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

• Published in: Medical physics (Lancaster) 2015-01, Vol.42 (1), p.391-399
• Main Authors: Cunliffe, Alexandra R., Contee, Clay, Armato, Samuel G., White, Bradley, Justusson, Julia, Malik, Renuka, Al‐Hallaq, Hania A.
• Format: Article
• Language: English
• Subjects: 60 APPLIED LIFE SCIENCES; Aged; ALGORITHMS; Biological material, e.g. blood, urine; Haemocytometers; cancer; Carcinoma, Non-Small-Cell Lung - diagnostic imaging; Carcinoma, Non-Small-Cell Lung - radiotherapy; CAT SCANNING; Combined Modality Therapy; Computed tomography; Computerised tomographs; computerised tomography; deformable registration; Digital computing or data processing equipment or methods, specially adapted for specific applications; dose difference; Dose‐volume analysis; dosimetry; Female; Humans; Image data processing or generation, in general; image registration; lung; Lung - diagnostic imaging; Lung - radiation effects; LUNGS; Male; medical image processing; Medical imaging; Medical treatment planning; Middle Aged; NEOPLASMS; PATIENTS; Pattern Recognition, Automated; Photons - therapeutic use; PLANNING; RADIATION DOSES; Radiation Imaging Physics; radiation therapy; Radiation treatment; RADIOTHERAPY; Radiotherapy Dosage; Radiotherapy Planning, Computer-Assisted - methods; Radiotherapy, Conformal - methods; Regression Analysis; Researchers; Retrospective Studies; Scintigraphy; Small Cell Lung Carcinoma - diagnostic imaging; Small Cell Lung Carcinoma - radiotherapy; Tissues; Tomography, X-Ray Computed - methods; User-Computer Interface
• ISSN: 0094-2405; 2473-4209
• DOI: 10.1118/1.4903267

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