1
|
He Z, Soullié P, Lefebvre P, Ambarki K, Felblinger J, Odille F. Changes of in vivo electrical conductivity in the brain and torso related to age, fat fraction and sex using MRI. Sci Rep 2024; 14:16109. [PMID: 38997324 PMCID: PMC11245625 DOI: 10.1038/s41598-024-67014-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2024] [Accepted: 07/08/2024] [Indexed: 07/14/2024] Open
Abstract
This work was inspired by the observation that a majority of MR-electrical properties tomography studies are based on direct comparisons with ex vivo measurements carried out on post-mortem samples in the 90's. As a result, the in vivo conductivity values obtained from MRI in the megahertz range in different types of tissues (brain, liver, tumors, muscles, etc.) found in the literature may not correspond to their ex vivo equivalent, which still serves as a reference for electromagnetic modelling. This study aims to pave the way for improving current databases since the definition of personalized electromagnetic models (e.g. for Specific Absorption Rate estimation) would benefit from better estimation. Seventeen healthy volunteers underwent MRI of both brain and thorax/abdomen using a three-dimensional ultrashort echo-time (UTE) sequence. We estimated conductivity (S/m) in several classes of macroscopic tissue using a customized reconstruction method from complex UTE images, and give general statistics for each of these regions (mean-median-standard deviation). These values are used to find possible correlations with biological parameters such as age, sex, body mass index and/or fat volume fraction, using linear regression analysis. In short, the collected in vivo values show significant deviations from the ex vivo values in conventional databases, and we show significant relationships with the latter parameters in certain organs for the first time, e.g. a decrease in brain conductivity with age.
Collapse
Affiliation(s)
- Zhongzheng He
- IADI U1254, INSERM and Université de Lorraine, Nancy, France
| | - Paul Soullié
- IADI U1254, INSERM and Université de Lorraine, Nancy, France.
| | | | | | - Jacques Felblinger
- IADI U1254, INSERM and Université de Lorraine, Nancy, France
- CIC-IT 1433, INSERM, Université de Lorraine and CHRU Nancy, Nancy, France
| | - Freddy Odille
- IADI U1254, INSERM and Université de Lorraine, Nancy, France
- CIC-IT 1433, INSERM, Université de Lorraine and CHRU Nancy, Nancy, France
| |
Collapse
|
2
|
Jung K, Mandija S, Cui C, Kim J, Al‐masni MA, Meerbothe TG, Park M, van den Berg CAT, Kim D. Data-driven electrical conductivity brain imaging using 3 T MRI. Hum Brain Mapp 2023; 44:4986-5001. [PMID: 37466309 PMCID: PMC10502651 DOI: 10.1002/hbm.26421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 06/14/2023] [Accepted: 07/03/2023] [Indexed: 07/20/2023] Open
Abstract
Magnetic resonance electrical properties tomography (MR-EPT) is a non-invasive measurement technique that derives the electrical properties (EPs, e.g., conductivity or permittivity) of tissues in the radiofrequency range (64 MHz for 1.5 T and 128 MHz for 3 T MR systems). Clinical studies have shown the potential of tissue conductivity as a biomarker. To date, model-based conductivity reconstructions rely on numerical assumptions and approximations, leading to inaccuracies in the reconstructed maps. To address such limitations, we propose an artificial neural network (ANN)-based non-linear conductivity estimator trained on simulated data for conductivity brain imaging. Network training was performed on 201 synthesized T2-weighted spin-echo (SE) data obtained from the finite-difference time-domain (FDTD) electromagnetic (EM) simulation. The dataset was composed of an approximated T2-w SE magnitude and transceive phase information. The proposed method was tested three in-silico and in-vivo on two volunteers and three patients' data. For comparison purposes, various conventional phase-based EPT reconstruction methods were used that ignoreB 1 + magnitude information, such as Savitzky-Golay kernel combined with Gaussian filter (S-G Kernel), phase-based convection-reaction EPT (cr-EPT), magnitude-weighted polynomial-fitting phase-based EPT (Poly-Fit), and integral-based phase-based EPT (Integral-based). From the in-silico experiments, quantitative analysis showed that the proposed method provides more accurate and improved quality (e.g., high structural preservation) conductivity maps compared to conventional reconstruction methods. Representatively, in the healthy brain in-silico phantom experiment, the proposed method yielded mean conductivity values of 1.97 ± 0.20 S/m for CSF, 0.33 ± 0.04 S/m for WM, and 0.52 ± 0.08 S/m for GM, which were closer to the ground-truth conductivity (2.00, 0.30, 0.50 S/m) than the integral-based method (2.56 ± 2.31, 0.39 ± 0.12, 0.68 ± 0.33 S/m). In-vivo ANN-based conductivity reconstructions were also of improved quality compared to conventional reconstructions and demonstrated network generalizability and robustness to in-vivo data and pathologies. The reported in-vivo brain conductivity values were in agreement with literatures. In addition, the proposed method was observed for various SNR levels (SNR levels = 10, 20, 40, and 58) and repeatability conditions (the eight acquisitions with the number of signal averages = 1). The preliminary investigations on brain tumor patient datasets suggest that the network trained on simulated dataset can generalize to unforeseen in-vivo pathologies, thus demonstrating its potential for clinical applications.
Collapse
Affiliation(s)
- Kyu‐Jin Jung
- Department of Electrical and Electronic EngineeringYonsei UniversitySeoulRepublic of Korea
| | - Stefano Mandija
- Computational Imaging Group for MR Therapy and DiagnosticsUniversity Medical Center UtrechtUtrechtThe Netherlands
- Department of RadiotherapyUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Chuanjiang Cui
- Department of Electrical and Electronic EngineeringYonsei UniversitySeoulRepublic of Korea
| | - Jun‐Hyeong Kim
- Department of Electrical and Electronic EngineeringYonsei UniversitySeoulRepublic of Korea
| | - Mohammed A. Al‐masni
- Department of Artificial IntelligenceCollege of Software & Convergence Technology, Daeyang AI Center, Sejong UniversitySeoulRepublic of Korea
| | - Thierry G. Meerbothe
- Computational Imaging Group for MR Therapy and DiagnosticsUniversity Medical Center UtrechtUtrechtThe Netherlands
- Department of RadiotherapyUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Mina Park
- Department of Radiology, Gangnam Severance HospitalYonsei University College of MedicineSeoulRepublic of Korea
| | - Cornelis A. T. van den Berg
- Computational Imaging Group for MR Therapy and DiagnosticsUniversity Medical Center UtrechtUtrechtThe Netherlands
- Department of RadiotherapyUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Dong‐Hyun Kim
- Department of Electrical and Electronic EngineeringYonsei UniversitySeoulRepublic of Korea
| |
Collapse
|
3
|
Groen JA, Crezee J, van Laarhoven HWM, Bijlsma MF, Kok HP. Quantification of tissue property and perfusion uncertainties in hyperthermia treatment planning: Multianalysis using polynomial chaos expansion. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2023; 240:107675. [PMID: 37339535 DOI: 10.1016/j.cmpb.2023.107675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 05/26/2023] [Accepted: 06/08/2023] [Indexed: 06/22/2023]
Abstract
INTRODUCTION Hyperthermia treatment planning (HTP) tools can guide treatment delivery, particularly with locoregional radiative phased array systems. Uncertainties in tissue and perfusion property values presently lead to quantitative inaccuracy of HTP, leading to sub-optimal treatment. Assessment of these uncertainties would allow for better judgement of the reliability of treatment plans and improve their value for treatment guidance. However, systematically investigating the impact of all uncertainties on treatment plans is a complex, high-dimensional problem and too computationally expensive for traditional Monte Carlo approaches. This study aims to systematically quantify the treatment-plan impact of tissue property uncertainties by investigating their individual contribution to, and combined impact on predicted temperature distributions. METHODS A novel Polynomial Chaos Expansion (PCE)-based HTP uncertainty quantification was developed and applied for locoregional hyperthermia of modelled tumours in the pancreatic head, prostate, rectum, and cervix. Patient models were based on the Duke and Ella digital human models. Using Plan2Heat, treatment plans were created to optimise tumour temperature (represented by T90) for treatment using the Alba4D system. For all 25-34 modelled tissues, the impact of tissue property uncertainties was analysed individually i.e., electrical and thermal conductivity, permittivity, density, specific heat capacity and perfusion. Next, combined analyses were performed on the top 30 uncertainties with the largest impact. RESULTS Uncertainties in thermal conductivity and heat capacity were found to have negligible impact on the predicted temperature ( < 1 × 10-10 °C), density and permittivity uncertainties had a small impact (< 0.3 °C). Uncertainties in electrical conductivity and perfusion can lead to large variations in predicted temperature. However, variations in muscle properties result in the largest impact at locations that could limit treatment quality, with a standard deviation up to almost 6 °C (pancreas) and 3.5 °C (prostate) for perfusion and electrical conductivity, respectively. The combined influence of all significant uncertainties leads to large variations with a standard deviation up to 9.0, 3.6, 3.7 and 4.1 °C for the pancreatic, prostate, rectal and cervical cases, respectively. CONCLUSION Uncertainties in tissue and perfusion property values can have a large impact on predicted temperatures from hyperthermia treatment planning. PCE-based analysis helps to identify all major uncertainties, their impact and judge the reliability of treatment plans.
Collapse
Affiliation(s)
- Jort A Groen
- Amsterdam UMC location University of Amsterdam, Radiation Oncology, Meibergdreef 9, Amsterdam, the Netherlands; Cancer Center Amsterdam, Cancer biology and immunology, Amsterdam, the Netherlands; Cancer Center Amsterdam, Treatment and quality of life, Amsterdam, the Netherlands.
| | - Johannes Crezee
- Amsterdam UMC location University of Amsterdam, Radiation Oncology, Meibergdreef 9, Amsterdam, the Netherlands; Cancer Center Amsterdam, Cancer biology and immunology, Amsterdam, the Netherlands; Cancer Center Amsterdam, Treatment and quality of life, Amsterdam, the Netherlands
| | - Hanneke W M van Laarhoven
- Amsterdam UMC location University of Amsterdam, Department of Medical Oncology, Amsterdam, the Netherlands; Cancer Center Amsterdam, Treatment and quality of life, Amsterdam, the Netherlands
| | - Maarten F Bijlsma
- Amsterdam UMC location University of Amsterdam, Center for Experimental and Molecular Medicine, Laboratory for Experimental Oncology and Radiobiology, Meibergdreef 9, Amsterdam, the Netherlands; Cancer Center Amsterdam, Cancer biology and immunology, Amsterdam, the Netherlands; Cancer Center Amsterdam, Imaging and biomarkers, Amsterdam, the Netherlands; Oncode Institute, Amsterdam, the Netherlands
| | - H Petra Kok
- Amsterdam UMC location University of Amsterdam, Radiation Oncology, Meibergdreef 9, Amsterdam, the Netherlands; Cancer Center Amsterdam, Cancer biology and immunology, Amsterdam, the Netherlands; Cancer Center Amsterdam, Treatment and quality of life, Amsterdam, the Netherlands
| |
Collapse
|
4
|
Cao J, Ball I, Humburg P, Dokos S, Rae C. Repeatability of brain phase-based magnetic resonance electric properties tomography methods and effect of compressed SENSE and RF shimming. Phys Eng Sci Med 2023; 46:753-766. [PMID: 36995580 DOI: 10.1007/s13246-023-01248-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Accepted: 03/19/2023] [Indexed: 03/31/2023]
Abstract
Magnetic resonance electrical properties tomography (MREPT) is an emerging imaging modality to noninvasively measure tissue conductivity and permittivity. Implementation of MREPT in the clinic requires repeatable measurements at a short scan time and an appropriate protocol. The aim of this study was to investigate the repeatability of conductivity measurements using phase-based MREPT and the effects of compressed SENSE (CS), and RF shimming on the precision of conductivity measurements. Conductivity measurements using turbo spin echo (TSE) and three-dimensional balanced fast field echo (bFFE) with CS factors were repeatable. Conductivity measurement using bFFE phase showed smaller mean and variance that those measured by TSE. The conductivity measurements using bFFE showed minimal deviation with CS factors up to 8, with deviation increasing at CS factors > 8. Subcortical structures produced less consistent measurements than cortical parcellations at higher CS factors. RF shimming using full slice coverage 2D dual refocusing echo acquisition mode (DREAM) and full coverage 3D dual TR approaches further improved measurement precision. BFFE is a more optimal sequence than TSE for phase-based MREPT in brain. Depending on the area of the brain being measured, the scan can be safely accelerated with compressed SENSE without sacrifice of precision, offering the potential to employ MREPT in clinical research and applications. RF shimming with better field mapping further improves precision of the conductivity measures.
