Automatic treatment planning facilitates fast generation of high-quality treatment plans for esophageal cancer

Publikation: Bidrag til tidsskriftKonferenceartikelForskningpeer review


BACKGROUND: The quality of radiotherapy planning has improved substantially in the last decade with the introduction of intensity modulated radiotherapy. The purpose of this study was to analyze the plan quality and efficacy of automatically (AU) generated VMAT plans for inoperable esophageal cancer patients.

MATERIAL AND METHODS: Thirty-two consecutive inoperable patients with esophageal cancer originally treated with manually (MA) generated volumetric modulated arc therapy (VMAT) plans were retrospectively replanned using an auto-planning engine. All plans were optimized with one full 6MV VMAT arc giving 60 Gy to the primary target and 50 Gy to the elective target. The planning techniques were blinded before clinical evaluation by three specialized oncologists. To supplement the clinical evaluation, the optimization time for the AU plan was recorded along with DVH parameters for all plans.

RESULTS: Upon clinical evaluation, the AU plan was preferred for 31/32 patients, and for one patient, there was no difference in the plans. In terms of DVH parameters, similar target coverage was obtained between the two planning methods. The mean dose for the spinal cord increased by 1.8 Gy using AU (p = .002), whereas the mean lung dose decreased by 1.9 Gy (p < .001). The AU plans were more modulated as seen by the increase of 12% in mean MUs (p = .001). The median optimization time for AU plans was 117 min.

CONCLUSIONS: The AU plans were in general preferred and showed a lower mean dose to the lungs. The automation of the planning process generated esophageal cancer treatment plans quickly and with high quality.

TidsskriftActa Oncologica
Udgave nummer11
Sider (fra-til)1495-1500
StatusUdgivet - 2. nov. 2017
Begivenhed15th Acta Oncologica symposium: BiGART2017 - Biology-Guided Adaptive Radiotherapy - Aarhus, Danmark
Varighed: 13. jun. 201716. jun. 2017


Konference15th Acta Oncologica symposium

Fingeraftryk Dyk ned i forskningsemnerne om 'Automatic treatment planning facilitates fast generation of high-quality treatment plans for esophageal cancer'. Sammen danner de et unikt fingeraftryk.