Performance of commercially available deformable image registration platforms for contour propagation using patient-based computational phantoms: A multi-institutional study
机构：[1]Department of Medical Physics, University Hospital “Maggiore della Carita”, Novara, Italy[2]Medical Physics Department, Veneto Institute of Oncology IOV IRCCS, Padua, Italy[3]R&D Department, Tecnologie Avanzate, Turin, Italy[4]Department of Medical Physics, S. Maria Nuova Hospital, Reggio Emilia, Italy[5]Unit of Radiation Research, European Institute of Oncology, Milano, Italy[6]ARNAS-Civico Hospital, Palermo, Italy[7]Department of Medical Physics, “Santa Croce e Carle” Hospital, Cuneo, Italy[8]Medical Physics Department, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Meldola, FC, Italy[9]Department of Diagnostic Imaging, Molecular Imaging, Interventional Radiology and Radiotherapy, Tor Vergata General Hospital,Rome, Italy[10]Medical Physics Unit, Centro Oncologico Fiorentino, Firenze, Italy Radiation Oncology Department, Sichuan Cancer Hospital, Chengdu, China四川省肿瘤医院[11]Medical Physics Department, Veneto Institute of Oncology IOV IRCCS, Padua, Italy[12]Department of Medical Physics, Ospedale Civile Giuseppe Mazzini, Teramo, Italy[13]SC Fisica sanitaria, A.O. Ordine Mauriziano di Torino, Turin, Italy[14]Laboratory of Medical Physics and Expert Systems, Regina Elena National Cancer Institute, Rome, Italy[15]Department of Oncology, University of Turin, Turin, Italy
Purpose: To investigate the performance of various algorithms for deformable image registration (DIR) to propagate regions of interest (ROIs) using multiple commercial platforms. Methods and materials: Thirteen institutions participated in the study with six commercial platforms: RayStation (RaySearch Laboratories, Stockholm, Sweden), MIM (Cleveland, OH, USA), VelocityAI and Smart Adapt (Varian Medical Systems, Palo Alto, CA, USA), Mirada XD (Mirada Medical Ltd, Oxford, UK), and ABAS (Elekta AB, Stockholm, Sweden). The DIR algorithms were tested on synthetic images generated with the ImSimQA package (Oncology Systems Limited, Shrewsbury, UK) by applying two specific Deformation Vector Fields (DVF) to real patient data-sets. Head-and-neck (HN), thorax, and pelvis sites were included. The accuracy of the algorithms was assessed by comparing the DIR-mapped ROIs from each center with those of reference, using the Dice Similarity Coefficient (DSC) and Mean Distance to Conformity (MDC) metrics. Statistical inference on validation results was carried out in order to identify the prognostic factors of DIR performances. Results: DVF intensity, anatomic site and participating center were significant prognostic factors of DIR performances. Sub-voxel accuracy was obtained in the HN by all algorithms. Large errors, with MDC ranging up to 6 mm, were observed in low-contrast regions that underwent significant deformation, such as in the pelvis, or large DVF with strong contrast, such as the clinical tumor volume (CTV) in the lung. Under these conditions, the hybrid DIR algorithms performed significantly better than the free-form intensity based algorithms and resulted robust against intercenter variability. Conclusions: The performances of the systems proved to be site specific, depending on the DVF type and the platforms and the procedures used at the various centers. The pelvis was the most challenging site for most of the algorithms, which failed to achieve sub-voxel accuracy. Improved reproducibility was observed among the centers using the same hybrid registration algorithm. (C) 2017 American Association of Physicists in Medicine
第一作者机构：[1]Department of Medical Physics, University Hospital “Maggiore della Carita”, Novara, Italy
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推荐引用方式(GB/T 7714)：
Loi Gianfranco,Fusella Marco,Lanzi Eleonora,et al.Performance of commercially available deformable image registration platforms for contour propagation using patient-based computational phantoms: A multi-institutional study[J].MEDICAL PHYSICS.2018,45(2):748-757.doi:10.1002/mp.12737.
APA：
Loi, Gianfranco,Fusella, Marco,Lanzi, Eleonora,Cagni, Elisabetta,Garibaldi, Cristina...&Fiandra, Christian.(2018).Performance of commercially available deformable image registration platforms for contour propagation using patient-based computational phantoms: A multi-institutional study.MEDICAL PHYSICS,45,(2)
MLA：
Loi, Gianfranco,et al."Performance of commercially available deformable image registration platforms for contour propagation using patient-based computational phantoms: A multi-institutional study".MEDICAL PHYSICS 45..2(2018):748-757
