Skip to main content
Top

04-05-2024 | Hepatocellular Carcinoma | Hepatobiliary

Interpretable machine learning based on CT-derived extracellular volume fraction to predict pathological grading of hepatocellular carcinoma

Authors: Jie Li, Linxuan Zou, Heng Ma, Jifu Zhao, Chengyan Wang, Jun Li, Guangchao Hu, Haoran Yang, Beizhong Wang, Donghao Xu, Yuanhao Xia, Yi Jiang, Xingyue Jiang, Naixuan Li

Published in: Abdominal Radiology

Login to get access

Abstract

Purpose

To develop a non-invasive auxiliary assessment method based on CT-derived extracellular volume (ECV) to predict the pathological grading (PG) of hepatocellular carcinoma (HCC).

Methods

The study retrospectively analyzed 238 patients who underwent HCC resection surgery between January 2013 and April 2023. Six machine learning algorithms were employed to construct predictive models for HCC PG: logistic regression, extreme gradient boosting, Light Gradient Boosting Machine (LightGBM), random forest, adaptive boosting, and Gaussian naive Bayes. Model performance was evaluated using receiver operating characteristic curve analysis, including area under the curve (AUC), sensitivity, specificity, accuracy, positive predictive value, negative predictive value, and F1 score. Calibration plots were used for visual evaluation of model calibration. Clinical decision curve analysis was performed to assess potential clinical utility by calculating net benefit.

Results

166 patients from Hospital A were allocated to the training set, while 72 patients from Hospital B (constituting 30.25% of the total sample) were assigned to the test set. The model achieved an AUC of 1.000 (95%CI: 1.000–1.000) in the training set and 0.927 (95%CI: 0.837–0.999) in the validation set, respectively. Ultimately, the model achieved an AUC of 0.909 (95%CI: 0.837–0.980) in the test set, with an accuracy of 0.778, sensitivity of 0.906, specificity of 0.789, negative predictive value of 0.556, and F1 score of 0.908.

