期刊
THERAPEUTIC ADVANCES IN MEDICAL ONCOLOGY
卷 12, 期 -, 页码 -出版社
SAGE PUBLICATIONS LTD
DOI: 10.1177/1758835920971416
关键词
digital pathology; multi-scale features; nasopharyngeal carcinoma; radiomics; survival analysis
类别
资金
- National Key R&D Program of China [2018YFC0910600, 2017YFA0205200]
- 2016 Guangdong special support program outstanding talent project
- 2017 Zhuhai High-level Health Team Project
- National Natural Science Foundation of China [81620108017, 81901699, 82022036, 91959130, 81971776, 81771924, 81930053]
- Beijing Natural Science Foundation [L182061]
- Strategic Priority Research Program of Chinese Academy of Sciences [XDB 38040200]
- Youth Innovation Promotion Association CAS [2017175]
Background: To explore the prognostic value of radiomics-based and digital pathology-based imaging biomarkers from macroscopic magnetic resonance imaging (MRI) and microscopic whole-slide images for patients with nasopharyngeal carcinoma (NPC). Methods: We recruited 220 NPC patients and divided them into training (n = 132), internal test (n = 44), and external test (n = 44) cohorts. The primary endpoint was failure-free survival (FFS). Radiomic features were extracted from pretreatment MRI and selected and integrated into a radiomic signature. The histopathological signature was extracted from whole-slide images of biopsy specimens using an end-to-end deep-learning method. Incorporating two signatures and independent clinical factors, a multi-scale nomogram was constructed. We also tested the correlation between the key imaging features and genetic alternations in an independent cohort of 16 patients (biological test cohort). Results: Both radiomic and histopathologic signatures presented significant associations with treatment failure in the three cohorts (C-index: 0.689-0.779, all p < 0.050). The multi-scale nomogram showed a consistent significant improvement for predicting treatment failure compared with the clinical model in the training (C-index: 0.817 versus 0.730, p < 0.050), internal test (C-index: 0.828 versus 0.602, p < 0.050) and external test (C-index: 0.834 versus 0.679, p < 0.050) cohorts. Furthermore, patients were stratified successfully into two groups with distinguishable prognosis (log-rank p < 0.0010) using our nomogram. We also found that two texture features were related to the genetic alternations of chromatin remodeling pathways in another independent cohort. Conclusion: The multi-scale imaging features showed a complementary value in prognostic prediction and may improve individualized treatment in NPC.
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