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Rabbani N, Calvet L, Espinel Y, Le Roy B, Ribeiro M, Buc E, Bartoli A. A methodology and clinical dataset with ground-truth to evaluate registration accuracy quantitatively in computer-assisted Laparoscopic Liver Resection. COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING: IMAGING & VISUALIZATION 2021. [DOI: 10.1080/21681163.2021.1997642] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
- N. Rabbani
- EnCoV, Institut Pascal, Clermont-Ferrand, France
| | - L. Calvet
- EnCoV, Institut Pascal, Clermont-Ferrand, France
- CHU, Clermont-Ferrand, France
- IRIT, University of Toulouse
| | - Y. Espinel
- EnCoV, Institut Pascal, Clermont-Ferrand, France
| | - B. Le Roy
- EnCoV, Institut Pascal, Clermont-Ferrand, France
- CHU, Saint-Etienne, France
| | - M. Ribeiro
- EnCoV, Institut Pascal, Clermont-Ferrand, France
- CHU, Clermont-Ferrand, France
| | - E. Buc
- EnCoV, Institut Pascal, Clermont-Ferrand, France
- CHU, Clermont-Ferrand, France
| | - A. Bartoli
- EnCoV, Institut Pascal, Clermont-Ferrand, France
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Heiselman JS, Jarnagin WR, Miga MI. Intraoperative Correction of Liver Deformation Using Sparse Surface and Vascular Features via Linearized Iterative Boundary Reconstruction. IEEE TRANSACTIONS ON MEDICAL IMAGING 2020; 39:2223-2234. [PMID: 31976882 PMCID: PMC7314378 DOI: 10.1109/tmi.2020.2967322] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
During image guided liver surgery, soft tissue deformation can cause considerable error when attempting to achieve accurate localization of the surgical anatomy through image-to-physical registration. In this paper, a linearized iterative boundary reconstruction technique is proposed to account for these deformations. The approach leverages a superposed formulation of boundary conditions to rapidly and accurately estimate the deformation applied to a preoperative model of the organ given sparse intraoperative data of surface and subsurface features. With this method, tracked intraoperative ultrasound (iUS) is investigated as a potential data source for augmenting registration accuracy beyond the capacity of conventional organ surface registration. In an expansive simulated dataset, features including vessel contours, vessel centerlines, and the posterior liver surface are extracted from iUS planes. Registration accuracy is compared across increasing data density to establish how iUS can be best employed to improve target registration error (TRE). From a baseline average TRE of 11.4 ± 2.2 mm using sparse surface data only, incorporating additional sparse features from three iUS planes improved average TRE to 6.4 ± 1.0 mm. Furthermore, increasing the sparse coverage to 16 tracked iUS planes improved average TRE to 3.9 ± 0.7 mm, exceeding the accuracy of registration based on complete surface data available with more cumbersome intraoperative CT without contrast. Additionally, the approach was applied to three clinical cases where on average error improved 67% over rigid registration and 56% over deformable surface registration when incorporating additional features from one independent tracked iUS plane.
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Affiliation(s)
| | - William R. Jarnagin
- Department of Surgery at Memorial Sloan Kettering Cancer Center, New York, NY 10065 USA
| | - Michael I. Miga
- Department of Biomedical Engineering at Vanderbilt University, Nashville, TN 37235 USA
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Augmented reality technology for preoperative planning and intraoperative navigation during hepatobiliary surgery: A review of current methods. Hepatobiliary Pancreat Dis Int 2018; 17:101-112. [PMID: 29567047 DOI: 10.1016/j.hbpd.2018.02.002] [Citation(s) in RCA: 61] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2017] [Accepted: 11/16/2017] [Indexed: 02/05/2023]
Abstract
BACKGROUND Augmented reality (AR) technology is used to reconstruct three-dimensional (3D) images of hepatic and biliary structures from computed tomography and magnetic resonance imaging data, and to superimpose the virtual images onto a view of the surgical field. In liver surgery, these superimposed virtual images help the surgeon to visualize intrahepatic structures and therefore, to operate precisely and to improve clinical outcomes. DATA SOURCES The keywords "augmented reality", "liver", "laparoscopic" and "hepatectomy" were used for searching publications in the PubMed database. The primary source of literatures was from peer-reviewed journals up to December 2016. Additional articles were identified by manual search of references found in the key articles. RESULTS In general, AR technology mainly includes 3D reconstruction, display, registration as well as tracking techniques and has recently been adopted gradually for liver surgeries including laparoscopy and laparotomy with video-based AR assisted laparoscopic resection as the main technical application. By applying AR technology, blood vessels and tumor structures in the liver can be displayed during surgery, which permits precise navigation during complex surgical procedures. Liver transformation and registration errors during surgery were the main factors that limit the application of AR technology. CONCLUSIONS With recent advances, AR technologies have the potential to improve hepatobiliary surgical procedures. However, additional clinical studies will be required to evaluate AR as a tool for reducing postoperative morbidity and mortality and for the improvement of long-term clinical outcomes. Future research is needed in the fusion of multiple imaging modalities, improving biomechanical liver modeling, and enhancing image data processing and tracking technologies to increase the accuracy of current AR methods.
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Heiselman JS, Clements LW, Collins JA, Weis JA, Simpson AL, Geevarghese SK, Kingham TP, Jarnagin WR, Miga MI. Characterization and correction of intraoperative soft tissue deformation in image-guided laparoscopic liver surgery. J Med Imaging (Bellingham) 2017; 5:021203. [PMID: 29285519 DOI: 10.1117/1.jmi.5.2.021203] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2017] [Accepted: 11/21/2017] [Indexed: 12/12/2022] Open
Abstract
Laparoscopic liver surgery is challenging to perform due to a compromised ability of the surgeon to localize subsurface anatomy in the constrained environment. While image guidance has the potential to address this barrier, intraoperative factors, such as insufflation and variable degrees of organ mobilization from supporting ligaments, may generate substantial deformation. The severity of laparoscopic deformation in humans has not been characterized, and current laparoscopic correction methods do not account for the mechanics of how intraoperative deformation is applied to the liver. We first measure the degree of laparoscopic deformation at two insufflation pressures over the course of laparoscopic-to-open conversion in 25 patients. With this clinical data alongside a mock laparoscopic phantom setup, we report a biomechanical correction approach that leverages anatomically load-bearing support surfaces from ligament attachments to iteratively reconstruct and account for intraoperative deformations. Laparoscopic deformations were significantly larger than deformations associated with open surgery, and our correction approach yielded subsurface target error of [Formula: see text] and surface error of [Formula: see text] using only sparse surface data with realistic surgical extent. Laparoscopic surface data extents were examined and found to impact registration accuracy. Finally, we demonstrate viability of the correction method with clinical data.
