PURPOSE: To develop a knowledge-based planning (KBP) routine for stereotactic body radiotherapy (SBRT) of peripherally located early-stage non-small-cell lung cancer (NSCLC) tumors via dynamic conformal arc (DCA)-based volumetric modulated arc therapy (VMAT) using the commercially available RapidPlanTM software. This proposed technique potentially improves plan quality, reduces complexity, and minimizes interplay effect and small-field dosimetry errors associated with treatment delivery. METHODS: KBP model was developed and validated using 70 clinically treated high quality non-coplanar VMAT lung SBRT plans for training and 20 independent plans for validation. All patients were treated with 54 Gy in three treatments. Additionally, a novel k-DCA planning routine was deployed to create plans incorporating historical three-dimensional-conformal SBRT planning practices via DCA-based approach prior to VMAT optimization in an automated planning engine. Conventional KBPs and k-DCA plans were compared with clinically treated plans per RTOG-0618 requirements for target conformity, tumor dose heterogeneity, intermediate dose fall-off and organs-at-risk (OAR) sparing. Treatment planning time, treatment delivery efficiency, and accuracy were recorded. RESULTS: KBPs and k-DCA plans were similar or better than clinical plans. Average planning target volume for validation was 22.4 ± 14.1 cc (7.1-62.3 cc). KBPs and k-DCA plans provided similar conformity to clinical plans with average absolute differences of 0.01 and 0.01, respectively. Maximal doses to OAR were lowered in both KBPs and k-DCA plans. KBPs increased monitor units (MU) on average 1316 (P < 0.001) while k-DCA reduced total MU on average by 1114 (P < 0.001). This routine can create k-DCA plan in less than 30 min. Independent Monte Carlo calculation demonstrated that k-DCA plans showed better agreement with planned dose distribution. CONCLUSION: A k-DCA planning routine was developed in concurrence with a knowledge-based approach for the treatment of peripherally located lung tumors. This method minimizes plan complexity associated with model-based KBP techniques and improve plan quality and treatment planning efficiency.
PURPOSE: To develop a knowledge-based planning (KBP) routine for stereotactic body radiotherapy (SBRT) of peripherally located early-stage non-small-cell lung cancer (NSCLC) tumors via dynamic conformal arc (DCA)-based volumetric modulated arc therapy (VMAT) using the commercially available RapidPlanTM software. This proposed technique potentially improves plan quality, reduces complexity, and minimizes interplay effect and small-field dosimetry errors associated with treatment delivery. METHODS: KBP model was developed and validated using 70 clinically treated high quality non-coplanar VMAT lung SBRT plans for training and 20 independent plans for validation. All patients were treated with 54 Gy in three treatments. Additionally, a novel k-DCA planning routine was deployed to create plans incorporating historical three-dimensional-conformal SBRT planning practices via DCA-based approach prior to VMAT optimization in an automated planning engine. Conventional KBPs and k-DCA plans were compared with clinically treated plans per RTOG-0618 requirements for target conformity, tumor dose heterogeneity, intermediate dose fall-off and organs-at-risk (OAR) sparing. Treatment planning time, treatment delivery efficiency, and accuracy were recorded. RESULTS: KBPs and k-DCA plans were similar or better than clinical plans. Average planning target volume for validation was 22.4 ± 14.1 cc (7.1-62.3 cc). KBPs and k-DCA plans provided similar conformity to clinical plans with average absolute differences of 0.01 and 0.01, respectively. Maximal doses to OAR were lowered in both KBPs and k-DCA plans. KBPs increased monitor units (MU) on average 1316 (P < 0.001) while k-DCA reduced total MU on average by 1114 (P < 0.001). This routine can create k-DCA plan in less than 30 min. Independent Monte Carlo calculation demonstrated that k-DCA plans showed better agreement with planned dose distribution. CONCLUSION: A k-DCA planning routine was developed in concurrence with a knowledge-based approach for the treatment of peripherally located lung tumors. This method minimizes plan complexity associated with model-based KBP techniques and improve plan quality and treatment planning efficiency.
Authors: Stanley H Benedict; Kamil M Yenice; David Followill; James M Galvin; William Hinson; Brian Kavanagh; Paul Keall; Michael Lovelock; Sanford Meeks; Lech Papiez; Thomas Purdie; Ramaswamy Sadagopan; Michael C Schell; Bill Salter; David J Schlesinger; Almon S Shiu; Timothy Solberg; Danny Y Song; Volker Stieber; Robert Timmerman; Wolfgang A Tomé; Dirk Verellen; Lu Wang; Fang-Fang Yin Journal: Med Phys Date: 2010-08 Impact factor: 4.071
Authors: Saar Van't Hof; Alexander R Delaney; Hilâl Tekatli; Jos Twisk; Ben J Slotman; Suresh Senan; Max Dahele; Wilko F A R Verbakel Journal: Int J Radiat Oncol Biol Phys Date: 2018-08-14 Impact factor: 7.038
Authors: Lydia L Handsfield; Ryan Jones; David D Wilson; Jeffery V Siebers; Paul W Read; Quan Chen Journal: Med Phys Date: 2014-10 Impact factor: 4.071
Authors: Kelly C Younge; Robin B Marsh; Dawn Owen; Huaizhi Geng; Ying Xiao; Daniel E Spratt; Joseph Foy; Krithika Suresh; Q Jackie Wu; Fang-Fang Yin; Samuel Ryu; Martha M Matuszak Journal: Int J Radiat Oncol Biol Phys Date: 2018-01-04 Impact factor: 7.038
Authors: A Fogliata; G Reggiori; A Stravato; F Lobefalo; C Franzese; D Franceschini; S Tomatis; P Mancosu; M Scorsetti; L Cozzi Journal: Radiat Oncol Date: 2017-04-27 Impact factor: 3.481
Authors: Ying Xiao; Stephen F Kry; Richard Popple; Ellen Yorke; Niko Papanikolaou; Sotirios Stathakis; Ping Xia; Saiful Huq; John Bayouth; James Galvin; Fang-Fang Yin Journal: J Appl Clin Med Phys Date: 2015-05-08 Impact factor: 2.102
Authors: Damodar Pokhrel; Lana Sanford; Bhaswanth Dhanireddy; Janelle Molloy; Marcus Randall; Ronald C McGarry Journal: J Appl Clin Med Phys Date: 2020-02-10 Impact factor: 2.102