Abstract
Objectives
To determine whether image texture parameters analysed on pre-operative contrast-enhanced computed tomography (CT) can predict overall survival and recurrence-free survival in patients with hepatocellular carcinoma (HCC) treated by surgical resection.
Methods
We retrospectively included all patients operated for HCC who had liver contrast-enhanced CT within 3 months prior to treatment in our centre between 2010 and 2015. The following texture parameters were evaluated on late-arterial and portal-venous phases: mean grey-level, standard deviation, kurtosis, skewness and entropy. Measurements were made before and after spatial filtration at different anatomical scales (SSF) ranging from 2 (fine texture) to 6 (coarse texture). Lasso penalised Cox regression analyses were performed to identify independent predictors of overall survival and recurrence-free survival.
Results
Forty-seven patients were included. Median follow-up time was 345 days (interquartile range [IQR], 176–569). Nineteen patients had a recurrence at a median time of 190 days (IQR, 141–274) and 13 died at a median time of 274 days (IQR, 96–411). At arterial CT phase, kurtosis at SSF = 4 (hazard ratio [95% confidence interval] = 3.23 [1.35–7.71] p = 0.0084) was independent predictor of overall survival. At portal-venous phase, skewness without filtration (HR [CI 95%] = 353.44 [1.31–95102.23], p = 0.039), at SSF2 scale (HR [CI 95%] = 438.73 [2.44–78968.25], p = 0.022) and SSF3 (HR [CI 95%] = 14.43 [1.38–150.51], p = 0.026) were independently associated with overall survival. No textural feature was identified as predictor of recurrence-free survival.
Conclusions
In patients with resectable HCC, portal venous phase–derived CT skewness is significantly associated with overall survival and may potentially become a useful tool to select the best candidates for resection.
Key Points
• HCC heterogeneity as evaluated by texture analysis of contrast-enhanced CT images may predict overall survival in patients treated by surgical resection.
• Among texture parameters, skewness assessed at different anatomical scales at portal-venous phase CT is an independent predictor of overall survival after resection.
• In patients with HCC, CT texture analysis may have the potential to become a useful tool to select the best candidates for resection.
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Abbreviations
- AFP:
-
Alpha-fetoprotein
- HCC:
-
Hepatocellular carcinoma
- MVI:
-
Microvascular invasion
- NASH:
-
Non-alcoholic steatohepatitis
- OS:
-
Overall survival
- PE:
-
Portal embolisation
- RFS:
-
Recurrence-free survival
- SSF:
-
Spatial scale image filtration
- TACE:
-
Transcatheter arterial chemoembolisation
References
Ferlay J, Soerjomataram I, Dikshit R et al (2015) Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer 136:E359–E386
Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A (2015) Global cancer statistics, 2012. CA Cancer J Clin 65:87–108
Lim KC, Chow PK, Allen JC, Siddiqui FJ, Chan ES, Tan SB (2012) Systematic review of outcomes of liver resection for early hepatocellular carcinoma within the Milan criteria. Br J Surg 99:1622–1629
Kluger MD, Salceda JA, Laurent A et al (2015) Liver resection for hepatocellular carcinoma in 313 Western patients: tumor biology and underlying liver rather than tumor size drive prognosis. J Hepatol 62:1131–1140
Imamura H, Matsuyama Y, Tanaka E et al (2003) Risk factors contributing to early and late phase intrahepatic recurrence of hepatocellular carcinoma after hepatectomy. J Hepatol 38:200–207
Marusyk A, Almendro V, Polyak K (2012) Intra-tumour heterogeneity: a looking glass for cancer? Nat Rev Cancer 12:323–334
Davnall F, Yip CS, Ljungqvist G et al (2012) Assessment of tumor heterogeneity: an emerging imaging tool for clinical practice? Insights Imaging 3:573–589
Ganeshan B, Miles KA (2013) Quantifying tumour heterogeneity with CT. Cancer Imaging 13:140–149
Ganeshan B, Skogen K, Pressney I, Coutroubis D, Miles K (2012) Tumour heterogeneity in oesophageal cancer assessed by CT texture analysis: preliminary evidence of an association with tumour metabolism, stage, and survival. Clin Radiol 67:157–164
Ng F, Ganeshan B, Kozarski R, Miles KA, Goh V (2013) Assessment of primary colorectal cancer heterogeneity by using whole-tumor texture analysis: contrast-enhanced CT texture as a biomarker of 5-year survival. Radiology 266:177–184
Zhang H, Graham CM, Elci O et al (2013) Locally advanced squamous cell carcinoma of the head and neck: CT texture and histogram analysis allow independent prediction of overall survival in patients treated with induction chemotherapy. Radiology 269:801–809
Ganeshan B, Panayiotou E, Burnand K, Dizdarevic S, Miles K (2012) Tumour heterogeneity in non-small cell lung carcinoma assessed by CT texture analysis: a potential marker of survival. Eur Radiol 22:796–802
Ravanelli M, Farina D, Morassi M et al (2013) Texture analysis of advanced non-small cell lung cancer (NSCLC) on contrast-enhanced computed tomography: prediction of the response to the first-line chemotherapy. Eur Radiol 23:3450–3455
Tian F, Hayano K, Kambadakone AR, Sahani DV (2015) Response assessment to neoadjuvant therapy in soft tissue sarcomas: using CT texture analysis in comparison to tumor size, density, and perfusion. Abdom Imaging 40:1705–1712
Barry B, Buch K, Soto JA, Jara H, Nakhmani A, Anderson SW (2014) Quantifying liver fibrosis through the application of texture analysis to diffusion weighted imaging. Magn Reson Imaging 32:84–90
Lubner MG, Malecki K, Kloke J, Ganeshan B, Pickhardt PJ (2017) Texture analysis of the liver at MDCT for assessing hepatic fibrosis. Abdom Radiol (NY) 42:2069–2078