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Affiliation(s)
- Jon S Heiselman
- Vanderbilt University, Department of Biomedical Engineering, Nashville, Tennessee, United States.,Vanderbilt University, Vanderbilt Institute for Surgery and Engineering, Nashville, Tennessee, United States
| | - Logan W Clements
- Vanderbilt University, Department of Biomedical Engineering, Nashville, Tennessee, United States.,Vanderbilt University, Vanderbilt Institute for Surgery and Engineering, Nashville, Tennessee, United States
| | - Jarrod A Collins
- Vanderbilt University, Department of Biomedical Engineering, Nashville, Tennessee, United States.,Vanderbilt University, Vanderbilt Institute for Surgery and Engineering, Nashville, Tennessee, United States
| | - Jared A Weis
- Wake Forest School of Medicine, Department of Biomedical Engineering, Winston-Salem, North Carolina, United States
| | - Amber L Simpson
- Memorial Sloan-Kettering Cancer Center, Hepatopancreatobiliary Service, Department of Surgery, New York, New York, United States
| | - Sunil K Geevarghese
- Vanderbilt University Medical Center, Division of Hepatobiliary Surgery and Liver Transplantation, Nashville, Tennessee, United States
| | - T Peter Kingham
- Memorial Sloan-Kettering Cancer Center, Hepatopancreatobiliary Service, Department of Surgery, New York, New York, United States
| | - William R Jarnagin
- Memorial Sloan-Kettering Cancer Center, Hepatopancreatobiliary Service, Department of Surgery, New York, New York, United States
| | - Michael I Miga
- Vanderbilt University, Department of Biomedical Engineering, Nashville, Tennessee, United States.,Vanderbilt University, Vanderbilt Institute for Surgery and Engineering, Nashville, Tennessee, United States
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5
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Collins JA, Weis JA, Heiselman JS, Clements LW, Simpson AL, Jarnagin WR, Miga MI. Improving Registration Robustness for Image-Guided Liver Surgery in a Novel Human-to-Phantom Data Framework. IEEE TRANSACTIONS ON MEDICAL IMAGING 2017; 36:1502-1510. [PMID: 28212080 PMCID: PMC5757161 DOI: 10.1109/tmi.2017.2668842] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
In open image-guided liver surgery (IGLS), a sparse representation of the intraoperative organ surface can be acquired to drive image-to-physical registration. We hypothesize that uncharacterized error induced by variation in the collection patterns of organ surface data limits the accuracy and robustness of an IGLS registration. Clinical validation of such registration methods is challenged due to the difficulty in obtaining data representative of the true state of organ deformation. We propose a novel human-to-phantom validation framework that transforms surface collection patterns from in vivo IGLS procedures (n = 13) onto a well-characterized hepatic deformation phantom for the purpose of validating surface-driven, volumetric nonrigid registration methods. An important feature of the approach is that it centers on combining workflow-realistic data acquisition and surgical deformations that are appropriate in behavior and magnitude. Using the approach, we investigate volumetric target registration error (TRE) with both current rigid IGLS and our improved nonrigid registration methods. Additionally, we introduce a spatial data resampling approach to mitigate the workflow-sensitive sampling problem. Using our human-to-phantom approach, TRE after routine rigid registration was 10.9 ± 0.6 mm with a signed closest point distance associated with residual surface fit in the range of ±10 mm, highly representative of open liver resections. After applying our novel resampling strategy and improved deformation correction method, TRE was reduced by 51%, i.e., a TRE of 5.3 ± 0.5 mm. This paper reported herein realizes a novel tractable approach for the validation of image-to-physical registration methods and demonstrates promising results for our correction method.
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Affiliation(s)
| | - Jared A. Weis
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235 USA
| | - Jon S. Heiselman
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235 USA
| | - Logan W. Clements
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235 USA
| | | | | | - Michael I. Miga
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235 USA
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Si W, Liao X, Wang Q, Heng PA. Personalized heterogeneous deformable model for fast volumetric registration. Biomed Eng Online 2017; 16:30. [PMID: 28219432 PMCID: PMC5319060 DOI: 10.1186/s12938-017-0321-3] [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: 10/12/2016] [Accepted: 02/10/2017] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Biomechanical deformable volumetric registration can help improve safety of surgical interventions by ensuring the operations are extremely precise. However, this technique has been limited by the accuracy and the computational efficiency of patient-specific modeling. METHODS This study presents a tissue-tissue coupling strategy based on penalty method to model the heterogeneous behavior of deformable body, and estimate the personalized tissue-tissue coupling parameters in a data-driven way. Moreover, considering that the computational efficiency of biomechanical model is highly dependent on the mechanical resolution, a practical coarse-to-fine scheme is proposed to increase runtime efficiency. Particularly, a detail enrichment database is established in an offline fashion to represent the mapping relationship between the deformation results of high-resolution hexahedral mesh extracted from the raw medical data and a newly constructed low-resolution hexahedral mesh. At runtime, the mechanical behavior of human organ under interactions is simulated with this low-resolution hexahedral mesh, then the microstructures are synthesized in virtue of the detail enrichment database. RESULTS The proposed method is validated by volumetric registration in an abdominal phantom compression experiments. Our personalized heterogeneous deformable model can well describe the coupling effects between different tissues of the phantom. Compared with high-resolution heterogeneous deformable model, the low-resolution deformable model with our detail enrichment database can achieve 9.4× faster, and the average target registration error is 3.42 mm, which demonstrates that the proposed method shows better volumetric registration performance than state-of-the-art. CONCLUSIONS Our framework can well balance the precision and efficiency, and has great potential to be adopted in the practical augmented reality image-guided robotic systems.
