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Preoperative Microvascular Invasion Prediction to Assist in Surgical Plan for Single Hepatocellular Carcinoma: Better Together with Radiomics

  • Hepatobiliary Tumors
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Abstract

Background

Prediction models with or without radiomic analysis for microvascular invasion (MVI) in hepatocellular carcinoma (HCC) have been reported, but the potential for model-predicted MVI in surgical planning is unclear. Therefore, we aimed to explore the effect of predicted MVI on early recurrence after anatomic resection (AR) and non-anatomic resection (NAR) to assist surgical strategies.

Methods

Patients with a single HCC of 2–5 cm receiving curative resection were enrolled from 2 centers. Their data were used to develop (n = 230) and test (n = 219) two prediction models for MVI using clinical factors and preoperative computed tomography images. The two prediction models, clinico-radiologic model and clinico-radiologic-radiomic (CRR) model (clinico-radiologic variables + radiomic signature), were compared using the Delong test. Early recurrence based on model-predicted high-risk MVI was evaluated between AR (n = 118) and NAR (n = 85) via propensity score matching using patient data from another 2 centers for external validation.

Results

The CRR model showed higher area under the curve values (0.835–0.864 across development, test, and external validation) but no statistically significant improvement over the clinico-radiologic model (0.796–0.828). After propensity score matching, difference in 2-year recurrence between AR and NAR was found in the CRR model predicted high-risk MVI group (P = 0.005) but not in the clinico-radiologic model predicted high-risk MVI group (P = 0.31).

Conclusions

The prediction model incorporating radiomics provided an accurate preoperative estimation of MVI, showing the potential for choosing the more appropriate surgical procedure between AR and NAR.

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References

  1. Sung H, Ferlay J, Siegel RL, et al. Global Cancer Statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 Countries. CA Cancer J Clin. 2021;71(3):209–49.

    Article  Google Scholar 

  2. Forner A, Reig M, Bruix J. Hepatocellular carcinoma. Lancet. 2018;391(10127):1301–14.

    Article  Google Scholar 

  3. Marrero JA, Kulik LM, Sirlin CB, et al. Diagnosis, staging, and management of hepatocellular carcinoma: 2018 practice guidance by the american association for the study of liver diseases. Hepatology. 2018;68(2):723–50.

    Article  Google Scholar 

  4. European Association for the Study of the Liver. EASL Clinical Practice Guidelines: Management of hepatocellular carcinoma. J Hepatol. 2018;69(1):182–236.

    Article  Google Scholar 

  5. Wu JC, Huang YH, Chau GY, et al. Risk factors for early and late recurrence in hepatitis B-related hepatocellular carcinoma. J Hepatol. 2009;51(5):890–7.

    Article  Google Scholar 

  6. Chan AWH, Zhong J, Berhane S, et al. Development of pre- and post-operative models to predict early recurrence of hepatocellular carcinoma after surgical resection. J Hepatol. 2018;69(6):1284–93.

    Article  Google Scholar 

  7. Lim KC, Chow PK, Allen JC, et al. Microvascular invasion is a better predictor of tumor recurrence and overall survival following surgical resection for hepatocellular carcinoma compared to the Milan criteria. Ann Surg. 2011;254(1):108–13.

    Article  Google Scholar 

  8. Rodriguez-Peralvarez M, Luong TV, Andreana L, Meyer T, Dhillon AP, Burroughs AK. A systematic review of microvascular invasion in hepatocellular carcinoma: diagnostic and prognostic variability. Ann Surg Oncol. 2013;20(1):325–39.

    Article  Google Scholar 

  9. Chen ZH, Zhang XP, Feng JK, et al. Actual long-term survival in hepatocellular carcinoma patients with microvascular invasion: a multicenter study from China. Hepatol Int. 2021;15(3):642–50.

    Article  Google Scholar 

  10. Shindoh J, Andreou A, Aloia TA, et al. Microvascular invasion does not predict long-term survival in hepatocellular carcinoma up to 2 cm: reappraisal of the staging system for solitary tumors. Ann Surg Oncol. 2013;20(4):1223–9.

