Electrical properties based B1+ prediction for electrical properties tomography reconstruction evaluation

Purpose In MR electrical properties tomography (EPT), conductivity and permittivity are reconstructed from MR measurements. However, depending on the reconstruction method, reconstructed electrical properties (EPs) show large variability in vivo, reducing confidence in the reconstructed values for c...

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Published in:Magnetic resonance in medicine Vol. 94; no. 3; pp. 1269 - 1283
Main Authors: Meerbothe, Thierry G., Jung, Kyu‐Jin, Cui, Chuanjiang, Kim, Dong‐Hyun, Berg, Cornelis A. T., Mandija, Stefano
Format: Journal Article
Language:English
Published: Hoboken Wiley Subscription Services, Inc 01.09.2025
John Wiley and Sons Inc
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ISSN:0740-3194, 1522-2594
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Abstract Purpose In MR electrical properties tomography (EPT), conductivity and permittivity are reconstructed from MR measurements. However, depending on the reconstruction method, reconstructed electrical properties (EPs) show large variability in vivo, reducing confidence in the reconstructed values for clinical application in practice. To overcome this problem we present a method to evaluate the reconstructed EPs using a physics‐based B1+$$ {\mathrm{B}}_1^{+} $$ estimation model. Methods A physics‐based method using a finite difference based recurrent relation is used to estimate the B1+$$ {\mathrm{B}}_1^{+} $$ field from a set of given EPs and the boundary of the measured B1+$$ {\mathrm{B}}_1^{+} $$ field. Reconstructed EPs can be evaluated by comparing the estimated B1+$$ {\mathrm{B}}_1^{+} $$ field with the measured B1+$$ {\mathrm{B}}_1^{+} $$ field. The method was first validated in simulations and afterward tested using MRI data from phantoms and in vivo. Results The simulation experiments show that the B1+$$ {\mathrm{B}}_1^{+} $$ field can be accurately estimated, within 90 s for a typical brain at 1 mm3 isotropic resolution, when correct EPs are used as input. When incorrect EPs are used as input the estimated B1+$$ {\mathrm{B}}_1^{+} $$ fields shows differences with the measured B1+$$ {\mathrm{B}}_1^{+} $$ fields. These differences directly correspond to the errors in the underlying EPs, enabling detection of errors in the reconstructions. The results obtained in MRI experiments using phantoms and in vivo show the applicability of the method in practice. Conclusion With the proposed method, B1+$$ {\mathrm{B}}_1^{+} $$ fields can be accurately estimated from EPs. This approach can be used to evaluate EPT reconstructions and consequently gain more confidence in reconstructed EPs values in vivo.
AbstractList Purpose In MR electrical properties tomography (EPT), conductivity and permittivity are reconstructed from MR measurements. However, depending on the reconstruction method, reconstructed electrical properties (EPs) show large variability in vivo, reducing confidence in the reconstructed values for clinical application in practice. To overcome this problem we present a method to evaluate the reconstructed EPs using a physics‐based B1+$$ {\mathrm{B}}_1^{+} $$ estimation model. Methods A physics‐based method using a finite difference based recurrent relation is used to estimate the B1+$$ {\mathrm{B}}_1^{+} $$ field from a set of given EPs and the boundary of the measured B1+$$ {\mathrm{B}}_1^{+} $$ field. Reconstructed EPs can be evaluated by comparing the estimated B1+$$ {\mathrm{B}}_1^{+} $$ field with the measured B1+$$ {\mathrm{B}}_1^{+} $$ field. The method was first validated in simulations and afterward tested using MRI data from phantoms and in vivo. Results The simulation experiments show that the B1+$$ {\mathrm{B}}_1^{+} $$ field can be accurately estimated, within 90 s for a typical brain at 1 mm3 isotropic resolution, when correct EPs are used as input. When incorrect EPs are used as input the estimated B1+$$ {\mathrm{B}}_1^{+} $$ fields shows differences with the measured B1+$$ {\mathrm{B}}_1^{+} $$ fields. These differences directly correspond to the errors in the underlying EPs, enabling detection of errors in the reconstructions. The results obtained in MRI experiments using phantoms and in vivo show the applicability of the method in practice. Conclusion With the proposed method, B1+$$ {\mathrm{B}}_1^{+} $$ fields can be accurately estimated from EPs. This approach can be used to evaluate EPT reconstructions and consequently gain more confidence in reconstructed EPs values in vivo.