Collapse
Affiliation(s)
- Jun Cao
- Neuroscience Research Australia, 139 Barker St, Randwick, NSW, 2031, Australia
- School of Biomedical Sciences, The University of New South Wales, Kensington, NSW, 2052, Australia
| | - Iain Ball
- Philips Australia & New Zealand, North Ryde, NSW, 2113, Australia
| | - Peter Humburg
- Neuroscience Research Australia, 139 Barker St, Randwick, NSW, 2031, Australia
- Mark Wainwright Analytical Centre, Stats Central, The University of New South Wales, Kensington, NSW, 2052, Australia
| | - Socrates Dokos
- Graduate School of Biomedical Engineering, The University of New South Wales, Kensington, NSW, 2052, Australia
| | - Caroline Rae
- Neuroscience Research Australia, 139 Barker St, Randwick, NSW, 2031, Australia.
- School of Psychology, The University of New South Wales, Kensington, NSW, 2052, Australia.
| |
Collapse
|
5
|
Eda N, Fushimi M, Hasegawa K, Nara T. A Method for Electrical Property Tomography Based on a Three-Dimensional Integral Representation of the Electric Field. IEEE TRANSACTIONS ON MEDICAL IMAGING 2022; 41:1400-1409. [PMID: 34968176 DOI: 10.1109/tmi.2021.3139455] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Magnetic resonance electrical properties tomography (MREPT) noninvasively reconstructs high-resolution electrical property (EP) maps using MRI scanners and is useful for diagnosing cancerous tissues. However, conventional MREPT methods have limitations: sensitivity to noise in the numerical Laplacian operation, difficulty in reconstructing three-dimensional (3D) EPs and convergence not guaranteed in the iterative process. We propose a novel, iterative 3D reconstruction MREPT method without a numerical Laplacian operation. We derive an integral representation of the electric field using its Helmholtz decomposition with Maxwell's equations, under the assumption that the EPs are known on the boundary of the region of interest with the approximation that the unmeasurable magnetic field components are zero. Then, we solve the simultaneous equations composed of the integral representation and Ampere's law using a convex projection algorithm whose convergence is theoretically guaranteed. The efficacy of the proposed method was validated through numerical simulations and a phantom experiment. The results showed that this method is effective in reconstructing 3D EPs and is robust to noise. It was also shown that our proposed method with the unmeasurable component H- enhances the accuracy of the EPs in a background and that with all the components of the magnetic field reduces the artifacts at the center of the slices except when all the components of the electric field are close to zero.
Collapse
|
6
|
Lee JH, Yoon YC, Kim HS, Lee J, Kim E, Findeklee C, Katscher U. In vivo electrical conductivity measurement of muscle, cartilage, and peripheral nerve around knee joint using MR-electrical properties tomography. Sci Rep 2022; 12:73. [PMID: 34996978 PMCID: PMC8741940 DOI: 10.1038/s41598-021-03928-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Accepted: 12/10/2021] [Indexed: 11/20/2022] Open
Abstract
This study aimed to investigate whether in vivo MR-electrical properties tomography (MR-EPT) is feasible in musculoskeletal tissues by evaluating the conductivity of muscle, cartilage, and peripheral nerve around the knee joint, and to explore whether these measurements change after exercise. This prospective study was approved by the institutional review board. On February 2020, ten healthy volunteers provided written informed consent and underwent MRI of the right knee using a three-dimensional balanced steady-state free precession (bSSFP) sequence. To test the effect of loading, the subjects performed 60 squatting exercises after baseline MRI, immediately followed by post-exercise MRI with the same sequences. After reconstruction of conductivity map based on the bSSFP sequence, conductivity of muscles, cartilages, and nerves were measured. Measurements between the baseline and post-exercise MRI were compared using the paired t-test. Test–retest reliability for baseline conductivity was evaluated using the intraclass correlation coefficient. The baseline and post-exercise conductivity values (mean ± standard deviation) [S/m] of muscles, cartilages, and nerves were 1.73 ± 0.40 and 1.82 ± 0.50 (p = 0.048), 2.29 ± 0.47 and 2.51 ± 0.37 (p = 0.006), and 2.35 ± 0.57 and 2.36 ± 0.57 (p = 0.927), respectively. Intraclass correlation coefficient for the baseline conductivity of muscles, cartilages, and nerves were 0.89, 0.67, and 0.89, respectively. In conclusion, in vivo conductivity measurement of musculoskeletal tissues is feasible using MR-EPT. Conductivity of muscles and cartilages significantly changed with an overall increase after exercise.
Collapse
Affiliation(s)
- Ji Hyun Lee
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, 06351, Seoul, Korea
| | - Young Cheol Yoon
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, 06351, Seoul, Korea.
| | - Hyun Su Kim
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, 06351, Seoul, Korea
| | - Jiyeong Lee
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, 06351, Seoul, Korea
| | | | | | | |
Collapse
|
7
|
Katscher U, Minhas AS, Katoch N. Magnetic Resonance Electrical Properties Tomography (MREPT). ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2022; 1380:185-202. [DOI: 10.1007/978-3-031-03873-0_8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
|
8
|
|
9
|
Jung KJ, Mandija S, Kim JH, Ryu K, Jung S, Cui C, Kim SY, Park M, van den Berg CAT, Kim DH. Improving phase-based conductivity reconstruction by means of deep learning-based denoising of B 1 + phase data for 3T MRI. Magn Reson Med 2021; 86:2084-2094. [PMID: 33949721 DOI: 10.1002/mrm.28826] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 03/28/2021] [Accepted: 04/13/2021] [Indexed: 12/24/2022]
Abstract
PURPOSE To denoise B 1 + phase using a deep learning method for phase-based in vivo electrical conductivity reconstruction in a 3T MR system. METHODS For B 1 + phase deep-learning denoising, a convolutional neural network (U-net) was chosen. Training was performed on data sets from 10 healthy volunteers. Input data were the real and imaginary components of single averaged spin-echo data (SNR = 45), which was used to approximate the B 1 + phase. For label data, multiple signal-averaged spin-echo data (SNR = 128) were used. Testing was performed on in silico and in vivo data. Reconstructed conductivity maps were derived using phase-based conductivity reconstructions. Additionally, we investigated the usability of the network to various SNR levels, imaging contrasts, and anatomical sites (ie, T1 , T2 , and proton density-weighted brain images and proton density-weighted breast images. In addition, conductivity reconstructions from deep learning-based denoised data were compared with conventional image filters, which were used for data denoising in electrical properties tomography (ie, the Gaussian filtering and the Savitzky-Golay filtering). RESULTS The proposed deep learning-based denoising approach showed improvement for B 1 + phase for both in silico and in vivo experiments with reduced quantitative error measures compared with other methods. Subsequently, this resulted in an improvement of reconstructed conductivity maps from the denoised B 1 + phase with deep learning. CONCLUSION The results suggest that the proposed approach can be used as an alternative preprocessing method to denoise B 1 + maps for phase-based conductivity reconstruction without relying on image filters or signal averaging.
Collapse
Affiliation(s)
- Kyu-Jin Jung
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Stefano Mandija
- Computational Imaging Group for MR Diagnostic & Therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands.,Department of Radiotherapy, Division of Imaging & Oncology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Jun-Hyeong Kim
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Kanghyun Ryu
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea.,Department of Radiology, Stanford University, Stanford, California, USA
| | - Soozy Jung
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Chuanjiang Cui
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Soo-Yeon Kim
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Mina Park
- Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Cornelis A T van den Berg
- Computational Imaging Group for MR Diagnostic & Therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands.,Department of Radiotherapy, Division of Imaging & Oncology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Dong-Hyun Kim
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| |
Collapse
|
10
|
Stijnman PRS, Stefano Mandija, Fuchs PS, van den Berg CAT, Remis RF. Transceive phase corrected 2D contrast source inversion-electrical properties tomography. Magn Reson Med 2021; 85:2856-2868. [PMID: 33280166 PMCID: PMC7898605 DOI: 10.1002/mrm.28619] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 10/08/2020] [Accepted: 11/05/2020] [Indexed: 11/11/2022]
Abstract
PURPOSE To remove the necessity of the tranceive phase assumption for CSI-EPT and show electrical properties maps reconstructed from measured data obtained using a standard 3T birdcage body coil setup. METHODS The existing CSI-EPT algorithm is reformulated to use the transceive phase rather than relying on the transceive phase assumption. Furthermore, the radio frequency (RF)-shield is numerically implemented to accurately model the RF fields inside the MRI scanner. We verify that the reformulated two-dimensional (2D) CSI-EPT algorithm can reconstruct electrical properties maps given 2D electromagnetic simulations. Afterward, the algorithm is tested with three-dimensional (3D) FDTD simulations to investigate if the 2D CSI-EPT can retrieve the electrical properties for 3D RF fields. Finally, an MR experiment at 3T with a phantom is performed. RESULTS From the results of the 2D simulations, it is seen that CSI-EPT can reconstruct the electrical properties using MRI accessible quantities. For 3D simulations, it is observed that the electrical properties are underestimated, nonetheless, CSI-EPT has a lower standard deviation than the standard Helmholtz based methods. Finally, the first CSI-EPT reconstructions based on measured data are presented showing comparable accuracy and precision to reconstructions based on simulated data, and demonstrating the feasibility of CSI-EPT. CONCLUSIONS The CSI-EPT algorithm was rewritten to use MRI accessible quantities. This allows for CSI-EPT to fully exploit the benefits of the higher static magnetic field strengths with a standard quadrature birdcage coil setup.
