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

  • Ji-Eun Kim
  • Jung Hoon KimEmail author
  • Sang Joon Park
  • Seo-Youn Choi
  • Nam-Joon Yi
  • Joon Koo Han



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: \( [(V_{\text{LR}} - V_{\text{FLR}} )/V_{\text{FLR}} ]\, \times \,100 \). 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.


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).


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.


Liver Liver transplantation Tissue Donor Regeneration Tomography 



Living donor liver transplantation


Computed tomography


Regions of interest


Future liver remnant


Standard deviation


Gray-Level Co-occurrence Matrix


Angular second moment


GLCM inverse difference moment


Liver remnant


Akaike information criteria


Variance inflation factor


Confidence intervals



We would like to thank Bonnie Hami, MA (USA) and Seunghyun Kim for her editorial assistance in the preparation of this manuscript.

Compliance with ethical standards

Conflict of interest

All authors confirm that no disclosure of potential conflicts of interest.

Ethical approval

This retrospective study was approved by our institutional review board, and the requirement to obtain written, informed consent was waived.


  1. 1.
    Haga J, Shimazu M, Wakabayashi G, et al. (2008) Liver regeneration in donors and adult recipients after living donor liver transplantation. Liver Transpl 14:1718–1724CrossRefGoogle Scholar
  2. 2.
    Taner CB, Dayangac M, Akin B, et al. (2008) Donor safety and remnant liver volume in living donor liver transplantation. Liver Transpl 14:1174–1179CrossRefGoogle Scholar
  3. 3.
    Kim PT, Testa G (2016) Living donor liver transplantation in the USA. Hepatobiliary Surg Nutr 5:133–140CrossRefGoogle Scholar
  4. 4.
    Broelsch CE, Burdelski M, Rogiers X, et al. (1994) Living donor for liver transplantation. Hepatology 20:49S–55SCrossRefGoogle Scholar
  5. 5.
    Lee SY, Ko GY, Gwon DI, et al. (2004) Living donor liver transplantation: complications in donors and interventional management. Radiology 230:443–449CrossRefGoogle Scholar
  6. 6.
    Hashikura Y, Ichida T, Umeshita K, et al. (2009) Donor complications associated with living donor liver transplantation in Japan. Transplantation 88:110–114CrossRefGoogle Scholar
  7. 7.
    Kamel IR, Kruskal JB, Warmbrand G, et al. (2001) Accuracy of volumetric measurements after virtual right hepatectomy in potential donors undergoing living adult liver transplantation. AJR Am J Roentgenol 176:483–487CrossRefGoogle Scholar
  8. 8.
    Emiroglu R, Coskun M, Yilmaz U, et al. (2006) Safety of multidetector computed tomography in calculating liver volume for living-donor liver transplantation. Transplant Proc 38:3576–3578CrossRefGoogle Scholar
  9. 9.
    Joyeux H, Berticelli J, Chemouny S, Masson B, Borianne P (2003) Semi-automatic measurements of hepatic lobes. Application to study of liver volumes. Analysis of 50 computed tomography of normal liver. Ann Chir 128:251–255CrossRefGoogle Scholar
  10. 10.
    Leelaudomlipi S, Sugawara Y, Kaneko J, et al. (2002) Volumetric analysis of liver segments in 155 living donors. Liver Transpl 8:612–614CrossRefGoogle Scholar
  11. 11.
    Kim SJ, Kim DG, Chung ES, et al. (2006) Adult living donor liver transplantation using the right lobe. Transplant Proc 38:2117–2120CrossRefGoogle Scholar
  12. 12.
    Hiroshige S, Shimada M, Harada N, et al. (2003) Accurate preoperative estimation of liver-graft volumetry using three-dimensional computed tomography. Transplantation 75:1561–1564CrossRefGoogle Scholar
  13. 13.
    Kassner A, Thornhill RE (2010) Texture analysis: a review of neurologic MR imaging applications. AJNR Am J Neuroradiol 31:809–816CrossRefGoogle Scholar
  14. 14.
    Tourassi GD (1999) Journey toward computer-aided diagnosis: role of image texture analysis. Radiology 213:317–320CrossRefGoogle Scholar
  15. 15.
    Bayanati H, Thornhill RE, Souza CA, et al. (2015) Quantitative CT texture and shape analysis: can it differentiate benign and malignant mediastinal lymph nodes in patients with primary lung cancer? European Radiology 25:480–487CrossRefGoogle Scholar
  16. 16.
    Ravanelli M, Farina D, Morassi M, et al. (2013) Texture analysis of advanced non-small cell lung cancer (NSCLC) on contrast-enhanced computed tomography: prediction of the response to the first-line chemotherapy. European Radiology 23:3450–3455CrossRefGoogle Scholar
  17. 17.
    Ganeshan B, Abaleke S, Young RCD, Chatwin CR, Miles KA (2010) Texture analysis of non-small cell lung cancer on unenhanced computed tomography: initial evidence for a relationship with tumour glucose metabolism and stage. Cancer Imaging 10:137–143CrossRefGoogle Scholar
