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Uribe Rivera AK, Seeliger B, Goffin L, García-Vázquez A, Mutter D, Giménez ME. Robotic Assistance in Percutaneous Liver Ablation Therapies: A Systematic Review and Meta-Analysis. ANNALS OF SURGERY OPEN 2024; 5:e406. [PMID: 38911657 PMCID: PMC11191991 DOI: 10.1097/as9.0000000000000406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 02/19/2024] [Indexed: 06/25/2024] Open
Abstract
Objective The aim of this systematic review and meta-analysis is to identify current robotic assistance systems for percutaneous liver ablations, compare approaches, and determine how to achieve standardization of procedural concepts for optimized ablation outcomes. Background Image-guided surgical approaches are increasingly common. Assistance by navigation and robotic systems allows to optimize procedural accuracy, with the aim to consistently obtain adequate ablation volumes. Methods Several databases (PubMed/MEDLINE, ProQuest, Science Direct, Research Rabbit, and IEEE Xplore) were systematically searched for robotic preclinical and clinical percutaneous liver ablation studies, and relevant original manuscripts were included according to the Preferred Reporting items for Systematic Reviews and Meta-Analyses guidelines. The endpoints were the type of device, insertion technique (freehand or robotic), planning, execution, and confirmation of the procedure. A meta-analysis was performed, including comparative studies of freehand and robotic techniques in terms of radiation dose, accuracy, and Euclidean error. Results The inclusion criteria were met by 33/755 studies. There were 24 robotic devices reported for percutaneous liver surgery. The most used were the MAXIO robot (8/33; 24.2%), Zerobot, and AcuBot (each 2/33, 6.1%). The most common tracking system was optical (25/33, 75.8%). In the meta-analysis, the robotic approach was superior to the freehand technique in terms of individual radiation (0.5582, 95% confidence interval [CI] = 0.0167-1.0996, dose-length product range 79-2216 mGy.cm), accuracy (0.6260, 95% CI = 0.1423-1.1097), and Euclidean error (0.8189, 95% CI = -0.1020 to 1.7399). Conclusions Robotic assistance in percutaneous ablation for liver tumors achieves superior results and reduces errors compared with manual applicator insertion. Standardization of concepts and reporting is necessary and suggested to facilitate the comparison of the different parameters used to measure liver ablation results. The increasing use of image-guided surgery has encouraged robotic assistance for percutaneous liver ablations. This systematic review analyzed 33 studies and identified 24 robotic devices, with optical tracking prevailing. The meta-analysis favored robotic assessment, showing increased accuracy and reduced errors compared with freehand technique, emphasizing the need for conceptual standardization.
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Affiliation(s)
- Ana K Uribe Rivera
- From the IHU-Strasbourg, Institute of Image-Guided Surgery, Strasbourg, France
| | - Barbara Seeliger
- From the IHU-Strasbourg, Institute of Image-Guided Surgery, Strasbourg, France
- Department of Visceral and Digestive Surgery, University Hospitals of Strasbourg, Strasbourg, France
- IRCAD, Research Institute Against Digestive Cancer, Strasbourg, France
- ICube, UMR 7357 CNRS, INSERM U1328 RODIN, University of Strasbourg, Strasbourg, France
- Inserm U1110, Institute for Viral and Liver Diseases, Strasbourg. France
- Trustworthy AI Lab, Centre National de la Recherche Scientifique (CNRS), France
| | - Laurent Goffin
- ICube, UMR 7357 CNRS, INSERM U1328 RODIN, University of Strasbourg, Strasbourg, France
- Trustworthy AI Lab, Centre National de la Recherche Scientifique (CNRS), France
- Computational Surgery SAS, Schiltigheim, France
| | | | - Didier Mutter
- From the IHU-Strasbourg, Institute of Image-Guided Surgery, Strasbourg, France
- Department of Visceral and Digestive Surgery, University Hospitals of Strasbourg, Strasbourg, France