Collapse
Affiliation(s)
- Peter R. S. Stijnman
- Computational Imaging Group for MRI Diagnostics and TherapyCentre for Image Sciences UMC UtrechtUtrechtThe Netherlands
- Department of Biomedical EngineeringEindhoven University of TechnologyEindhovenThe Netherlands
| | - Stefano Mandija
- Computational Imaging Group for MRI Diagnostics and TherapyCentre for Image Sciences UMC UtrechtUtrechtThe Netherlands
| | - Patrick S. Fuchs
- Circuit & Systems Group of the Electrical EngineeringDelft University of TechnologyDelftThe Netherlands
| | - Cornelis A. T. van den Berg
- Computational Imaging Group for MRI Diagnostics and TherapyCentre for Image Sciences UMC UtrechtUtrechtThe Netherlands
| | - Rob F. Remis
- Circuit & Systems Group of the Electrical EngineeringDelft University of TechnologyDelftThe Netherlands
| |
Collapse
|
11
|
Lee SK, Oh S, Kim HS, Song BP. Radio-Frequency Vector Magnetic Field Mapping in Magnetic Resonance Imaging. IEEE TRANSACTIONS ON MEDICAL IMAGING 2021; 40:963-973. [PMID: 33290213 DOI: 10.1109/tmi.2020.3043294] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
A method is presented to measure the radio-frequency (RF) vector magnetic field inside an object using magnetic resonance imaging (MRI). Conventional " [Formula: see text] mapping" in MRI can measure the proton co-rotating component ( [Formula: see text] of the RF field produced by a transmit coil. Here we show that by repeating [Formula: see text] mapping on the same object and coil at multiple (8) specific orientations with respect to the main magnet, the magnitudes and relative phases of all (x, y, z) Cartesian components of the RF field can be determined unambiguously. We demonstrate the method on a circularly polarized volume coil and a loop coil tuned at 123.25 MHz in a 3 Tesla MRI scanner, with liquid phantoms. The volume coil measurement showed the axial component of the RF field, which is normally unmeasurable in MRI, away from the center of the coil. The measured RF vector field maps of both coils compared favorably with numerical simulation, with volumetric normalized root-mean-square difference in the range of 7~20%. While the proposed method cannot be applied to human imaging at present, applications to phantoms and small animals could provide a useful experimental tool to validate RF simulation and verify certain assumptions in [Formula: see text] map-based electrical properties tomography (EPT).
Collapse
|
12
|
Leijsen R, Brink W, van den Berg C, Webb A, Remis R. Electrical Properties Tomography: A Methodological Review. Diagnostics (Basel) 2021; 11:176. [PMID: 33530587 PMCID: PMC7910937 DOI: 10.3390/diagnostics11020176] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Revised: 01/18/2021] [Accepted: 01/22/2021] [Indexed: 11/25/2022] Open
Abstract
Electrical properties tomography (EPT) is an imaging method that uses a magnetic resonance (MR) system to non-invasively determine the spatial distribution of the conductivity and permittivity of the imaged object. This manuscript starts by providing clear definitions about the data required for, and acquired in, EPT, followed by comprehensively formulating the physical equations underlying a large number of analytical EPT techniques. This thorough mathematical overview of EPT harmonizes several EPT techniques in a single type of formulation and gives insight into how they act on the data and what their data requirements are. Furthermore, the review describes machine learning-based algorithms. Matlab code of several differential and iterative integral methods is available upon request.
Collapse
Affiliation(s)
- Reijer Leijsen
- Department of Radiology, C.J. Gorter Center for High Field MRI, Leiden University Medical Center, 2333ZA Leiden, The Netherlands; (R.L.); (W.B.); (A.W.)
| | - Wyger Brink
- Department of Radiology, C.J. Gorter Center for High Field MRI, Leiden University Medical Center, 2333ZA Leiden, The Netherlands; (R.L.); (W.B.); (A.W.)
| | - Cornelis van den Berg
- Computational Imaging Group for MRI Diagnostics and Therapy, Centre for Image Sciences, University Medical Centre Utrecht, 3508GA Utrecht, The Netherlands;
| | - Andrew Webb
- Department of Radiology, C.J. Gorter Center for High Field MRI, Leiden University Medical Center, 2333ZA Leiden, The Netherlands; (R.L.); (W.B.); (A.W.)
| | - Rob Remis
- Circuits and Systems Group, Faculty of Electrical Engineering, Mathematics and Computes Science, Delft University of Technology, 2628CD Delft, The Netherlands
| |
Collapse
|
13
|
Han J, Gao Y, Nan X, Yu X, Liu F, Xin SX. Effect of radiofrequency inhomogeneity on water-content based electrical properties tomography and its correction by flip angle maps. Magn Reson Imaging 2021; 78:25-34. [PMID: 33450296 DOI: 10.1016/j.mri.2020.12.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 12/24/2020] [Accepted: 12/31/2020] [Indexed: 10/22/2022]
Abstract
Water-content based electrical properties tomography (wEPT) can retrieve electrical properties (EPs) from water-content maps. B1+ field information is not involved in the traditional magnetic resonance electrical properties tomography approach. wEPT can be performed through conventional MR scanning, such as T1-weighted spin-echo imaging, which provides convenient access to multiple clinical applications. However, the inhomogeneous radiofrequency (RF) field induced by RF coils would cause inaccuracy in wEPT reconstructions during MR scanning. We conducted a detailed investigation to evaluate the effect of inhomogeneous RF field on wEPT reconstructions to guarantee that EP mapping is desired for clinical practice. Two important considerations are involved, namely, multiple typical coil configurations and various flip angles (FAs). We proposed a correction scheme with actual FA mapping to calibrate the RF inhomogeneity and finally validated it by using human imaging at 3 T. This study illustrates a detailed evaluation for wEPT under imperfect RF homogeneity and further provides a feasible correction procedure to mitigate it. The profound knowledge of wEPT provided in our work will benefit its performance in clinical applications.
Collapse
Affiliation(s)
- Jijun Han
- School of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China
| | - Yunyu Gao
- School of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China
| | - Xiang Nan
- Center for Biomedical Engineering, University of Science and Technology of China, Hefei, Anhui, China
| | - Xuefei Yu
- School of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China
| | - Feng Liu
- School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, QLD, Australia
| | - Sherman Xuegang Xin
- School of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China; School of Medicine, South China University of Technology, Guangzhou, Guangdong, China.
| |
Collapse
|
14
|
Liu C, Guo L, Li M, Chen H, Jin J, Chen W, Liu F, Crozier S. Divergence-Based Magnetic Resonance Electrical Properties Tomography. IEEE Trans Biomed Eng 2021; 68:192-203. [DOI: 10.1109/tbme.2020.3003460] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
|
15
|
Iyyakkunnel S, Schäper J, Bieri O. Configuration-based electrical properties tomography. Magn Reson Med 2020; 85:1855-1864. [PMID: 33107082 DOI: 10.1002/mrm.28542] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Revised: 09/09/2020] [Accepted: 09/14/2020] [Indexed: 11/07/2022]
Abstract
PURPOSE To introduce phase-based conductivity mapping from a configuration space analysis. METHODS The frequency response function of balanced SSFP (bSSFP) is used to perform a configuration space analysis. It is shown that the transceive phase for conductivity mapping can be directly obtained by a simple fast Fourier transform of a series of phase-cycled bSSFP scans. For validation, transceive phase and off-resonance mapping with fast Fourier transform is compared with phase estimation using a recently proposed method, termed PLANET. Experiments were performed in phantoms and for in vivo brain imaging at 3 T using a quadrature head coil. RESULTS For fast Fourier transform, aliasing can lead to systematic phase errors. This bias, however, decreases rapidly with increasing sampling points. Interestingly, Monte Carlo simulations revealed a lower uncertainty for the transceive phase and the off-resonance using fast Fourier transform as compared with PLANET. Both methods, however, essentially retrieve the same phase information from a set of phase-cycled bSSFP scans. As a result, configuration-based conductivity mapping was successfully performed using eight phase-cycled bSSFP scans in the phantoms and for brain tissues. Overall, the retrieved values were in good agreement with expectations. Conductivity estimation and mapping of the field inhomogeneities can therefore be performed in conjunction with the estimation of other quantitative parameters, such as relaxation, using configuration theory. CONCLUSIONS Phase-based conductivity mapping can be estimated directly from a simple Fourier analysis, such as in conjunction with relaxometry, using a series of phase-cycled bSSFP scans.
Collapse
Affiliation(s)
- Santhosh Iyyakkunnel
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland.,Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Jessica Schäper
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland.,Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Oliver Bieri
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland.,Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| |
Collapse
|
16
|
de Buck MHS, Jezzard P, Jeong H, Hess AT. An investigation into the minimum number of tissue groups required for 7T in-silico parallel transmit electromagnetic safety simulations in the human head. Magn Reson Med 2020; 85:1114-1122. [PMID: 32845034 DOI: 10.1002/mrm.28467] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Revised: 06/22/2020] [Accepted: 07/16/2020] [Indexed: 02/03/2023]
Abstract
PURPOSE Safety limits for the permitted specific absorption rate (SAR) place restrictions on pulse sequence design, especially at ultrahigh fields (≥ 7 tesla). Due to intersubject variability, the SAR is usually conservatively estimated based on standard human models that include an applied safety margin to ensure safe operation. One approach to reducing the restrictions is to create more accurate subject-specific models from their segmented MR images. This study uses electromagnetic simulations to investigate the minimum number of tissue groups required to accurately determine SAR in the human head. METHODS Tissue types from a fully characterized electromagnetic human model with 47 tissue types in the head and neck region were grouped into different tissue clusters based on the conductivities, permittivities, and mass densities of the tissues. Electromagnetic simulations of the head model inside a parallel transmit head coil at 7 tesla were used to determine the minimum number of required tissue clusters to accurately determine the subject-specific SAR. The identified tissue clusters were then evaluated using 2 additional well-characterized electromagnetic human models. RESULTS A minimum of 4-clusters-plus-air was found to be required for accurate SAR estimation. These tissue clusters are centered around gray matter, fat, cortical bone, and cerebrospinal fluid. For all 3 simulated models, the parallel transmit maximum 10g SAR was consistently determined to within an error of <12% relative to the full 47-tissue model. CONCLUSION A minimum of 4-clusters-plus-air are required to produce accurate personalized SAR simulations of the human head when using parallel transmit at 7 tesla.
Collapse
Affiliation(s)
- Matthijs H S de Buck
- Wellcome Centre for Integrative Neuroimaging, FMRIB Division, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Peter Jezzard
- Wellcome Centre for Integrative Neuroimaging, FMRIB Division, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Hongbae Jeong
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Maryland, USA.,Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Aaron T Hess
- Oxford Centre for Clinical Magnetic Resonance Research, Department of Cardiovascular Medicine, University of Oxford, Oxford, United Kingdom.,BHF Centre of Research Excellence, University of Oxford, Oxford, United Kingdom
| |
Collapse
|
17
|
Soullié P, Missoffe A, Ambarki K, Felblinger J, Odille F. MR electrical properties imaging using a generalized image-based method. Magn Reson Med 2020; 85:762-776. [PMID: 32783236 DOI: 10.1002/mrm.28458] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Revised: 07/08/2020] [Accepted: 07/10/2020] [Indexed: 11/12/2022]
Abstract
PURPOSE To develop a fast and easy-to-use electrical properties tomography (EPT) method based on a single MR scan, avoiding both the need of a B1 -map and transceive phase assumption, and that is robust against noise. THEORY Derived from Maxwell's equations, conductivity, and permittivity are reconstructed from a new partial differential equation involving the product of the RF fields and its derivatives. This also allows us to clarify and revisit the relevance of common assumptions of MREPT. METHODS Our new governing equation is solved using a 3D finite-difference scheme and compared to previous frameworks. The benefits of our method over selected existing MREPT methods are demonstrated for different simulation models, as well as for both an inhomogeneous agar phantom gel and in vivo brain data at 3T. RESULTS Simulation and experimental results are illustrated to highlight the merits of the proposed method over existing methods. We show the validity of our algorithm in versatile configurations, with many transition regions notably. Complex admittivity maps are also provided as a complementary MR contrast. CONCLUSION Because it avoids time-consuming RF field mapping and generalizes the use of standard MR image for electrical properties reconstruction, this contribution is promising as a new step forward for clinical applications.
