Zhongzheng He¹, Martin Doguet¹, Paul Soullié¹, Paulo Loureiro de Sousa², Pauline Lefebvre¹, and Freddy Odille^1,3
1IADI U1254, INSERM, Université de Lorraine, Nancy, France, ²ICube, Université de Strasbourg, CNRS, Strasbourg, France, ³CIC-IT 1433, CHRU Nancy, INSERM, Université de Lorraine, Nancy, France

Many MR-EPT reconstruction methods have been published, however, there is a lack of comparative experiments to verify the reconstructed electrical properties (EP) maps. In this work, we compared and validated the phase-based (PB), complex-image-based (CIB), and their simplified methods with ground truth vector network analyzer measurements on different conductivity phantoms. After serval comparative experiment repetitions, the complex-image-based method by Soullié et al.[1] was the most consistent to the VNA ground truth measurements. The proposed setup can be used to compare other MR-EPT reconstruction methods.

Ilias Giannakopoulos^1,2, Jose Seralles³, Jan Paska^1,2, Georgy Guryev³, Carlotta Ianniello^1,2, Luca Daniel³, Jacob White³, Ryan Brown^1,2,4, Daniel Sodickson^1,2,4, and Riccardo Lattanzi^1,2,4
1Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States, ²The Bernard and Irene Schwartz Center for Biomedical Imaging (CBI), Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States, ³Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, United States, ⁴Vilcek Institute of Graduate Biomedical Sciences, New York University Grossman School of Medicine, New York, NY, United States

Global Maxwell Tomography (GMT) is an inverse scattering technique that estimates electrical properties (EP) from magnetic resonance measurements. The original GMT relies on an approximation of the incident fields, which is not accurate for experiments, especially in-vivo. We propose a new GMT formulation, based on the volume-surface integral equation (VSIE) method, where we implicitly re-estimate the incident fields accounting for the updated EP in every GMT iteration. We show average EP reconstruction error below 8% for a uniform phantom experiment and below 10% for a simulation experiment with a heterogeneous head model and realistic SNR.

Alessandro Arduino¹, Stefano Mandija^2,3, Francesca Pennecchi¹, Cornelis A. T. Van Den Berg^2,3, and Luca Zilberti^1
1Istituto Nazionale di Ricerca Metrologica (INRiM), Torino, Italy, ²Department of Radiotherapy, University Medical Center Utrecht, Utrecht, Netherlands, ³Computational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, Netherlands

In this work, a procedure for the automatic selection of the optimal kernel size in Helmholtz-based electric properties tomography (MR-EPT) with phase-based approximation is presented and tested on experimental data acquired on a phantom with a 3 T MRI scanner. The procedure is exclusively based on the map of the transceive phase, making no assumptions on the data in addition to those used in the derivation of the Helmholtz-based MR-EPT technique. As a by-product, the approach provides a map indicating the reliability of the reconstructed electric conductivity pixel-by-pixel.

Santhosh Iyyakkunnel^1,2 and Oliver Bieri^1,2
1Department of Radiology, University Hospital Basel, Basel, Switzerland, ²Department of Biomedical Engineering, University of Basel, Basel, Switzerland

Conductivity mapping depends sensitively on the signal-to-noise ratio (SNR) of the transmit phase estimation. It is thus questionable, whether conductivity mapping can be performed at low field. Due to reduced off-resonances, however, a possible solution for the reduced SNR might be offered by balanced steady state free precession (bSSFP). Brain conductivity mapping with bSSFP was investigated at 0.55 T and appears to be feasible but besides SNR also the reduced curvature of the transmit field becomes challenging.

Chuanjiang Cui¹, Jun-Hyeong Kim¹, Kyu-Jin Jung¹, Jaeuk Yi¹, and Dong-Hyun Kim^1
1Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea, Republic of

Phase-based EPT algorithm is extremely sensitive to noise. Although many studies have investigated such as linear(Gaussian filter) or non-linear filter(TV norm) to cope with amplification, textured noise and staircasing effect still remain in phase image, which lead to conductivity error such as broadening boundary artifact or high std value in reconstructed conductivity maps. In this study, we propose a deep prior based denoising method, which achieve to not only suppress instability brought by noise amplification but reduce boundary error.

Safa Özdemir¹, Efe Ilicak¹, Lothar R. Schad¹, and Frank G. Zöllner^1,2
1Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany, ²Mannheim Institute for Intelligent Systems in Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany

Magnetic Resonance Electrical Properties Tomography (MREPT) technique is used to obtain conductivity (σ) and permittivity (ε), using phase of the B₁⁺ information. While spin echo and bSSFP based pulse sequences were shown to successfully obtain phase images, they are either very slow or suffer from artifacts and require multi-acquisitions. To overcome these limitations, in this work we investigate the use of spiral trajectory-based sequences in MREPT. Our results indicate that even for sub-second acquisition times, conductivity maps can be successfully acquired via spiral trajectory-based sequence, and therefore can improve the utility of MREPT techniques by shortening the acquisition time drastically.