- IRCAD, Research Institute Against Digestive Cancer, Strasbourg, France
| | - Mariano E Giménez
- From the IHU-Strasbourg, Institute of Image-Guided Surgery, Strasbourg, France
- IRCAD, Research Institute Against Digestive Cancer, Strasbourg, France
- DAICIM Foundation (Training, Research and Clinical Activity in Minimally Invasive Surgery), Buenos Aires, Argentina
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Zhou W, Li X, Zabihollahy F, Lu DS, Wu HH. Deep learning-based automatic pipeline for 3D needle localization on intra-procedural 3D MRI. Int J Comput Assist Radiol Surg 2024:10.1007/s11548-024-03077-3. [PMID: 38520646 DOI: 10.1007/s11548-024-03077-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 02/09/2024] [Indexed: 03/25/2024]
Abstract
PURPOSE Accurate and rapid needle localization on 3D magnetic resonance imaging (MRI) is critical for MRI-guided percutaneous interventions. The current workflow requires manual needle localization on 3D MRI, which is time-consuming and cumbersome. Automatic methods using 2D deep learning networks for needle segmentation require manual image plane localization, while 3D networks are challenged by the need for sufficient training datasets. This work aimed to develop an automatic deep learning-based pipeline for accurate and rapid 3D needle localization on in vivo intra-procedural 3D MRI using a limited training dataset. METHODS The proposed automatic pipeline adopted Shifted Window (Swin) Transformers and employed a coarse-to-fine segmentation strategy: (1) initial 3D needle feature segmentation with 3D Swin UNEt TRansfomer (UNETR); (2) generation of a 2D reformatted image containing the needle feature; (3) fine 2D needle feature segmentation with 2D Swin Transformer and calculation of 3D needle tip position and axis orientation. Pre-training and data augmentation were performed to improve network training. The pipeline was evaluated via cross-validation with 49 in vivo intra-procedural 3D MR images from preclinical pig experiments. The needle tip and axis localization errors were compared with human intra-reader variation using the Wilcoxon signed rank test, with p < 0.05 considered significant. RESULTS The average end-to-end computational time for the pipeline was 6 s per 3D volume. The median Dice scores of the 3D Swin UNETR and 2D Swin Transformer in the pipeline were 0.80 and 0.93, respectively. The median 3D needle tip and axis localization errors were 1.48 mm (1.09 pixels) and 0.98°, respectively. Needle tip localization errors were significantly smaller than human intra-reader variation (median 1.70 mm; p < 0.01). CONCLUSION The proposed automatic pipeline achieved rapid pixel-level 3D needle localization on intra-procedural 3D MRI without requiring a large 3D training dataset and has the potential to assist MRI-guided percutaneous interventions.
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Affiliation(s)
- Wenqi Zhou
- Department of Radiological Sciences, University of California Los Angeles, 300 UCLA Medical Plaza, Suite B119, Los Angeles, CA, 90095, USA
- Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, USA
| | - Xinzhou Li
- Department of Radiological Sciences, University of California Los Angeles, 300 UCLA Medical Plaza, Suite B119, Los Angeles, CA, 90095, USA
- Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, USA
| | - Fatemeh Zabihollahy
- Department of Radiological Sciences, University of California Los Angeles, 300 UCLA Medical Plaza, Suite B119, Los Angeles, CA, 90095, USA
- Joint Department of Medical Imaging, Sinai Health System and University of Toronto, Toronto, Canada
| | - David S Lu
- Department of Radiological Sciences, University of California Los Angeles, 300 UCLA Medical Plaza, Suite B119, Los Angeles, CA, 90095, USA
| | - Holden H Wu
- Department of Radiological Sciences, University of California Los Angeles, 300 UCLA Medical Plaza, Suite B119, Los Angeles, CA, 90095, USA.
- Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, USA.
