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Effect of deformable registration on the dose calculated in radiation therapy planning CT scans of lung cancer patients a)
Author(s) -
Cunliffe Alexandra R.,
Contee Clay,
Armato Samuel G.,
White Bradley,
Justusson Julia,
Malik Renuka,
AlHallaq Hania A.
Publication year - 2015
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4903267
Subject(s) - image registration , radiation treatment planning , nuclear medicine , landmark , radiation therapy , image guided radiation therapy , computed tomography , medicine , medical imaging , artificial intelligence , computer science , radiology , image (mathematics)
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 ( d E ) and the absolute difference in planned dose (|Δ D |) were calculated. Using regression modeling, |Δ D | was modeled as a function of d E , dose ( D ), dose standard deviation (SD dose ) 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 |Δ D | 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 d E across patients of 5.2 mm (compared with >7 mm for the other two algorithms). Consequently, average |Δ D | was also lowest using the Fraunhofer MEVIS EMPIRE10 algorithm. |Δ D | increased significantly as a function of d E (0.42 Gy/mm), D (0.05 Gy/Gy), SD dose (1.4 Gy/Gy), and the algorithm used (≤1 Gy). Conclusions: An average error of <4 Gy in radiation dose was introduced when points were mapped between CT scan pairs using deformable registration, with the majority of points yielding dose‐mapping error <2 Gy (approximately 3% of the total prescribed dose). Registration accuracy was highest using the Fraunhofer MEVIS EMPIRE10 algorithm, resulting in the smallest errors in mapped dose. Dose differences following registration increased significantly with increasing spatial registration errors, dose, and dose gradient (i.e., SD dose ). This model provides a measurement of the uncertainty in the radiation dose when points are mapped between serial CT scans through deformable registration.