title: Development and evaluation of a clinical model for lung cancer patients using stereotactic body radiotherapy (SBRT) within a knowledge-based algorithm for treatment planning.
abstract: The purpose of this study was to describe the development of a clinical model for lung cancer patients treated with stereotactic body radiotherapy (SBRT) within a knowledge-based algorithm for treatment planning, and to evaluate the model performance and applicability to different planning techniques, tumor locations, and beam arrangements. 105 SBRT plans for lung cancer patients previously treated at our institution were included in the development of the knowledge-based model (KBM). The KBM was trained with a combination of IMRT, VMAT, and 3D CRT techniques. Model performance was validated with 25 cases, for both IMRT and VMAT. The full KBM encompassed lesions located centrally vs. peripherally (43:62), upper vs. lower (62:43), and anterior vs. posterior (60:45). Four separate sub-KBMs were created based on tumor location. Results were compared with the full KBM to evaluate its robustness. Beam templates were used in conjunction with the optimizer to evaluate the model's ability to handle suboptimal beam placements. Dose differences to organs-at-risk (OAR) were evaluated between the plans gener-ated by each KBM. Knowledge-based plans (KBPs) were comparable to clinical plans with respect to target conformity and OAR doses. The KBPs resulted in a lower maximum spinal cord dose by 1.0 ± 1.6 Gy compared to clinical plans, p = 0.007. Sub-KBMs split according to tumor location did not produce significantly better DVH estimates compared to the full KBM. For central lesions, compared to the full KBM, the peripheral sub-KBM resulted in lower dose to 0.035 cc and 5 cc of the esophagus, both by 0.4Gy ± 0.8Gy, p = 0.025. For all lesions, compared to the full KBM, the posterior sub-KBM resulted in higher dose to 0.035 cc, 0.35 cc, and 1.2 cc of the spinal cord by 0.2 ± 0.4Gy, p = 0.01. Plans using template beam arrangements met target and OAR criteria, with an increase noted in maximum heart dose (1.2 ± 2.2Gy, p = 0.01) and GI (0.2 ± 0.4, p = 0.01) for the nine-field plans relative to KBPs planned with custom beam angles. A knowledge-based model for lung SBRT consisting of multiple treatment modalities and lesion loca-tions produced comparable plan quality to clinical plans. With proper training and validation, a robust KBM can be created that encompasses both IMRT and VMAT techniques, as well as different lesion locations.
authors.affiliation: Henry Ford Health System. ksnyder2@hfhs.org.
authors.forename: Karen
authors.initials: K
authors.lastname: Chin Snyder
authors.forename: Jinkoo
authors.initials: J
authors.lastname: Kim
authors.forename: Anne
authors.initials: A
authors.lastname: Reding
authors.forename: Corey
authors.initials: C
authors.lastname: Fraser
authors.forename: James
authors.initials: J
authors.lastname: Gordon
authors.forename: Munther
authors.initials: M
authors.lastname: Ajlouni
authors.forename: Benjamin
authors.initials: B
authors.lastname: Movsas
authors.forename: Indrin J
authors.initials: IJ
authors.lastname: Chetty
mesh_terms: D000465:Algorithms; D006801:Humans; D051188:Knowledge Bases; D008175:Lung Neoplasms / Q000601:surgery*; D008954:Models, Biological; D058958:Organs at Risk / Q000528:radiation effects*; D016634:Radiosurgery / Q000379:methods*; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D050397:Radiotherapy, Intensity-Modulated / Q000379:methods*