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Wang Y, Fu T, Wu C, Xiao J, Fan J, Song H, Liang P, Yang J. Multimodal registration of ultrasound and MR images using weighted self-similarity structure vector. Comput Biol Med 2023; 155:106661. [PMID: 36827789 DOI: 10.1016/j.compbiomed.2023.106661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 01/22/2023] [Accepted: 02/09/2023] [Indexed: 02/12/2023]
Abstract
PROPOSE Multimodal registration of 2D Ultrasound (US) and 3D Magnetic Resonance (MR) for fusion navigation can improve the intraoperative detection accuracy of lesion. However, multimodal registration remains a challenge because of the poor US image quality. In the study, a weighted self-similarity structure vector (WSSV) is proposed to registrate multimodal images. METHOD The self-similarity structure vector utilizes the normalized distance of symmetrically located patches in the neighborhood to describe the local structure information. The texture weights are extracted using the local standard deviation to reduce the speckle interference in the US images. The multimodal similarity metric is constructed by combining a self-similarity structure vector with a texture weight map. RESULTS Experiments were performed on US and MR images of the liver from 88 groups of data including 8 patients and 80 simulated samples. The average target registration error was reduced from 14.91 ± 3.86 mm to 4.95 ± 2.23 mm using the WSSV-based method. CONCLUSIONS The experimental results show that the WSSV-based registration method could robustly align the US and MR images of the liver. With further acceleration, the registration framework can be potentially applied in time-sensitive clinical settings, such as US-MR image registration in image-guided surgery.
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Affiliation(s)
- Yifan Wang
- Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, PR China
| | - Tianyu Fu
- School of Medical Technology, Beijing Institute of Technology, Beijing, 100081, PR China.
| | - Chan Wu
- Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, PR China
| | - Jian Xiao
- School of Medical Technology, Beijing Institute of Technology, Beijing, 100081, PR China
| | - Jingfan Fan
- Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, PR China
| | - Hong Song
- School of Software, Beijing Institute of Technology, Beijing, 100081, PR China
| | - Ping Liang
- Department of Interventional Ultrasound, Chinese PLA General Hospital, Beijing, 100853, PR China.
| | - Jian Yang
- Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, PR China.
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Peng C, Cai Q, Chen M, Jiang X. Recent Advances in Tracking Devices for Biomedical Ultrasound Imaging Applications. MICROMACHINES 2022; 13:mi13111855. [PMID: 36363876 PMCID: PMC9695235 DOI: 10.3390/mi13111855] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/08/2022] [Revised: 10/26/2022] [Accepted: 10/27/2022] [Indexed: 05/27/2023]
Abstract
With the rapid advancement of tracking technologies, the applications of tracking systems in ultrasound imaging have expanded across a wide range of fields. In this review article, we discuss the basic tracking principles, system components, performance analyses, as well as the main sources of error for popular tracking technologies that are utilized in ultrasound imaging. In light of the growing demand for object tracking, this article explores both the potential and challenges associated with different tracking technologies applied to various ultrasound imaging applications, including freehand 3D ultrasound imaging, ultrasound image fusion, ultrasound-guided intervention and treatment. Recent development in tracking technology has led to increased accuracy and intuitiveness of ultrasound imaging and navigation with less reliance on operator skills, thereby benefiting the medical diagnosis and treatment. Although commercially available tracking systems are capable of achieving sub-millimeter resolution for positional tracking and sub-degree resolution for orientational tracking, such systems are subject to a number of disadvantages, including high costs and time-consuming calibration procedures. While some emerging tracking technologies are still in the research stage, their potentials have been demonstrated in terms of the compactness, light weight, and easy integration with existing standard or portable ultrasound machines.
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Affiliation(s)
- Chang Peng
- School of Biomedical Engineering, ShanghaiTech University, Shanghai 201210, China
| | - Qianqian Cai
- Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC 27695, USA
| | - Mengyue Chen
- Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC 27695, USA
| | - Xiaoning Jiang
- Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC 27695, USA
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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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4
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Shapey J, Dowrick T, Delaunay R, Mackle EC, Thompson S, Janatka M, Guichard R, Georgoulas A, Pérez-Suárez D, Bradford R, Saeed SR, Ourselin S, Clarkson MJ, Vercauteren T. Integrated multi-modality image-guided navigation for neurosurgery: open-source software platform using state-of-the-art clinical hardware. Int J Comput Assist Radiol Surg 2021; 16:1347-1356. [PMID: 33937966 PMCID: PMC8295168 DOI: 10.1007/s11548-021-02374-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Accepted: 04/08/2021] [Indexed: 01/19/2023]
Abstract
PURPOSE Image-guided surgery (IGS) is an integral part of modern neuro-oncology surgery. Navigated ultrasound provides the surgeon with reconstructed views of ultrasound data, but no commercial system presently permits its integration with other essential non-imaging-based intraoperative monitoring modalities such as intraoperative neuromonitoring. Such a system would be particularly useful in skull base neurosurgery. METHODS We established functional and technical requirements of an integrated multi-modality IGS system tailored for skull base surgery with the ability to incorporate: (1) preoperative MRI data and associated 3D volume reconstructions, (2) real-time intraoperative neurophysiological data and (3) live reconstructed 3D ultrasound. We created an open-source software platform to integrate with readily available commercial hardware. We tested the accuracy of the system's ultrasound navigation and reconstruction using a polyvinyl alcohol phantom model and simulated the use of the complete navigation system in a clinical operating room using a patient-specific phantom model. RESULTS Experimental validation of the system's navigated ultrasound component demonstrated accuracy of [Formula: see text] and a frame rate of 25 frames per second. Clinical simulation confirmed that system assembly was straightforward, could be achieved in a clinically acceptable time of [Formula: see text] and performed with a clinically acceptable level of accuracy. CONCLUSION We present an integrated open-source research platform for multi-modality IGS. The present prototype system was tailored for neurosurgery and met all minimum design requirements focused on skull base surgery. Future work aims to optimise the system further by addressing the remaining target requirements.
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Affiliation(s)
- Jonathan Shapey
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK. .,Wellcome/EPSRC Centre for Interventional and Surgical Sciences, UCL, London, UK. .,Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK.
| | - Thomas Dowrick
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, UCL, London, UK.,Centre for Medical Image Computing, UCL, London, UK.,Department of Medical Physics and Biomedical Engineering, UCL, London, UK
| | - Rémi Delaunay
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, UCL, London, UK
| | - Eleanor C Mackle
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, UCL, London, UK
| | - Stephen Thompson
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, UCL, London, UK.,Centre for Medical Image Computing, UCL, London, UK.,Department of Medical Physics and Biomedical Engineering, UCL, London, UK
| | - Mirek Janatka
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, UCL, London, UK.,Centre for Medical Image Computing, UCL, London, UK.,Department of Medical Physics and Biomedical Engineering, UCL, London, UK
| | - Roland Guichard
- Research Software Development Group, Research IT Services, UCL, London, UK
| | | | - David Pérez-Suárez
- Research Software Development Group, Research IT Services, UCL, London, UK
| | - Robert Bradford
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - Shakeel R Saeed
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK.,The Ear Institute, UCL, London, UK.,The Royal National Throat, Nose and Ear Hospital, London, UK
| | - Sébastien Ourselin
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Matthew J Clarkson
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, UCL, London, UK.,Centre for Medical Image Computing, UCL, London, UK.,Department of Medical Physics and Biomedical Engineering, UCL, London, UK
| | - Tom Vercauteren
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
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Gueziri HE, Rabau O, Santaguida C, Collins DL. Evaluation of an Ultrasound-Based Navigation System for Spine Neurosurgery: A Porcine Cadaver Study. Front Oncol 2021; 11:619204. [PMID: 33763355 PMCID: PMC7982867 DOI: 10.3389/fonc.2021.619204] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Accepted: 01/18/2021] [Indexed: 11/13/2022] Open
Abstract
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.
