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Cao J, Ball IK, Cassidy B, Rae CD. Functional conductivity imaging: quantitative mapping of brain activity. Phys Eng Sci Med 2024:10.1007/s13246-024-01484-z. [PMID: 39259483 DOI: 10.1007/s13246-024-01484-z] [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: 07/31/2023] [Accepted: 08/28/2024] [Indexed: 09/13/2024]
Abstract
Theory and modelling suggest that detection of neuronal activity may be feasible using phase sensitive MRI methods. Successful detection of neuronal activity both in vitro and in vivo has been described while others have reported negative results. Magnetic resonance electrical properties tomography may be a route by which signal changes can be identified. Here, we report successful and repeatable detection at 3 Tesla of human brain activation in response to visual and somatosensory stimuli using a functional version of tissue conductivity imaging (funCI). This detects activation in both white and grey matter with apparent tissue conductivity changes of 0.1 S/m (17-20%, depending on the tissue baseline conductivity measure) allowing visualization of complete system circuitry. The degree of activation scales with the degree of the stimulus (duration or contrast). The conductivity response functions show a distinct timecourse from that of traditional fMRI haemodynamic (BOLD or Blood Oxygenation Level Dependent) response functions, peaking within milliseconds of stimulus cessation and returning to baseline within 3-4 s. We demonstrate the utility of the funCI approach by showing robust activation of the lateral somatosensory circuitry on stimulation of an index finger, on stimulation of a big toe or of noxious (heat) stimulation of the face as well as activation of visual circuitry on visual stimulation in up to five different individuals. The sensitivity and repeatability of this approach provides further evidence that magnetic resonance imaging approaches can detect brain activation beyond changes in blood supply.
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Affiliation(s)
- Jun Cao
- Neuroscience Research Australia, 139 Barker St, Randwick, NSW, 2031, Australia
| | - Iain K Ball
- Philips Australia & New Zealand, North Ryde, NSW, 2113, Australia
| | - Benjamin Cassidy
- Neuroscience Research Australia, 139 Barker St, Randwick, NSW, 2031, Australia
- Pathfinder Exploration LLC, Tonopah, NV, USA
| | - Caroline D Rae
- Neuroscience Research Australia, 139 Barker St, Randwick, NSW, 2031, Australia.
- School of Psychology, The University of New South Wales, Sydney, NSW, 2052, Australia.
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2
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Iyyakkunnel S, Weigel M, Bieri O. Fast bias-corrected conductivity mapping using stimulated echoes. MAGMA (NEW YORK, N.Y.) 2024:10.1007/s10334-024-01194-3. [PMID: 39105952 DOI: 10.1007/s10334-024-01194-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Revised: 07/15/2024] [Accepted: 07/22/2024] [Indexed: 08/07/2024]
Abstract
OBJECTIVE To demonstrate the potential of a double angle stimulated echo (DA-STE) method for fast and accurate "full" homogeneous Helmholtz-based electrical properties tomography using a simultaneous B 1 + magnitude and transceive phase measurement. METHODS The combination of a spin and stimulated echo can be used to yield an estimate of both B 1 + magnitude and transceive phase and thus provides the means for "full" EPT reconstruction. An interleaved 2D acquisition scheme is used for rapid acquisition. The method was validated in a saline phantom and compared to a double angle method based on two single gradient echo acquisitions (GRE-DAM). The method was evaluated in the brain of a healthy volunteer. RESULTS The B 1 + magnitude obtained with DA-STE showed excellent agreement with the GRE-DAM method. Conductivity values based on the "full" EPT reconstruction also agreed well with the expectations in the saline phantom. In the brain, the method delivered conductivity values close to literature values. DISCUSSION The method allows the use of the "full" Helmholtz-based EPT reconstruction without the need for additional measurements. As a result, quantitative conductivity values are improved compared to phase-based EPT reconstructions. DA-STE is a fast complex- B 1 + mapping technique that could render EPT clinically relevant at 3 T.
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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.
| | - Matthias Weigel
- Division of Radiological Physics, Department of Radiology , University Hospital Basel, Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel, Basel, Switzerland
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and 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
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3
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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.
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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
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4
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Çan MK, Ider YZ. Bias correction for phase-based cr-MREPT using low resolution B1+ magnitude. Phys Med Biol 2024; 69:125020. [PMID: 38830364 DOI: 10.1088/1361-6560/ad53a1] [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: 02/07/2024] [Accepted: 06/03/2024] [Indexed: 06/05/2024]
Abstract
ObjectiveFull-form Magnetic Resonance Electrical Properties Tomography (MREPT) requires bothB1+magnitude and phase information. SinceB1+phase can be obtained faster and with higher SNR compared toB1+magnitude, several phase-based methods have been developed for conductivity imaging. However, phase-based methods suffer from a concave bias due to the assumption that∇|B1+|is negligible in the ROI.ApproachIn this paper, we re-derive the central equation of phase-based cr-MREPT without assuming that∇|B1+|is negligible and thus propose a correction method directly integrated into the equation system.Main resultsProposed method successfully corrects the concave bias on both simulated and experimental data and significantly increases image quality.SignificanceThe proposed correction method depends on a very low-resolution|B1+|map, and therefore the imaging time does not increase significantly for obtainingB1+magnitude. Moreover, correction can be achieved using simulatedB1+magnitude, hence completely removing the additional imaging requirement.
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Affiliation(s)
- Mustafa Kaan Çan
- Department of Electrical and Electronics Engineering, Bilkent University, 06800 Ankara, Turkey
| | - Yusuf Ziya Ider
- Department of Biomedical Engineering, Başkent University, 06790 Ankara, Turkey
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Schmid W, Danstrom IA, Crespo Echevarria M, Adkinson J, Mattar L, Banks GP, Sheth SA, Watrous AJ, Heilbronner SR, Bijanki KR, Alabastri A, Bartoli E. A biophysically constrained brain connectivity model based on stimulation-evoked potentials. J Neurosci Methods 2024; 405:110106. [PMID: 38453060 PMCID: PMC11233030 DOI: 10.1016/j.jneumeth.2024.110106] [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: 11/03/2023] [Revised: 01/24/2024] [Accepted: 03/04/2024] [Indexed: 03/09/2024]
Abstract
BACKGROUND Single-pulse electrical stimulation (SPES) is an established technique used to map functional effective connectivity networks in treatment-refractory epilepsy patients undergoing intracranial-electroencephalography monitoring. While the connectivity path between stimulation and recording sites has been explored through the integration of structural connectivity, there are substantial gaps, such that new modeling approaches may advance our understanding of connectivity derived from SPES studies. NEW METHOD Using intracranial electrophysiology data recorded from a single patient undergoing stereo-electroencephalography (sEEG) evaluation, we employ an automated detection method to identify early response components, C1, from pulse-evoked potentials (PEPs) induced by SPES. C1 components were utilized for a novel topology optimization method, modeling 3D electrical conductivity to infer neural pathways from stimulation sites. Additionally, PEP features were compared with tractography metrics, and model results were analyzed with respect to anatomical features. RESULTS The proposed optimization model resolved conductivity paths with low error. Specific electrode contacts displaying high error correlated with anatomical complexities. The C1 component strongly correlated with additional PEP features and displayed stable, weak correlations with tractography measures. COMPARISON WITH EXISTING METHOD Existing methods for estimating neural signal pathways are imaging-based and thus rely on anatomical inferences. CONCLUSIONS These results demonstrate that informing topology optimization methods with human intracranial SPES data is a feasible method for generating 3D conductivity maps linking electrical pathways with functional neural ensembles. PEP-estimated effective connectivity is correlated with but distinguished from structural connectivity. Modeled conductivity resolves connectivity pathways in the absence of anatomical priors.
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Affiliation(s)
- William Schmid
- Department of Electrical and Computer Engineering, Rice University, 6100 Main Street, Houston, TX 77005, USA
| | - Isabel A Danstrom
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA
| | - Maria Crespo Echevarria
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA
| | - Joshua Adkinson
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA
| | - Layth Mattar
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA
| | - Garrett P Banks
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA
| | - Sameer A Sheth
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA
| | - Andrew J Watrous
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA
| | - Sarah R Heilbronner
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA
| | - Kelly R Bijanki
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA
| | - Alessandro Alabastri
- Department of Electrical and Computer Engineering, Rice University, 6100 Main Street, Houston, TX 77005, USA.
| | - Eleonora Bartoli
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA.
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6
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Meerbothe TG, Meliado EF, Stijnman PRS, van den Berg CAT, Mandija S. A database for MR-based electrical properties tomography with in silico brain data-ADEPT. Magn Reson Med 2024; 91:1190-1199. [PMID: 37876351 DOI: 10.1002/mrm.29904] [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: 05/22/2023] [Revised: 10/06/2023] [Accepted: 10/06/2023] [Indexed: 10/26/2023]
Abstract
PURPOSE Several reconstruction methods for MR-based electrical properties tomography (EPT) have been developed. However, the lack of common data makes it difficult to objectively compare their performances. This is, however, a necessary precursor for standardizing and introducing this technique in the clinical setting. To enable objective comparison of the performances of reconstruction methods and provide common data for their training and testing, we created ADEPT, a database of simulated data for brain MR-EPT reconstructions. METHODS ADEPT is a database containing in silico data for brain EPT reconstructions. This database was created from 25 different brain models, with and without tumors. Rigid geometric augmentations were applied, and different electrical properties were assigned to white matter, gray matter, CSF, and tumors to generate 120 different brain models. These models were used as input for finite-difference time-domain simulations in Sim4Life, used to compute the electromagnetic fields needed for MR-EPT reconstructions. RESULTS Electromagnetic fields from 84 healthy and 36 tumor brain models were simulated. The simulated fields relevant for MR-EPT reconstructions (transmit and receive RF fields and transceive phase) and their ground-truth electrical properties are made publicly available through ADEPT. Additionally, nonattainable fields such as the total magnetic field and the electric field are available upon request. CONCLUSION ADEPT will serve as reference database for objective comparisons of reconstruction methods and will be a first step toward standardization of MR-EPT reconstructions. Furthermore, it provides a large amount of data that can be exploited to train data-driven methods. It can be accessed from https://doi.org/10.34894/V0HBJ8.