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Affiliation(s)
- Weixin Si
- Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong.,Shenzhen Key Laboratory of Virtual Reality and Human Interaction Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, 503644, Shenzhen, China
| | - Xiangyun Liao
- Shenzhen Key Laboratory of Virtual Reality and Human Interaction Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, 503644, Shenzhen, China
| | - Qiong Wang
- Shenzhen Key Laboratory of Virtual Reality and Human Interaction Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, 503644, Shenzhen, China.
| | - Pheng Ann Heng
- Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong.,Shenzhen Key Laboratory of Virtual Reality and Human Interaction Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, 503644, Shenzhen, China
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Ong R, Glisson CL, Burgner-Kahrs J, Simpson A, Danilchenko A, Lathrop R, Herrell SD, Webster RJ, Miga M, Galloway RL. A novel method for texture-mapping conoscopic surfaces for minimally invasive image-guided kidney surgery. Int J Comput Assist Radiol Surg 2016; 11:1515-26. [PMID: 26758889 PMCID: PMC4942405 DOI: 10.1007/s11548-015-1339-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2015] [Accepted: 12/09/2015] [Indexed: 10/22/2022]
Abstract
PURPOSE Organ-level registration is critical to image-guided therapy in soft tissue. This is especially important in organs such as the kidney which can freely move. We have developed a method for registration that combines three-dimensional locations from a holographic conoscope with an endoscopically obtained textured surface. By combining these data sources clear decisions as to the tissue from which the points arise can be made. METHODS By localizing the conoscope's laser dot in the endoscopic space, we register the textured surface to the cloud of conoscopic points. This allows the cloud of points to be filtered for only those arising from the kidney surface. Once a valid cloud is obtained we can use standard surface registration techniques to perform the image-space to physical-space registration. Since our methods use two distinct data sources we test for spatial accuracy and characterize temporal effects in phantoms, ex vivo porcine and human kidneys. In addition we use an industrial robot to provide controlled motion and positioning for characterizing temporal effects. RESULTS Our initial surface acquisitions are hand-held. This means that we take approximately 55 s to acquire a surface. At that rate we see no temporal effects due to acquisition synchronization or probe speed. Our surface registrations were able to find applied targets with submillimeter target registration errors. CONCLUSION The results showed that the textured surfaces could be reconstructed with submillimetric mean registration errors. While this paper focuses on kidney applications, this method could be applied to any anatomical structures where a line of sight can be created via open or minimally invasive surgical techniques.
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Affiliation(s)
- Rowena Ong
- Medtronic Surgical Technologies, Louisville, CO, 80027, USA
| | - Courtenay L Glisson
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, 37235, USA
| | | | - Amber Simpson
- Memorial Sloan Cancer Center, New York City, NY, USA
| | | | - Ray Lathrop
- Department of Mechanical Engineering, Vanderbilt University, Nashville, TN, 37235, USA
| | - S Duke Herrell
- Department of Urologic Surgery, Vanderbilt Medical Center, Nashville, TN, 37235, USA
| | - Robert J Webster
- Department of Mechanical Engineering, Vanderbilt University, Nashville, TN, 37235, USA
| | - Michael Miga
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, 37235, USA
| | - Robert L Galloway
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, 37235, USA.
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Time-Of-Flight Camera, Optical Tracker and Computed Tomography in Pairwise Data Registration. PLoS One 2016; 11:e0159493. [PMID: 27434396 PMCID: PMC4951045 DOI: 10.1371/journal.pone.0159493] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2015] [Accepted: 07/05/2016] [Indexed: 11/21/2022] Open
Abstract
Purpose A growing number of medical applications, including minimal invasive surgery, depends on multi-modal or multi-sensors data processing. Fast and accurate 3D scene analysis, comprising data registration, seems to be crucial for the development of computer aided diagnosis and therapy. The advancement of surface tracking system based on optical trackers already plays an important role in surgical procedures planning. However, new modalities, like the time-of-flight (ToF) sensors, widely explored in non-medical fields are powerful and have the potential to become a part of computer aided surgery set-up. Connection of different acquisition systems promises to provide a valuable support for operating room procedures. Therefore, the detailed analysis of the accuracy of such multi-sensors positioning systems is needed. Methods We present the system combining pre-operative CT series with intra-operative ToF-sensor and optical tracker point clouds. The methodology contains: optical sensor set-up and the ToF-camera calibration procedures, data pre-processing algorithms, and registration technique. The data pre-processing yields a surface, in case of CT, and point clouds for ToF-sensor and marker-driven optical tracker representation of an object of interest. An applied registration technique is based on Iterative Closest Point algorithm. Results The experiments validate the registration of each pair of modalities/sensors involving phantoms of four various human organs in terms of Hausdorff distance and mean absolute distance metrics. The best surface alignment was obtained for CT and optical tracker combination, whereas the worst for experiments involving ToF-camera. Conclusion The obtained accuracies encourage to further develop the multi-sensors systems. The presented substantive discussion concerning the system limitations and possible improvements mainly related to the depth information produced by the ToF-sensor is useful for computer aided surgery developers.
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Clements LW, Collins JA, Weis JA, Simpson AL, Adams LB, Jarnagin WR, Miga MI. Evaluation of model-based deformation correction in image-guided liver surgery via tracked intraoperative ultrasound. J Med Imaging (Bellingham) 2016; 3:015003. [PMID: 27081664 DOI: 10.1117/1.jmi.3.1.015003] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2015] [Accepted: 02/11/2016] [Indexed: 11/14/2022] Open
Abstract
Soft-tissue deformation represents a significant error source in current surgical navigation systems used for open hepatic procedures. While numerous algorithms have been proposed to rectify the tissue deformation that is encountered during open liver surgery, clinical validation of the proposed methods has been limited to surface-based metrics, and subsurface validation has largely been performed via phantom experiments. The proposed method involves the analysis of two deformation-correction algorithms for open hepatic image-guided surgery systems via subsurface targets digitized with tracked intraoperative ultrasound (iUS). Intraoperative surface digitizations were acquired via a laser range scanner and an optically tracked stylus for the purposes of computing the physical-to-image space registration and for use in retrospective deformation-correction algorithms. Upon completion of surface digitization, the organ was interrogated with a tracked iUS transducer where the iUS images and corresponding tracked locations were recorded. Mean closest-point distances between the feature contours delineated in the iUS images and corresponding three-dimensional anatomical model generated from preoperative tomograms were computed to quantify the extent to which the deformation-correction algorithms improved registration accuracy. The results for six patients, including eight anatomical targets, indicate that deformation correction can facilitate reduction in target error of [Formula: see text].