    Article  Google Scholar 

  11. Hwang S, Lee YJ, Kim KH, et al. The impact of tumor size on long-term survival outcomes after resection of solitary hepatocellular carcinoma: single-institution experience with 2558 patients. J Gastrointest Surg. 2015;19(7):1281–90.

    Article  Google Scholar 

  12. Sheng X, Ji Y, Ren GP, et al. A standardized pathological proposal for evaluating microvascular invasion of hepatocellular carcinoma: a multicenter study by LCPGC. Hepatol Int. 2020;14(6):1034–47.

    Article  Google Scholar 

  13. McHugh PP, Gilbert J, Vera S, Koch A, Ranjan D, Gedaly R. Alpha-fetoprotein and tumour size are associated with microvascular invasion in explanted livers of patients undergoing transplantation with hepatocellular carcinoma. HPB (Oxford). 2010;12(1):56–61.

    Article  Google Scholar 

  14. Cucchetti A, Piscaglia F, Grigioni AD, et al. Preoperative prediction of hepatocellular carcinoma tumour grade and micro-vascular invasion by means of artificial neural network: a pilot study. J Hepatol. 2010;52(6):880–8.

    Article  Google Scholar 

  15. Lei Z, Li J, Wu D, et al. Nomogram for preoperative estimation of microvascular invasion risk in Hepatitis B Virus-Related Hepatocellular Carcinoma within the Milan Criteria. JAMA Surg. 2016;151(4):356–63.

    Article  Google Scholar 

  16. Chou CT, Chen RC, Lin WC, Ko CJ, Chen CB, Chen YL. Prediction of microvascular invasion of hepatocellular carcinoma: preoperative CT and histopathologic correlation. AJR Am J Roentgenol. 2014;203(3):W253-259.

    Article  Google Scholar 

  17. Renzulli M, Brocchi S, Cucchetti A, et al. Can Current preoperative imaging be used to detect microvascular invasion of hepatocellular carcinoma? Radiology. 2016;279(2):432–42.

    Article  Google Scholar 

  18. Gillies RJ, Kinahan PE, Hricak H. Radiomics: Images Are More than Pictures, They Are Data. Radiology. 2016;278(2):563–77.

    Article  Google Scholar 

  19. Zheng J, Chakraborty J, Chapman WC, et al. Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma Using Quantitative Image Analysis. J Am Coll Surg. 2017;225(6):778-788 e771.

  20. Xu X, Zhang HL, Liu QP, et al. Radiomic analysis of contrast-enhanced CT predicts microvascular invasion and outcome in hepatocellular carcinoma. J Hepatol. 2019;70(6):1133–44.

    Article  Google Scholar 

  21. Meng XP, Wang YC, Zhou JY, et al. Comparison of MRI and CT for the prediction of microvascular invasion in solitary hepatocellular carcinoma based on a non-radiomics and radiomics method: Which Imaging Modality Is Better? J Magn Reson Imaging. 2021;54(2):526–36.

    Article  Google Scholar 

  22. Park VY, Choi JY, Chung YE, et al. Dynamic enhancement pattern of HCC smaller than 3 cm in diameter on gadoxetic acid-enhanced MRI: comparison with multiphasic MDCT. Liver Int. 2014;34(10):1593–602.

    Article  CAS  Google Scholar 

  23. Eguchi S, Kanematsu T, Arii S, et al. Comparison of the outcomes between an anatomical subsegmentectomy and a non-anatomical minor hepatectomy for single hepatocellular carcinomas based on a Japanese nationwide survey. Surgery. 2008;143(4):469–75.

    Article  Google Scholar 

  24. Marubashi S, Gotoh K, Akita H, et al. Anatomical versus non-anatomical resection for hepatocellular carcinoma. Br J Surg. 2015;102(7):776–84.

    Article  CAS  Google Scholar 

  25. Feng X, Su Y, Zheng S, et al. A double blinded prospective randomized trial comparing the effect of anatomic versus non-anatomic resection on hepatocellular carcinoma recurrence. HPB (Oxford). 2017;19(8):667–74.

