ESTRO 2024 - Abstract Book

S4015

Physics - Inter-fraction motion management and offline adaptive radiotherapy

ESTRO 2024

planning methods to test an automated workflow with conventional linear accelerators where the final plan exactly matches the patient’s anatomy of the day.

Material/Methods:

A research version of the commercial software ABAS (Elekta) for the multi atlas-based segmentation of H&N structures on CT images is used. A deformable contour propagation is then employed to generate sCT images from the CBCT. Thirty-three anatomical structures and five HU layers (air, bones, tissue, fat, patient) are contoured. The mCycle algorithm, recently launched under the name of ElektaONE AutoPlanning, is used for the a-priori Lexicographic multicriteria plan calculation with a wish-list for Simultaneously Integrated Boost (SIB) treatment. The retrospective planning on CBCT images is performed using bulk density assignment, with the average electron densities of each structure derived from the simulation CT. Two patients are chosen for a retrospective CBCT adaptive online feasibility analysis. The same strategy conventionally adopted for MRgRT, the Adapt to Position (ATP) and Adapt to Shape (ATS) techniques, is replicated. For eleven fractions, an ATS and ATP plan is generated. To assess the differences for the two adaptive modalities the clinical goals for targets and OARs and the percentage passing rate of constraints, corresponding to how many times on the eleven fractions that constraint is met, are explored for each fraction. Signed-rank Wilcoxon test is performed to assess the statistical relevance. An analysis of the timing for the different steps required to produce an online adaptive plan is also carried out to assess its clinical applicability.

Results:

In the ATP techniques target coverage is inadequate and statistically different from the accepted values. In the ATS the results align with the initial approved values. The pass percentages for both PTVs are 100% for the ATS technique for both patient while for the ATP in 9% and 91% for PTV1 and PTV2 for the first patient, (Fig.1), and 27% and 18% for the second patient, (Fig.2). Relevant results are also obtained for one of the parotids. For the first patient the pass percentage for the right parotid is 100% for ATS and 73% for ATP, while for the left parotid of the second patient is 100% for ATS and 55% for ATP. For the two analysed patients, the ATP and ATS re-planning time are around 2 minutes and 14 minutes respectively. The estimated total workflow time (which is the sum of the pre-treatment CBCT, adapt anatomy tool contour, replanning time, position verification CBCT and dose delivery) for online ATP treatment is 9 minutes while for the online ATS is approximately 20 minutes.