Computed Tomography Radiomics Signatures: Sensitive biomarkers for clinical decision support in pancreatic cancer- a pilot study

Aim To evaluate if suitably designed computed tomography (CT) radiomic signatures are sensitive to tumour transformation, and able to predict disease free survival (DFS) and overall survival (OS) time in patients with pancreatic cancer. Method Ethical approval by UNSW review board was obtained for this retrospective analysis. This study consisted of 27 patients with pancreatic cancer. Unsupervised principal component analysis was employed to evaluate the sensitivity of radiomic signatures to cancer presence and treatment. Further, optimised radiomic signatures were discovered using swarm intelligence and assessed for their capability to predict DFS and OS based on Kaplan-Meier analysis and receiver-operator characteristics (ROC) curves. Results We found that appropriate two radiomic signature are sensitive to cancer presence (area under the curve, AUC=0.95) and cancer treatment, respectively. Two other optimized radiomics signatures showed significant correlations with DFS and OS, respectively (p<0.05). Conclusion The CT radiomics signatures are an independent biomarkers which are modified when cancer is present and can help to estimate DFS and OS in patients. These signatures have the potential to be used to support clinical decision-making in pancreatic cancer treatment.