title: Statistical simulations to estimate motion-inclusive dose-volume histograms for prediction of rectal morbidity following radiotherapy.
abstract: OBJECTIVE
  Internal organ motion over a course of radiotherapy (RT) leads to uncertainties in the actual delivered dose distributions. In studies predicting RT morbidity, the single estimate of the delivered dose provided by the treatment planning computed tomography (pCT) is typically assumed to be representative of the dose distribution throughout the course of RT. In this paper, a simple model for describing organ motion is introduced, and is associated to late rectal morbidity data, with the aim of improving morbidity prediction.
  
  
  METHODS
  Organ motion was described by normally distributed translational motion, with its magnitude characterised by the standard deviation (SD) of this distribution. Simulations of both isotropic and anisotropic (anterior-posterior only) motion patterns were performed, as were random, systematic or combined random and systematic motion. The associations between late rectal morbidity and motion-inclusive delivered dose-volume histograms (dDVHs) were quantified using Spearman's rank correlation coefficient (Rs) in a series of 232 prostate cancer patients, and were compared to the associations obtained with the static/planned DVH (pDVH).
  
  
  RESULTS
  For both isotropic and anisotropic motion, different associations with rectal morbidity were seen with the dDVHs relative to the pDVHs. The differences were most pronounced in the mid-dose region (40-60 Gy). The associations were dependent on the applied motion patterns, with the strongest association with morbidity obtained by applying random motion with an SD in the range 0.2-0.8 cm.
  
  
  CONCLUSIONS
  In this study we have introduced a simple model for describing organ motion occurring during RT. Differing and, for some cases, stronger dose-volume dependencies were found between the motion-inclusive dose distributions and rectal morbidity as compared to the associations with the planned dose distributions. This indicates that rectal organ motion during RT influences the efforts to model the risk of morbidity using planning distributions alone.
authors.affiliation: Department of Oncology and Medical Physics, Aarhus University Hospital, Aarhus, Denmark.
authors.forename: Maria
authors.initials: M
authors.lastname: Thor
authors.forename: Aditya
authors.initials: A
authors.lastname: Apte
authors.forename: Joseph O
authors.initials: JO
authors.lastname: Deasy
authors.forename: Ludvig Paul
authors.initials: LP
authors.lastname: Muren
mesh_terms: D015331:Cohort Studies; D003198:Computer Simulation / Q000706:statistics & numerical data; D004307:Dose-Response Relationship, Radiation; D005500:Follow-Up Studies; D006801:Humans; D008297:Male; D009017:Morbidity; D009038:Motion; D009068:Movement / Q000502:physiology; D058958:Organs at Risk / Q000473:pathology / Q000528:radiation effects; D011379:Prognosis; D011467:Prostate / Q000473:pathology / Q000502:physiology; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology / Q000532:radiotherapy*; D011832:Radiation Injuries / Q000175:diagnosis / Q000453:epidemiology / Q000209:etiology; D011859:Radiography; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods; D020266:Radiotherapy, Conformal / Q000009:adverse effects* / Q000379:methods; D012002:Rectal Diseases / Q000453:epidemiology* / Q000209:etiology; D012007:Rectum / Q000473:pathology / Q000528:radiation effects*; D013223:Statistics as Topic / Q000379:methods*; D047368:Tumor Burden / Q000502:physiology