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Affiliation(s)
- Houssem-Eddine Gueziri
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Oded Rabau
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Carlo Santaguida
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - D. Louis Collins
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
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Chel H, Bora PK, Ramchiary KK. A fast technique for hyper-echoic region separation from brain ultrasound images using patch based thresholding and cubic B-spline based contour smoothing. ULTRASONICS 2021; 111:106304. [PMID: 33360770 DOI: 10.1016/j.ultras.2020.106304] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Revised: 11/14/2020] [Accepted: 11/14/2020] [Indexed: 06/12/2023]
Abstract
Ultrasound image guided brain surgery (UGBS) requires an automatic and fast image segmentation method. The level-set and active contour based algorithms have been found to be useful for obtaining topology-independent boundaries between different image regions. But slow convergence limits their use in online US image segmentation. The performance of these algorithms deteriorates on US images because of the intensity inhomogeneity. This paper proposes an effective region-driven method for the segmentation of hyper-echoic (HE) regions suppressing the hypo-echoic and anechoic regions in brain US images. An automatic threshold estimation scheme is developed with a modified Niblack's approach. The separation of the hyper-echoic and non-hyper-echoic (NHE) regions is performed by successively applying patch based intensity thresholding and boundary smoothing. First, a patch based segmentation is performed, which separates roughly the two regions. The patch based approach in this process reduces the effect of intensity heterogeneity within an HE region. An iterative boundary correction step with reducing patch size improves further the regional topology and refines the boundary regions. For avoiding the slope and curvature discontinuities and obtaining distinct boundaries between HE and NHE regions, a cubic B-spline model of curve smoothing is applied. The proposed method is 50-100 times faster than the other level-set based image segmentation algorithms. The segmentation performance and the convergence speed of the proposed method are compared with four other competing level-set based algorithms. The computational results show that the proposed segmentation approach outperforms other level-set based techniques both subjectively and objectively.
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Affiliation(s)
- Haradhan Chel
- Department of Electronics and Communication, Central Institute of Technology Kokrajhar, Assam 783370, India; City Clinic and Research Centre, Kokrajhar, Assam, India.
| | - P K Bora
- Department of EEE, Indian Institute of Technology Guwahati, Assam, India.
| | - K K Ramchiary
- City Clinic and Research Centre, Kokrajhar, Assam, India.
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Gueziri HE, Yan CXB, Collins DL. Open-source software for ultrasound-based guidance in spinal fusion surgery. ULTRASOUND IN MEDICINE & BIOLOGY 2020; 46:3353-3368. [PMID: 32907772 DOI: 10.1016/j.ultrasmedbio.2020.08.005] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/11/2020] [Revised: 07/10/2020] [Accepted: 08/05/2020] [Indexed: 06/11/2023]
Abstract
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.
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Affiliation(s)
- Houssem-Eddine Gueziri
- McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada.
| | - Charles X B Yan
- Joint Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada
| | - D Louis Collins
- McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
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Abstract
This article discusses intraoperative imaging techniques used during high-grade glioma surgery. Gliomas can be difficult to differentiate from surrounding tissue during surgery. Intraoperative imaging helps to alleviate problems encountered during glioma surgery, such as brain shift and residual tumor. There are a variety of modalities available all of which aim to give the surgeon more information, address brain shift, identify residual tumor, and increase the extent of surgical resection. The article starts with a brief introduction followed by a review of with the latest advances in intraoperative ultrasound, intraoperative MRI, and intraoperative computed tomography.
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Affiliation(s)
- Thomas Noh
- Department of Neurosurgery, Brigham and Women's Hospital, 75 Francis Street, Boston, MA 02115, USA; Hawaii Pacific Health, John A Burns School of Medicine, Honolulu, Hawaii, USA
| | - Martina Mustroph
- Department of Neurosurgery, Brigham and Women's Hospital, 75 Francis Street, Boston, MA 02115, USA; Harvard Medical School, Boston, Massachusetts, USA
| | - Alexandra J Golby
- Department of Neurosurgery, Brigham and Women's Hospital, 75 Francis Street, Boston, MA 02115, USA; Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA.
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Abstract
In neurosurgery, the extent of resection plays a critical role, especially in the management of malignant gliomas. These tumors are characterized through a diffuse infiltration into the surrounding brain parenchyma. Delineation between tumor and normal brain parenchyma can therefore often be challenging. During the recent years, several techniques, aiming at better intraoperative tumor visualization, have been developed and implemented in the field of brain tumor surgery. In this chapter, we discuss current strategies for intraoperative imaging in brain tumor surgery, comprising conventional techniques such as neuronavigation, techniques using fluorescence-guided surgery, and further highly precise developments such as targeted fluorescence spectroscopy or Raman spectroscopy.
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Affiliation(s)
- Stephanie Schipmann-Miletić
- Department of Neurosurgery, University Hospital Münster, Albert-Schweitzer-Campus 1, Building A1, 48149, Münster, Germany.
| | - Walter Stummer
- Department of Neurosurgery, University Hospital Münster, Albert-Schweitzer-Campus 1, Building A1, 48149, Münster, Germany
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Enhanced Regional Functional Connectivity Indicates Seizure Onset Zone. Brain Topogr 2020; 33:545-557. [PMID: 32419099 DOI: 10.1007/s10548-020-00775-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Accepted: 05/11/2020] [Indexed: 02/01/2023]
Abstract
This project aims to explore if stronger functional connectivity (FC) exists in the maximal BOLD response of EEG/fMRI analysis when it is concordant with seizure-onset-zone (SOZ). Twenty-six patients with drug-resistant focal epilepsy who had an EEG/fMRI and later underwent stereo-EEG implantation were included. Different types of IEDs were labeled in scalp EEG and IED-related maximal BOLD responses were evaluated separately, each constituting one study. After evaluating concordance between maximal BOLD and SOZ, twenty-seven studies were placed in the concordant group and eight in the discordant group. We evaluated the local connectivity and ipsilaterally distant connectivity difference between the maximal BOLD and the contralateral homotopic region. Significantly stronger local FC was found for the maximal BOLD in the concordant group (p < 0.05, Bonferroni corrected). 52% of the studies in the concordant group and 13% in the discordant group had a significant difference compared to healthy subjects (p < 0.05, uncorrected). The finding suggests that, when concordant with the SOZ, the maximal BOLD is more likely to have stronger local FC compared to its contralateral counterpart. This asymmetry in functional connectivity may help to noninvasively improve the specificity of EEG/fMRI analysis.
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Machado I, Toews M, George E, Unadkat P, Essayed W, Luo J, Teodoro P, Carvalho H, Martins J, Golland P, Pieper S, Frisken S, Golby A, Wells Iii W, Ou Y. Deformable MRI-Ultrasound registration using correlation-based attribute matching for brain shift correction: Accuracy and generality in multi-site data. Neuroimage 2019; 202:116094. [PMID: 31446127 PMCID: PMC6819249 DOI: 10.1016/j.neuroimage.2019.116094] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Revised: 07/18/2019] [Accepted: 08/09/2019] [Indexed: 11/16/2022] Open
Abstract
Intraoperative tissue deformation, known as brain shift, decreases the benefit of using preoperative images to guide neurosurgery. Non-rigid registration of preoperative magnetic resonance (MR) to intraoperative ultrasound (iUS) has been proposed as a means to compensate for brain shift. We focus on the initial registration from MR to predurotomy iUS. We present a method that builds on previous work to address the need for accuracy and generality of MR-iUS registration algorithms in multi-site clinical data. High-dimensional texture attributes were used instead of image intensities for image registration and the standard difference-based attribute matching was replaced with correlation-based attribute matching. A strategy that deals explicitly with the large field-of-view mismatch between MR and iUS images was proposed. Key parameters were optimized across independent MR-iUS brain tumor datasets acquired at 3 institutions, with a total of 43 tumor patients and 758 reference landmarks for evaluating the accuracy of the proposed algorithm. Despite differences in imaging protocols, patient demographics and landmark distributions, the algorithm is able to reduce landmark errors prior to registration in three data sets (5.37±4.27, 4.18±1.97 and 6.18±3.38 mm, respectively) to a consistently low level (2.28±0.71, 2.08±0.37 and 2.24±0.78 mm, respectively). This algorithm was tested against 15 other algorithms and it is competitive with the state-of-the-art on multiple datasets. We show that the algorithm has one of the lowest errors in all datasets (accuracy), and this is achieved while sticking to a fixed set of parameters for multi-site data (generality). In contrast, other algorithms/tools of similar performance need per-dataset parameter tuning (high accuracy but lower generality), and those that stick to fixed parameters have larger errors or inconsistent performance (generality but not the top accuracy). Landmark errors were further characterized according to brain regions and tumor types, a topic so far missing in the literature.
