Ultrasound-CT registration of vertebrae without reconstruction

Robot-assisted ultrasound reconstruction for spine surgery: from bench-top to pre-clinical study

PURPOSE

Robot-assisted ultrasound (rUS) systems have already been used to provide non-radiative three-dimensional (3D) reconstructions that form the basis for guiding spine surgical procedures. Despite promising studies on this technology, there are few studies that offer insight into the robustness and generality of the approach by verifying performance in various testing scenarios. Therefore, this study aims at providing an assessment of a rUS system, with technical details from experiments starting at the bench-top to the pre-clinical study.

METHODS

A semi-automatic control strategy was proposed to ensure continuous and smooth robotic scanning. Next, a U-Net-based segmentation approach was developed to automatically process the anatomic features and derive a high-quality 3D US reconstruction. Experiments were conducted on synthetic phantoms and human cadavers to validate the proposed approach.

RESULTS

Average deviations of scanning force were found to be 2.84±0.45 N on synthetic phantoms and to be 5.64±1.10 N on human cadavers. The anatomic features could be reliably reconstructed at mean accuracy of 1.28±0.87 mm for the synthetic phantoms and of 1.74±0.89 mm for the human cadavers.

CONCLUSION

The results and experiments demonstrate the feasibility of the proposed system in a pre-clinical setting. This work is complementary to previous work, encouraging further exploration of the potential of this technology in in vivo studies.

Accurate and robust registration method for computer-assisted high tibial osteotomy surgery

PURPOSE

Computer-assisted high tibial osteotomy (HTO) is a frequently used treatment technique for lower extremity orthopedics, and its small incision and low exposure area are major limitations in tibial registration. This work combines skin surface features and gives a suitable registration algorithm based on Iterative Closest Points (ICP) algorithm to improve registration results. Furthermore, the precision, stability and efficiency of the described method is evaluated.

METHODS

After the initialization stage, the bone surface and skin surface data are combined to construct registration features. Then, a steepest perturbation search method is performed after the ICP algorithm (SPS-ICP) to obtain the optimal transformation through several iterations. Finally, the registration result is evaluated by establishing ground-truth through manual landmarks.

RESULTS

Phantom experiments including simulated human tissue show that the proximal fiducial registration error (FRE) of our method can reach 0.80 ± 0.30 mm (mean ± SD) with an overall rotational error < 1° and translational error < 1.5 mm. Furthermore, it remains stable when the point set is sparse. The average registration time is less than 40 s to ensure the high efficiency of surgical operation.

CONCLUSIONS

The approach fully describes a well-defined framework without additional imaging acquisition equipment for Computer-assisted HTO. By the experiment on the basis of a phantom with simulated soft tissue, the proposed method enables the accurate and robust registration of the tibia, and its computation time meets the demands of surgery.

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.

3D ultrasound navigation system for screw insertion in posterior spine surgery: a phantom study

PURPOSE

Posterior spinal fusion surgery is required to correct severe idiopathic scoliosis. The surgery involves insertion of screws which requires high accuracy to prevent neurologic damage to the spinal cord. Although conventional CT navigation can reduce this risk, 3D-ultrasound-based navigation could achieve this without added ionizing radiation and usage of expensive and bulky equipment. This study aimed to evaluate the accuracy of a 3D ultrasound navigation system for posterior spine surgery.

METHODS

A custom 3D ultrasound (3DUS) with model-to-surface registration algorithm was developed and integrated into a 3D navigation environment. A CT scan of an adolescent spine (T3-T11) was segmented and 3D printed for experiments. A probe with reflective markers was placed in vertebral pedicles 684 times in varying levels, positions in the capture space and orientation of vertebra, and the entrypoint and trajectory accuracies were measured.

RESULTS

Among 684 probe placements in vertebral levels T3 to T11 in the phantom spine, 95.5% were within 1 mm and 5° of accuracy, with an average accuracy of 0.4 ± 0.4 mm and 2.1 ± 0.9°, requiring 8.8 s to process. Accuracies were statistically significantly affected by vertebral orientation and position in the capture volume, though this was still within the targeted accuracies of 1 mm and 5°.

