Validation of deformable image registration algorithms on CT images of ex vivo porcine bladders with fiducial markers

• Published in: Medical physics (Lancaster) 2014-07, Vol.41 (7), p.071916-n/a
• Main Authors: Wognum, S., Heethuis, S. E., Rosario, T., Hoogeman, M. S., Bel, A.
• Format: Article
• Language: English
• Subjects: 60 APPLIED LIFE SCIENCES; ACCURACY; ALGORITHMS; Animals; Biological material, e.g. blood, urine; Haemocytometers; BLADDER; Cancer; CAT SCANNING; Computed tomography; Computerised tomographs; computerised tomography; Contrast; CONTRAST MEDIA; deformable image registration; deformation; Digital computing or data processing equipment or methods, specially adapted for specific applications; Dosimetry; Fiducial Markers; Flow visualization; Image data processing or generation, in general; IMAGE PROCESSING; image registration; Medical image contrast; medical image processing; Models, Biological; organ deformation; pelvic radiotherapy; PHANTOMS; Phantoms, Imaging; physiological bladder phantom; radiation therapy; RADIOLOGY AND NUCLEAR MEDICINE; RADIOTHERAPY; Registration; Software; software packages; Spatial dimensions; Surface structure; Swine; Therapeutic applications, including brachytherapy; Tomography, X-Ray Computed - instrumentation; Tomography, X-Ray Computed - methods; Urinary Bladder - diagnostic imaging; Urinary Bladder - physiology; VALIDATION; Water
• ISSN: 0094-2405; 2473-4209
• DOI: 10.1118/1.4883839

Purpose: The spatial accuracy of deformable image registration (DIR) is important in the implementation of image guided adaptive radiotherapy techniques for cancer in the pelvic region. Validation of algorithms is best performed on phantoms with fiducial markers undergoing controlled large deformations. Excised porcine bladders, exhibiting similar filling and voiding behavior as human bladders, provide such an environment. The aim of this study was to determine the spatial accuracy of different DIR algorithms on CT images ofex vivo porcine bladders with radiopaque fiducial markers applied to the outer surface, for a range of bladder volumes, using various accuracy metrics. Methods: Five excised porcine bladders with a grid of 30–40 radiopaque fiducial markers attached to the outer wall were suspended inside a water‐filled phantom. The bladder was filled with a controlled amount of water with added contrast medium for a range of filling volumes (100–400 ml in steps of 50 ml) using a luer lock syringe, and CT scans were acquired at each filling volume. DIR was performed for each data set, with the 100 ml bladder as the reference image. Six intensity‐based algorithms (optical flow or demons‐based) implemented in theMATLAB platform DIRART, a b‐spline algorithm implemented in the commercial software package VelocityAI, and a structure‐based algorithm (Symmetric Thin Plate Spline Robust Point Matching) were validated, using adequate parameter settings according to values previously published. The resulting deformation vector field from each registration was applied to the contoured bladder structures and to the marker coordinates for spatial error calculation. The quality of the algorithms was assessed by comparing the different error metrics across the different algorithms, and by comparing the effect of deformation magnitude (bladder volume difference) per algorithm, using the Independent Samples Kruskal‐Wallis test. Results: The authors found good structure accuracy without dependency on bladder volume difference for all but one algorithm, and with the best result for the structure‐based algorithm. Spatial accuracy as assessed from marker errors was disappointing for all algorithms, especially for large volume differences, implying that the deformations described by the registration did not represent anatomically correct deformations. The structure‐based algorithm performed the best in terms of marker error for the large volume difference (100–400 ml). In gen