PURPOSE: To compare the quality of volumetric modulated arc therapy (VMAT) or intensity-modulated radiation therapy (IMRT) plans generated by an automated inverse planning system with that of dosimetrist-generated IMRT treatment plans for patients with stage III lung cancer. METHODS AND MATERIALS: Two groups of 8 patients with stage III lung cancer were randomly selected. For group 1, the dosimetrists spent their best effort in designing IMRT plans to compete with the automated inverse planning system (mdaccAutoPlan); for group 2, the dosimetrists were not in competition and spent their regular effort. Five experienced radiation oncologists independently blind-reviewed and ranked the three plans for each patient: a rank of 1 was the best and 3 was the worst. Dosimetric measures were also performed to quantitatively evaluate the three types of plans. RESULTS: Blind rankings from different oncologists were generally consistent. For group 1, the auto-VMAT, auto-IMRT, and manual IMRT plans received average ranks of 1.6, 2.13, and 2.18, respectively. The auto-VMAT plans in group 1 had 10% higher planning tumor volume (PTV) conformality and 24% lower esophagus V70 (the volume receiving 70 Gy or more) than the manual IMRT plans; they also resulted in more than 20% higher complication-free tumor control probability (P+) than either type of IMRT plans. The auto- and manual IMRT plans in this group yielded generally comparable dosimetric measures. For group 2, the auto-VMAT, auto-IMRT, and manual IMRT plans received average ranks of 1.55, 1.75, and 2.75, respectively. Compared to the manual IMRT plans in this group, the auto-VMAT plans and auto-IMRT plans showed, respectively, 17% and 14% higher PTV dose conformality, 8% and 17% lower mean lung dose, 17% and 26% lower mean heart dose, and 36% and 23% higher P+. CONCLUSIONS: mdaccAutoPlan is capable of generating high-quality VMAT and IMRT treatment plans for stage III lung cancer. Manual IMRT plans could achieve quality similar to auto-IMRT plans if best effort was spent.
PURPOSE: To compare the quality of volumetric modulated arc therapy (VMAT) or intensity-modulated radiation therapy (IMRT) plans generated by an automated inverse planning system with that of dosimetrist-generated IMRT treatment plans for patients with stage III lung cancer. METHODS AND MATERIALS: Two groups of 8 patients with stage III lung cancer were randomly selected. For group 1, the dosimetrists spent their best effort in designing IMRT plans to compete with the automated inverse planning system (mdaccAutoPlan); for group 2, the dosimetrists were not in competition and spent their regular effort. Five experienced radiation oncologists independently blind-reviewed and ranked the three plans for each patient: a rank of 1 was the best and 3 was the worst. Dosimetric measures were also performed to quantitatively evaluate the three types of plans. RESULTS: Blind rankings from different oncologists were generally consistent. For group 1, the auto-VMAT, auto-IMRT, and manual IMRT plans received average ranks of 1.6, 2.13, and 2.18, respectively. The auto-VMAT plans in group 1 had 10% higher planning tumor volume (PTV) conformality and 24% lower esophagus V70 (the volume receiving 70 Gy or more) than the manual IMRT plans; they also resulted in more than 20% higher complication-free tumor control probability (P+) than either type of IMRT plans. The auto- and manual IMRT plans in this group yielded generally comparable dosimetric measures. For group 2, the auto-VMAT, auto-IMRT, and manual IMRT plans received average ranks of 1.55, 1.75, and 2.75, respectively. Compared to the manual IMRT plans in this group, the auto-VMAT plans and auto-IMRT plans showed, respectively, 17% and 14% higher PTV dose conformality, 8% and 17% lower mean lung dose, 17% and 26% lower mean heart dose, and 36% and 23% higher P+. CONCLUSIONS: mdaccAutoPlan is capable of generating high-quality VMAT and IMRT treatment plans for stage III lung cancer. Manual IMRT plans could achieve quality similar to auto-IMRT plans if best effort was spent.
Authors: David Palma; Emily Vollans; Kerry James; Sandy Nakano; Vitali Moiseenko; Richard Shaffer; Michael McKenzie; James Morris; Karl Otto Journal: Int J Radiat Oncol Biol Phys Date: 2008-05-01 Impact factor: 7.038
Authors: Carmen C Popescu; Ivo A Olivotto; Wayne A Beckham; Will Ansbacher; Sergei Zavgorodni; Richard Shaffer; Elaine S Wai; Karl Otto Journal: Int J Radiat Oncol Biol Phys Date: 2010-01-01 Impact factor: 7.038
Authors: Wilko F A R Verbakel; Johan P Cuijpers; Daan Hoffmans; Michael Bieker; Ben J Slotman; Suresh Senan Journal: Int J Radiat Oncol Biol Phys Date: 2009-05-01 Impact factor: 7.038
Authors: Nilesh S Tambe; Isabel M Pires; Craig Moore; Christopher Cawthorne; Andrew W Beavis Journal: Br J Radiol Date: 2020-01-06 Impact factor: 3.039
Authors: Jim P Tol; Max Dahele; Jarkko Peltola; Janne Nord; Ben J Slotman; Wilko F A R Verbakel Journal: Radiat Oncol Date: 2015-04-01 Impact factor: 3.481
Authors: Abdul Wahab M Sharfo; Sebastiaan Breedveld; Peter W J Voet; Sabrina T Heijkoop; Jan-Willem M Mens; Mischa S Hoogeman; Ben J M Heijmen Journal: PLoS One Date: 2016-12-29 Impact factor: 3.240
Authors: Giuseppe Della Gala; Maarten L P Dirkx; Nienke Hoekstra; Dennie Fransen; Nico Lanconelli; Marjan van de Pol; Ben J M Heijmen; Steven F Petit Journal: Strahlenther Onkol Date: 2017-03-17 Impact factor: 3.621