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Affiliation(s)
- T G Meerbothe
- Department of Radiotherapy, Division of Imaging and Oncology, University Medical Center Utrecht, Utrecht, The Netherlands
- Computational Imaging Group for MR Therapy and Diagnostics, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - E F Meliado
- Department of Radiotherapy, Division of Imaging and Oncology, University Medical Center Utrecht, Utrecht, The Netherlands
- Computational Imaging Group for MR Therapy and Diagnostics, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - P R S Stijnman
- Department of Radiotherapy, Division of Imaging and Oncology, University Medical Center Utrecht, Utrecht, The Netherlands
- Computational Imaging Group for MR Therapy and Diagnostics, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - C A T van den Berg
- Department of Radiotherapy, Division of Imaging and Oncology, University Medical Center Utrecht, Utrecht, The Netherlands
- Computational Imaging Group for MR Therapy and Diagnostics, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - S Mandija
- Department of Radiotherapy, Division of Imaging and Oncology, University Medical Center Utrecht, Utrecht, The Netherlands
- Computational Imaging Group for MR Therapy and Diagnostics, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
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7
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Cencini M, Lancione M, Pasquariello R, Peretti L, Pirkl CM, Schulte RF, Buonincontri G, Arduino A, Zilberti L, Biagi L, Tosetti M. Fast high-resolution electric properties tomography using three-dimensional quantitative transient-state imaging-based water fraction estimation. NMR IN BIOMEDICINE 2024; 37:e5039. [PMID: 37714527 DOI: 10.1002/nbm.5039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 08/18/2023] [Accepted: 08/28/2023] [Indexed: 09/17/2023]
Abstract
In this study, we aimed to develop a fast and robust high-resolution technique for clinically feasible electrical properties tomography based on water content maps (wEPT) using Quantitative Transient-state Imaging (QTI), a multiparametric transient state-based method that is similar to MR fingerprinting. Compared with the original wEPT implementation based on standard spin-echo acquisition, QTI provides robust electrical properties quantification towards B1 + inhomogeneities and full quantitative relaxometry data. To validate the proposed approach, 3D QTI data of 12 healthy volunteers were acquired on a 1.5 T scanner. QTI-provided T1 maps were used to compute water content maps of the tissues using an empirical relationship based on literature ex-vivo measurements. Assuming that electrical properties are modulated mainly by tissue water content, the water content maps were used to derive electrical conductivity and relative permittivity maps. The proposed technique was compared with a conventional phase-only Helmholtz EPT (HH-EPT) acquisition both within whole white matter, gray matter, and cerebrospinal fluid masks, and within different white and gray matter subregions. In addition, QTI-based wEPT was retrospectively applied to four multiple sclerosis adolescent and adult patients, compared with conventional contrast-weighted imaging in terms of lesion delineation, and quantitatively assessed by measuring the variation of electrical properties in lesions. Results obtained with the proposed approach agreed well with theoretical predictions and previous in vivo findings in both white and gray matter. The reconstructed maps showed greater anatomical detail and lower variability compared with standard phase-only HH-EPT. The technique can potentially improve delineation of pathology when compared with conventional contrast-weighted imaging and was able to detect significant variations in lesions with respect to normal-appearing tissues. In conclusion, QTI can reliably measure conductivity and relative permittivity of brain tissues within a short scan time, opening the way to the study of electric properties in clinical settings.
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Affiliation(s)
- Matteo Cencini
- Istituto Nazionale di Fisica Nucleare, Sezione di Pisa, Pisa, Italy
| | | | | | | | | | | | | | | | - Luca Zilberti
- Istituto Nazionale di Ricerca Metrologica (INRiM), Torino, Italy
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8
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Schmid W, Danstrom IA, Echevarria MC, Adkinson J, Mattar L, Banks GP, Sheth SA, Watrous AJ, Heilbronner SR, Bijanki KR, Alabastri A, Bartoli E. A biophysically constrained brain connectivity model based on stimulation-evoked potentials. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.03.565525. [PMID: 37986830 PMCID: PMC10659345 DOI: 10.1101/2023.11.03.565525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Background Single-pulse electrical stimulation (SPES) is an established technique used to map functional effective connectivity networks in treatment-refractory epilepsy patients undergoing intracranial-electroencephalography monitoring. While the connectivity path between stimulation and recording sites has been explored through the integration of structural connectivity, there are substantial gaps, such that new modeling approaches may advance our understanding of connectivity derived from SPES studies. New Method Using intracranial electrophysiology data recorded from a single patient undergoing sEEG evaluation, we employ an automated detection method to identify early response components, C1, from pulse-evoked potentials (PEPs) induced by SPES. C1 components were utilized for a novel topology optimization method, modeling 3D conductivity propagation from stimulation sites. Additionally, PEP features were compared with tractography metrics, and model results were analyzed with respect to anatomical features. Results The proposed optimization model resolved conductivity paths with low error. Specific electrode contacts displaying high error correlated with anatomical complexities. The C1 component strongly correlates with additional PEP features and displayed stable, weak correlations with tractography measures. Comparison with existing methods Existing methods for estimating conductivity propagation are imaging-based and thus rely on anatomical inferences. Conclusions These results demonstrate that informing topology optimization methods with human intracranial SPES data is a feasible method for generating 3D conductivity maps linking electrical pathways with functional neural ensembles. PEP-estimated effective connectivity is correlated with but distinguished from structural connectivity. Modeled conductivity resolves connectivity pathways in the absence of anatomical priors.
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Affiliation(s)
- William Schmid
- Department of Electrical and Computer Engineering, Rice University, 6100 Main Street, Houston 77005, Texas, USA
| | - Isabel A. Danstrom
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston 77030, Texas, USA
| | - Maria Crespo Echevarria
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston 77030, Texas, USA
| | - Joshua Adkinson
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston 77030, Texas, USA
| | - Layth Mattar
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston 77030, Texas, USA
| | - Garrett P. Banks
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston 77030, Texas, USA
| | - Sameer A. Sheth
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston 77030, Texas, USA
| | - Andrew J. Watrous
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston 77030, Texas, USA
| | - Sarah R. Heilbronner
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston 77030, Texas, USA
| | - Kelly R. Bijanki
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston 77030, Texas, USA
| | - Alessandro Alabastri
- Department of Electrical and Computer Engineering, Rice University, 6100 Main Street, Houston 77005, Texas, USA
| | - Eleonora Bartoli
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston 77030, Texas, USA
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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.
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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
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10
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Soon RH, Yin Z, Dogan MA, Dogan NO, Tiryaki ME, Karacakol AC, Aydin A, Esmaeili-Dokht P, Sitti M. Pangolin-inspired untethered magnetic robot for on-demand biomedical heating applications. Nat Commun 2023; 14:3320. [PMID: 37339969 PMCID: PMC10282021 DOI: 10.1038/s41467-023-38689-x] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 05/11/2023] [Indexed: 06/22/2023] Open
Abstract
Untethered magnetic miniature soft robots capable of accessing hard-to-reach regions can enable safe, disruptive, and minimally invasive medical procedures. However, the soft body limits the integration of non-magnetic external stimuli sources on the robot, thereby restricting the functionalities of such robots. One such functionality is localised heat generation, which requires solid metallic materials for increased efficiency. Yet, using these materials compromises the compliance and safety of using soft robots. To overcome these competing requirements, we propose a pangolin-inspired bi-layered soft robot design. We show that the reported design achieves heating > 70 °C at large distances > 5 cm within a short period of time <30 s, allowing users to realise on-demand localised heating in tandem with shape-morphing capabilities. We demonstrate advanced robotic functionalities, such as selective cargo release, in situ demagnetisation, hyperthermia and mitigation of bleeding, on tissue phantoms and ex vivo tissues.
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Affiliation(s)
- Ren Hao Soon
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
- Institute for Biomedical Engineering, ETH Zürich, 8092, Zürich, Switzerland
| | - Zhen Yin
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
- Department of Control Science and Engineering, Tongji University, Shanghai, China
- Frontiers Science Center for Intelligent Autonomous Systems, Shanghai, China
| | - Metin Alp Dogan
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
| | - Nihal Olcay Dogan
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
- Institute for Biomedical Engineering, ETH Zürich, 8092, Zürich, Switzerland
| | - Mehmet Efe Tiryaki
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
- Institute for Biomedical Engineering, ETH Zürich, 8092, Zürich, Switzerland
| | - Alp Can Karacakol
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
| | - Asli Aydin
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
| | - Pouria Esmaeili-Dokht
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
| | - Metin Sitti
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany.
- Institute for Biomedical Engineering, ETH Zürich, 8092, Zürich, Switzerland.
- School of Medicine and College of Engineering, Koç University, 34450, Istanbul, Turkey.
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11
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Shin DJ, Choi H, Oh DK, Sung HP, Kim JH, Kim DH, Kim SY. Correlation between standardized uptake value of 18F-FDG PET/CT and conductivity with pathologic prognostic factors in breast cancer. Sci Rep 2023; 13:9844. [PMID: 37330544 PMCID: PMC10276807 DOI: 10.1038/s41598-023-36958-9] [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: 01/17/2023] [Accepted: 06/13/2023] [Indexed: 06/19/2023] Open
Abstract
We investigated the correlation between standardized uptake value (SUV) of 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) and conductivity parameters in breast cancer and explored the feasibility of conductivity as an imaging biomarker. Both SUV and conductivity have the potential to reflect the tumors' heterogeneous characteristics, but their correlations have not been investigated until now. Forty four women diagnosed with breast cancer who underwent breast MRI and 18F-FDG PET/CT at the time of diagnosis were included. Among them, 17 women received neoadjuvant chemotherapy followed by surgery and 27 women underwent upfront surgery. For conductivity parameters, maximum and mean values of the tumor region-of-interests were examined. For SUV parameters, SUVmax, SUVmean, and SUVpeak of the tumor region-of-interests were examined. Correlations between conductivity and SUV were evaluated, and among them, the highest correlation was observed between mean conductivity and SUVpeak (Spearman's correlation coefficient = 0.381). In a subgroup analysis for 27 women with upfront surgery, tumors with lymphovascular invasion (LVI) showed higher mean conductivity than those without LVI (median: 0.49 S/m vs 0.06 S/m, p < 0.001). In conclusion, our study shows a low positive correlation between SUVpeak and mean conductivity in breast cancer. Furthermore, conductivity showed a potential to noninvasively predict LVI status.
