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Zotov AK, Pushkarev AV, Alekseeva AI, Zaytsev KI, Ryabikin SS, Tsiganov DI, Zhidkov DA, Burkov IA, Kurlov VN, Dolganova IN. Optical Sensing of Tissue Freezing Depth by Sapphire Cryo-Applicator and Steady-State Diffuse Reflectance Analysis. SENSORS (BASEL, SWITZERLAND) 2024; 24:3655. [PMID: 38894444 PMCID: PMC11175356 DOI: 10.3390/s24113655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Revised: 05/31/2024] [Accepted: 06/02/2024] [Indexed: 06/21/2024]
Abstract
This work describes a sapphire cryo-applicator with the ability to sense tissue freezing depth during cryosurgery by illumination of tissue and analyzing diffuse optical signals in a steady-state regime. The applicator was manufactured by the crystal growth technique and has several spatially resolved internal channels for accommodating optical fibers. The method of reconstructing freezing depth proposed in this work requires one illumination and two detection channels. The analysis of the detected intensities yields the estimation of the time evolution of the effective attenuation coefficient, which is compared with the theoretically calculated values obtained for a number of combinations of tissue parameters. The experimental test of the proposed applicator and approach for freezing depth reconstruction was performed using gelatin-based tissue phantom and rat liver tissue in vivo. It revealed the ability to estimate depth up to 8 mm. The in vivo study confirmed the feasibility of the applicator to sense the freezing depth of living tissues despite the possible diversity of their optical parameters. The results justify the potential of the described design of a sapphire instrument for cryosurgery.
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Affiliation(s)
- Arsen K. Zotov
- Osipyan Institute of Solid State Physics of the Russian Academy of Sciences, Chernogolovka 142432, Russia; (A.K.Z.)
- Prokhorov General Physics Institute of the Russian Academy of Sciences, Moscow 119991, Russia
| | - Aleksandr V. Pushkarev
- Bauman Moscow State Technical University, Moscow 105005, Russia
- Federal State Budgetary Educational Institution of Further Professional Education “Russian Medical Academy of Continuous Professional Education”, Ministry of Healthcare of the Russian Federation, Moscow 125993, Russia
| | - Anna I. Alekseeva
- Avtsyn Research Institute of Human Morphology, FSBSI “Petrovsky National Research Centre of Surgery”, Moscow 117418, Russia
| | - Kirill I. Zaytsev
- Prokhorov General Physics Institute of the Russian Academy of Sciences, Moscow 119991, Russia
| | - Sergey S. Ryabikin
- Bauman Moscow State Technical University, Moscow 105005, Russia
- Federal State Budgetary Educational Institution of Further Professional Education “Russian Medical Academy of Continuous Professional Education”, Ministry of Healthcare of the Russian Federation, Moscow 125993, Russia
| | - Dmitry I. Tsiganov
- Bauman Moscow State Technical University, Moscow 105005, Russia
- Federal State Budgetary Educational Institution of Further Professional Education “Russian Medical Academy of Continuous Professional Education”, Ministry of Healthcare of the Russian Federation, Moscow 125993, Russia
| | - Dmitriy A. Zhidkov
- Bauman Moscow State Technical University, Moscow 105005, Russia
- Federal State Budgetary Educational Institution of Further Professional Education “Russian Medical Academy of Continuous Professional Education”, Ministry of Healthcare of the Russian Federation, Moscow 125993, Russia
| | - Ivan A. Burkov
- Bauman Moscow State Technical University, Moscow 105005, Russia
| | - Vladimir N. Kurlov
- Osipyan Institute of Solid State Physics of the Russian Academy of Sciences, Chernogolovka 142432, Russia; (A.K.Z.)
| | - Irina N. Dolganova
- Osipyan Institute of Solid State Physics of the Russian Academy of Sciences, Chernogolovka 142432, Russia; (A.K.Z.)
