org/10.1007/s00261-023-03958-2

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