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Affiliation(s)
- Dong-Joo Shin
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Radiology, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Republic of Korea
- Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea
| | - Hongyoon Choi
- Department of Nuclear Medicine, Seoul National University Hospital, Seoul, Republic of Korea
| | - Dong Kyu Oh
- Department of Nuclear Medicine, Seoul National University Hospital, Seoul, Republic of Korea
| | - Hyun Pil Sung
- Department of Nuclear Medicine, Seoul National University Hospital, 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
| | - Soo-Yeon Kim
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea.
- Department of Radiology, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Republic of Korea.
- Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea.
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12
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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.
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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.
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13
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Kim JH, Shin J, Jung KJ, Cui C, Kim SY, Lee JH, Kim DH. Technical note: Multi-receiver combination method for phase-based electrical property tomography of the breast. Med Phys 2023; 50:1660-1669. [PMID: 36585806 DOI: 10.1002/mp.16195] [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: 02/21/2022] [Revised: 11/15/2022] [Accepted: 12/11/2022] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND Phase-based electrical property tomography (EPT) is a technique that allows conductivity reconstruction with only phase of the B1 field under the assumption that the magnitude of the B1 fields are homogeneous. The more this assumption is violated, the less accurate the reconstructed conductivity. Thus, a method that ensures homogeneity of | B 1 - | $| {{\rm{B}}_1^ - } |$ field is important for breast image using multi-receiver coil. PURPOSE To develop a method for multi-receiver combination for phase-based EPT usable for breast EPT imaging in the clinic. METHODS Theory of the proposed method is presented. To validate the proposed method, the phantom and in-vivo experiments were conducted. Conductivity images were reconstructed using the transceive phase of the combined image and results were compared with another combination method. RESULTS The proposed method's conductivity results were more stable than those of the previous method when | B 1 + | $| {{\rm{B}}_1^ + } |$ was not homogeneous and when the homogeneous contrast region was small. The phantom and in-vivo results indicate that the proposed method produces improved conductivity images than the previous method. The proposed combination method also increased the conductivity contrast between benign and cancerous tissues. CONCLUSION The proposed method produced more stable multi-receiver combination for phase-based EPT of the breast in a clinical environment.
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Affiliation(s)
- Jun-Hyeong Kim
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Jaewook Shin
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Kyu-Jin 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
| | - Jae-Hun Lee
- 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
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14
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High frequency conductivity decomposition by solving physically constraint underdetermined inverse problem in human brain. Sci Rep 2023; 13:3273. [PMID: 36841894 PMCID: PMC9968322 DOI: 10.1038/s41598-023-30344-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Accepted: 02/21/2023] [Indexed: 02/27/2023] Open
Abstract
The developed magnetic resonance electrical properties tomography (MREPT) can visualize the internal conductivity distribution at Larmor frequency by measuring the B1 transceive phase data from magnetic resonance imaging (MRI). The recovered high-frequency conductivity (HFC) value is highly complex and heterogeneous in a macroscopic imaging voxel. Using high and low b-value diffusion weighted imaging (DWI) data, the multi-compartment spherical mean technique (MC-SMT) characterizes the water molecule movement within and between intra- and extra-neurite compartments by analyzing the microstructures and underlying architectural organization of brain tissues. The proposed method decomposes the recovered HFC into the conductivity values in the intra- and extra-neurite compartments via the recovered intra-neurite volume fraction (IVF) and the diffusion patterns using DWI data. As a form of decomposition of intra- and extra-neurite compartments, the problem to determine the intra- and extra-neurite conductivity values from the HFC is still an underdetermined inverse problem. To solve the underdetermined problem, we use the compartmentalized IVF as a criterion to decompose the electrical properties because the ion-concentration and mobility have different characteristics in the intra- and extra-neurite compartments. The proposed method determines a representative apparent intra- and extra-neurite conductivity values by changing the underdetermined equation for a voxel into an over-determined minimization problem over a local window consisting of surrounding voxels. To suppress the noise amplification and estimate a feasible conductivity, we define a diffusion pattern distance to weight the over-determined system in the local window. To quantify the proposed method, we conducted a simulation experiment. The simulation experiments show the relationships between the noise reduction and the spatial resolution depending on the designed local window sizes and diffusion pattern distance. Human brain experiments (five young healthy volunteers and a patient with brain tumor) were conducted to evaluate and validate the reliability of the proposed method. To quantitatively compare the results with previously developed methods, we analyzed the errors for reconstructed extra-neurite conductivity using existing methods and indirectly verified the feasibility of the proposed method.
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15
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Arduino A, Pennecchi F, Katscher U, Cox M, Zilberti L. Repeatability and Reproducibility Uncertainty in Magnetic Resonance-Based Electric Properties Tomography of a Homogeneous Phantom. Tomography 2023; 9:420-435. [PMID: 36828386 PMCID: PMC9961522 DOI: 10.3390/tomography9010034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Revised: 02/10/2023] [Accepted: 02/14/2023] [Indexed: 02/19/2023] Open
Abstract
Uncertainty assessment is a fundamental step in quantitative magnetic resonance imaging because it makes comparable, in a strict metrological sense, the results of different scans, for example during a longitudinal study. Magnetic resonance-based electric properties tomography (EPT) is a quantitative imaging technique that retrieves, non-invasively, a map of the electric properties inside a human body. Although EPT has been used in some early clinical studies, a rigorous experimental assessment of the associated uncertainty has not yet been performed. This paper aims at evaluating the repeatability and reproducibility uncertainties in phase-based Helmholtz-EPT applied on homogeneous phantom data acquired with a clinical 3 T scanner. The law of propagation of uncertainty is used to evaluate the uncertainty in the estimated conductivity values starting from the uncertainty in the acquired scans, which is quantified through a robust James-Stein shrinkage estimator to deal with the dimensionality of the problem. Repeatable errors are detected in the estimated conductivity maps and are quantified for various values of the tunable parameters of the EPT implementation. The spatial dispersion of the estimated electric conductivity maps is found to be a good approximation of the reproducibility uncertainty, evaluated by changing the position of the phantom after each scan. The results underpin the use of the average conductivity (calculated by weighting the local conductivity values by their uncertainty and taking into account the spatial correlation) as an estimate of the conductivity of the homogeneous phantom.
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Affiliation(s)
- Alessandro Arduino
- Istituto Nazionale di Ricerca Metrologica, Strada delle Cacce 91, 10135 Torino, Italy
- Correspondence:
| | - Francesca Pennecchi
- Istituto Nazionale di Ricerca Metrologica, Strada delle Cacce 91, 10135 Torino, Italy
| | | | - Maurice Cox
- National Physical Laboratory, Teddington TW11 0LW, UK
| | - Luca Zilberti
- Istituto Nazionale di Ricerca Metrologica, Strada delle Cacce 91, 10135 Torino, Italy
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16
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Choi BK, Katoch N, Park JA, Kim JW, Oh TI, Kim HJ, Woo EJ. Measurement of extracellular volume fraction using magnetic resonance-based conductivity tensor imaging. Front Physiol 2023. [DOI: 10.3389/fphys.2023.132911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/17/2023] Open
Abstract
Conductivity tensor imaging (CTI) using MRI is an advanced method that can non-invasively measure the electrical properties of living tissues. The contrast of CTI is based on underlying hypothesis about the proportionality between the mobility and diffusivity of ions and water molecules inside tissues. The experimental validation of CTI in both in vitro and in vivo settings is required as a reliable tool to assess tissue conditions. The changes in extracellular space can be indicators for disease progression, such as fibrosis, edema, and cell swelling. In this study, we conducted a phantom imaging experiment to test the feasibility of CTI for measuring the extracellular volume fraction in biological tissue. To mimic tissue conditions with different extracellular volume fractions, four chambers of giant vesicle suspension (GVS) with different vesicle densities were included in the phantom. The reconstructed CTI images of the phantom were compared with the separately-measured conductivity spectra of the four chambers using an impedance analyzer. Moreover, the values of the estimated extracellular volume fraction in each chamber were compared with those measured by a spectrophotometer. As the vesicle density increased, we found that the extracellular volume fraction, extracellular diffusion coefficient, and low-frequency conductivity decreased, while the intracellular diffusion coefficient slightly increased. On the other hand, the high-frequency conductivity could not clearly distinguish the four chambers. The extracellular volume fraction measured by the spectrophotometer and CTI method in each chamber were quite comparable, i.e., (1.00, 0.98 ± 0.01), (0.59, 0.63 ± 0.02), (0.40, 0.40 ± 0.05), and (0.16, 0.18 ± 0.02). The prominent factor influencing the low-frequency conductivity at different GVS densities was the extracellular volume fraction. Further studies are needed to validate the CTI method as a tool to measure the extracellular volume fractions in living tissues with different intracellular and extracellular compartments.
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17
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Choi BK, Katoch N, Park JA, Kim JW, Oh TI, Kim HJ, Woo EJ. Measurement of extracellular volume fraction using magnetic resonance-based conductivity tensor imaging. Front Physiol 2023; 14:1132911. [PMID: 36875031 PMCID: PMC9983119 DOI: 10.3389/fphys.2023.1132911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 02/02/2023] [Indexed: 02/19/2023] Open
Abstract
Conductivity tensor imaging (CTI) using MRI is an advanced method that can non-invasively measure the electrical properties of living tissues. The contrast of CTI is based on underlying hypothesis about the proportionality between the mobility and diffusivity of ions and water molecules inside tissues. The experimental validation of CTI in both in vitro and in vivo settings is required as a reliable tool to assess tissue conditions. The changes in extracellular space can be indicators for disease progression, such as fibrosis, edema, and cell swelling. In this study, we conducted a phantom imaging experiment to test the feasibility of CTI for measuring the extracellular volume fraction in biological tissue. To mimic tissue conditions with different extracellular volume fractions, four chambers of giant vesicle suspension (GVS) with different vesicle densities were included in the phantom. The reconstructed CTI images of the phantom were compared with the separately-measured conductivity spectra of the four chambers using an impedance analyzer. Moreover, the values of the estimated extracellular volume fraction in each chamber were compared with those measured by a spectrophotometer. As the vesicle density increased, we found that the extracellular volume fraction, extracellular diffusion coefficient, and low-frequency conductivity decreased, while the intracellular diffusion coefficient slightly increased. On the other hand, the high-frequency conductivity could not clearly distinguish the four chambers. The extracellular volume fraction measured by the spectrophotometer and CTI method in each chamber were quite comparable, i.e., (1.00, 0.98 ± 0.01), (0.59, 0.63 ± 0.02), (0.40, 0.40 ± 0.05), and (0.16, 0.18 ± 0.02). The prominent factor influencing the low-frequency conductivity at different GVS densities was the extracellular volume fraction. Further studies are needed to validate the CTI method as a tool to measure the extracellular volume fractions in living tissues with different intracellular and extracellular compartments.