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Affiliation(s)
- Inês Machado
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Mechanical Engineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal.
| | - Matthew Toews
- Department of Systems Engineering, École de Technologie Supérieure, Montreal, Canada
| | - Elizabeth George
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Prashin Unadkat
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Walid Essayed
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jie Luo
- Graduate School of Frontier Sciences, University of Tokyo, Tokyo, Japan
| | - Pedro Teodoro
- Escola Superior Náutica Infante D. Henrique, Lisbon, Portugal
| | - Herculano Carvalho
- Department of Neurosurgery, Hospital de Santa Maria, CHLN, Lisbon, Portugal
| | - Jorge Martins
- Department of Mechanical Engineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Polina Golland
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA, USA
| | - Steve Pieper
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Isomics, Inc., Cambridge, MA, USA
| | - Sarah Frisken
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Alexandra Golby
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - William Wells Iii
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA, USA
| | - Yangming Ou
- Department of Pediatrics and Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
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Su J, Khoo HM, von Ellenrieder N, Zeng LL, Hu D, Dubeau F, Gotman J. fMRI functional connectivity as an indicator of interictal epileptic discharges. NEUROIMAGE-CLINICAL 2019; 24:102038. [PMID: 31734531 PMCID: PMC6861611 DOI: 10.1016/j.nicl.2019.102038] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Revised: 10/02/2019] [Accepted: 10/15/2019] [Indexed: 11/26/2022]
Abstract
Functional connectivity to successful EEG/fMRI response indicates higher IED rates. The results hold when correcting for distance to maximum EEG-fMRI and laterality. Intracranial IED rates correlate with functional connectivity to EEG/fMRI maxima. Results suggest it is feasible to non-invasively infer the brain regions with IEDs.
Objective To explore the relationship between functional connectivity and presence of interictal epileptic discharges (IEDs) in different brain regions in intracranial EEG (iEEG). Methods We studied 38 focal epilepsy patients who underwent simultaneous EEG/fMRI scanning and subsequent intracerebral stereo-EEG investigation. In EEG/fMRI analysis, IEDs with different spatial distributions were considered independent studies and IED-related maximal BOLD responses were evaluated. Studies with iEEG electrodes inside the maximal responses were selected and divided into three groups: Studies with 1. distinct maximal BOLD highly concordant with seizure-onset-zone (SOZ); 2. Moderate maximal BOLD concordant with SOZ; 3. maximal BOLD discordant with SOZ. Using maximal BOLD as seed, its functionally connected zone (FCZ) was determined. IED rates in iEEG channels inside and outside the FCZ were compared in the three groups. The effect of laterality and distance between channels and maximal BOLD, and correlation between functional connectivity values and IED rates were analyzed. Results Thirty-six studies in 25 patients were included. IED rates of intracranial EEG channels inside the FCZ were significantly higher than outside in Group 1 (p = 2.6×10−6) and Group 2 (p = 1.2×10−3) and the inside-outside difference remained after regressing distance and laterality factors. In Group 1, connectivity values were significantly correlated with IED rates in channels inside the FCZ (p < 0.05). Significance Our results indicate a higher probability of finding intracranial IEDs in the FCZ of SOZ-concordant maximal BOLD responses than in other regions, regardless of distance and laterality. In studies with distinct maximal BOLD, connectivity values can partially predict IED rates in intracranial EEG. It is thus feasible to non-invasively delineate brain regions that are likely to have high IED rates.
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Affiliation(s)
- Jianpo Su
- Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada; College of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan, China.
| | - Hui Ming Khoo
- Department of Neurosurgery, Osaka University Graduate School of Medicine, Suita, Japan
| | | | - Ling-Li Zeng
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan, China
| | - Dewen Hu
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan, China
| | - François Dubeau
- Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Jean Gotman
- Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
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Khoo HM, von Ellenrieder N, Zazubovits N, Hall JA, Dubeau F, Gotman J. Internodular functional connectivity in heterotopia-related epilepsy. Ann Clin Transl Neurol 2019; 6:1010-1023. [PMID: 31211165 PMCID: PMC6562032 DOI: 10.1002/acn3.769] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Accepted: 03/05/2019] [Indexed: 11/13/2022] Open
Abstract
Objective A vast network involving the nodules and overlying cortices is believed to be responsible for the epileptogenicity in gray matter heterotopia with multiple nodules, which often associated with difficult‐to‐treat epilepsy. We sought to determine if functional magnetic resonance imaging (fMRI) could detect internodular functional connectivity (FC), and if this connectivity reflects an actual synchronized neuronal activity and partakes in epileptogenicity. Methods We studied 16 epilepsy patients with multiple heterotopic nodules; eight underwent subsequent intracerebral EEG. We examined the internodular FC using fMRI and its correspondence with internodular synchrony of intracerebral interictal activity. We then compared the spreading speed of ictal activity between connected and unconnected nodules; and the FC among possible combinations of nodule pairs in terms of their involvement at seizure onset. Results Seventy nodules were studied: 83% have significant connection to at least one other nodule. Among the 49 pairs studied with intracerebral EEG, (1) synchronized interictal activity is more prevalent in fMRI‐connected pairs (P < 0.05), (2) ictal activity spreads faster between connected pairs (P < 0.0001), and (3) stronger FC was observed between pairs in which both nodules were involved at seizure onset (P < 0.01). Interpretation fMRI could reliably and noninvasively detect the FC between heterotopic nodules. These functional connections correspond to the synchrony of interictal epileptic activity between the nodules and to the ability of nodules to generate synchronous seizure onsets or rapid seizure spread. These findings may help in understanding the complexity of the epileptogenic network in multiple heterotopic nodules and better targeting the likely epileptogenic nodules.
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Affiliation(s)
- Hui Ming Khoo
- Montreal Neurological Institute and Hospital McGill University Montreal Quebec Canada.,Department of Neurosurgery Osaka University Graduate School of Medicine Suita Japan
| | | | - Natalja Zazubovits
- Montreal Neurological Institute and Hospital McGill University Montreal Quebec Canada
| | - Jeffery A Hall
- Montreal Neurological Institute and Hospital McGill University Montreal Quebec Canada
| | - François Dubeau
- Montreal Neurological Institute and Hospital McGill University Montreal Quebec Canada
| | - Jean Gotman
- Montreal Neurological Institute and Hospital McGill University Montreal Quebec Canada
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Khoo HM, von Ellenrieder N, Zazubovits N, He D, Dubeau F, Gotman J. The spike onset zone: The region where epileptic spikes start and from where they propagate. Neurology 2018; 91:e666-e674. [PMID: 30006411 DOI: 10.1212/wnl.0000000000005998] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2017] [Accepted: 05/11/2018] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To determine whether the maximum hemodynamic response to scalp interictal epileptic discharges (IEDs) corresponds to the region where IEDs originate and from where they propagate. METHODS We studied 19 patients who underwent first an EEG-fMRI showing responses in the gray matter, and then intracranial EEG (iEEG). We coregistered the hemodynamic responses to the iEEG electrode contacts and analyzed IEDs in the iEEG channel adjacent to a maximum response (labeled the main channel), in relation to IEDs in other channels during a widespread intracranial IED event. IEDs in the main channel were aligned at their peak, and IEDs in each channel were averaged time-locked to these instants. The beginning and peak of IEDs in the averaged trace were identified, blinded to the identity of the main channel. The latency of IEDs was computed between the earliest and all other channels. RESULTS The median latency of IEDs in the main channel was significantly smaller than in other channels for either the peak (15.5 vs 67.5 milliseconds, p = 0.00037) or the beginning (46.5 vs 118.4 milliseconds, p = 0.000048). The latency of IED was significantly correlated to the distance from the maximum hemodynamic response (p < 0.0001 for either the peak or the beginning). CONCLUSION IED adjacent to a maximum hemodynamic response, which often corresponds to the seizure onset zone, is more likely to precede IEDs in remote locations during a widespread intracranial discharge. Thus, EEG-fMRI is a unique noninvasive method to reveal the origin of IEDs, which we propose to label the spike onset zone.
