Model-based registration of preprocedure MR and intraprocedure US of the lumbar spine

Ultrasound-based navigated pedicle screw insertion without intraoperative radiation: feasibility study on porcine cadavers

BACKGROUND

Navigation systems for spinal fusion surgery rely on intraoperative computed tomography (CT) or fluoroscopy imaging. Both expose patient, surgeons and operating room staff to significant amounts of radiation. Alternative methods involving intraoperative ultrasound (iUS) imaging have recently shown promise for image-to-patient registration. Yet, the feasibility and safety of iUS navigation in spinal fusion have not been demonstrated.

PURPOSE

To evaluate the accuracy of pedicle screw insertion in lumbar and thoracolumbar spinal fusion using a fully automated iUS navigation system.

STUDY DESIGN

Prospective porcine cadaver study.

METHODS

Five porcine cadavers were used to instrument the lumbar and thoracolumbar spine using posterior open surgery. During the procedure, iUS images were acquired and used to establish automatic registration between the anatomy and preoperative CT images. Navigation was performed with the preoperative CT using tracked instruments. The accuracy of the system was measured as the distance of manually collected points to the preoperative CT vertebral surface and compared against fiducial-based registration. A postoperative CT was acquired, and screw placements were manually verified. We report breach rates, as well as axial and sagittal screw deviations.

RESULTS

A total of 56 screws were inserted (5.50 mm diameter n=50, and 6.50 mm diameter n=6). Fifty-two screws were inserted safely without breach. Four screws (7.14%) presented a medial breach with an average deviation of 1.35±0.37 mm (all <2 mm). Two breaches were caused by 6.50 mm diameter screws, and two by 5.50 mm screws. For vertebrae instrumented with 5.50 mm screws, the average axial diameter of the pedicle was 9.29 mm leaving a 1.89 mm margin in the left and right pedicle. For vertebrae instrumented with 6.50 mm screws, the average axial diameter of the pedicle was 8.99 mm leaving a 1.24 mm error margin in the left and right pedicle. The average distance to the vertebral surface was 0.96 mm using iUS registration and 0.97 mm using fiducial-based registration.

CONCLUSIONS

We successfully implanted all pedicle screws in the thoracolumbar spine using the ultrasound-based navigation system. All breaches recorded were minor (<2 mm) and the breach rate (7.14%) was comparable to existing literature. More investigation is needed to evaluate consistency, reproducibility, and performance in surgical context.

CLINICAL SIGNIFICANCE

Intraoperative US-based navigation is feasible and practical for pedicle screw insertion in a porcine model. It might be used as a low-cost and radiation-free alternative to intraoperative CT and fluoroscopy in the future.

The state-of-the-art in ultrasound-guided spine interventions

During the last two decades, intra-operative ultrasound (iUS) imaging has been employed for various surgical procedures of the spine, including spinal fusion and needle injections. Accurate and efficient registration of pre-operative computed tomography or magnetic resonance images with iUS images are key elements in the success of iUS-based spine navigation. While widely investigated in research, iUS-based spine navigation has not yet been established in the clinic. This is due to several factors including the lack of a standard methodology for the assessment of accuracy, robustness, reliability, and usability of the registration method. To address these issues, we present a systematic review of the state-of-the-art techniques for iUS-guided registration in spinal image-guided surgery (IGS). The review follows a new taxonomy based on the four steps involved in the surgical workflow that include pre-processing, registration initialization, estimation of the required patient to image transformation, and a visualization process. We provide a detailed analysis of the measurements in terms of accuracy, robustness, reliability, and usability that need to be met during the evaluation of a spinal IGS framework. Although this review is focused on spinal navigation, we expect similar evaluation criteria to be relevant for other IGS applications.

Spinal pain relief procedures with the assistance of the MRI-updated statistical shape model

BACKGROUND

Updating the statistical shape model (SSM) used in image guidance systems for the treatment of back pain using pre-op computed tomography (CT) and intra-op ultrasound (US) is challenging due to the scarce availability of pre-op images and the low resolution of the two imaging modalities.

METHODS

A new approach is proposed here to update SSMs based on the sparse representation of the preoperative MRI images of patients as well as CT images, followed by displaying the injection needle and 3D tracking view of the patients' spine.

