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

The utility of intraoperative ultrasonography for spinal cord surgery

OBJECTIVES

Intraoperative ultrasonography (IOUS) offers the advantage of providing real-time imaging features, yet it is not generally used. This study aims to discuss the benefits of utilizing IOUS in spinal cord surgery and review related literature.

MATERIALS AND METHODS

Patients who underwent spinal cord surgery utilizing IOUS at a single institution were retrospectively collected and analyzed to evaluate the benefits derived from the use of IOUS.

RESULTS

A total of 43 consecutive patients were analyzed. Schwannoma was the most common tumor (35%), followed by cavernous angioma (23%) and ependymoma (16%). IOUS confirmed tumor extent and location before dura opening in 42 patients (97.7%). It was particularly helpful for myelotomy in deep-seated intramedullary lesions to minimize neural injury in 13 patients (31.0% of 42 patients). IOUS also detected residual or hidden lesions in 3 patients (7.0%) and verified the absence of hematoma post-tumor removal in 23 patients (53.5%). In 3 patients (7.0%), confirming no intradural lesions after removing extradural tumors avoided additional dural incisions. IOUS identified surrounding blood vessels and detected dural defects in one patient (2.3%) respectively.

CONCLUSIONS

The IOUS can be a valuable tool for spinal cord surgery in identifying the exact location of the pathologic lesions, confirming the completeness of surgery, and minimizing the risk of neural and vascular injury in a real-time fashion.

Shape completion in the dark: completing vertebrae morphology from 3D ultrasound

PURPOSE

Ultrasound (US) imaging, while advantageous for its radiation-free nature, is challenging to interpret due to only partially visible organs and a lack of complete 3D information. While performing US-based diagnosis or investigation, medical professionals therefore create a mental map of the 3D anatomy. In this work, we aim to replicate this process and enhance the visual representation of anatomical structures.

METHODS

We introduce a point cloud-based probabilistic deep learning (DL) method to complete occluded anatomical structures through 3D shape completion and choose US-based spine examinations as our application. To enable training, we generate synthetic 3D representations of partially occluded spinal views by mimicking US physics and accounting for inherent artifacts.

RESULTS

The proposed model performs consistently on synthetic and patient data, with mean and median differences of 2.02 and 0.03 in Chamfer Distance (CD), respectively. Our ablation study demonstrates the importance of US physics-based data generation, reflected in the large mean and median difference of 11.8 CD and 9.55 CD, respectively. Additionally, we demonstrate that anatomical landmarks, such as the spinous process (with reconstruction CD of 4.73) and the facet joints (mean distance to ground truth (GT) of 4.96 mm), are preserved in the 3D completion.

CONCLUSION

Our work establishes the feasibility of 3D shape completion for lumbar vertebrae, ensuring the preservation of level-wise characteristics and successful generalization from synthetic to real data. The incorporation of US physics contributes to more accurate patient data completions. Notably, our method preserves essential anatomical landmarks and reconstructs crucial injections sites at their correct locations.

Anatomy-aware computed tomography-to-ultrasound spine registration

BACKGROUND

Ultrasound (US) has demonstrated to be an effective guidance technique for lumbar spine injections, enabling precise needle placement without exposing the surgeon or the patient to ionizing radiation. However, noise and acoustic shadowing artifacts make US data interpretation challenging. To mitigate these problems, many authors suggested using computed tomography (CT)-to-US registration to align the spine in pre-operative CT to intra-operative US data, thus providing localization of spinal landmarks.

PURPOSE

In this paper, we propose a deep learning (DL) pipeline for CT-to-US registration and address the problem of a need for annotated medical data for network training. Firstly, we design a data generation method to generate paired CT-US data where the spine is deformed in a physically consistent manner. Secondly, we train a point cloud (PC) registration network using anatomy-aware losses to enforce anatomically consistent predictions.

METHODS

Our proposed pipeline relies on training the network on realistic generated data. In our data generation method, we model the properties of the joints and disks between vertebrae based on biomechanical measurements in previous studies. We simulate the supine and prone position deformation by applying forces on the spine models. We choose the spine models from 35 patients in VerSe dataset. Each spine is deformed 10 times to create a noise-free data with ground-truth segmentation at hand. In our experiments, we use one-leave-out cross-validation strategy to measure the performance and the stability of the proposed method. For each experiment, we choose generated PCs from three spines as the test set. From the remaining, data from 3 spines act as the validation set and we use the rest of the data for training the algorithm. To train our network, we introduce anatomy-aware losses and constraints on the movement to match the physics of the spine, namely, rigidity loss and bio-mechanical loss. We define rigidity loss based on the fact that each vertebra can only transform rigidly while the disks and the surrounding tissue are deformable. Second, by using bio-mechanical loss we stop the network from inferring extreme movements by penalizing the force needed to get to a certain pose.

