Prediction for early recurrence of intrahepatic mass-forming cholangiocarcinoma: quantitative magnetic resonance imaging combined with prognostic immunohistochemical markers

Abstract

Background Partial hepatectomy is the first option for intrahepatic mass-forming cholangiocarcinoma (IMCC) treatment, which would prolong survival. The main reason for the poor outcome after curative resection is the high incidence of early recurrence (ER). The aim of this study was to investigate the combined predictive performance of qualitative and quantitative magnetic resonance imaging (MRI) features and prognostic immunohistochemical markers for the ER of IMCC. Methods Forty-seven patients with pathologically proven IMCC were enrolled in this retrospective study. Preoperative contrast-enhanced MRI and post-operative immunohistochemical staining of epidermal growth factor receptors (EGFR), vascular endothelial growth factor receptor (VEGFR), P53 and Ki67 were performed. Univariate analysis identified clinic-radiologic and pathological risk factors of ER. Radiomics analysis was performed based on four MRI sequences including fat suppression T2-weighted imaging (T2WI/FS), arterial phase (AP), portal venous phase (PVP), and delayed phase (DP) contrast enhanced imaging. A clinicoradiologic-pathological (CRP) model, radiomics model, and combined model were developed. And ROC curves were used to explore their predictive performance for ER stratification. Results Enhancement patterns and VEGFR showed significant differences between the ER group and non-ER group ( P = 0.001 and 0.034, respectively). The radiomics model based on AP, PVP and DP images presented superior AUC (0.889, 95% confidence interval (CI): 0.783–0.996) among seven radiomics models with a sensitivity of 0.938 and specificity of 0.839. The combined model, containing enhancement patterns, VEGFR and radiomics features, showed a preferable ER predictive performance compared to the radiomics model or CRP model alone, with AUC, sensitivity and specificity of 0.949, 0.875 and 0.774, respectively. Conclusions The combined model was the superior predictive model of ER. Combining qualitative and quantitative MRI features and VEGFR enables ER prediction, thus facilitating personalized treatment for patients with IMCC.

Translating Biomarkers of Cholangiocarcinoma for Theranosis: A Systematic Review

“…This review included 15 different studies which report Epidermal Growth Factor Receptor (EGFR) presence in CCA [ 50 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 ]. Ten out of fifteen studies investigating EGFR involve Eastern tissue specimens from Japan, China, Korea, and Thailand with 5/15 originating from USA, Brazil, Italy, and Germany.…”

Radiomics in liver diseases: Current progress and future opportunities

“…Data used in radiomics studies can be single‐centre or multi‐centre, and retrospective or prospective. Here, we searched PubMed (8 October 2019) for radiomics studies on liver diseases using terms (liver diseases AND radiomics), and found 36 clinical target‐oriented published work 13‐48 . Most (33 out of 36) studies were performed on single‐centre with retrospective cohort, while only two studies were performed on multi‐centre and prospective cohort (Table 1).…”

“…This groundbreaking result laid a foundation and greatly encouraged researchers to explore the potential of quantitative imaging tool in preoperative genetic/pathological outcome prediction. Hence, a great deal of radiomics studies have been conducted using multi‐parametric and multi‐modality imaging in terms of liver disease diagnosis and treatment decision making 13‐48 . In certain scenarios, this artificial intelligence‐based technique could even compete pathological gold standard, providing new ways for unsolved clinical problems in the paradigm of liver disease management 16 .…”

Radiomics for liver tumours

“…Furthermore, by combining radiomics features with clinical data, survival prediction might even be improved in patients with HCC [ 13 , 107 , 108 ]. Even in case of cholangiocarcinoma, pre-operative MRI was able to predict early recurrence, especially in combination with immunohistochemical markers [ 109 ].…”

“…[ 13 ] To identify aggressive behaviour and predict recurrence of HCC after liver transplantation (LT) CECT 133 T: 93 V: 40 Radiomics signature extracted from CT images may be a potential imaging biomarker for liver cancer invasion and enable accurate prediction of HCC recurrence after LT Zhao et al. [ 109 ] To investigate the combined predictive performance of qualitative and quantitative MRI features and prognostic immunohistochemical markers for the ER of intrahepatic mass-forming cholangiocarcinoma (IMCC) CEMRI 47 The combined model was the superior predictive model of ER The columns Aims and Conclusion are directly based on the original work as cited in the column Author (wording partly adapted). CECT contrast-enhanced computed tomography, ER early recurrence, HCC hepatocellular carcinoma, MRI magnetic resonance imaging, MVI microvascular invasion …”