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Affiliation(s)
- Bup Kyung Choi
- Department of Biomedical Engineering, Kyung Hee University, Seoul, Republic of Korea
| | - Nitish Katoch
- Department of Biomedical Engineering, Kyung Hee University, Seoul, Republic of Korea
| | - Ji Ae Park
- Division of Applied RI, Korea Institute of Radiological and Medical Science, Seoul, Republic of Korea
| | - Jin Woong Kim
- Department of Radiology, Chosun University Hospital and Chosun University College of Medicine, Gwangju, Republic of Korea
| | - Tong In Oh
- Department of Biomedical Engineering, Kyung Hee University, Seoul, Republic of Korea
| | - Hyung Joong Kim
- Department of Biomedical Engineering, Kyung Hee University, Seoul, Republic of Korea
| | - Eung Je Woo
- Department of Biomedical Engineering, Kyung Hee University, Seoul, Republic of Korea
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18
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Correlation analysis between the complex electrical permittivity and relaxation time of tissue mimicking phantoms in 7 T MRI. Sci Rep 2022; 12:15444. [PMID: 36104392 PMCID: PMC9474530 DOI: 10.1038/s41598-022-19832-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 09/05/2022] [Indexed: 12/04/2022] Open
Abstract
Dielectric relaxation theory describes the complex permittivity of a material in an alternating field; in particular, Debye theory relates the time it takes for an applied field to achieve the maximum polarization and the electrical properties of the material. Although, Debye’s equations were proposed for electrical polarization, in this study, we investigate the correlation between the magnetic longitudinal relaxation time T1 and the complex electrical permittivity of tissue-mimicking phantoms using a 7 T magnetic resonance scanner. We created phantoms that mimicked several human tissues with specific electrical properties. The electrical properties of the phantoms were measured using bench-test equipment. T1 values were acquired from phantoms using MRI. The measured values were fitted with functions based on dielectric estimations, using relaxation times of electrical polarization, and the mixture theory for dielectrics. The results show that, T1 and the real permittivity are correlated; therefore, the correlation can be approximated with a rational function in the case of water-based phantoms. The correlation between index loss and T1 was determined using a fitting function based on the Debye equation and mixture theory equation, in which the fraction of the materials was taken into account. This phantom study and analysis provide an insight into the application relaxation times used for estimating dielectric properties. Currently, the measurement of electrical properties based on dielectric relaxation theory is based on an antenna, sometimes invasive, that irradiates an electric field into a small sample; thus, it is not possible to create a map of electrical properties for a complex structure such as the human body. This study could be further used to compute the electrical properties maps of tissues by scanning images and measuring T1 maps.
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Sasaki K, Porter E, Rashed EA, Farrugia L, Schmid G. Measurement and image-based estimation of dielectric properties of biological tissues —past, present, and future—. Phys Med Biol 2022; 67. [DOI: 10.1088/1361-6560/ac7b64] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2022] [Accepted: 06/22/2022] [Indexed: 12/23/2022]
Abstract
Abstract
The dielectric properties of biological tissues are fundamental pararmeters that are essential for electromagnetic modeling of the human body. The primary database of dielectric properties compiled in 1996 on the basis of dielectric measurements at frequencies from 10 Hz to 20 GHz has attracted considerable attention in the research field of human protection from non-ionizing radiation. This review summarizes findings on the dielectric properties of biological tissues at frequencies up to 1 THz since the database was developed. Although the 1996 database covered general (normal) tissues, this review also covers malignant tissues that are of interest in the research field of medical applications. An intercomparison of dielectric properties based on reported data is presented for several tissue types. Dielectric properties derived from image-based estimation techniques developed as a result of recent advances in dielectric measurement are also included. Finally, research essential for future advances in human body modeling is discussed.
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20
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Park S, Jung SM, Lee MB, Rhee HY, Ryu CW, Cho AR, Kwon OI, Jahng GH. Application of High-Frequency Conductivity Map Using MRI to Evaluate It in the Brain of Alzheimer's Disease Patients. Front Neurol 2022; 13:872878. [PMID: 35651350 PMCID: PMC9150564 DOI: 10.3389/fneur.2022.872878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 04/19/2022] [Indexed: 11/13/2022] Open
Abstract
Background The previous studies reported increased concentrations of metallic ions, imbalanced Na+ and K+ ions, and the increased mobility of protons by microstructural disruptions in Alzheimer's disease (AD). Purpose (1) to apply a high-frequency conductivity (HFC) mapping technique using a clinical 3T MRI system, (2) compare HFC values in the brains of participants with AD, amnestic mild cognitive impairment (MCI), and cognitively normal (CN) elderly people, (3) evaluate the relationship between HFC values and cognitive decline, and (4) explore usefulness of HFC values as an imaging biomarker to evaluate the differentiation of AD from CN. Materials and Methods This prospective study included 74 participants (23 AD patients, 27 amnestic MCI patients, and 24 CN elderly people) to explore the clinical application of HFC mapping in the brain from March 2019 to August 2021. We performed statistical analyses to compare HFC maps between the three participant groups, evaluate the association of HFC maps with Mini-Mental State Examination (MMSE) scores, and to evaluate the differentiation between the participant groups for HFC values for some brain areas. Results We obtained a good HFC map non-invasively. The HFC value was higher in the AD group than in the CN and MCI groups. MMSE scores were negatively associated with HFC values. Age was positively associated with HFC values. The HFC value in the insula has a high area under the receiver operating characteristic (ROC) curve (AUC) value to differentiate AD patients from the CN participants (Sensitivity [SE] = 82, Specificity [SP] =97, AUC = 0.902, p < 0.0001), better than gray matter volume (GMV) in hippocampus (SE = 79, SP = 83, AUC = 0.880, p < 0.0001). The classification for differentiating AD from CN was highest by adding the hippocampal GMV to the insular HFC value (SE = 87, SP = 87, AUC = 0.928, p < 0.0001). Conclusion High-frequency conductivity values were significantly increased in the AD group compared to the CN group and increased with age and disease severity. HFC values of the insula along with the GMV of the hippocampus can be used as an imaging biomarker to improve the differentiation of AD from CN.
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Affiliation(s)
- Soonchan Park
- Department of Radiology, College of Medicine, Kyung Hee University Hospital at Gangdong, Kyung Hee University, Seoul, South Korea
| | - Sue Min Jung
- Department of Biomedical Engineering, Undergraduate School, College of Electronics and Information, Kyung Hee University, Yongin-si, South Korea
| | - Mun Bae Lee
- Department of Mathematics, College of Basic Science, Konkuk University, Seoul, South Korea
| | - Hak Young Rhee
- Department of Neurology, College of Medicine, Kyung Hee University Hospital at Gangdong, Kyung Hee University, Seoul, South Korea
| | - Chang-Woo Ryu
- Department of Radiology, College of Medicine, Kyung Hee University Hospital at Gangdong, Kyung Hee University, Seoul, South Korea
| | - Ah Rang Cho
- Department of Psychiatry, College of Medicine, Kyung Hee University Hospital at Gangdong, Kyung Hee University, Seoul, South Korea
| | - Oh In Kwon
- Department of Mathematics, College of Basic Science, Konkuk University, Seoul, South Korea
| | - Geon-Ho Jahng
- Department of Radiology, College of Medicine, Kyung Hee University Hospital at Gangdong, Kyung Hee University, Seoul, South Korea
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Garcia Inda AJ, Huang SY, Imamoglu N, Yu W. Physics-Coupled Neural Network Magnetic Resonance Electrical Property Tomography (MREPT) for Conductivity Reconstruction. IEEE TRANSACTIONS ON IMAGE PROCESSING : A PUBLICATION OF THE IEEE SIGNAL PROCESSING SOCIETY 2022; 31:3463-3478. [PMID: 35533164 DOI: 10.1109/tip.2022.3172220] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
The electrical property (EP) of human tissues is a quantitative biomarker that facilitates early diagnosis of cancerous tissues. Magnetic resonance electrical properties tomography (MREPT) is an imaging modality that reconstructs EPs by the radio-frequency field in an MRI system. MREPT reconstructs EPs by solving analytic models numerically based on Maxwell's equations. Most MREPT methods suffer from artifacts caused by inaccuracy of the hypotheses behind the models, and/or numerical errors. These artifacts can be mitigated by adding coefficients to stabilize the models, however, the selection of such coefficient has been empirical, which limit its medical application. Alternatively, end-to-end Neural networks-based MREPT (NN-MREPT) learns to reconstruct the EPs from training samples, circumventing Maxwell's equations. However, due to its pattern-matching nature, it is difficult for NN-MREPT to produce accurate reconstructions for new samples. In this work, we proposed a physics-coupled NN for MREPT (PCNN-MREPT), in which an analytic model, cr-MREPT, works with diffusion and convection coefficients, learned by NNs from the difference between the reconstructed and ground-truth EPs to reduce artifacts. With two simulated datasets, three generalization experiments in which test samples deviate gradually from the training samples, and one noise-robustness experiment were conducted. The results show that the proposed PCNN-MREPT achieves higher accuracy than two representative analytic methods. Moreover, compared with an end-to-end NN-MREPT, the proposed method attained higher accuracy in two critical generalization tests. This is an important step to practical MREPT medical diagnoses.
