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Low tube voltage and deep-learning reconstruction for reducing radiation and contrast medium doses in thin-slice abdominal CT: a prospective clinical trial

  • Computed Tomography
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objectives

To investigate the feasibility of low-radiation dose and low iodinated contrast medium (ICM) dose protocol combining low-tube voltage and deep-learning reconstruction (DLR) algorithm in thin-slice abdominal CT.

Methods

This prospective study included 148 patients who underwent contrast-enhanced abdominal CT with either 120-kVp (600 mgL/kg, n = 74) or 80-kVp protocol (360 mgL/kg, n = 74). The 120-kVp images were reconstructed using hybrid iterative reconstruction (HIR) (120-kVp-HIR), while 80-kVp images were reconstructed using HIR (80-kVp-HIR) and DLR (80-kVp-DLR) with 0.5 mm thickness. Size-specific dose estimate (SSDE) and iodine dose were compared between protocols. Image noise, CT attenuation, and contrast-to-noise ratio (CNR) were quantified. Noise power spectrum (NPS) and edge rise slope (ERS) were used to evaluate noise texture and edge sharpness, respectively. The subjective image quality was rated on a 4-point scale.

Results

SSDE and iodine doses of 80-kVp were 40.4% (8.1 ± 0.9 vs. 13.6 ± 2.7 mGy) and 36.3% (21.2 ± 3.9 vs. 33.3 ± 4.3 gL) lower, respectively, than those of 120-kVp (both, p < 0.001). CT attenuation of vessels and solid organs was higher in 80-kVp than in 120-kVp images (all, p < 0.001). Image noise of 80-kVp-HIR and 80-kVp-DLR was higher and lower, respectively than that of 120-kVp-HIR (both p < 0.001). The highest CNR and subjective scores were attained in 80-kVp-DLR (all, p < 0.001). There were no significant differences in average NPS frequency and ERS between 120-kVp-HIR and 80-kVp-DLR (p ≥ 0.38).

Conclusion

Compared with the 120-kVp-HIR protocol, the combined use of 80-kVp and DLR techniques yielded superior subjective and objective image quality with reduced radiation and ICM doses at thin-section abdominal CT.

Clinical relevance statement

Scanning at low-tube voltage (80-kVp) combined with the deep-learning reconstruction algorithm may enhance diagnostic efficiency and patient safety by improving image quality and reducing radiation and contrast doses of thin-slice abdominal CT.

Key Points

  • Reducing radiation and iodine doses is desirable; however, contrast and noise degradation can be detrimental.

  • The 80-kVp scan with the deep-learning reconstruction technique provided better images with lower radiation and contrast doses.

  • This technique may be efficient for improving diagnostic confidence and patient safety in thin-slice abdominal CT.

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Abbreviations

CNR:

Contrast-to-noise ratio

DLR:

Deep-learning-based reconstruction

ERS:

Edge rise slope

HIR:

Hybrid iterative reconstruction

ICM:

Iodinated contrast medium

NPS:

Noise power spectrum

SSDE:

Size-specific dose estimate

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Funding

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Authors and Affiliations

  1. Department of Radiology, Yamaga Medical Center, 511 Yamaga, Kumamoto, 861-0501, Japan

    Kenichiro Yoshida

  2. Graduate School of Health Sciences, Kumamoto University, 4-24-1 Kuhonji, Chuo-ku, Kumamoto, 862-0976, Japan

    Kenichiro Yoshida

  3. Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1, Honjo, Chuo-ku, Kumamoto, 860-8556, Japan

    Yasunori Nagayama, Soichiro Ishiuchi, Takeshi Nakaura & Toshinori Hirai

  4. Department of Medical Radiation Sciences, Faculty of Life Sciences, Kumamoto University, 4-24-1 Kuhonji, Chuo-ku, Kumamoto, 862-0976, Japan

    Yoshinori Funama

  5. Department of Gastroenterology, Yamaga Medical Center, 511 Yamaga, Kumamoto, 861-0501, Japan

    Toshihiko Motohara

  6. Department of Surgery, Yamaga Medical Center, 511 Yamaga, Kumamoto, 861-0501, Japan

    Toshiro Masuda, Takatoshi Ishiko & Toru Beppu

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  1. Kenichiro Yoshida
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Correspondence to Yasunori Nagayama.

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Guarantor

The scientific guarantor of this publication is Toru Beppu.

Conflict of interest

Toshinori Hirai has received research support from Canon Medical Systems. The Canon Medical Systems had no control over the interpretation, writing, or publication of this work.

Statistics and biometry

No complex statistical methods were necessary for this paper.

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Written informed consent was obtained from all subjects (patients) in this study.

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Yoshida, K., Nagayama, Y., Funama, Y. et al. Low tube voltage and deep-learning reconstruction for reducing radiation and contrast medium doses in thin-slice abdominal CT: a prospective clinical trial. Eur Radiol (2024). https://doi.org/10.1007/s00330-024-10793-6

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  • DOI: https://doi.org/10.1007/s00330-024-10793-6

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