Evidence map›Paper›PMID 41795132›Full record

ReviewJournal of magnetic resonance imaging : JMRI2026

Clinical Applications of Electrical Conductivity Imaging Using MRI.

Stefano Mandija, Khin Khin Tha, Nitish Katoch, Cihan Göksu, Ulrich Katscher, Rosalind Sadleir, Kyu-Jin Jung, Jierong Luo, Ilias I Giannakopoulos, Dong-Hyun Kim and 5 more

Abstract readReview
In one paragraph

Review in Journal of magnetic resonance imaging : JMRI, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Stefano MandijaComputational Imaging Group for MR Therapy and Diagnostic, Department of Radiotherapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands.ORCID 0000-0002-4612-5509
Khin Khin ThaGlobal Center for Biomedical Science and Engineering, Hokkaido University Faculty of Medicine, Sapporo, Japan.ORCID 0000-0002-9072-4509
Nitish KatochPhilips Healthcare, Seoul, Republic of Korea.
Cihan GöksuDepartment of Electrical and Electronics Engineering, İzmir Institute of Technology, Izmir, Turkey.
Ulrich KatscherPhilips Innovative Technologies, Hamburg, Germany.ORCID 0000-0003-1379-1115
Rosalind SadleirSchool of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona, USA.
Kyu-Jin JungDepartment of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea.
Jierong LuoDepartment of Medical Physics and Biomedical Engineering, University College London, London, UK.
Ilias I GiannakopoulosBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA.ORCID 0000-0003-2180-5898
Dong-Hyun KimDepartment of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea.ORCID 0000-0002-6717-7770
Karin ShmueliDepartment of Medical Physics and Biomedical Engineering, University College London, London, UK.
Riccardo LattanziBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA.
Yusuf Ziya IderDepartment of Biomedical Engineering, Baskent University, Ankara, Turkey.
Axel ThielscherDepartment of Health Technology, Technical University of Denmark, Kgs. Lyngby, Denmark.
Cornelis van den BergComputational Imaging Group for MR Therapy and Diagnostic, Department of Radiotherapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands.

Funding

Open-Source Software Tools for Rapid Radiofrequency Coil Modeling and Simulation in MRIK99EB035163 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI GIANNAKOPOULOS, ILIAS · 2024 to 2025
$233k
European Partnership on Metrology, European Union's Horizon Europe Research and Innovation Programme 24DIT01German Research Foundation 1330/6-1German Research Foundation 1330/7-1German Research Foundation 5429/1JSPS KAKENHI 17K10390JSPS KAKENHI 20K12590JSPS KAKENHI 24K15693JSPS KAKENHI 26461817Lundbeck Foundation R313-2019-622NIH HHS K99 EB035163
6 · The paper itself

Abstract

Magnetic resonance imaging (MRI) has emerged as a noninvasive technique for probing the electrical properties of biological tissues: electrical conductivity and relative permittivity. This review focuses on the electrical conductivity and provides a comprehensive overview of applications across both low- and high-frequency regimes. At low frequencies (below 1 MHz), conductivity mapping primarily reflects tissue microstructure and ionic composition. In contrast, at high frequencies (around 100 MHz), tissue conductivity primarily reflects ionic composition. First, we summarize the theoretical foundations, technical developments, and reconstruction algorithms that underpin conductivity imaging, highlighting advances in magnetic resonance electrical impedance tomography, current density imaging, and electrical properties tomography. The main part of the article discusses preclinical and clinical applications, demonstrating the potential and possible roles of conductivity imaging in clinical settings, along with current challenges and emerging applications. Finally, we outline future directions toward integrating conductivity imaging into routine MRI protocols, with the potential to enhance diagnostic precision and therapeutic monitoring. EVIDENCE LEVEL: 1. TECHNICAL EFFICACY: Stage 3.

Indexed as

Electric ConductivityMagnetic Resonance ImagingAlgorithmsAnimalsElectric ImpedanceHumansImage Processing, Computer-AssistedTomographyconductivity MRIcurrent density imagingelectrical impedance tomographyelectrical properties tomographyMR‐EPT

Identifiers

PMID41795132
PMCPMC13066538

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.