Skip to main content
Top
Published in: Abdominal Radiology 8/2021

Open Access 01-08-2021 | Magnetic Resonance Imaging | Hepatobiliary

Predicting the prognosis of hepatocellular carcinoma with the treatment of transcatheter arterial chemoembolization combined with microwave ablation using pretreatment MR imaging texture features

Authors: Jun Liu, Yigang Pei, Yu Zhang, Yifan Wu, Fuquan Liu, Shanzhi Gu

Published in: Abdominal Radiology | Issue 8/2021

Login to get access

Abstract

Objective

To investigate the prognostic value of baseline magnetic resonance imaging (MRI) texture analysis of hepatocellular carcinoma (HCC) treated with transcatheter arterial chemoembolization (TACE) and microwave ablation (MWA).

Methods

MRI was performed on 102 patients with HCC before receiving TACE combined with MWA in this retrospective study. The best 10 texture features were screened as a feature group for each MRI sequence by MaZda software using mutual information coefficient (MI), nonlinear discriminant analysis (NDA) and other methods. The optimal feature group with the lowest misdiagnosis rate was achieved on one MRI sequence between two groups dichotomized by 3-year survival, which was used to optimize the significant texture features with the optimal cutoff values. The Cox proportional hazards model was generated for the significant texture features and clinical variables to determine the independent predictors of overall survival (OS). The predictive performance of the model was further evaluated by the area under the ROC curve (AUC). Kaplan–Meier and log-rank tests were performed for disease-free survival (DFS) and Local recurrence-free survival (LRFS).

Results

The optimal feature group with the lowest misdiagnosis rate of 8.82% was obtained on T2WI using MI combined with NDA feature analysis. For Cox proportional hazards regression models, the independent prognostic factors associated with OS were albumin (P = 0.047), BCLC stage (P = 0.001), Correlat(1,− 1)T2 (P = 0.01) and SumEntrp(3,0)T2 (P = 0.015), and the prediction efficiency of multivariate model is AUC = 0.876, 95%CI = 0.803–0.949. Kaplan–Meier analyses further demonstrated that BCLC (P < 0.001), Correlat(1,− 1)T2 (P = 0.023) and SumEntrp(3,0)T2 (P < 0.001) were associated with DFS, and BCLC (P = 0.007) related to LRFS.

