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Preoperative prediction of cholangiocyte phenotype hepatocellular carcinoma on contrast-enhanced MRI and the prognostic implication after hepatectomy

Authors :
Yidi Chen
Jie Chen
Chongtu Yang
Yuanan Wu
Hong Wei
Ting Duan
Zhen Zhang
Liling Long
Hanyu Jiang
Bin Song
Source :
Insights into Imaging, Vol 14, Iss 1, Pp 1-14 (2023)
Publication Year :
2023
Publisher :
SpringerOpen, 2023.

Abstract

Abstract Background Hepatocellular carcinoma (HCC) expressing cytokeratin (CK) 7 or CK19 has a cholangiocyte phenotype that stimulates HCC proliferation, metastasis, and sorafenib therapy resistance This study aims to noninvasively predict cholangiocyte phenotype-positive HCC and assess its prognosis after hepatectomy. Methods Between January 2010 and May 2022, preoperative contrast-enhanced MRI was performed on consecutive patients who underwent hepatectomy and had pathologically confirmed solitary HCC. Two abdominal radiologists separately assessed the MRI features. A predictive model for cholangiocyte phenotype HCC was created using logistic regression analysis and five-fold cross-validation. A receiver operating characteristic curve was used to calculate the model performance. Kaplan–Meier and log-rank methods were used to evaluate survival outcomes. Results In total, 334 patients were included in this retrospective study. Four contrast-enhanced MRI features, including “rim arterial phase hyperenhancement” (OR = 5.9, 95% confidence interval [CI]: 2.9–12.0, 10 points), “nodule in nodule architecture” (OR = 3.5, 95% CI: 2.1–5.9, 7 points), “non-smooth tumor margin” (OR = 1.6, 95% CI: 0.8–2.9, 3 points), and “non-peripheral washout” (OR = 0.6, 95% CI: 0.3–1.0, − 3 points), were assigned to the cholangiocyte phenotype HCC prediction model. The area under the curves for the training and independent validation set were 0.76 and 0.73, respectively. Patients with model-predicted cholangiocyte phenotype HCC demonstrated lower rates of recurrence-free survival (RFS) and overall survival (OS) after hepatectomy, with an estimated median RFS and OS of 926 vs. 1565 days (p

Details

Language :
English
ISSN :
18694101
Volume :
14
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Insights into Imaging
Publication Type :
Academic Journal
Accession number :
edsdoj.fbcd18337e245b8af4c7ac32fdae5ad
Document Type :
article
Full Text :
https://doi.org/10.1186/s13244-023-01539-x