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Affiliation(s)
- Hui Ming Khoo
- From the Montreal Neurological Institute and Hospital (H.M.K., N.v.E., N.Z., D.H., F.D., J.G.), McGill University, Montreal, Canada; and Department of Neurosurgery (H.M.K.), Osaka University Graduate School of Medicine, Suita, Japan.
| | - Nicolás von Ellenrieder
- From the Montreal Neurological Institute and Hospital (H.M.K., N.v.E., N.Z., D.H., F.D., J.G.), McGill University, Montreal, Canada; and Department of Neurosurgery (H.M.K.), Osaka University Graduate School of Medicine, Suita, Japan
| | - Natalja Zazubovits
- From the Montreal Neurological Institute and Hospital (H.M.K., N.v.E., N.Z., D.H., F.D., J.G.), McGill University, Montreal, Canada; and Department of Neurosurgery (H.M.K.), Osaka University Graduate School of Medicine, Suita, Japan
| | - Daniel He
- From the Montreal Neurological Institute and Hospital (H.M.K., N.v.E., N.Z., D.H., F.D., J.G.), McGill University, Montreal, Canada; and Department of Neurosurgery (H.M.K.), Osaka University Graduate School of Medicine, Suita, Japan
| | - François Dubeau
- From the Montreal Neurological Institute and Hospital (H.M.K., N.v.E., N.Z., D.H., F.D., J.G.), McGill University, Montreal, Canada; and Department of Neurosurgery (H.M.K.), Osaka University Graduate School of Medicine, Suita, Japan
| | - Jean Gotman
- From the Montreal Neurological Institute and Hospital (H.M.K., N.v.E., N.Z., D.H., F.D., J.G.), McGill University, Montreal, Canada; and Department of Neurosurgery (H.M.K.), Osaka University Graduate School of Medicine, Suita, Japan
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Gerard IJ, Kersten-Oertel M, Drouin S, Hall JA, Petrecca K, De Nigris D, Di Giovanni DA, Arbel T, Collins DL. Combining intraoperative ultrasound brain shift correction and augmented reality visualizations: a pilot study of eight cases. J Med Imaging (Bellingham) 2018; 5:021210. [PMID: 29392162 DOI: 10.1117/1.jmi.5.2.021210] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2017] [Accepted: 01/08/2018] [Indexed: 11/14/2022] Open
Abstract
We present our work investigating the feasibility of combining intraoperative ultrasound for brain shift correction and augmented reality (AR) visualization for intraoperative interpretation of patient-specific models in image-guided neurosurgery (IGNS) of brain tumors. We combine two imaging technologies for image-guided brain tumor neurosurgery. Throughout surgical interventions, AR was used to assess different surgical strategies using three-dimensional (3-D) patient-specific models of the patient's cortex, vasculature, and lesion. Ultrasound imaging was acquired intraoperatively, and preoperative images and models were registered to the intraoperative data. The quality and reliability of the AR views were evaluated with both qualitative and quantitative metrics. A pilot study of eight patients demonstrates the feasible combination of these two technologies and their complementary features. In each case, the AR visualizations enabled the surgeon to accurately visualize the anatomy and pathology of interest for an extended period of the intervention. Inaccuracies associated with misregistration, brain shift, and AR were improved in all cases. These results demonstrate the potential of combining ultrasound-based registration with AR to become a useful tool for neurosurgeons to improve intraoperative patient-specific planning by improving the understanding of complex 3-D medical imaging data and prolonging the reliable use of IGNS.
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Affiliation(s)
- Ian J Gerard
- McGill University, Montreal Neurological Institute and Hospital, Department of Biomedical Engineering, Montreal, Québec, Canada
| | - Marta Kersten-Oertel
- Concordia University, PERFORM Centre, Department of Computer Science and Software Engineering, Montreal, Québec, Canada
| | - Simon Drouin
- McGill University, Montreal Neurological Institute and Hospital, Department of Biomedical Engineering, Montreal, Québec, Canada
| | - Jeffery A Hall
- McGill University, Montreal Neurological Institute and Hospital, Department of Neurology and Neurosurgery, Montreal, Québec, Canada
| | - Kevin Petrecca
- McGill University, Montreal Neurological Institute and Hospital, Department of Neurology and Neurosurgery, Montreal, Québec, Canada
| | - Dante De Nigris
- McGill University, Centre for Intelligent Machines, Department of Electrical and Computer Engineering, Montreal, Québec, Canada
| | - Daniel A Di Giovanni
- McGill University, Montreal Neurological Institute and Hospital, Department of Neurology and Neurosurgery, Montreal, Québec, Canada
| | - Tal Arbel
- McGill University, Centre for Intelligent Machines, Department of Electrical and Computer Engineering, Montreal, Québec, Canada
| | - D Louis Collins
- McGill University, Montreal Neurological Institute and Hospital, Department of Biomedical Engineering, Montreal, Québec, Canada.,McGill University, Montreal Neurological Institute and Hospital, Department of Neurology and Neurosurgery, Montreal, Québec, Canada.,McGill University, Centre for Intelligent Machines, Department of Electrical and Computer Engineering, Montreal, Québec, Canada
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Wen T, Yang F, Gu J, Chen S, Wang L, Xie Y. An adaptive kernel regression method for 3D ultrasound reconstruction using speckle prior and parallel GPU implementation. Neurocomputing 2018. [DOI: 10.1016/j.neucom.2017.06.014] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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17
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Mozaffari MH, Lee WS. Freehand 3-D Ultrasound Imaging: A Systematic Review. ULTRASOUND IN MEDICINE & BIOLOGY 2017; 43:2099-2124. [PMID: 28716431 DOI: 10.1016/j.ultrasmedbio.2017.06.009] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2017] [Revised: 06/01/2017] [Accepted: 06/05/2017] [Indexed: 05/20/2023]
Abstract
Two-dimensional ultrasound (US) imaging has been successfully used in clinical applications as a low-cost, portable and non-invasive image modality for more than three decades. Recent advances in computer science and technology illustrate the promise of the 3-D US modality as a medical imaging technique that is comparable to other prevalent modalities and that overcomes certain drawbacks of 2-D US. This systematic review covers freehand 3-D US imaging between 1970 and 2017, highlighting the current trends in research fields, the research methods, the main limitations, the leading researchers, standard assessment criteria and clinical applications. Freehand 3-D US systems are more prevalent in the academic environment, whereas in clinical applications and industrial research, most studies have focused on 3-D US transducers and improvement of hardware performance. This topic is still an interesting active area for researchers, and there remain many unsolved problems to be addressed.
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Affiliation(s)
- Mohammad Hamed Mozaffari
- School of Electrical Engineering and Computer Science (EECS), University of Ottawa, Ottawa, Ontario, Canada.
| | - Won-Sook Lee
- School of Electrical Engineering and Computer Science (EECS), University of Ottawa, Ottawa, Ontario, Canada
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18
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Khoo HM, von Ellenrieder N, Zazubovits N, Dubeau F, Gotman J. Epileptic networks in action: Synchrony between distant hemodynamic responses. Ann Neurol 2017; 82:57-66. [DOI: 10.1002/ana.24973] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2016] [Revised: 05/31/2017] [Accepted: 06/01/2017] [Indexed: 01/21/2023]
Affiliation(s)
- Hui Ming Khoo
- Montreal Neurological Institute and Hospital; McGill University; Montreal Canada
- Department of Neurosurgery; Osaka University Graduate School of Medicine; Suita Japan
| | | | - Natalja Zazubovits
- Montreal Neurological Institute and Hospital; McGill University; Montreal Canada
| | - François Dubeau
- Montreal Neurological Institute and Hospital; McGill University; Montreal Canada
| | - Jean Gotman
- Montreal Neurological Institute and Hospital; McGill University; Montreal Canada
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19
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Mohammadi A, Ahmadian A, Rabbani S, Fattahi E, Shirani S. A combined registration and finite element analysis method for fast estimation of intraoperative brain shift; phantom and animal model study. Int J Med Robot 2016; 13. [PMID: 27917580 DOI: 10.1002/rcs.1792] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2016] [Revised: 10/05/2016] [Accepted: 11/01/2016] [Indexed: 11/11/2022]
Abstract
BACKGROUND Finite element models for estimation of intraoperative brain shift suffer from huge computational cost. In these models, image registration and finite element analysis are two time-consuming processes. METHODS The proposed method is an improved version of our previously developed Finite Element Drift (FED) registration algorithm. In this work the registration process is combined with the finite element analysis. In the Combined FED (CFED), the deformation of whole brain mesh is iteratively calculated by geometrical extension of a local load vector which is computed by FED. RESULTS While the processing time of the FED-based method including registration and finite element analysis was about 70 s, the computation time of the CFED was about 3.2 s. The computational cost of CFED is almost 50% less than similar state of the art brain shift estimators based on finite element models. CONCLUSIONS The proposed combination of registration and structural analysis can make the calculation of brain deformation much faster.