Conclusions

MR imaging texture features may be used to predict the prognosis of HCC treated with TACE combined with MWA.
Literature
1.
go back to reference Ferenci P, Fried M, Labrecque D, et al. World Gastroenterology Organisation Guideline. Hepatocellular carcinoma (HCC): a global perspective. J Gastrointestin Liver Dis. 2010;19(3):311–7. Ferenci P, Fried M, Labrecque D, et al. World Gastroenterology Organisation Guideline. Hepatocellular carcinoma (HCC): a global perspective. J Gastrointestin Liver Dis. 2010;19(3):311–7.
2.
go back to reference Venook AP, Papandreou C, Furuse J, de Guevara LL. The incidence and epidemiology of hepatocellular carcinoma: a global and regional perspective. Oncologist. 2010;15 Suppl 4:5-13.CrossRef Venook AP, Papandreou C, Furuse J, de Guevara LL. The incidence and epidemiology of hepatocellular carcinoma: a global and regional perspective. Oncologist. 2010;15 Suppl 4:5-13.CrossRef
3.
go back to reference Padhya KT, Marrero JA, Singal AG. Recent advances in the treatment of hepatocellular carcinoma. Curr Opin Gastroenterol. 2013;29(3):285-92.CrossRef Padhya KT, Marrero JA, Singal AG. Recent advances in the treatment of hepatocellular carcinoma. Curr Opin Gastroenterol. 2013;29(3):285-92.CrossRef
4.
go back to reference McCurdy HM. Improving outcomes for patients receiving transarterial chemoembolization for hepatocellular carcinoma. Gastroenterol Nurs. 2013;36(2):114-20.CrossRef McCurdy HM. Improving outcomes for patients receiving transarterial chemoembolization for hepatocellular carcinoma. Gastroenterol Nurs. 2013;36(2):114-20.CrossRef
5.
go back to reference Kim KM, Kim JH, Park IS, et al. Reappraisal of repeated transarterial chemoembolization in the treatment of hepatocellular carcinoma with portal vein invasion. J Gastroenterol Hepatol. 2009;24(5):806-14.CrossRef Kim KM, Kim JH, Park IS, et al. Reappraisal of repeated transarterial chemoembolization in the treatment of hepatocellular carcinoma with portal vein invasion. J Gastroenterol Hepatol. 2009;24(5):806-14.CrossRef
6.
go back to reference Marelli L, Shusang V, Buscombe JR, et al. Transarterial injection of (131)I-lipiodol, compared with chemoembolization, in the treatment of unresectable hepatocellular cancer. J Nucl Med. 2009;50(6):871-7.CrossRef Marelli L, Shusang V, Buscombe JR, et al. Transarterial injection of (131)I-lipiodol, compared with chemoembolization, in the treatment of unresectable hepatocellular cancer. J Nucl Med. 2009;50(6):871-7.CrossRef
7.
go back to reference Zhu AX, Abou-Alfa GK. Expanding the treatment options for hepatocellular carcinoma: combining transarterial chemoembolization with radiofrequency ablation. JAMA. 2008;299(14):1716-8.CrossRef Zhu AX, Abou-Alfa GK. Expanding the treatment options for hepatocellular carcinoma: combining transarterial chemoembolization with radiofrequency ablation. JAMA. 2008;299(14):1716-8.CrossRef
8.
go back to reference Liu C, Liang P, Liu F, et al. MWA combined with TACE as a combined therapy for unresectable large-sized hepotocellular carcinoma. Int J Hyperthermia. 2011;27(7):654-62.CrossRef Liu C, Liang P, Liu F, et al. MWA combined with TACE as a combined therapy for unresectable large-sized hepotocellular carcinoma. Int J Hyperthermia. 2011;27(7):654-62.CrossRef
9.
go back to reference Xu LF, Sun HL, Chen YT, et al. Large primary hepatocellular carcinoma: transarterial chemoembolization monotherapy versus combined transarterial chemoembolization-percutaneous microwave coagulation therapy. J Gastroenterol Hepatol. 2013;28(3):456-63.CrossRef Xu LF, Sun HL, Chen YT, et al. Large primary hepatocellular carcinoma: transarterial chemoembolization monotherapy versus combined transarterial chemoembolization-percutaneous microwave coagulation therapy. J Gastroenterol Hepatol. 2013;28(3):456-63.CrossRef
10.
go back to reference Davnall F, Yip CS, Ljungqvist G, et al. Assessment of tumor heterogeneity: an emerging imaging tool for clinical practice? Insights Imaging. 2012;3(6):573-89.CrossRef Davnall F, Yip CS, Ljungqvist G, et al. Assessment of tumor heterogeneity: an emerging imaging tool for clinical practice? Insights Imaging. 2012;3(6):573-89.CrossRef