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Fang G, Chow MCK, Ho JDL, He Z, Wang K, Ng TC, Tsoi JKH, Chan PL, Chang HC, Chan DTM, Liu YH, Holsinger FC, Chan JYK, Kwok KW. Soft robotic manipulator for intraoperative MRI-guided transoral laser microsurgery. Sci Robot 2021; 6:6/57/eabg5575. [PMID: 34408096 DOI: 10.1126/scirobotics.abg5575] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Accepted: 07/27/2021] [Indexed: 01/14/2023]
Abstract
Magnetic resonance (MR) imaging (MRI) provides compelling features for the guidance of interventional procedures, including high-contrast soft tissue imaging, detailed visualization of physiological changes, and thermometry. Laser-based tumor ablation stands to benefit greatly from MRI guidance because 3D resection margins alongside thermal distributions can be evaluated in real time to protect critical structures while ensuring adequate resection margins. However, few studies have investigated the use of projection-based lasers like those for transoral laser microsurgery, potentially because dexterous laser steering is required at the ablation site, raising substantial challenges in the confined MRI bore and its strong magnetic field. Here, we propose an MR-safe soft robotic system for MRI-guided transoral laser microsurgery. Owing to its miniature size (Ø12 × 100 mm), inherent compliance, and five degrees of freedom, the soft robot ensures zero electromagnetic interference with MRI and enables safe and dexterous operation within the confined oral and pharyngeal cavities. The laser manipulator is rapidly fabricated with hybrid soft and hard structures and is powered by microvolume (<0.004 milliter) fluid flow to enable laser steering with enhanced stiffness and lowered hysteresis. A learning-based controller accommodates the inherent nonlinear robot actuation, which was validated with laser path-following tests. Submillimeter laser steering accuracy was demonstrated with a mean error < 0.20 mm. MRI compatibility testing demonstrated zero observable image artifacts during robot operation. Ex vivo tissue ablation and a cadaveric head-and-neck trial were carried out under MRI, where we employed MR thermometry to monitor the tissue ablation margin and thermal diffusion intraoperatively.
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Affiliation(s)
- Ge Fang
- Department of Mechanical Engineering, University of Hong Kong, Hong Kong, China
| | - Marco C K Chow
- Department of Mechanical Engineering, University of Hong Kong, Hong Kong, China
| | - Justin D L Ho
- Department of Mechanical Engineering, University of Hong Kong, Hong Kong, China
| | - Zhuoliang He
- Department of Mechanical Engineering, University of Hong Kong, Hong Kong, China
| | - Kui Wang
- Department of Mechanical Engineering, University of Hong Kong, Hong Kong, China
| | - T C Ng
- Faculty of Dentistry, University of Hong Kong, Hong Kong, China
| | - James K H Tsoi
- Faculty of Dentistry, University of Hong Kong, Hong Kong, China
| | - Po-Ling Chan
- Department of Otorhinolaryngology, Head and Neck Surgery, Chinese University of Hong Kong, Hong Kong, China
| | - Hing-Chiu Chang
- Department of Diagnostic Radiology, University of Hong Kong, Hong Kong, China.,Department of Biomedical Engineering, Chinese University of Hong Kong, Hong Kong, China
| | | | - Yun-Hui Liu
- Department of Mechanical and Automation Engineering, Chinese University of Hong Kong, Hong Kong, China
| | | | - Jason Ying-Kuen Chan
- Department of Otorhinolaryngology, Head and Neck Surgery, Chinese University of Hong Kong, Hong Kong, China.
| | - Ka-Wai Kwok
- Department of Mechanical Engineering, University of Hong Kong, Hong Kong, China.
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Reichert A, Reiss S, Krafft AJ, Bock M. Passive needle guide tracking with radial acquisition and phase-only cross-correlation. Magn Reson Med 2020; 85:1039-1046. [PMID: 32767451 DOI: 10.1002/mrm.28448] [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: 04/21/2020] [Revised: 07/07/2020] [Accepted: 07/07/2020] [Indexed: 12/24/2022]
Abstract
PURPOSE Acceleration of a passive tracking sequence based on phase-only cross-correlation (POCC) using radial undersampling. METHODS The phase-only cross-correlation (POCC) algorithm allows passive tracking of interventional instruments in real-time. In a POCC sequence, two cross-sectional images of a needle guide with a positive MR contrast are continuously acquired from which the instrument trajectory is calculated. Conventional Cartesian imaging for tracking is very time consuming; here, a higher temporal resolution is achieved using a highly undersampled radial acquisition together with a modified POCC algorithm that incorporates the point-spread-function. Targeting and needle insertion is performed in two phantom experiments with 16 fiducial targets, each using 4 and 16 radial projections for passive tracking. Additionally, targeting of eight deep lying basivertebral veins in the lumbar spines is performed for in vivo proof-of-application with four radial projections for needle guide tracking. RESULTS The radially undersampled POCC sequence yielded in the phantom experiments a lateral targeting accuracy of 1.1 ± 0.4 mm and 1.0 ± 0.5 mm for 16 and 4 radial projections, respectively, without any statistically significant difference. In the in vivo application, a mean targeting duration of 62 ± 13 s was measured. CONCLUSION Radial undersampling can drastically reduce the acquisition time for passive tracking in a POCC sequences for MR-guided needle interventions without compromising the targeting accuracy.
