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Azampour MF, Tirindelli M, Lameski J, Gafencu M, Tagliabue E, Fatemizadeh E, Hacihaliloglu I, Navab N. Anatomy-aware computed tomography-to-ultrasound spine registration. Med Phys 2024; 51:2044-2056. [PMID: 37708456 DOI: 10.1002/mp.16731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 07/04/2023] [Accepted: 07/06/2023] [Indexed: 09/16/2023] Open
Abstract
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.
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Affiliation(s)
- Mohammad Farid Azampour
- Chair for Computer Aided Medical Procedures & Augmented Reality, Technical University of Munich, Munich, Bavaria, Germany
- Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran
| | - Maria Tirindelli
- Chair for Computer Aided Medical Procedures & Augmented Reality, Technical University of Munich, Munich, Bavaria, Germany
- ImFusion GmbH, Munich, Bavaria, Germany
| | - Jane Lameski
- Chair for Computer Aided Medical Procedures & Augmented Reality, Technical University of Munich, Munich, Bavaria, Germany
| | - Miruna Gafencu
- Chair for Computer Aided Medical Procedures & Augmented Reality, Technical University of Munich, Munich, Bavaria, Germany
| | | | - Emad Fatemizadeh
- Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran
- Department of Computer Science, University of Verona, Verona VR, Italy
| | - Ilker Hacihaliloglu
- Department of Radiology, Department of Medicine, University of British Columbia, Vancouver, Canada
| | - Nassir Navab
- Chair for Computer Aided Medical Procedures & Augmented Reality, Technical University of Munich, Munich, Bavaria, Germany
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Gueziri HE, Georgiopoulos M, Santaguida C, Collins DL. Ultrasound-based navigated pedicle screw insertion without intraoperative radiation: feasibility study on porcine cadavers. Spine J 2022; 22:1408-1417. [PMID: 35523390 DOI: 10.1016/j.spinee.2022.04.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 04/15/2022] [Accepted: 04/26/2022] [Indexed: 02/03/2023]
Abstract
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.
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Affiliation(s)
- Houssem-Eddine Gueziri
- McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, McGill University, 3801 University St, Montreal, Quebec, Canada.
| | - Miltiadis Georgiopoulos
- Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, 3801 University St, Montreal, Quebec, Canada
| | - Carlo Santaguida
- Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, 3801 University St, Montreal, Quebec, Canada
| | - D Louis Collins
- McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, McGill University, 3801 University St, Montreal, Quebec, Canada; Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, 3801 University St, Montreal, Quebec, Canada
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Cai Y, Wu S, Fan X, Olson J, Evans L, Lollis S, Mirza SK, Paulsen KD, Ji S. A level-wise spine registration framework to account for large pose changes. Int J Comput Assist Radiol Surg 2021; 16:943-953. [PMID: 33973113 PMCID: PMC8358825 DOI: 10.1007/s11548-021-02395-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Accepted: 04/29/2021] [Indexed: 11/27/2022]
Abstract
PURPOSES Accurate and efficient spine registration is crucial to success of spine image guidance. However, changes in spine pose cause intervertebral motion that can lead to significant registration errors. In this study, we develop a geometrical rectification technique via nonlinear principal component analysis (NLPCA) to achieve level-wise vertebral registration that is robust to large changes in spine pose. METHODS We used explanted porcine spines and live pigs to develop and test our technique. Each sample was scanned with preoperative CT (pCT) in an initial pose and rescanned with intraoperative stereovision (iSV) in a different surgical posture. Patient registration rectified arbitrary spinal postures in pCT and iSV into a common, neutral pose through a parameterized moving-frame approach. Topologically encoded depth projection 2D images were then generated to establish invertible point-to-pixel correspondences. Level-wise point correspondences between pCT and iSV vertebral surfaces were generated via 2D image registration. Finally, closed-form vertebral level-wise rigid registration was obtained by directly mapping 3D surface point pairs. Implanted mini-screws were used as fiducial markers to measure registration accuracy. RESULTS In seven explanted porcine spines and two live animal surgeries (maximum in-spine pose change of 87.5 mm and 32.7 degrees averaged from all spines), average target registration errors (TRE) of 1.70 ± 0.15 mm and 1.85 ± 0.16 mm were achieved, respectively. The automated spine rectification took 3-5 min, followed by an additional 30 secs for depth image projection and level-wise registration. CONCLUSIONS Accuracy and efficiency of the proposed level-wise spine registration support its application in human open spine surgeries. The registration framework, itself, may also be applicable to other intraoperative imaging modalities such as ultrasound and MRI, which may expand utility of the approach in spine registration in general.