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Dolganova IN, Zotov AK, Safonova LP, Aleksandrova PV, Reshetov IV, Zaytsev KI, Tuchin VV, Kurlov VN. Feasibility test of a sapphire cryoprobe with optical monitoring of tissue freezing. JOURNAL OF BIOPHOTONICS 2023; 16:e202200288. [PMID: 36510652 DOI: 10.1002/jbio.202200288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 11/22/2022] [Accepted: 11/29/2022] [Indexed: 06/17/2023]
Abstract
This article describes a sapphire cryoprobe as a promising solution to the significant problem of modern cryosurgery that is the monitoring of tissue freezing. This probe consists of a sapphire rod manufactured by the edge-defined film-fed growth technique from Al2 O3 melt and optical fibers accommodated inside the rod and connected to the source and the detector. The probe's design enables detection of spatially resolved diffuse reflected intensities of tissue optical response, which are used for the estimation of tissue freezing depth. The current type of the 12.5-mm diameter sapphire probe cooled down by the liquid nitrogen assumes a superficial cryoablation. The experimental test made by using a gelatin-intralipid tissue phantom shows the feasibility of such concept, revealing the capabilities of monitoring the freezing depth up to 10 mm by the particular instrumentation realization of the probe. This justifies a potential of sapphire-based instruments aided by optical diagnosis in modern cryosurgery.
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Affiliation(s)
- Irina N Dolganova
- Osipyan Institute of Solid State Physics of the Russian Academy of Sciences, Chernogolovka, Russia
| | - Arsen K Zotov
- Osipyan Institute of Solid State Physics of the Russian Academy of Sciences, Chernogolovka, Russia
| | | | - Polina V Aleksandrova
- Prokhorov General Physics Institute of the Russian Academy of Sciences, Moscow, Russia
| | - Igor V Reshetov
- Institute for Cluster Oncology, Sechenov University, Moscow, Russia
| | - Kirill I Zaytsev
- Prokhorov General Physics Institute of the Russian Academy of Sciences, Moscow, Russia
| | - Valery V Tuchin
- Science Medical Center, Saratov State University, Saratov, Russia
- Institute of Precision Mechanics and Control, FRC "Saratov Scientific Centre of the Russian Academy of Sciences", Saratov, Russia
- Tomsk State University, Tomsk, Russia
| | - Vladimir N Kurlov
- Osipyan Institute of Solid State Physics of the Russian Academy of Sciences, Chernogolovka, Russia
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Tuna EE, Poirot NL, Franson D, Bayona JB, Huang S, Seiberlich N, Griswold MA, Cavusoglu MC. MRI Distortion Correction and Robot-to-MRI Scanner Registration for an MRI-Guided Robotic System. IEEE ACCESS : PRACTICAL INNOVATIONS, OPEN SOLUTIONS 2022; 10:99205-99220. [PMID: 37041984 PMCID: PMC10085576 DOI: 10.1109/access.2022.3207156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Magnetic resonance imaging (MRI) guided robotic procedures require safe robotic instrument navigation and precise target localization. This depends on reliable tracking of the instrument from MR images, which requires accurate registration of the robot to the scanner. A novel differential image based robot-to-MRI scanner registration approach is proposed that utilizes a set of active fiducial coils, where background subtraction method is employed for coil detection. In order to use the presented preoperative registration approach jointly with the real-time high speed MRI image acquisition and reconstruction methods in real-time interventional procedures, the effects of the geometric MRI distortion in robot to scanner registration is analyzed using a custom distortion mapping algorithm. The proposed approach is validated by a set of target coils placed within the workspace, employing multi-planar capabilities of the scanner. Registration and validation errors are respectively 2.05 mm and 2.63 mm after the distortion correction showing an improvement of respectively 1.08 mm and 0.14 mm compared to the results without distortion correction.
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Affiliation(s)
- E Erdem Tuna
- Department of Electrical, Computer, and Systems Engineering, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Nate Lombard Poirot
- Department of Electrical, Computer, and Systems Engineering, Case Western Reserve University, Cleveland, OH 44106, USA
| | | | - Juana Barrera Bayona
- School of Medicine, University of California San Francisco, San Francisco, CA 94143, USA
| | - Sherry Huang
- General Electric Healthcare, Royal Oak, MI 48067, USA
| | - Nicole Seiberlich
- Department of Radiology, University of Michigan, Ann-Anbor, MI 48109, USA
| | - Mark A Griswold
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, USA
| | - M Cenk Cavusoglu
- Department of Electrical, Computer, and Systems Engineering, Case Western Reserve University, Cleveland, OH 44106, USA
