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Prediction of liver regeneration in recipients after living-donor liver transplantation in using preoperative CT texture analysis and clinical features

  • Hepatobiliary
  • Published:
Abdominal Radiology Aims and scope Submit manuscript

A Letter to the Editor to this article was published on 06 July 2020

A Letter to the Editor to this article was published on 07 May 2020

Abstract

Purpose

The aim of the study is to predict the rate of liver regeneration in recipients after living-donor liver transplantation using preoperative CT texture and shape analysis of the future graft.

Methods

102 donor–recipient pairs who underwent living-donor liver transplantation using right lobe grafts were retrospectively included. We semi-automatically segmented the future graft from preoperative CT. The volume of the future graft (LVpre) was measured, and texture and shape analyses were performed. The graft liver was segmented from postoperative follow-up CT and the volume of the graft (LVpost) was measured. The regeneration index was defined by the following equation: [(LVpost−LVpre)/LVpre] × 100(%). We performed a stepwise, multivariate linear regression analysis to investigate the association between clinical, texture and shape parameters and the RI and to make the best-fit predictive model.

Results

The mean regeneration index was 47.5 ± 38.6%. In univariate analysis, the volume of the future graft, energy, effective diameter, surface area, sphericity, roundnessm, compactness1, and grey-level co-occurrence matrix contrast as well as several clinical parameters were significantly associated with the regeneration index (p < 0.05). The best-fit predictive model for the regeneration index made by multivariate analysis was as follows: Regeneration index (%) = 127.020–0.367 × effective diameter − 1.827 × roundnessm + 47.371 × recipient body surface area (m2) + 12.041 × log(recipient white blood cell count) (× 103/μL)+ 18.034 (if the donor was female).

Conclusion

The effective diameter and roundnessm of the future graft were associated with liver regeneration. Preoperative CT texture analysis of future grafts can be useful for predicting liver regeneration in recipients after living-donor liver transplantation.

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Abbreviations

LDLT:

Living-donor liver transplantation

CTTA:

CT texture analysis

LC:

Liver cirrhosis

HBV:

Hepatitis B virus

LVpre :

Volume of the future graft

GLCM:

Gray-level co-occurrence matrix

LVpost :

Volume of the transplanted liver

RI:

Regeneration index

GRWR:

Graft-to-recipient weight ratio

rWBC:

White blood cell count of the recipient

rBSA:

Recipient body surface area

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Acknowledgements

We would like to thank Bonnie Hami, MA (USA) for her editorial assistance in the preparation of this manuscript. Thanks to Juhee Lee, Medical Research Collaborating Center, Seoul National University Hospital, Seoul, Korea, for assistance with statistical analysis.

Funding

No grant support has been received.

Author information

Authors and Affiliations

  1. Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea

    Junghoan Park, Jung Hoon Kim, Ji-Eun Kim, Sang Joon Park & Joon Koo Han

  2. Department of Radiology and Institute of Radiation Medicine, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea

    Jung Hoon Kim & Joon Koo Han

  3. Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Korea

    Jung Hoon Kim & Joon Koo Han

  4. Department of Surgery, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea

    Nam-Joon Yi

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  1. Junghoan Park
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Correspondence to Jung Hoon Kim.

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Ethical approval

Our institutional review board (Seoul National University Hospital Institutional Review Board) approved this study.

Informed consent

Informed consent was waived due to the retrospective nature of the study (IRB No. 1902–090-1010).

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Park, J., Kim, J.H., Kim, JE. et al. Prediction of liver regeneration in recipients after living-donor liver transplantation in using preoperative CT texture analysis and clinical features. Abdom Radiol 45, 3763–3774 (2020). https://doi.org/10.1007/s00261-020-02518-2

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