Dosimetric benefits of daily treatment plan adaptation for prostate cancer stereotactic body radiotherapy

Miriam Eckl,Sandra Springer,Jens Fleckenstein,Marvin Willam,Frederik Wenz,Volker Steil,Michael Ehmann,Gustavo R Sarria,Arne M Ruder

doi:10.1186/s13014-021-01872-9

Abstract

BackgroundHypofractionation is increasingly being applied in radiotherapy for prostate cancer, requiring higher accuracy of daily treatment deliveries than in conventional image-guided radiotherapy (IGRT). Different adaptive radiotherapy (ART) strategies were evaluated with regard to dosimetric benefits.MethodsTreatments plans for 32 patients were retrospectively generated and analyzed according to the PACE-C trial treatment scheme (40 Gy in 5 fractions). Using a previously trained cycle-generative adversarial network algorithm, synthetic CT (sCT) were generated out of five daily cone-beam CT. Dose calculation on sCT was performed for four different adaptation approaches: IGRT without adaptation, adaptation via segment aperture morphing (SAM) and segment weight optimization (ART1) or additional shape optimization (ART2) as well as a full re-optimization (ART3). Dose distributions were evaluated regarding dose-volume parameters and a penalty score.ResultsCompared to the IGRT approach, the ART1, ART2 and ART3 approaches substantially reduced the V37Gy(bladder) and V36Gy(rectum) from a mean of 7.4cm3 and 2.0cm3 to (5.9cm3, 6.1cm3, 5.2cm3) as well as to (1.4cm3, 1.4cm3, 1.0cm3), respectively. Plan adaptation required on average 2.6 min for the ART1 approach and yielded doses to the rectum being insignificantly different from the ART2 approach. Based on an accumulation over the total patient collective, a penalty score revealed dosimetric violations reduced by 79.2%, 75.7% and 93.2% through adaptation.ConclusionTreatment plan adaptation was demonstrated to adequately restore relevant dose criteria on a daily basis. While for SAM adaptation approaches dosimetric benefits were realized through ensuring sufficient target coverage, a full re-optimization mainly improved OAR sparing which helps to guide the decision of when to apply which adaptation strategy.

Highlights

Hypofractionation is increasingly being applied in radiotherapy for prostate cancer, requiring higher accuracy of daily treatment deliveries than in conventional image-guided radiotherapy (IGRT)
Methods of adaptive radiotherapy (ART) can address this issue [2], for example by using daily cone-beam computed tomography (CBCT) images to adapt the initial treatment plan according to daily organ deformations, tissue motion or weight loss [3,4,5]
The IGRT approach showed the largest standard deviations (SD)-ribbons for all four structures

Summary

Introduction

Hypofractionation is increasingly being applied in radiotherapy for prostate cancer, requiring higher accuracy of daily treatment deliveries than in conventional image-guided radiotherapy (IGRT). Methods of adaptive radiotherapy (ART) can address this issue [2], for example by using daily cone-beam computed tomography (CBCT) images to adapt the initial treatment plan according to daily organ deformations, tissue motion or weight loss [3,4,5] In this context, inferior CBCT image quality poses a major challenge for the clinical implementation of ART procedures at a conventional linac [6, 7]. Inferior CBCT image quality poses a major challenge for the clinical implementation of ART procedures at a conventional linac [6, 7] Nowadays, this can mostly be overcome by deep learning algorithms which are trained a priori with specific multimodal image datasets (treatment planning CT (pCT) and CBCT) and are afterwards used to generate corrected synthetic CT (sCT) images. These sCT were proven to successfully allow for reasonably fast workflow steps like automated image segmentation and accurate dose calculation for different tumor sites [8,9,10,11]

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