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CT for evaluation of urolithiasis: image quality of ultralow-dose (Sub mSv) CT with knowledge-based iterative reconstruction and diagnostic performance of low-dose CT with statistical iterative reconstruction

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Abstract

Purpose

To compare radiation dose and image quality in regular, low, and ultralow-dose CT protocols, and to evaluate diagnostic performance of low-dose CT for urolithiasis.

Materials and methods

Sixty-five patients with suspected urolithiasis underwent three different scans under the regular, low, and ultralow-dose protocols. The regular dose scans were reconstructed using filtered back projection and the low-dose scans were reconstructed using a statistical iterative reconstruction. The ultralow-dose scans were reconstructed using both techniques in addition to a knowledge-based IR. Effective radiation doses were compared. Objective image noise was assessed by measuring standard deviation of HU and subjective image assessment was performed with a 3- or 5-point scale. Diagnostic performance of the low-dose image was evaluated, using the regular dose image as a standard reference and the interobserver agreement between two reviewers with different levels of experience was calculated.

Results

The effective radiation dose was significantly different in each protocol (p < 0.001) and estimated dose reduction of the low-dose and ultralow-dose protocols was 76.4% and 89.8%, respectively. The knowledge-based iterative reconstruction algorithm showed poorer subjective image quality than the regular and low-dose protocols, but it also had the least objective image noise. Overall, the low-dose image set showed a greater than 84% concordance rate and 100% in ureter stones larger than 3 mm. Interobserver agreement was substantial (kappa value = 0.61).

Conclusions

The knowledge-based IR can provide a better quality image while reducing radiation exposure under the same protocol. Furthermore, the diagnostic performance of the low-dose CT protocol is comparable to the regular dose scan.

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Acknowledgments

We appreciate the assistance of Philips Healthcare by providing the knowledge-based IR, IMR prototype. We also appreciate the assistance in working the study of Young Mi Chun (Philips Healthcare) and Chul Lee, RT.

Author information

Author notes

  1. Jong Kyou Kwon

    Present address: Department of Urology, Haeundae Paik Hospital, Inje University College of Medicine, 875, Haeundae-ro, Haeundae-gu, Busan, 612-896, Korea

Authors and Affiliations

  1. Department of Radiology, Chung-Ang University College of Medicine, Chung-Ang University Hospital, 102, Heukseok-ro, Dongjak-gu, Seoul, 156-755, Korea

    Joonho Hur, Sung Bin Park, Jong Beum Lee, Hyun Jeong Park & Yang Soo Kim

  2. Department of Urology, Chung-Ang University College of Medicine, Chung-Ang University Hospital, 102, Heukseok-ro, Dongjak-gu, Seoul, 156-755, Korea

    In Ho Chang & Jong Kyou Kwon

Authors
  1. Joonho Hur
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  2. Sung Bin Park
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  3. Jong Beum Lee
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  4. Hyun Jeong Park
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Correspondence to Sung Bin Park.

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Hur, J., Park, S.B., Lee, J.B. et al. CT for evaluation of urolithiasis: image quality of ultralow-dose (Sub mSv) CT with knowledge-based iterative reconstruction and diagnostic performance of low-dose CT with statistical iterative reconstruction. Abdom Imaging 40, 2432–2440 (2015). https://doi.org/10.1007/s00261-015-0411-2

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