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22
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Zhu D, Schär M, Qin Q. Ultrafast B1 mapping with RF-prepared 3D FLASH acquisition: Correcting the bias due to T 1 -induced k-space filtering effect. Magn Reson Med 2022; 88:757-769. [PMID: 35381114 PMCID: PMC9232926 DOI: 10.1002/mrm.29247] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 03/06/2022] [Accepted: 03/07/2022] [Indexed: 01/25/2023]
Abstract
Purpose The traditional radiofrequency (RF)‐prepared B1 mapping technique consists of one scan with an RF preparation module for flip angle‐encoding and a second scan without this module for normalizing. To reduce the T1‐induced k‐space filtering effect, this method is limited to 2D FLASH acquisition with a two‐parameter method. A novel 3D RF‐prepared three‐parameter method for ultrafast B1‐mapping is proposed to correct the T1‐induced quantification bias. Theory The point spread function analysis of FLASH shows that the prepared longitudinal magnetization before the FLASH acquisition and the image signal obeys a linear (not proportional) relationship. The intercept of the linear function causes the quantification bias and can be captured by a third saturated scan. Methods Using the 2D double‐angle method (DAM) as the reference, a 3D RF‐prepared three‐parameter protocol with 9 s duration was compared with the two‐parameter method, as well as the saturated DAM (SDAM) method, the dual refocusing echo acquisition mode (DREAM) method, and the actual flip‐angle imaging (AFI) method, for B1 mapping of brain, breast, and abdomen with different orientations and shim settings at 3T. Results The 3D RF‐prepared three‐parameter method with complex‐subtraction delivered consistently lower RMS error, error mean, error standard deviation, and higher concordance correlation coefficients values than the two‐parameter method, the three‐parameter method with magnitude‐subtraction, the multi‐slice DREAM and the 3D AFI, and were close to the results of 2D or multi‐slice SDAM. Conclusion The proposed ultrafast 3D RF‐prepared three‐parameter method with complex‐subtraction was demonstrated with high accuracy for B1 mapping of brain, breast, and abdomen.
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Affiliation(s)
- Dan Zhu
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA.,The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Michael Schär
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Qin Qin
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA.,The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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Liu W, Cao Y, Zhou X, Han D. Interstitial Fluid Behavior and Diseases. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2022; 9:e2100617. [PMID: 34978164 PMCID: PMC8867152 DOI: 10.1002/advs.202100617] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/14/2021] [Revised: 10/18/2021] [Indexed: 06/14/2023]
Abstract
Living things comprise a typical hierarchical and porous medium, and their most fundamental logical architectures are interstitial structures encapsulating parenchymal structures. The recent discovery of the efficient transport mechanisms of interstitial streams has provided a new understanding of these complex activities. The substance transport of interstitial streams follows mesoscopic fluid behavior dynamics, which is intimately associated with material transfer in nanoconfined spaces and a unique signal transmission. Accordingly, the evaluation of interstitial stream transport behavior at the mesoscopic scale is essential. In this review, recent advances in physical and chemical properties, the substance transport model, and the characterization methods of interstitial streams at the mesoscopic scale, as well as the relationships between interstitial streams and disease are summarized. Interstitial stream transport can be used as a basis to fully mine hierarchal behavior in images to expand imaging behavior into an omics field. By starting from the perspective of soft matter, a new understanding can be gained of health and disease and quantitative physical markers for research, clinical diagnosis, and treatment can be provided, as well as prognosis evaluation in complex diseases such as cancer and Alzheimer's disease. This will provide a foundation for the development of medicine of soft matter.
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Affiliation(s)
- Wen‐Tao Liu
- CAS Center for Excellence in NanoscienceNational Center for Nanoscience and TechnologyBeijing100190P. R. China
| | - Yu‐Peng Cao
- CAS Center for Excellence in NanoscienceNational Center for Nanoscience and TechnologyBeijing100190P. R. China
- School of Future TechnologyUniversity of Chinese Academy of SciencesBeijing100049P. R. China
| | - Xiao‐Han Zhou
- CAS Center for Excellence in NanoscienceNational Center for Nanoscience and TechnologyBeijing100190P. R. China
- School of Future TechnologyUniversity of Chinese Academy of SciencesBeijing100049P. R. China
| | - Dong Han
- CAS Center for Excellence in NanoscienceNational Center for Nanoscience and TechnologyBeijing100190P. R. China
- School of Future TechnologyUniversity of Chinese Academy of SciencesBeijing100049P. R. China
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24
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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: 12] [Impact Index Per Article: 6.0] [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.
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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
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25
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Chauhan M, Sadleir R. Phantom Construction and Equipment Configurations for Characterizing Electrical Properties Using MRI. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2022; 1380:83-110. [PMID: 36306095 DOI: 10.1007/978-3-031-03873-0_4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Phantom objects are commonly employed in MRI systems as stable substitutes for biological tissues to ensure systems for measuring images are operating correctly and safely. For magnetic resonance electrical impedance tomography (MREIT) and magnetic resonance electrical property tomography (MREPT), conductivity or permittivity phantoms play an important role in checking MRI pulse sequences, MREIT equipment performance, and algorithm validation. The construction of these phantoms is explained in this chapter. In the first part, materials used for phantom construction are introduced. Ingredients for modifying the electromagnetic properties and relaxation times are presented, and the advantages and disadvantages of aqueous, gel, and hybrid conductivity phantoms are explained. The devices and methods used to confirm phantom electromagnetic properties are explained. Next, different types of MREIT electrode materials and the constant current sources used for MREIT studies are discussed. In the last section, we present the results of previous MREIT and MREPT studies.
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Affiliation(s)
- Munish Chauhan
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - Rosalind Sadleir
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA.
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26
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Chauhan M, Sadleir R. MR Current Density and MREIT Data Acquisition. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2022; 1380:111-134. [DOI: 10.1007/978-3-031-03873-0_5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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27
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Iyyakkunnel S, Weigel M, Ganter C, Bieri O. Complex B 1 + mapping with Carr-Purcell spin echoes and its application to electrical properties tomography. Magn Reson Med 2021; 87:1250-1260. [PMID: 34752636 PMCID: PMC9298742 DOI: 10.1002/mrm.29020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 08/12/2021] [Accepted: 09/05/2021] [Indexed: 11/09/2022]
Abstract
Purpose To present a new complex‐valued B1+ mapping method for electrical properties tomography using Carr‐Purcell spin echoes. Methods A Carr‐Purcell (CP) echo train generates pronounced flip‐angle dependent oscillations that can be used to estimate the magnitude of B1+. To this end, a dictionary is used that takes into account the slice profile as well as T2 relaxation along the echo train. For validation, the retrieved B1+ map is compared with the actual flip angle imaging (AFI) method in a phantom (79 ε0, 0.34 S/m). Moreover, the phase of the first echo reflects the transceive phase. Overall, the CP echo train yields an estimate of the complex‐valued B1+, allowing electrical properties tomography with both permittivity and conductivity. The presented method is evaluated in phantom scans as well as for in vivo brain at 3 T. Results In the phantom, the obtained magnitude B1+ maps retrieved from the CP echo train and the AFI method show excellent agreement, and both the reconstructed estimated permittivity (79 ± 3) ε0 and conductivity (0.35 ± 0.04) S/m values are in accordance with expectations. In the brain, the obtained electrical properties are also close to expectations. In addition to the retrieved complex B1+ information, the decay of the CP echo trains also yields an estimate for T2. Conclusion The CP sequence can be used to simultaneously provide both B1+ magnitude and phase estimations, and therefore allows for full reconstruction of the electrical properties.
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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
| | - Matthias Weigel
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland.,Department of Biomedical Engineering, University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel, Basel, Switzerland.,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Carl Ganter
- Department of Radiology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Oliver Bieri
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland.,Department of Biomedical Engineering, University of Basel, Basel, Switzerland
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28
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Marino M, Cordero-Grande L, Mantini D, Ferrazzi G. Conductivity Tensor Imaging of the Human Brain Using Water Mapping Techniques. Front Neurosci 2021; 15:694645. [PMID: 34393709 PMCID: PMC8363203 DOI: 10.3389/fnins.2021.694645] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Accepted: 07/14/2021] [Indexed: 11/13/2022] Open
Abstract
Conductivity tensor imaging (CTI) has been recently proposed to map the conductivity tensor in 3D using magnetic resonance imaging (MRI) at the frequency range of the brain at rest, i.e., low-frequencies. Conventional CTI mapping methods process the trans-receiver phase of the MRI signal using the MR electric properties tomography (MR-EPT) technique, which in turn involves the application of the Laplace operator. This results in CTI maps with a low signal-to-noise ratio (SNR), artifacts at tissue boundaries and a limited spatial resolution. In order to improve on these aspects, a methodology independent from the MR-EPT method is proposed. This relies on the strong assumption for which electrical conductivity is univocally pre-determined by water concentration. In particular, CTI maps are calculated by combining high-frequency conductivity derived from water maps and multi b-value diffusion tensor imaging (DTI) data. Following the implementation of a pipeline to optimize the pre-processing of diffusion data and the fitting routine of a multi-compartment diffusivity model, reconstructed conductivity images were evaluated in terms of the achieved spatial resolution in five healthy subjects scanned at rest. We found that the pre-processing of diffusion data and the optimization of the fitting procedure improve the quality of conductivity maps. We achieve reproducible measurements across healthy participants and, in particular, we report conductivity values across subjects of 0.55 ± 0.01Sm, 0.3 ± 0.01Sm and 2.15 ± 0.02Sm for gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF), respectively. By attaining an actual spatial resolution of the conductivity tensor close to 1 mm in-plane isotropic, partial volume effects are reduced leading to good discrimination of tissues with similar conductivity values, such as GM and WM. The application of the proposed framework may contribute to a better definition of the head tissue compartments in electroencephalograpy/magnetoencephalography (EEG/MEG) source imaging and be used as biomarker for assessing conductivity changes in pathological conditions, such as stroke and brain tumors.
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Affiliation(s)
- Marco Marino
- Research Center for Motor Control and Neuroplasticity, KU Leuven, Leuven, Belgium.,IRCCS San Camillo Hospital, Venice, Italy
| | - Lucilio Cordero-Grande
- Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politécnica de Madrid and CIBER-BBN, Madrid, Spain
| | - Dante Mantini
- Research Center for Motor Control and Neuroplasticity, KU Leuven, Leuven, Belgium.,IRCCS San Camillo Hospital, Venice, Italy
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29
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Lesbats C, Katoch N, Minhas AS, Taylor A, Kim HJ, Woo EJ, Poptani H. High-frequency electrical properties tomography at 9.4T as a novel contrast mechanism for brain tumors. Magn Reson Med 2021; 86:382-392. [PMID: 33533114 PMCID: PMC8603929 DOI: 10.1002/mrm.28685] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Revised: 12/03/2020] [Accepted: 12/24/2020] [Indexed: 11/11/2022]
Abstract
PURPOSE To establish high-frequency magnetic resonance electrical properties tomography (MREPT) as a novel contrast mechanism for the assessment of glioblastomas using a rat brain tumor model. METHODS Six F98 intracranial tumor bearing rats were imaged longitudinally 8, 11 and 14 days after tumor cell inoculation. Conductivity and mean diffusivity maps were generated using MREPT and Diffusion Tensor Imaging. These maps were co-registered with T2 -weighted images and volumes of interests (VOIs) were segmented from the normal brain, ventricles, edema, viable tumor, tumor rim, and tumor core regions. Longitudinal changes in conductivity and mean diffusivity (MD) values were compared in these regions. A correlation analysis was also performed between conductivity and mean diffusivity values. RESULTS The conductivity of ventricles, edematous area and tumor regions (tumor rim, viable tumor, tumor core) was significantly higher (P < .01) compared to the contralateral cortex. The conductivity of the tumor increased over time while MD from the tumor did not change. A marginal positive correlation was noted between conductivity and MD values for tumor rim and viable tumor, whereas this correlation was negative for the tumor core. CONCLUSION We demonstrate a novel contrast mechanism based on ionic concentration and mobility, which may aid in providing complementary information to water diffusion in probing the microenvironment of brain tumors.
