Vlad Negnevitsky¹, Benjamin Menküc², Thomas O'Reilly³, José Miguel Algarín^4,5, Teresa Guallart⁶, Rubén Pellicer-Guridi^4,5, Yolanda Vives-Gilabert⁷, Lincoln Craven-Brightman⁸, Jason Stockmann⁸, David Schote⁹, Marcus Prier¹⁰, Thomas Witzel¹¹, Andrew Webb³, and Joseba Alonso^4,5
1Oxford Ionics, Oxford, United Kingdom, ²University of Applied Sciences and Arts Dortmund, Dortmund, Germany, ³Department of Radiology, Leiden University Medical Centre, Leiden, Netherlands, ⁴MRILab, Institute for Molecular Imaging and Instrumentation (i3M), Spanish National Research Council (CSIC), Valencia, Spain, ⁵MRILab, Institute for Molecular Imaging and Instrumentation (i3M), Universitat Politècnica de València (UPV), Valencia, Spain, ⁶Tesoro Imaging S.L., Valencia, Spain, ⁷Department of Electronic Engineering, Universidad de Valencia, Valencia, Spain, ⁸Massachusetts General Hospital, A. A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States, ⁹Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany, ¹⁰Department of Biomagnetical Resonance, Otto-von-Guericke University Magdeburg, Forschungscampus STIMULATE, Magdeburg, Germany, ¹¹Q Bio Inc., San Carlos, CA, United States

In recent years, low-field scanners have proven their potential for clinical, preclinical, research and teaching applications. However, a critical milestone is yet to be achieved on the path to affordable, high-performance MRI systems: the availability of an inexpensive, versatile electronic control system (MR console), competitive with commercial spectrometers, but without dramatically increasing the overall scanner cost. In this work we show the status of MaRCoS (MAgnetic Resonance COntrol System), an open-source MR console and software package with powerful features, that offers higher versatility than many commercial spectrometers, and show its use in several MR setups, including in vivo acquisitions.

Paul Mcelhinney¹ and Shajan Gunamony^1
1Center for Cognitive Neuroimaging, Glasgow University, Glasgow, United Kingdom

We have generated a numerical model of a 64-channel receive array at 7T and analysed its influence on SAR on an 8-channel transmit array. Simulations were conducted using a finite integration technique in CST Microwave Studio to create a model of the combined Tx/Rx system on both our phantom and the Duke human body model. Each receive element was actively detuned and implemented within our 8 channel transmit array model to provide us with an improved model from which we found that there was a negligible effect on the B₁⁺ field and a reduction in the SAR of ~20%. 

Shiloh Sison¹ and Negin Behzadian^2
1Research and Development, Abbott, Sunnyvale, CA, United States, ²Abbott, sylmar, CA, United States

With the emergence of B_1+RMS as a more precise RF exposure metric than SAR, implantable device manufacturers have begun MR Conditional labeling to fixed B_1+RMS levels, in addition to SAR labeling. We previously characterized the relationship between wbSAR-scaled and B_1+RMS-scaled RF heating of cardiac pacing leads in the context of 3T Normal Operating Mode and First Level Controlled Mode MRI exposure [1]. In this study, we extend the analysis to 1.5T.

Jiajun Chang¹, Jianfeng Zheng¹, Ran Guo¹, Qianlong Lan¹, Mayur Thakore², Wolfgang Kainz³, and Ji Chen^1
1Electrical and Computer Engineering, University of Houston, Houston, TX, United States, ²Stryker Corporation, Mahwah, NJ, United States, ³High Performance Computing for MRI Safety, LLC, Jasper, GA, United States

In this research, a convolutional neural network (CNN) model is developed to predict the RF-induced heating for several tibia plate systems. One thousand four hundred and sixteen device configurations were developed, and the peak 1g-average SAR values were extracted. A subset of the data was used as training set and simulation meshes were used as the input of the CNN model. Results showed a quick network convergence and high correlation. The network also had a low absolute and percentage error level. This demonstrates that one can potentially use CNN model to predict the RF-induced heating of plate systems.

Kisoo Kim¹, Muhammad Zubair², Chris J Diederich², and Eugene Ozhinsky^1
1Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States, ²Radiation Oncology, University of California, San Francisco, San Francisco, CA, United States

Hyperthermia refers to a cancer treatment by elevating tissue temperature to 40-45 °C. Hyperthermia can be achieved by clinical MRgFUS system, allowing real-time temperature monitoring for the precise control of hyperthermia heating. Currently the ExAblate is MR-guided FUS ablation system with the largest installation worldwide, however, requires advanced beamforming strategies for volumetric hyperthermia. This study proposed electronic beam steering, multi-focal patterns, and sector-vortex beamforming approaches in conjunction with partial array activation and was evaluated in biothermal simulations and phantom experiments. This study demonstrated the feasibility of sustained large volume heating with MR thermometry feedback using the ExAblate body system.