  18. 18.
    Olthoff KM, Emond JC, Shearon TH, et al. (2015) Liver regeneration after living donor transplantation: adult-to-adult living donor liver transplantation cohort study. Liver Transpl 21:79–88CrossRefGoogle Scholar
  19. 19.
    Boykov YY, Jolly M-P (2001) Interactive graph cuts for optimal boundary & region segmentation of objects in ND imagesComputer Vision, 2001 ICCV 2001 Proceedings Eighth IEEE International Conference on. IEEE, pp 105-112Google Scholar
  20. 20.
    Ger R (1989) Surgical anatomy of the liver. Surg Clin North Am 69:179–192CrossRefGoogle Scholar
  21. 21.
    Chambolle A (2004) An algorithm for total variation minimization and applications. Journal of Mathematical imaging and vision 20:89–97CrossRefGoogle Scholar
  22. 22.
    Zappa M, Dondero F, Sibert A, et al. (2009) Liver regeneration at day 7 after right hepatectomy: global and segmental volumetric analysis by using CT. Radiology 252:426–432CrossRefGoogle Scholar
  23. 23.
    Sakamoto T, Ezure T, Lunz J, et al. (2000) Concanavalin A simultaneously primes liver hematopoietic and epithelial progenitor cells for parallel expansion during liver regeneration after partial hepatectomy in mice. Hepatology 32:256–267CrossRefGoogle Scholar
  24. 24.
    Botha JF, Langnas AN, Campos BD, et al. (2010) Left lobe adult-to-adult living donor liver transplantation: small grafts and hemiportocaval shunts in the prevention of small-for-size syndrome. Liver Transpl 16:649–657CrossRefGoogle Scholar
  25. 25.
    Davnall F, Yip CS, Ljungqvist G, et al. (2012) Assessment of tumor heterogeneity: an emerging imaging tool for clinical practice? Insights Imaging 3:573–589CrossRefGoogle Scholar
  26. 26.
    Ganeshan B, Miles KA (2013) Quantifying tumour heterogeneity with CT. Cancer Imaging 13:140–149CrossRefGoogle Scholar
  27. 27.
    Ju MK, Choi GH, Park JS, et al. (2012) Difference of regeneration potential between healthy and diseased liver. Transplant Proc 44:338–340CrossRefGoogle Scholar
  28. 28.
    Kele PG, van der Jagt EJ, Gouw AS, et al. (2013) The impact of hepatic steatosis on liver regeneration after partial hepatectomy. Liver Int 33:469–475CrossRefGoogle Scholar
  29. 29.
    Dello SA, Kele PG, Porte RJ, et al. (2014) Influence of preoperative chemotherapy on CT volumetric liver regeneration following right hemihepatectomy. World J Surg 38:497–504CrossRefGoogle Scholar
  30. 30.
    Shimada M, Matsumata T, Maeda T, et al. (1994) Hepatic regeneration following right lobectomy: estimation of regenerative capacity. Surg Today 24:44–48CrossRefGoogle Scholar
  31. 31.
    Kwon KH, Kim YW, Kim SI, et al. (2003) Postoperative liver regeneration and complication in live liver donor after partial hepatectomy for living donor liver transplantation. Yonsei Med J 44:1069–1077CrossRefGoogle Scholar
  32. 32.
    Paluszkiewicz R, Zieniewicz K, Kalinowski P, et al. (2009) Liver regeneration in 120 consecutive living-related liver donors. Transplant Proc 41:2981–2984CrossRefGoogle Scholar
  33. 33.
    Gaglio PJ, Liu H, Dash S, et al. (2002) Liver regeneration investigated in a non-human primate model (Macaca mulatta). J Hepatol 37:625–632CrossRefGoogle Scholar
  34. 34.
    Greig JD, Krukowski ZH, Matheson NA (1988) Surgical morbidity and mortality in one hundred and twenty-nine patients with obstructive jaundice. Br J Surg 75:216–219CrossRefGoogle Scholar
  35. 35.
    Scheingraber S, Bauer M, Bauer I, et al. (2009) Inhibition of hemoxygenase-1 improves survival after liver resection in jaundiced rats. Eur Surg Res 42:157–167CrossRefGoogle Scholar
  36. 36.
    Cherqui D, Benoist S, Malassagne B, et al. (2000) Major liver resection for carcinoma in jaundiced patients without preoperative biliary drainage. Arch Surg 135:302–308CrossRefGoogle Scholar
  37. 37.
    Das BC, Isaji S, Kawarada Y (2001) Analysis of 100 consecutive hepatectomies: risk factors in patients with liver cirrhosis or obstructive jaundice. World J Surg 25:266-272; discussion 272-263Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Ji-Eun Kim
    • 1
  • Jung Hoon Kim
    • 1
    • 2
    • 3
    Email author
  • Sang Joon Park
    • 1
  • Seo-Youn Choi
    • 4
  • Nam-Joon Yi
    • 5
  • Joon Koo Han
    • 1
    • 2
    • 3
  1. 1.Department of RadiologySeoul National University HospitalSeoulRepublic of Korea
  2. 2.Department of RadiologySeoul National University College of MedicineSeoulRepublic of Korea
  3. 3.Institute of Radiation MedicineSeoul National University Medical Research CenterSeoulRepublic of Korea
  4. 4.Department of RadiologySoonchunhyang University Bucheon HospitalBucheon-Si, Gyeonggi-DoSouth Korea
  5. 5.Department of SurgerySeoul National University HospitalSeoulRepublic of Korea

Personalised recommendations