Collapse
Affiliation(s)
- Paul Soullié
- IADI, INSERM U1254, Université de Lorraine, Nancy, France
| | | | | | - Jacques Felblinger
- IADI, INSERM U1254, Université de Lorraine, Nancy, France.,CIC-IT 1433, INSERM, Université de Lorraine and CHRU de Nancy, Nancy, France
| | - Freddy Odille
- IADI, INSERM U1254, Université de Lorraine, Nancy, France.,CIC-IT 1433, INSERM, Université de Lorraine and CHRU de Nancy, Nancy, France
| |
Collapse
|
18
|
Han J, Gao Y, Nan X, Liu F, Xin SX. Statistical analysis of the accuracy of water content-based electrical properties tomography. NMR IN BIOMEDICINE 2020; 33:e4273. [PMID: 32048385 DOI: 10.1002/nbm.4273] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2019] [Revised: 01/04/2020] [Accepted: 01/24/2020] [Indexed: 06/10/2023]
Abstract
Water content-based electrical properties tomography (wEPT) can retrieve electrical properties (EPs) from water content maps, thereby eliminating the need for B1 field measurement in the traditional magnetic resonance electrical properties tomography method. The wEPT is performed by conventional MR scanning, such as T1 -weighted spin-echo imaging, and thus can be directly applied to clinical settings. However, the random noise propagation involved in wEPT causes inaccuracy in EP mapping. To guarantee the EP estimates desired for clinical practice, this study statically investigates the noise-specific uncertainty of wEPT through probability density function models. We calculated the probability distribution of EP maps with different noise levels and examined the effects of scan parameters on reconstruction accuracy with various flip angles (FAs) and repetition time (TR) settings. The theoretical derivation was validated by Monte Carlo simulations and human imaging experiment at 3 T. Results showed that a serious deviation could occur in tissues with large conductivity value at a low signal-to-noise ratio and quantitatively demonstrate that such deviation could be mitigated by increased FAs or TRs. This study provided useful information for the setup of scan parameters, evaluation of accuracy of the wEPT under specific SNR levels, and promote its clinical applications.
Collapse
Affiliation(s)
- Jijun Han
- School of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China
| | - Yunyu Gao
- School of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China
| | - Xiang Nan
- Center for Biomedical Engineering, University of Science and Technology of China, Hefei, Anhui, China
| | - Feng Liu
- School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, QLD, Australia
| | - Sherman Xuegang Xin
- School of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China
- School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
| |
Collapse
|
19
|
Gavazzi S, van den Berg CAT, Savenije MHF, Kok HP, de Boer P, Stalpers LJA, Lagendijk JJW, Crezee H, van Lier ALHMW. Deep learning-based reconstruction of in vivo pelvis conductivity with a 3D patch-based convolutional neural network trained on simulated MR data. Magn Reson Med 2020; 84:2772-2787. [PMID: 32314825 PMCID: PMC7402024 DOI: 10.1002/mrm.28285] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2019] [Revised: 03/25/2020] [Accepted: 03/26/2020] [Indexed: 12/21/2022]
Abstract
PURPOSE To demonstrate that mapping pelvis conductivity at 3T with deep learning (DL) is feasible. METHODS 210 dielectric pelvic models were generated based on CT scans of 42 cervical cancer patients. For all dielectric models, electromagnetic and MR simulations with realistic accuracy and precision were performed to obtain B 1 + and transceive phase (ϕ± ). Simulated B 1 + and ϕ± served as input to a 3D patch-based convolutional neural network, which was trained in a supervised fashion to retrieve the conductivity. The same network architecture was retrained using only ϕ± in input. Both network configurations were tested on simulated MR data and their conductivity reconstruction accuracy and precision were assessed. Furthermore, both network configurations were used to reconstruct conductivity maps from a healthy volunteer and two cervical cancer patients. DL-based conductivity was compared in vivo and in silico to Helmholtz-based (H-EPT) conductivity. RESULTS Conductivity maps obtained from both network configurations were comparable. Accuracy was assessed by mean error (ME) with respect to ground truth conductivity. On average, ME < 0.1 Sm-1 for all tissues. Maximum MEs were 0.2 Sm-1 for muscle and tumour, and 0.4 Sm-1 for bladder. Precision was indicated with the difference between 90th and 10th conductivity percentiles, and was below 0.1 Sm-1 for fat, bone and muscle, 0.2 Sm-1 for tumour and 0.3 Sm-1 for bladder. In vivo, DL-based conductivity had median values in agreement with H-EPT values, but a higher precision. CONCLUSION Anatomically detailed, noise-robust 3D conductivity maps with good sensitivity to tissue conductivity variations were reconstructed in the pelvis with DL.
Collapse
Affiliation(s)
- Soraya Gavazzi
- Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Cornelis A T van den Berg
- Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands.,Computational Imaging Group for MR diagnostics and therapy, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Mark H F Savenije
- Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands.,Computational Imaging Group for MR diagnostics and therapy, University Medical Center Utrecht, Utrecht, The Netherlands
| | - H Petra Kok
- Department of Radiation Oncology, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Peter de Boer
- Radiotherapy Institute Friesland, Leeuwarden, The Netherlands
| | - Lukas J A Stalpers
- Department of Radiation Oncology, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Jan J W Lagendijk
- Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Hans Crezee
- Department of Radiation Oncology, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | | |
Collapse
|
20
|
Sun X, Lu L, Qi L, Mei Y, Liu X, Chen W. A robust electrical conductivity imaging method with total variation and wavelet regularization. Magn Reson Imaging 2020; 69:28-39. [PMID: 32145270 DOI: 10.1016/j.mri.2020.02.015] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2019] [Revised: 01/23/2020] [Accepted: 02/27/2020] [Indexed: 11/29/2022]
Abstract
PURPOSE This study aims to develop and evaluate a robust conductivity imaging method that combines total variation and wavelet regularization to enhance the accuracy of conductivity maps. THEORY AND METHODS The proposed approach is based on a gradient-based method. The central equation is derived from Maxwell's equation and describes the relationship between conductivity and the transceive phase. A linear system equation is obtained via a finite-difference method and solved using a least-squares method. Total variation and wavelet transform regularization terms are added to the minimization problem and solved using the Split Bregman method to improve reconstruction stability. The proposed approach is compared with conventional and gradient-based methods. Numerical simulations are performed to validate the accuracy of the developed method, and the effects of noise are determined. Phantom and in vivo experiments are conducted at 3 T to verify the clinical applicability of the proposed method. RESULTS Numerical simulations show that the proposed method is more robust than other methods and can suppress the effects of noise. The quantitative conductivity value of the phantom experiment agrees with the measured value. The in vivo experiment results present a clear structure, and the conductivity value of the tumor region is significantly higher than that around healthy tissues. CONCLUSION The proposed electrical conductivity imaging method can improve the quality of conductivity reconstruction, and thus, has future clinical applications.
Collapse
Affiliation(s)
- Xiangdong Sun
- School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China; School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China
| | - Lijun Lu
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China
| | - Li Qi
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China
| | - Yingjie Mei
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China
| | - Xiaoyun Liu
- School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Wufan Chen
- School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China; School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China.
| |
Collapse
|
21
|
Amouzandeh G, Mentink-Vigier F, Helsper S, Bagdasarian FA, Rosenberg JT, Grant SC. Magnetic resonance electrical property mapping at 21.1 T: a study of conductivity and permittivity in phantoms, ex vivo tissue and in vivo ischemia. Phys Med Biol 2020; 65:055007. [PMID: 31307020 PMCID: PMC7223161 DOI: 10.1088/1361-6560/ab3259] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Electrical properties (EP), namely conductivity and permittivity, can provide endogenous contrast for tissue characterization. Using electrical property tomography (EPT), maps of EP can be generated from conventional MRI data. This report investigates the feasibility and accuracy of EPT at 21.1 T for multiple RF coils and modes of operation using phantoms. Additionally, it demonstrates the EP of the in vivo rat brain with and without ischemia. Helmholtz-based EPT was implemented in its Full-form, which demands the complex [Formula: see text] field, and a simplified form requiring either just the [Formula: see text] field phase for conductivity or the [Formula: see text] field magnitude for permittivity. Experiments were conducted at 21.1 T using birdcage and saddle coils operated in linear or quadrature transceive mode, respectively. EPT approaches were evaluated using a phantom, ex and in vivo Sprague-Dawley rats under naïve conditions and ischemic stroke via transient middle cerebral artery occlusion. Different conductivity reconstruction approaches applied to the phantom displayed average errors of 12%-73% to the target acquired from dielectric probe measurements. Permittivity reconstructions showed higher agreement and an average 3%-8% error to the target depending on reconstruction approach. Conductivity and permittivity of ex and in vivo rodent brain were measured. Elevated EP in the ischemia region correlated with the increased sodium content and the influx of water intracellularly following ischemia in the lesion were detected. The Full-form technique generated from the linear birdcage provided the best accuracy for EP of the phantom. Phase-based conductivity and magnitude-based permittivity mapping provided reasonable estimates but also demonstrated the limitations of Helmholtz-based EPT at 21.1 T. Permittivity reconstruction was improved significantly over lower fields, suggesting a novel metric for in vivo brain studies. EPT applied to ischemic rat brain proved sensitivity to physiological changes, motivating the future application of more advanced reconstruction approaches.
Collapse
Affiliation(s)
- Ghoncheh Amouzandeh
- Department of Physics, Florida State University, Tallahassee, FL, USA
- The National High Magnetic Field Laboratory, Florida State University, Tallahassee, FL, USA
| | | | - Shannon Helsper
- The National High Magnetic Field Laboratory, Florida State University, Tallahassee, FL, USA
- Department of Chemical & Biomedical Engineering, FAMU-FSU College of Engineering, Tallahassee, FL, USA
| | - F. Andrew Bagdasarian
- The National High Magnetic Field Laboratory, Florida State University, Tallahassee, FL, USA
- Department of Chemical & Biomedical Engineering, FAMU-FSU College of Engineering, Tallahassee, FL, USA
| | - Jens T. Rosenberg
- The National High Magnetic Field Laboratory, Florida State University, Tallahassee, FL, USA
| | - Samuel C. Grant
- The National High Magnetic Field Laboratory, Florida State University, Tallahassee, FL, USA
- Department of Chemical & Biomedical Engineering, FAMU-FSU College of Engineering, Tallahassee, FL, USA
| |
Collapse
|
22
|
Duan S, Zhu Y, Liu F, Xin SX. Numerical Experiments on the Contrast Capability of Magnetic Resonance Electrical Property Tomography. Magn Reson Med Sci 2020; 19:77-85. [PMID: 31019159 PMCID: PMC7067912 DOI: 10.2463/mrms.mp.2018-0167] [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] [Indexed: 11/09/2022] Open
Abstract
Purpose: Magnetic resonance electrical property tomography (MR EPT) is a technique for non-invasively obtaining the electric property (EP) distribution of biological tissues, with a promising potential for application in the early detection of tumors. However, the contrast capability (CC) of this technique has not been fully studied. This work aims to theoretically explore the CC for detecting the variation of EP values and the size of the imaging region. Methods: A simulation scheme was specifically designed to evaluate the CC of MR EPT. The simulation study has the advantage that the magnetic field can be accurately obtained. EP maps of the designed phantom embedded with target regions of designated various sizes and EPs were reconstructed using the homogeneous Helmholtz equation based on B1+ with different signal-to-noise ratios (SNRs). The CC was estimated by determining the smallest detectable EP contrast when the target region size was as large as the Laplacian kernel and the smallest detectable target region size when the EP contrast was the same as the difference between healthy and malignant tissues in the brain, based on the reconstructed EP maps. Results: Using noise free B1+, the smallest detectable contrastσ and contrastεr were 1% and 3%, respectively, and the smallest detectable target region size was 1 mesh unit (the base unit size used in the simulation) for conductivity and relative permittivity. The smallest detectable EP contrast and target region size were decreased as the B1+ SNR increased. Conclusion: The CC of MR EPT was related with the SNR of the magnetic field. A small EP contrast and size were necessary for detection at a high-SNR magnetic field. Obtaining a high-SNR magnetic field is important for improving the CC of MR EPT.
