Comprehensive evaluation of ten deformable image registration algorithms for contour propagation between CT and cone-beam CT images in adaptive head & neck radiotherapy

• Published in: PloS one Vol. 12; no. 4; p. e0175906
• Main Authors: Li, Xin, Zhang, Yuyu, Shi, Yinghua, Wu, Shuyu, Xiao, Yang, Gu, Xuejun, Zhen, Xin, Zhou, Linghong
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 17.04.2017; Public Library of Science (PLoS)
• Subjects: Accuracy; Adult; Aged; Algorithms; Analysis; Anatomy; Artificial intelligence; Benchmarks; Biology and Life Sciences; Biomedical engineering; Calculi; Cancer; Cancer therapies; CAT scans; Computed tomography; Computer programs; Cone-Beam Computed Tomography - methods; Conferences; Contours; Convergence; Deformation; Engineering; Engineering and Technology; Evaluation; Female; Formability; Growth hormone; Head; Head & neck cancer; Head - diagnostic imaging; Head and neck cancer; Head and Neck Neoplasms - diagnostic imaging; Health services; Humans; Image acquisition; Image processing; Image Processing, Computer-Assisted - methods; Image registration; Immobilization; Institutions; Lungs; Male; Medical imaging; Medicine and Health Sciences; Metric space; Middle Aged; Neck; Neck - diagnostic imaging; Oncology; Optical flow (image analysis); Organs; Patients; Physical Sciences; Propagation; Quality assurance; Quality control; Radiation; Radiation therapy; Radiographic Image Interpretation, Computer-Assisted - methods; Radiotherapy; Radiotherapy Planning, Computer-Assisted - methods; Radiotherapy, Intensity-Modulated - methods; Registration; Research and Analysis Methods; Salivary glands; Simulation; Spine; Studies; Throat cancer; Tomography; Tumors; Vertebrae
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0175906

Deformable image registration (DIR) is a critical technic in adaptive radiotherapy (ART) for propagating contours between planning computerized tomography (CT) images and treatment CT/cone-beam CT (CBCT) images to account for organ deformation for treatment re-planning. To validate the ability and accuracy of DIR algorithms in organ at risk (OAR) contour mapping, ten intensity-based DIR strategies, which were classified into four categories-optical flow-based, demons-based, level-set-based and spline-based-were tested on planning CT and fractional CBCT images acquired from twenty-one head & neck (H&N) cancer patients who underwent 6~7-week intensity-modulated radiation therapy (IMRT). Three similarity metrics, i.e., the Dice similarity coefficient (DSC), the percentage error (PE) and the Hausdorff distance (HD), were employed to measure the agreement between the propagated contours and the physician-delineated ground truths of four OARs, including the vertebra (VTB), the vertebral foramen (VF), the parotid gland (PG) and the submandibular gland (SMG). It was found that the evaluated DIRs in this work did not necessarily outperform rigid registration. DIR performed better for bony structures than soft-tissue organs, and the DIR performance tended to vary for different ROIs with different degrees of deformation as the treatment proceeded. Generally, the optical flow-based DIR performed best, while the demons-based DIR usually ranked last except for a modified demons-based DISC used for CT-CBCT DIR. These experimental results suggest that the choice of a specific DIR algorithm depends on the image modality, anatomic site, magnitude of deformation and application. Therefore, careful examinations and modifications are required before accepting the auto-propagated contours, especially for automatic re-planning ART systems.