Fróði Gregersen^1,2,3, Cihan Göksu^2,4, Hasan Eroğlu^1,2, Zhentao Zuo^3,5,6, Axel Thielscher^1,2, and Lars Hanson^1,2
1Section for Magnetic Resonance, DTU Health Tech, Technical University of Denmark, Kgs. Lyngby, Denmark, ²Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark, ³Sino-Danish College, University of Chinese Academy of Sciences, Beijing, China, ⁴High-Field Magnetic Resonance Center, Max-Planck-Institute for Biological Cybernetics, Tübingen, Germany, ⁵State Key Laboratory of Brain and Cognitive Science, Beijing MRI Center for Brain Research, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China, ⁶Center for Excellence in Brain and Science and Intelligence Technology, Chinese Academy of Sciences, Beijing, China

Magnetic resonance current density imaging (MRCDI) can measure the magnetic fields created in the human brain from currents injected via surface electrodes. Previous methods have demonstrated high sensitivity sufficient for low current strengths (~1 mA). However, they have also proven susceptible to physiological noise. Here we increase the temporal resolution of the method and thereby the robustness to physiological noise by using echo-planar imaging (EPI) for the acquisition. We show that the method produces reliable magnetic field measurements with an average sensitivity of 52 pT for a 2 minutes scan with 3 mm isotropic resolution.

Jessica A. Martinez¹, Alessandro Arduino¹, Kevin Moulin^2,3, Adriano Troia¹, Oriano Bottauscio¹, and Luca Zilberti^1
1Advanced Materials Metrology and Life Science, Istituto Nazionale di Ricerca Metrologica, Turin, Italy, ²CREATIS, Lyon, France, ³University Hospital of Saint-Etienne, Saint-Etienne, France

The feasibility of EPT to obtain electrical conductivity data during temperature increase was analyzed. Experiments were performed in two homogeneous phantoms with different saline concentrations during temperature increase.

Cihan Göksu^1,2, Klaus Scheffler^2,3, Fróði Gregersen^1,4,5, Hasan Hüseyin Eroğlu^1,4, Rahel Heule^2,3, Hartwig R. Siebner^1,6,7, Lars G. Hanson^1,4, and Axel Thielscher^1,4
1Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital, Amager and Hvidovre, Denmark, ²High-Field Magnetic Resonance Center, Max-Planck-Institute for Biological Cybernetics, Tübingen, Germany, ³Department of Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany, ⁴Section for Magnetic Resonance, DTU Health Tech, Technical University of Denmark, Kgs Lyngby, Denmark, ⁵Sino-Danish Center for Education and Research, Aarhus, Denmark, ⁶Department of Neurology, Copenhagen University Hospital, Bispebjerg, Denmark, ⁷Institute for Clinical Medicine, Faculty of Medical and Health Sciences, University of Copenhagen, Copenhagen, Denmark

Exact knowledge of current distributions induced by transcranial electrical stimulation (TES) in the brain is important for effective clinical use of TES. MRCDI uses MRI to measure the TES-induced magnetic fields for estimating the underlying current flow distributions. The estimation methods can benefit from highly sensitive volume MRCDI measurements at a high spatial resolution. Here, we advanced our 2D spoiled gradient-echo-based MRCDI method for a sparse volume acquisition by using simultaneous-multi-slice (SMS) acquisition. Our SMS strategy demonstrated 25% improvement in noise floors against 2D. We test the performance of our methods by phantom and human in-vivo experiments using cable-loop currents.

Maximilian Gram^1,2, Petra Albertova^1,2, Verena Schirmer², Martin Blaimer³, Matthias Gamer⁴, Martin J. Herrmann⁵, Peter Michael Jakob², and Peter Nordbeck^1,6
1Department of Internal Medicine I, University Hospital Würzburg, Würzburg, Germany, ²Experimental Physics 5, University of Würzburg, Würzburg, Germany, ³Magnetic Resonance and X-ray Imaging Department Fraunhofer IIS, Fraunhofer Institute for Integrated Circuits IIS, Würzburg, Germany, ⁴Department of Psychology, University of Würzburg, Würzburg, Germany, ⁵Center of Mental Health, Dept. of Psychiatry, Psychosomatics, and Psychotherapy, University Hospital Würzburg, Würzburg, Germany, ⁶Comprehensive Heart Failure Center (CHFC), University Hospital Würzburg, Würzburg, Germany

Resonant absorption during spin-lock preparation can be used to measure tiny oscillating magnetic fields acting as direct evidence of electrical neuronal activity. Different spin-locking techniques were compared with respect to their sensitivity in magnetic field detection. As a specialty, the oscillating magnetic fields were generated by the built-in gradient system in an offcenter slice. The spin-lock time was identified as the crucial parameter for the performance of NEMO (neuro-electro-magnetic-oscillations) detection, since minima and maxima in the signal amplitude emerged in phantom and in vivo experiments. Affirmative, the experimental results show an excellent agreement with simulation results.