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Affiliation(s)
- Clémentine Lesbats
- Centre for Preclinical ImagingDepartment of Molecular and Clinical Cancer MedicineUniversity of LiverpoolLiverpoolUK
| | - Nitish Katoch
- Department of Biomedical EngineeringKyung Hee UniversitySeoulSouth Korea
| | - Atul Singh Minhas
- Centre for Preclinical ImagingDepartment of Molecular and Clinical Cancer MedicineUniversity of LiverpoolLiverpoolUK
- School of EngineeringMacquarie UniversitySydneyNSWAustralia
| | - Arthur Taylor
- Centre for Preclinical ImagingDepartment of Molecular and Clinical Cancer MedicineUniversity of LiverpoolLiverpoolUK
| | - Hyung Joong Kim
- Department of Biomedical EngineeringKyung Hee UniversitySeoulSouth Korea
| | - Eung Je Woo
- Department of Biomedical EngineeringKyung Hee UniversitySeoulSouth Korea
| | - Harish Poptani
- Centre for Preclinical ImagingDepartment of Molecular and Clinical Cancer MedicineUniversity of LiverpoolLiverpoolUK
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30
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Lee MB, Jahng GH, Kim HJ, Kwon OI. High-frequency conductivity at Larmor-frequency in human brain using moving local window multilayer perceptron neural network. PLoS One 2021; 16:e0251417. [PMID: 34014939 PMCID: PMC8136747 DOI: 10.1371/journal.pone.0251417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Accepted: 04/26/2021] [Indexed: 11/18/2022] Open
Abstract
Magnetic resonance electrical properties tomography (MREPT) aims to visualize the internal high-frequency conductivity distribution at Larmor frequency using the B1 transceive phase data. From the magnetic field perturbation by the electrical field associated with the radiofrequency (RF) magnetic field, the high-frequency conductivity and permittivity distributions inside the human brain have been reconstructed based on the Maxwell’s equation. Starting from the Maxwell’s equation, the complex permittivity can be described as a second order elliptic partial differential equation. The established reconstruction algorithms have focused on simplifying and/or regularizing the elliptic partial differential equation to reduce the noise artifact. Using the nonlinear relationship between the Maxwell’s equation, measured magnetic field, and conductivity distribution, we design a deep learning model to visualize the high-frequency conductivity in the brain, directly derived from measured magnetic flux density. The designed moving local window multi-layer perceptron (MLW-MLP) neural network by sliding local window consisting of neighboring voxels around each voxel predicts the high-frequency conductivity distribution in each local window. The designed MLW-MLP uses a family of multiple groups, consisting of the gradients and Laplacian of measured B1 phase data, as the input layer in a local window. The output layer of MLW-MLP returns the conductivity values in each local window. By taking a non-local mean filtering approach in the local window, we reconstruct a noise suppressed conductivity image while maintaining spatial resolution. To verify the proposed method, we used B1 phase datasets acquired from eight human subjects (five subjects for training procedure and three subjects for predicting the conductivity in the brain).
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Affiliation(s)
- Mun Bae Lee
- Department of Mathematics, Konkuk University, Seoul, Korea
| | - Geon-Ho Jahng
- Department of Radiology, Kyung Hee University Hospital at Gangdong, College of Medicine, Kyung Hee University, Seoul, Korea
| | - Hyung Joong Kim
- Department of Biomedical Engineering, Kyung Hee University, Seoul, Korea
| | - Oh-In Kwon
- Department of Mathematics, Konkuk University, Seoul, Korea
- * E-mail:
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31
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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.
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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
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32
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Lv Y, Luo H. A New Method of Haemorrhagic Stroke Detection Via Deep Magnetic Induction Tomography. Front Neurosci 2021; 15:659095. [PMID: 34025343 PMCID: PMC8131561 DOI: 10.3389/fnins.2021.659095] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 04/06/2021] [Indexed: 11/25/2022] Open
Abstract
Hemorrhage imaging is one of the most common applications of magnetic induction tomography (MIT). Depth and the mass of stroke stimulated (MSS) are the most important issues that need to be solved for this application. Transcranial magnetic stimulation (TMS) is a technique belonging to the deep brain stimulation (DBS) field, which aims at overcoming human diseases such as depression. TMS coils, namely, circular, figure-8, and H-coils, play an important role in TMS. Among these, H-coils individually focus on the issues of achieving effective stimulation of deep region. MIT and TMS mechanisms are similar. Herein, for the first time, improved TMS coils, including figure-8 and H-coils, are applied as MIT excitation coils to study the possibility of achieving the mass of stroke stimulated and deep detection through MIT. In addition, the configurations of the detection coils are varied to analyze their influence and determine the optimal coils array. Finally, MIT is used to detect haemorrhagic stroke occurring in humans, and the application of deep MIT to the haemorrhagic stroke problem is computationally explored. Results show that among the various coils, the improved H-coils have MSS and depth characteristics that enable the detection of deep strokes through MIT. Although the detecting depth of the figure-8 coil is weaker, its surface signal is good. The deep MIT technique can be applied to haemorrhagic detection, providing a critical base for deeper research.
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Affiliation(s)
- Yi Lv
- College of Electronic and Information Engineering, Shenyang Aerospace University, Shenyang, China
| | - Haijun Luo
- College of Physics and Electronic Engineering, Chongqing Normal University, Chongqing, China
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33
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Huang Y, Omar M, Tian W, Lopez-Schier H, Westmeyer GG, Chmyrov A, Sergiadis G, Ntziachristos V. Noninvasive visualization of electrical conductivity in tissues at the micrometer scale. SCIENCE ADVANCES 2021; 7:eabd1505. [PMID: 33980478 PMCID: PMC8115913 DOI: 10.1126/sciadv.abd1505] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Accepted: 03/23/2021] [Indexed: 06/12/2023]
Abstract
Despite its importance in regulating cellular or tissue function, electrical conductivity can only be visualized in tissue indirectly as voltage potentials using fluorescent techniques, or directly with radio waves. These either requires invasive procedures like genetic modification or suffers from limited resolution. Here, we introduce radio-frequency thermoacoustic mesoscopy (RThAM) for the noninvasive imaging of conductivity by exploiting the direct absorption of near-field ultrashort radio-frequency pulses to stimulate the emission of broadband ultrasound waves. Detection of ultrasound rather than radio waves enables micrometer-scale resolutions, over several millimeters of tissue depth. We confirm an imaging resolution of <30 μm in phantoms and demonstrate microscopic imaging of conductivity correlating to physical structures in 1- and 512-cell zebrafish embryos, as well as larvae. These results support RThAM as a promising method for high-resolution, label-free assessment of conductivity in tissues.
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Affiliation(s)
- Yuanhui Huang
- Institute for Biological and Medical Imaging (IBMI), Helmholtz Zentrum München, D-85764 Neuherberg, Germany
- Chair of Biological Imaging at the Central Institute for Translational Cancer Research (TranslaTUM), School of Medicine, Technical University of Munich, D-81675 Munich, Germany
| | - Murad Omar
- Institute for Biological and Medical Imaging (IBMI), Helmholtz Zentrum München, D-85764 Neuherberg, Germany
- Chair of Biological Imaging at the Central Institute for Translational Cancer Research (TranslaTUM), School of Medicine, Technical University of Munich, D-81675 Munich, Germany
| | - Weili Tian
- Research Unit Sensory Biology and Organogenesis, Helmholtz Zentrum München, D-85764 Neuherberg, Germany
| | - Hernán Lopez-Schier
- Research Unit Sensory Biology and Organogenesis, Helmholtz Zentrum München, D-85764 Neuherberg, Germany
| | - Gil Gregor Westmeyer
- Institute for Biological and Medical Imaging (IBMI), Helmholtz Zentrum München, D-85764 Neuherberg, Germany
- Institute of Developmental Genetics (IDG), Helmholtz Zentrum München, D-85764 Neuherberg, Germany
| | - Andriy Chmyrov
- Institute for Biological and Medical Imaging (IBMI), Helmholtz Zentrum München, D-85764 Neuherberg, Germany
- Chair of Biological Imaging at the Central Institute for Translational Cancer Research (TranslaTUM), School of Medicine, Technical University of Munich, D-81675 Munich, Germany
| | - George Sergiadis
- Institute for Biological and Medical Imaging (IBMI), Helmholtz Zentrum München, D-85764 Neuherberg, Germany
- Chair of Biological Imaging at the Central Institute for Translational Cancer Research (TranslaTUM), School of Medicine, Technical University of Munich, D-81675 Munich, Germany
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, 215163 Suzhou, China
| | - Vasilis Ntziachristos
- Institute for Biological and Medical Imaging (IBMI), Helmholtz Zentrum München, D-85764 Neuherberg, Germany.
