Evaluation of tumour pseudocapsule using computed tomography-based radiomics in pancreatic neuroendocrine tumours to predict prognosis and guide surgical strategy: a cohort study.
Authors
Affiliations (12)
Affiliations (12)
- Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.
- Center for Neuroendocrine Tumours, Fudan University Shanghai Cancer Center, Shanghai, China.
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
- Shanghai Pancreatic Cancer Institute, Shanghai, China.
- Pancreatic Cancer Institute, Fudan University, Shanghai, China.
- Department of Artificial Intelligence Medicine, Graduate School of Medicine, Chiba University, Chiba, Japan.
- Department of Diagnostic and Interventional Radiology, University of Tsukuba, Ibaraki, Japan.
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China.
- Institute of Pathology, Fudan University, Shanghai, China.
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.
- Department of Head, Neck and Neuroendocrine Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
- Neuroendocrine Tumour Center, Fudan University Shanghai Cancer Center, Shanghai, China.
Abstract
To date, indications for a surgical approach of small pancreatic neuroendocrine tumours (PanNETs) remain controversial. This cohort study aimed to identify the pseudocapsule status preoperatively to estimate the rationality of enucleation and survival prognosis of PanNETs, particularly in small tumours. Clinicopathological data were collected from patients with PanNETs who underwent the first pancreatectomy at our hospital (n = 578) between February 2012 and September 2023. Kaplan-Meier curves were constructed to visualise prognostic differences. Five distinct tissue samples were obtained for single-cell RNA sequencing (scRNA-seq) to evaluate variations in the tumour microenvironment. Radiological features were extracted from preoperative arterial-phase contrast-enhanced computed tomography. The performance of the pseudocapsule radiomics model was assessed using the area under the curve (AUC) metric. 475 cases (mean [SD] age, 53.01 [12.20] years; female vs male, 1.24:1) were eligible for this study. The mean pathological diameter of tumour was 2.99 cm (median: 2.50 cm; interquartile range [IQR]: 1.50-4.00 cm). These cases were stratified into complete (223, 46.95%) and incomplete (252, 53.05%) pseudocapsule groups. A statistically significant difference in aggressive indicators was observed between the two groups (P < 0.001). Through scRNA-seq analysis, we identified that the incomplete group presented a markedly immunosuppressive microenvironment. Regarding the impact on recurrence-free survival, the 3-year and 5-year rates were 94.8% and 92.5%, respectively, for the complete pseudocapsule group, compared to 76.7% and 70.4% for the incomplete pseudocapsule group. The radiomics-predictive model has a significant discrimination for the state of the pseudocapsule, particularly in small tumours (AUC, 0.744; 95% CI, 0.652-0.837). By combining computed tomography-based radiomics and machine learning for preoperative identification of pseudocapsule status, the intact group is more likely to benefit from enucleation.