Collapse
Affiliation(s)
- Song Duan
- Department of Radiation Oncology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University
| | - Yurong Zhu
- Department of Biomedical Engineering, Southern Medical University
| | - Feng Liu
- School of Information Technology and Electrical Engineering, University of Queensland
| | - Sherman Xuegang Xin
- School of Medicine, South China University of Technology, Guangzhou Higher Education Mega Centre
| |
Collapse
|
23
|
Guo L, Li M, Nguyen P, Liu F, Crozier S. Integral MR-EPT With the Calculation of Coil Current Distributions. IEEE TRANSACTIONS ON MEDICAL IMAGING 2020; 39:175-187. [PMID: 31199256 DOI: 10.1109/tmi.2019.2922318] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Many integral equation (IE)-based magnetic resonance electrical property tomography (MR-EPT) methods use unloaded incident radio-frequency (RF) fields from simulations that may not fully reflect the real situation and thus lead to reconstruction errors. To improve the accuracy of IE-based MR-EPT methods, a novel approach that enables the calculation of loaded coil current distributions and avoids the explicit use of incident RF fields is presented in this paper. In the proposed method, a hybrid source composed of the current source from the coil and the contrast source from the subject are introduced in the integral equations. Because the loaded coil current distributions can be extracted from the reconstructed hybrid source, the simulated incident RF fields are eliminated from the problem formulations. To improve the convergence performance, a modified conjugate gradient (CG) scheme was used where the gradients of the current source and contrast source were balanced through using different weighting parameters. The proposed method was verified through full-wave simulations at 9.4 and 7 T involving a heterogeneous ball and an anatomical head phantom. The numerical results indicated that by using the proposed method, an accurate coil current distributions and EPs profiles can be reconstructed and the desirable robustness against noise can also be achieved.
Collapse
|
24
|
Automated gradient-based electrical properties tomography in the human brain using 7 Tesla MRI. Magn Reson Imaging 2019; 63:258-266. [PMID: 31425805 DOI: 10.1016/j.mri.2019.08.003] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2019] [Revised: 08/01/2019] [Accepted: 08/15/2019] [Indexed: 12/18/2022]
Abstract
Electrical properties of the brain tissues may yield useful biomarkers for neurological disorders and diseases, as well as contribute to safety assurance of ultra-high-field MRI. It has been reported that using B1 maps from a multi-channel RF coil, the spatial variation of the electrical properties can be robustly retrieved. The absolute electrical property values can then be obtained by spatial integration, given that an integration seed point is assigned. In this study, we propose to exploit automatically detected seed points based on tissue piece-wise homogeneity (Helmholtz equation) for spatial integration. Numerical simulations of a numerical brain model and experiments involving 12 healthy volunteers were performed to demonstrate its feasibility and robustness in various noisy conditions and head positions. For in vivo imaging, we consistently observed higher conductivity and permittivity values in the white and gray matter compared to tabulated ex vivo probe measurement results found in the literature, a discrepancy that may be attributed to ex vivo experimental constraints. Our results suggest that the proposed technique produces consistent brain electrical properties in vivo that may contribute to improving diagnostic and therapeutic decisions.
Collapse
|
25
|
Mandija S, Meliadò EF, Huttinga NRF, Luijten PR, van den Berg CAT. Opening a new window on MR-based Electrical Properties Tomography with deep learning. Sci Rep 2019; 9:8895. [PMID: 31222055 PMCID: PMC6586684 DOI: 10.1038/s41598-019-45382-x] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2019] [Accepted: 06/04/2019] [Indexed: 11/09/2022] Open
Abstract
In the radiofrequency (RF) range, the electrical properties of tissues (EPs: conductivity and permittivity) are modulated by the ionic and water content, which change for pathological conditions. Information on tissues EPs can be used e.g. in oncology as a biomarker. The inability of MR-Electrical Properties Tomography techniques (MR-EPT) to accurately reconstruct tissue EPs by relating MR measurements of the transmit RF field to the EPs limits their clinical applicability. Instead of employing electromagnetic models posing strict requirements on the measured MRI quantities, we propose a data driven approach where the electrical properties reconstruction problem can be casted as a supervised deep learning task (DL-EPT). DL-EPT reconstructions for simulations and MR measurements at 3 Tesla on phantoms and human brains using a conditional generative adversarial network demonstrate high quality EPs reconstructions and greatly improved precision compared to conventional MR-EPT. The supervised learning approach leverages the strength of electromagnetic simulations, allowing circumvention of inaccessible MR electromagnetic quantities. Since DL-EPT is more noise-robust than MR-EPT, the requirements for MR acquisitions can be relaxed. This could be a major step forward to turn electrical properties tomography into a reliable biomarker where pathological conditions can be revealed and characterized by abnormalities in tissue electrical properties.
Collapse
Affiliation(s)
- Stefano Mandija
- Computational Imaging Group for MR diagnostic & therapy, Center for Image Sciences, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands.
- Department of Radiotherapy, Division of Imaging & Oncology, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands.
| | - Ettore F Meliadò
- Computational Imaging Group for MR diagnostic & therapy, Center for Image Sciences, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
- Department of Radiology, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
| | - Niek R F Huttinga
- Computational Imaging Group for MR diagnostic & therapy, Center for Image Sciences, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
- Department of Radiotherapy, Division of Imaging & Oncology, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
| | - Peter R Luijten
- Department of Radiology, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
| | - Cornelis A T van den Berg
- Computational Imaging Group for MR diagnostic & therapy, Center for Image Sciences, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
- Department of Radiotherapy, Division of Imaging & Oncology, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
| |
Collapse
|
26
|
Gavazzi S, van den Berg CAT, Sbrizzi A, Kok HP, Stalpers LJA, Lagendijk JJW, Crezee H, van Lier ALHMW. Accuracy and precision of electrical permittivity mapping at 3T: the impact of three B 1 + mapping techniques. Magn Reson Med 2019; 81:3628-3642. [PMID: 30737816 PMCID: PMC6593818 DOI: 10.1002/mrm.27675] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2018] [Revised: 01/07/2019] [Accepted: 01/08/2019] [Indexed: 12/29/2022]
Abstract
Purpose To investigate the sequence‐specific impact of B1+ amplitude mapping on the accuracy and precision of permittivity reconstruction at 3T in the pelvic region. Methods B1+ maps obtained with actual flip angle imaging (AFI), Bloch–Siegert (BS), and dual refocusing echo acquisition mode (DREAM) sequences, set to a clinically feasible scan time of 5 minutes, were compared in terms of accuracy and precision with electromagnetic and Bloch simulations and MR measurements. Permittivity maps were reconstructed based on these B1+ maps with Helmholtz‐based electrical properties tomography. Accuracy and precision in permittivity were assessed. A 2‐compartment phantom with properties and size similar to the human pelvis was used for both simulations and measurements. Measurements were also performed on a female volunteer’s pelvis. Results Accuracy was evaluated with noiseless simulations on the phantom. The maximum B1+ bias relative to the true B1+ distribution was 1% for AFI and BS and 6% to 15% for DREAM. This caused an average permittivity bias relative to the true permittivity of 7% to 20% for AFI and BS and 12% to 35% for DREAM. Precision was assessed in MR experiments. The lowest standard deviation in permittivity, found in the phantom for BS, measured 22.4 relative units and corresponded to a standard deviation in B1+ of 0.2% of the B1+ average value. As regards B1+ precision, in vivo and phantom measurements were comparable. Conclusions Our simulation framework quantitatively predicts the different impact of B1+ mapping techniques on permittivity reconstruction and shows high sensitivity of permittivity reconstructions to sequence‐specific bias and noise perturbation in the B1+ map. These findings are supported by the experimental results.
Collapse
Affiliation(s)
- Soraya Gavazzi
- Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Cornelis A T van den Berg
- Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands.,Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Alessandro Sbrizzi
- Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - H Petra Kok
- Department of Radiation Oncology, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Lukas J A Stalpers
- Department of Radiation Oncology, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Jan J W Lagendijk
- Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Hans Crezee
- Department of Radiation Oncology, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | | |
Collapse
|
27
|
Wang Y, Van de Moortele PF, He B. CONtrast Conformed Electrical Properties Tomography (CONCEPT) Based on Multi- Channel Transmission and Alternating Direction Method of Multipliers. IEEE TRANSACTIONS ON MEDICAL IMAGING 2019; 38:349-359. [PMID: 30106715 PMCID: PMC6372102 DOI: 10.1109/tmi.2018.2865121] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
In magnetic resonance-based electrical properties tomography (EPT), circularly polarized magnetic field B1 from a transmit radiofrequency (RF) coil is measured and utilized to infer the electrical conductivity and permittivity of biological tissues. Compared with a quadrature RF coil, a multi-channel transmit coil provides a plurality of unique transmit B1 patterns that help to alleviate the under-determinedness of EPT reconstruction problem, and it also allows to circumvent the "transceive phase assumption" that fails at ultra-high-field MRI. Here, a new approach, contrast conformed electrical properties tomography or CONCEPT, is proposed based on the multi-channel transmission that retrieves electrical properties (EPs) by solving a linear partial differential equation with discriminated L1 and L2 norm regularization informed by intermediate EP gradient. The theory of CONCEPT and a fast reconstruction algorithm based on the alternating direction method of multipliers are described and evaluated using numerical simulations, phantom experiment, and analysis of in vivo human brain data at 7 T MRI. Compared with the multi-channel gradient-based EPT (gEPT) method, this new technology does not require receive- B1 sensitivity profiles and does not rely on symmetry assumption regarding RF coil design and imaged target. Moreover, it is not dependent on external prior information, such as integration seed point or anatomical MRI, which can be sources of bias in reconstructed EP values. By deriving EPs from transmit B1 profiles only, CONCEPT can be used with RF coils that include receive-only arrays with large channel count which can, in turn, offer substantial gains in signal-to-noise ratio. It also holds potentials to image unsymmetrical body organs and diseased brain. CONCEPT provides solutions for the practical problems during the implementation of gEPT, thus representing a more generalized framework in the context of multi-channel RF transmission.
Collapse
Affiliation(s)
- Yicun Wang
- Department of Biomedical Engineering, University of Minnesota, MN 55455, USA
| | | | - Bin He
- Department of Biomedical Engineering, University of Minnesota, MN 55455, USA; and is with the Department of Biomedical Engineering, Carnegie Mellon University, PA 15213, USA. ()
| |
Collapse
|
28
|
Yildiz G, Ider YZ. Use of dielectric padding to eliminate low convective field artifact in cr-MREPT conductivity images. Magn Reson Med 2019; 81:3168-3184. [PMID: 30693565 DOI: 10.1002/mrm.27648] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2018] [Revised: 12/05/2018] [Accepted: 12/05/2018] [Indexed: 11/07/2022]
Abstract
PURPOSE Convection-reaction equation-based magnetic resonance electrical properties tomography (cr-MREPT) provides conductivity images that are boundary artifact-free and robust against noise. However, these images suffer from the low convective field (LCF) artifact. We propose to use dielectric pads to alter the transmit magnetic field (B1 + ), shift the LCF region, and eliminate the LCF artifact. METHODS Computer simulations were conducted to analyze the effects of pad electrical properties, pad thickness, pad height, arc angle, and thickness of the pad-object gap. In 3T MR experiments, water pads and BaTiO3 pads were used with agar-saline phantoms. Two data sets (e.g., with the pad located on the left or on the right of the object [phantom]) were acquired, and the corresponding linear systems were simultaneously solved to get LCF artifact-free conductivity images. RESULTS A pad needed to have 180° arc angle and the same height with the phantom for maximum benefit. Increasing the pad thickness and/or the relative permittivity of the pad increased the LCF shift, whereas excessive amounts of these parameters caused errors in conductivity reconstructions because the effect of neglected Bz terms became noticeable. Conductivity of the pad, on the other hand, had minimal effect on elimination of the LCF artifact. Combining 2 data sets (i.e., with 2 different dielectric pad positions) resulted in more accurate conductivity maps (low L2 -errors) as opposed to no pad or single pad cases in experiments and simulations. CONCLUSIONS Using the proposed technique, LCF artifact is significantly removed, and the reconstructed conductivity values are improved.
