2019
DOI: 10.1186/s13014-019-1443-5
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A hybrid automated treatment planning solution for esophageal cancer

Abstract: Objective: This study aims to investigate a hybrid automated treatment planning (HAP) solution that combines knowledge-based planning (KBP) and script-based planning for esophageal cancer. Methods: In order to fully investigate the advantages of HAP, three planning strategies were implemented in the present study: HAP, KBP, and full manual planning. Each method was applied to 20 patients. For HAP and KBP, the objective functions for plan optimization were generated from a dose-volume histogram (DVH) estimation… Show more

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Cited by 17 publications
(9 citation statements)
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“…In the study on 20 patients, comparing manual and hybrid automated (script-based planning and knowledge-based planning combination) treatment planning, similar results were shown regarding dose burden on the heart, lungs and liver [18]. However, there are limitations in the direct comparison of the cited studies with our cohort.…”
Section: Discussionsupporting
confidence: 67%
“…In the study on 20 patients, comparing manual and hybrid automated (script-based planning and knowledge-based planning combination) treatment planning, similar results were shown regarding dose burden on the heart, lungs and liver [18]. However, there are limitations in the direct comparison of the cited studies with our cohort.…”
Section: Discussionsupporting
confidence: 67%
“…The use of volumetric modulated arc therapy (VMAT) was investigated by several authors [12][13][14][15][16][17][18] and, at least from a dosimetric point of view can be considered a promising further step in comparison to IMRT. Also, knowledge-based planning methods have been developed [19][20][21][22] to simplify the planning process.…”
Section: Introductionmentioning
confidence: 99%
“…The a ‐RESIST method can be used to reduce treatment planning errors and potentially reduce the chance of tumor misalignment for treatment by aligning soft‐tissues tumor matching one at a time. Recent publications have discussed the challenges of lung SBRT plan optimization including multicenter plan comparison 25,26 and explored automation of treatment planning for various treatment of other sites 27–29 although a ‐RESIST is the first of its kind for multiple lesions VMAT lung SBRT treatment. Based on these results, we have further validated a ‐RESIST via pretreatment QA measurement on our selected four new patients with two synchronous lesions and implemented clinically for lung SBRT treatments.…”
Section: Discussionmentioning
confidence: 99%