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Construction and Validation of a MRI‑Based Radiomic Nomogram to Predict Overall Survival in Patients with Local
Yun Lin1, Yixin Gao2, Tingsong Weng2
1Department of Obstetrics and Gynecology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China; Central laboratory, Cancer Hospital of Shantou University Medical College, Shantou, China.
This study developed a radiomics nomogram to predict survival in locally advanced cervical cancer patients. The nomogram, using MRI radiomic features, age, and parametrial invasion, accurately forecasts overall survival outcomes.
Area of Science:
- Oncology
- Medical Imaging
- Radiomics
Background:
- Cervical cancer is a significant global health concern, ranking as the fourth most common cancer in women.
- Radiomics offers a novel approach to extract quantitative imaging features for enhanced cancer management.
- Locally advanced cervical cancer requires accurate prognostic tools for effective treatment planning.
Purpose of the Study:
- To develop and validate a radiomics nomogram for predicting survival in patients with locally advanced cervical cancer.
- To identify independent prognostic factors, including radiomic features from MRI, for overall survival.
- To assess the clinical utility of the nomogram in forecasting survival outcomes.
Main Methods:
- A retrospective analysis of 582 locally advanced cervical cancer patients across three centers (training, internal, and external validation cohorts).
- Extraction of radiomic features from pretreatment MRI scans.
- Application of LASSO regression for feature selection and calculation of radiomic scores, followed by Cox regression for nomogram construction incorporating clinicopathological factors.
Main Results:
- Six radiomic features were significantly associated with overall survival (OS).
- The radiomics nomogram demonstrated favorable discrimination, with AUC values ranging from 0.634-0.881 across validation cohorts.
- Age, parametrial invasion, and radiomic score were identified as independent prognostic indicators.
Conclusions:
- The developed radiomics nomogram, integrating MRI-derived radiomic features and clinicopathological factors, provides satisfactory discrimination for predicting OS in locally advanced cervical cancer.
- The nomogram shows clinical utility in predicting 1-, 2-, and 3-year survival rates.
- Decision curve analysis confirmed the nomogram's high clinical net benefit.
