To establish a prediction model for survival benefits of locally advanced pancreatic cancer (LAPC) patients after sequential radiochemotherapy based on the signal value of diffusion-weighted imaging (DWI) before treatment.

Clinical imaging data of 39 patients with LAPC who received stereotactic body radiotherapy (SBRT) in the First Affiliated Hospital of Naval Medical University from January 2015 to December 2017 were retrospectively analyzed. The informed consents of all patients were obtained and the local ethical committee approval was received. Among them, 26 patients were male and 13 female, aged from 33 to 80 years, with a median age of 64 years. 33 patients were diagnosed with pancreatic head cancer and 6 cases of pancreatic body and tail cancer. 30 patients were treated with SBRT followed by S-1 chemotherapy. DWI sequence imaging with multiple b values was performed before SBRT. 11 b values (0, 25, 50, 75, 100, 150, 200, 400, 600, 800, 1 000 s/mm²) were adopted to obtain 11 overlapping DWI images with different b values. Cox regression model was used to analyze the correlation between the average signal intensity (SI) of the region of interests (ROI) and overall survival (OS) under different b values, to screen the independent risk factors, and to establish a nomogram prediction model, thereby predicting the survival benefits of patients with LAPC scheduled to undergo sequential radiochemotherapy. Prediction error curve (PEC) analysis was utilized to assess the prediction error by calculating integrated Brier score (IBS).

The follow-up time was ranged from 87 to 1 095 d, with a median of 353 d. During follow-up, 38 patients died and 1 survived. The OS of all patients was ranged from 84 to 1 095 d, with a median OS of 352 d, and the 1-year survival rate was 46%. Cox regression analysis showed that SI₁₀₀ (HR=0.997, 95%CI: 0.996-0.998), SI₆₀₀ (HR=0.996, 95%CI: 0.993-0.998), SI₈₀₀ (HR=0.994, 95%CI: 0.991-0.997) and SI₁₀₀₀ (HR=0.993, 95%CI: 0.989-0.996) were the independent predictive factors of OS (P<0.05). PEC analysis revealed that prediction model 1 (SI₁₀₀ + S-1, C-index 0.712), model 2 (SI₆₀₀ + age + S-1, C-index 0.731), model 3 (SI₈₀₀ + age + S-1, C-index 0.736) and model 4 (SI₁₀₀₀ + age + S-1, C-index 0.732) had smaller errors than other combinations within each model, and the IBS was 0.134, 0.133, 0.130 and 0.133, respectively. Corresponding nomogram prediction models were also established. Linear calibration chart indicated a high degree of consistency between the prediction effect and the actual effect, which further confirmed the reliability of the nomogram prediction model.

The nomogram prediction model based on the signal value of DWI sequence before radiochemotherapy can predict the survival benefits of LAPC patients scheduled to undergo radiochemtherapy, providing evidence for clinicians to make individualized treatment decisions and avoid overtreatment.