RESULTS

The statistical analysis shows that updating the SSM using the patients' available MRI images (in more than 95% of the cases) instead of CT images (in less than 5%) will help maintain the required accuracy of needle injection based on the evaluation of injection in different parts of the phantom.

CONCLUSION

The results show that using the proposed model helps reduce the dosage and processing time significantly while maintaining the precision required for the pain procedures.

Real-time, image-based slice-to-volume registration for ultrasound-guided spinal intervention

Real-time fusion of magnetic resonance (MR) and ultrasound (US) images could facilitate safe and accurate needle placement in spinal interventions. We develop an entirely image-based registration method (independent of or complementary to surgical trackers) that includes an efficient US probe pose initialization algorithm. The registration enables the simultaneous display of 2D ultrasound image slices relative to 3D pre-procedure MR images for navigation. A dictionary-based 3D-2D pose initialization algorithm was developed in which likely probe positions are predefined in a dictionary with feature encoding by Haar wavelet filters. Feature vectors representing the 2D US image are computed by scaling and translating multiple Haar basis filters to capture scale, location, and relative intensity patterns of distinct anatomical features. Following pose initialization, fast 3D-2D registration was performed by optimizing normalized cross-correlation between intra- and pre-procedure images using Powell's method. Experiments were performed using a lumbar puncture phantom and a fresh cadaver specimen presenting realistic image quality in spinal US imaging. Accuracy was quantified by comparing registration transforms to ground truth motion imparted by a computer-controlled motion system and calculating target registration error (TRE) in anatomical landmarks. Initialization using a 315-length feature vector yielded median translation accuracy of 2.7 mm (3.4 mm interquartile range, IQR) in the phantom and 2.1 mm (2.5 mm IQR) in the cadaver. By comparison, storing the entire image set in the dictionary and optimizing correlation yielded a comparable median accuracy of 2.1 mm (2.8 mm IQR) in the phantom and 2.9 mm (3.5 mm IQR) in the cadaver. However, the dictionary-based method reduced memory requirements by 47×  compared to storing the entire image set. The overall 3D error after registration measured using 3D landmarks was 3.2 mm (1.8 mm IQR) mm in the phantom and 3.0 mm (2.3 mm IQR) mm in the cadaver. The system was implemented in a 3D Slicer interface to facilitate translation to clinical studies. Haar feature based initialization provided accuracy and robustness at a level that was sufficient for real-time registration using an entirely image-based method for ultrasound navigation. Such an approach could improve the accuracy and safety of spinal interventions in broad utilization, since it is entirely software-based and can operate free from the cost and workflow requirements of surgical trackers.

Registration of 3D freehand ultrasound to a bone model for orthopedic procedures of the forearm

PURPOSE

For guidance of orthopedic surgery, the registration of preoperative images and corresponding surgical plans with the surgical setting can be of great value. Ultrasound (US) is an ideal modality for surgical guidance, as it is non-ionizing, real time, easy to use, and requires minimal (magnetic/radiation) safety limitations. By extracting bone surfaces from 3D freehand US and registering these to preoperative bone models, complementary information from these modalities can be fused and presented in the surgical realm.

METHODS

A partial bone surface is extracted from US using phase symmetry and a factor graph-based approach. This is registered to the detailed 3D bone model, conventionally generated for preoperative planning, based on a proposed multi-initialization and surface-based scheme robust to partial surfaces.

RESULTS

36 forearm US volumes acquired using a tracked US probe were independently registered to a 3D model of the radius, manually extracted from MRI. Given intraoperative time restrictions, a computationally efficient algorithm was determined based on a comparison of different approaches. For all 36 registrations, a mean (± SD) point-to-point surface distance of [Formula: see text] was obtained from manual gold standard US bone annotations (not used during the registration) to the 3D bone model.

CONCLUSIONS

A registration framework based on the bone surface extraction from 3D freehand US and a subsequent fast, automatic surface alignment robust to single-sided view and large false-positive rates from US was shown to achieve registration accuracy feasible for practical orthopedic scenarios and a qualitative outcome indicating good visual image alignment.