Conclusion

This study successfully developed and validated a non-invasive auxiliary assessment method based on CT-derived ECV to predict the HCC PG, providing important supplementary information for clinical decision-making.
Literature
3.
go back to reference Zeng J, Zeng J, Lin K, Lin H, Wu Q, Guo P, Zhou W, Liu J. (2022). Development of a machine learning model to predict early recurrence for hepatocellular carcinoma after curative resection. HEPATOBIL SURG NUTR, 11(2), 176–187. https://doi.org/10.21037/hbsn-20-466 Zeng J, Zeng J, Lin K, Lin H, Wu Q, Guo P, Zhou W, Liu J. (2022). Development of a machine learning model to predict early recurrence for hepatocellular carcinoma after curative resection. HEPATOBIL SURG NUTR, 11(2), 176–187. https://​doi.​org/​10.​21037/​hbsn-20-466
4.
9.
go back to reference Mao Y, Wang J, Zhu Y, Chen J, Mao L, Kong W, Qiu Y, Wu X, Guan Y, He J. (2022). Gd-EOB-DTPA-enhanced MRI radiomic features for predicting histological grade of hepatocellular carcinoma. HEPATOBIL SURG NUTR, 11(1), 13–24. https://doi.org/10.21037/hbsn-19-870 Mao Y, Wang J, Zhu Y, Chen J, Mao L, Kong W, Qiu Y, Wu X, Guan Y, He J. (2022). Gd-EOB-DTPA-enhanced MRI radiomic features for predicting histological grade of hepatocellular carcinoma. HEPATOBIL SURG NUTR, 11(1), 13–24. https://​doi.​org/​10.​21037/​hbsn-19-870
15.
go back to reference Ameli S, Venkatesh BA, Shaghaghi M, Ghadimi M, Hazhirkarzar B, Rezvani HR, Aliyari GM, Khoshpouri P, Pandey A, Pandey P, Pan L, Grimm R, Kamel IR. (2022). Role of MRI-Derived Radiomics Features in Determining Degree of Tumor Differentiation of Hepatocellular Carcinoma. DIAGNOSTICS, 12(10). https://doi.org/10.3390/diagnostics12102386 Ameli S, Venkatesh BA, Shaghaghi M, Ghadimi M, Hazhirkarzar B, Rezvani HR, Aliyari GM, Khoshpouri P, Pandey A, Pandey P, Pan L, Grimm R, Kamel IR. (2022). Role of MRI-Derived Radiomics Features in Determining Degree of Tumor Differentiation of Hepatocellular Carcinoma. DIAGNOSTICS, 12(10). https://​doi.​org/​10.​3390/​diagnostics12102​386
19.
go back to reference Kim HY, Choi JY, Kim CW, Bae SH, Yoon SK, Lee YJ, Rha SE, You YK, Kim DG, Jung ES. (2012). Gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid-enhanced magnetic resonance imaging predicts the histological grade of hepatocellular carcinoma only in patients with Child-Pugh class A cirrhosis. LIVER TRANSPLANT, 18(7), 850-857. https://doi.org/10.1002/lt.23426CrossRef Kim HY, Choi JY, Kim CW, Bae SH, Yoon SK, Lee YJ, Rha SE, You YK, Kim DG, Jung ES. (2012). Gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid-enhanced magnetic resonance imaging predicts the histological grade of hepatocellular carcinoma only in patients with Child-Pugh class A cirrhosis. LIVER TRANSPLANT, 18(7), 850-857. https://​doi.​org/​10.​1002/​lt.​23426CrossRef
21.
go back to reference Adams LC, Jurmeister P, Ralla B, Bressem KK, Fahlenkamp UL, Engel G, Siepmann S, Wagner M, Hamm B, Busch J, Makowski MR. (2019). Assessment of the extracellular volume fraction for the grading of clear cell renal cell carcinoma: first results and histopathological findings. EUR RADIOL, 29(11), 5832-5843. https://doi.org/10.1007/s00330-019-06087-xCrossRefPubMed Adams LC, Jurmeister P, Ralla B, Bressem KK, Fahlenkamp UL, Engel G, Siepmann S, Wagner M, Hamm B, Busch J, Makowski MR. (2019). Assessment of the extracellular volume fraction for the grading of clear cell renal cell carcinoma: first results and histopathological findings. EUR RADIOL, 29(11), 5832-5843. https://​doi.​org/​10.​1007/​s00330-019-06087-xCrossRefPubMed
22.
go back to reference Fukukura Y, Kumagae Y, Higashi R, Hakamada H, Takumi K, Maemura K, Higashi M, Kamimura K, Nakajo M, Yoshiura T. (2019). Extracellular volume fraction determined by equilibrium contrast-enhanced multidetector computed tomography as a prognostic factor in unresectable pancreatic adenocarcinoma treated with chemotherapy. EUR RADIOL, 29(1), 353-361. https://doi.org/10.1007/s00330-018-5570-4CrossRefPubMed Fukukura Y, Kumagae Y, Higashi R, Hakamada H, Takumi K, Maemura K, Higashi M, Kamimura K, Nakajo M, Yoshiura T. (2019). Extracellular volume fraction determined by equilibrium contrast-enhanced multidetector computed tomography as a prognostic factor in unresectable pancreatic adenocarcinoma treated with chemotherapy. EUR RADIOL, 29(1), 353-361. https://​doi.​org/​10.​1007/​s00330-018-5570-4CrossRefPubMed