Purpose In MR electrical properties tomography (EPT), conductivity and permittivity are reconstructed from MR measurements. However, depending on the reconstruction method, reconstructed electrical properties (EPs) show large variability in vivo, reducing confidence in the reconstructed values for clinical application in practice. To overcome this problem we present a method to evaluate the reconstructed EPs using a physics‐based B1+$$ {\mathrm{B}}_1^{+} $$ estimation model. Methods A physics‐based method using a finite difference based recurrent relation is used to estimate the B1+$$ {\mathrm{B}}_1^{+} $$ field from a set of given EPs and the boundary of the measured B1+$$ {\mathrm{B}}_1^{+} $$ field. Reconstructed EPs can be evaluated by comparing the estimated B1+$$ {\mathrm{B}}_1^{+} $$ field with the measured B1+$$ {\mathrm{B}}_1^{+} $$ field. The method was first validated in simulations and afterward tested using MRI data from phantoms and in vivo. Results The simulation experiments show that the B1+$$ {\mathrm{B}}_1^{+} $$ field can be accurately estimated, within 90 s for a typical brain at 1 mm3 isotropic resolution, when correct EPs are used as input. When incorrect EPs are used as input the estimated B1+$$ {\mathrm{B}}_1^{+} $$ fields shows differences with the measured B1+$$ {\mathrm{B}}_1^{+} $$ fields. These differences directly correspond to the errors in the underlying EPs, enabling detection of errors in the reconstructions. The results obtained in MRI experiments using phantoms and in vivo show the applicability of the method in practice. Conclusion With the proposed method, B1+$$ {\mathrm{B}}_1^{+} $$ fields can be accurately estimated from EPs. This approach can be used to evaluate EPT reconstructions and consequently gain more confidence in reconstructed EPs values in vivo.
Author Jung, Kyu‐Jin
Berg, Cornelis A. T.
Meerbothe, Thierry G.
Mandija, Stefano
Cui, Chuanjiang
Kim, Dong‐Hyun
AuthorAffiliation 1 Department of Radiotherapy, Division of Imaging and Oncology University Medical Center Utrecht Utrecht The Netherlands
2 Computational Imaging Group for MR Therapy and Diagnostics, Center for Image Sciences University Medical Center Utrecht Utrecht The Netherlands
3 Department of Electrical and Electronic Engineering Yonsei University Seoul Republic of Korea
AuthorAffiliation_xml – name: 3 Department of Electrical and Electronic Engineering Yonsei University Seoul Republic of Korea
– name: 2 Computational Imaging Group for MR Therapy and Diagnostics, Center for Image Sciences University Medical Center Utrecht Utrecht The Netherlands
– name: 1 Department of Radiotherapy, Division of Imaging and Oncology University Medical Center Utrecht Utrecht The Netherlands
Author_xml – sequence: 1
  givenname: Thierry G.
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  surname: Meerbothe
  fullname: Meerbothe, Thierry G.
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  organization: University Medical Center Utrecht
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  givenname: Kyu‐Jin
  orcidid: 0000-0003-2842-1707
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  givenname: Chuanjiang
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Snippet Purpose In MR electrical properties tomography (EPT), conductivity and permittivity are reconstructed from MR measurements. However, depending on the...
Purpose In MR electrical properties tomography (EPT), conductivity and permittivity are reconstructed from MR measurements. However, depending on the...
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StartPage 1269
SubjectTerms Computer Processing and Modeling
conductivity
confidence
Electrical properties
electrical properties tomography
Electrical resistivity
Error detection
finite differences
Image reconstruction
In vivo methods and tests
Magnetic resonance imaging
Tomography
Title Electrical properties based B1+ prediction for electrical properties tomography reconstruction evaluation
URI https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fmrm.30520
https://www.proquest.com/docview/3229052669
https://pubmed.ncbi.nlm.nih.gov/PMC12202738
Volume 94
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