Deformable 3D-2D Registration of Known Components for Image Guidance in Spine Surgery

Uneri, Ali; Goerres, J.; Silva, T. De; Jacobson, M.; Ketcha, Michael D.; Reaungamornrat, S.; Kleinszig, Gerhard; Vogt, Sebastian; Khanna, A. Jay; Wolinsky, J.-P.; Siewerdsen, Jeffrey H.

doi:10.1007/978-3-319-46726-9_15

Cited by 16 publications

(24 citation statements)

References 9 publications

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“…Since K-Wires are prone to deformation, we apply a deformable cylinder component based on recent work (Uneri et al, 2016). Instead of alternating a rigid transform

T_{K} false(\overset{p}{true} false), \overset{p}{true} \subset p

of the known-component, B-spline knots are varied to deform the wire model.…”

Section: Methodsmentioning

confidence: 99%

“…With the patient registered via 3D-2D registration of preoperative CT and intraoperative fluoroscopy, visualization (CT overlay) analogous to surgical navigation can be created without additional devices in the OR. Recent work on deformable known components (dKC) (Uneri et al, 2016) relaxes the constraints of device rigidity, allowing deformable devices such as K-wires to be localized for surgical guidance.…”

Section: Introductionmentioning

confidence: 99%

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Planning, guidance, and quality assurance of pelvic screw placement using deformable image registration

et al. 2017

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Percutaneous pelvic screw placement is challenging due to narrow bone corridors surrounded by vulnerable structures and difficult visual interpretation of complex anatomical shapes in 2D x-ray projection images. To address these challenges, a system for planning, guidance, and quality assurance (QA) is presented, providing functionality analogous to surgical navigation, but based on robust 3D-2D image registration techniques using fluoroscopy images already acquired in routine workflow. Two novel aspects of the system are investigated: automatic planning of pelvic screw trajectories and the ability to account for deformation of surgical devices (K-wire deflection). Atlas-based registration is used to calculate a patient-specific plan of screw trajectories in preoperative CT. 3D-2D registration aligns the patient to CT within the projective geometry of intraoperative fluoroscopy. Deformable known-component registration (dKC-Reg) localizes the surgical device, and the combination of plan and device location is used to provide guidance and QA. A leave-one-out analysis evaluated the accuracy of automatic planning, and a cadaver experiment compared the accuracy of dKC-Reg to rigid approaches (e.g., optical tracking). Surgical plans conformed within the bone cortex by 3–4 mm for the narrowest corridor (superior pubic ramus) and >5 mm for the widest corridor (tear drop). The dKC-Reg algorithm localized the K-wire tip within 1.1 mm and 1.4° and was consistently more accurate than rigid-body tracking (errors up to 9 mm). The system was shown to automatically compute reliable screw trajectories and accurately localize deformed surgical devices (K-wires). Such capability could improve guidance and QA in orthopaedic surgery, where workflow is impeded by manual planning, conventional tool trackers add complexity and cost, rigid tool assumptions are often inaccurate, and qualitative interpretation of complex anatomy from 2D projections is prone to trial-and-error with extended fluoroscopy time.

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“…Since K-Wires are prone to deformation, we apply a deformable cylinder component based on recent work (Uneri et al, 2016). Instead of alternating a rigid transform

T_{K} false(\overset{p}{true} false), \overset{p}{true} \subset p

of the known-component, B-spline knots are varied to deform the wire model.…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Planning, guidance, and quality assurance of pelvic screw placement using deformable image registration

et al. 2017

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“…Electromagnetic tracking systems can overcome this problem but can experience a loss of accuracy in proximity to metal structures and may require tool-specific manufacturing to accomplish tracking of devices within the body. In contrast to such navigation systems, the C-arm imaging system itself can be used to localize tools using 3D-2D registration, as previously shown in the context of spinal surgery [3],[4]. Based on this approach, we present a new system for accurate K-wire localization from three pelvic inlet- and outlet- view x-ray projections.…”

