title: Four-dimensional radiotherapy planning for DMLC-based respiratory motion tracking.
abstract: Four-dimensional (4D) radiotherapy is the explicit inclusion of the temporal changes in anatomy during the imaging, planning, and delivery of radiotherapy. Temporal anatomic changes can occur for many reasons, though the focus of the current investigation is respiration motion for lung tumors. The aim of this study was to develop 4D radiotherapy treatment-planning methodology for DMLC-based respiratory motion tracking. A 4D computed tomography (CT) scan consisting of a series of eight 3D CT image sets acquired at different respiratory phases was used for treatment planning. Deformable image registration was performed to map each CT set from the peak-inhale respiration phase to the CT image sets corresponding to subsequent respiration phases. Deformable registration allows the contours defined on the peak-inhale CT to be automatically transferred to the other respiratory phase CT image sets. Treatment planning was simultaneously performed on each of the eight 3D image sets via automated scripts in which the MLC-defined beam aperture conforms to the PTV (which in this case equaled the GTV due to CT scan length limitations) plus a penumbral margin at each respiratory phase. The dose distribution from each respiratory phase CT image set was mapped back to the peak-inhale CT image set for analysis. The treatment intent of 4D planning is that the radiation beam defined by the DMLC tracks the respiration-induced target motion based on a feedback loop including the respiration signal to a real-time MLC controller. Deformation with respiration was observed for the lung tumor and normal tissues. This deformation was verified by examining the mapping of high contrast objects, such as the lungs and cord, between image sets. For the test case, dosimetric reductions for the cord, heart, and lungs were found for 4D planning compared with 3D planning. 4D radiotherapy planning for DMLC-based respiratory motion tracking is feasible and may offer tumor dose escalation and/or a reduction in treatment-related complications. However, 4D planning requires new planning tools, such as deformable registration and automated treatment planning on multiple CT image sets.
authors.affiliation: Department of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia 23298, USA. pjkeall@vcu.edu
authors.forename: Paul J
authors.initials: PJ
authors.lastname: Keall
authors.forename: Sarang
authors.initials: S
authors.lastname: Joshi
authors.forename: S Sastry
authors.initials: SS
authors.lastname: Vedam
authors.forename: Jeffrey V
authors.initials: JV
authors.lastname: Siebers
authors.forename: Vijaykumar R
authors.initials: VR
authors.lastname: Kini
authors.forename: Radhe
authors.initials: R
authors.lastname: Mohan
mesh_terms: D004307:Dose-Response Relationship, Radiation; D006801:Humans; D007091:Image Processing, Computer-Assisted; D021621:Imaging, Three-Dimensional; D008175:Lung Neoplasms / Q000473:pathology / Q000532:radiotherapy*; D009038:Motion; D009068:Movement; D011857:Radiographic Image Interpretation, Computer-Assisted; D013902:Radiography, Thoracic / Q000379:methods; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods; D011881:Radiotherapy, Computer-Assisted; D020266:Radiotherapy, Conformal / Q000379:methods*; D012119:Respiration; D013997:Time Factors; D014057:Tomography, X-Ray Computed