Investigation of Artifacts and Optimization in Proton Resonance Frequency Thermometry Towards Heating Risk Monitoring of Implantable Medical Devices in Magnetic Resonance Imaging

被引:6
|
作者
Zhang, Feng [1 ]
Jiang, Changqing [1 ]
Li, Yichao [2 ]
Niu, Xiaoyue [3 ,4 ]
Long, Tiangang [1 ]
He, Changgeng [1 ]
Ding, Jianqi [1 ]
Li, Linze [1 ]
Li, Luming [1 ]
机构
[1] Tsinghua Univ, Sch Aerosp Engn, Natl Engn Lab Neuromodulat, Beijing 100084, Peoples R China
[2] Tsinghua Univ, Ctr Stat Sci, Beijing, Peoples R China
[3] Penn State Univ, Dept Stat, University Pk, PA 16802 USA
[4] Tsinghua Univ, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
Electrodes; Heating systems; Magnetic resonance imaging; Phantoms; Radio frequency; Lead; Temperature measurement; Artifact; deep brain stimulation; magnetic resonance thermometry; proton resonance frequency; radio frequency heating; DEEP BRAIN-STIMULATION; MRI; MODEL; FIELD; CHALLENGES; SAFETY;
D O I
10.1109/TBME.2021.3081599
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Objective: Artifacts limit the application of proton resonance frequency (PRF) thermometry for on-site, individualized heating evaluations of implantable medical devices such as deep brain stimulation (DBS) for use in magnetic resonance imaging (MRI). Its properties are unclear and the research on how to choose an unaffected measurement region is insufficient. Methods: The properties of PRF signals around the metallic DBS electrode were investigated through simulations and phantom experiments considering electromagnetic interferences from material susceptibility and the radio frequency (RF) interactions. A threshold method on phase difference Delta phi was used to define a measurement area to estimate heating at the electrode surface. Its performance was compared to that of the Bayesian magnitude method and probe measurements. Results: The B-0 magnetic field inhomogeneity due to the electrode susceptibility was the main influencing factor on PRF compared to the RF artifact. Delta phi around the electrode followed normal distribution but was distorted. Underestimation occurred at places with high temperature rises. The noise was increased and could be well estimated from magnitude images using a modified NEMA method. The Delta phi-threshold method based on this knowledge outperformed the Bayesian magnitude method by more than 42% in estimation error of the electrode heating. Conclusion: The findings favor the use of PRF with the proposed approach as a reliable method for electrode heating estimation. Significance: This study clarified the influence of device artifacts and could improve the performance of PRF thermometry for individualized heating assessments of patients with implants under MRI.
引用
收藏
页码:3638 / 3646
页数:9
相关论文
共 50 条
  • [41] Virtual Humans for Implantable Device Safety Assessment in MRI Mitigating magnetic resonance imaging hazards for implanted medical devices
    Brown, James E.
    Qiang, Rui
    Stadnik, Paul J.
    Stotts, Larry J.
    Von Arx, Jeffrey A.
    IEEE PULSE, 2017, 8 (04) : 50 - 53
  • [42] Clinical Performance of Magnetic Resonance Imaging Conditional and Nonconditional Cardiac Implantable Electronic Devices
    Shah, Anand D.
    Patel, Adarsh U.
    Knezevic, Andrea
    Hoskins, Michael H.
    Hirsh, David S.
    Merchant, Faisal M.
    El Chami, Mikhael F.
    Delurgio, David B.
    Patel, Anshul M.
    Leon, Angel R.
    Langberg, Jonathan J.
    Lloyd, Michael S.
    PACE-PACING AND CLINICAL ELECTROPHYSIOLOGY, 2017, 40 (05): : 467 - 475
  • [43] The Safety of Cardiac and Thoracic Magnetic Resonance Imaging in Patients with Cardiac Implantable Electronic Devices
    Dandamudi, Sanjay
    Collins, Jeremy D.
    Carr, James C.
    Mongkolwat, Pat
    Rahsepar, Amir A.
    Tomson, Todd T.
    Verma, Nishant
    Arora, Rishi
    Chicos, Alex B.
    Kim, Susan S.
    Lin, Albert C.
    Passman, Rod S.
    Knight, Bradley P.
    ACADEMIC RADIOLOGY, 2016, 23 (12) : 1498 - 1505
  • [44] "Power-on resets" in cardiac implantable electronic devices during magnetic resonance imaging
    Higgins, John V.
    Sheldon, Seth H.
    Watson, Robert E., Jr.
    Dalzell, Connie
    Acker, Nancy
    Cha, Yong-Mei
    Asirvatham, Samuel J.
    Kapa, Suraj
    Felmlee, Joel P.
    Friedman, Paul A.
    HEART RHYTHM, 2015, 12 (03) : 540 - 544
  • [45] Synopsis of JBS recommendations for magnetic resonance imaging in patients with cardiac implantable electronic devices
    Zghaib, Tarek
    Nazarian, Saman
    HEART, 2024, 110 (04) : 225 - 227
  • [46] Flexible Sensor for Real-Time Monitoring of Motion Artifacts in Magnetic Resonance Imaging
    Hu, Yiran
    Han, Chengcheng
    Huo, Xiaoqing
    Cao, Xiaole
    Chen, Yongyang
    Cao, Zhi
    Xu, Yong
    Tao, Li
    Wu, Zhiyi
    ACS SENSORS, 2024, 9 (05): : 2614 - 2621
  • [47] Assessment of Proton Resonance Frequency Shift Magnetic Resonance Thermography Imaging Quality for Head and Neck Tumors
    Ginat, Daniel T.
    Sammet, Steffen
    ENT-EAR NOSE & THROAT JOURNAL, 2024, 103 (03) : NP135 - NP138
  • [48] TOWARDS LOWER COST MEDICAL NUCLEAR MAGNETIC-RESONANCE IMAGING
    HILL, DW
    JOURNAL OF PHYSICS E-SCIENTIFIC INSTRUMENTS, 1984, 17 (12): : 1098 - 1099
  • [49] Accurate and fast temperature mapping during ohmic heating using proton resonance frequency shift MRI thermometry
    Ye, XF
    Ruan, R
    Chen, P
    Chang, KH
    Ning, K
    Taub, IA
    Doona, C
    JOURNAL OF FOOD ENGINEERING, 2003, 59 (2-3) : 143 - 150
  • [50] Quantitative Assessment of Artifacts on Cardiac Magnetic Resonance Imaging of Patients With Pacemakers and Implantable Cardioverter-Defibrillators
    Sasaki, Takeshi
    Hansford, Rozann
    Zviman, Menekhem M.
    Kolandaivelu, Aravindan
    Bluemke, David A.
    Berger, Ronald D.
    Calkins, Hugh
    Halperin, Henry R.
    Nazarian, Saman
    CIRCULATION-CARDIOVASCULAR IMAGING, 2011, 4 (06) : 662 - U104