23.
go back to reference Engblom H, Kanski M, Kopic S, Nordlund D, Xanthis CG, Jablonowski R, Heiberg E, Aletras AH, Carlsson M, Arheden H. (2018). Importance of standardizing timing of hematocrit measurement when using cardiovascular magnetic resonance to calculate myocardial extracellular volume (ECV) based on pre- and post-contrast T1 mapping. J CARDIOVASC MAGN R, 20(1), 46. https://doi.org/10.1186/s12968-018-0464-9CrossRef Engblom H, Kanski M, Kopic S, Nordlund D, Xanthis CG, Jablonowski R, Heiberg E, Aletras AH, Carlsson M, Arheden H. (2018). Importance of standardizing timing of hematocrit measurement when using cardiovascular magnetic resonance to calculate myocardial extracellular volume (ECV) based on pre- and post-contrast T1 mapping. J CARDIOVASC MAGN R, 20(1), 46. https://​doi.​org/​10.​1186/​s12968-018-0464-9CrossRef
29.
go back to reference Fulgenzi C, Cheon J, D'Alessio A, Nishida N, Ang C, Marron TU, Wu L, Saeed A, Wietharn B, Cammarota A, Pressiani T, Personeni N, Pinter M, Scheiner B, Balcar L, Napolitano A, Huang YH, Phen S, Naqash AR, Vivaldi C, Salani F, Masi G, Bettinger D, Vogel A, Schonlein M, von Felden J, Schulze K, Wege H, Galle PR, Kudo M, Rimassa L, Singal AG, Sharma R, Cortellini A, Gaillard VE, Chon HJ, Pinato DJ. (2022). Reproducible safety and efficacy of atezolizumab plus bevacizumab for HCC in clinical practice: Results of the AB-real study. EUR J CANCER, 175, 204-213. https://doi.org/10.1016/j.ejca.2022.08.024CrossRefPubMed Fulgenzi C, Cheon J, D'Alessio A, Nishida N, Ang C, Marron TU, Wu L, Saeed A, Wietharn B, Cammarota A, Pressiani T, Personeni N, Pinter M, Scheiner B, Balcar L, Napolitano A, Huang YH, Phen S, Naqash AR, Vivaldi C, Salani F, Masi G, Bettinger D, Vogel A, Schonlein M, von Felden J, Schulze K, Wege H, Galle PR, Kudo M, Rimassa L, Singal AG, Sharma R, Cortellini A, Gaillard VE, Chon HJ, Pinato DJ. (2022). Reproducible safety and efficacy of atezolizumab plus bevacizumab for HCC in clinical practice: Results of the AB-real study. EUR J CANCER, 175, 204-213. https://​doi.​org/​10.​1016/​j.​ejca.​2022.​08.​024CrossRefPubMed
30.
go back to reference Zhou J, Sun H, Wang Z, Cong W, Wang J, Zeng M, Zhou W, Bie P, Liu L, Wen T, Han G, Wang M, Liu R, Lu L, Ren Z, Chen M, Zeng Z, Liang P, Liang C, Chen M, Yan F, Wang W, Ji Y, Yun J, Cai D, Chen Y, Cheng W, Cheng S, Dai C, Guo W, Hua B, Huang X, Jia W, Li Y, Li Y, Liang J, Liu T, Lv G, Mao Y, Peng T, Ren W, Shi H, Shi G, Tao K, Wang W, Wang X, Wang Z, Xiang B, Xing B, Xu J, Yang J, Yang J, Yang Y, Yang Y, Ye S, Yin Z, Zhang B, Zhang B, Zhang L, Zhang S, Zhang T, Zhao Y, Zheng H, Zhu J, Zhu K, Liu R, Shi Y, Xiao Y, Dai Z, Teng G, Cai J, Wang W, Cai X, Li Q, Shen F, Qin S, Dong J, Fan J. (2020). Guidelines for the Diagnosis and Treatment of Hepatocellular Carcinoma (2019 Edition). LIVER CANCER, 9(6), 682–720. https://doi.org/10.1159/000509424 Zhou J, Sun H, Wang Z, Cong W, Wang J, Zeng M, Zhou W, Bie P, Liu L, Wen T, Han G, Wang M, Liu R, Lu L, Ren Z, Chen M, Zeng Z, Liang P, Liang C, Chen M, Yan F, Wang W, Ji Y, Yun J, Cai D, Chen Y, Cheng W, Cheng S, Dai C, Guo W, Hua B, Huang X, Jia W, Li Y, Li Y, Liang J, Liu T, Lv G, Mao Y, Peng T, Ren W, Shi H, Shi G, Tao K, Wang W, Wang X, Wang Z, Xiang B, Xing B, Xu J, Yang J, Yang J, Yang Y, Yang Y, Ye S, Yin Z, Zhang B, Zhang B, Zhang L, Zhang S, Zhang T, Zhao Y, Zheng H, Zhu J, Zhu K, Liu R, Shi Y, Xiao Y, Dai Z, Teng G, Cai J, Wang W, Cai X, Li Q, Shen F, Qin S, Dong J, Fan J. (2020). Guidelines for the Diagnosis and Treatment of Hepatocellular Carcinoma (2019 Edition). LIVER CANCER, 9(6), 682–720. https://​doi.​org/​10.​1159/​000509424
31.
33.
go back to reference Fu J, Cai W, Zeng B, He L, Bao L, Lin Z, Lin F, Hu W, Lin L, Huang H, Zheng S, Chen L, Zhou W, Lin Y, Fu F. (2022). Development and validation of a predictive model for peripherally inserted central catheter-related thrombosis in breast cancer patients based on artificial neural network: A prospective cohort study. INT J NURS STUD, 135, 104341. https://doi.org/10.1016/j.ijnurstu.2022.104341CrossRefPubMed Fu J, Cai W, Zeng B, He L, Bao L, Lin Z, Lin F, Hu W, Lin L, Huang H, Zheng S, Chen L, Zhou W, Lin Y, Fu F. (2022). Development and validation of a predictive model for peripherally inserted central catheter-related thrombosis in breast cancer patients based on artificial neural network: A prospective cohort study. INT J NURS STUD, 135, 104341. https://​doi.​org/​10.​1016/​j.​ijnurstu.​2022.​104341CrossRefPubMed