- Chair of Biological Imaging at the Central Institute for Translational Cancer Research (TranslaTUM), School of Medicine, Technical University of Munich, D-81675 Munich, Germany
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34
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Suh J, Kim JH, Kim SY, Cho N, Kim DH, Kim R, Kim ES, Jang MJ, Ha SM, Lee SH, Chang JM, Moon WK. Noncontrast-Enhanced MR-Based Conductivity Imaging for Breast Cancer Detection and Lesion Differentiation. J Magn Reson Imaging 2021; 54:631-645. [PMID: 33894088 DOI: 10.1002/jmri.27655] [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: 01/13/2021] [Revised: 04/01/2021] [Accepted: 04/01/2021] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND There is increasing interest in noncontrast-enhanced MRI due to safety concerns for gadolinium contrast agents. PURPOSE To investigate the clinical feasibility of MR-based conductivity imaging for breast cancer detection and lesion differentiation. STUDY TYPE Prospective. SUBJECTS One hundred and ten women, with 112 known cancers and 17 benign lesions (biopsy-proven), scheduled for preoperative MRI. FIELD STRENGTH/SEQUENCE Non-fat-suppressed T2-weighted turbo spin-echo sequence (T2WI), dynamic contrast-enhanced MRI and diffusion-weighted imaging (DWI) at 3T. ASSESSMENT Cancer detectability on each imaging modality was qualitatively evaluated on a per-breast basis: the conductivity maps derived from T2WI were independently reviewed by three radiologists (R1-R3). T2WI, DWI, and pre-operative digital mammography were independently reviewed by three other radiologists (R4-R6). Conductivity and apparent diffusion coefficient (ADC) measurements (mean, minimum, and maximum) were performed for 112 cancers and 17 benign lesions independently by two radiologists (R1 and R2). Tumor size was measured from surgical specimens. STATISTICAL TESTS Cancer detection rates were compared using generalized estimating equations. Multivariable logistic regression analysis was performed to identify factors associated with cancer detectability. Discriminating ability of conductivity and ADC was evaluated by using the areas under the receiver operating characteristic curve (AUC). RESULTS Conductivity imaging showed lower cancer detection rates (20%-32%) compared to T2WI (62%-71%), DWI (85%-90%), and mammography (79%-88%) (all P < 0.05). Fatty breast on MRI (odds ratio = 11.8, P < 0.05) and invasive tumor size (odds ratio = 1.7, P < 0.05) were associated with cancer detectability of conductivity imaging. The maximum conductivity showed comparable ability to the mean ADC in discriminating between cancers and benign lesions (AUC = 0.67 [95% CI: 0.59, 0.75] vs. 0.84 [0.76, 0.90], P = 0.06 (R1); 0.65 [0.56, 0.73] vs. 0.82 [0.74, 0.88], P = 0.07 (R2)). DATA CONCLUSION Although conductivity imaging showed suboptimal performance in breast cancer detection, the quantitative measurement of conductivity showed the potential for lesion differentiation. EVIDENCE LEVEL 1 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- June Suh
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Jun-Hyeong Kim
- 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
| | - Nariya Cho
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Dong-Hyun Kim
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Rihyeon Kim
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Eun Sil Kim
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Myoung-Jin Jang
- Medical Research Collaborating Center, Seoul National University Hospital, Seoul, Republic of Korea
| | - Su Min Ha
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Su Hyun Lee
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Jung Min Chang
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Woo Kyung Moon
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
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Lee MB, Kim HJ, Kwon OI. Decomposition of high-frequency electrical conductivity into extracellular and intracellular compartments based on two-compartment model using low-to-high multi-b diffusion MRI. Biomed Eng Online 2021; 20:29. [PMID: 33766044 PMCID: PMC7993544 DOI: 10.1186/s12938-021-00869-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Accepted: 03/16/2021] [Indexed: 01/21/2023] Open
Abstract
Background As an object’s electrical passive property, the electrical conductivity is proportional to the mobility and concentration of charged carriers that reflect the brain micro-structures. The measured multi-b diffusion-weighted imaging (Mb-DWI) data by controlling the degree of applied diffusion weights can quantify the apparent mobility of water molecules within biological tissues. Without any external electrical stimulation, magnetic resonance electrical properties tomography (MREPT) techniques have successfully recovered the conductivity distribution at a Larmor-frequency. Methods This work provides a non-invasive method to decompose the high-frequency conductivity into the extracellular medium conductivity based on a two-compartment model using Mb-DWI. To separate the intra- and extracellular micro-structures from the recovered high-frequency conductivity, we include higher b-values DWI and apply the random decision forests to stably determine the micro-structural diffusion parameters. Results To demonstrate the proposed method, we conducted phantom and human experiments by comparing the results of reconstructed conductivity of extracellular medium and the conductivity in the intra-neurite and intra-cell body. The phantom and human experiments verify that the proposed method can recover the extracellular electrical properties from the high-frequency conductivity using a routine protocol sequence of MRI scan. Conclusion We have proposed a method to decompose the electrical properties in the extracellular, intra-neurite, and soma compartments from the high-frequency conductivity map, reconstructed by solving the electro-magnetic equation with measured B1 phase signals.
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Affiliation(s)
- Mun Bae Lee
- Department of Mathematics, Konkuk University, 05029, Seoul, South Korea
| | - Hyung Joong Kim
- Department of Biomedical Engineering, Kyung Hee University, 02447, Seoul, South Korea
| | - Oh In Kwon
- Department of Mathematics, Konkuk University, 05029, Seoul, South Korea.
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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.
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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
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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.
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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.
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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]
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Mandija S, Petrov PI, Vink JJT, Neggers SFW, van den Berg CAT. Brain Tissue Conductivity Measurements with MR-Electrical Properties Tomography: An In Vivo Study. Brain Topogr 2021; 34:56-63. [PMID: 33289858 PMCID: PMC7803705 DOI: 10.1007/s10548-020-00813-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2020] [Accepted: 11/28/2020] [Indexed: 01/19/2023]
Abstract
First in vivo brain conductivity reconstructions using Helmholtz MR-Electrical Properties Tomography (MR-EPT) have been published. However, a large variation in the reconstructed conductivity values is reported and these values differ from ex vivo conductivity measurements. Given this lack of agreement, we performed an in vivo study on eight healthy subjects to provide reference in vivo brain conductivity values. MR-EPT reconstructions were performed at 3 T for eight healthy subjects. Mean conductivity and standard deviation values in the white matter, gray matter and cerebrospinal fluid (σWM, σGM, and σCSF) were computed for each subject before and after erosion of regions at tissue boundaries, which are affected by typical MR-EPT reconstruction errors. The obtained values were compared to the reported ex vivo literature values. To benchmark the accuracy of in vivo conductivity reconstructions, the same pipeline was applied to simulated data, which allow knowledge of ground truth conductivity. Provided sufficient boundary erosion, the in vivo σWM and σGM values obtained in this study agree for the first time with literature values measured ex vivo. This could not be verified for the CSF due to its limited spatial extension. Conductivity reconstructions from simulated data verified conductivity reconstructions from in vivo data and demonstrated the importance of discarding voxels at tissue boundaries. The presented σWM and σGM values can therefore be used for comparison in future studies employing different MR-EPT techniques.
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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.
- Division of Imaging & Oncology, Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands.
| | - Petar I Petrov
- Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
| | - Jord J T Vink
- Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
| | - Sebastian F W Neggers
- Rudolf Magnus Institute of Neuroscience, 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
- Division of Imaging & Oncology, Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
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Huang S, Cai W, Han S, Lin Y, Wang Y, Chen F, Shao G, Liu Y, Yu X, Cai Z, Zou Z, Yao S, Wang Q, Li Z. Differences in the dielectric properties of various benign and malignant thyroid nodules. Med Phys 2020; 48:760-769. [PMID: 33119125 DOI: 10.1002/mp.14562] [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: 01/30/2020] [Revised: 08/28/2020] [Accepted: 10/14/2020] [Indexed: 12/26/2022] Open
Abstract
PURPOSE This experiment was conducted to investigate the dielectric properties of different types of thyroid nodules. Our goal was to find a simple and fast method to detect thyroid diseases at different stages from the dielectric properties of thyroid nodules. METHODS We used the open-ended coaxial line method to measure the dielectric permittivities of thyroid tissues from 155 patients at frequencies ranging from 1 to 4000 MHz. Tissues that were investigated included normal thyroid tissue and benign and malignant thyroid nodules (nodular goiter, follicular adenoma, papillary carcinoma, and follicular carcinoma), as determined from pathological reports. Differences in dielectric properties were measured between each nodule and the surrounding 1 cm of tissue. RESULTS The analysis results revealed that the dielectric permittivity and conductivity values were positively correlated with the degree of malignancy of the nodule (normal < benign < malignant; all differences P < 0.05). This was more obvious at frequencies within 20~70 MHz, following the order normal tissue < nodular goiter < follicular adenoma < papillary carcinoma < follicular carcinoma. A significant difference (P < 0.05) in dielectric permittivity and conductivity was found when comparing these nodules with the surrounding 1 cm of tissue. CONCLUSIONS Normal, benign, and malignant nodules were successfully distinguished from one another, and dielectric permittivity was found to be a more sensitive parameter than conductivity. In particular, different disease types can be distinguished at a stimulation frequency of 20~70 MHz, which shows that dielectric properties have application prospects for the detection and diagnosis of cancer. At the same time, the dielectric parameter differences between the surrounding 1 cm of tissue and the diseased nodule can distinguish the tumor and its surrounding tissues in real time during surgery to determine the tumor boundary.
