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| Content Provider | Springer Nature : BioMed Central |
|---|---|
| Author | Wang, Gongzheng Ding, Feier Chen, Kaige Liang, Zhuoshuai Han, Pengxi Wang, Linxiang Cui, Fengyun Zhu, Qiang Cheng, Zhaoping Chen, Xingzhi Huang, Chencui Cheng, Hongxia Wang, Ximing Zhao, Xinya |
| Abstract | Background Proliferative hepatocellular carcinomas (HCCs) is a class of aggressive tumors with poor prognosis. We aimed to construct a computed tomography (CT)-based radiomics nomogram to predict proliferative HCC, stratify clinical outcomes and explore the tumor microenvironment. Methods Patients with pathologically diagnosed HCC following a hepatectomy were retrospectively collected from two medical centers. A CT-based radiomics nomogram incorporating radiomics model and clinicoradiological features to predict proliferative HCC was constructed using the training cohort (n = 184), and validated using an internal test cohort (n = 80) and an external test cohort (n = 89). The predictive performance of the nomogram for clinical outcomes was evaluated for HCC patients who underwent surgery (n = 201) or received transarterial chemoembolization (TACE, n = 104). RNA sequencing data and histological tissue slides from The Cancer Imaging Archive database were used to perform transcriptomics and pathomics analysis. Results The areas under the receiver operating characteristic curve of the radiomics nomogram to predict proliferative HCC were 0.84, 0.87, and 0.85 in the training, internal test, and external test cohorts, respectively. The radiomics nomogram could stratify early recurrence-free survivals in the surgery outcome cohort (hazard ratio [HR] = 2.25; P < 0.001) and progression-free survivals in the TACE outcome cohort (HR = 2.21; P = 0.03). Transcriptomics and pathomics analysis indicated that the radiomics nomogram was associated with carbon metabolism, immune cells infiltration, TP53 mutation, and heterogeneity of tumor cells. Conclusion The CT-based radiomics nomogram could predict proliferative HCC, stratify clinical outcomes, and measure a pro-tumor microenvironment. |
| Related Links | https://translational-medicine.biomedcentral.com/counter/pdf/10.1186/s12967-024-05393-3.pdf |
| Ending Page | 16 |
| Page Count | 16 |
| Starting Page | 1 |
| File Format | HTM / HTML |
| ISSN | 14795876 |
| DOI | 10.1186/s12967-024-05393-3 |
| Journal | Journal of Translational Medicine |
| Issue Number | 1 |
| Volume Number | 22 |
| Language | English |
| Publisher | BioMed Central |
| Publisher Date | 2024-09-02 |
| Access Restriction | Open |
| Subject Keyword | Biomedicine Medicine Public Health Hepatocellular carcinoma Radiomics Diagnostic study Prognostic study Tumor microenvironment Medicine/Public Health |
| Content Type | Text |
| Resource Type | Article |
| Subject | Biochemistry, Genetics and Molecular Biology Medicine |
| Journal Impact Factor | 6.1/2023 |
| 5-Year Journal Impact Factor | 6.3/2023 |
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