Signature of survival: a 18F-FDG PET based whole-liver radiomic analysis predicts survival after 90Y-TARE for hepatocellular carcinoma

被引:45
作者
Blanc-Durand, Paul [1 ]
Van der Gucht, Axel [1 ]
Jreige, Mario [1 ]
Nicod-Lalonde, Marie [1 ]
Silva-Monteiro, Marina [1 ]
Prior, John O. [1 ]
Denys, Alban [2 ]
Depeursinge, Adrien [3 ]
Schaefer, Niklaus [1 ]
机构
[1] Lausanne Univ Hosp, Dept Nucl Med & Mol Imaging, Lausanne, Switzerland
[2] Lausanne Univ Hosp, Dept Radiol & Intervent Radiol, Lausanne, Switzerland
[3] Univ Appl Sci Western Switzerland HES SO, Inst Informat Syst, Sierre, Switzerland
基金
瑞士国家科学基金会;
关键词
F-18-FDG PET; TARE; radiomics; hepatocellular carcinoma; survival; GENE-EXPRESSION PROGRAMS; PROGNOSTIC VALUE; FDG PET/CT; TUMOR; CT; RECURRENCE; CANCER; RADIOEMBOLIZATION; TRANSPLANTATION; BIOMARKER;
D O I
10.18632/oncotarget.23423
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Purpose: To generate a predictive whole-liver radiomics scoring system for progression-free survival (PFS) and overall survival (OS) in patients undergoing transarterial radioembolization using Yttrium-90 (Y-90-TARE) for unresectable hepatocellular carcinoma (uHCC). Results: The generated pPET-RadScores were significantly correlated with survival for PFS (median of 11.4 mo [95% confidence interval CI: 6.3-16.5 mo] in low-risk group [PFS-pPET-RadScore < 0.09] vs. 4.0 mo [95% CI: 2.3-5.7 mo] in high-risk group [PFS-pPET-RadScore > 0.09]; P = 0.0004) and OS (median of 20.3 mo [95% CI: 5.7-35 mo] in low-risk group [OS-pPET-RadScore < 0.11] vs. 7.7 mo [95% CI: 6.0-9.5 mo] in high-risk group [OS-pPET-RadScore > 0.11]; P = 0.007). The multivariate analysis confirmed PFS-pPET-RadScore (P = 0.006) and OS-pPET-RadScore (P = 0.001) as independent negative predictors. Conclusion: Pretreatment F-18-FDG PET whole-liver radiomics signature appears as an independent negative predictor for PFS and OS in patients undergoing Y-90-TARE for uHCC. Methods: Pretreatment F-18-FDG PET of 47 consecutive patients undergoing Y-90-TARE for uHCC (31 resin spheres, 16 glass spheres) were retrospectively analyzed. For each patient, based on PET radiomics signature from whole-liver semi-automatic segmentation, PFS and OS predictive PET-radiomics scores (pPET-RadScores) were obtained using LASSO Cox regression. Using X-tile software, the optimal score to predict PFS (PFS-pPET-RadScore) and OS (OS-pPET-RadScore) served as cutoff to separate high and low-risk patients. Survival curves were estimated using the Kaplan-Meier method. The prognostic value of PFS and OS-pPET-RadScore, Barcelona-Clinic Liver Cancer staging system and serum alpha-fetoprotein level was analyzed to predict PFS and OS in multivariate analysis.
引用
收藏
页码:4549 / 4558
页数:10
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