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Affiliation(s)
- Logan W Clements
- Vanderbilt University , Department of Biomedical Engineering, 5824 Stevenson Center, Nashville, Tennessee 37232, United States
| | - Jarrod A Collins
- Vanderbilt University , Department of Biomedical Engineering, 5824 Stevenson Center, Nashville, Tennessee 37232, United States
| | - Jared A Weis
- Vanderbilt University , Department of Biomedical Engineering, 5824 Stevenson Center, Nashville, Tennessee 37232, United States
| | - Amber L Simpson
- Memorial Sloan-Kettering Cancer Center , Department of Surgery, 1275 York Avenue, New York, New York 10065, United States
| | - Lauryn B Adams
- Memorial Sloan-Kettering Cancer Center , Department of Surgery, 1275 York Avenue, New York, New York 10065, United States
| | - William R Jarnagin
- Memorial Sloan-Kettering Cancer Center , Department of Surgery, 1275 York Avenue, New York, New York 10065, United States
| | - Michael I Miga
- Vanderbilt University , Department of Biomedical Engineering, 5824 Stevenson Center, Nashville, Tennessee 37232, United States
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10
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Reichard D, Bodenstedt S, Suwelack S, Mayer B, Preukschas A, Wagner M, Kenngott H, Müller-Stich B, Dillmann R, Speidel S. Intraoperative on-the-fly organ-mosaicking for laparoscopic surgery. J Med Imaging (Bellingham) 2015; 2:045001. [PMID: 26693166 DOI: 10.1117/1.jmi.2.4.045001] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2015] [Accepted: 11/04/2015] [Indexed: 11/14/2022] Open
Abstract
The goal of computer-assisted surgery is to provide the surgeon with guidance during an intervention, e.g., using augmented reality. To display preoperative data, soft tissue deformations that occur during surgery have to be taken into consideration. Laparoscopic sensors, such as stereo endoscopes, can be used to create a three-dimensional reconstruction of stereo frames for registration. Due to the small field of view and the homogeneous structure of tissue, reconstructing just one frame, in general, will not provide enough detail to register preoperative data, since every frame only contains a part of an organ surface. A correct assignment to the preoperative model is possible only if the patch geometry can be unambiguously matched to a part of the preoperative surface. We propose and evaluate a system that combines multiple smaller reconstructions from different viewpoints to segment and reconstruct a large model of an organ. Using graphics processing unit-based methods, we achieved four frames per second. We evaluated the system with in silico, phantom, ex vivo, and in vivo (porcine) data, using different methods for estimating the camera pose (optical tracking, iterative closest point, and a combination). The results indicate that the proposed method is promising for on-the-fly organ reconstruction and registration.
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Affiliation(s)
- Daniel Reichard
- Karlsruhe Institute of Technology , Institute for Anthropomatics and Robotics, Adenauerring 2, D-76131 Karlsruhe, Germany
| | - Sebastian Bodenstedt
- Karlsruhe Institute of Technology , Institute for Anthropomatics and Robotics, Adenauerring 2, D-76131 Karlsruhe, Germany
| | - Stefan Suwelack
- Karlsruhe Institute of Technology , Institute for Anthropomatics and Robotics, Adenauerring 2, D-76131 Karlsruhe, Germany
| | - Benjamin Mayer
- University of Heidelberg , Department of General, Abdominal and Transplantation Surgery, Im Neuenheimer Feld 110, D-69120 Heidelberg, Germany
| | - Anas Preukschas
- University of Heidelberg , Department of General, Abdominal and Transplantation Surgery, Im Neuenheimer Feld 110, D-69120 Heidelberg, Germany
| | - Martin Wagner
- University of Heidelberg , Department of General, Abdominal and Transplantation Surgery, Im Neuenheimer Feld 110, D-69120 Heidelberg, Germany
| | - Hannes Kenngott
- University of Heidelberg , Department of General, Abdominal and Transplantation Surgery, Im Neuenheimer Feld 110, D-69120 Heidelberg, Germany
| | - Beat Müller-Stich
- University of Heidelberg , Department of General, Abdominal and Transplantation Surgery, Im Neuenheimer Feld 110, D-69120 Heidelberg, Germany
| | - Rüdiger Dillmann
- Karlsruhe Institute of Technology , Institute for Anthropomatics and Robotics, Adenauerring 2, D-76131 Karlsruhe, Germany
| | - Stefanie Speidel
- Karlsruhe Institute of Technology , Institute for Anthropomatics and Robotics, Adenauerring 2, D-76131 Karlsruhe, Germany
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Azagury DE, Dua MM, Barrese JC, Henderson JM, Buchs NC, Ris F, Cloyd JM, Martinie JB, Razzaque S, Nicolau S, Soler L, Marescaux J, Visser BC. Image-guided surgery. Curr Probl Surg 2015; 52:476-520. [PMID: 26683419 DOI: 10.1067/j.cpsurg.2015.10.001] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2015] [Accepted: 10/01/2015] [Indexed: 12/11/2022]
Affiliation(s)
- Dan E Azagury
- Department of Surgery, Stanford University School of Medicine, Stanford, CA
| | - Monica M Dua
- Department of Surgery, Stanford University School of Medicine, Stanford, CA
| | - James C Barrese
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA
| | - Jaimie M Henderson
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA
| | - Nicolas C Buchs
- Department of Surgery, University Hospital of Geneva, Clinic for Visceral and Transplantation Surgery, Geneva, Switzerland
| | - Frederic Ris
- Department of Surgery, University Hospital of Geneva, Clinic for Visceral and Transplantation Surgery, Geneva, Switzerland
| | - Jordan M Cloyd
- Department of Surgery, Stanford University School of Medicine, Stanford, CA
| | - John B Martinie
- Department of Surgery, Carolinas Healthcare System, Charlotte, NC
| | - Sharif Razzaque
- Department of Surgery, Carolinas Healthcare System, Charlotte, NC
| | - Stéphane Nicolau
- IRCAD (Research Institute Against Digestive Cancer), Strasbourg, France
| | - Luc Soler
- IRCAD (Research Institute Against Digestive Cancer), Strasbourg, France
| | - Jacques Marescaux
- IRCAD (Research Institute Against Digestive Cancer), Strasbourg, France
| | - Brendan C Visser
- Department of Surgery, Stanford University School of Medicine, Stanford, CA.
