Towards near real-time adaptive proton therapy: the partial adaptation strategy
Virginia Gambetta,
Germany
MO-0481
Abstract
Towards near real-time adaptive proton therapy: the partial adaptation strategy
Authors: Virginia Gambetta1,2, Albin Fredriksson3, Stefan Menkel4, Christian Richter1,2,4,5,6, Kristin Stützer1,2,6
1OncoRay – National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany; 2Helmholtz-Zentrum Dresden - Rossendorf, Institute of Radiooncology – OncoRay, Dresden, Germany; 3RaySearch Laboratories AB, Research, Stockholm, Sweden; 4Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany; 5German Cancer Consortium (DKTK), Partner Site Dresden, and German Cancer Research Center (DKFZ), Heidelberg, Germany; 6Shared senior authorship, -, -, Germany
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Purpose or Objective
The preparation for an online-adaptive replanning in proton therapy (OAPT), including e.g. daily anatomy assessment and contouring of relevant structures, can considerably prolong the treatment session. We therefore propose for the first time a concept of partial adaptation as a step towards near real-time OAPT: the first non-adapted field is delivered during the replanning process while the remaining adapted fields shall also compensate for the suboptimal dose from the first field. The dosimetric consequences are demonstrated for head and neck cancer (HNC) patients.
Material and Methods
A partial adaptation workflow was implemented in RayStation (v.11.0.100) via the dose tracking module and the consideration of field-wise background dose. For six HNC patients, simultaneous integrated boost plans with three fields delivering 54Gy/66Gy to the low-risk/high-risk clinical target volume (CTV_Low/CTV_High) in 33 fractions were robustly optimized. Partially adapted fraction doses considering a non-adapted posterior field were generated on 3 control CTs (cCT) per patient, acquired in the first week, at mid of treatment and in the last week. Results were compared with doses from the non-adapted plan and from fully adapted plans on the cCT anatomy by analysing CTV coverage (D98%>95%), overdose (D1%) and organ at risk (OAR) sparing. Paired t-tests were used to indicate significant differences (p<0.05).
Results
In general, dose distributions from the partial and full adaptation strategy were quite similar, while non-adapted plans resulted in different individual deficits (Fig.1).
In all 18 fractions (Fig.2), partial as well as full adaptation led to sufficient coverage of both CTVs without significant differences (median D98% for both strategies: 97.2%/98.5% for CTV_Low/CTV_High), while the D98% of non-adapted plans was significantly lower, even below 95% in 6 and 3 cases and had median values of 95.3% and 97.5% for CTV_Low and CTV_High, respectively. Hotspot dose D1%(CTV_High) was above 105% in 6 cases for non-adapted and well below for adapted plans (median: 104%, 101.5% and 102.3% for no, partial and full adaptation).
Dose changes in OARs with respect to the initial plan were case dependent and usually within constraints. Absolute dose changes for D50%(Parotids) and D1%(Spinal Cord) were significantly smaller for both partial and full adaptation compared to the non-adapted plans that led more often to relevant dose increase.
Conclusion
The new concept of partial adaptation was proven to compensate for the dosimetric influence of anatomic changes similarly well as fully adapted plans, especially in terms of restoring target coverage and reducing hotspots. It could therefore be used to shorten OAPT treatment sessions towards near real-time OAPT. Moreover, the same implementation of partial adaptation would be beneficial for online adaptations that are triggered by online treatment verification (e.g. by prompt gamma imaging) after the first non-adapted field delivery.