11.
go back to reference Ng F, Ganeshan B, Kozarski R, Miles KA, Goh V. Assessment of primary colorectal cancer heterogeneity by using whole-tumor texture analysis: contrast-enhanced CT texture as a biomarker of 5-year survival. Radiology. 2013;266(1):177-84.CrossRef Ng F, Ganeshan B, Kozarski R, Miles KA, Goh V. Assessment of primary colorectal cancer heterogeneity by using whole-tumor texture analysis: contrast-enhanced CT texture as a biomarker of 5-year survival. Radiology. 2013;266(1):177-84.CrossRef
12.
go back to reference Ganeshan B, Panayiotou E, Burnand K, Dizdarevic S, Miles K. Tumour heterogeneity in non-small cell lung carcinoma assessed by CT texture analysis: a potential marker of survival. Eur Radiol. 2012;22(4):796-802.CrossRef Ganeshan B, Panayiotou E, Burnand K, Dizdarevic S, Miles K. Tumour heterogeneity in non-small cell lung carcinoma assessed by CT texture analysis: a potential marker of survival. Eur Radiol. 2012;22(4):796-802.CrossRef
13.
go back to reference Lubner MG, Stabo N, Lubner SJ, et al. CT textural analysis of hepatic metastatic colorectal cancer: pre-treatment tumor heterogeneity correlates with pathology and clinical outcomes. Abdom Imaging. 2015;40(7):2331-7.CrossRef Lubner MG, Stabo N, Lubner SJ, et al. CT textural analysis of hepatic metastatic colorectal cancer: pre-treatment tumor heterogeneity correlates with pathology and clinical outcomes. Abdom Imaging. 2015;40(7):2331-7.CrossRef
14.
go back to reference Shenoy-Bhangle A, Baliyan V, Kordbacheh H, Guimaraes AR, Kambadakone A. Diffusion weighted magnetic resonance imaging of liver: Principles, clinical applications and recent updates. World J Hepatol. 2017;9(26):1081-91.CrossRef Shenoy-Bhangle A, Baliyan V, Kordbacheh H, Guimaraes AR, Kambadakone A. Diffusion weighted magnetic resonance imaging of liver: Principles, clinical applications and recent updates. World J Hepatol. 2017;9(26):1081-91.CrossRef
15.
go back to reference Gong NJ, Wong CS, Chu YC, Gu J. Treatment response monitoring in patients with gastrointestinal stromal tumor using diffusion-weighted imaging: preliminary results in comparison with positron emission tomography/computed tomography. Nmr Biomed. 2013;26(2):185-92.CrossRef Gong NJ, Wong CS, Chu YC, Gu J. Treatment response monitoring in patients with gastrointestinal stromal tumor using diffusion-weighted imaging: preliminary results in comparison with positron emission tomography/computed tomography. Nmr Biomed. 2013;26(2):185-92.CrossRef
16.
go back to reference Fu S, Chen S, Liang C, et al. Texture analysis of intermediate-advanced hepatocellular carcinoma: prognosis and patients' selection of transcatheter arterial chemoembolization and sorafenib. Oncotarget. 2017;8(23):37855-65.CrossRef Fu S, Chen S, Liang C, et al. Texture analysis of intermediate-advanced hepatocellular carcinoma: prognosis and patients' selection of transcatheter arterial chemoembolization and sorafenib. Oncotarget. 2017;8(23):37855-65.CrossRef
17.
go back to reference Szczypinski PM, Strzelecki M, Materka A, Klepaczko A. MaZda--a software package for image texture analysis. Comput Methods Programs Biomed. 2009;94(1):66-76.CrossRef Szczypinski PM, Strzelecki M, Materka A, Klepaczko A. MaZda--a software package for image texture analysis. Comput Methods Programs Biomed. 2009;94(1):66-76.CrossRef
18.
go back to reference Kinoshita M, Sakai M, Arita H, et al. Introduction of high throughput magnetic resonance T2-weighted image texture analysis for WHO grade 2 and 3 gliomas. PLOS ONE. 2016;11(10):e0164268.CrossRef Kinoshita M, Sakai M, Arita H, et al. Introduction of high throughput magnetic resonance T2-weighted image texture analysis for WHO grade 2 and 3 gliomas. PLOS ONE. 2016;11(10):e0164268.CrossRef
19.
go back to reference Ganeshan B, Miles KA. Quantifying tumour heterogeneity with CT. Cancer Imaging. 2013;13:140–9.CrossRef Ganeshan B, Miles KA. Quantifying tumour heterogeneity with CT. Cancer Imaging. 2013;13:140–9.CrossRef
