A knowledge-based quantitative approach to characterize treatment plan quality

• Verfasst von: Alnaalwa, Buthayna [VerfasserIn]
• Verfasst von: Nwankwo, Obioma [VerfasserIn]
• Verfasst von: Abo-Madyan, Yasser [VerfasserIn]
• Verfasst von: Giordano, Frank Anton [VerfasserIn]
• Verfasst von: Wenz, Frederik [VerfasserIn]
• Verfasst von: Glatting, Gerhard [VerfasserIn]
• Titel: A knowledge-based quantitative approach to characterize treatment plan quality
• Titelzusatz: application to prostate VMAT planning
• Verf.angabe: Buthayna Alnaalwa, Obioma Nwankwo, Yasser Abo-Madyan, Frank A. Giordano, Frederik Wenz, Gerhard Glatting
• Jahr: 2021
• Umfang: 11 S.
• Fussnoten: 29 October 2020 ; Gesehen am 07.07.2021
• Titel Quelle: Enthalten in: Medical physics
• Ort Quelle: Hoboken, NJ : Wiley, 1974
• Jahr Quelle: 2021
• Band/Heft Quelle: 48(2021), 1, Seite 94-104
• ISSN Quelle: 2473-4209
• ISSN Quelle: 1522-8541
• DOI: doi:10.1002/mp.14564
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: knowledge-based radiation therapy treatment planning
• Sach-SW: OARs dose sparing
• Sach-SW: quantitative quality control algorithm
• Sach-SW: VMAT treatment plans re-optimization
• K10plus-PPN: 1762335530
• K10plus-PPN:
  Universitätsbibliothek
• Lokale URL UB: Zum Volltext

Abstract

Purpose To characterize treatment plan (TP) quality, a quantitative quality control (QC) tool is proposed. The tool is validated using volumetric modulated arc therapy (VMAT) plans for treatment of prostate cancer by estimating the achievable organ at risk (OAR) sparing, based on the knowledge learned from prior plans. Methods Prostate TP quality was investigated by evaluating the achieved OAR sparing in the rectum and bladder, based on their proximity to target surface. The knowledge base used in this work comprises 450 plans, consisting of 181 homogenous prostate plans and 269 simultaneous integrated boost (SIB) prostate plans. A knowledge-based algorithm was used to relate the absorbed doses of the OARs (rectum and bladder) and their proximity to the planning target volume (PTV). A metric (Mq,r value) was calculated to characterize the OAR sparing based on the weighted differences of the mean doses at binned distances to the PTV surface. The 90% probability ellipse of the normally distributed OARs Mq,r values was considered to define a threshold above which the treatment plan was re-optimized. Results Following re-optimization, 8/11 of the homogenous plans and 6/13 of the SIB plans outside the 90% probability ellipse could be re-optimized to gain better OAR sparing while achieving the same or better target coverage. However, 3/4 of the homogenous TPs and 1/9 of the SIB TPs between 80% and 90% were improved. Mq,r values of bladder and rectum after re-optimizing the plans in both groups of homogenous and SIB showed lower values compared to the corresponding values before re-optimization, which implies that better OARs sparing was achieved. Conclusions This work demonstrates an effective anatomy-specific QC tool for identifying suboptimal plans and determining the achievable OAR sparing for each individual patient anatomy.