Data-Driven Deformable 3D-2D Registration for Guiding Neuroelectrode Placement in Deep Brain Stimulation

PURPOSE

Deep brain stimulation is a neurosurgical procedure used in treatment of a growing spectrum of movement disorders. Inaccuracies in electrode placement, however, can result in poor symptom control or adverse effects and confound variability in clinical outcomes. A deformable 3D-2D registration method is presented for high-precision 3D guidance of neuroelectrodes.

METHODS

The approach employs a model-based, deformable algorithm for 3D-2D image registration. Variations in lead design are captured in a parametric 3D model based on a B-spline curve. The registration is solved through iterative optimization of 16 degrees-of-freedom that maximize image similarity between the 2 acquired radiographs and simulated forward projections of the neuroelectrode model. The approach was evaluated in phantom models with respect to pertinent imaging parameters, including view selection and imaging dose.

RESULTS

The results demonstrate an accuracy of (0.2 ± 0.2) mm in 3D localization of individual electrodes. The solution was observed to be robust to changes in pertinent imaging parameters, which demonstrate accurate localization with ≥20° view separation and at 1/10^th the dose of a standard fluoroscopy frame.

CONCLUSIONS

The presented approach provides the means for guiding neuroelectrode placement from 2 low-dose radiographic images in a manner that accommodates potential deformations at the target anatomical site. Future work will focus on improving runtime though learning-based initialization, application in reducing reconstruction metal artifacts for 3D verification of placement, and extensive evaluation in clinical data from an IRB study underway.

3D-2D Image Registration in Virtual Long-Film Imaging: Application to Spinal Deformity Correction

PURPOSE

Intraoperative 2D virtual long-film (VLF) imaging is investigated for 3D guidance and confirmation of the surgical product in spinal deformity correction. Multi-slot-scan geometry (rather than a single-slot "topogram") is exploited to produce parallax views of the scene for accurate 3D colocalization from a single radiograph.

METHODS

The multi-slot approach uses additional angled collimator apertures to form fan-beams with disparate views (parallax) of anatomy and instrumentation and to extend field-of-view beyond the linear motion limits. Combined with a knowledge of surgical implants (pedicle screws and/or spinal rods modeled as "known components"), 3D-2D image registration is used to solve for pose estimates via optimization of image gradient correlation. Experiments were conducted in cadaver studies emulating the system geometry of the O-arm (Medtronic, Minneapolis MN).

RESULTS

Experiments demonstrated feasibility of multi-slot VLF and quantified the geometric accuracy of 3D-2D registration using VLF acquisitions. Registration of pedicle screws from a single VLF yielded mean target registration error of (2.0±0.7) mm, comparable to the accuracy of surgical trackers and registration using multiple radiographs (e.g., AP and LAT).

CONCLUSIONS

3D-2D registration in a single VLF image offers a promising new solution for image guidance in spinal deformity correction. The ability to accurately resolve pose from a single view absolves workflow challenges of multiple-view registration and suggests application beyond spine surgery, such as reduction of long-bone fractures.

Extrinsic Factors as Component Positions to Bone and Intrinsic Factors Affecting Postoperative Rotational Limb Alignment in Total Knee Arthroplasty

BACKGROUND

This study aimed to identify the factors affecting postoperative rotational limb alignment of the tibia relative to the femur. We hypothesized that not only component positions but also several intrinsic factors were associated with postoperative rotational limb alignment.

METHODS

This study included 99 knees (90 women and 9 men) with a mean age of 77 ± 6 years. A three-dimensional (3D) assessment system was applied under weight-bearing conditions to biplanar long-leg radiographs using 3D-to-2D image registration technique. The evaluation parameters were (1) component position; (2) preoperative and postoperative coronal, sagittal, and rotational limb alignment; (3) preoperative bony deformity, including femoral torsion, condylar twist angle, and tibial torsion; and (4) preoperative and postoperative range of motion (ROM).

RESULTS

In multiple linear regression analysis using a stepwise procedure, postoperative rotational limb alignment was associated with the following: (1) rotation of the component position (tibia: β = 0.371, P < .0001; femur: β = -0.327, P < .0001), (2) preoperative rotational limb alignment (β = 0.253, P = .001), (3) postoperative flexion angle (β = 0.195, P = .007), and (4) tibial torsion (β = 0.193, P = .010).

CONCLUSION

In addition to component positions, the intrinsic factors, such as preoperative rotational limb alignment, ROM, and tibial torsion, affected postoperative rotational limb alignment. On a premise of correct component positions, the intrinsic factors that can be controlled by surgeons should be taken care. In particular, ROM is necessary to be improved within the possible range to acquire better postoperative rotational limb alignment.