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Affiliation(s)
- Yunliang Cai
- Worcester Polytechnic Institute, 100 Institute Rd, Worcester, MA, 01609, USA
| | - Shaoju Wu
- Worcester Polytechnic Institute, 100 Institute Rd, Worcester, MA, 01609, USA
| | - Xiaoyao Fan
- Dartmouth College Dartmouth-Hitchcock Medical Center, 1 Medical Center Dr, Lebanon, NH, 03766, USA
| | - Jonathan Olson
- Dartmouth College Dartmouth-Hitchcock Medical Center, 1 Medical Center Dr, Lebanon, NH, 03766, USA
| | - Linton Evans
- Dartmouth College Dartmouth-Hitchcock Medical Center, 1 Medical Center Dr, Lebanon, NH, 03766, USA
| | - Scott Lollis
- University of Vermont Medical Center, Burlington, VT, 05401, USA
| | - Sohail K Mirza
- Dartmouth College Dartmouth-Hitchcock Medical Center, 1 Medical Center Dr, Lebanon, NH, 03766, USA
| | - Keith D Paulsen
- Dartmouth College Dartmouth-Hitchcock Medical Center, 1 Medical Center Dr, Lebanon, NH, 03766, USA
| | - Songbai Ji
- Worcester Polytechnic Institute, 100 Institute Rd, Worcester, MA, 01609, USA.
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Gueziri HE, Santaguida C, Collins DL. The state-of-the-art in ultrasound-guided spine interventions. Med Image Anal 2020; 65:101769. [PMID: 32668375 DOI: 10.1016/j.media.2020.101769] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2019] [Revised: 06/23/2020] [Accepted: 06/25/2020] [Indexed: 02/07/2023]
Abstract
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.
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Affiliation(s)
- Houssem-Eddine Gueziri
- McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, Montreal (QC), Canada; McGill University, Montreal (QC), Canada.
| | - Carlo Santaguida
- Department of Neurology and Neurosurgery, McGill University Health Center, Montreal (QC), Canada
| | - D Louis Collins
- McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, Montreal (QC), Canada; McGill University, Montreal (QC), Canada
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Porto LR, Tang R, Sawka A, Lessoway V, Anas EMA, Behnami D, Abolmaesumi P, Rohling R. Comparison of Patient Position and Midline Lumbar Neuraxial Access Via Statistical Model Registration to Ultrasound. ULTRASOUND IN MEDICINE & BIOLOGY 2019; 45:255-263. [PMID: 30292460 DOI: 10.1016/j.ultrasmedbio.2018.08.016] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/18/2018] [Revised: 08/09/2018] [Accepted: 08/20/2018] [Indexed: 06/08/2023]
Abstract
Patient positioning and needle puncture site are important for lumbar neuraxial anesthesia. We sought to identify optimal patient positioning and puncture sites with a novel ultrasound registration. We registered a statistical model to volumetric ultrasound data acquired from volunteers (n = 10) in three positions: (i) prone; (ii) seated with thoracic and lumbar flexion; and (iii) seated as in position ii, with a 10° dorsal tilt. We determined injection target size and penetration success by simulating lumbar injections on validated registered models. Injection window and target area sizes in seated positions were significantly larger than those in prone positions by 65% in L2-3 and 130% in L3-4; a 10° tilt had no significant effect on target sizes between seated positions. In agreement with computed tomography studies, simulated L2-3 and L3-4 injections had the highest success at the 50% and 75% midline puncture sites, respectively, measured from superior to inferior spinous process. We conclude that our registration to ultrasound technique is a potential tool for tolerable determination of puncture site success in vivo.
