Using Dynamic 99mTc-GSA SPECT/CT Fusion Images for Hepatectomy Planning and Postoperative Liver Failure Prediction

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Available tools in liver surgery planning rely on the future remnant liver (FRL) volume. Inappropriate decision might be made since the same FRL volume might represent different liver functions depending on the severity of underlying liver damage. This study developed an alternative system to estimate FRL function and to predict the risk of postoperative liver failure.


Current study recruited 71 prehepatectomy patients and 71 healthy volunteers. A technetium-99-labelled asialoglycoproteins was given to participants and SPECT was used to capture the intensity of the signal, represented by uptake index (UI). The agreement between preoperative UI values, liver function tests, and Child scores were evaluated. Linear regression was used to evaluate the agreement between predicted UI for FRL and postoperative UI values. Area under the receiver operating characteristic (AUC) curve was used to evaluate the discriminative performance of UI in differentiating patient with high risk of liver failure.


Preoperative UIs are highly correlated with Child score (P < 0.0001), especially to identify patients with ascites and elevated bilirubin. The predicted UIs were in close agreement with the actual postoperative UI values (r = 0.95 P < 0.001). The AUC analysis indicated that UI values had a high accuracy in predicting the risk of liver failure (AUC = 0.95, P < 0.0001). The best cut-off point was 0.9 and the corresponding sensitivity was 100 % and specificity was 92 %.


The new methodology reliably estimates FRL function and predicts the risk of liver failure. It provides a visual aid for liver surgeon in surgery planning and risk assessment.

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The authors thank EDDA Technique Corp, Ltd. for their collaboration and assistance in the computerization and image development of our system. This work was supported by the China Medical Board of New York (CMB) (06-837 and 11-045), National Natural Science Foundation of China (30901453 and 81201566) and National Key Technology Research and Development Program of China (BAI06B01).


All authors declared: no financial relationships with any organizations that might have an interest in the submitted work; no other relationships or activities have influenced the submitted work.

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Correspondence to Yilei Mao MD or Jiping Wang MD.

Additional information

Yilei Mao, Shunda Du and Jiantao Ba contribute equally to the paper.

Trial Registration Identifier NCT01350726.

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Mao, Y., Du, S., Ba, J. et al. Using Dynamic 99mTc-GSA SPECT/CT Fusion Images for Hepatectomy Planning and Postoperative Liver Failure Prediction. Ann Surg Oncol 22, 1301–1307 (2015).

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  • Liver Failure
  • Receiver Operating Characteristic Analysis
  • Future Remnant Liver
  • Peking Union Medical College
  • Postoperative Liver Failure