Multi-body 3D–2D registration for image-guided reduction of pelvic dislocation in orthopaedic trauma surgery. (3rd July 2020)

• Record Type: Journal Article
• Authors: Han, R; Uneri, A; Ketcha, M; Vijayan, R; Sheth, N; Wu, P; Vagdargi, P; Vogt, S; Kleinszig, G; Osgood, G M; Siewerdsen, J H
• Is Part Of: Physics in medicine & biology. Volume 65:Number 13(2020:Jul.)
• Publication Date: 2020-07-03
• Subjects: image-guided surgery -- image registration -- 3D–2D registration -- orthopaedic trauma -- pelvic trauma -- statistical shape model -- fluoroscopy guidance; Biophysics -- Periodicals; Medical physics -- Periodicals; 610.153
• DOI: 10.1088/1361-6560/ab843c
• Languages: English
• ISSNs: 0031-9155

Abstract

Abstract: Surgical reduction of pelvic dislocation is a challenging procedure with poor long-term prognosis if reduction does not accurately restore natural morphology. The procedure often requires long fluoroscopic exposure times and trial-and-error to achieve accurate reduction. We report a method to automatically compute the target pose of dislocated bones in preoperative CT and provide 3D guidance of reduction using routine 2D fluoroscopy. A pelvic statistical shape model (SSM) and a statistical pose model (SPM) were formed from an atlas of 40 pelvic CT images. Multi-body bone segmentation was achieved by mapping the SSM to a preoperative CT via an active shape model. The target reduction pose for the dislocated bone is estimated by fitting the poses of undislocated bones to the SPM. Intraoperatively, multiple bones are registered to fluoroscopy images via 3D–2D registration to obtain 3D pose estimates from 2D images. The method was examined in three studies: (1) a simulation study of 40 CT images simulating a range of dislocation patterns; (2) a pelvic phantom study with controlled dislocation of the left innominate bone; (3) a clinical case study investigating feasibility in images acquired during pelvic reduction surgery. Experiments investigated the accuracy of registration as a function of initialization error (capture range), image quality (radiation dose and image noise), and field of view (FOV) size. The simulation study achieved target pose estimation with translational error of median 2.3 mm (1.4 mm interquartile range, IQR) and rotational error of 2.1° (1.3° IQR). 3D–2D registration yielded 0.3 mm (0.2 mm IQR) in-plane and 0.3 mm (0.2 mm IQR) out-of-plane translational error, with in-plane capture range of ±50 mm and out-of-plane capture range of ±120 mm. The phantom study demonstrated 3D–2D target registration error of 2.5 mm (1.5 mm IQR), and the method was robust over a large dose range, down to 5 μ Gy/frame (an order of magnitude lower than the nominal fluoroscopic dose). The clinical feasibility study demonstrated accurate registration with both preoperative and intraoperative radiographs, yielding 3.1 mm (1.0 mm IQR) projection distance error with robust performance for FOV ranging from 340 × 340 mm 2 to 170 × 170 mm 2 (at the image plane). The method demonstrated accurate estimation of the target reduction pose in simulation, phantom, and a clinical feasibility study for a broad range of dislocation patterns, initialization error, dose levels, and FOV size. The system provides a novel means of guidance and assessment of pelvic reduction from routinely acquired preoperative CT and intraoperative fluoroscopy. The method has the potential to reduce radiation dose by minimizing trial-and-error and to improve outcomes by guiding more accurate reduction of joint dislocations.