O20. Full automation of radiation therapy treatment planning. (September 2016)

• Record Type: Journal Article
• Authors: Court, L.; McCarroll, R.; Kisling, K.; Zhang, L.; Yang, J.; Jhingran, A.; Balter, P.; Simonds, H.; du Toit, M.; Mejia, M.; Beadle, B.
• Is Part Of: Physica medica. Volume 32(2016)Supplement 2
• Page Start: 147
• Publication Date: 2016-09
• Subjects: Medical physics -- Periodicals; Biophysics -- Periodicals; Biophysics -- Periodicals; Imagerie médicale -- Périodiques; Radiothérapie -- Périodiques; Rayons X -- Sécurité -- Mesures -- Périodiques; Physique -- Périodiques; Médecine -- Périodiques; 610.153
• DOI: 10.1016/j.ejmp.2016.07.028
• Languages: English
• ISSNs: 1120-1797

Abstract

Abstract : Introduction: We are using the Eclipse Application Programming Interface (API) and Mobius 3D QA system, together with in-house code, to develop an automated treatment planning system for cervix, breast (and chest wall), and head/neck cancers. The goal is to develop a system that includes multiple layers of internal QA that can be used by junior staff. Materials and methods: Currently, the following preparatory steps have been fully automated: isocenter detection, couch removal, and body segmentation. For head and neck treatments, the normal tissue segmentation has been automated using an in-house algorithm, and the results scored by a radiation oncologist on 118 patients. For 4-field box cervical cancer treatments, two independent approaches have been developed to create the field apertures (jaw and MLC positions): (1) Atlas-based segmentation of bony anatomy on the patient's CT, then calculation of apertures based on the projection of these bones to each beam's-eye-view; (2) Deformably register atlas DRRs to the patient's DRR for each beam, then use the deformation matrix to deform atlas blocks (MLC positions) to the patient's DRR. These methods were tested on 39 patients, and the results scored by a radiation oncologist. Finished treatment plans (all sites) are automatically sent to Mobius to verify the dose calculation, and all parameters (MU, etc.) compared with population ranges. Results: Head/neck auto contouring takes ∼15 minutes. For cord, brainstem, brain, parotid and mandible, auto-contours were scored acceptable, except for situations when the head position was non-standard. Esophagus and cochlea were generally close, but will require margins before use as a planning avoidance structures. For cervical cancer 4-field box treatments, method 1 was scored as acceptable for 96% of beams, with all failures caused by a slight error in the position of the superior border (10–15 mins per patient). Method 2 was scored as acceptable for 79% of beams, so improvements are needed here before it can be used to verify method 1. Completion of a complete cervical cancer plan, including dose calculation in Eclipse and secondary dose calculation in Mobius takes <30 mins. Conclusions: We report on preliminary results of an automated treatment planning approach. Normal tissue segmentation for head/neck patients is very successful and has been introduced into use at our clinic. Determination of the jaw/MLC positions for 4-field box treatments of cervical cancer is also successful and has been introduced into use in our clinic.