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Affiliation(s)
- Amrollah Mohammadi
- Department of Medical Physics & Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Alireza Ahmadian
- Department of Medical Physics & Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.,Research Centre for Biomedical Technology and Robotics (RCBTR), Tehran, Iran
| | - Shahram Rabbani
- Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Ehsan Fattahi
- Department of Neurosurgery, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Shapour Shirani
- Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran
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20
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Drouin S, Kochanowska A, Kersten-Oertel M, Gerard IJ, Zelmann R, De Nigris D, Bériault S, Arbel T, Sirhan D, Sadikot AF, Hall JA, Sinclair DS, Petrecca K, DelMaestro RF, Collins DL. IBIS: an OR ready open-source platform for image-guided neurosurgery. Int J Comput Assist Radiol Surg 2016; 12:363-378. [DOI: 10.1007/s11548-016-1478-0] [Citation(s) in RCA: 49] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2016] [Accepted: 08/19/2016] [Indexed: 10/21/2022]
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21
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Gerard IJ, Kersten-Oertel M, Petrecca K, Sirhan D, Hall JA, Collins DL. Brain shift in neuronavigation of brain tumors: A review. Med Image Anal 2016; 35:403-420. [PMID: 27585837 DOI: 10.1016/j.media.2016.08.007] [Citation(s) in RCA: 153] [Impact Index Per Article: 19.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2015] [Revised: 08/22/2016] [Accepted: 08/23/2016] [Indexed: 10/21/2022]
Abstract
PURPOSE Neuronavigation based on preoperative imaging data is a ubiquitous tool for image guidance in neurosurgery. However, it is rendered unreliable when brain shift invalidates the patient-to-image registration. Many investigators have tried to explain, quantify, and compensate for this phenomenon to allow extended use of neuronavigation systems for the duration of surgery. The purpose of this paper is to present an overview of the work that has been done investigating brain shift. METHODS A review of the literature dealing with the explanation, quantification and compensation of brain shift is presented. The review is based on a systematic search using relevant keywords and phrases in PubMed. The review is organized based on a developed taxonomy that classifies brain shift as occurring due to physical, surgical or biological factors. RESULTS This paper gives an overview of the work investigating, quantifying, and compensating for brain shift in neuronavigation while describing the successes, setbacks, and additional needs in the field. An analysis of the literature demonstrates a high variability in the methods used to quantify brain shift as well as a wide range in the measured magnitude of the brain shift, depending on the specifics of the intervention. The analysis indicates the need for additional research to be done in quantifying independent effects of brain shift in order for some of the state of the art compensation methods to become useful. CONCLUSION This review allows for a thorough understanding of the work investigating brain shift and introduces the needs for future avenues of investigation of the phenomenon.
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Affiliation(s)
- Ian J Gerard
- McConnell Brain Imaging Center, MNI, McGill University, Montreal, Canada.
| | | | - Kevin Petrecca
- Department of Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Denis Sirhan
- Department of Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Jeffery A Hall
- Department of Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - D Louis Collins
- McConnell Brain Imaging Center, MNI, McGill University, Montreal, Canada; Department of Neurosurgery, McGill University, Montreal, Quebec, Canada
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Sastry R, Bi WL, Pieper S, Frisken S, Kapur T, Wells W, Golby AJ. Applications of Ultrasound in the Resection of Brain Tumors. J Neuroimaging 2016; 27:5-15. [PMID: 27541694 DOI: 10.1111/jon.12382] [Citation(s) in RCA: 93] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2016] [Revised: 07/04/2016] [Accepted: 07/05/2016] [Indexed: 12/23/2022] Open
Abstract
Neurosurgery makes use of preoperative imaging to visualize pathology, inform surgical planning, and evaluate the safety of selected approaches. The utility of preoperative imaging for neuronavigation, however, is diminished by the well-characterized phenomenon of brain shift, in which the brain deforms intraoperatively as a result of craniotomy, swelling, gravity, tumor resection, cerebrospinal fluid (CSF) drainage, and many other factors. As such, there is a need for updated intraoperative information that accurately reflects intraoperative conditions. Since 1982, intraoperative ultrasound has allowed neurosurgeons to craft and update operative plans without ionizing radiation exposure or major workflow interruption. Continued evolution of ultrasound technology since its introduction has resulted in superior imaging quality, smaller probes, and more seamless integration with neuronavigation systems. Furthermore, the introduction of related imaging modalities, such as 3-dimensional ultrasound, contrast-enhanced ultrasound, high-frequency ultrasound, and ultrasound elastography, has dramatically expanded the options available to the neurosurgeon intraoperatively. In the context of these advances, we review the current state, potential, and challenges of intraoperative ultrasound for brain tumor resection. We begin by evaluating these ultrasound technologies and their relative advantages and disadvantages. We then review three specific applications of these ultrasound technologies to brain tumor resection: (1) intraoperative navigation, (2) assessment of extent of resection, and (3) brain shift monitoring and compensation. We conclude by identifying opportunities for future directions in the development of ultrasound technologies.
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Affiliation(s)
- Rahul Sastry
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Wenya Linda Bi
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | | | - Sarah Frisken
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Tina Kapur
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - William Wells
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Alexandra J Golby
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.,Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
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Gerard IJ, Kersten-Oertel M, Drouin S, Hall JA, Petrecca K, De Nigris D, Arbel T, Louis Collins D. Improving Patient Specific Neurosurgical Models with Intraoperative Ultrasound and Augmented Reality Visualizations in a Neuronavigation Environment. ACTA ACUST UNITED AC 2016. [DOI: 10.1007/978-3-319-31808-0_4] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/31/2023]
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Xiao Y, Yan CXB, Drouin S, De Nigris D, Kochanowska A, Collins DL. User-friendly freehand ultrasound calibration using Lego bricks and automatic registration. Int J Comput Assist Radiol Surg 2016; 11:1703-11. [PMID: 26984553 DOI: 10.1007/s11548-016-1368-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2015] [Accepted: 02/26/2016] [Indexed: 11/24/2022]
Abstract
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.
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Affiliation(s)
- Yiming Xiao
- McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, 3801 University Street, Montreal, Quebec, Canada, H3A 2B4.
| | - Charles Xiao Bo Yan
- Department of Radiology, McGill University Health Centre, Montreal, Quebec, Canada
| | - Simon Drouin
- McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, 3801 University Street, Montreal, Quebec, Canada, H3A 2B4
| | | | - Anna Kochanowska
- McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, 3801 University Street, Montreal, Quebec, Canada, H3A 2B4
| | - D Louis Collins
- McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, 3801 University Street, Montreal, Quebec, Canada, H3A 2B4
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Towards Augmented Reality Guided Craniotomy Planning in Tumour Resections. LECTURE NOTES IN COMPUTER SCIENCE 2016. [DOI: 10.1007/978-3-319-43775-0_15] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
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26
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Baskan O, Silav G, Demirci S, Canoz O, Turanli G, Elmaci I. Focal megalencephaly: intraoperative ultrasound imaging in epilepsy surgery. J Med Ultrason (2001) 2015; 42:127-31. [PMID: 26578502 DOI: 10.1007/s10396-014-0569-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2014] [Accepted: 08/14/2014] [Indexed: 11/25/2022]
Abstract
Hemimegalencephaly is a rare neuronal migration disorder that can be defined as abnormal neural and glial proliferation localized to all or part of a cerebral hemisphere. Most patients demonstrate intractable epilepsy, with early onset before 1 year of age. Surgical resection is one of the treatment options. In recent years, many advanced intraoperative techniques have been used for brain surgery for various pathologies. Intraoperative ultrasonography is a time-saving and noninvasive method for intraoperative imaging. In this report, we present the use of intraoperative ultrasonography in a patient with focal megalencephaly as an anatomical navigation with the functional navigation system, electrocorticography. In this report, we present the use of intraoperative ultrasonography in a patient with focal megalencephaly as an anatomical navigation with the functional navigation system, electrocorticography.
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Affiliation(s)
- Ozdil Baskan
- Department of Radiology, School of Medicine, Istanbul Medipol University, TasliCikis sk. 8/4 KabatasBeyoglu, 34427, Istanbul, Turkey.
