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Dual-energy computed tomography for non-invasive prediction of the risk of oesophageal variceal bleeding with hepatitis B cirrhosis

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

Abstract

Objective

Oesophageal variceal bleeding (OVB) is a fatal complication of cirrhosis and/or portal hypertension. We aimed to develop a non-invasive prediction model for the risk of OVB using dual-energy computed tomography (CT).

Methods

317 oesophageal varices (OV) patients with hepatitis B virus-related cirrhosis were retrospectively assessed from January 2018 to December 2018. All patients underwent dual-energy CT scans within 14 days before endoscopy. 222 of 317 patients (174 OVB-negative patients and 48 OVB-positive patients) were included in the training cohort and 95 patients (74 OVB-negative patients and 21 OVB-positive patients) were included in the validation cohort chronologically. A model with the selected conventional CT features and a model with the conventional CT and dual-energy CT features were developed. The prediction accuracy was evaluated using the receiver operating characteristic (ROC) curve. The accuracy and reproducibility of the models for OVB risk prediction of cirrhosis were validated by the validation cohort. The areas under the curve (AUC) of the two models were compared with Delong test.

Results

Diameter of oesophageal vein (OV(mm)), diameter of splenic vein (SPV(mm)), ascites (AS), iodine concentration in short gastric vein (SGV(HU)), iodine concentration in spleen (SP(HU)) were independent predictors of OVB risk (P < 0.05). Then, we developed a model with the selected conventional CT features [OV(mm), SPV(mm), AS] and a model with the conventional CT and dual-energy CT features [OV(mm), SPV(mm), AS, SGV(HU), SP(HU)]. The AUCs of the model built with the conventional CT and dual-energy CT features were higher than the model built only with the conventional CT features in the training (0.839 vs 0.809) and validation cohorts (0.798 vs 0.738).

Conclusion

The non-invasive prediction model developed with the conventional CT and dual-energy CT features may have added value in noninvasively predicting OVB than the model built only with the conventional CT features and may have significant clinical implications on early prevention and treatment of OVB.

Advances in knowledge

Combination of dual-energy CT with conventional CT may have added value for non-invasive prediction of OVB compared to conventional CT.

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Acknowledgements

We would like to thank Editage (www.editage.jp) for English language editing.

Funding

This work was supported by Lanzhou University Second Hospital “Cuiying Technology Innovation Plan” Applied Basic Research Project [CY2018-QN09].

Author information

Author notes

  1. Hong Liu, Jianqing Sun, and Xianwang Liu have contributed equally to this work.

Authors and Affiliations

  1. Radiology of Department, Lanzhou University Second Hospital, Cuiyingmen No.82, Chengguan District, Lanzhou, 730030, People’s Republic of China

    Hong Liu, Xianwang Liu, Qing Zhou, Juan Deng & Junlin Zhou

  2. Second Clinical School, Lanzhou University, Lanzhou, People’s Republic of China

    Hong Liu, Xianwang Liu, Guangyao Liu, Qing Zhou, Juan Deng & Junlin Zhou

  3. Key Laboratory of Medical Imaging of Gansu Province, Lanzhou University, Lanzhou, People’s Republic of China

    Hong Liu, Xianwang Liu, Qing Zhou, Juan Deng & Junlin Zhou

  4. Shukun (Beijing) Technology Co., Ltd., Jinhui Bd, Qiyang Rd, Beijing, 100102, China

    Jianqing Sun

  5. Magnetic Resonance of Department, Lanzhou University Second Hospital, Lanzhou, People’s Republic of China

    Guangyao Liu

Authors
  1. Hong Liu
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Corresponding author

Correspondence to Junlin Zhou.

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This retrospective study was approved by the institutional review board. All patients waived the informed consent form requirement.

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Liu, H., Sun, J., Liu, X. et al. Dual-energy computed tomography for non-invasive prediction of the risk of oesophageal variceal bleeding with hepatitis B cirrhosis. Abdom Radiol 46, 5190–5200 (2021). https://doi.org/10.1007/s00261-021-03251-0

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  • DOI: https://doi.org/10.1007/s00261-021-03251-0

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