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Affiliation(s)
- Lucas Resque Porto
- Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, Canada.
| | - Raymond Tang
- Department of Anesthesiology, Vancouver General Hospital, Vancouver, Canada
| | - Andrew Sawka
- Department of Anesthesiology, Vancouver General Hospital, Vancouver, Canada
| | | | - Emran Mohammad Abu Anas
- Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, Canada
| | - Delaram Behnami
- Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, Canada
| | - Purang Abolmaesumi
- Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, Canada
| | - Robert Rohling
- Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, Canada
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Shajudeen PMS, Righetti R. Spine surface detection from local phase‐symmetry enhanced ridges in ultrasound images. Med Phys 2017; 44:5755-5767. [DOI: 10.1002/mp.12509] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2017] [Revised: 05/29/2017] [Accepted: 06/23/2017] [Indexed: 11/08/2022] Open
Affiliation(s)
| | - Raffaella Righetti
- Department of Electrical and Computer Engineering Texas A&M University College Station TX 77840 USA
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Ebrahim FH, Ruellas ACO, Paniagua B, Benavides E, Jepsen K, Wolford L, Goncalves JR, Cevidanes LHS. Accuracy of biomarkers obtained from cone beam computed tomography in assessing the internal trabecular structure of the mandibular condyle. Oral Surg Oral Med Oral Pathol Oral Radiol 2017; 124:588-599. [PMID: 29055644 DOI: 10.1016/j.oooo.2017.08.013] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2017] [Revised: 08/03/2017] [Accepted: 08/12/2017] [Indexed: 11/17/2022]
Abstract
OBJECTIVE The aim of this study was to validate the ability of cone beam computed tomography (CBCT) to measure condylar internal trabecular bone structure and bone texture parameters accurately. STUDY DESIGN Sixteen resected condyles of individuals undergoing temporomandibular joint replacement were collected and used as samples. These condyles were then radiographically imaged by using clinically oriented dental CBCT and research oriented micro-computed tomography (micro-CT). The CBCT scans were then compared with the gold standard micro-CT scans in terms of 21 bone imaging parameters. Descriptive histologic investigation of the specimens was also performed. RESULTS Significant correlations were found for several imaging parameters between the CBCT and micro-CT images, including trabecular thickness (r = 0.92), trabecular separation (r = 0.78), bone volume (r = 0.90), bone surface area (r = 0.79), and degree of anisotropy measurements (r = 0.77). CONCLUSIONS Measurements of trabecular thickness, trabecular separation, bone volume, bone surface area, and degree of anisotropy obtained from high-resolution dental CBCT images may be suitable bone imaging biomarkers that can be utilized clinically and in future research.
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Affiliation(s)
- Fouad H Ebrahim
- School of Dentistry, University of Michigan, Ann Arbor, MI, USA
| | - Antonio C O Ruellas
- School of Dentistry, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil; Department of Pediatric Dentistry and Orthodontics, Visiting Post-doctoral Scholar, School of Dentistry, University of Michigan, Ann Arbor, MI, USA.
| | | | - Erika Benavides
- School of Dentistry, University of Michigan, Ann Arbor, MI, USA
| | - Karl Jepsen
- Biomedical Sciences Research Building, University of Michigan, Ann Arbor, MI, USA
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A Review on Real-Time 3D Ultrasound Imaging Technology. BIOMED RESEARCH INTERNATIONAL 2017; 2017:6027029. [PMID: 28459067 PMCID: PMC5385255 DOI: 10.1155/2017/6027029] [Citation(s) in RCA: 99] [Impact Index Per Article: 14.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/09/2016] [Accepted: 03/07/2017] [Indexed: 01/06/2023]
Abstract
Real-time three-dimensional (3D) ultrasound (US) has attracted much more attention in medical researches because it provides interactive feedback to help clinicians acquire high-quality images as well as timely spatial information of the scanned area and hence is necessary in intraoperative ultrasound examinations. Plenty of publications have been declared to complete the real-time or near real-time visualization of 3D ultrasound using volumetric probes or the routinely used two-dimensional (2D) probes. So far, a review on how to design an interactive system with appropriate processing algorithms remains missing, resulting in the lack of systematic understanding of the relevant technology. In this article, previous and the latest work on designing a real-time or near real-time 3D ultrasound imaging system are reviewed. Specifically, the data acquisition techniques, reconstruction algorithms, volume rendering methods, and clinical applications are presented. Moreover, the advantages and disadvantages of state-of-the-art approaches are discussed in detail.
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