| | - Gokalp Silav
- Department of Neurosurgery, School of Medicine, Istanbul Medipol University, TEM AvrupaOtoyoluGoztepeCikisi No: 1 Bagcılar, 34214, Istanbul, Turkey
| | - Sema Demirci
- Department of Neurology, School of Medicine, Istanbul Medipol University, TEM AvrupaOtoyoluGoztepeCikisi No: 1 Bagcılar, 34214, Istanbul, Turkey
| | - Ozlem Canoz
- Department of Medical Pathology, School of Medicine, Istanbul Medipol University, TEM AvrupaOtoyoluGoztepeCikisi No: 1 Bagcılar, 34214, Istanbul, Turkey
| | - Guzide Turanli
- Department of Pediatrics Neurology, Istanbul Medipol Mega University Hospital, TEM AvrupaOtoyoluGoztepeCikisi No: 1 Bagcılar, 34214, Istanbul, Turkey
| | - Ilhan Elmaci
- Department of Neurosurgery, School of Medicine, Istanbul Medipol University, TEM AvrupaOtoyoluGoztepeCikisi No: 1 Bagcılar, 34214, Istanbul, Turkey
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Askeland C, Solberg OV, Bakeng JBL, Reinertsen I, Tangen GA, Hofstad EF, Iversen DH, Våpenstad C, Selbekk T, Langø T, Hernes TAN, Olav Leira H, Unsgård G, Lindseth F. CustusX: an open-source research platform for image-guided therapy. Int J Comput Assist Radiol Surg 2015; 11:505-19. [PMID: 26410841 PMCID: PMC4819973 DOI: 10.1007/s11548-015-1292-0] [Citation(s) in RCA: 53] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2015] [Accepted: 08/31/2015] [Indexed: 12/14/2022]
Abstract
Purpose CustusX is an image-guided therapy (IGT) research platform dedicated to intraoperative navigation and ultrasound imaging. In this paper, we present CustusX as a robust, accurate, and extensible platform with full access to data and algorithms and show examples of application in technological and clinical IGT research. Methods CustusX has been developed continuously for more than 15 years based on requirements from clinical and technological researchers within the framework of a well-defined software quality process. The platform was designed as a layered architecture with plugins based on the CTK/OSGi framework, a superbuild that manages dependencies and features supporting the IGT workflow. We describe the use of the system in several different clinical settings and characterize major aspects of the system such as accuracy, frame rate, and latency. Results The validation experiments show a navigation system accuracy of \documentclass[12pt]{minimal}
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\begin{document}$$<$$\end{document}<1.1 mm, a frame rate of 20 fps, and latency of 285 ms for a typical setup. The current platform is extensible, user-friendly and has a streamlined architecture and quality process. CustusX has successfully been used for IGT research in neurosurgery, laparoscopic surgery, vascular surgery, and bronchoscopy. Conclusions CustusX is now a mature research platform for intraoperative navigation and ultrasound imaging and is ready for use by the IGT research community. CustusX is open-source and freely available at http://www.custusx.org.
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Affiliation(s)
- Christian Askeland
- Department of Medical Technology, SINTEF Technology and Society, Trondheim, Norway. .,Norwegian National Advisory Unit on Ultrasound and Image-Guided Therapy, St. Olavs Hospital - Trondheim University Hospital, Trondheim, Norway.
| | - Ole Vegard Solberg
- Department of Medical Technology, SINTEF Technology and Society, Trondheim, Norway
| | | | - Ingerid Reinertsen
- Department of Medical Technology, SINTEF Technology and Society, Trondheim, Norway
| | - Geir Arne Tangen
- Department of Medical Technology, SINTEF Technology and Society, Trondheim, Norway
| | | | - Daniel Høyer Iversen
- Department of Medical Technology, SINTEF Technology and Society, Trondheim, Norway.,Norwegian University of Science and Technology (NTNU), Trondheim, Norway.,Norwegian National Advisory Unit on Ultrasound and Image-Guided Therapy, St. Olavs Hospital - Trondheim University Hospital, Trondheim, Norway
| | - Cecilie Våpenstad
- Department of Medical Technology, SINTEF Technology and Society, Trondheim, Norway.,Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Tormod Selbekk
- Department of Medical Technology, SINTEF Technology and Society, Trondheim, Norway.,Norwegian National Advisory Unit on Ultrasound and Image-Guided Therapy, St. Olavs Hospital - Trondheim University Hospital, Trondheim, Norway
| | - Thomas Langø
- Department of Medical Technology, SINTEF Technology and Society, Trondheim, Norway.,Norwegian National Advisory Unit on Ultrasound and Image-Guided Therapy, St. Olavs Hospital - Trondheim University Hospital, Trondheim, Norway
| | - Toril A Nagelhus Hernes
- Norwegian University of Science and Technology (NTNU), Trondheim, Norway.,Norwegian National Advisory Unit on Ultrasound and Image-Guided Therapy, St. Olavs Hospital - Trondheim University Hospital, Trondheim, Norway
| | - Håkon Olav Leira
- Norwegian University of Science and Technology (NTNU), Trondheim, Norway.,Norwegian National Advisory Unit on Ultrasound and Image-Guided Therapy, St. Olavs Hospital - Trondheim University Hospital, Trondheim, Norway
| | - Geirmund Unsgård
- Norwegian University of Science and Technology (NTNU), Trondheim, Norway.,Norwegian National Advisory Unit on Ultrasound and Image-Guided Therapy, St. Olavs Hospital - Trondheim University Hospital, Trondheim, Norway
| | - Frank Lindseth
- Department of Medical Technology, SINTEF Technology and Society, Trondheim, Norway.,Norwegian University of Science and Technology (NTNU), Trondheim, Norway.,Norwegian National Advisory Unit on Ultrasound and Image-Guided Therapy, St. Olavs Hospital - Trondheim University Hospital, Trondheim, Norway
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Gerard IJ, Hall JA, Mok K, Collins DL. New Protocol for Skin Landmark Registration in Image-Guided Neurosurgery: Technical Note. Oper Neurosurg (Hagerstown) 2015; 11 Suppl 3:376-80; discussion 380-1. [DOI: 10.1227/neu.0000000000000868] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Abstract
BACKGROUND
Newer versions of the commercial Medtronic StealthStation allow the use of only 8 landmark pairs for patient-to-image registration as opposed to 9 landmarks in older systems. The choice of which landmark pair to drop in these newer systems can have an effect on the quality of the patient-to-image registration.
OBJECTIVE
To investigate 4 landmark registration protocols based on 8 landmark pairs and compare the resulting registration accuracy with a 9-landmark protocol.
METHODS
Four different protocols were tested on both phantoms and patients. Two of the protocols involved using 4 ear landmarks and 4 facial landmarks and the other 2 involved using 3 ear landmarks and 5 facial landmarks. Both the fiducial registration error and target registration error were evaluated for each of the different protocols to determine any difference between them and the 9-landmark protocol.
RESULTS
No difference in fiducial registration error was found between any of the 8-landmark protocols and the 9-landmark protocol. A significant decrease (P < .05) in target registration error was found when using a protocol based on 4 ear landmarks and 4 facial landmarks compared with the other protocols based on 3 ear landmarks.
CONCLUSION
When using 8 landmarks to perform the patient-to-image registration, the protocol using 4 ear landmarks and 4 facial landmarks greatly outperformed the other 8-landmark protocols and 9-landmark protocol, resulting in the lowest target registration error.
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Affiliation(s)
- Ian J Gerard
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, Quebec, Canada
- Department of Biomedical Engineering, McGill University, Montreal, Quebec, Canada
| | - Jeffery A Hall
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Kelvin Mok
- Neuronavigation Unit, Montreal Neurological Institute and Hospital, Montreal, Quebec, Canada
| | - D Louis Collins
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, Quebec, Canada
- Department of Biomedical Engineering, McGill University, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
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Zelmann R, Beriault S, Marinho MM, Mok K, Hall JA, Guizard N, Haegelen C, Olivier A, Pike GB, Collins DL. Improving recorded volume in mesial temporal lobe by optimizing stereotactic intracranial electrode implantation planning. Int J Comput Assist Radiol Surg 2015; 10:1599-615. [PMID: 25808256 DOI: 10.1007/s11548-015-1165-6] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2014] [Accepted: 02/13/2015] [Indexed: 11/30/2022]
Abstract
PURPOSE Intracranial electrodes are sometimes implanted in patients with refractory epilepsy to identify epileptic foci and propagation. Maximal recording of EEG activity from regions suspected of seizure generation is paramount. However, the location of individual contacts cannot be considered with current manual planning approaches. We propose and validate a procedure for optimizing intracranial electrode implantation planning that maximizes the recording volume, while constraining trajectories to safe paths. METHODS Retrospective data from 20 patients with epilepsy that had electrodes implanted in the mesial temporal lobes were studied. Clinical imaging data (CT/A and T1w MRI) were automatically segmented to obtain targets and structures to avoid. These data were used as input to the optimization procedure. Each electrode was modeled to assess risk, while individual contacts were modeled to estimate their recording capability. Ordered lists of trajectories per target were obtained. Global optimization generated the best set of electrodes. The procedure was integrated into a neuronavigation system. RESULTS Trajectories planned automatically covered statistically significant larger target volumes than manual plans [Formula: see text]. Median volume coverage was [Formula: see text] for automatic plans versus [Formula: see text] for manual plans. Furthermore, automatic plans remained at statistically significant safer distance to vessels [Formula: see text] and sulci [Formula: see text]. Surgeon's scores of the optimized electrode sets indicated that 95% of the automatic trajectories would be likely considered for use in a clinical setting. CONCLUSIONS This study suggests that automatic electrode planning for epilepsy provides safe trajectories and increases the amount of information obtained from the intracranial investigation.