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Su H, Kwok KW, Cleary K, Iordachita I, Cavusoglu MC, Desai JP, Fischer GS. State of the Art and Future Opportunities in MRI-Guided Robot-Assisted Surgery and Interventions. PROCEEDINGS OF THE IEEE. INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS 2022; 110:968-992. [PMID: 35756185 PMCID: PMC9231642 DOI: 10.1109/jproc.2022.3169146] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/17/2023]
Abstract
Magnetic resonance imaging (MRI) can provide high-quality 3-D visualization of target anatomy, surrounding tissue, and instrumentation, but there are significant challenges in harnessing it for effectively guiding interventional procedures. Challenges include the strong static magnetic field, rapidly switching magnetic field gradients, high-power radio frequency pulses, sensitivity to electrical noise, and constrained space to operate within the bore of the scanner. MRI has a number of advantages over other medical imaging modalities, including no ionizing radiation, excellent soft-tissue contrast that allows for visualization of tumors and other features that are not readily visible by other modalities, true 3-D imaging capabilities, including the ability to image arbitrary scan plane geometry or perform volumetric imaging, and capability for multimodality sensing, including diffusion, dynamic contrast, blood flow, blood oxygenation, temperature, and tracking of biomarkers. The use of robotic assistants within the MRI bore, alongside the patient during imaging, enables intraoperative MR imaging (iMRI) to guide a surgical intervention in a closed-loop fashion that can include tracking of tissue deformation and target motion, localization of instrumentation, and monitoring of therapy delivery. With the ever-expanding clinical use of MRI, MRI-compatible robotic systems have been heralded as a new approach to assist interventional procedures to allow physicians to treat patients more accurately and effectively. Deploying robotic systems inside the bore synergizes the visual capability of MRI and the manipulation capability of robotic assistance, resulting in a closed-loop surgery architecture. This article details the challenges and history of robotic systems intended to operate in an MRI environment and outlines promising clinical applications and associated state-of-the-art MRI-compatible robotic systems and technology for making this possible.
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Affiliation(s)
- Hao Su
- Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC 27695 USA
| | - Ka-Wai Kwok
- Department of Mechanical Engineering, The University of Hong Kong, Hong Kong
| | - Kevin Cleary
- Children's National Health System, Washington, DC 20010 USA
| | - Iulian Iordachita
- Laboratory for Computational Sensing and Robotics (LCSR), Johns Hopkins University, Baltimore, MD 21218 USA
| | - M Cenk Cavusoglu
- Department of Electrical, Computer, and Systems Engineering, Case Western Reserve University, Cleveland, OH 44106 USA
| | - Jaydev P Desai
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332 USA
| | - Gregory S Fischer
- Department of Robotics Engineering, Worcester Polytechnic Institute, Worcester, MA 01609 USA
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Li G, Patel NA, Melzer A, Sharma K, Iordachita I, Cleary K. MRI-guided lumbar spinal injections with body-mounted robotic system: cadaver studies. MINIM INVASIV THER 2022; 31:297-305. [PMID: 32729771 PMCID: PMC7855543 DOI: 10.1080/13645706.2020.1799017] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Accepted: 06/26/2020] [Indexed: 02/03/2023]
Abstract
INTRODUCTION This paper reports the system integration and cadaveric assessment of a body-mounted robotic system for MRI-guided lumbar spine injections. The system is developed to enable MR-guided interventions in closed bore magnet and avoid problems due to patient movement during cannula guidance. MATERIAL AND METHODS The robot is comprised by a lightweight and compact structure so that it can be mounted directly onto the lower back of a patient using straps. Therefore, it can minimize the influence of patient movement by moving with the patient. The MR-Conditional robot is integrated with an image-guided surgical planning workstation. A dedicated clinical workflow is created for the robot-assisted procedure to improve the conventional freehand MRI-guided procedure. RESULTS Cadaver studies were performed with both freehand and robot-assisted approaches to validate the feasibility of the clinical workflow and to assess the positioning accuracy of the robotic system. The experiment results demonstrate that the root mean square (RMS) error of the target position to be 2.57 ± 1.09 mm and of the insertion angle to be 2.17 ± 0.89°. CONCLUSION The robot-assisted approach is able to provide more accurate and reproducible cannula placements than the freehand procedure, as well as to reduce the number of insertion attempts.