Peter Stijnman^1,2, Bart Steensma¹, Gerrit Melis³, Cornelis van den Berg¹, and Alexander Raaijmakers^4
1Computational Imaging, UMC Utrecht, Utrecht, Netherlands, ²Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands, ³Radiology, UMC Utrecht, Utrecht, Netherlands, ⁴Eindhoven University of Technology, Eindhoven, Netherlands

Patients with non-labelled implants are often ineligible for MRI. Sometimes non-labelled implants are scanned by some hospitals based on literature and empirical insights, power constraints are abided to avoid tissue heating. Using an accelerated simulation method we demonstrate a proof of concept workflow to obtain the patient-specific SAR increase for multiple patient and implant positions within 2-3 hours. This workflow uses two orthogonal X-ray images to construct a 3D model of the implant which is inserted in a human model. The method enables more accurate scanning constraints and, a more informed risk vs benefit analysis for each patient.

Xin Huang¹, Xiyao Xin¹, Kevin Feng¹, Vick Chen¹, and Shiloh Sison^1
1Abbott Laboratories, Sylmar, CA, United States

To assess the impact of RF frequency variation on AIMD MRI RF safety, the tangential electric field and cardiac pacing lead electrode RF heating transfer functions were obtained at different frequencies: around 64 MHz for 1.5T scanners and 128 MHz for 3T scanners. The result shows that the impact on in vivo RF heating prediction due to RF frequency shift is insignificant.

Feng Jia¹, Sebastian Littin¹, Philipp Amrein¹, and Maxim Zaitsev^1,2
1Department of Radiology, Medical Physics, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany, ²High Field MR Center, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria

Optimize the shape of pole shoes of a 0.55 T permanent magnet to increase the homogeneity of the main magnetic field in a region of interest.

Marina Santini¹, Oskar Jerdhaf², Anette Karlsson², Emma Eneling³, Magnus Stridsman³, Arne Jönsson⁴, and Peter Lundberg^2,5
1Digital Health, Research Institutes of Sweden (RISE), Stockholm, Sweden, ²Radiation Physics, Linköping University, Linköping, Sweden, ³Unit for Technology Assessment, Testing and Innovation and Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden, ⁴Department of Computer and Information Science, Linköping University, Linköping, Sweden, ⁵Center for medical Imaging and Visualization (CMIV), Linköping, Sweden

It is important for radiologists to know in advance if a patient has an implant, since MR-scanning is incompatible with some implants. At present, the unbiased process to ascertain whether a patient could be at risk is manual and not entirely reliable. We argue that this process can be enhanced and accelerated using AI-based clinical text-mining. We therefore investigated the automatic discovery of medical implant terms in electronic-medical-records (EMRs) written in Swedish using an AI-based text mining algorithm called BERT. BERT is a state-of-the-art language model trained using a deep learning algorithm based on transformers. Results are promising.   

Michael Childers¹, Dorab Sethna¹, Vick Chen¹, and Shiloh Sison^2
1Abbott, Sylmar, CA, United States, ²Abbott, Sunnyvale, CA, United States

Simulations and benchtop testing were performed to assess potential gradient induced device heating of leadless pacemakers. Results of the evaluation showed leadless pacemakers sized objects, made from commonly used conductive materials, heated less than 1°C when exposed to the gradient induced device heating safety test conditions per ISO/TS 10974.  In general, a temperature rise less than 2°C is considered to be clinically insignificant. As such, the risk of leadless pacemaker gradient induced device heating is negligible and assessments for this hazard per ISO/TS 10974 may not be necessary.

Kevin Feng¹, Ruoli Jiang¹, and Shiloh Sison^1
1Abbott Laboratories, Sylmar, CA, United States

A 3D tailored excitation sequence at 3T was found to have peak RF simultaneous with gradient slewing. The exposure levels generated by this sequence were determined and impact to the transvenous implantable pacemakers, implantable Cardioverter Defibrillators (ICDs) and Cardiac Resynchronization Therapy (CRT) systems safety evaluation of RF and gradient voltages was assessed. It is demonstrated that the combined RF and gradient level is expected to be covered by the separate RF and gradient test level required by ISO/CD 10974, and the bandwidth of the 3D sequence is well within the frequency ranged specified in ISO/CD 10974.

Johannes Lindemeyer¹, Lukas Christian Sebeke¹, Ari Partanen², Christian Lucas Haas¹, and Holger Grüll^1,3
1Department of Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany, ²Profound Medical Inc, Mississauga, ON, Canada, ³Department of Chemistry, Faculty of Mathematics and Natural Sciences, University of Cologne, Cologne, Germany

High intensity focused ultrasound-mediated histotripsy is a modality for targeted, non-invasive interventions. As temperature changes detected by MR-thermometry are not directly related to histotripsy treatment success, we propose quantitative susceptibility mapping (QSM) to evaluate and monitor treatment efficacy. Fresh porcine heart muscle tissue was sonicated using a clinical MR-HIFU system. Herein, we demonstrate the successful visualization of histotripsy-induced lesions by QSM.

Eric D. Anttila¹, Grant M. Baker¹, Alan R. Leewood¹, Seoggwan Kim¹, and David C. Gross^1
1MED Institute Inc., West Lafayette, IN, United States

The primary goal of this study was to compare radiofrequency (RF) induced temperature rises of a stent within the ASTM phantom and two virtual human anatomies in a 1.2 T Hitachi Oasis open bore, 1.5 T Siemens Altea closed bore, and 3.0 T Siemens Prisma closed bore MRI systems for the purpose of MRI labeling according to ASTM F2503¹. The secondary goal was to simulate RF-induced heating of the same stent within the Duke virtual human model containing 1) internal organs with individual material properties and 2) no internal organs and average tissue properties throughout and compare predicted temperature rises.