Advanced Image Registration and Reconstruction using the O-Arm System: Dose Reduction, Image Quality, and Guidance using Known-Component Models

Purpose

Model-based image registration and reconstruction offer strong potential for improved safety and precision in image-guided interventions. Advantages include reduced radiation dose, improved soft-tissue visibility (detection of complications), and accurate guidance with/without a dedicated navigation system. This work reports the development and performance of such methods on an O-arm system for intraoperative imaging and translates them to first clinical studies.

Methods

Two novel methodologies predicate the work: (1) Known-Component Registration (KC-Reg) for 3D localization of the patient and interventional devices from 2D radiographs; and (2) Penalized-Likelihood reconstruction (PLH) for improved 3D image quality and dose reduction. A thorough assessment of geometric stability, dosimetry, and image quality was performed to define algorithm parameters for imaging and guidance protocols. Laboratory studies included: evaluation of KC-Reg in localization of spine screws delivered in cadaver; and PLH performance in contrast, noise, and resolution in phantoms/cadaver compared to filtered backprojection (FBP).

Results

KC-Reg was shown to successfully register screw implants within ~1 mm based on as few as 3 radiographs. PLH was shown to improve soft-tissue visibility (61% improvement in CNR) compared to FBP at matched resolution. Cadaver studies verified the selection of algorithm parameters and the methods were successfully translated to clinical studies under an IRB protocol.

Conclusions

Model-based registration and reconstruction approaches were shown to reduce dose and provide improved visualization of anatomy and surgical instrumentation. Immediate future work will focus on further integration of KC-Reg and PLH for Known-Component Reconstruction (KC-Recon) to provide high-quality intraoperative imaging in the presence of dense instrumentation.

Video see-through augmented reality for oral and maxillofacial surgery

BACKGROUND

Oral and maxillofacial surgery has not been benefitting from image guidance techniques owing to the limitations in image registration.

METHODS

A real-time markerless image registration method is proposed by integrating a shape matching method into a 2D tracking framework. The image registration is performed by matching the patient's teeth model with intraoperative video to obtain its pose. The resulting pose is used to overlay relevant models from the same CT space on the camera video for augmented reality.

RESULTS

The proposed system was evaluated on mandible/maxilla phantoms, a volunteer and clinical data. Experimental results show that the target overlay error is about 1 mm, and the frame rate of registration update yields 3-5 frames per second with a 4 K camera.

CONCLUSIONS

The significance of this work lies in its simplicity in clinical setting and the seamless integration into the current medical procedure with satisfactory response time and overlay accuracy. Copyright © 2016 John Wiley & Sons, Ltd.

Known-Component 3D-2D Registration for Image Guidance and Quality Assurance in Spine Surgery Pedicle Screw Placement

PURPOSE

To extend the functionality of radiographic/fluoroscopic imaging systems already within standard spine surgery workflow to: 1) provide guidance of surgical device analogous to an external tracking system; and 2) provide intraoperative quality assurance (QA) of the surgical product.

METHODS

Using fast, robust 3D-2D registration in combination with 3D models of known components (surgical devices), the 3D pose determination was solved to relate known components to 2D projection images and 3D preoperative CT in near-real-time. Exact and parametric models of the components were used as input to the algorithm to evaluate the effects of model fidelity. The proposed algorithm employs the covariance matrix adaptation evolution strategy (CMA-ES) to maximize gradient correlation (GC) between measured projections and simulated forward projections of components. Geometric accuracy was evaluated in a spine phantom in terms of target registration error at the tool tip (TRE _x ), and angular deviation (TRE _ϕ ) from planned trajectory.

RESULTS

Transpedicle surgical devices (probe tool and spine screws) were successfully guided with TRE _x <2 mm and TRE _ϕ <0.5° given projection views separated by at least >30° (easily accommodated on a mobile C-arm). QA of the surgical product based on 3D-2D registration demonstrated the detection of pedicle screw breach with TRE _x <1 mm, demonstrating a trend of improved accuracy correlated to the fidelity of the component model employed.

CONCLUSIONS

3D-2D registration combined with 3D models of known surgical components provides a novel method for near-real-time guidance and quality assurance using a mobile C-arm without external trackers or fiducial markers. Ongoing work includes determination of optimal views based on component shape and trajectory, improved robustness to anatomical deformation, and expanded preclinical testing in spine and intracranial surgeries.