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Affiliation(s)
- Shengyi Huang
- Department of General Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510280, China
| | - Weizhen Cai
- Department of General Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510280, China
| | - Shuai Han
- Department of General Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510280, China
| | - Yu Lin
- Department of Pathology, Zhujiang Hospital, Southern Medical University, Guangzhou, 510280, China
| | - Yu Wang
- Department of Pathology, Zhujiang Hospital, Southern Medical University, Guangzhou, 510280, China
| | - Fei Chen
- Department of Thyroid Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510280, China
| | - Guoli Shao
- Special Medical Service Center, Zhujiang Hospital, Southern Medical University, Guangzhou, 510280, China
| | - Yonghong Liu
- School of Biomedical Engineering, Southern Medical University, Guangzhou, 510515, China
| | - Xuefei Yu
- School of Biomedical Engineering, Southern Medical University, Guangzhou, 510515, China
| | - Zhai Cai
- Department of General Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510280, China
| | - Zenan Zou
- Department of General Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510280, China
| | - Shun Yao
- Department of General Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510280, China
| | - Qiaohui Wang
- Department of General Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510280, China
| | - Zhou Li
- Department of General Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510280, China
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Deng G, Cai L, Feng J, Duan S, Zhang P, Xin SX. Reliable Method for Fabricating Tissue-Mimicking Materials With Designated Relative Permittivity and Conductivity at 128 MHz. Bioelectromagnetics 2020; 42:86-94. [PMID: 33305868 DOI: 10.1002/bem.22303] [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: 05/26/2019] [Accepted: 10/10/2020] [Indexed: 02/01/2023]
Abstract
Artificial materials that can simultaneously mimic the relative permittivity and conductivity of various human tissues are usually used in medical applications. However, the method of precisely designing these materials with designated values of both relative permittivity and conductivity at 3 T MRI resonance frequency is lacking. In this study, a reliable method is established to determine the compositions of artificial dielectric materials with designated relative permittivity and conductivity at 128 MHz. Sixty dielectric materials were produced using oil, sodium chloride, gelatin, and deionized water as the main raw materials. The dielectric properties of these dielectric materials were measured using the open-ended coaxial line method at 128 MHz. Nonlinear least-squares Marquardt-Levenberg algorithm was used to obtain the formula, establishing the relationship between the compositions of the dielectric materials and their dielectric properties at 128 MHz. The dielectric properties of the blood, gall bladder, muscle, skin, lung, and bone at 128 MHz were selected to verify the reliability of the obtained formula. For the obtained formula, the coefficient of determination and the expanded uncertainties with a coverage factor of k = 2 were 0.991% and 4.9% for relative permittivity and 0.992% and 6.4% for conductivity. For the obtained artificial materials measured using the open-ended coaxial line method, the maximal difference of relative permittivity and conductivity were 1.0 and 0.02 S/m, respectively, with respect to the designated values. In conclusion, the compositions of tissue-mimicking material can be quickly determined after the establishment of the formulas with the expanded uncertainties of less than 10%. Bioelectromagnetics. 2021;42:86-94. © 2020 Bioelectromagnetics Society.
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Affiliation(s)
- Guanhua Deng
- Department of Oncology, Guangdong Sanjiu Brain Hospital, Guangzhou, China
| | - Linbo Cai
- Department of Oncology, Guangdong Sanjiu Brain Hospital, Guangzhou, China
| | - Jian Feng
- Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China
| | - Song Duan
- Department of Radiation Oncology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China
| | - Ping Zhang
- Department of Oncology, Guangdong Sanjiu Brain Hospital, Guangzhou, China
| | - Sherman X Xin
- School of Medicine, South China University of Technology, Guangzhou, China
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42
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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.
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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
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Jahng GH, Lee MB, Kim HJ, Je Woo E, Kwon OI. Low-frequency dominant electrical conductivity imaging of in vivo human brain using high-frequency conductivity at Larmor-frequency and spherical mean diffusivity without external injection current. Neuroimage 2020; 225:117466. [PMID: 33075557 DOI: 10.1016/j.neuroimage.2020.117466] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2019] [Revised: 08/24/2020] [Accepted: 10/12/2020] [Indexed: 10/23/2022] Open
Abstract
Diffusion weighted imaging based on random Brownian motion of water molecules within a voxel provides information on the micro-structure of biological tissues through water molecule diffusivity. As the electrical conductivity is primarily determined by the concentration and mobility of ionic charge carriers, the macroscopic electrical conductivity of biological tissues is also related to the diffusion of electrical ions. This paper aims to investigate the low-frequency electrical conductivity by relying on a pre-defined biological model that separates the brain into the intracellular (restricted) and extracellular (hindered) compartments. The proposed method uses B1 mapping technique, which provides a high-frequency conductivity distribution at Larmor frequency, and the spherical mean technique, which directly estimates the microscopic tissue structure based on the water molecule diffusivity and neurite orientation distribution. The total extracellular ion concentration, which is separated from the high-frequency conductivity, is recovered using the estimated diffusivity parameters and volume fraction in each compartment. We propose a method to reconstruct the low-frequency dominant conductivity tensor by taking into consideration the extracted extracellular diffusion tensor map and the reconstructed electrical parameters. To demonstrate the reliability of the proposed method, we conducted two phantom experiments. The first one used a cylindrical acrylic cage filled with an agar in the background region and four anomalies for the effect of ion concentration on the electrical conductivity. The other experiment, in which the effect of ion mobility on the conductivity was verified, used cell-like materials with thin insulating membranes suspended in an electrolyte. Animal and human brain experiments were conducted to visualize the low-frequency dominant conductivity tensor images. The proposed method using a conventional MRI scanner can predict the internal current density map in the brain without directly injected external currents.
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Affiliation(s)
- Geon-Ho Jahng
- Department of Radiology, Kyung Hee University Hospital at Gangdong, College of Medicine, Kyung Hee University, Dongnam-ro, Gangdong-gu, Seoul 05278, Republic of Korea
| | - Mun Bae Lee
- Department of Mathematics, Konkuk University, Neungdong-ro, Gwangjin-gu, Seoul 05029, Republic of Korea
| | - Hyung Joong Kim
- Department of Biomedical Engineering, Kyung Hee University, Seoul 02447, Republic of Korea
| | - Eung Je Woo
- Department of Biomedical Engineering, Kyung Hee University, Seoul 02447, Republic of Korea
| | - Oh-In Kwon
- Department of Mathematics, Konkuk University, Neungdong-ro, Gwangjin-gu, Seoul 05029, Republic of Korea.
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Accelerating quantitative MR imaging with the incorporation of B1 compensation using deep learning. Magn Reson Imaging 2020; 72:78-86. [DOI: 10.1016/j.mri.2020.06.011] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Revised: 05/20/2020] [Accepted: 06/13/2020] [Indexed: 11/21/2022]
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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.
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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
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Kim JW, Kim HB, Hur YH, Choi BK, Katoch N, Park JA, Kim HJ, Woo EJ. MR-Based Electrical Conductivity Imaging of Liver Fibrosis in an Experimental Rat Model. J Magn Reson Imaging 2020; 53:554-563. [PMID: 32614131 DOI: 10.1002/jmri.27275] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2020] [Revised: 06/13/2020] [Accepted: 06/16/2020] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Liver fibrosis is characterized by the excessive accumulation of extracellular matrix proteins. Electrical conductivity imaging at low frequency can provide novel contrast because the contrast mechanisms originate from the changes in the concentration and mobility of ions in the extracellular space. PURPOSE To evaluate the feasibility of an MR-based electrical conductivity imaging that can detect the changes in a tissue condition associated with the progression of liver fibrosis. STUDY TYPE Prospective phantom and animal study. ANIMAL MODEL Fibrosis was induced by weekly intraperitoneal injection of dimethylnitrosamine (DMN) in 45 male Sprague-Dawley rats. FIELD STRENGTH/SEQUENCE 3T MRI with a multispin-echo pulse sequence. ASSESSMENT The percentage change of conductivity (Δσ, %) in the same region-of-interest (ROI) was calculated from the DMN-treated rats based on the values of the normal control rats. The percentage change was also calculated between the ROIs in each DMN-treated group. STATISTICAL TESTS One-way analysis of variance (ANOVA) and a two-sample t-test were performed. RESULTS Liver tissues in normal control rats showed a uniform conductivity distribution of 56.6 ± 4.4 (mS/m). In rats more than 5 weeks after induction, the fibrous region showed an increased conductivity of ≥12% compared to that of the corresponding normal control rats. From regional comparisons in the same liver, the fibrous region showed an increased conductivity of ≥11% compared to the opposite, less induced region of rats more than 5 weeks after induction. Liver samples from the fibrous region represent tissue damages such as diffuse centrilobular congestion with marked dilatation of central veins from the histological findings. Immunohistochemistry revealed significant levels of attenuated fibrosis and increased inflammatory response. DATA CONCLUSION The increased conductivity in the fibrous region is related to the changes of the extracellular space. The correlation between the collagen deposition and conductivity changes is essential for future clinical studies. Level of Evidence 2 Technical Efficacy Stage 2 J. MAGN. RESON. IMAGING 2021;53:554-563.
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Affiliation(s)
- Jin Woong Kim
- Department of Radiology, Chosun University Hospital and Chosun University College of Medicine, Gwangju, 61453, Korea
| | - Hyun Bum Kim
- Department of East-West Medical Science, Kyung Hee University, Yongin, 17104, Korea
| | - Young Hoe Hur
- Department of Hepato-Biliary-Pancreas Surgery, Chonnam National University Hwasun Hospital and Chonnam National University Medical School, Gwangju, 61469, Korea
| | - Bup Kyung Choi
- Department of Biomedical Engineering, Kyung Hee University, Seoul, 02447, Korea
| | - Nitish Katoch
- Department of Biomedical Engineering, Kyung Hee University, Seoul, 02447, Korea
| | - Ji Ae Park
- Division of Applied RI, Korea Institute of Radiological & Medical Science, Seoul, 01812, Korea
| | - Hyung Joong Kim
- Department of Biomedical Engineering, Kyung Hee University, Seoul, 02447, Korea
| | - Eung Je Woo
- Department of Biomedical Engineering, Kyung Hee University, Seoul, 02447, Korea
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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.
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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
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Extracellular electrical conductivity property imaging by decomposition of high-frequency conductivity at Larmor-frequency using multi-b-value diffusion-weighted imaging. PLoS One 2020; 15:e0230903. [PMID: 32267858 PMCID: PMC7141654 DOI: 10.1371/journal.pone.0230903] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2020] [Accepted: 03/11/2020] [Indexed: 01/03/2023] Open
Abstract
Magnetic resonance electrical properties tomography (MREPT) uses the B1 mapping technique to provide the high-frequency conductivity distribution at Larmor frequency that simultaneously reflects the intracellular and extracellular effects. In biological tissues, the electrical conductivity can be described as the concentration and mobility of charge carriers. For the water molecule diffusivity, diffusion weighted imaging (DWI) measures the random Brownian motion of water molecules within biological tissues. The DWI data can quantitatively access the mobility of microscopic water molecules within biological tissues. By measuring multi-b-value DWI data and the recovered high-frequency conductivity at Larmor frequency, we propose a new method to decompose the conductivity into the total ion concentration and mobility in the extracellular space (ECS) within a routinely applicable MR scan time. Using the measured multi-b-value DWI data, a constrained compartment model is designed to estimate the extracellular volume fraction and extracellular mean diffusivity. With the extracted extracellular volume fraction and water molecule diffusivity, we directly reconstruct the low-frequency electrical properties including the extracellular mean conductivity and extracellular conductivity tensor. To demonstrate the proposed method by comparing the ion concentration and the ion mobility, we conducted human experiments for the proposed low-frequency conductivity imaging. Human experiments verify that the proposed method can recover the low-frequency electrical properties using a conventional MRI scanner.
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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.
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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
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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.
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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
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