    Article  Google Scholar 

  26. Shindoh J, Makuuchi M, Matsuyama Y, et al. Complete removal of the tumor-bearing portal territory decreases local tumor recurrence and improves disease-specific survival of patients with hepatocellular carcinoma. J Hepatol. 2016;64(3):594–600.

    Article  Google Scholar 

  27. Zhong XP, Zhang YF, Mei J, et al. Anatomical versus non-anatomical resection for hepatocellular carcinoma with microscope vascular invasion: a propensity score matching analysis. J Cancer. 2019;10(17):3950–7.

    Article  Google Scholar 

  28. Sun Z, Li Z, Shi XL, He XW, Chen J, Song JH. Anatomic versus non-anatomic resection of hepatocellular carcinoma with microvascular invasion: A systematic review and meta-analysis. Asian J Surg. 2021;44(9):1143–50.

    Article  Google Scholar 

  29. Lee S, Kang TW, Song KD, et al. Effect of microvascular invasion risk on early recurrence of hepatocellular carcinoma after surgery and radiofrequency ablation. Ann Surg. 2021;273(3):564–71.

    Article  Google Scholar 

  30. Frank E. Harrell, Jr. Regression Modeling Strategies. In: Frank E. Harrell, Jr. Binary Logistic Regression. New York: Springer; 2015:224–231.

  31. Kobayashi A, Miyagawa S, Miwa S, Nakata T. Prognostic impact of anatomical resection on early and late intrahepatic recurrence in patients with hepatocellular carcinoma. J Hepatobiliary Pancreat Surg. 2008;15(5):515–21.

    Article  Google Scholar 

  32. Strasberg SM, Belghiti J, Clavien PA, et al. The Brisbane 2000 terminology of liver anatomy and resections. HPB. 2000;2(3):333–9.

    Article  Google Scholar 

  33. Pote N, Cauchy F, Albuquerque M, et al. Performance of PIVKA-II for early hepatocellular carcinoma diagnosis and prediction of microvascular invasion. J Hepatol. 2015;62(4):848–54.

    Article  CAS  Google Scholar 

Download references

Acknowledgments

This research was supported by the National Natural Science Foundation of China (NSFC, No. 81830053, 92059202, and 61821002), the Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX21_0153), and the Key Research and Development Program of Jiangsu Province (BE2020717).

Funding

This research was supported by the National Natural Science Foundation of China (NSFC, No. 81830053, 92059202, and 61821002), the Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX21_0153), and the Key Research and Development Program of Jiangsu Province (BE2020717).

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Authors and Affiliations

  1. Department of Radiology, Jiangsu Key Laboratory of Molecular and Functional Imaging, Zhongda Hospital, Medical School of Southeast University, Nanjing, China

    Xiang-Pan Meng M.D., Tian-Yu Tang Ph.D., Zhi-Min Ding M.D., Chun-Qiang Lu M.D., Qian Yu M.D., Cong Xia M.D., Yuan-Cheng Wang M.D. & Shenghong Ju M.D.

  2. Hepatic-Biliary-Pancreatic Center, Zhongda Hospital, Medical School of Southeast University, Nanjing, China

    Jitao Wang M.D.

  3. Department of Hepatopancreatobiliary Surgery, Xingtai Institute of Cancer Control, Xingtai People’s Hospital, Xingtai, China

    Jitao Wang M.D.

  4. Department of Radiology, The Third Hospital Affiliated of Nantong University, Nantong, China

    Tao Zhang M.D.

  5. Department of Radiology, The Xiangya Hospital of Central South University, Changsha, China

    Xueying Long M.D.

  6. Department of Radiology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China

    Wenbo Xiao M.D.

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  1. Xiang-Pan Meng M.D.
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Correspondence to Shenghong Ju M.D..

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Meng, XP., Tang, TY., Ding, ZM. et al. Preoperative Microvascular Invasion Prediction to Assist in Surgical Plan for Single Hepatocellular Carcinoma: Better Together with Radiomics. Ann Surg Oncol 29, 2960–2970 (2022). https://doi.org/10.1245/s10434-022-11346-1

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