RESULTS

To validate the effectiveness of our fully automated data generation pipeline, we qualitatively assess the fidelity of the generated data. This assessment involves verifying the realism of the spinal deformation and subsequently confirming the plausibility of the simulated ultrasound images. Next, we demonstrate that the introduction of the anatomy-aware losses brings us closer to state-of-the-art (SOTA) and yields a reduction of 0.25 mm in terms of target registration error (TRE) compared to using only mean squared error (MSE) loss on the generated dataset. Furthermore, by using the proposed losses, the rigidity loss in inference decreases which shows that the inferred deformation respects the rigidity of the vertebrae and only introduces deformations in the soft tissue area to compensate the difference to the target PC. We also show that our results are close to the SOTA for the simulated US dataset with TRE of 3.89 mm and 3.63 mm for the proposed method and SOTA respectively. In addition, we show that our method is more robust against errors in the initialization in comparison to SOTA and significantly achieves better results (TRE of 4.88 mm compared to 5.66 mm) in this experiment.

CONCLUSIONS

In conclusion, we present a pipeline for spine CT-to-US registration and explore the potential benefits of utilizing anatomy-aware losses to enhance registration results. Additionally, we propose a fully automatic method to synthesize paired CT-US data with physically consistent deformations, which offers the opportunity to generate extensive datasets for network training. The generated dataset and the source code for data generation and registration pipeline can be accessed via https://github.com/mfazampour/medphys_ct_us_registration.

Craniofacial Soft-Tissue Anthropomorphic Database with Magnetic Resonance Imaging and Unbiased Diffeomorphic Registration

BACKGROUND

Objective assessment of craniofacial surgery outcomes in a pediatric population is challenging because of the complexity of patient presentations, diversity of procedures performed, and rapid craniofacial growth. There is a paucity of robust methods to quantify anatomical measurements by age and objectively compare craniofacial dysmorphology and postoperative outcomes. Here, the authors present data in developing a racially and ethnically sensitive anthropomorphic database, providing plastic and craniofacial surgeons with "normal" three-dimensional anatomical parameters with which to appraise and optimize aesthetic and reconstructive outcomes.

METHODS

Patients with normal craniofacial anatomy undergoing head magnetic resonance imaging (MRI) scans from 2008 to 2021 were included in this retrospective study. Images were used to construct composite (template) images with diffeomorphic image registration method using the Advanced Normalization Tools package. Composites were thresholded to generate binary three-dimensional segmentations used for anatomical measurements in Materalise Mimics.

RESULTS

High-resolution MRI scans from 130 patients generated 12 composites from an average of 10 MRI sequences each: four 3-year-olds, four 4-year-olds, and four 5-year-olds (two male, two female, two Black, and two White). The average head circumference of 3-, 4-, and 5-year-old composites was 50.3, 51.5, and 51.7 cm, respectively, comparable to normative data published by the World Health Organization.

CONCLUSIONS

Application of diffeomorphic registration-based image template algorithm to MRI is effective in creating composite templates to represent "normal" three-dimensional craniofacial and soft-tissue anatomy. Future research will focus on development of automated computational tools to characterize anatomical normality, generation of indices to grade preoperative severity, and quantification of postoperative results to reduce subjectivity bias.

Assessment of thoracic spinal curvatures in static postures using spatially tracked 3D ultrasound volumes: a proof-of-concept study

The assessment of spinal posture is a difficult endeavour given the lack of identifiable bony landmarks for placement of skin markers. Moreover, potentially significant soft tissue artefacts along the spine further affect the accuracy of marker-based approaches. The objective of this proof-of-concept study was to develop an experimental framework to assess spinal postures by using three-dimensional (3D) ultrasound (US) imaging. A phantom spine model immersed in water was scanned using 3D US in a neutral and two curved postures mimicking a forward flexion in the sagittal plane while the US probe was localised by three electromagnetic tracking sensors attached to the probe head. The obtained anatomical 'coarse' registrations were further refined using an automatic registration algorithm and validated by an experienced sonographer. Spinal landmarks were selected in the US images and validated against magnetic resonance imaging data of the same phantom through image registration. Their position was then related to the location of the tracking sensors identified in the acquired US volumes, enabling the localisation of landmarks in the global coordinate system of the tracking device. Results of this study show that localised 3D US enables US-based anatomical reconstructions comparable to clinical standards and the identification of spinal landmarks in different postures of the spine. The accuracy in sensor identification was 0.49 mm on average while the intra- and inter-observer reliability in sensor identification was strongly correlated with a maximum deviation of 0.8 mm. Mapping of landmarks had a small relative distance error of 0.21 mm (SD = ± 0.16) on average. This study implies that localised 3D US holds the potential for the assessment of full spinal posture by accurately and non-invasively localising vertebrae in space.