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Affiliation(s)
- Andreas Reichert
- Department of Radiology, Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Simon Reiss
- Department of Radiology, Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Axel Joachim Krafft
- Department of Radiology, Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Michael Bock
- Department of Radiology, Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
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Pan L, Valdeig S, Kägebein U, Qing K, Fetics B, Roth A, Nevo E, Hensen B, Weiss CR, Wacker FK. Integration and evaluation of a gradient-based needle navigation system for percutaneous MR-guided interventions. PLoS One 2020; 15:e0236295. [PMID: 32706813 PMCID: PMC7380643 DOI: 10.1371/journal.pone.0236295] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Accepted: 07/01/2020] [Indexed: 12/22/2022] Open
Abstract
The purpose of the present study was to integrate an interactive gradient-based needle navigation system and to evaluate the feasibility and accuracy of the system for real-time MR guided needle puncture in a multi-ring phantom and in vivo in a porcine model. The gradient-based navigation system was implemented in a 1.5T MRI. An interactive multi-slice real-time sequence was modified to provide the excitation gradients used by two sets of three orthogonal pick-up coils integrated into a needle holder. Position and orientation of the needle holder were determined and the trajectory was superimposed on pre-acquired MR images. A gel phantom with embedded ring targets was used to evaluate accuracy using 3D distance from needle tip to target. Six punctures were performed in animals to evaluate feasibility, time, overall error (target to needle tip) and system error (needle tip to the guidance needle trajectory) in vivo. In the phantom experiments, the overall error was 6.2±2.9 mm (mean±SD) and 4.4±1.3 mm, respectively. In the porcine model, the setup time ranged from 176 to 204 seconds, the average needle insertion time was 96.3±40.5 seconds (min: 42 seconds; max: 154 seconds). The overall error and the system error was 8.8±7.8 mm (min: 0.8 mm; max: 20.0 mm) and 3.3±1.4 mm (min: 1.8 mm; max: 5.2 mm), respectively.
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Affiliation(s)
- Li Pan
- Siemens Healthineers, Baltimore, MD, United States of America
| | - Steffi Valdeig
- Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, United States of America
| | - Urte Kägebein
- Department of Radiology, Hannover Medical School, Hannover, Germany
- STIMULATE–Research Campus: Solution Centre for Image Guided Local Therapies, Magdeburg, Germany
| | - Kun Qing
- Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, VA, United States of America
- Siemens Corporate Technology, Baltimore, MD, United States of America
| | - Barry Fetics
- Robin Medical Inc., Baltimore, MD, United States of America
| | - Amir Roth
- Robin Medical Inc., Baltimore, MD, United States of America
| | - Erez Nevo
- Robin Medical Inc., Baltimore, MD, United States of America
| | - Bennet Hensen
- Department of Radiology, Hannover Medical School, Hannover, Germany
- STIMULATE–Research Campus: Solution Centre for Image Guided Local Therapies, Magdeburg, Germany
- * E-mail:
| | - Clifford R. Weiss
- Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, United States of America
| | - Frank K. Wacker
- Department of Radiology, Hannover Medical School, Hannover, Germany
- STIMULATE–Research Campus: Solution Centre for Image Guided Local Therapies, Magdeburg, Germany
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A CT-guided robotic needle puncture method for lung tumours with respiratory motion. Phys Med 2020; 73:48-56. [PMID: 32315807 DOI: 10.1016/j.ejmp.2020.04.003] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Revised: 03/14/2020] [Accepted: 04/02/2020] [Indexed: 01/16/2023] Open
Abstract
PURPOSE Percutaneous interventions rely on needle puncture to deliver medical devices into lesions. For lung tumours, respiratory motion makes effective puncture procedures difficult to achieve. To address this issue, a needle puncture method considering respiration is proposed to improve the accuracy of lung puncture. METHODS The accuracy of puncture is ensured by visualization and needle guidance. Dynamic visualization of the respiratory motion is developed for needle path planning based on four-dimensional computed tomography (4DCT) images. The rendered image is synchronized with the actual breathing by using respiratory signals. A robotic needle insertion strategy for velocity adjustment based on these respiratory signals is designed to guide the needle towards the moving tumour. RESULTS The dynamic visualization was tested on multiple 4DCT datasets and achieved a frame rate of over 32 frames per second (FPS). A computer simulation was carried out to verify the feasibility of the needle insertion strategy. Needle puncture was performed on a phantom, and a mean accuracy of 1.34±0.18 mm was achieved. CONCLUSIONS In this paper, an efficient and robust method is proposed to improve the visualization and targeting of lung puncture, which reduces the impact of respiratory motion on the accuracy.
