Effect of deformable registration on the dose calculated in radiation therapy planning CT scans of lung cancer patients a)

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Abstract
Purpose: To characterize the effects of deformable image registration of serial computed tomography (CT) scans on the radiation dose calculated from a treatment planning scan.Methods: Eighteen patients who received curative doses (≥60 Gy, 2 Gy/fraction) of photon radiation therapy for lung cancer treatment were retrospectively identified. For each patient, a diagnostic‐quality pretherapy (4–75 days) CT scan and a treatment planning scan with an associated dose map were collected. To establish correspondence between scan pairs, a researcher manually identified anatomically corresponding landmark point pairs between the two scans. Pretherapy scans then were coregistered with planning scans (and associated dose maps) using the demons deformable registration algorithm and two variants of the Fraunhofer MEVIS algorithm (“Fast” and “EMPIRE10”). Landmark points in each pretherapy scan were automatically mapped to the planning scan using the displacement vector field output from each of the three algorithms. The Euclidean distance between manually and automatically mapped landmark points (dE) and the absolute difference in planned dose (|ΔD|) were calculated. Using regression modeling, |ΔD| was modeled as a function of dE, dose (D), dose standard deviation (SDdose) in an eight‐pixel neighborhood, and the registration algorithm used.Results: Over 1400 landmark point pairs were identified, with 58–93 (median: 84) points identified per patient. Average |ΔD| across patients was 3.5 Gy (range: 0.9–10.6 Gy). Registration accuracy was highest using the Fraunhofer MEVIS EMPIRE10 algorithm, with an average dE across patients of 5.2 mm (compared with >7 mm for the other two algorithms). Consequently, average |ΔD| was also lowest using the Fraunhofer MEVIS EMPIRE10 algorithm. |ΔD| increased significantly as a function of dE (0.42 Gy/mm), D (0.05 Gy/Gy), SDdose (1.4 Gy/Gy), and the algorithm used (≤1 Gy).Conclusions: An average error of dose). This model provides a measurement of the uncertainty in the radiation dose when points are mapped between serial CT scans through deformable registration.
Funding Information
  • 2013 AAPM Minority Undergraduate Summer Experience Fellowship
  • National Institutes of Health (P30 CA14599)
  • National Institutes of Health (S10 RR021039)
  • National Institutes of Health (T32 EB002103)
  • Virginia and D.K. Ludwig Fund for Cancer Research, The University of Chicago
  • National Science Foundation (NSF) (REU Award No. 1062909)
  • National Institutes of Health (P30 CA14599)
  • National Institutes of Health (S10 RR021039)
  • National Institutes of Health (T32 EB002103)
  • Virginia and D.K. Ludwig Fund for Cancer Research
  • National Science Foundation (REU Award No. 1062909)
  • 2013 AAPM Minority Undergraduate Summer Experience Fellowship
  • National Institutes of Health (P30 CA14599, S10 RR021039, T32 EB002103)
  • Virginia and D.K. Ludwig Fund for Cancer Research
  • National Science Foundation (REU Award No. 1062909)

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