Collapse
Affiliation(s)
- Gulsah Yildiz
- Department of Electrical and Electronics Engineering, Bilkent University, Ankara, Turkey
| | - Yusuf Ziya Ider
- Department of Electrical and Electronics Engineering, Bilkent University, Ankara, Turkey
| |
Collapse
|
29
|
Ariturk G, Ider YZ. $B_1^+$ phase retrieval for non-quadrature radio frequency excitation and its preliminary application in MR-EPT. ACTA ACUST UNITED AC 2019; 64:02NT02. [DOI: 10.1088/1361-6560/aaf7be] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
|
30
|
Wang Y, Shao Q, Van de Moortele PF, Racila E, Liu J, Bischof J, He B. Mapping electrical properties heterogeneity of tumor using boundary informed electrical properties tomography (BIEPT) at 7T. Magn Reson Med 2019; 81:393-409. [PMID: 30230603 PMCID: PMC6258314 DOI: 10.1002/mrm.27414] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2018] [Revised: 05/30/2018] [Accepted: 05/31/2018] [Indexed: 11/06/2022]
Abstract
PURPOSES To develop and evaluate a boundary informed electrical properties tomography (BIEPT) technique for high-resolution imaging of tumor electrical properties (EPs) heterogeneity on a rodent tumor xenograft model. METHODS Tumor EP distributions were inferred from a reference area external to the tumor, as well as internal EP spatial variations derived from a plurality of relative transmit B1 measurements at 7T. Edge sparsity constraint was enforced to enhance numerical stability. Phantom experiments were performed to determine the imaging accuracy and sensitivity for structures of various EP values, as well as geometrical sizes down to 1.5 mm. Numerical simulation of a realistic rodent model was used to quantify the algorithm performance in the presence of noise. Eleven athymic rats with human breast cancer xenograft were imaged in vivo, and representative pathological samples were acquired for comparison. RESULTS Reconstructed EPs of the phantoms correspond well to the ground truth acquired from dielectric probe measurements, with the smallest structure reliably detectable being 3 mm. EPs heterogeneity inside a tumor is successfully retrieved in both simulated and experimental cases. In vivo tumor imaging results demonstrate similar local features and spatial patterns to anatomical MRI and pathological slides. The imaged conductivity of necrotic tissue is higher than that of viable tissues, which agrees with our expectation. CONCLUSION BIEPT enables robust detection of tumor EPs heterogeneity with high accuracy and sensitivity to small structures. The retrieved quantitative EPs reflect tumor pathological features (e.g., necrosis). These results provide strong rationale to further expand BIEPT studies toward pathological conditions where EPs may yield valuable, non-invasive biomarkers.
Collapse
Affiliation(s)
- Yicun Wang
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455
| | - Qi Shao
- Department of Mechanical Engineering, University of Minnesota, Minneapolis, MN 55455
| | | | - Emilian Racila
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN 55455
| | - Jiaen Liu
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892
| | - John Bischof
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455
- Department of Mechanical Engineering, University of Minnesota, Minneapolis, MN 55455
| | - Bin He
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455
- Department of Biomedical Engineering, Carnegie Mellon University, PA 15213, USA
| |
Collapse
|
31
|
Guo L, Jin J, Li M, Wang Y, Liu CY, Liu F, Crozier S. Reference-Based Integral MR-EPT:Simulation and Experiment Studies on the 9.4T MRI. IEEE Trans Biomed Eng 2018; 66:1832-1843. [PMID: 30403619 DOI: 10.1109/tbme.2018.2879667] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Current integral-equation (IE) based MR electrical properties tomography (EPT) methods utilize simulated incident radio-frequency (RF) fields, which are inaccurate and lead to reconstruction errors. To improve the accuracy and practicability of IE-based MR-EPT methods, a new approach is presented that obtains the incident fields using reference subjects and RF field mapping techniques. The Incident field approximation (IFA) is first demonstrated in this paper. This approximation assumes that two imaged subjects with similar coil/subject interactions will have similar incident RF fields, thus one can feed the estimation of the incident fields within the imaged subject into the calculation of those within a homogeneous subject (reference subject). This is done by measuring the total RF fields ( field) of the reference using field mapping techniques, using the known EPs of the reference subject and by rearranging Ampere's Law and the integral equations. The calculated incident RF fields are then used to reconstruct the EPs' distribution with a three-dimensional (3D) integral-based MR-EPT method. Numerical simulation results indicated that the incident RF fields obtained from the reference subject provide accurate 3D reconstruction of EPs with less than 16% root mean square error (RMSE) in noise-free scenario while the conventional IE method had more than 28% RMSE. The phantom-based experiments at 9.4T MRI system have also been conducted to evaluate the performance of the proposed method and the results indicated that the proposed method achieved desirable robustness against the noise in practical scenario with less than 21% RMSE while the conventional differential equation-based method showed worse than 37% RMSE.
Collapse
|
32
|
Ozdemir S, Ider YZ. bSSFP phase correction and its use in magnetic resonance electrical properties tomography. Magn Reson Med 2018; 81:934-946. [PMID: 30357891 DOI: 10.1002/mrm.27446] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2018] [Revised: 06/06/2018] [Accepted: 06/12/2018] [Indexed: 11/05/2022]
Abstract
PURPOSE Balanced steady-state free precession (bSSFP) sequence is widely used because of its high SNR and high speed. However, bSSFP images suffer from "banding artifact" caused by B0 inhomogeneity. In this article, we propose a method to remove this artifact in bSSFP phase images and investigate the usage of the corrected phase images in phase-based magnetic resonance electrical properties tomography (MREPT). THEORY AND METHODS Two bSSFP phase images, obtained with different excitation frequencies, are collaged to get rid of the regions containing banding artifacts. Phase of the collaged bSSFP image is the sum of the transceive phase of the RF system and an error term that depends on B0 and T2 . By using B0 and T2 maps, this error is eliminated from bSSFP phase images by using pixel-wise corrections. Conductivity maps are obtained from the uncorrected and the corrected phase images using the phase-based cr-MREPT method. RESULTS Phantom and human experiment results of the proposed method are illustrated for both phase images and conductivity maps. It is shown that uncorrected phase images yield unacceptable conductivity images. When only B0 information is used for phase correction conductivity, reconstructions are substantially improved, and yet T2 information is still needed to fully recover accurate and undistorted conductivity images. CONCLUSIONS With the proposed technique, B0 sensitivity of the bSSFP phase images can be removed by using B0 and T2 maps. It is also shown that corrected bSSFP phase images are of sufficient quality to be used in conductivity imaging.
Collapse
Affiliation(s)
- Safa Ozdemir
- Department of Electrical and Electronics Engineering, Bilkent University, Ankara, Turkey
| | - Yusuf Ziya Ider
- Department of Electrical and Electronics Engineering, Bilkent University, Ankara, Turkey
| |
Collapse
|
33
|
Hancu I, Liu J, Hua Y, Lee SK. Electrical properties tomography: Available contrast and reconstruction capabilities. Magn Reson Med 2018; 81:803-810. [PMID: 30325052 DOI: 10.1002/mrm.27453] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2018] [Revised: 06/10/2018] [Accepted: 06/24/2018] [Indexed: 12/29/2022]
Abstract
MR-based electrical properties tomography converts the MRI transmit/receive RF field measurements to tissue electrical property maps through dedicated reconstruction algorithms. Recent reports showed that despite limitations, electrical properties tomography holds promise for generating additional contrast for tumor detection and patient-specific modeling of tissue-RF field interactions. This review summarizes the available tissue electrical property contrasts and compares them with the capabilities of the most commonly used electrical properties tomography reconstruction method. Future directions and prospects of clinical translation are discussed.
Collapse
Affiliation(s)
| | - Jiaen Liu
- National Institute of Neurological, Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
| | - Yihe Hua
- GE Global Research, Niskayuna, New York
| | - Seung-Kyun Lee
- IBS Center for Neuroscience Imaging Research, Suwon, Republic of Korea
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea
| |
Collapse
|
34
|
Shin J, Kim JH, Kim DH. Redesign of the Laplacian kernel for improvements in conductivity imaging using MRI. Magn Reson Med 2018; 81:2167-2175. [PMID: 30298524 DOI: 10.1002/mrm.27528] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2018] [Revised: 08/08/2018] [Accepted: 08/22/2018] [Indexed: 11/10/2022]
Abstract
PURPOSE To develop an electrical property tomography reconstruction method that achieves improvements over standard method by redesigning the Laplacian kernel. THEORY AND METHODS A decomposition property of the governing PET equation shows the possibility of redesigning the Laplacian kernel for conductivity reconstruction. Hence, the discrete Laplacian operator used for electrical property tomography reconstruction is redesigned to have a Gaussian-like envelope, which enables manipulation of the spatial and spectral response. The characteristics of the proposed kernel are investigated through numerical simulations and in vivo brain experiments. RESULTS The proposed method reduces textured noise, which hampers observing features of the conductivity image. Furthermore, the proposed scheme can mitigate the propagation of local phase error such as flow-induced phase. By doing so, the proposed method can recover feature information in conductivity (or resistivity) images. Lastly, the proposed kernel can be extended to other electrical property tomography reconstructions, improving the quality of images. CONCLUSION An alternative design of the Laplacian kernel for conductivity imaging has been developed to mitigate the textured noise and the propagation of local phase artifact.
Collapse
Affiliation(s)
- Jaewook Shin
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Jun-Hyeong Kim
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Dong-Hyun Kim
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| |
Collapse
|
35
|
Hampe N, Herrmann M, Amthor T, Findeklee C, Doneva M, Katscher U. Dictionary-based electric properties tomography. Magn Reson Med 2018; 81:342-349. [PMID: 30246342 DOI: 10.1002/mrm.27401] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2017] [Revised: 05/18/2018] [Accepted: 05/21/2018] [Indexed: 12/24/2022]
Abstract
PURPOSE To develop and validate a new algorithm called "dictionary-based electric properties tomography" (dbEPT) for deriving tissue electric properties from measured B1 maps. METHODS Inspired by Magnetic Resonance fingerprinting, dbEPT uses a dictionary of local patterns ("atoms") of B1 maps and corresponding electric properties distributions, derived from electromagnetic field simulations. For reconstruction, a pattern from a measured B1 map is compared with the B1 atoms of the dictionary. The B1 atom showing the best match with the measured B1 pattern yields the optimum electric properties pattern that is chosen for reconstruction. Matching was performed through machine learning algorithms. Two dictionaries, using transmit and transceive phases, were evaluated. The spatial distribution of local matching distance between optimal atom and measured pattern yielded a reconstruction reliability map. The method was applied to reconstruct conductivity of 4 volunteers' brains. A conventional, Helmholtz-based Electric properties tomography (EPT) reconstruction was performed for reference. Noise performance was studied through phantom simulations. RESULTS Quantitative values of conductivity agree with literature values. Results of the 2 dictionaries exhibit only minor differences. Somewhat larger differences are visible between dbEPT and Helmholtz-based EPT. Quantified by the correlation between conductivity and anatomic images, dbEPT depicts brain details more clearly than Helmholtz-based EPT. Matching distance is minimal in homogeneous brain ventricles and increases with tissue heterogeneity. Central processing unit time was approximately 2 minutes per dictionary training and 3 minutes per brain conductivity reconstruction using standard hardware equipment. CONCLUSION A new, dictionary-based approach for reconstructing electric properties is presented. Its conductivity reconstruction is able to overcome the EPT transceive-phase problem.
