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

Autor: Zhao L; Department of Diagnostic Radiology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and PekingUnion Medical College, No.17, Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China., Ma X; Department of Diagnostic Radiology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and PekingUnion Medical College, No.17, Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China. maxiaohong@cicams.ac.cn., Liang M; Department of Diagnostic Radiology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and PekingUnion Medical College, No.17, Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China., Li D; Department of Diagnostic Radiology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and PekingUnion Medical College, No.17, Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China., Ma P; Department of Pathology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and PekingUnion Medical College, No.17, Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China., Wang S; Department of Pharmaceutical Diagnosis, GE Healthcare, Life Sciences, No.1 Tongji South Road, Beijing, 100176, China., Wu Z; State Key Laboratory of Molecular Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and PekingUnion Medical College , No.17, Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China., Zhao X; Department of Diagnostic Radiology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and PekingUnion Medical College, No.17, Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China. zhaoxinming@cicams.ac.cn.
Jazyk: angličtina
Zdroj: Cancer imaging : the official publication of the International Cancer Imaging Society [Cancer Imaging] 2019 Jul 15; Vol. 19 (1), pp. 49. Date of Electronic Publication: 2019 Jul 15.
DOI: 10.1186/s40644-019-0234-4
Abstrakt: 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.
Databáze: MEDLINE
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