CONCLUSION

This preliminary ultrasound-based navigation system is accurate and fast enough for guiding placement of pedicle screws into the spine in posterior fusion surgery. The current results are limited to phantom spines, and future study in animal or human cadavers is needed to investigate soft tissue effects on registration accuracy.

A CNN-based method to reconstruct 3-D spine surfaces from US images in vivo

Three-dimensional (3-D) reconstruction of the spine surface is of strong clinical relevance for the diagnosis and prognosis of spine disorders and intra-operative image guidance. In this paper, we report a new technique to reconstruct lumbar spine surfaces in 3-D from non-invasive ultrasound (US) images acquired in free-hand mode. US images randomly sampled from in vivo scans of 9 rabbits were used to train a U-net convolutional neural network (CNN). More specifically, a late fusion (LF)-based U-net trained jointly on B-mode and shadow-enhanced B-mode images was generated by fusing two individual U-nets and expanding the set of trainable parameters to around twice the capacity of a basic U-net. This U-net was then applied to predict spine surface labels in in vivo images obtained from another rabbit, which were then used for 3-D spine surface reconstruction. The underlying pose of the transducer during the scan was estimated by registering stacks of US images to a geometrical model derived from corresponding CT data and used to align detected surface points. Final performance of the reconstruction method was assessed by computing the mean absolute error (MAE) between pairs of spine surface points detected from US and CT and by counting the total number of surface points detected from US. Comparison was made between the LF-based U-net and a previously developed phase symmetry (PS)-based method. Using the LF-based U-net, the averaged number of US surface points across the lumbar region increased by 21.61% and MAE reduced by 26.28% relative to the PS-based method. The overall MAE (in mm) was 0.24±0.29. Based on these results, we conclude that: 1) the proposed U-net can detect the spine posterior arch with low MAE and large number of US surface points and 2) the newly proposed reconstruction framework may complement and, under certain circumstances, be used without the aid of an external tracking system in intra-operative spine applications.

Open-source software for ultrasound-based guidance in spinal fusion surgery

Spinal instrumentation and surgical manipulations may cause loss of navigation accuracy requiring an efficient re-alignment of the patient anatomy with pre-operative images during surgery. While intra-operative ultrasound (iUS) guidance has shown clear potential to reduce surgery time, compared with clinical computed tomography (CT) guidance, rapid registration aiming to correct for patient misalignment has not been addressed. In this article, we present an open-source platform for pedicle screw navigation using iUS imaging. The alignment method is based on rigid registration of CT to iUS vertebral images and has been designed for fast and fully automatic patient re-alignment in the operating room. Two steps are involved: first, we use the iUS probe's trajectory to achieve an initial coarse registration; then, the registration transform is refined by simultaneously optimizing gradient orientation alignment and mean of iUS intensities passing through the CT-defined posterior surface of the vertebra. We evaluated our approach on a lumbosacral section of a porcine cadaver with seven vertebral levels. We achieved a median target registration error of 1.47 mm (100% success rate, defined by a target registration error <2 mm) when applying the probe's trajectory initial alignment. The approach exhibited high robustness to partial visibility of the vertebra with success rates of 89.86% and 88.57% when missing either the left or right part of the vertebra and robustness to initial misalignments with a success rate of 83.14% for random starts within ±20° rotation and ±20 mm translation. Our graphics processing unit implementation achieves an efficient registration time under 8 s, which makes the approach suitable for clinical application.

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.