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He Z, Dong Z, Fang G, Ho JDL, Cheung CL, Chang HC, Chong CCN, Chan JYK, Chan DTM, Kwok KW. Design of a Percutaneous MRI-Guided Needle Robot With Soft Fluid-Driven Actuator. IEEE Robot Autom Lett 2020. [DOI: 10.1109/lra.2020.2969929] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Kim GH, Patel N, Yan J, Wu D, Li G, Cleary K, Iordachita I. Shoulder-mounted Robot for MRI-Guided Arthrography: Clinically Optimized System. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2019:1977-1980. [PMID: 31946287 DOI: 10.1109/embc.2019.8856630] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
This paper introduces our compact and lightweight patient-mounted MRI-compatible 4 degree-of-freedom (DOF) robot with an improved transmission system for MRI-guided arthrography procedures. This robot could make the traditional two-stage arthrography procedure (fluoroscopy-guided needle insertion followed by a diagnostic MRI scan) simpler by converting it to a one-stage procedure but more accurate with an optimized system. The new transmission system is proposed, using different mechanical components, to result in higher accuracy of needle insertion. The results of a recent accuracy study are reported. Experimental results show that the new system has an error of 1.7 mm in positioning the needle tip at a depth of 50 mm, which indicates high accuracy.
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Yamada A, Tokuda J, Naka S, Murakami K, Tani T, Morikawa S. Magnetic resonance and ultrasound image-guided navigation system using a needle manipulator. Med Phys 2019; 47:850-858. [PMID: 31829440 DOI: 10.1002/mp.13958] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Revised: 12/06/2019] [Accepted: 12/06/2019] [Indexed: 12/23/2022] Open
Abstract
PURPOSE Image guidance is crucial for percutaneous tumor ablations, enabling accurate needle-like applicator placement into target tumors while avoiding tissues that are sensitive to injury and/or correcting needle deflection. Although ultrasound (US) is widely used for image guidance, magnetic resonance (MR) is preferable due to its superior soft tissue contrast. The objective of this study was to develop and evaluate an MR and US multi-modal image-guided navigation system with a needle manipulator to enable US-guided applicator placement during MR imaging (MRI)-guided percutaneous tumor ablation. METHODS The MRI-compatible needle manipulator with US probe was installed adjacent to a 3 Tesla MRI scanner patient table. Coordinate systems for the MR image, patient table, manipulator, and US probe were all registered using an optical tracking sensor. The patient was initially scanned in the MRI scanner bore for planning and then moved outside the bore for treatment. Needle insertion was guided by real-time US imaging fused with the reformatted static MR image to enhance soft tissue contrast. Feasibility, targeting accuracy, and MR compatibility of the system were evaluated using a bovine liver and agar phantoms. RESULTS Targeting error for 50 needle insertions was 1.6 ± 0.6 mm (mean ± standard deviation). The experiment confirmed that fused MR and US images provided real-time needle localization against static MR images with soft tissue contrast. CONCLUSIONS The proposed MR and US multi-modal image-guided navigation system using a needle manipulator enabled accurate needle insertion by taking advantage of static MR and real-time US images simultaneously. Real-time visualization helped determine needle depth, tissue monitoring surrounding the needle path, target organ shifts, and needle deviation from the path.