Section: Description Of Purposementioning

confidence: 99%

Deformable 3D-2D registration for guiding K-wire placement in pelvic trauma surgery

et al. 2017

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Pelvic Kirschner wire (K-wire) insertion is a challenging surgical task requiring interpretation of complex 3D anatomical shape from 2D projections (fluoroscopy) and delivery of device trajectories within fairly narrow bone corridors in proximity to adjacent nerves and vessels. Over long trajectories (~10–25 cm), K-wires tend to curve (deform), making conventional rigid navigation inaccurate at the tip location. A system is presented that provides accurate 3D localization and guidance of rigid or deformable surgical devices (“components” – e.g., K-wires) based on 3D-2D registration. The patient is registered to a preoperative CT image by virtually projecting digitally reconstructed radiographs (DRRs) and matching to two or more intraoperative x-ray projections. The K-wire is localized using an analogous procedure matching DRRs of a deformably parametrized model for the device component (deformable known-component registration, or dKC-Reg). A cadaver study was performed in which a K-wire trajectory was delivered in the pelvis. The system demonstrated target registration error (TRE) of 2.1 ± 0.3 mm in location of the K-wire tip (median ± interquartile range, IQR) and 0.8 ± 1.4° in orientation at the tip (median ± IQR), providing functionality analogous to surgical tracking/navigation using imaging systems already in the surgical arsenal without reliance on a surgical tracker. The method offers quantitative 3D guidance using images (e.g., inlet/outlet views) already acquired in the standard of care, potentially extending the advantages of navigation to broader utilization in trauma surgery to improve surgical precision and safety.

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“…Previous work has illustrated that deformable 3D-2D registration is a challenging and often ill-posed problem; for example, in the case of a single 2D view there is degenerate geometric relationship between projection magnification and changes in object size. Several advances in deformable 3D-2D image registration have been reported for scenarios in which multiple 2D images are acquired (Benameur et al 2003, Prummer et al 2006, Rivest-Henault et al 2012, Guyot et al 2013, Uneri et al 2016), in applications such as radiographic vertebrae segmentation and surgical guidance using digital subtraction angiography. For single-view 3D-2D registration, at least two general methods to mitigate the effects of deformation have been proposed: (i) apply a deformable method with constraints imposed by 3D segmentations and deformation models (Groher 2007, Penney et al 2002); and (ii) perform piece-wise rigid registrations, often involving shape models (Schmid and Chênes 2014) or segmentations of rigid bodies.…”

Section: Introductionmentioning

confidence: 99%

Multi-stage 3D–2D registration for correction of anatomical deformation in image-guided spine surgery

et al. 2017

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Purpose A multi-stage image-based 3D-2D registration method is presented that maps annotations in a 3D image (e.g., point labels annotating individual vertebrae in preoperative CT) to an intraoperative radiograph in which the patient has undergone non-rigid anatomical deformation due to changes in patient positioning or due to the intervention itself. Methods The proposed method (termed msLevelCheck) extends a previous rigid registration solution (LevelCheck) to provide an accurate mapping of vertebral labels in the presence of spinal deformation. The method employs a multi-stage series of rigid 3D-2D registrations performed on sets of automatically determined and increasingly localized sub-images, with the final stage achieving a rigid mapping for each label to yield a locally rigid yet globally deformable solution. The method was evaluated first in a phantom study in which a CT image of the spine was acquired followed by a series of 7 mobile radiographs with increasing degree of deformation applied. Second, the method was validated using a clinical data set of patients exhibiting strong spinal deformation during thoracolumbar spine surgery. Registration accuracy was assessed using projection distance error (PDE) and failure rate (PDE > 20 mm – i.e., label registered outside vertebra). Results The msLevelCheck method was able to register all vertebrae accurately for all cases of deformation in the phantom study, improving the maximum PDE of the rigid method from 22.4 mm to 3.9 mm. The clinical study demonstrated the feasibility of the approach in real patient data by accurately registering all vertebral labels in each case, eliminating all instances of failure encountered in the conventional rigid method. Conclusion The multi-stage approach demonstrated accurate mapping of vertebral labels in the presence of strong spinal deformation. The msLevelCheck method maintains other advantageous aspects of the original LevelCheck method (e.g., compatibility with standard clinical workflow, large capture range, and robustness against mismatch in image content) and extends capability to cases exhibiting strong changes in spinal curvature.

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Deformable 3D-2D Registration of Known Components for Image Guidance in Spine Surgery

Cited by 16 publications

References 9 publications

Planning, guidance, and quality assurance of pelvic screw placement using deformable image registration

Planning, guidance, and quality assurance of pelvic screw placement using deformable image registration

Deformable 3D-2D registration for guiding K-wire placement in pelvic trauma surgery

Multi-stage 3D–2D registration for correction of anatomical deformation in image-guided spine surgery

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