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Affiliation(s)
- Gang Li
- Laboratory for Computational Sensing and Robotics (LCSR), Johns Hopkins University, Baltimore, USA
| | - Niravkumar A. Patel
- Laboratory for Computational Sensing and Robotics (LCSR), Johns Hopkins University, Baltimore, USA
| | - Andreas Melzer
- Institute of Medical Science and Technology, University of Dundee, Dundee, UK
| | - Karun Sharma
- Sheikh Zayed Institute for Pediatric Surgical Innovation, Children’s National Health System, Washington, DC, USA
| | - Iulian Iordachita
- Laboratory for Computational Sensing and Robotics (LCSR), Johns Hopkins University, Baltimore, USA
| | - Kevin Cleary
- Sheikh Zayed Institute for Pediatric Surgical Innovation, Children’s National Health System, Washington, DC, USA
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Li G, Patel NA, Sharma K, Monfaredi R, Dumoulin C, Fritz J, Iordachita I, Cleary K. Body-Mounted Robotics for Interventional MRI Procedures. IEEE TRANSACTIONS ON MEDICAL ROBOTICS AND BIONICS 2020; 2:557-560. [PMID: 33778433 PMCID: PMC7996400 DOI: 10.1109/tmrb.2020.3030532] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/01/2023]
Abstract
This paper reports the development and initial cadaveric evaluation of a robotic framework for MRI-guided interventions using a body-mounted approach. The framework is developed based on modular design principles. The framework consists of a body-mounted needle placement manipulator, robot control software, robot controller, interventional planning workstation, and MRI scanner. The framework is modular in the sense that all components are connected independently, making it readily extensible and reconfigurable for supporting the clinical workflow of various interventional MRI procedures. Based on this framework we developed two body-mounted robots for musculoskeletal procedures. The first robot is a four-degree of freedom system called ArthroBot for shoulder arthrography in pediatric patients. The second robot is a six-degree of freedom system called PainBot for perineural injections used to treat pain in adult and pediatric patients. Body-mounted robots are designed with compact and lightweight structure so that they can be attached directly to the patient, which minimizes the effect of patient motion by allowing the robot to move with the patient. A dedicated clinical workflow is proposed for the MRI-guided musculoskeletal procedures using body-mounted robots. Initial cadaveric evaluations of both systems were performed to verify the feasibility of the systems and validate the clinical workflow.
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Affiliation(s)
- Gang Li
- Laboratory for Computational Sensing and Robotics (LCSR), Johns Hopkins University, Baltimore, MD, USA
| | - Niravkumar A Patel
- Laboratory for Computational Sensing and Robotics (LCSR), Johns Hopkins University, Baltimore, MD, USA
| | - Karun Sharma
- Sheikh Zayed Institute for Pediatric Surgical Innovation, Childrens National Hospital, Washington, DC, USA
| | - Reza Monfaredi
- Sheikh Zayed Institute for Pediatric Surgical Innovation, Childrens National Hospital, Washington, DC, USA
| | - Charles Dumoulin
- Cincinnati Childrens Hospital Medical Center, Cincinnati, OH, USA
| | - Jan Fritz
- New York University, New York, NY, USA
| | - Iulian Iordachita
- Laboratory for Computational Sensing and Robotics (LCSR), Johns Hopkins University, Baltimore, MD, USA
| | - Kevin Cleary
- Sheikh Zayed Institute for Pediatric Surgical Innovation, Childrens National Hospital, Washington, DC, USA
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Tuna EE, Poirot NL, Bayona JB, Franson D, Huang S, Narvaez J, Seiberlich N, Griswold M, Çavuşoğlu MC. Differential Image Based Robot to MRI Scanner Registration with Active Fiducial Markers for an MRI-Guided Robotic Catheter System. PROCEEDINGS OF THE ... IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS. IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS 2020; 2020:2958-2964. [PMID: 34136309 PMCID: PMC8202025 DOI: 10.1109/iros45743.2020.9341043] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
In magnetic resonance imaging (MRI) guided robotic catheter ablation procedures, reliable tracking of the catheter within the MRI scanner is needed to safely navigate the catheter. This requires accurate registration of the catheter to the scanner. This paper presents a differential, multi-slice image-based registration approach utilizing active fiducial coils. The proposed method would be used to preoperatively register the MRI image space with the physical catheter space. In the proposed scheme, the registration is performed with the help of a registration frame, which has a set of embedded electromagnetic coils designed to actively create MRI image artifacts. These coils are detected in the MRI scanner's coordinate system by background subtraction. The detected coil locations in each slice are weighted by the artifact size and then registered to known ground truth coil locations in the catheter's coordinate system via least-squares fitting. The proposed approach is validated by using a set of target coils placed withing the workspace, employing multi-planar capabilities of the MRI scanner. The average registration and validation errors are respectively computed as 1.97 mm and 2.49 mm. The multi-slice approach is also compared to the single-slice method and shown to improve registration and validation by respectively 0.45 mm and 0.66 mm.
