title: Interfractional target variations for partial breast irradiation.
abstract: OBJECTIVE
  In this work, we quantify the interfractional variations in the shape of the clinical target volume (CTV) by analyzing the daily CT data acquired during CT-guided partial breast irradiation (PBI) and compare the effectiveness of various repositioning alignment strategies considered to account for the variations.
  
  
  METHODS
  The daily CT data for 13 breast cancer patients treated with PBI in either prone (10 patients) or supine (3 patients) with daily kV CT guidance using CT on Rails (CTVision, Siemens, Malvern, PA) were analyzed. For approximately 25 points on the surface of the CTV, deformation vectors were calculated by means of deformable image registration and verified by visual inspection. These were used to calculate the distances along surface normals (DSN), which directly related to the required margin expansions for each point. The DSN values were determined for seven alignment methods based on volumetric imaging and also two-dimensional projections (portal imaging).
  
  
  RESULTS
  The margin expansion necessary to cover 99% of all points for all days was 2.7 mm when utilizing the alignment method based on deformation field data (the best alignment method). The center-of-mass based alignment yielded slightly worse results (a margin of 4.0 mm), and shifts obtained by operator placement (7.9 mm), two-dimensional-based methods (7.0-10.1 mm), and skin marks (13.9 mm) required even larger margin expansions. Target shrinkage was evident for most days by the negative values of DSN. Even with the best alignment, the range of DSN values could be as high as 7 mm, resulting in a large amount of normal tissue irradiation, unless adaptive replanning is employed.
  
  
  CONCLUSIONS
  The appropriate alignment method is important to minimize the margin requirement to cover the significant interfractional target deformations observed during PBI. The amount of normal tissue unnecessarily irradiated is still not insignificant, and can be minimized if adaptive radiotherapy is applied.
authors.affiliation: Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI, USA. eahunbay@mcw.edu
authors.forename: Ergun E
authors.initials: EE
authors.lastname: Ahunbay
authors.forename: Jared
authors.initials: J
authors.lastname: Robbins
authors.forename: Robert
authors.initials: R
authors.lastname: Christian
authors.forename: Andrew
authors.initials: A
authors.lastname: Godley
authors.forename: Julia
authors.initials: J
authors.lastname: White
authors.forename: X Allen
authors.initials: XA
authors.lastname: Li
mesh_terms: D059925:Anatomic Landmarks / Q000000981:diagnostic imaging; D001943:Breast Neoplasms / Q000000981:diagnostic imaging* / Q000532:radiotherapy* / Q000601:surgery; D019583:Dose Fractionation, Radiation; D005260:Female; D006801:Humans; D015412:Mastectomy, Segmental; D009068:Movement; D058958:Organs at Risk / Q000000981:diagnostic imaging / Q000528:radiation effects; D056888:Patient Positioning; D018787:Radiation Oncology / Q000379:methods; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D061106:Radiotherapy Setup Errors; D061089:Radiotherapy, Image-Guided / Q000379:methods*; D012189:Retrospective Studies; D014057:Tomography, X-Ray Computed / Q000379:methods*; D047368:Tumor Burden