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.

Comparative analysis of wavelet transform filtering systems for noise reduction in ultrasound images

Wavelet transform (WT) is a commonly used method for noise suppression and feature extraction from biomedical images. The selection of WT system settings significantly affects the efficiency of denoising procedure. This comparative study analyzed the efficacy of the proposed WT system on real 292 ultrasound images from several areas of interest. The study investigates the performance of the system for different scaling functions of two basic wavelet bases, Daubechies and Symlets, and their efficiency on images artificially corrupted by three kinds of noise. To evaluate our extensive analysis, we used objective metrics, namely structural similarity index (SSIM), correlation coefficient, mean squared error (MSE), peak signal-to-noise ratio (PSNR) and universal image quality index (Q-index). Moreover, this study includes clinical insights on selected filtration outcomes provided by clinical experts. The results show that the efficiency of the filtration strongly depends on the specific wavelet system setting, type of ultrasound data, and the noise present. The findings presented may provide a useful guideline for researchers, software developers, and clinical professionals to obtain high quality images.

AutoInFocus, a new paradigm for ultrasound-guided spine intervention: a multi-platform validation study

PURPOSE

Ultrasound-guided spine interventions often suffer from the insufficient visualization of key anatomical structures due to the complex shapes of the self-shadowing vertebrae. Therefore, we propose an ultrasound imaging paradigm, AutoInFocus (automatic insonification optimization with controlled ultrasound), to improve the key structure visibility.

METHODS

A phased-array probe is used in conjunction with a motion platform to image a controlled workspace, and the resulting images from multiple insonification angles are combined to reveal the target anatomy. This idea is first evaluated in simulation and then realized as a robotic platform and a miniaturized patch device. A spine phantom (CIRS) and its CT scan were used in the evaluation experiments to quantitatively and qualitatively analyze the advantages of the proposed method over the traditional approach.

RESULTS

We showed in simulation that the proposed system setup increased the visibility of interspinous space boundary, a key feature for lumbar puncture guidance, from 44.13 to 67.73% on average, and the 3D spine surface coverage from 14.31 to 35.87%, compared to traditional imaging setup. We also demonstrated the feasibility of both robotic and patch-based realizations in a spine phantom study.

CONCLUSION

This work lays the foundation for a new imaging paradigm that leverages redundant and controlled insonification to allow for imaging optimization of the complex vertebrae anatomy, making it possible for high-quality visualization of key anatomies during ultrasound-guided spine interventions.

Systematic Review: Applications of Intraoperative Ultrasound in Spinal Surgery

BACKGROUND

Due to increased practicality and decreased costs and radiation, interest has risen for intraoperative ultrasound (iUS) in spinal surgery applications; however, few studies have provided a robust overview of its use in spinal surgery. We synthesize findings of existing literature on usage of iUS in navigation, pedicle screw placement, and identification of anatomy during spinal interventions.

METHODS

Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were utilized in this systematic review. Studies were identified through PubMed, Scopus, and Google Scholar databases using the search string. Abstracts mentioning iUS in spine applications were included. Upon full-text review, exclusion criteria were implemented, including outdated studies or those with weak topic relevance or statistical power. Upon elimination of duplicates, multi-reviewer screening for eligibility, and citation search, 44 manuscripts were analyzed.

RESULTS

Navigation using iUS is safe, effective, and economical. iUS registration accuracy and success is within clinically acceptable limits for image-guided navigation (Table 2). Pedicle screw instrumentation with iUS is precise with a favorable safety profile (Table 2). Anatomical landmarks are reliably identified with iUS, and surgeons are overwhelmingly successful in neural or vascular tissue identification with iUS modalities including standard B mode, doppler, and contrast-enhanced ultrasound (CE-US) (Table 3). iUS use in traumatic reduction of fractures properly identifies anatomical structures, intervertebral disc space, and vasculature (Table 3).