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A clinically applicable laser-based image-guided system for laparoscopic liver procedures. Int J Comput Assist Radiol Surg 2015; 11:1499-513. [PMID: 26476640 DOI: 10.1007/s11548-015-1309-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2015] [Accepted: 09/24/2015] [Indexed: 10/22/2022]
Abstract
PURPOSE Laser range scanners (LRS) allow performing a surface scan without physical contact with the organ, yielding higher registration accuracy for image-guided surgery (IGS) systems. However, the use of LRS-based registration in laparoscopic liver surgery is still limited because current solutions are composed of expensive and bulky equipment which can hardly be integrated in a surgical scenario. METHODS In this work, we present a novel LRS-based IGS system for laparoscopic liver procedures. A triangulation process is formulated to compute the 3D coordinates of laser points by using the existing IGS system tracking devices. This allows the use of a compact and cost-effective LRS and therefore facilitates the integration into the laparoscopic setup. The 3D laser points are then reconstructed into a surface to register to the preoperative liver model using a multi-level registration process. RESULTS Experimental results show that the proposed system provides submillimeter scanning precision and accuracy comparable to those reported in the literature. Further quantitative analysis shows that the proposed system is able to achieve a patient-to-image registration accuracy, described as target registration error, of [Formula: see text]. CONCLUSIONS We believe that the presented approach will lead to a faster integration of LRS-based registration techniques in the surgical environment. Further studies will focus on optimizing scanning time and on the respiratory motion compensation.
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Suwelack S, Röhl S, Bodenstedt S, Reichard D, Dillmann R, dos Santos T, Maier-Hein L, Wagner M, Wünscher J, Kenngott H, Müller BP, Speidel S. Physics-based shape matching for intraoperative image guidance. Med Phys 2014; 41:111901. [DOI: 10.1118/1.4896021] [Citation(s) in RCA: 56] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
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14
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dos Santos TR, Seitel A, Kilgus T, Suwelack S, Wekerle AL, Kenngott H, Speidel S, Schlemmer HP, Meinzer HP, Heimann T, Maier-Hein L. Pose-independent surface matching for intra-operative soft-tissue marker-less registration. Med Image Anal 2014; 18:1101-14. [DOI: 10.1016/j.media.2014.06.002] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2013] [Revised: 04/10/2014] [Accepted: 06/11/2014] [Indexed: 10/25/2022]
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Kumar AN, Miga MI, Pheiffer TS, Chambless LB, Thompson RC, Dawant BM. Persistent and automatic intraoperative 3D digitization of surfaces under dynamic magnifications of an operating microscope. Med Image Anal 2014; 19:30-45. [PMID: 25189364 DOI: 10.1016/j.media.2014.07.004] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2013] [Revised: 07/22/2014] [Accepted: 07/23/2014] [Indexed: 12/15/2022]
Abstract
One of the major challenges impeding advancement in image-guided surgical (IGS) systems is the soft-tissue deformation during surgical procedures. These deformations reduce the utility of the patient's preoperative images and may produce inaccuracies in the application of preoperative surgical plans. Solutions to compensate for the tissue deformations include the acquisition of intraoperative tomographic images of the whole organ for direct displacement measurement and techniques that combines intraoperative organ surface measurements with computational biomechanical models to predict subsurface displacements. The later solution has the advantage of being less expensive and amenable to surgical workflow. Several modalities such as textured laser scanners, conoscopic holography, and stereo-pair cameras have been proposed for the intraoperative 3D estimation of organ surfaces to drive patient-specific biomechanical models for the intraoperative update of preoperative images. Though each modality has its respective advantages and disadvantages, stereo-pair camera approaches used within a standard operating microscope is the focus of this article. A new method that permits the automatic and near real-time estimation of 3D surfaces (at 1 Hz) under varying magnifications of the operating microscope is proposed. This method has been evaluated on a CAD phantom object and on full-length neurosurgery video sequences (∼1 h) acquired intraoperatively by the proposed stereovision system. To the best of our knowledge, this type of validation study on full-length brain tumor surgery videos has not been done before. The method for estimating the unknown magnification factor of the operating microscope achieves accuracy within 0.02 of the theoretical value on a CAD phantom and within 0.06 on 4 clinical videos of the entire brain tumor surgery. When compared to a laser range scanner, the proposed method for reconstructing 3D surfaces intraoperatively achieves root mean square errors (surface-to-surface distance) in the 0.28-0.81 mm range on the phantom object and in the 0.54-1.35 mm range on 4 clinical cases. The digitization accuracy of the presented stereovision methods indicate that the operating microscope can be used to deliver the persistent intraoperative input required by computational biomechanical models to update the patient's preoperative images and facilitate active surgical guidance.