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Affiliation(s)
- R Zelmann
- McConnell Brain Imaging Center, Montreal Neurological Hospital and Institute, McGill University, 3801 University Street, Montreal, QC, H3A 2B4, Canada.
| | - S Beriault
- McConnell Brain Imaging Center, Montreal Neurological Hospital and Institute, McGill University, 3801 University Street, Montreal, QC, H3A 2B4, Canada
| | - M M Marinho
- Neurology and Neurosurgery, Montreal Neurological Hospital and Institute, McGill University, 3801 University Street, Montreal, QC, H3A 2B4, Canada
| | - K Mok
- Neurology and Neurosurgery, Montreal Neurological Hospital and Institute, McGill University, 3801 University Street, Montreal, QC, H3A 2B4, Canada
| | - J A Hall
- Neurology and Neurosurgery, Montreal Neurological Hospital and Institute, McGill University, 3801 University Street, Montreal, QC, H3A 2B4, Canada
| | - N Guizard
- McConnell Brain Imaging Center, Montreal Neurological Hospital and Institute, McGill University, 3801 University Street, Montreal, QC, H3A 2B4, Canada
| | - C Haegelen
- LTSI - U1099 INSERM, CS34317, Université Rennes 1, 35043, Rennes, France
| | - A Olivier
- Neurology and Neurosurgery, Montreal Neurological Hospital and Institute, McGill University, 3801 University Street, Montreal, QC, H3A 2B4, Canada
| | - G B Pike
- McConnell Brain Imaging Center, Montreal Neurological Hospital and Institute, McGill University, 3801 University Street, Montreal, QC, H3A 2B4, Canada
| | - D L Collins
- McConnell Brain Imaging Center, Montreal Neurological Hospital and Institute, McGill University, 3801 University Street, Montreal, QC, H3A 2B4, Canada
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Kersten-Oertel M, Gerard I, Drouin S, Mok K, Sirhan D, Sinclair DS, Collins DL. Augmented reality in neurovascular surgery: feasibility and first uses in the operating room. Int J Comput Assist Radiol Surg 2015; 10:1823-36. [DOI: 10.1007/s11548-015-1163-8] [Citation(s) in RCA: 67] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2014] [Accepted: 02/10/2015] [Indexed: 11/24/2022]
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Rivaz H, Collins DL. Near real-time robust non-rigid registration of volumetric ultrasound images for neurosurgery. ULTRASOUND IN MEDICINE & BIOLOGY 2015; 41:574-587. [PMID: 25542482 DOI: 10.1016/j.ultrasmedbio.2014.08.013] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/29/2013] [Revised: 08/12/2014] [Accepted: 08/20/2014] [Indexed: 06/04/2023]
Abstract
Ultrasound images are acquired before and after the resection of brain tumors to help the surgeon to localize the tumor and its extent and to minimize the amount of residual tumor after the resection. Because the brain undergoes large deformation between these two acquisitions, deformable image-based registration of these data sets is of substantial clinical importance. In this work, we present an algorithm for non-rigid registration of ultrasound images (RESOUND) that models the deformation with free-form cubic B-splines. We formulate a regularized cost function that uses normalized cross-correlation as the similarity metric. To optimize the cost function, we calculate its analytic derivative and use the stochastic gradient descent technique to achieve near real-time performance. We further propose a robust technique to minimize the effect of non-corresponding regions such as the resected tumor and possible hemorrhage in the post-resection image. Using manually labeled corresponding landmarks in the pre- and post-resection ultrasound volumes, we illustrate that our registration algorithm reduces the mean target registration error from an initial value of 3.7 to 1.5 mm. We also compare RESOUND with the previous work of Mercier et al. (2013) and illustrate that it has three important advantages: (i) it is fully automatic and does not require a manual segmentation of the tumor, (ii) it produces smaller registration errors and (iii) it is about 30 times faster. The clinical data set is available online on the BITE database website.
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Affiliation(s)
- Hassan Rivaz
- Department of Electrical and Computer Engineering, Concordia PERFORM Centre, Concordia University, Montreal, Quebec, Canada.
| | - D Louis Collins
- McConnell Brain Imaging Center, Montreal Neurologic Institute, McGill University, Montreal, Quebec, Canada
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Rivaz H, Chen SJS, Collins DL. Automatic deformable MR-ultrasound registration for image-guided neurosurgery. IEEE TRANSACTIONS ON MEDICAL IMAGING 2015; 34:366-380. [PMID: 25248177 DOI: 10.1109/tmi.2014.2354352] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
In this work, we present a novel algorithm for registration of 3-D volumetric ultrasound (US) and MR using Robust PaTch-based cOrrelation Ratio (RaPTOR). RaPTOR computes local correlation ratio (CR) values on small patches and adds the CR values to form a global cost function. It is therefore invariant to large amounts of spatial intensity inhomogeneity. We also propose a novel outlier suppression technique based on the orientations of the RaPTOR gradients. Our deformation is modeled with free-form cubic B-splines. We analytically derive the derivatives of RaPTOR with respect to the transformation, i.e., the displacement of the B-spline nodes, and optimize RaPTOR using a stochastic gradient descent approach. RaPTOR is validated on MR and tracked US images of neurosurgery. Deformable registration of the US and MR images acquired, respectively, preoperation and postresection is of significant clinical significance, but challenging due to, among others, the large amount of missing correspondences between the two images. This work is also novel in that it performs automatic registration of this challenging dataset. To validate the results, we manually locate corresponding anatomical landmarks in the US and MR images of tumor resection in brain surgery. Compared to rigid registration based on the tracking system alone, RaPTOR reduces the mean initial mTRE over 13 patients from 5.9 to 2.9 mm, and the maximum initial TRE from 17.0 to 5.9 mm. Each volumetric registration using RaPTOR takes about 30 sec on a single CPU core. An important challenge in the field of medical image analysis is the shortage of publicly available dataset, which can both facilitate the advancement of new algorithms to clinical settings and provide a benchmark for comparison. To address this problem, we will make our manually located landmarks available online.
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Gerard IJ, Collins DL. An analysis of tracking error in image-guided neurosurgery. Int J Comput Assist Radiol Surg 2015; 10:1579-88. [PMID: 25556526 DOI: 10.1007/s11548-014-1145-2] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2014] [Accepted: 12/18/2014] [Indexed: 11/25/2022]
Abstract
PURPOSE This study quantifies some of the technical and physical factors that contribute to error in image-guided interventions. Errors associated with tracking, tool calibration and registration between a physical object and its corresponding image were investigated and compared with theoretical descriptions of these errors. METHODS A precision milled linear testing apparatus was constructed to perform the measurements. RESULTS The tracking error was shown to increase in linear fashion with distance normal to the camera, and the tracking error ranged between 0.15 and 0.6 mm. The tool calibration error increased as a function of distance from the camera and the reference tool (0.2-0.8 mm). The fiducial registration error was shown to improve when more points were used up until a plateau value was reached which corresponded to the total fiducial localization error ([Formula: see text]0.8 mm). The target registration error distributions followed a [Formula: see text] distribution with the largest error and variation around fiducial points. CONCLUSIONS To minimize errors, tools should be calibrated as close as possible to the reference tool and camera, and tools should be used as close to the front edge of the camera throughout the intervention, with the camera pointed in the direction where accuracy is least needed during surgery.
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Affiliation(s)
- Ian J Gerard
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, WB 221, 3801 University Street, Montreal, QC, H3A 2B4, Canada.
| | - D Louis Collins
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, WB 221, 3801 University Street, Montreal, QC, H3A 2B4, Canada
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Bériault S, Sadikot AF, Alsubaie F, Drouin S, Collins DL, Pike GB. Neuronavigation using susceptibility-weighted venography: application to deep brain stimulation and comparison with gadolinium contrast. J Neurosurg 2014; 121:131-41. [DOI: 10.3171/2014.3.jns131860] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Careful trajectory planning on preoperative vascular imaging is an essential step in deep brain stimulation (DBS) to minimize risks of hemorrhagic complications and postoperative neurological deficits. This paper compares 2 MRI methods for visualizing cerebral vasculature and planning DBS probe trajectories: a single data set T1-weighted scan with double-dose gadolinium contrast (T1w-Gd) and a multi–data set protocol consisting of a T1-weighted structural, susceptibility-weighted venography, and time-of-flight angiography (T1w-SWI-TOF). Two neurosurgeons who specialize in neuromodulation surgery planned bilateral STN DBS in 18 patients with Parkinson's disease (36 hemispheres) using each protocol separately. Planned trajectories were then evaluated across all vascular data sets (T1w-Gd, SWI, and TOF) to detect possible intersection with blood vessels along the entire path via an objective vesselness measure. The authors' results show that trajectories planned on T1w-SWI-TOF successfully avoided the cerebral vasculature imaged by conventional T1w-Gd and did not suffer from missing vascular information or imprecise data set registration. Furthermore, with appropriate planning and visualization software, trajectory corridors planned on T1w-SWI-TOF intersected significantly less fine vasculature that was not detected on the T1w-Gd (p < 0.01 within 2 mm and p < 0.001 within 4 mm of the track centerline). The proposed T1w-SWI-TOF protocol comes with minimal effects on the imaging and surgical workflow, improves vessel avoidance, and provides a safe cost-effective alternative to injection of gadolinium contrast.
