A Safe Framework for Quantitative In Vivo Human Evaluation of Image Guidance

被引:0
|
作者
Cannon, Piper C. [1 ]
Ferguson, James M. [1 ]
Pitt, E. Bryn [1 ]
Shrand, Jason A. [1 ]
Setia, Shaan A. [2 ]
Nimmagadda, Naren [2 ,3 ]
Barth, Eric J. [1 ]
Kavoussi, Nicholas L. [2 ]
Galloway, Robert L. [1 ]
Herrell, S. Duke [2 ]
Webster, Robert J. [1 ]
机构
[1] Vanderbilt Univ, Nashville, TN 37235 USA
[2] Vanderbilt Univ, Med Ctr, Nashville, TN 37232 USA
[3] Johns Hopkins Univ, Sch Med, Baltimore, MD 21287 USA
来源
IEEE OPEN JOURNAL OF ENGINEERING IN MEDICINE AND BIOLOGY | 2024年 / 5卷
基金
美国国家卫生研究院;
关键词
Surgery; Protocols; Robots; Phantoms; Kidney; In vivo; Three-dimensional displays; Image-guided surgery; partial nephrectomy; robotic surgery; LAPAROSCOPIC PARTIAL NEPHRECTOMY; SURGERY SYSTEM; TECHNOLOGY; ACCURACY; TRACKING; DISPLAY; MODEL;
D O I
10.1109/OJEMB.2023.3271853
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Goal: We present a new framework for in vivo image guidance evaluation and provide a case study on robotic partial nephrectomy. Methods: This framework (called the "bystander protocol") involves two surgeons, one who solely performs the therapeutic process without image guidance, and another who solely periodically collects data to evaluate image guidance. This isolates the evaluation from the therapy, so that in-development image guidance systems can be tested without risk of negatively impacting the standard of care. We provide a case study applying this protocol in clinical cases during robotic partial nephrectomy surgery. Results: The bystander protocol was performed successfully in 6 patient cases. We find average lesion centroid localization error with our IGS system to be 6.5 mm in vivo compared to our prior result of 3.0 mm in phantoms. Conclusions: The bystander protocol is a safe, effective method for testing in-development image guidance systems in human subjects.
引用
收藏
页码:133 / 139
页数:7
相关论文
共 50 条
  • [21] Experimental Evaluation of Human Motion Prediction Toward Safe and Efficient Human Robot Collaboration
    Zhao, Weiye
    Sun, Liting
    Liu, Changliu
    Tomizuka, Masayoshi
    2020 AMERICAN CONTROL CONFERENCE (ACC), 2020, : 4349 - 4354
  • [22] In Vivo Evaluation of Quantitative MR Angiography in a Canine Carotid Artery Stenosis Model
    Calderon-Arnulphi, M.
    Amin-Hanjani, S.
    Alaraj, A.
    Zhao, M.
    Du, X.
    Ruland, S.
    Zhou, X. J.
    Thulborn, K. R.
    Charbel, F. T.
    AMERICAN JOURNAL OF NEURORADIOLOGY, 2011, 32 (08) : 1552 - 1559
  • [23] An Optimized Triple Modality Reporter for Quantitative In Vivo Tumor Imaging and Therapy Evaluation
    Levin, Rachel A.
    Felsen, Csilla N.
    Yang, Jin
    Lin, John Y.
    Whitney, Michael A.
    Nguyen, Quyen T.
    Tsien, Roger Y.
    PLOS ONE, 2014, 9 (05):
  • [24] Methodological Research on Image Registration Based on Human Brain Tissue In Vivo
    Nan, Jiaofen
    Su, Junya
    Zhang, Jincan
    ELECTRONICS, 2023, 12 (03)
  • [25] An MR-Safe Endovascular Robotic Platform: Design, Control, and Ex-Vivo Evaluation
    Kundrat, Dennis
    Dagnino, Giulio
    Kwok, Trevor M. Y.
    Abdelaziz, Mohamed E. M. K.
    Chi, Wenqiang
    Nguyen, Anh
    Riga, Celia
    Yang, Guang-Zhong
    IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2021, 68 (10) : 3110 - 3121
  • [26] Evaluation of surface image guidance and Deep inspiration Breath Hold technique for breast treatments with Halcyon
    Crop, Frederik
    Laffarguette, Julien
    Achag, Ilias
    Pasquier, David
    Mirabel, Xavier
    Cayez, Romain
    Lacornerie, Thomas
    PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS, 2023, 108
  • [27] Evaluation of coronary stenosis with the aid of quantitative image analysis in histological cross sections
    Dulohery, Kate
    Papavdi, Asteria
    Michalodimitrakis, Manolis
    Kranioti, Elena F.
    JOURNAL OF FORENSIC AND LEGAL MEDICINE, 2012, 19 (08) : 485 - 489
  • [28] The Atlas Benchmark: an Automated Evaluation Framework for Human Motion Prediction
    Rudenko, Andrey
    Palmieri, Luigi
    Huang, Wanting
    Lilienthal, Achim J.
    Arras, Kai O.
    2022 31ST IEEE INTERNATIONAL CONFERENCE ON ROBOT AND HUMAN INTERACTIVE COMMUNICATION (IEEE RO-MAN 2022), 2022, : 636 - 643
  • [29] In-Vivo Hyperspectral Human Brain Image Database for Brain Cancer Detection
    Fabelo, Himar
    Ortega, Samuel
    Szolna, Adam
    Bulters, Diederik
    Pineiro, Juan F.
    Kabwama, Silvester
    J-O'Shanahan, Aruma
    Bulstrode, Harry
    Bisshopp, Sara
    Kiran, B. Ravi
    Ravi, Daniele
    Lazcano, Raquel
    Madronal, Daniel
    Sosa, Coralia
    Espino, Carlos
    Marquez, Mariano
    De La Luz Plaza, Maria
    Camacho, Rafael
    Carrera, David
    Hernandez, Maria
    Callico, Gustavo M.
    Morera Molina, Jesus
    Stanciulescu, Bogdan
    Yang, Guang-Zhong
    Salvador, Ruben
    Juarez, Eduardo
    Sanz, Cesar
    Sarmiento, Roberto
    IEEE ACCESS, 2019, 7 : 39098 - 39116
  • [30] Toward Safe Retinal Microsurgery: Development and Evaluation of an RNN-Based Active Interventional Control Framework
    He, Changyan
    Patel, Niravkumar
    Shahbazi, Mahya
    Yang, Yang
    Gehlbach, Peter
    Kobilarov, Marin
    Iordachita, Iulian
    IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2020, 67 (04) : 966 - 977