title: Utilize target motion to cover clinical target volume (ctv)--a novel and practical treatment planning approach to manage respiratory motion.
abstract: OBJECTIVE
  To use probability density function (PDF) to model motion effects and incorporate this information into treatment planning for lung cancers.
  
  
  METHODS
  PDFs were calculated from the respiratory motion traces of 10 patients. Motion effects were evaluated by convolving static dose distributions with various PDFs. Based on a differential dose prescription with relatively lower dose to the clinical target volume (CTV) than to the gross tumor volume (GTV), two approaches were proposed to incorporate PDFs into treatment planning. The first approach uses the GTV-based internal target volume (ITV) as the planning target volume (PTV) to ensure full dose to the GTV, and utilizes the motion-induced dose gradient to cover the CTV. The second approach employs an inhomogeneous static dose distribution within a minimized PTV to best match the prescription dose gradient.
  
  
  RESULTS
  Motion effects on dose distributions were minimal in the anterior-posterior (AP) and lateral directions: a 10-mm motion only induced about 3% of dose reduction in the peripheral target region. The motion effect was remarkable in the cranial-caudal direction. It varied with the motion amplitude, but tended to be similar for various respiratory patterns. For the first approach, a 10-15 mm motion would adequately cover the CTV (presumed to be 60-70% of the GTV dose) without employing the CTV in planning. For motions < 10-mm, an additional PTV with a margin inversely related to the motion was needed to cover the CTV. The second approach was used for motions > 15-mm. An example of inhomogeneous static dose distribution in a reduced PTV was given, and it showed significant dose reduction in the normal tissue without compromising target coverage.
  
  
  CONCLUSIONS
  Respiratory motion-induced dose gradient can be utilized to cover the CTV and minimize the lung dose without the need for more sophisticated technologies.
authors.affiliation: Department of Radiation Oncology, Henry Ford Hospital, Detroit, MI 48202, USA. jjin1@hfhs.org
authors.forename: Jian-Yue
authors.initials: JY
authors.lastname: Jin
authors.forename: Munther
authors.initials: M
authors.lastname: Ajlouni
authors.forename: Feng-Ming Spring
authors.initials: FM
authors.lastname: Kong
authors.forename: Samuel
authors.initials: S
authors.lastname: Ryu
authors.forename: Indrin J
authors.initials: IJ
authors.lastname: Chetty
authors.forename: Benjamin
authors.initials: B
authors.lastname: Movsas
mesh_terms: D006801:Humans; D008175:Lung Neoplasms / Q000532:radiotherapy*; D009038:Motion; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D012119:Respiration