Minimally Invasive Live Tissue High-Fidelity Thermophysical Modeling Using Real-Time Thermography

被引:5
|
作者
El-Kebir, Hamza [1 ]
Ran, Junren [2 ]
Lee, Yongseok [2 ]
Chamorro, Leonardo P. [2 ]
Ostoja-Starzewski, Martin [2 ]
Berlin, Richard [3 ,4 ]
Cornejo, Gabriela M. Aguiluz [5 ]
Benedetti, Enrico [5 ]
Giulianotti, Pier C. [5 ]
Bentsman, Joseph [6 ]
机构
[1] Univ Illinois, Dept Aerosp Engn, Urbana, IL USA
[2] Univ Illinois, Dept Mech Sci & Engn, Urbana, IL USA
[3] Carle Hosp, Dept Trauma Surg, Urbana, IL USA
[4] Carle Illinois Coll Med, Dept Biomed & Translat Sci, Urbana, IL USA
[5] Univ Illinois, Dept Surg, Chicago, IL USA
[6] Univ Illinois, Dept Mech Sci & Engn, Urbana, IL 61801 USA
基金
美国国家卫生研究院;
关键词
Biomedical infrared imaging; thermography; tissue thermodynamics; real-time model estimation; THERMAL-CONDUCTIVITY;
D O I
10.1109/TBME.2022.3230728
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
We present a novel thermodynamic parameter estimation framework for energy-based surgery on live tissue, with direct applications to tissue characterization during electrosurgery. This framework addresses the problem of estimating tissue-specific thermodynamics in real-time, which would enable accurate prediction of thermal damage impact to the tissue and damage-conscious planning of electrosurgical procedures. Our approach provides basic thermodynamic information such as thermal diffusivity, and also allows for obtaining the thermal relaxation time and a model of the heat source, yielding in real-time a controlled hyperbolic thermodynamics model. The latter accounts for the finite thermal propagation time necessary for modeling of the electrosurgical action, in which the probe motion speed often surpasses the speed of thermal propagation in the tissue operated on. Our approach relies solely on thermographer feedback and a knowledge of the power level and position of the electrosurgical pencil, imposing only very minor adjustments to normal electrosurgery to obtain a high-fidelity model of the tissue-probe interaction. Our method is minimally invasive and can be performed in situ. We apply our method first to simulated data based on porcine muscle tissue to verify its accuracy and then to in vivo liver tissue, and compare the results with those from the literature. This comparison shows that parameterizing the Maxwell-Cattaneo model through the framework proposed yields a noticeably higher fidelity real-time adaptable representation of the thermodynamic tissue response to the electrosurgical impact than currently available. A discussion on the differences between the live and the dead tissue thermodynamics is also provided.
引用
收藏
页码:1849 / 1857
页数:9
相关论文
共 50 条
  • [21] Developing optoelectronic methods for real-time tissue characterization in minimally invasive surgery
    Narayan, Meenakshi
    Bhowmick, Mithun
    ADVANCED BIOMEDICAL AND CLINICAL DIAGNOSTIC AND SURGICAL GUIDANCE SYSTEMS XXI, 2023, 12368
  • [22] High-Fidelity Real-Time Hardware-in-the-Loop Emulation of PMSM Inverter Drives
    Poon, Jason
    Chai, Elaina
    Celanovic, Ivan
    Genic, Adrien
    Adzic, Evgenije
    2013 IEEE ENERGY CONVERSION CONGRESS AND EXPOSITION (ECCE), 2013, : 1760 - 1764
  • [23] Air-dropped Sensor Network for Real-time High-fidelity Volcano Monitoring
    Song, Wen-Zhan
    Huang, Renjie
    Xu, Mingsen
    Ma, Andy
    Shirazi, Behrooz
    LaHusen, Richard
    MOBISYS'09: PROCEEDINGS OF THE 7TH ACM INTERNATIONAL CONFERENCE ON MOBILE SYSTEMS, APPLICATIONS, AND SERVICES, 2009, : 305 - 318
  • [24] Introducing MantisBot: Hexapod Robot Controlled by a High-Fidelity, Real-Time Neural Simulation
    Szczecinski, Nicholas S.
    Chrzanowski, David M.
    Cofer, David W.
    Terrasi, Andrea S.
    Moore, David R.
    Martin, Joshua P.
    Ritzmann, Roy E.
    Quinn, Roger D.
    2015 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2015, : 3875 - 3881
  • [25] WG-WaveNet: Real-Time High-Fidelity Speech Synthesis without GPU
    Hsu, Po-chun
    Lee, Hung-yi
    INTERSPEECH 2020, 2020, : 210 - 214
  • [26] High-Fidelity Real-Time Imaging With Electromagnetic Logging-While-Drilling Measurements
    Thiel, Michael
    Omeragic, Dzevat
    IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING, 2017, 3 (02): : 369 - 378
  • [27] Padding-enabled real-time high-fidelity temporal single pixel imaging
    Keyaki, Ryota
    Matsuno, Jin
    Fukatsu, Susumu
    APPLIED PHYSICS EXPRESS, 2025, 18 (01)
  • [28] VocGAN: A High-Fidelity Real-time Vocoder with a Hierarchically-nested Adversarial Network
    Yang, Jinhyeok
    Lee, Junmo
    Kim, Youngik
    Cho, Hoon-Young
    Kim, Injung
    INTERSPEECH 2020, 2020, : 200 - 204
  • [29] Poster: Enabling High-Fidelity and Real-Time Mobility Digital Twin with Edge Computing
    Liu, Yueyang
    Wang, Haoxin
    Cai, Zhipeng
    Chen, Dawei
    Han, Kyungtae
    2022 IEEE/ACM 7TH SYMPOSIUM ON EDGE COMPUTING (SEC 2022), 2022, : 281 - 283
  • [30] Nonlinear Behavioral Modeling and Real-Time Simulation of Electric Propulsion System for the High-Fidelity X-in-the-Loop Applications
    Bai, Hao
    Li, Qian
    Luo, Huan
    Huangfu, Yigeng
    Gao, Fei
    IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION, 2023, 9 (01) : 1708 - 1722