Development and Evaluation of CT-to-3D Ultrasound Image Registration Algorithm in Vertebral Phantoms for Spine Surgery

Posterior spinal fusion surgery requires careful insertion of screws into the spine to avoid neurologic injury. While current systems use CT-scans, three-dimensional ultrasound (3DUS) could provide guidance by reconstructing the vertebral surface, and then registering a pre-operative vertebral model to that surface for localization. The aim of this study was to evaluate the accuracy and processing time of a custom CT-3DUS registration algorithm. A phantom human vertebra was 3D-printed and scanned with a motion capture-based 3D ultrasound (3DUS) system. Image registration was performed that included a pre-alignment phase using vertebral symmetry information, and then comparing Gaussian pyramid intensity-based registration with iterative-closest-point registration for final transformations. Image registration was performed 192 times while surgical registration between CT and real-world position was performed 84 times. The accuracy of image registration (CT-to-3DUS) was 0.3 ± 0.2 mm and 0.9 ± 0.8° completed in 13.3 ± 2.9 s. The surgical navigation accuracy (CT model to real-world position) of the system was 1.2 ± 0.5 mm and 2.2 ± 2.0° completed in 16.2 ± 3.0 s. Both meet accuracy thresholds of < 2 mm and < 5° required for the surgery. A feasibility study on porcine spine qualitatively showed appropriate overlapping anatomy in CT-3DUS registrations. The usage of 3D ultrasound for navigation has demonstrated accuracy to provide radiation-free image guidance for spine surgery.

Reconstruction and positional accuracy of 3D ultrasound on vertebral phantoms for adolescent idiopathic scoliosis spinal surgery

PURPOSE

Determine the positional, rotational and reconstruction accuracy of a 3D ultrasound system to be used for image registration in navigation surgery.

METHODS

A custom 3D ultrasound for spinal surgery image registration was developed using Optitrack Prime 13-W motion capture cameras and a SonixTablet Ultrasound System. Temporal and spatial calibration was completed to account for time latencies between the two systems and to ensure accurate motion tracking of the ultrasound transducer. A mock operating room capture volume with a pegboard grid was set up to allow phantoms to be placed at a variety of predetermined positions to validate accuracy measurements. Five custom-designed ultrasound phantoms were 3D printed to allow for a range of linear and angular dimensions to be measured when placed on the pegboard.

RESULTS

Temporal and spatial calibration was completed with measurement repeatabilities of 0.2 mm and 0.5° after calibration. The mean positional accuracy was within 0.4 mm, with all values within 0.5 mm within the critical surgical regions and 96% of values within 1 mm within the full capture volume. All orientation values were within 1.5°. Reconstruction accuracy was within 0.6 mm and 0.9° for geometrically shaped phantoms and 0.5 and 1.9° for vertebrae-mimicking phantoms.

CONCLUSIONS

The accuracy of the developed 3D ultrasound system meets the 1 mm and 5° requirements of spinal surgery from this study. Further repeatability studies and evaluation on vertebrae are needed to validate the system for surgical use.

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.

Integration of free-hand 3D ultrasound and mobile C-arm cone-beam CT: Feasibility and characterization for real-time guidance of needle insertion

This work presents development of an integrated ultrasound (US)-cone-beam CT (CBCT) system for image-guided needle interventions, combining a low-cost ultrasound system (Interson VC 7.5MHz, Pleasanton, CA) with a mobile C-arm for fluoroscopy and CBCT via use of a surgical tracker. Imaging performance of the ultrasound system was characterized in terms of depth-dependent contrast-to-noise ratio (CNR) and spatial resolution. US-CBCT system was evaluated in phantom studies simulating three needle-based procedures: drug delivery, tumor ablation, and lumbar puncture. Low-cost ultrasound provided flexibility but exhibited modest CNR and spatial resolution that is likely limited to fairly superficial applications within a ∼10cm depth of view. Needle tip localization demonstrated target registration error 2.1-3.0mm using fiducial-based registration.

User-friendly freehand ultrasound calibration using Lego bricks and automatic registration

PURPOSE

As an inexpensive, noninvasive, and portable clinical imaging modality, ultrasound (US) has been widely employed in many interventional procedures for monitoring potential tissue deformation, surgical tool placement, and locating surgical targets. The application requires the spatial mapping between 2D US images and 3D coordinates of the patient. Although positions of the devices (i.e., ultrasound transducer) and the patient can be easily recorded by a motion tracking system, the spatial relationship between the US image and the tracker attached to the US transducer needs to be estimated through an US calibration procedure. Previously, various calibration techniques have been proposed, where a spatial transformation is computed to match the coordinates of corresponding features in a physical phantom and those seen in the US scans. However, most of these methods are difficult to use for novel users.

