Planning comparison of five automated treatment planning solutions for locally advanced head and neck cancer.
Background: Automated treatment planning and/or optimization systems (ATPS) are in the process of broad clinical implementation aiming at reducing inter-planner variability, reducing the planning time allocated for the optimization process and improving plan quality. Five different ATPS used clinica...
| Publicado en: | Radiation Oncology Vol. 13; no. 1 |
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| Autores principales: | , , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
BioMed Central
9/10/2018
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=131698722&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 131698722 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 1748717X 38NX jtl: Radiation Oncology issn: 1748717X maglogo: N pubinfo: dt: 9/10/2018 vid: 13 iid: 1 pid: 24147 pub: BioMed Central artinfo: ui: 131698722 131698722 NLM30201017 131698722 10.1186/s13014-018-1113-z NLM30201017 131698722 ppct: 1 formats: tig: atl: Planning comparison of five automated treatment planning solutions for locally advanced head and neck cancer. aug: au: Krayenbuehl, J. Zamburlini, M. Ghandour, S. Pachoud, M. Lang-Tanadini, S. Tol, J. Guckenberger, M. Verbakel, W. F. A. R. Tanadini-Lang, S affil: Department of Radiation Oncology, University Hospital Zurich, Rämistrasse 100, CH-8091, Zurich, Switzerland sug: subj: Radiotherapy, Computer-Assisted Methods Head and Neck Neoplasms Radiotherapy Human Head and Neck Neoplasms Pathology Body Regions Radiation Effects Radiotherapy, Conformal Algorithms Radiation Dosage Validation Studies Comparative Studies Evaluation Research Multicenter Studies Ferrans and Powers Quality of Life Index Scales ab: Background: Automated treatment planning and/or optimization systems (ATPS) are in the process of broad clinical implementation aiming at reducing inter-planner variability, reducing the planning time allocated for the optimization process and improving plan quality. Five different ATPS used clinically were evaluated for advanced head and neck cancer (HNC).Methods: Three radiation oncology departments compared 5 different ATPS: 1) Automatic Interactive Optimizer (AIO) in combination with RapidArc (in-house developed and Varian Medical Systems); 2) Auto-Planning (AP) (Philips Radiation Oncology Systems); 3) RapidPlan version 13.6 (RP1) with HNC model from University Hospital A (Varian Medical Systems, Palo Alto, USA); 4) RapidPlan version 13.7 (RP2) combined with scripting for automated setup of fields with HNC model from University Hospital B; 5) Raystation multicriteria optimization algorithm version 5 (RS) (Laboratories AB, Stockholm, Sweden). Eight randomly selected HNC cases from institution A and 8 from institution B were used. PTV coverage, mean and maximum dose to the organs at risk and effective planning time were compared. Ranking was done based on 3 Gy increments for the parallel organs.Results: All planning systems achieved the hard dose constraints for the PTVs and serial organs for all patients. Overall, AP achieved the best ranking for the parallel organs followed by RS, AIO, RP2 and RP1. The oral cavity mean dose was the lowest for RS (31.3 ± 17.6 Gy), followed by AP (33.8 ± 17.8 Gy), RP1 (34.1 ± 16.7 Gy), AIO (36.1 ± 16.8 Gy) and RP2 (36.3 ± 16.2 Gy). The submandibular glands mean dose was 33.6 ± 10.8 Gy (AP), 35.2 ± 8.4 Gy (AIO), 35.5 ± 9.3 Gy (RP2), 36.9 ± 7.6 Gy (RS) and 38.2 ± 7.0 Gy (RP1). The average effective planning working time was substantially different between the five ATPS (in minutes): < 2 ± 1 for AIO and RP2, 5 ± 1 for AP, 15 ± 2 for RP1 and 340 ± 48 for RS, respectively.Conclusions: All ATPS were able to achieve all planning DVH constraints and the effective working time was kept bellow 20 min for each ATPS except for RS. For the parallel organs, AP performed the best, although the differences were small. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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