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Affiliation(s)
- Ankur N Kumar
- Vanderbilt University, Department of Electrical Engineering, Nashville, TN 37235, USA
| | - Michael I Miga
- Vanderbilt University, Department of Biomedical Engineering, Nashville, TN 37235, USA
| | - Thomas S Pheiffer
- Vanderbilt University, Department of Biomedical Engineering, Nashville, TN 37235, USA
| | - Lola B Chambless
- Vanderbilt University Medical Center, Department of Neurological Surgery, Nashville, TN 37232, USA
| | - Reid C Thompson
- Vanderbilt University Medical Center, Department of Neurological Surgery, Nashville, TN 37232, USA
| | - Benoit M Dawant
- Vanderbilt University, Department of Electrical Engineering, Nashville, TN 37235, USA
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Sun K, Pheiffer TS, Simpson AL, Weis JA, Thompson RC, Miga MI. Near Real-Time Computer Assisted Surgery for Brain Shift Correction Using Biomechanical Models. IEEE JOURNAL OF TRANSLATIONAL ENGINEERING IN HEALTH AND MEDICINE 2014; 2:2500113. [PMID: 25914864 PMCID: PMC4405800 DOI: 10.1109/jtehm.2014.2327628] [Citation(s) in RCA: 47] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/05/2013] [Revised: 12/17/2013] [Accepted: 05/05/2014] [Indexed: 11/05/2022]
Abstract
Conventional image-guided neurosurgery relies on preoperative images to provide surgical navigational information and visualization. However, these images are no longer accurate once the skull has been opened and brain shift occurs. To account for changes in the shape of the brain caused by mechanical (e.g., gravity-induced deformations) and physiological effects (e.g., hyperosmotic drug-induced shrinking, or edema-induced swelling), updated images of the brain must be provided to the neuronavigation system in a timely manner for practical use in the operating room. In this paper, a novel preoperative and intraoperative computational processing pipeline for near real-time brain shift correction in the operating room was developed to automate and simplify the processing steps. Preoperatively, a computer model of the patient's brain with a subsequent atlas of potential deformations due to surgery is generated from diagnostic image volumes. In the case of interim gross changes between diagnosis, and surgery when reimaging is necessary, our preoperative pipeline can be generated within one day of surgery. Intraoperatively, sparse data measuring the cortical brain surface is collected using an optically tracked portable laser range scanner. These data are then used to guide an inverse modeling framework whereby full volumetric brain deformations are reconstructed from precomputed atlas solutions to rapidly match intraoperative cortical surface shift measurements. Once complete, the volumetric displacement field is used to update, i.e., deform, preoperative brain images to their intraoperative shifted state. In this paper, five surgical cases were analyzed with respect to the computational pipeline and workflow timing. With respect to postcortical surface data acquisition, the approximate execution time was 4.5 min. The total update process which included positioning the scanner, data acquisition, inverse model processing, and image deforming was ~11-13 min. In addition, easily implemented hardware, software, and workflow processes were identified for improved performance in the near future.
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Affiliation(s)
- Kay Sun
- Department of Biomedical EngineeringVanderbilt UniversityNashvilleTN37235USA
| | - Thomas S. Pheiffer
- Department of Biomedical EngineeringVanderbilt UniversityNashvilleTN37235USA
| | - Amber L. Simpson
- Department of Biomedical EngineeringVanderbilt UniversityNashvilleTN37235USA
| | - Jared A. Weis
- Department of Biomedical EngineeringVanderbilt UniversityNashvilleTN37235USA
| | - Reid C. Thompson
- Department of Neurological SurgeryVanderbilt University Medical CenterNashvilleTN37232USA
| | - Michael I. Miga
- Department of Biomedical EngineeringVanderbilt UniversityNashvilleTN37235USA
- Department of Neurological SurgeryVanderbilt University Medical CenterNashvilleTN37232USA
- Department of Radiology and Radiological SciencesVanderbilt University Medical CenterNashvilleTN37232USA
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Rucker DC, Wu Y, Clements LW, Ondrake JE, Pheiffer TS, Simpson AL, Jarnagin WR, Miga MI. A Mechanics-Based Nonrigid Registration Method for Liver Surgery Using Sparse Intraoperative Data. IEEE TRANSACTIONS ON MEDICAL IMAGING 2014; 33:147-58. [PMID: 24107926 PMCID: PMC4057359 DOI: 10.1109/tmi.2013.2283016] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
In open abdominal image-guided liver surgery, sparse measurements of the organ surface can be taken intraoperatively via a laser-range scanning device or a tracked stylus with relatively little impact on surgical workflow. We propose a novel nonrigid registration method which uses sparse surface data to reconstruct a mapping between the preoperative CT volume and the intraoperative patient space. The mapping is generated using a tissue mechanics model subject to boundary conditions consistent with surgical supportive packing during liver resection therapy. Our approach iteratively chooses parameters which define these boundary conditions such that the deformed tissue model best fits the intraoperative surface data. Using two liver phantoms, we gathered a total of five deformation datasets with conditions comparable to open surgery. The proposed nonrigid method achieved a mean target registration error (TRE) of 3.3 mm for targets dispersed throughout the phantom volume, using a limited region of surface data to drive the nonrigid registration algorithm, while rigid registration resulted in a mean TRE of 9.5 mm. In addition, we studied the effect of surface data extent, the inclusion of subsurface data, the trade-offs of using a nonlinear tissue model, robustness to rigid misalignments, and the feasibility in five clinical datasets.
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Affiliation(s)
- D. Caleb Rucker
- Department of Mechanical, Aerospace, and Biomedical Engineering, University of Tennessee, Knoxville, TN 37996 USA
| | - Yifei Wu
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235 USA
| | - Logan W. Clements
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235 USA
| | - Janet E. Ondrake
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235 USA
| | - Thomas S. Pheiffer
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235 USA
| | - Amber L. Simpson
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235 USA
| | | | - Michael I. Miga
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235 USA
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18
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Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery. Med Image Anal 2013; 17:974-96. [DOI: 10.1016/j.media.2013.04.003] [Citation(s) in RCA: 182] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2012] [Revised: 04/05/2013] [Accepted: 04/12/2013] [Indexed: 12/16/2022]
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Reaungamornrat S, Liu WP, Wang AS, Otake Y, Nithiananthan S, Uneri A, Schafer S, Tryggestad E, Richmon J, Sorger JM, Siewerdsen JH, Taylor RH. Deformable image registration for cone-beam CT guided transoral robotic base-of-tongue surgery. Phys Med Biol 2013; 58:4951-79. [PMID: 23807549 PMCID: PMC3990286 DOI: 10.1088/0031-9155/58/14/4951] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Transoral robotic surgery (TORS) offers a minimally invasive approach to resection of base-of-tongue tumors. However, precise localization of the surgical target and adjacent critical structures can be challenged by the highly deformed intraoperative setup. We propose a deformable registration method using intraoperative cone-beam computed tomography (CBCT) to accurately align preoperative CT or MR images with the intraoperative scene. The registration method combines a Gaussian mixture (GM) model followed by a variation of the Demons algorithm. First, following segmentation of the volume of interest (i.e. volume of the tongue extending to the hyoid), a GM model is applied to surface point clouds for rigid initialization (GM rigid) followed by nonrigid deformation (GM nonrigid). Second, the registration is refined using the Demons algorithm applied to distance map transforms of the (GM-registered) preoperative image and intraoperative CBCT. Performance was evaluated in repeat cadaver studies (25 image pairs) in terms of target registration error (TRE), entropy correlation coefficient (ECC) and normalized pointwise mutual information (NPMI). Retraction of the tongue in the TORS operative setup induced gross deformation >30 mm. The mean TRE following the GM rigid, GM nonrigid and Demons steps was 4.6, 2.1 and 1.7 mm, respectively. The respective ECC was 0.57, 0.70 and 0.73, and NPMI was 0.46, 0.57 and 0.60. Registration accuracy was best across the superior aspect of the tongue and in proximity to the hyoid (by virtue of GM registration of surface points on these structures). The Demons step refined registration primarily in deeper portions of the tongue further from the surface and hyoid bone. Since the method does not use image intensities directly, it is suitable to multi-modality registration of preoperative CT or MR with intraoperative CBCT. Extending the 3D image registration to the fusion of image and planning data in stereo-endoscopic video is anticipated to support safer, high-precision base-of-tongue robotic surgery.