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Affiliation(s)
| | - Abbas F. Sadikot
- 1McConnell Brain Imaging Centre and
- 2Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Quebec; and
| | - Fahd Alsubaie
- 1McConnell Brain Imaging Centre and
- 2Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Quebec; and
| | - Simon Drouin
- 1McConnell Brain Imaging Centre and
- 2Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Quebec; and
| | | | - G. Bruce Pike
- 3Department of Radiology, Hotchkiss Brain Institute, University of Calgary, Alberta, Canada
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Orringer DA, Golby A, Jolesz F. Neuronavigation in the surgical management of brain tumors: current and future trends. Expert Rev Med Devices 2013; 9:491-500. [PMID: 23116076 DOI: 10.1586/erd.12.42] [Citation(s) in RCA: 142] [Impact Index Per Article: 12.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Neuronavigation has become an ubiquitous tool in the surgical management of brain tumors. This review describes the use and limitations of current neuronavigational systems for brain tumor biopsy and resection. Methods for integrating intraoperative imaging into neuronavigational datasets developed to address the diminishing accuracy of positional information that occurs over the course of brain tumor resection are discussed. In addition, the process of integration of functional MRI and tractography into navigational models is reviewed. Finally, emerging concepts and future challenges relating to the development and implementation of experimental imaging technologies in the navigational environment are explored.
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Affiliation(s)
- Daniel A Orringer
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02115, USA
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Ji S, Roberts DW, Hartov A, Paulsen KD. Intraoperative patient registration using volumetric true 3D ultrasound without fiducials. Med Phys 2012; 39:7540-52. [PMID: 23231302 PMCID: PMC3523742 DOI: 10.1118/1.4767758] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2011] [Revised: 10/02/2012] [Accepted: 10/30/2012] [Indexed: 11/07/2022] Open
Abstract
PURPOSE Accurate patient registration is crucial for effective image-guidance in open cranial surgery. Typically, it is accomplished by matching skin-affixed fiducials manually identified in the operating room (OR) with their counterparts in the preoperative images, which not only consumes OR time and personnel resources but also relies on the presence (and subsequent fixation) of the fiducials during the preoperative scans (until the procedure begins). In this study, the authors present a completely automatic, volumetric image-based patient registration technique that does not rely on fiducials by registering tracked (true) 3D ultrasound (3DUS) directly with preoperative magnetic resonance (MR) images. METHODS Multistart registrations between binary 3DUS and MR volumes were first executed to generate an initial starting point without incorporating prior information on the US transducer contact point location or orientation for subsequent registration between grayscale 3DUS and MR via maximization of either mutual information (MI) or correlation ratio (CR). Patient registration was then computed through concatenation of spatial transformations. RESULTS In ten (N = 10) patient cases, an average fiducial (marker) distance error (FDE) of 5.0 mm and 4.3 mm was achieved using MI or CR registration (FDE was smaller with CR vs MI in eight of ten cases), which are comparable to values reported for typical fiducial- or surface-based patient registrations. The translational and rotational capture ranges were found to be 24.0 mm and 27.0° for binary registrations (up to 32.8 mm and 36.4°), 12.2 mm and 25.6° for MI registrations (up to 18.3 mm and 34.4°), and 22.6 mm and 40.8° for CR registrations (up to 48.5 mm and 65.6°), respectively. The execution time to complete a patient registration was 12-15 min with parallel processing, which can be significantly reduced by confining the 3DUS transducer location to the center of craniotomy in MR before registration (an execution time of 5 min is achievable). CONCLUSIONS Because common features deep in the brain and throughout the surgical volume of interest are used, intraoperative fiducial-less patient registration is possible on-demand, which is attractive in cases where preoperative patient registration is compromised (e.g., from loss∕movement of skin-affixed fiducials) or not possible (e.g., in cases of emergency when external fiducials were not placed in time). CR registration was more robust than MI (capture range about twice as big) and appears to be more accurate, although both methods are comparable to or better than fiducial-based registration in the patient cases evaluated. The results presented here suggest that 3DUS image-based patient registration holds promise for clinical application in the future.
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Affiliation(s)
- Songbai Ji
- Thayer School of Engineering, Dartmouth College, Hanover, NH, USA.
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Petrecca K, Guiot MC, Panet-Raymond V, Souhami L. Failure pattern following complete resection plus radiotherapy and temozolomide is at the resection margin in patients with glioblastoma. J Neurooncol 2012; 111:19-23. [DOI: 10.1007/s11060-012-0983-4] [Citation(s) in RCA: 199] [Impact Index Per Article: 16.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2012] [Accepted: 10/01/2012] [Indexed: 11/25/2022]
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Bériault S, Subaie FA, Collins DL, Sadikot AF, Pike GB. A multi-modal approach to computer-assisted deep brain stimulation trajectory planning. Int J Comput Assist Radiol Surg 2012; 7:687-704. [PMID: 22718401 DOI: 10.1007/s11548-012-0768-4] [Citation(s) in RCA: 60] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2012] [Accepted: 05/29/2012] [Indexed: 01/20/2023]
Abstract
PURPOSE Both frame-based and frameless approaches to deep brain stimulation (DBS) require planning of insertion trajectories that mitigate hemorrhagic risk and loss of neurological function. Currently, this is done by manual inspection of multiple potential electrode trajectories on MR-imaging data. We propose and validate a method for computer-assisted DBS trajectory planning. METHOD Our framework integrates multi-modal MRI analysis (T1w, SWI, TOF-MRA) to compute suitable DBS trajectories that optimize the avoidance of specific critical brain structures. A cylinder model is used to process each trajectory and to evaluate complex surgical constraints described via a combination of binary and fuzzy segmented datasets. The framework automatically aggregates the multiple constraints into a unique ranking of recommended low-risk trajectories. Candidate trajectories are represented as a few well-defined cortical entry patches of best-ranked trajectories and presented to the neurosurgeon for final trajectory selection. RESULTS The proposed algorithm permits a search space containing over 8,000 possible trajectories to be processed in less than 20 s. A retrospective analysis on 14 DBS cases of patients with severe Parkinson's disease reveals that our framework can improve the simultaneous optimization of many pre-formulated surgical constraints. Furthermore, all automatically computed trajectories were evaluated by two neurosurgeons, were judged suitable for surgery and, in many cases, were judged preferable or equivalent to the manually planned trajectories used during the operation. CONCLUSIONS This work provides neurosurgeons with an intuitive and flexible decision-support system that allows objective and patient-specific optimization of DBS lead trajectories, which should improve insertion safety and reduce surgical time.
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Affiliation(s)
- Silvain Bériault
- McConnell Brain Imaging Centre, Montreal Neurological Institute, 3801 University Street, Montreal, QC H3A 2B4, Canada.
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Mercier L, Del Maestro RF, Petrecca K, Araujo D, Haegelen C, Collins DL. Online database of clinical MR and ultrasound images of brain tumors. Med Phys 2012; 39:3253-61. [DOI: 10.1118/1.4709600] [Citation(s) in RCA: 78] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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A Realistic Test and Development Environment for Mixed Reality in Neurosurgery. AUGMENTED ENVIRONMENTS FOR COMPUTER-ASSISTED INTERVENTIONS 2012. [DOI: 10.1007/978-3-642-32630-1_2] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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De Lorenzo D, Vaccarella A, Khreis G, Moennich H, Ferrigno G, De Momi E. Accurate calibration method for 3D freehand ultrasound probe using virtual plane. Med Phys 2011; 38:6710-20. [DOI: 10.1118/1.3663674] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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Yan CXB, Goulet B, Chen SJS, Tampieri D, Collins DL. Validation of automated ultrasound-CT registration of vertebrae. Int J Comput Assist Radiol Surg 2011; 7:601-10. [DOI: 10.1007/s11548-011-0666-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2011] [Accepted: 11/08/2011] [Indexed: 10/15/2022]
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Treating the neurosurgical patient: beyond the pathology and technology. Can J Neurol Sci 2010; 38:1-2. [PMID: 21156418 DOI: 10.1017/s0317167100011008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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