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Barua R, Datta S, RoyChowdhury A, Datta P. Study of the surgical needle and biological soft tissue interaction phenomenon during insertion process for medical application: A Survey. Proc Inst Mech Eng H 2022; 236:1465-1477. [DOI: 10.1177/09544119221122024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
The insertion of the surgical needle in soft tissue has involved significant interest in the current time because of its purpose in minimally invasive surgery (MIS) and percutaneous events like biopsies, PCNL, and brachytherapy. This study represents a review of the existing condition of investigation on insertion of a surgical needle in biological living soft tissue material. As observes the issue from numerous phases, like, analysis of the cutting forces modeling (insertion), tissue material deformation, analysis of the needle deflection for the period of the needle insertion, and the robot-controlled insertion procedures. All analysis confirms that the total needle insertion force is the total of dissimilar forces spread sideways the shaft of the insertion needle for example cutting force, stiffness force, and frictional force. Various investigations have analyzed all these kinds of forces during the needle insertion process. The force data in several measures are applied for recognizing the biological tissue materials as the needle is penetrated or for path planning. The deflection of the needle during insertion and tissue material deformation is the main trouble for defined needle placing and efforts have been prepared to model them. Applying existing models numerous insertion methods are established that are discussed in this review.
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Affiliation(s)
- Ranjit Barua
- Indian Institute of Engineering Science and Technology, Howrah, West Bengal, India
| | - Sudipto Datta
- Indian Institute of Technology, Delhi, New Delhi, Delhi, India
| | - Amit RoyChowdhury
- Indian Institute of Engineering Science and Technology, Howrah, West Bengal, India
| | - Pallab Datta
- National Institute of Pharmaceutical Education and Research-Kolkata, Kolkata, West Bengal, India
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Christou AS, Amalou A, Lee H, Rivera J, Li R, Kassin MT, Varble N, Tsz Ho Tse Z, Xu S, Wood BJ. Image-Guided Robotics for Standardized and Automated Biopsy and Ablation. Semin Intervent Radiol 2021; 38:565-575. [PMID: 34853503 DOI: 10.1055/s-0041-1739164] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
Image-guided robotics for biopsy and ablation aims to minimize procedure times, reduce needle manipulations, radiation, and complications, and enable treatment of larger and more complex tumors, while facilitating standardization for more uniform and improved outcomes. Robotic navigation of needles enables standardized and uniform procedures which enhance reproducibility via real-time precision feedback, while avoiding radiation exposure to the operator. Robots can be integrated with computed tomography (CT), cone beam CT, magnetic resonance imaging, and ultrasound and through various techniques, including stereotaxy, table-mounted, floor-mounted, and patient-mounted robots. The history, challenges, solutions, and questions facing the field of interventional radiology (IR) and interventional oncology are reviewed, to enable responsible clinical adoption and value definition via ergonomics, workflows, business models, and outcome data. IR-integrated robotics is ready for broader adoption. The robots are coming!
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Affiliation(s)
- Anna S Christou
- Center for Interventional Oncology, National Institutes of Health, Bethesda, Maryland
| | - Amel Amalou
- Center for Interventional Oncology, National Institutes of Health, Bethesda, Maryland
| | - HooWon Lee
- Center for Interventional Oncology, National Institutes of Health, Bethesda, Maryland
| | - Jocelyne Rivera
- Center for Interventional Oncology, National Institutes of Health, Bethesda, Maryland
| | - Rui Li
- Tandon School of Engineering, New York University, Brooklyn, New York
| | - Michael T Kassin
- Center for Interventional Oncology, National Institutes of Health, Bethesda, Maryland
| | - Nicole Varble
- Center for Interventional Oncology, National Institutes of Health, Bethesda, Maryland.,Philips Research North America, Cambridge, Massachusetts
| | - Zion Tsz Ho Tse
- Department of Electrical Engineering, University of York, Heslington, York, United Kingdom
| | - Sheng Xu
- Center for Interventional Oncology, National Institutes of Health, Bethesda, Maryland
| | - Bradford J Wood
- Center for Interventional Oncology, National Institutes of Health, Bethesda, Maryland.,Department of Radiology and Imaging Sciences, National Institutes of Health, Bethesda, Maryland.,National Cancer Institute, National Institutes of Health, Bethesda, Maryland.,Interventional Radiology, Radiology and Imaging Sciences, National Institutes of Health, Bethesda, Maryland
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Tip Estimation Method in Phantoms for Curved Needle Using 2D Transverse Ultrasound Images. APPLIED SCIENCES-BASEL 2019. [DOI: 10.3390/app9245305] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Flexible needles have been widely used in minimally invasive surgeries, especially in percutaneous interventions. Among the interventions, tip position of the curved needle is very important, since it directly affects the success of the surgeries. In this paper, we present a method to estimate the tip position of a long-curved needle by using 2D transverse ultrasound images from a robotic ultrasound system. Ultrasound is first used to detect the cross section of long-flexible needle. A new imaging approach is proposed based on the selection of numbers of pixels with a higher gray level, which can directly remove the lower gray level to highlight the needle. After that, the needle shape tracking method is proposed by combining the image processing with the Kalman filter by using 3D needle positions, which develop a robust needle tracking procedure from 1 mm to 8 mm scan intervals. Shape reconstruction is then achieved using the curve fitting method. Finally, the needle tip position is estimated based on the curve fitting result. Experimental results showed that the estimation error of tip position is less than 1 mm within 4 mm scan intervals. The advantage of the proposed method is that the shape and tip position can be estimated through scanning the needle’s cross sections at intervals along the direction of needle insertion without detecting the tip.
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