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Affiliation(s)
- S Reaungamornrat
- Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA
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Burgner J, Simpson AL, Fitzpatrick JM, Lathrop RA, Herrell SD, Miga MI, Webster RJ. A study on the theoretical and practical accuracy of conoscopic holography-based surface measurements: toward image registration in minimally invasive surgery. Int J Med Robot 2013; 9:190-203. [PMID: 22761086 PMCID: PMC3819208 DOI: 10.1002/rcs.1446] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/08/2012] [Indexed: 11/10/2022]
Abstract
BACKGROUND Registered medical images can assist with surgical navigation and enable image-guided therapy delivery. In soft tissues, surface-based registration is often used and can be facilitated by laser surface scanning. Tracked conoscopic holography (which provides distance measurements) has been recently proposed as a minimally invasive way to obtain surface scans. Moving this technique from concept to clinical use requires a rigorous accuracy evaluation, which is the purpose of our paper. METHODS We adapt recent non-homogeneous and anisotropic point-based registration results to provide a theoretical framework for predicting the accuracy of tracked distance measurement systems. Experiments are conducted a complex objects of defined geometry, an anthropomorphic kidney phantom and a human cadaver kidney. RESULTS Experiments agree with model predictions, producing point RMS errors consistently < 1 mm, surface-based registration with mean closest point error < 1 mm in the phantom and a RMS target registration error of 0.8 mm in the human cadaver kidney. CONCLUSIONS Tracked conoscopic holography is clinically viable; it enables minimally invasive surface scan accuracy comparable to current clinical methods that require open surgery.
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Affiliation(s)
- J Burgner
- Department of Mechanical Engineering, Vanderbilt University, Nashville, TN, USA.
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21
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Simpson AL, Dumpuri P, Ondrake JE, Weis JA, Jarnagin WR, Miga MI. Preliminary study of a novel method for conveying corrected image volumes in surgical navigation. Int J Med Robot 2012; 9:109-18. [PMID: 22991306 DOI: 10.1002/rcs.1459] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/21/2012] [Indexed: 11/11/2022]
Abstract
BACKGROUND Commercial image-guided surgery systems rely on the fundamental assumption that preoperative medical images represent the physical state of the patient in the operating room. The guidance display typically consists of a three-dimensional (3D) model derived from medical images and three orthogonal views of the imaging data. A challenging question in image-guided surgery is: what happens when the images used in the guidance display no longer correspond to the current geometric state of the anatomy and guidance information is still desirable? METHODS We modify the conventional display with two techniques for incorporating a displacement field from a finite-element model into the guidance display and present a preliminary study of the effect of our method on performance with a simple surgical task. The topic of this paper is methods for conveying the computational model solution, not the model itself. To address the integration of the computational model solution into the display, a novel method of applying the deformation to the tool tip was developed, which quickly corrects for deformation but also maintains the pristine nature of the preoperative images. We compare the proposed technique to an existing method that applies the deformation field to the image volume. RESULTS A pilot study compared mean performance with our method of applying the deformation to the tool tip and the conventional technique. These methods were statistically similar with respect to accuracy of localization (p < 0.05) and amount of time (p < 0.05) required for localization of the target. CONCLUSIONS These results suggest that our new technique can be used in place of the computationally expensive task of deforming the image volume, without affecting the time or accuracy of the surgical task. Most notably, our work addresses the problem of incorporating deformation correction into the guidance display and offers a first step toward understanding its effect on surgical performance.
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Affiliation(s)
- Amber L Simpson
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA.
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Kingham TP, Scherer MA, Neese BW, Clements LW, Stefansic JD, Jarnagin WR. Image-guided liver surgery: intraoperative projection of computed tomography images utilizing tracked ultrasound. HPB (Oxford) 2012; 14:594-603. [PMID: 22882196 PMCID: PMC3461385 DOI: 10.1111/j.1477-2574.2012.00487.x] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
BACKGROUND Ultrasound (US) is the most commonly used form of image guidance during liver surgery. However, the use of navigation systems that incorporate instrument tracking and three-dimensional visualization of preoperative tomography is increasing. This report describes an initial experience using an image-guidance system with navigated US. METHODS An image-guidance system was used in a total of 50 open liver procedures to aid in localization and targeting of liver lesions. An optical tracking system was employed to localize surgical instruments. Customized hardware and calibration of the US transducer were required. The results of three procedures are highlighted in order to illustrate specific navigation techniques that proved useful in the broader patient cohort. RESULTS Over a 7-month span, the navigation system assisted in completing 21 (42%) of the procedures, and tracked US alone provided additional information required to perform resection or ablation in six procedures (12%). Average registration time during the three illustrative procedures was <1 min. Average set-up time was approximately 5 min per procedure. CONCLUSIONS The Explorer™ Liver guidance system represents novel technology that continues to evolve. This initial experience indicates that image guidance is valuable in certain procedures, specifically in cases in which difficult anatomy or tumour location or echogenicity limit the usefulness of traditional guidance methods.
