Finite Element-Based Personalized Simulation of Duodenal Hydrogel Spacer: Spacer Location Dependent Duodenal Sparing and a Decision Support System for Spacer-Enabled Pancreatic Cancer Radiation Therapy

Purpose: Pancreatic cancer is the fourth leading cause of cancer-related death, with a very low 5-year overall survival rate (OS). Radiation therapy (RT) together with dose escalation significantly increases the OS at 2 and 3 years. However, dose escalation is very limited due to the proximity of the duodenum. Hydrogel spacers are an effective way to reduce duodenal toxicity, but the complexity of the anatomy and the procedure makes the success and effectiveness of the spacer procedure highly uncertain. To provide a preoperative simulation of hydrogel spacers, we presented a patient-specific spacer simulator algorithm and used it to create a decision support system (DSS) to provide a preoperative optimal spacer location to maximize the spacer benefits. Materials and Methods: Our study was divided into three phases. In the validation phase, we evaluated the patient-specific spacer simulator algorithm (FEMOSSA) for the duodenal spacer using the dice similarity coefficient (DSC), overlap volume histogram (OVH), and radial nearest neighbor distance (RNND). For the simulation phase, we simulated four virtual spacer scenarios based on the location of the spacer in para-duodenal space. Next, stereotactic body radiation therapy (SBRT) plans were designed and dosimetrically analyzed. Finally, in the prediction phase, using the result of the simulation phase, we created a Bayesian DSS to predict the optimal spacer location and biological effective dose (BED). Results: A realistic simulation of the spacer was achieved, reflected in a statistically significant increase in average target and duodenal DSC for the simulated spacer. Moreover, the small difference in average mean and 5th-percentile RNNDs (0.5 and 2.1 mm) and OVH thresholds (average of less than 0.75 mm) showed that the simulation attained similar separation as the real spacer. We found a spacer-location-independent decrease in duodenal V20Gy, a highly spacer-location-dependent change in V33Gy, and a strong correlation between L1cc and V33Gy. Finally, the Bayesian DSS predicted the change in BED with a root mean squared error of 3.6 Gys. Conclusions: A duodenal spacer simulator platform was developed and used to systematically study the dosimetric effect of spacer location. Further, L1cc is an informative anatomical feedback to guide the DSS to indicate the spacer efficacy, optimum location, and expected improvement.