20.
go back to reference Campos JT, Sirlin CB, Choi JY. Focal hepatic lesions in Gd-EOB-DTPA enhanced MRI: the atlas. Insights Imaging. 2012;3(5):451-74.CrossRef Campos JT, Sirlin CB, Choi JY. Focal hepatic lesions in Gd-EOB-DTPA enhanced MRI: the atlas. Insights Imaging. 2012;3(5):451-74.CrossRef
21.
go back to reference Park HJ, Kim JH, Choi SY, et al. Prediction of Therapeutic Response of Hepatocellular Carcinoma to Transcatheter Arterial Chemoembolization Based on Pretherapeutic Dynamic CT and Textural Findings. AJR Am J Roentgenol. 2017;209(4):W211-20.CrossRef Park HJ, Kim JH, Choi SY, et al. Prediction of Therapeutic Response of Hepatocellular Carcinoma to Transcatheter Arterial Chemoembolization Based on Pretherapeutic Dynamic CT and Textural Findings. AJR Am J Roentgenol. 2017;209(4):W211-20.CrossRef
22.
go back to reference Li M, Fu S, Zhu Y, et al. Computed tomography texture analysis to facilitate therapeutic decision making in hepatocellular carcinoma. Oncotarget. 2016;7(11):13248-59.CrossRef Li M, Fu S, Zhu Y, et al. Computed tomography texture analysis to facilitate therapeutic decision making in hepatocellular carcinoma. Oncotarget. 2016;7(11):13248-59.CrossRef
23.
go back to reference Kolarevic D, Tomasevic Z, Dzodic R, Kanjer K, Vukosavljevic DN, Radulovic M. Early prognosis of metastasis risk in inflammatory breast cancer by texture analysis of tumour microscopic images. Biomed Microdevices. 2015;17(5):92.CrossRef Kolarevic D, Tomasevic Z, Dzodic R, Kanjer K, Vukosavljevic DN, Radulovic M. Early prognosis of metastasis risk in inflammatory breast cancer by texture analysis of tumour microscopic images. Biomed Microdevices. 2015;17(5):92.CrossRef
24.
go back to reference Kim JH, Ko ES, Lim Y, et al. Breast Cancer Heterogeneity: MR Imaging Texture Analysis and Survival Outcomes. Radiology. 2017;282(3):665-75.CrossRef Kim JH, Ko ES, Lim Y, et al. Breast Cancer Heterogeneity: MR Imaging Texture Analysis and Survival Outcomes. Radiology. 2017;282(3):665-75.CrossRef
25.
go back to reference Win T, Miles KA, Janes SM, et al. Tumor heterogeneity and permeability as measured on the CT component of PET/CT predict survival in patients with non-small cell lung cancer. Clin Cancer Res. 2013;19(13):3591-9.CrossRef Win T, Miles KA, Janes SM, et al. Tumor heterogeneity and permeability as measured on the CT component of PET/CT predict survival in patients with non-small cell lung cancer. Clin Cancer Res. 2013;19(13):3591-9.CrossRef
26.
go back to reference Meyer HJ, Schob S, Hohn AK, Surov A. MRI Texture Analysis Reflects Histopathology Parameters in Thyroid Cancer - A First Preliminary Study. Transl Oncol. 2017;10(6):911-6.CrossRef Meyer HJ, Schob S, Hohn AK, Surov A. MRI Texture Analysis Reflects Histopathology Parameters in Thyroid Cancer - A First Preliminary Study. Transl Oncol. 2017;10(6):911-6.CrossRef
27.
go back to reference Liu J, Mao Y, Li Z, et al. Use of texture analysis based on contrast-enhanced MRI to predict treatment response to chemoradiotherapy in nasopharyngeal carcinoma. J Magn Reson Imaging. 2016;44(2):445-55.CrossRef Liu J, Mao Y, Li Z, et al. Use of texture analysis based on contrast-enhanced MRI to predict treatment response to chemoradiotherapy in nasopharyngeal carcinoma. J Magn Reson Imaging. 2016;44(2):445-55.CrossRef
28.
go back to reference Thibault G, Tudorica A, Afzal A, et al. DCE-MRI Texture Features for Early Prediction of Breast Cancer Therapy Response. Tomography. 2017;3(1):23-32.CrossRef Thibault G, Tudorica A, Afzal A, et al. DCE-MRI Texture Features for Early Prediction of Breast Cancer Therapy Response. Tomography. 2017;3(1):23-32.CrossRef
29.
go back to reference Miles KA, Ganeshan B, Hayball MP. CT texture analysis using the filtration-histogram method: what do the measurements mean? Cancer Imaging. 2013;13(3):400-6.CrossRef Miles KA, Ganeshan B, Hayball MP. CT texture analysis using the filtration-histogram method: what do the measurements mean? Cancer Imaging. 2013;13(3):400-6.CrossRef
