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Abdom Radiol (NY). 2019 May;44(5):1785-1794. doi: 10.1007/s00261-018-01892-2.

Prediction of liver remnant regeneration after living donor liver transplantation using preoperative CT texture analysis.

Kim JE1, Kim JH2,3,4, Park SJ1, Choi SY5, Yi NJ6, Han JK1,7,8.

Author information

1
Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
2
Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea. jhkim2008@gmail.com.
3
Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea. jhkim2008@gmail.com.
4
Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea. jhkim2008@gmail.com.
5
Department of Radiology, Soonchunhyang University Bucheon Hospital, Bucheon-Si, Gyeonggi-Do, South Korea.
6
Department of Surgery, Seoul National University Hospital, Seoul, Republic of Korea.
7
Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea.
8
Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea.

Abstract

PURPOSE:

To predict the rate of liver regeneration after living donor liver transplantation (LDLT) using pre-operative computed tomography (CT) texture analysis.

MATERIALS AND METHODS:

112 living donors who performed right hepatectomy for LDLT were included retrospectively. We measured the volume of future remnant liver (FLR) on pre-operative CT and the volume of remnant liver (LR) on follow-up CT, taken at a median of 123 days after transplantation. The regeneration index (RI) was calculated using the following equation: [Formula: see text]. Computerized texture analysis of the semi-automatically segmented FLR was performed. We used a stepwise, multivariable linear regression to assess associations of clinical features and texture parameters in relation to RI and to make the best-fit predictive model.

RESULTS:

The mean RI was 110.7 ± 37.8%, highly variable ranging from 22.4% to 247.0%. Among texture parameters, volume of FLR, standard deviation, variance, and gray level co-occurrence matrices (GLCM) contrast were found to have significant correlations between RI. In multivariable analysis, smaller volume of FLR (ß - 0.17, 95% CI - 0.22 to - 0.13) and lower GLCM contrast (ß - 1.87, 95% CI - 3.64 to - 0.10) were associated with higher RI. The regression equation predicting RI was following: RI = 203.82 + 10.42 × pre-operative serum total bilirubin (mg/dL) - 0.17 × VFLR (cm3) - 1.87 × GLCM contrast (× 100).

CONCLUSION:

Volume of FLR and GLCM contrast were independent predictors of RI, showing significant negative correlations. Pre-operative CT with texture analysis can be useful for predicting the rate of liver regeneration in living donor of liver transplantation.

KEYWORDS:

Liver; Liver transplantation; Regeneration; Tissue Donor; Tomography

PMID:
30612157
DOI:
10.1007/s00261-018-01892-2

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