Collapse
Affiliation(s)
| | - Max Herrmann
- University of Applied Sciences, Hamburg, Germany
| | | | | | | | | |
Collapse
|
36
|
Leijsen RL, Brink WM, van den Berg CAT, Webb AG, Remis RF. 3-D Contrast Source Inversion-Electrical Properties Tomography. IEEE TRANSACTIONS ON MEDICAL IMAGING 2018; 37:2080-2089. [PMID: 29994520 DOI: 10.1109/tmi.2018.2816125] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Contrast source inversion-electrical properties tomography (CSI-EPT) is an iterative reconstruction method to retrieve the electrical properties (EPs) of tissues from magnetic resonance data. The method is based on integral representations of the electromagnetic field and has been shown to allow EP reconstructions of small structures as well as tissue boundaries with compelling accuracy. However, to date, the CSI-EPT has been implemented for 2-D configurations only, which limits its applicability. In this paper, a full 3-D extension of the CSI-EPT method is presented, to enable CSI-EPT to be applied to realistic 3-D scenarios. Here, we demonstrate a proof-of-principle of 3-D CSI-EPT and present the reconstructions of a 3-D abdominal body section and a 3-D head model using different settings of the transmit coil. Numerical results show that the full 3-D approach yields accurate reconstructions of the EPs, even at tissue boundaries and is most accurate in regions where the absolute value of the electric field is highest.
Collapse
|
37
|
Sajib SZK, Kwon OI, Kim HJ, Woo EJ. Electrodeless conductivity tensor imaging (CTI) using MRI: basic theory and animal experiments. Biomed Eng Lett 2018; 8:273-282. [PMID: 30603211 PMCID: PMC6208539 DOI: 10.1007/s13534-018-0066-3] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2018] [Revised: 04/12/2018] [Accepted: 04/12/2018] [Indexed: 11/26/2022] Open
Abstract
The electrical conductivity is a passive material property primarily determined by concentrations of charge carriers and their mobility. The macroscopic conductivity of a biological tissue at low frequency may exhibit anisotropy related with its structural directionality. When expressed as a tensor and properly quantified, the conductivity tensor can provide diagnostic information of numerous diseases. Imaging conductivity distributions inside the human body requires probing it by externally injecting conduction currents or inducing eddy currents. At low frequency, the Faraday induction is negligible and it has been necessary in most practical cases to inject currents through surface electrodes. Here we report a novel method to reconstruct conductivity tensor images using an MRI scanner without current injection. This electrodeless method of conductivity tensor imaging (CTI) utilizes B1 mapping to recover a high-frequency isotropic conductivity image which is influenced by contents in both extracellular and intracellular spaces. Multi-b diffusion weighted imaging is then utilized to extract the effects of the extracellular space and incorporate its directional structural property. Implementing the novel CTI method in a clinical MRI scanner, we reconstructed in vivo conductivity tensor images of canine brains. Depending on the details of the implementation, it may produce conductivity contrast images for conductivity weighted imaging (CWI). Clinical applications of CTI and CWI may include imaging of tumor, ischemia, inflammation, cirrhosis, and other diseases. CTI can provide patient-specific models for source imaging, transcranial dc stimulation, deep brain stimulation, and electroporation.
Collapse
Affiliation(s)
- Saurav Z. K. Sajib
- Department of Biomedical Engineering, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul, 02447 Korea
| | - Oh In Kwon
- Department of Mathematics, Konkuk University, 120 Neungdongro, Gwangjin-gu, Seoul, 05029 Korea
| | - Hyung Joong Kim
- Department of Biomedical Engineering, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul, 02447 Korea
| | - Eung Je Woo
- Department of Biomedical Engineering, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul, 02447 Korea
| |
Collapse
|
38
|
Liu C, Jin J, Guo L, Li M, Tesiram Y, Chen H, Liu F, Xin X, Crozier S. MR-based electrical property tomography using a modified finite difference scheme. Phys Med Biol 2018; 63:145013. [PMID: 29897046 DOI: 10.1088/1361-6560/aacc35] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Magnetic resonance electrical property tomography (MR-EPT) reconstructs electrical properties (EPs) from measured magnetic fields in magnetic resonance imaging (MRI) systems. In this study, an MR-EPT method was proposed that utilized a new finite difference approximation of the involved differential wave equation. Compared with existing MR-EPT approaches, the construction of the system matrix involves applying the first derivative twice based on a larger number of neighbouring finite-difference grids, which is different from a standard Laplacian operator on a regular grid structure, leading to a better conditioned linear inverse problem. With improved noise robustness, more faithful EPs can be obtained by the proposed method, particularly at tissue boundaries and regions with a poorly measured magnetic field (low signal-to-noise ratio). Numerical simulations with a specially designed multi-slice phantom and an anatomically accurate head model (Duke) have demonstrated that the proposed method can provide a more faithful reconstruction of EPs compared to existing methods, which usually offer unreliable solutions associated with traditional finite difference approximation of the central wave equation and unrealistic assumptions. Experiments on a 9.4 T MRI system have been conducted to validate the simulations.
Collapse
Affiliation(s)
- Chunyi Liu
- School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, QLD 4072, Australia
| | | | | | | | | | | | | | | | | |
Collapse
|
39
|
Chauhan M, Indahlastari A, Kasinadhuni AK, Schar M, Mareci TH, Sadleir RJ. Low-Frequency Conductivity Tensor Imaging of the Human Head In Vivo Using DT-MREIT: First Study. IEEE TRANSACTIONS ON MEDICAL IMAGING 2018; 37:966-976. [PMID: 29610075 PMCID: PMC5963516 DOI: 10.1109/tmi.2017.2783348] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
We present the first in vivo images of anisotropic conductivity distribution in the human head, measured at a frequency of approximately 10 Hz. We used magnetic resonance electrical impedance tomography techniques to encode phase changes caused by current flow within the head via two independent electrode pairs. These results were then combined with diffusion tensor imaging data to reconstruct full anisotropic conductivity distributions in 5-mm-thick slices of the brains of two participants. Conductivity values recovered in this paper were broadly consistent with literature values. We anticipate that this technique will be of use in many areas of neuroscience, most importantly in functional imaging via inverse electroencephalogram. Future studies will involve pulse sequence acceleration to maximize brain coverage and resolution.
Collapse
|
40
|
Ariturk G, Ider YZ. Optimal multichannel transmission for improved cr-MREPT. ACTA ACUST UNITED AC 2018; 63:045001. [DOI: 10.1088/1361-6560/aaa732] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
|
41
|
Guo L, Jin J, Liu C, Liu F, Crozier S. An Efficient Integral-Based Method for Three-Dimensional MR-EPT and the Calculation of the RF-Coil-Induced ${B_z}$ Field. IEEE Trans Biomed Eng 2018; 65:282-293. [DOI: 10.1109/tbme.2017.2763590] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
|
42
|
Liu J, Shao Q, Wang Y, Adriany G, Bischof J, Van de Moortele PF, He B. In vivo imaging of electrical properties of an animal tumor model with an 8-channel transceiver array at 7 T using electrical properties tomography. Magn Reson Med 2017; 78:2157-2169. [PMID: 28112824 PMCID: PMC5522781 DOI: 10.1002/mrm.26609] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2016] [Revised: 12/20/2016] [Accepted: 12/22/2016] [Indexed: 02/02/2023]
Abstract
PURPOSE To develop and evaluate a technique for imaging electrical properties ((EPs), conductivity and permittivity) of an animal tumor model in vivo using MRI. METHODS Electrical properties were reconstructed from the calculated EP gradient, which was derived using two sets of measured transmit B1 magnitude and relative phase maps with the sample and radiofrequency (RF) coil oriented in the positive and negative z-directions, respectively. An eight-channel transceiver microstrip array RF coil fitting the size of the animal was developed for generating and mapping B1 fields to reconstruct EPs. The technique was evaluated at 7 tesla using a physical phantom and in vivo on two Copenhagen rats with subcutaneously implanted AT-1 rat prostate cancer on a hind limb. RESULTS The reconstructed EPs in the phantom experiment was in good agreement with the target EP map determined by a dielectric probe. Reconstructed conductivity map of the animals revealed the boundary between tumor and healthy tissue consistent with the boundary indicated by T1 -weighted MRI. CONCLUSION A technique for imaging EP of an animal tumor model using MRI has been developed with high sensitivity, accuracy, and resolution, as demonstrated in the phantom experiment. Further animal experiments are needed to demonstrate its translational value for tumor diagnosis. Magn Reson Med 78:2157-2169, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
Collapse
Affiliation(s)
- Jiaen Liu
- Department of Biomedical Engineering, University of
Minnesota, Minneapolis, MN, U.S
| | - Qi Shao
- Department of Biomedical Engineering, University of
Minnesota, Minneapolis, MN, U.S
| | - Yicun Wang
- Department of Biomedical Engineering, University of
Minnesota, Minneapolis, MN, U.S
| | - Gregor Adriany
- Center for Magnetic Resonance Research, University of
Minnesota, Minneapolis, MN, U.S
| | - John Bischof
- Department of Biomedical Engineering, University of
Minnesota, Minneapolis, MN, U.S
- Department of Mechanical Engineering, University of
Minnesota, Minneapolis, Minnesota, MN, U.S
- Institute for Engineering in Medicine, University of
Minnesota, Minneapolis, MN, U.S
| | | | - Bin He
- Department of Biomedical Engineering, University of
Minnesota, Minneapolis, MN, U.S
- Institute for Engineering in Medicine, University of
Minnesota, Minneapolis, MN, U.S
| |
Collapse
|
43
|
Mandija S, Sbrizzi A, Katscher U, Luijten PR, van den Berg CAT. Error analysis of helmholtz-based MR-electrical properties tomography. Magn Reson Med 2017; 80:90-100. [PMID: 29144031 DOI: 10.1002/mrm.27004] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2017] [Revised: 10/19/2017] [Accepted: 10/21/2017] [Indexed: 11/10/2022]
Abstract
PURPOSE MR electrical properties tomography (MR-EPT) aims to measure tissue electrical properties by computing spatial derivatives of measured B1+ data. This computation is very sensitive to spatial fluctuations caused, for example, by noise and Gibbs ringing. In this work, the error arising from the computation of spatial derivatives using finite difference kernels (FD error) has been investigated. In relation to this FD error, it has also been investigated whether mitigation strategies such as Gibbs ringing correction and Gaussian apodization can be beneficial for conductivity reconstructions. METHODS Conductivity reconstructions were performed on a phantom (by means of simulations and MR measurements at 3T) and on a human brain model. The accuracy was evaluated as a function of image resolution, FD kernel size, k-space windowing, and signal-to-noise ratio. The impact of mitigation strategies was also investigated. RESULTS The adopted small FD kernel is highly sensitive to spatial fluctuations, whereas the large FD kernel is more noise-robust. However, large FD kernels lead to extended numerical boundary error propagation, which severely hampers the MR-EPT reconstruction accuracy for highly spatially convoluted tissue structures such as the human brain. Mitigation strategies slightly improve the accuracy of conductivity reconstructions. For the adopted derivative kernels and the investigated scenario, MR-EPT conductivity reconstructions show low accuracy: less than 37% of the voxels have a relative error lower than 30%. CONCLUSION The numerical error introduced by the computation of spatial derivatives using FD kernels is one of the major causes of limited accuracy in Helmholtz-based MR-EPT reconstructions. Magn Reson Med 80:90-100, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
Collapse
Affiliation(s)
- Stefano Mandija
- Center For Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Alessandro Sbrizzi
- Center For Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | | | - Peter R Luijten
- Center For Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands.,Department of Radiology, Imaging Division, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Cornelis A T van den Berg
- Center For Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands.,Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands
| |
Collapse
|
44
|
Liu J, Wang Y, Katscher U, He B. Electrical Properties Tomography Based on $B_{{1}}$ Maps in MRI: Principles, Applications, and Challenges. IEEE Trans Biomed Eng 2017; 64:2515-2530. [PMID: 28829299 PMCID: PMC5675043 DOI: 10.1109/tbme.2017.2725140] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
OBJECTIVE The purpose is to provide a comprehensive review of the electrical properties tomography (EPT) technique, which was introduced to image the electrical properties (EPs) of tissue noninvasively by exploiting the measured field data of MRI. METHODS We reviewed the principle of EPT, reconstruction methods, biomedical applications such as tumor imaging, and existing challenges. As a key application of EPT, the estimation of specific absorption rate (SAR) due to MRI was discussed in the background of elevated risk of tissue heating at high field. RESULTS AND CONCLUSION Since the originally proposed local, homogeneous Helmholtz equation-based reconstruction algorithm, advanced EPT algorithms have emerged to address the challenges of EPT, including reconstruction error near tissue boundaries, noise sensitivity, inaccurate phase estimation, and elimination of the unmeasurable component, along with demonstrations of in vivo experiments. EPT techniques have been applied to investigate EPs of both healthy and pathological tissues in vivo and factors contributing to various EP value, including sodium, water content, etc. More studies are anticipated to consolidate the current findings. EPT-based subject-specific SAR estimation has led to in vivo demonstration of its feasibility and prediction of temperature increase of phantom during MRI scans merely using measured data. SIGNIFICANCE EPT has the advantage of high resolution and practical feasibility in a clinical setup for imaging the biomedically interesting EPs of tissue in the radiofrequency range. EPT-based SAR estimation is another promising topic for predicting tissue heating of individual subjects during a specific MRI scan.