36.
go back to reference Li X, Zhao Y, Zhang D, Kuang L, Huang H, Chen W, Fu X, Wu Y, Li T, Zhang J, Yuan L, Hu H, Liu Y, Zhang M, Hu F, Sun X, Hu D. (2023). Development of an interpretable machine learning model associated with heavy metals' exposure to identify coronary heart disease among US adults via SHAP: Findings of the US NHANES from 2003 to 2018. CHEMOSPHERE, 311(Pt 1), 137039. https://doi.org/10.1016/j.chemosphere.2022.137039CrossRefPubMed Li X, Zhao Y, Zhang D, Kuang L, Huang H, Chen W, Fu X, Wu Y, Li T, Zhang J, Yuan L, Hu H, Liu Y, Zhang M, Hu F, Sun X, Hu D. (2023). Development of an interpretable machine learning model associated with heavy metals' exposure to identify coronary heart disease among US adults via SHAP: Findings of the US NHANES from 2003 to 2018. CHEMOSPHERE, 311(Pt 1), 137039. https://​doi.​org/​10.​1016/​j.​chemosphere.​2022.​137039CrossRefPubMed
40.
go back to reference Fukukura Y, Kumagae Y, Higashi R, Hakamada H, Nakajo M, Maemura K, Arima S, Yoshiura T. (2020). Extracellular volume fraction determined by equilibrium contrast-enhanced dual-energy CT as a prognostic factor in patients with stage IV pancreatic ductal adenocarcinoma. EUR RADIO, 30(3), 1679–1689. https://doi.org/10.1007/s00330-019-06517-w. Fukukura Y, Kumagae Y, Higashi R, Hakamada H, Nakajo M, Maemura K, Arima S, Yoshiura T. (2020). Extracellular volume fraction determined by equilibrium contrast-enhanced dual-energy CT as a prognostic factor in patients with stage IV pancreatic ductal adenocarcinoma. EUR RADIO, 30(3), 1679–1689. https://​doi.​org/​10.​1007/​s00330-019-06517-w.
41.
go back to reference Iwaya H, Fukukura Y, Hashimoto S, Tanoue S, Kawahira M, Hinokuchi M, Fujita T, Komaki Y, Arima S, Sasaki F, Kanmura S, Higashi M, Tamada K, Ido A. (2021). Prognostic significance of extracellular volume fraction with equilibrium contrast-enhanced computed tomography for pancreatic neuroendocrine neoplasms. PANCREATOLOGY, 21(4), 779-786. https://doi.org/10.1016/j.pan.2021.02.020.CrossRefPubMed Iwaya H, Fukukura Y, Hashimoto S, Tanoue S, Kawahira M, Hinokuchi M, Fujita T, Komaki Y, Arima S, Sasaki F, Kanmura S, Higashi M, Tamada K, Ido A. (2021). Prognostic significance of extracellular volume fraction with equilibrium contrast-enhanced computed tomography for pancreatic neuroendocrine neoplasms. PANCREATOLOGY, 21(4), 779-786. https://​doi.​org/​10.​1016/​j.​pan.​2021.​02.​020.CrossRefPubMed
Metadata
Title
Interpretable machine learning based on CT-derived extracellular volume fraction to predict pathological grading of hepatocellular carcinoma
Authors
Jie Li
Linxuan Zou
Heng Ma
Jifu Zhao
Chengyan Wang
Jun Li
Guangchao Hu
Haoran Yang
Beizhong Wang
Donghao Xu
Yuanhao Xia
Yi Jiang
Xingyue Jiang
Naixuan Li
Publication date
04-05-2024
Publisher
Springer US
Published in
Abdominal Radiology
Print ISSN: 2366-004X
Electronic ISSN: 2366-0058
DOI
https://doi.org/10.1007/s00261-024-04313-9
Live Webinar | 27-06-2024 | 18:00 (CEST)

Keynote webinar | Spotlight on medication adherence

Live: Thursday 27th June 2024, 18:00-19:30 (CEST)

WHO estimates that half of all patients worldwide are non-adherent to their prescribed medication. The consequences of poor adherence can be catastrophic, on both the individual and population level.

Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.

Prof. Kevin Dolgin
Prof. Florian Limbourg
Prof. Anoop Chauhan
Developed by: Springer Medicine
Obesity Clinical Trial Summary

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.

Developed by: Springer Medicine
Webinar | 06-02-2024 | 20:00 (CET)

Mastering chronic pancreatitis pain: A multidisciplinary approach and practical solutions

Severe pain is the most common symptom of chronic pancreatitis. In this webinar, experts share the latest insights in pain management for chronic pancreatitis patients. Experts from a range of disciplines discuss pertinent cases and provide practical suggestions for use within clinical practice.

Sponsored by: Viatris

Developed by: Springer Healthcare