CONCLUSION

iUS eliminates radiation, decreases costs, and provides sufficient accuracy and reliability in identification of anatomical and neurovascular structures in various spinal surgery settings.

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.

Image Guidance in Spinal Surgery: A Critical Appraisal and Future Directions

BACKGROUND

Image-guided spinal surgery (IGSS) underwent rapid development over the past decades. The goal of IGSS is to increase patient safety and improve workflow. We present an overview of the history of IGSS, illustrate its current state, and highlight future developments. Currently, IGSS requires an image set, a tracking system, and a calibration method.

IMAGING

Two-dimensional images have many disadvantages as a source for navigation. Currently, the most common navigation technique is three-dimensional (3D) navigation based on cross-sectional imaging techniques such as cone-beam computed tomography (CT) or fan-beam CT.

TRACKING

Electromagnetic tracking uses an electromagnetic field to localize instruments. Optical tracking using infrared cameras has currently become one of the most common tracking methods in IGSS.

CALIBRATION

The three most common techniques currently used are the point-matching registration technique, the surface-matching registration technique, and the automated registration technique.

FUTURE

Augmented reality (AR) describes a computer-generated image that can be superimposed onto the real-world environment. Marking pathologies and anatomical landmarks are a few examples of many possible future applications. Additionally, AR offers a wide range of possibilities in surgical training. The latest development in IGSS is robotic-assisted surgery (RAS). The presently available data on RAS are very encouraging, but further improvements of these procedures is expected.

CONCLUSION

IGSS significantly evolved since its inception and is becoming a routinely used technology. In the future, IGSS will combine the advantages of "active/freehand 3D navigation" with AR and RAS and will one day find its way into all aspects of spinal surgery, not only in instrumented procedures.

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.

Chinese Association for the Study of Pain: Experts consensus on ultrasound-guided injections for the treatment of spinal pain in China (2020 edition)

Spinal pain (SP) is a common condition that has a major negative impact on a patient’s quality of life. Recent developments in ultrasound-guided injections for the treatment of SP are increasingly being used in clinical practice. This clinical expert consensus describes the purpose, significance, implementation methods, indications, contraindications, and techniques of ultrasound-guided injections. This consensus offers a practical reference point for physicians to implement successfully ultrasound-guided injections in the treatment of chronic SP.

Evaluation of an Ultrasound-Based Navigation System for Spine Neurosurgery: A Porcine Cadaver Study

BACKGROUND

With the growing incidence of patients receiving surgical treatment for spinal metastatic tumours, there is a need for developing cost-efficient and radiation-free alternatives for spinal interventions. In this paper, we evaluate the capabilities and limitations of an image-guided neurosurgery (IGNS) system that uses intraoperative ultrasound (iUS) imaging for guidance.

METHODS

Using a lumbosacral section of a porcine cadaver, we explored the impact of CT image resolution, ultrasound depth and ultrasound frequency on system accuracy, robustness and effectiveness. Preoperative CT images with an isotropic resolution of , and were acquired. During surgery, vertebrae L1 to L6 were exposed. For each vertebra, five iUS scans were acquired using two depth parameters (5 cm and 7 cm) and two frequencies (6 MHz and 12 MHz). A total of 120 acquisition trials were evaluated. Ultrasound-based registration performance is compared to the standard alignment procedure using intraoperative CT. We report target registration error (TRE) and computation time. In addition, the scans' trajectories were analyzed to identify vertebral regions that provide the most relevant features for the alignment.

RESULTS

For all acquisitions, the median TRE ranged from 1.42 mm to 1.58 mm and the overall computation time was 9.04 s ± 1.58 s. Fourteen out of 120 iUS acquisitions (11.66%) yielded a level-to-level mismatch (and these are included in the accuracy measurements reported). No significant effect on accuracy was found with CT resolution (F (2,10) = 1.70, p = 0.232), depth (F (1,5) = 0.22, p= 0.659) nor frequency (F (1,5) = 1.02, p = 0.359). While misalignment increases linearly with the distance from the imaged vertebra, accuracy was satisfactory for directly adjacent levels. A significant relationship was found between iUS scan coverage of laminae and articular processes, and accuracy.

CONCLUSION

Intraoperative ultrasound can be used for spine surgery neuronavigation. We demonstrated that the IGNS system yield acceptable accuracy and high efficiency compared to the standard CT-based navigation procedure. The flexibility of the iUS acquisitions can have repercussions on the system performance, which are not fully identified. Further investigation is needed to understand the relationship between iUS acquisition and alignment performance.

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.