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Affiliation(s)
- E Erdem Tuna
- Department of Electrical, Computer, and Systems Engineering, Case Western Reserve University, Cleveland, OH, USA
| | - Nate Lombard Poirot
- Department of Electrical, Computer, and Systems Engineering, Case Western Reserve University, Cleveland, OH, USA
| | - Juana Barrera Bayona
- Department of Electrical, Computer, and Systems Engineering, Case Western Reserve University, Cleveland, OH, USA
| | - Dominique Franson
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
| | - Sherry Huang
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
| | - Julian Narvaez
- Department of Electrical, Computer, and Systems Engineering, Case Western Reserve University, Cleveland, OH, USA
| | | | - Mark Griswold
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
| | - M Cenk Çavuşoğlu
- Department of Electrical, Computer, and Systems Engineering, Case Western Reserve University, Cleveland, OH, USA
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Li G, Patel NA, Wang Y, Dumoulin C, Loew W, Loparo O, Schneider K, Sharma K, Cleary K, Fritz J, Iordachita I. Fully Actuated Body-Mounted Robotic System for MRI-Guided Lower Back Pain Injections: Initial Phantom and Cadaver Studies. IEEE Robot Autom Lett 2020; 5:5245-5251. [PMID: 33748414 PMCID: PMC7971162 DOI: 10.1109/lra.2020.3007459] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
This paper reports the improved design, system integration, and initial experimental evaluation of a fully actuated body-mounted robotic system for real-time MRI-guided lower back pain injections. The 6-DOF robot is composed of a 4-DOF needle alignment module and a 2-DOF remotely actuated needle driver module, which together provide a fully actuated manipulator that can operate inside the scanner bore during imaging. The system minimizes the need to move the patient in and out of the scanner during a procedure, and thus may shorten the procedure time and streamline the clinical workflow. The robot is devised with a compact and lightweight structure that can be attached directly to the patient's lower back via straps. This approach minimizes the effect of patient motion by allowing the robot to move with the patient. The robot is integrated with an image-based surgical planning module. A dedicated clinical workflow is proposed for robot-assisted lower back pain injections under real-time MRI guidance. Targeting accuracy of the system was evaluated with a real-time MRI-guided phantom study, demonstrating the mean absolute errors (MAE) of the tip position to be 1.50±0.68mm and of the needle angle to be 1.56±0.93°. An initial cadaver study was performed to validate the feasibility of the clinical workflow, indicating the maximum error of the position to be less than 1.90mm and of the angle to be less than 3.14°.
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Affiliation(s)
- Gang Li
- Gang Li, Niravkumar A. Patel, Yanzhou Wang, and Iulian Iordachita are with Laboratory for Computational Sensing and Robotics (LCSR), Johns Hopkins University, Baltimore, MD, USA
| | - Niravkumar A Patel
- Gang Li, Niravkumar A. Patel, Yanzhou Wang, and Iulian Iordachita are with Laboratory for Computational Sensing and Robotics (LCSR), Johns Hopkins University, Baltimore, MD, USA
| | - Yanzhou Wang
- Gang Li, Niravkumar A. Patel, Yanzhou Wang, and Iulian Iordachita are with Laboratory for Computational Sensing and Robotics (LCSR), Johns Hopkins University, Baltimore, MD, USA
| | - Charles Dumoulin
- Charles Dumoulin, Wolfgang Loew, Olivia Loparo, and Katherine Schneider are with Cincinnati Childrens Hospital Medical Center, Cincinnati, OH, USA
| | - Wolfgang Loew
- Charles Dumoulin, Wolfgang Loew, Olivia Loparo, and Katherine Schneider are with Cincinnati Childrens Hospital Medical Center, Cincinnati, OH, USA
| | - Olivia Loparo
- Charles Dumoulin, Wolfgang Loew, Olivia Loparo, and Katherine Schneider are with Cincinnati Childrens Hospital Medical Center, Cincinnati, OH, USA
| | - Katherine Schneider
- Charles Dumoulin, Wolfgang Loew, Olivia Loparo, and Katherine Schneider are with Cincinnati Childrens Hospital Medical Center, Cincinnati, OH, USA
| | - Karun Sharma
- Karun Sharma and Kevin Cleary are with the Sheikh Zayed Institute for Pediatric Surgical Innovation, Childrens National Hospital, Washington, DC, USA
| | - Kevin Cleary
- Karun Sharma and Kevin Cleary are with the Sheikh Zayed Institute for Pediatric Surgical Innovation, Childrens National Hospital, Washington, DC, USA
| | - Jan Fritz
- Jan Fritz is with Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Iulian Iordachita
- Gang Li, Niravkumar A. Patel, Yanzhou Wang, and Iulian Iordachita are with Laboratory for Computational Sensing and Robotics (LCSR), Johns Hopkins University, Baltimore, MD, USA
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