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Affiliation(s)
- Atsushi Yamada
- Department of Research and Development for Innovative Medical Devices and Systems, Shiga University of Medical Science, Otsu, Shiga, 520-2192, Japan
| | - Junichi Tokuda
- National Center for Image Guided Therapy, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Shigeyuki Naka
- Department of Surgery, Shiga University of Medical Science, Otsu, Shiga, 520-2192, Japan
| | - Koichiro Murakami
- Department of Surgery, Shiga University of Medical Science, Otsu, Shiga, 520-2192, Japan
| | - Tohru Tani
- Department of Research and Development for Innovative Medical Devices and Systems, Shiga University of Medical Science, Otsu, Shiga, 520-2192, Japan
| | - Shigehiro Morikawa
- Molecular Neuroscience Research Center, Shiga University of Medical Science, Otsu, Shiga, 520-2192, Japan
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Ilyas F, Burbridge B, Babyn P. Health Care-Associated Infections and the Radiology Department. J Med Imaging Radiat Sci 2019; 50:596-606.e1. [PMID: 31623975 PMCID: PMC7104925 DOI: 10.1016/j.jmir.2019.07.011] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2017] [Revised: 07/01/2019] [Accepted: 07/29/2019] [Indexed: 12/12/2022]
Abstract
Health care-associated infections (HCAIs) are a significant concern for both health care workers (HCWs) and patients. They are a major contributing factor of disease in industrialized countries, and are responsible for significant morbidity, mortality, and a direct annual financial loss of $6-7 billion in North America alone. They are an increasingly challenging health issue due to multidrug-resistant pathogens such as methicillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococci among others, along with an increasing number of susceptible patients. Over the last three decades, the risk of HCAIs has increased in the radiology department (RD) in part because of an increased number of patients visiting the department and an increase in the utilization of imaging modalities. In this review, we will discuss how patients and staff can be exposed to HCAIs in the RD, including contaminated inanimate surfaces, radiology equipment, and associated medical devices. As the role of medical imaging has extended from primarily diagnosis to include more interventions, the implementation and development of standardized infection minimization protocols and infection control procedures are vital in the RD, particularly in interventional radiology. With globalisation and the rapid movement of people regionally, nationally, and globally, there is greater risk of exposure to contagious diseases such as Ebola, especially if infected patients are undiagnosed when they travel. For effective infection control, advanced training and education of HCWs in the RD is essential. The purpose of this article is to provide an overview of HCAIs as related to activities of the RD. We will discuss the following major topics including the variety of HCAIs commonly encountered, the role of the RD in HCAIs, transmission of infections to patients and HCWs in the RD, standard infection prevention measures, and the management of susceptible/infected patients in the RD. We shall also examine the role of, and the preparedness of, HCWs, including RD technologists and interventional radiologists, who may be exposed to undiagnosed, yet infected patients. We shall conclude with a brief discussion of the role of further research related to HCAIs. Learning Objectives After the completion of this review article, the readers will • Understand the exposure and role of radiology department in health care-associated infections, • Know the causes/modes/transmission of infections in radiology department, • Be conscious of standard disinfection protocols, • Be aware of current and future strategies required for the effective control of health care-associated infection in the radiology department. This is a CME article and provides the equivalent of 2 hours of continuing education that may be applied to your professional development credit system. A 10-question multiple-choice quiz follows this reading. Please note that no formalized credit (category A) is available from CAMRT.
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Affiliation(s)
- Fatima Ilyas
- Department of Medical Imaging, University of Saskatchewan, Royal University Hospital, 103 Hospital Drive, Saskatoon, Saskatchewan, Canada.
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Chen Y, Pais-Roldan P, Chen X, Frosz MH, Yu X. MRI-guided robotic arm drives optogenetic fMRI with concurrent Ca 2+ recording. Nat Commun 2019; 10:2536. [PMID: 31182714 PMCID: PMC6557837 DOI: 10.1038/s41467-019-10450-3] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2018] [Accepted: 05/11/2019] [Indexed: 12/16/2022] Open
Abstract
Optical fiber-mediated optogenetic activation and neuronal Ca2+ recording in combination with fMRI provide a multi-modal fMRI platform. Here, we developed an MRI-guided robotic arm (MgRA) as a flexible positioning system with high precision to real-time assist optical fiber brain intervention for multi-modal animal fMRI. Besides the ex vivo precision evaluation, we present the highly reliable brain activity patterns in the projected basal forebrain regions upon MgRA-driven optogenetic stimulation in the lateral hypothalamus. Also, we show the step-wise optical fiber targeting thalamic nuclei and map the region-specific functional connectivity with whole-brain fMRI accompanied by simultaneous calcium recordings to specify its circuit-specificity. The MgRA also guides the real-time microinjection to specific deep brain nuclei, which is demonstrated by an Mn-enhanced MRI method. The MgRA represents a clear advantage over the standard stereotaxic-based fiber implantation and opens a broad avenue to investigate the circuit-specific functional brain mapping with the multi-modal fMRI platform.
