title: Validation of a dose warping algorithm using clinically realistic scenarios.
abstract: OBJECTIVE
  Dose warping following deformable image registration (DIR) has been proposed for interfractional dose accumulation. Robust evaluation workflows are vital to clinically implement such procedures. This study demonstrates such a workflow and quantifies the accuracy of a commercial DIR algorithm for this purpose under clinically realistic scenarios.
  
  
  METHODS
  12 head and neck (H&N) patient data sets were used for this retrospective study. For each case, four clinically relevant anatomical changes have been manually generated. Dose distributions were then calculated on each artificially deformed image and warped back to the original anatomy following DIR by a commercial algorithm. Spatial registration was evaluated by quantitative comparison of the original and warped structure sets, using conformity index and mean distance to conformity (MDC) metrics. Dosimetric evaluation was performed by quantitative comparison of the dose-volume histograms generated for the calculated and warped dose distributions, which should be identical for the ideal "perfect" registration of mass-conserving deformations.
  
  
  RESULTS
  Spatial registration of the artificially deformed image back to the planning CT was accurate (MDC range of 1-2 voxels or 1.2-2.4 mm). Dosimetric discrepancies introduced by the DIR were low (0.02 ± 0.03 Gy per fraction in clinically relevant dose metrics) with no statistically significant difference found (Wilcoxon test, 0.6 ≥ p ≥ 0.2).
  
  
  CONCLUSIONS
  The reliability of CT-to-CT DIR-based dose warping and image registration was demonstrated for a commercial algorithm with H&N patient data.
  
  
  CONCLUSIONS
  This study demonstrates a workflow for validation of dose warping following DIR that could assist physicists and physicians in quantifying the uncertainties associated with dose accumulation in clinical scenarios.
authors: 1 School of Computer Sciences, University of Birmingham, Edgbaston, Birmingham, UK.
authors: Y G
authors: YG
authors: Roussakis
authors: H
authors: H
authors: Dehghani
authors: S
authors: S
authors: Green
authors: G J
authors: GJ
authors: Webster
mesh_terms: D000465:Algorithms; D006258:Head and Neck Neoplasms / Q000532:radiotherapy*; D009010:Monte Carlo Method; D011874:Radiometry / Q000379:methods; D011879:Radiotherapy Dosage / Q000592:standards*; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods; D015203:Reproducibility of Results; D012189:Retrospective Studies; D014057:Tomography, X-Ray Computed; D057188:Workflow