Petra Albertova^1,2, Maximilian Gram^1,2, Verena Schirmer¹, Martin Blaimer³, Martin J. Herrmann⁴, Matthias Gamer⁵, Peter Nordbeck^2,6, and Peter Michael Jakob^1
1Experimental Physics 5, University of Würzburg, Würzburg, Germany, ²Department of Internal Medicine I, University Hospital Würzburg, Würzburg, Germany, ³Magnetic Resonance and X-ray Imaging Department, Fraunhofer IIS, Fraunhofer Institute for Integrated Circuits IIS, Würzburg, Germany, ⁴Center of Mental Health, Dept. of Psychiatry, Psychosomatics, and Psychotherapy, University Hospital of Würzburg, Würzburg, Germany, ⁵Department of Psychology, University of Würzburg, Würzburg, Germany, ⁶Comprehensive Heart Failure Center (CHFC), University Hospital Würzburg, Würzburg, Germany

Spin-lock based absorption of magnetic oscillations offers potential for direct detection of electrical neuronal activity. We propose a novel versatile validation and calibration technique which paves the way for emulation and quantification of biomagnetic fields. Using ultra-weak gradient waveforms, the method mimics brain activity and thus projects artificial fields onto the tissue under investigation. The method applicable for sequence validation or signal calibration was tested in phantom and in vivo experiments with the built-in gradient system providing sinusoidal field modulations down to 1 nT. It proved to be reliable and reproducible and hence can potentially enable quantification of biomagnetic fields.

Thierry G. Meerbothe^1,2, Sammy Florczak³, Peter R. S. Stijnman^1,2, Cornelis A. T. van den Berg^1,2, Riccardo Levato^3,4, and Stefano Mandija^1,2
1Department of Radiotherapy, Division of Imaging and Oncology, University Medical Center Utrecht, Utrecht, Netherlands, ²Computational Imaging Group for MR Diagnostics and Therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, Netherlands, ³Department of Orthopaedics, University Medical Center Utrecht, Utrecht, Netherlands, ⁴Department of Clinical Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, Netherlands

This work presents a semi-realistic and reusable 3D printed brain phantom to benchmark MR-Electrical-Properties-Tomography reconstruction methods. We show that the hollow compartments of this phantom can be refilled multiple times with different water-based solutions of known electrical properties, which are otherwise not available from in-vivo measurements. Additionally, these brain phantoms can be used inside electromagnetic simulation software, allowing for MR-EPT reconstructions in controlled, simulation settings. In this way, a database comprising of simulated and measured data using these brain models and corresponding 3D printed phantoms will be generated and shared for the first MR-EPT reconstruction challenge.

Björn Wieslander¹, Felicia Seemann², Ahsan Javed², Christopher G Bruce², Rajiv Ramasawmy², Andi Jaimes², Katherine Lucas², Victoria Frasier², Amanda Potersnak², Robert J Lederman², and Adrienne E Campbell-Washburn^2
1Pulmonary Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, United States, ²Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States

Oxygen-enhanced lung MRI is promising for assessing regional lung function (ventilation and perfusion) but the physiological contributions to signal enhancement are poorly characterized. We sought to assess how oxygen-induced pulmonary vasodilation may contribute to signal enhancement by altering pulmonary blood volume and therefore lung proton density. We acquired repeated PDw and T1w images using a 0.55 T prototype MRI system in anesthetized pigs exposed to room air, 100% O2, 50% O2, hypoxia and experimental pulmonary hypovolemia. Our findings suggest that T1w signal intensity is affected by oxygen through both T1 shortening and vascular activity.

Alastair McCabe^1,2, Damian Borys³, Judith Christian¹, Solange Pereira⁴, Selene Rowe⁴, Paul S Morgan⁵, Jagrit Shah⁴, Elaine Blackshaw⁶, Stewart Martin⁷, and Rafal Panek^2,6
1Department of Clinical Oncology, Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom, ²School of Medicine, University of Nottingham, Nottingham, United Kingdom, ³Department of Systems Biology and Engineering, Silesian University of Technology, Gliwice, Poland, ⁴Department of Radiology, Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom, ⁵Radiological Sciences, University of Nottingham, Nottingham, United Kingdom, ⁶Department of Medical Physics & Clinical Engineering, Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom, ⁷University of Nottingham Biodiscovery Institute, Nottingham, United Kingdom

Oxygen enhanced MRI (OE-MRI) is a proposed tumour hypoxia imaging technique that is yet to be widely applied in the head and neck. 7 participants, 3 with suspected head and neck squamous cell carcinoma (HNSCC) were scanned using 3D spoiled GRE-DIXON. After on air scans, oxygen was delivered via a non-rebreather mask. T₁ times were determined on in-phase images. Oxygenation led to statistically significant T₁ shortening in CSF, thyroid and neck nodes. OE-MRI shows promise in identifying hypoxic regions in the head and neck. Further work investigating the feasibility of OE-MRI to detect hypoxic regions in HNSCC is warranted.