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Affiliation(s)
- T Peter Kingham
- Department of Surgery, Hepatobiliary Service, Memorial Sloan–Kettering Cancer CenterNew York, NY, USA
| | | | | | | | | | - William R Jarnagin
- Department of Surgery, Hepatobiliary Service, Memorial Sloan–Kettering Cancer CenterNew York, NY, USA
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Simpson AL, Burgner J, Glisson CL, Herrell SD, Ma B, Pheiffer TS, Webster RJ, Miga MI. Comparison study of intraoperative surface acquisition methods for surgical navigation. IEEE Trans Biomed Eng 2012; 60:1090-9. [PMID: 22929367 DOI: 10.1109/tbme.2012.2215033] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Soft-tissue image-guided interventions often require the digitization of organ surfaces for providing correspondence from medical images to the physical patient in the operating room. In this paper, the effect of several inexpensive surface acquisition techniques on target registration error and surface registration error (SRE) for soft tissue is investigated. A systematic approach is provided to compare image-to-physical registrations using three different methods of organ spatial digitization: 1) a tracked laser-range scanner (LRS), 2) a tracked pointer, and 3) a tracked conoscopic holography sensor (called a conoprobe). For each digitization method, surfaces of phantoms and biological tissues were acquired and registered to CT image volume counterparts. A comparison among these alignments demonstrated that registration errors were statistically smaller with the conoprobe than the tracked pointer and LRS (p<0.01). In all acquisitions, the conoprobe outperformed the LRS and tracked pointer: for example, the arithmetic means of the SRE over all data acquisitions with a porcine liver were 1.73 ± 0.77 mm, 3.25 ± 0.78 mm, and 4.44 ± 1.19 mm for the conoprobe, LRS, and tracked pointer, respectively. In a cadaveric kidney specimen, the arithmetic means of the SRE over all trials of the conoprobe and tracked pointer were 1.50 ± 0.50 mm and 3.51 ± 0.82 mm, respectively. Our results suggest that tissue displacements due to contact force and attempts to maintain contact with tissue, compromise registrations that are dependent on data acquired from a tracked surgical instrument and we provide an alternative method (tracked conoscopic holography) of digitizing surfaces for clinical usage. The tracked conoscopic holography device outperforms LRS acquisitions with respect to registration accuracy.
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Affiliation(s)
- Amber L Simpson
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA.
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Najmaei N, Mostafavi K, Shahbazi S, Azizian M. Image-guided techniques in renal and hepatic interventions. Int J Med Robot 2012; 9:379-95. [DOI: 10.1002/rcs.1443] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/30/2012] [Indexed: 12/24/2022]
Affiliation(s)
- Nima Najmaei
- Canadian Surgical Technologies and Advanced Robotics (CSTAR); London Health Science Center; London ON Canada
- Department of Electrical and Computer Engineering; University of Western Ontario; London ON Canada
| | - Kamal Mostafavi
- Department of Mechanical Engineering; University of Western Ontario; London ON Canada
| | - Sahar Shahbazi
- Department of Electrical and Computer Engineering; University of Western Ontario; London ON Canada
| | - Mahdi Azizian
- Sheikh Zayed Institute for Pediatric Surgical Innovation; Children's National Medical Center; Washington DC USA
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Galloway RL, Herrell SD, Miga MI. Image-Guided Abdominal Surgery and Therapy Delivery. JOURNAL OF HEALTHCARE ENGINEERING 2012; 3:203-228. [PMID: 25077012 PMCID: PMC4112601 DOI: 10.1260/2040-2295.3.2.203] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/01/2011] [Accepted: 07/01/2011] [Indexed: 01/31/2023]
Abstract
Image-Guided Surgery has become the standard of care in intracranial neurosurgery providing more exact resections while minimizing damage to healthy tissue. Moving that process to abdominal organs presents additional challenges in the form of image segmentation, image to physical space registration, organ motion and deformation. In this paper, we present methodologies and results for addressing these challenges in two specific organs: the liver and the kidney.
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Affiliation(s)
- Robert L. Galloway
- Department of Biomedical Engineering
- Department of Neurosurgery
- Department of Surgery
| | | | - Michael I. Miga
- Department of Biomedical Engineering
- Department of Neurosurgery
- Department of Radiology and Radiological Sciences Vanderbilt University
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Pheiffer TS, Simpson AL, Lennon B, Thompson RC, Miga MI. Design and evaluation of an optically-tracked single-CCD laser range scanner. Med Phys 2012; 39:636-42. [PMID: 22320772 DOI: 10.1118/1.3675397] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
PURPOSE Acquisition of laser range scans of an organ surface has the potential to efficiently provide measurements of geometric changes to soft tissue during a surgical procedure. A laser range scanner design is reported here which has been developed to drive intraoperative updates to conventional image-guided neurosurgery systems. METHODS The scanner is optically-tracked in the operating room with a multiface passive target. The novel design incorporates both the capture of surface geometry (via laser illumination) and color information (via visible light collection) through a single-lens onto the same charge-coupled device (CCD). The accuracy of the geometric data was evaluated by scanning a high-precision phantom and comparing relative distances between landmarks in the scans with the corresponding ground truth (known) distances. The range-of-motion of the scanner with respect to the optical camera was determined by placing the scanner in common operating room configurations while sampling the visibility of the reflective spheres. The tracking accuracy was then analyzed by fixing the scanner and phantom in place, perturbing the optical camera around the scene, and observing variability in scan locations with respect to a tracked pen probe ground truth as the camera tracked the same scene from different positions. RESULTS The geometric accuracy test produced a mean error and standard deviation of 0.25 ± 0.40 mm with an RMS error of 0.47 mm. The tracking tests showed that the scanner could be tracked at virtually all desired orientations required in the OR set up, with an overall tracking error and standard deviation of 2.2 ± 1.0 mm with an RMS error of 2.4 mm. There was no discernible difference between any of the three faces on the lasers range scanner (LRS) with regard to tracking accuracy. CONCLUSIONS A single-lens laser range scanner design was successfully developed and implemented with sufficient scanning and tracking accuracy for image-guided surgery.
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Affiliation(s)
- Thomas S Pheiffer
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA.
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Simpson AL, Dumpuri P, Jarnagin WR, Miga MI. Model-Assisted Image-Guided Liver Surgery Using Sparse Intraoperative Data. STUDIES IN MECHANOBIOLOGY, TISSUE ENGINEERING AND BIOMATERIALS 2012. [DOI: 10.1007/8415_2012_117] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
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Abstract
First used medically in 1985, robots now make an impact in laparoscopy, neurosurgery, orthopedic surgery, emergency response, and various other medical disciplines. This paper provides a review of medical robot history and surveys the capabilities of current medical robot systems, primarily focusing on commercially available systems while covering a few prominent research projects. By examining robotic systems across time and disciplines, trends are discernible that imply future capabilities of medical robots, for example, increased usage of intraoperative images, improved robot arm design, and haptic feedback to guide the surgeon.
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