Collapse
Affiliation(s)
- Jiaen Liu
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, 20892, USA
| | - Yicun Wang
- Department of Biomedical Engineering, University of Minnesota, Minnesota, 55455, USA
| | | | - Bin He
- Department of Biomedical Engineering and Institute for Engineering in Medicine, University of Minnesota, Minnesota, 55455, USA
| |
Collapse
|
45
|
Magnetic resonance electrical properties tomography for small anomalies using boundary conditions: A simulation study. Med Phys 2017; 44:4773-4785. [DOI: 10.1002/mp.12343] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2016] [Revised: 05/08/2017] [Accepted: 05/08/2017] [Indexed: 11/07/2022] Open
|
46
|
Katscher U, van den Berg CAT. Electric properties tomography: Biochemical, physical and technical background, evaluation and clinical applications. NMR IN BIOMEDICINE 2017; 30:e3729. [PMID: 28543640 DOI: 10.1002/nbm.3729] [Citation(s) in RCA: 49] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2017] [Revised: 03/13/2017] [Accepted: 03/14/2017] [Indexed: 06/07/2023]
Abstract
Electric properties tomography (EPT) derives the patient's electric properties, i.e. conductivity and permittivity, using standard magnetic resonance (MR) systems and standard MR sequences. Thus, EPT does not apply externally mounted electrodes, currents or radiofrequency (RF) probes, as is the case in competing techniques. EPT is quantitative MR, i.e. it yields absolute values of conductivity and permittivity. This review summarizes the physical equations underlying EPT, the corresponding basic and advanced reconstruction techniques and practical numerical aspects to realize these reconstruction techniques. MR sequences which map the field information required for EPT are outlined, and experiments to validate EPT in phantom and in vivo studies are described. Furthermore, the review describes the clinical findings which have been obtained with EPT so far, and attempts to understand the physiologic background of these findings.
Collapse
Affiliation(s)
- Ulrich Katscher
- Department of Tomographic Imaging, Philips Research Laboratories, Hamburg, Germany
| | | |
Collapse
|
47
|
Shin J, Kim MO, Cho S, Kim DH. Fast Spin Echo Imaging-Based Electric Property Tomography With K-Space Weighting via ${T}_{2}$ Relaxation (rEPT). IEEE TRANSACTIONS ON MEDICAL IMAGING 2017; 36:1615-1625. [PMID: 28328503 DOI: 10.1109/tmi.2017.2684194] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Magnetic resonance electrical property tomography (MREPT) is a technique used to extract the electrical properties of tissues (conductivity in particular) using a magnetic resonance imaging system. In this paper, we propose an improved data acquisition scheme for the electrical property tomography technique by utilizing T 2 modulation in fast spin echo (FSE) imaging. This technique was motivated by a numerical analysis of conductivity reconstruction in the frequency domain; results reveal the spatial frequency-dependent noise texture of conventional methods. A data-acquisition scheme using the FSE sequence was formulated to concentrate the signal within a specific frequency range where notable noise amplification is observed in the conventional method. Through numerical studies, the performance of the proposed acquisition was investigated. Furthermore, a compensation scheme was applied to reduce quantification errors due to tissue-specific T 2 modulation, which is inherent in FSE imaging. The technique was applied to phantom and in vivo experiments. Results showed improved conductivity contrasts in both experiments, as compared with conventional MREPT methods.
Collapse
|
48
|
Arduino A, Zilberti L, Chiampi M, Bottauscio O. CSI-EPT in Presence of RF-Shield for MR-Coils. IEEE TRANSACTIONS ON MEDICAL IMAGING 2017; 36:1396-1404. [PMID: 28186884 DOI: 10.1109/tmi.2017.2665688] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Contrast source inversion electric properties tomography (CSI-EPT) is a recently developed technique for the electric properties tomography that recovers the electric properties distribution starting from measurements performed by magnetic resonance imaging scanners. This method is an optimal control approach based on the contrast source inversion technique, which distinguishes itself from other electric properties tomography techniques for its capability to recover also the local specific absorption rate distribution, essential for online dosimetry. Up to now, CSI-EPT has only been described in terms of integral equations, limiting its applicability to homogeneous unbounded background. In order to extend the method to the presence of a shield in the domain-as in the recurring case of shielded radio frequency coils-a more general formulation of CSI-EPT, based on a functional viewpoint, is introduced here. Two different implementations of CSI-EPT are proposed for a 2-D transverse magnetic model problem, one dealing with an unbounded domain and one considering the presence of a perfectly conductive shield. The two implementations are applied on the same virtual measurements obtained by numerically simulating a shielded radio frequency coil. The results are compared in terms of both electric properties recovery and local specific absorption rate estimate, in order to investigate the requirement of an accurate modeling of the underlying physical problem.
Collapse
|
49
|
Boudreau M, Tardif CL, Stikov N, Sled JG, Lee W, Pike GB. B 1 mapping for bias-correction in quantitative T 1 imaging of the brain at 3T using standard pulse sequences. J Magn Reson Imaging 2017; 46:1673-1682. [PMID: 28301086 DOI: 10.1002/jmri.25692] [Citation(s) in RCA: 45] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2016] [Accepted: 02/10/2017] [Indexed: 11/07/2022] Open
Abstract
PURPOSE B1 mapping is important for many quantitative imaging protocols, particularly those that include whole-brain T1 mapping using the variable flip angle (VFA) technique. However, B1 mapping sequences are not typically available on many magnetic resonance imaging (MRI) scanners. The aim of this work was to demonstrate that B1 mapping implemented using standard scanner product pulse sequences can produce B1 (and VFA T1 ) maps comparable in quality and acquisition time to advanced techniques. MATERIALS AND METHODS Six healthy subjects were scanned at 3.0T. An interleaved multislice spin-echo echo planar imaging double-angle (EPI-DA) B1 mapping protocol, using a standard product pulse sequence, was compared to two alternative methods (actual flip angle imaging, AFI, and Bloch-Siegert shift, BS). Single-slice spin-echo DA B1 maps were used as a reference for comparison (Ref. DA). VFA flip angles were scaled using each B1 map prior to fitting T1 ; the nominal flip angle case was also compared. RESULTS The pooled-subject voxelwise correlation (ρ) for B1 maps (BS/AFI/EPI-DA) relative to the reference B1 scan (Ref. DA) were ρ = 0.92/0.95/0.98. VFA T1 correlations using these maps were ρ = 0.86/0.88/0.96, much better than without B1 correction (ρ = 0.53). The relative error for each B1 map (BS/AFI/EPI-DA/Nominal) had 95th percentiles of 5/4/3/13%. CONCLUSION Our findings show that B1 mapping implemented using product pulse sequences can provide excellent quality B1 (and VFA T1 ) maps, comparable to other custom techniques. This fast whole-brain measurement (∼2 min) can serve as an excellent alternative for researchers without access to advanced B1 pulse sequences. LEVEL OF EVIDENCE 1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1673-1682.
Collapse
Affiliation(s)
- Mathieu Boudreau
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Christine L Tardif
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Canada
| | - Nikola Stikov
- Ecole Polytechnique de Montreal, Montreal, Quebec, Canada.,Montreal Heart Institute, University of Montreal, Montreal, Quebec, Canada
| | - John G Sled
- Hospital for Sick Children, Toronto, Ontario, Canada.,Department of Medical Biophysics, University of Toronto, Ontario, Canada
| | - Wayne Lee
- Department of Medical Biophysics, University of Toronto, Ontario, Canada
| | - G Bruce Pike
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.,Hotchkiss Brain Institute and Department of Radiology, University of Calgary, Calgary, Alberta, Canada
| |
Collapse
|
50
|
Ropella KM, Noll DC. A regularized, model-based approach to phase-based conductivity mapping using MRI. Magn Reson Med 2016; 78:2011-2021. [PMID: 28039883 DOI: 10.1002/mrm.26590] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2016] [Revised: 11/16/2016] [Accepted: 11/28/2016] [Indexed: 11/11/2022]
Abstract
PURPOSE To develop a novel regularized, model-based approach to phase-based conductivity mapping that uses structural information to improve the accuracy of conductivity maps. THEORY AND METHODS The inverse of the three-dimensional Laplacian operator is used to model the relationship between measured phase maps and the object conductivity in a penalized weighted least-squares optimization problem. Spatial masks based on structural information are incorporated into the problem to preserve data near boundaries. The proposed Inverse Laplacian method was compared against a restricted Gaussian filter in simulation, phantom, and human experiments. RESULTS The Inverse Laplacian method resulted in lower reconstruction bias and error due to noise in simulations than the Gaussian filter. The Inverse Laplacian method also produced conductivity maps closer to the measured values in a phantom and with reduced noise in the human brain, as compared to the Gaussian filter. CONCLUSION The Inverse Laplacian method calculates conductivity maps with less noise and more accurate values near boundaries. Improving the accuracy of conductivity maps is integral for advancing the applications of conductivity mapping. Magn Reson Med 78:2011-2021, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
Collapse
Affiliation(s)
- Kathleen M Ropella
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA
| | - Douglas C Noll
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA
| |
Collapse
|