30.
go back to reference Pusiol T, Zorzi MG, Morichetti D, Piscioli I, Scialpi M. Uselessness of radiological differentiation of oncocytoma and renal cell carcinoma in management of small renal masses. World J Urol. 2013;31(4):1013-4.CrossRef Pusiol T, Zorzi MG, Morichetti D, Piscioli I, Scialpi M. Uselessness of radiological differentiation of oncocytoma and renal cell carcinoma in management of small renal masses. World J Urol. 2013;31(4):1013-4.CrossRef
31.
go back to reference Brynolfsson P, Nilsson D, Henriksson R, et al. ADC texture--an imaging biomarker for high-grade glioma? Med Phys. 2014;41(10):101903.CrossRef Brynolfsson P, Nilsson D, Henriksson R, et al. ADC texture--an imaging biomarker for high-grade glioma? Med Phys. 2014;41(10):101903.CrossRef
32.
go back to reference Lubner MG, Smith AD, Sandrasegaran K, Sahani DV, Pickhardt PJ. CT Texture Analysis: Definitions, Applications, Biologic Correlates, and Challenges. Radiographics. 2017;37(5):1483-503.CrossRef Lubner MG, Smith AD, Sandrasegaran K, Sahani DV, Pickhardt PJ. CT Texture Analysis: Definitions, Applications, Biologic Correlates, and Challenges. Radiographics. 2017;37(5):1483-503.CrossRef
33.
go back to reference Bruix J, Sherman M. Management of hepatocellular carcinoma: an update. Hepatology. 2011;53(3):1020-2.CrossRef Bruix J, Sherman M. Management of hepatocellular carcinoma: an update. Hepatology. 2011;53(3):1020-2.CrossRef
34.
go back to reference Kinoshita A, Onoda H, Imai N, et al. The C-reactive protein/albumin ratio, a novel inflammation-based prognostic score, predicts outcomes in patients with hepatocellular carcinoma. Ann Surg Oncol. 2015;22(3):803-10.CrossRef Kinoshita A, Onoda H, Imai N, et al. The C-reactive protein/albumin ratio, a novel inflammation-based prognostic score, predicts outcomes in patients with hepatocellular carcinoma. Ann Surg Oncol. 2015;22(3):803-10.CrossRef
35.
go back to reference Waugh SA, Purdie CA, Jordan LB, et al. Magnetic resonance imaging texture analysis classification of primary breast cancer. Eur Radiol. 2016;26(2):322-30.CrossRef Waugh SA, Purdie CA, Jordan LB, et al. Magnetic resonance imaging texture analysis classification of primary breast cancer. Eur Radiol. 2016;26(2):322-30.CrossRef
36.
go back to reference Savio SJ, Harrison LC, Luukkaala T, et al. Effect of slice thickness on brain magnetic resonance image texture analysis. Biomed Eng Online. 2010;9:60.CrossRef Savio SJ, Harrison LC, Luukkaala T, et al. Effect of slice thickness on brain magnetic resonance image texture analysis. Biomed Eng Online. 2010;9:60.CrossRef
Metadata
Title
Predicting the prognosis of hepatocellular carcinoma with the treatment of transcatheter arterial chemoembolization combined with microwave ablation using pretreatment MR imaging texture features
Authors
Jun Liu
Yigang Pei
Yu Zhang
Yifan Wu
Fuquan Liu
Shanzhi Gu
Publication date
01-08-2021
Publisher
Springer US
Published in
Abdominal Radiology / Issue 8/2021
Print ISSN: 2366-004X
Electronic ISSN: 2366-0058
DOI
https://doi.org/10.1007/s00261-020-02891-y

Other articles of this Issue 8/2021

Abdominal Radiology 8/2021 Go to the issue
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

Highlights from the ACC 2024 Congress

Year in Review: Pediatric cardiology

Watch Dr. Anne Marie Valente present the last year's highlights in pediatric and congenital heart disease in the official ACC.24 Year in Review session.

Year in Review: Pulmonary vascular disease

The last year's highlights in pulmonary vascular disease are presented by Dr. Jane Leopold in this official video from ACC.24.

Year in Review: Valvular heart disease

Watch Prof. William Zoghbi present the last year's highlights in valvular heart disease from the official ACC.24 Year in Review session.

Year in Review: Heart failure and cardiomyopathies

Watch this official video from ACC.24. Dr. Biykem Bozkurt discusses last year's major advances in heart failure and cardiomyopathies.