Simpson AL, Adams LB, Allen PJ et al (2015) Texture analysis of preoperative CT images for prediction of postoperative hepatic insufficiency: a preliminary study. J Am Coll Surg 220:339–346
Kiryu S, Akai H, Nojima M et al (2017) Impact of hepatocellular carcinoma heterogeneity on computed tomography as a prognostic indicator. Sci Rep 7:12689
Li M, Fu S, Zhu Y et al (2016) Computed tomography texture analysis to facilitate therapeutic decision making in hepatocellular carcinoma. Oncotarget 7:13248–13259
Fu S, Chen S, Liang C et al (2017) Texture analysis of intermediate-advanced hepatocellular carcinoma: prognosis and patients’ selection of transcatheter arterial chemoembolization and sorafenib. Oncotarget 8:37855–33765
Miles KA, Ganeshan B, Hayball MP (2013) CT texture analysis using the filtration-histogram method: what do the measurements mean? Cancer Imaging 13:400–406
Simon N, Friedman J, Hastie T, Tibshirani R (2011) Regularization paths for Cox's proportional hazards model via coordinate descent. J Stat Softw 39:1–13
Ganeshan B, Goh V, Mandeville HC, Ng QS, Hoskin PJ, Miles KA (2013) Non-small cell lung cancer: histopathologic correlates for texture parameters at CT. Radiology 266:326–336
Hayano K, Tian F, Kambadakone AR et al (2015) Texture analysis of non-contrast-enhanced computed tomography for assessing angiogenesis and survival of soft tissue sarcoma. J Comput Assist Tomogr 39:607–612
Ahn SY, Park CM, Park SJ et al (2015) Prognostic value of computed tomography texture features in non-small cell lung cancers treated with definitive concomitant chemoradiotherapy. Invest Radiol 50:719–725
Choi TW, Kim JH, Yu MH, Park SJ, Han JK (2018) Pancreatic neuroendocrine tumor: prediction of the tumor grade using CT findings and computerized texture analysis. Acta Radiol 59:383–392
Ganeshan B, Miles KA, Babikir S et al (2017) CT-based texture analysis potentially provides prognostic information complementary to interim FDG-PET for patients with Hodgkin’s and aggressive non-Hodgkin’s lymphomas. Eur Radiol 27:1012–1020
Craigie M, Squires J, Miles K (2017) Can CT measures of tumour heterogeneity stratify risk for nodal metastasis in patients with non-small cell lung cancer? Clin Radiol 72:899.e1–899.e7
Park Y, Kim YS, Rhim H, Lim HK, Choi D, Lee WJ (2009) Arterial enhancement of hepatocellular carcinoma before radiofrequency ablation as a predictor of postablation local tumor progression. AJR Am J Roentgenol 193:757–763
Ishii T, Numata K, Hao Y et al (2017) Evaluation of hepatocellular carcinoma tumor vascularity using contrast-enhanced ultrasonography as a predictor for local recurrence following radiofrequency ablation. Eur J Radiol 89:234–241
Ng F, Kozarski R, Ganeshan B, Goh V (2013) Assessment of tumor heterogeneity by CT texture analysis: can the largest cross-sectional area be used as an alternative to whole tumor analysis? Eur J Radiol 82:342–348
Choi JY, Lee JM, Sirlin CB (2014) CT and MR imaging diagnosis and staging of hepatocellular carcinoma: part I. Development, growth, and spread: key pathologic and imaging aspects. Radiology 272(3):635–654
Miles KA, Ganeshan B, Griffiths MR, Young RC, Chatwin CR (2009) Colorectal cancer: texture analysis of portal phase hepatic CT images as a potential marker of survival. Radiology 250:444–452
Duda D, Kretowski M, Bezy-Wendling J (2013) Effect of slice thickness on texture-based classification of liver dynamic CT scans. In: Saeed K, Chaki R, Cortesi A, Wierzchoń S (eds) Computer information systems and industrial management. CSIM 2013. Lecture Notes in Computer Science, vol 8104. Springer, Berlin Heidelberg
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The scientific guarantor of this publication is Prof. G Thiéfin, Service d’Hépato-Gastroentérologie et de Cancérologie Digestive, Centre Hospitalier Universitaire de Reims, France
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The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.
Statistics and biometry
Two of the authors (A. Tenenhaus, PhD and S. Mulé, MD, PhD) have statistical expertise.
Informed consent
Written informed consent was not required for this study. In accordance with French law, this retrospective study on medical records has been authorised by the Commission Nationale Informatique et Libertés (authorisation number 111 85 23), allowing the computerised management of the medical data at the Reims University Hospital. The participants were informed of the possibility of using the information concerning them, for biomedical research purposes, and had a right of opposition.
Ethical approval
Institutional Review Board approval was not required. In accordance with French law, this retrospective study on medical records has been authorised by the Commission Nationale Informatique et Libertés (authorisation number 111 85 23), allowing the computerised management of the medical data at the Reims University Hospital. The participants were informed of the possibility of using the information concerning them, for biomedical research purposes, and had a right of opposition.
Methodology
• retrospective
• diagnostic or prognostic study
• performed at one institution
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Brenet Defour, L., Mulé, S., Tenenhaus, A. et al. Hepatocellular carcinoma: CT texture analysis as a predictor of survival after surgical resection. Eur Radiol 29, 1231–1239 (2019). https://doi.org/10.1007/s00330-018-5679-5
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DOI: https://doi.org/10.1007/s00330-018-5679-5