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Affiliation(s)
- Yi Chen
- Research Group of Translational Neuroimaging and Neural Control, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, 72076, Tuebingen, Germany
- Graduate Training Centre of Neuroscience, University of Tuebingen, 72076, Tuebingen, Germany
| | - Patricia Pais-Roldan
- Research Group of Translational Neuroimaging and Neural Control, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, 72076, Tuebingen, Germany
- Graduate Training Centre of Neuroscience, University of Tuebingen, 72076, Tuebingen, Germany
| | - Xuming Chen
- Research Group of Translational Neuroimaging and Neural Control, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, 72076, Tuebingen, Germany
- Department of Neurology, Renmin Hospital of Wuhan University, Wuhan University, 430060 Wuhan, China
| | - Michael H Frosz
- Max Planck Institute for the Science of Light, 91058, Erlangen, Germany
| | - Xin Yu
- Research Group of Translational Neuroimaging and Neural Control, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, 72076, Tuebingen, Germany.
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, 02129, USA.
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Monfaredi R, Cleary K, Sharma K. MRI Robots for Needle-Based Interventions: Systems and Technology. Ann Biomed Eng 2018; 46:1479-1497. [PMID: 29922958 DOI: 10.1007/s10439-018-2075-x] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2018] [Accepted: 06/11/2018] [Indexed: 01/13/2023]
Abstract
Magnetic resonance imaging (MRI) provides high-quality soft-tissue images of anatomical structures and radiation free imaging. The research community has focused on establishing new workflows, developing new technology, and creating robotic devices to change an MRI room from a solely diagnostic room to an interventional suite, where diagnosis and intervention can both be done in the same room. Closed bore MRI scanners provide limited access for interventional procedures using intraoperative imaging. MRI robots could improve access and procedure accuracy. Different research groups have focused on different technology aspects and anatomical structures. This paper presents the results of a systematic search of MRI robots for needle-based interventions. We report the most recent advances in the field, present relevant technologies, and discuss possible future advances. This survey shows that robotic-assisted MRI-guided prostate biopsy has received the most interest from the research community to date. Multiple successful clinical experiments have been reported in recent years that show great promise. However, in general the field of MRI robotic systems is still in the early stage. The continued development of these systems, along with partnerships with commercial vendors to bring this technology to market, is encouraged to create new and improved treatment opportunities for future patients.
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Affiliation(s)
- Reza Monfaredi
- Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Health System, 111 Michigan ave. NW, Washington, DC, 20010, USA.
| | - Kevin Cleary
- Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Health System, 111 Michigan ave. NW, Washington, DC, 20010, USA
| | - Karun Sharma
- Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Health System, 111 Michigan ave. NW, Washington, DC, 20010, USA.,Diagnostic Imaging and Radiology Department, Children's National Health System, 111 Michigan ave. NW, Washington, DC, 20010, USA
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Li D, Cheng Z, Chen G, Liu F, Wu W, Yu J, Gu Y, Liu F, Ren C, Liang P. A multimodality imaging-compatible insertion robot with a respiratory motion calibration module designed for ablation of liver tumors: a preclinical study. Int J Hyperthermia 2018; 34:1194-1201. [PMID: 29566561 DOI: 10.1080/02656736.2018.1456680] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Affiliation(s)
- Dongrui Li
- Department of Interventional Ultrasound, Chinese PLA General Hospital, Beijing, China
| | - Zhigang Cheng
- Department of Interventional Ultrasound, Chinese PLA General Hospital, Beijing, China
| | - Gang Chen
- Department of Interventional Ultrasound, Chinese PLA General Hospital, Beijing, China
| | - Fangyi Liu
- Department of Interventional Ultrasound, Chinese PLA General Hospital, Beijing, China
| | - Wenbo Wu
- Beijing Baihui Weikang Medical Robot Technology Co., Ltd, Beijing, China
| | - Jie Yu
- Department of Interventional Ultrasound, Chinese PLA General Hospital, Beijing, China
| | - Ying Gu
- Department of Laser Medicine, Chinese PLA General Hospital, Beijing, China
| | - Fengyong Liu
- Department of Intervention Therapy, Chinese PLA General Hospital, Beijing, China
| | - Chao Ren
- Department of Interventional Ultrasound, Chinese PLA General Hospital, Beijing, China
| | - Ping Liang
- Department of Interventional Ultrasound, Chinese PLA General Hospital, Beijing, China
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