Radiation and Cancer Physics

PD 12 - Physics 6 - Poster Discussion - Adaptive Planning/Delivery and Motion

1107 - Retrospective Evaluation of Decision-Making for Pancreatic Stereotactic MR-Guided Adaptive Radiation Therapy

Tuesday, October 23
3:21 PM - 3:27 PM
Location: Room 217 C/D

Retrospective Evaluation of Decision-Making for Pancreatic Stereotactic MR-Guided Adaptive Radiation Therapy
N. Jiang1, M. Tyran1,2, M. Cao1, A. Raldow1, J. M. Lamb1, D. Low3, M. L. Steinberg4, and P. Lee1; 1Department of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA, 2Institut Paoli Calmettes, Marseille, France, 3David Geffen School of Medicine at UCLA, Los Angeles, CA, 4University of California, Los Angeles, Los Angeles, CA

Purpose/Objective(s): Stereotactic, magnetic resonance (MR)-guided online adaptive radiotherapy (SMART) is a promising tool for pancreas stereotactic body radiotherapy (SBRT). Our current online adaptive strategy relies on daily image overview by the daily covering physician (DCP), who decides the need for a predicted plan if significant interfractional anatomical changes are noted. Predicted plans are achieved through applying the baseline plan on deformed contours based on daily imaging. These contours are reviewed, and manually adjusted by the DCP. If the dose to target volume (planning target volume (PTV) or gross tumor volume (GTV)) or organs at risk (OARs) violate constraints, an adapted plan is generated and delivered for treatment. In-depth review of daily images and deformed contours is limited by time and logistical constraints as well as physician to physician variations. Thus this study questions the reliability and accuracy of our online adaptive decision-making. For this purpose we investigate retrospectively if the final decision to adapt would have been different if every structure was fully recontoured offline. Decisions to adapt were compared from online and offline approaches.

Materials/Methods: We analyzed 35 sets of daily images from 5-fractions SBRT treatments for pancreas using SMART. Every patient had at least one adapted fraction online (median=2[1-3]). Each OAR and GTV was fully recontoured offline by the same physician for each fraction. The decision to adapt based on target volume coverage (PTV-V95%, GTV-V100%) and institutional OAR constraints (V35Gy) was re-evaluated for each fraction.

Results: N=14/35 fractions (40%) were adapted based on our online adaptive decision-making. When the decision to adapt was reevaluated based on the offline recontoured structures, a total of N=25/35 fractions (71%) would have been adapted. Exceeding constraints on OAR was the main reason for offline adapting decision (N= 19/24 (80%) with 11 fractions on the duodenum, 2 on the stomach and for 6 fractions on both). Of the 14 fractions that were initially adapted, N=13/14 (93%) fractions remained adapted according to the offline contours. However, of the 21 fractions that originally did not undergo online adaptation, decision was made based on a predicted plan for only 2 fractions. According to predicted plans based on offline recontours, N=12/21 (57%) fractions would have been adapted (Table).

Conclusion: When using SMART for SBRT, online predicted plan based on deformed and manually adjusted contours deformed contours have a high positive predictive value when relied on to decide whether to adapt a plan. However, daily image review underestimate the need for adaptation, which possibly may be mitigated by generating a predicted plan for every fraction that is delivered using SMART.
Table: DECISION TO ADAPT, RESULTS
OFFLINE DECISION MISSMATCH
25 YES 10 NO
ONLINE 14 YES 13 1 7%
21 NO 12 9 57%

Author Disclosure: N. Jiang: None. M. Cao: None. A. Raldow: None. J.M. Lamb: Consultant; ViewRay, Inc. member; Smart Cancer Centres Clinical Advisory Board. D. Low: Research Grant; Varian Medican Systems Inc, Siemens. Travel Expenses; ViewRay Inc. Stock; ViewRay. M.L. Steinberg: Honoraria; Accuray. P. Lee: Honoraria; Viewray. Commitee Co-Chair; Committee Co-Chair.

Naomi Jiang, MD

UCLA Radiation Oncology

Disclosure:
Employment
UCLA: Resident Physician: Employee

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