Dose Prediction Model for Duodenum Sparing With a Biodegradable Hydrogel Spacer for Pancreatic Cancer Radiation Therapy

Purpose: We previously have shown the feasibility of duodenum sparing using a biodegradable hydrogel spacer in pancreatic cancer radiation therapy. In this study, we propose an overlap volume histogram (OVH) prediction model to select patients who might benefit from hydrogel placement and to predict the hydrogel spacing required to achieve clinical constraints. Methods and Materials: OVH metrics for the duodenum were collected from the stereotactic body radiation therapy plans of 232 patients with unresectable pancreatic cancer (33 Gy in 5 fractions). OVH metrics L-9cc and L-3cc were defined as the tumor volume expansion distance at which 9 cm(3) and 3 cm(3) volumes of the duodenum overlap with tumor. D-9cc, and D-3cc of the duodenum were defined as the dose-volume histogram dose to 9 cm(3) and 3 cm(3), respectively, of the duodenum. Prediction models were established by linear regression between L-x and D-x where x = 3 cm(3) and 9 cm(3). OVH thresholds were obtained for predicting the target spacer thickness. The accuracy of the prediction model was then evaluated using treatment plans on pre-and post -hydrogel injection computed tomography scans from 2 cadaver specimens and 6 patients with previously treated locally advanced pancreatic cancer with simulated spacer. Results: Linear regression analysis showed a significant correlation between L-x and D-x (r(2) = 0.51 and 0.51 for L-3cc-D-3cc and L-9cc -D(9cc )respectively; both P < .01). The OVH thresholds were <(L)over bar>(3cc) = 7 mm and (L) over bar (9cc) = 13 mm. The observed planning doses D-3cc and D-9cc of duodenum from pre-and post-hydrogel injection computed tomography scans of cadaver specimens and clinical patients with simulated spacer using predicted target spacer thickness were within the OVH model prediction range. Conclusion: Our model may predict which patients require placement of a hydrogel spacer before stereotactic body radiation therapy to meet predefined dose constraints. Furthermore, by predicting the required target hydrogel thickness, the spacer injection can be better guided to improve efficacy. (C) 2018 The Author(s). Published by Elsevier Inc.