METHODS

We proposed an ultrasound calibration method by constructing a phantom from simple Lego bricks and applying an automated multi-slice 2D-3D registration scheme without volumetric reconstruction. The method was validated for its calibration accuracy and reproducibility.

RESULTS

Our method yields a calibration accuracy of [Formula: see text] mm and a calibration reproducibility of 1.29 mm.

CONCLUSION

We have proposed a robust, inexpensive, and easy-to-use ultrasound calibration method.

Automatic registration of pre- and intraoperative data for long bones in minimally invasive surgery

The Minimally Invasive Procedures (MIP) in orthopedics have grown rapidly worldwide, as clinical results indicate that patients who undergo MIP typically experience minimized blood loss, smaller incision and shorter hospital stays. For most MIP, a preoperative 3D model of the patient anatomy is usually generated in order to plan the surgery. The challenge in MIP consists in finding the correspondence between the preoperative model and the actual position of the patient in the operating room, also known as image-to-patient registration. This paper proposes a real-time solution based on ultrasound (US) images: the patient anatomy is scanned by an US probe. Then, the segmentation and the extraction of bone contours from US images result in a 3D point cloud. The Poisson surface reconstruction method provides a 3D surface from 2D US data which will be registered with the preoperative model (CT volume) using the principal axes of inertia and the Iterative Closest Point robust (ICPr) algorithm. We present quantitative and qualitative results on both phantom and clinical data and show a mean registration accuracy of 0.66 mm for clinical radius scan. The promising registration results show the possible use of the proposed registration algorithm in clinical procedures.

Tracked ultrasound snapshots in percutaneous pedicle screw placement navigation: a feasibility study

BACKGROUND

Computerized navigation improves the accuracy of minimally invasive pedicle screw placement during spine surgery. Such navigation, however, exposes both the patient and the staff to radiation during surgery. To avoid intraoperative exposure to radiation, tracked ultrasound snapshots-ultrasound image frames coupled with corresponding spatial positions-could be used to map preoperatively defined screw plans into the intraoperative coordinate frame. The feasibility of such an approach, however, has not yet been investigated.

QUESTIONS/PURPOSES

Are there vertebral landmarks that can be identified using tracked ultrasound snapshots? Can tracked ultrasound snapshots allow preoperative pedicle screw plans to be accurately mapped--compared with CT-derived pedicle screw plans--into the intraoperative coordinate frame in a simulated setting?

METHODS

Ultrasound visibility of registration landmarks was checked on volunteers and phantoms. An ultrasound machine with integrated electromagnetic tracking was used for tracked ultrasound acquisition. Registration was performed using 3D Slicer open-source software (www.slicer.org). Two artificial lumbar spine phantoms were used to evaluate registration accuracy of pedicle screw plans using tracked ultrasound snapshots. Registration accuracy was determined by comparing the ultrasound-derived plans with the CT-derived plans.

RESULTS

The four articular processes proved to be identifiable using tracked ultrasound snapshots. Pedicle screw plans were registered to the intraoperative coordinate system using landmarks. The registrations were sufficiently accurate in that none of the registered screw plans intersected the pedicle walls. Registered screw plan positions had an error less than 1.28 ± 1.37 mm (average ± SD) in each direction and an angle difference less than 1.92° ± 1.95° around each axis relative to the CT-derived positions.

CONCLUSIONS

Registration landmarks could be located using tracked ultrasound snapshots and permitted accurate mapping of pedicle screw plans to the intraoperative coordinate frame in a simulated setting.

CLINICAL RELEVANCE

Tracked ultrasound may allow accurate computer-navigated pedicle screw placement while avoiding ionizing radiation in the operating room; however, further studies that compare this approach with other navigation techniques are needed to confirm the practical use of this new approach.