Comparison of MR-soft tissue based versus biliary stent based alignment for image guidance in pancreatic SBRT.

PURPOSE

The role of biliary stents in image-guided localization for pancreatic cancer has been inconclusive. To date, stent accuracy has been largely evaluated against implanted fiducials on cone beam computed tomography. We aim to use magnetic resonance (MR) soft tissue as a direct reference to examine the geometric and dosimetric impacts of stent-based localization on the newly available MR linear accelerator.

METHODS

Thirty pancreatic cancer patients (132 fractions) treated on our MR linear accelerator were identified to have a biliary stent. In our standard adaptive workflow, patients were set up to the target using soft tissue for image registration and structures were re-contoured on daily MR images. The original plan was then projected on treatment anatomy and dose predicted, followed by plan re-optimization and treatment delivery. These online predicted plans were soft tissue-based and served as reference plans. Retrospective image registration to the stent was performed offline to simulate stent-based localization and the magnitude of shifts was taken as the geometric accuracy of stent localization. New predicted plans were generated based on stent-alignment for dosimetric comparison.

RESULTS

Shifts were within 3 mm for 90% of the cases (mean = 1.5 mm); however, larger shifts up to 7.2 mm were observed. Average PTV coverage dropped by 1.1% with a maximum drop of 26.8%. The mean increase in V35Gy was 0.15, 0.05, 0.02, and 0.02 cc for duodenum, stomach, small bowel and large bowel, respectively. Stent alignment was significantly worse for all metrics except for small bowel (p = 0.07).

CONCLUSIONS

Overall discrepancy between stent- and soft tissue-alignment was modest; however, large discrepancies were observed for select cases. While PTV coverage loss may be compensated for by using a larger margin, the increase in dose to gastrointestinal organs at risk may limit the role of biliary stents in image-guided localization.