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Special Issue: Quantitative Body Magnetic Resonance Imaging

Submission status
Closed
Quantitative MRI – how to make it work in the body? While MRI in the routine clinical setting relies on the qualitative assessment of contrast-weighted images, there is a surge of activity in the MR community to develop quantitative imaging tools for tissue characterisation. Quantitative MRI (qMRI) has shown potential beyond traditional diagnostics in monitoring disease progression and therapeutic response, for its use towards precision medicine. However, qMRI typically requires the encoding of additional parameters, and has been traditionally challenged by prolonged acquisition times, inadequate repeatability and reproducibility, dependence on imaging platform, and confounding effects which bias results. qMRI in the abdomen and the pelvis has therefore faced critical challenges over the past two decades. Recent hardware and software developments in MRI have accelerated the interest in developing methods for body quantitative imaging and overcoming the associated technical challenges. High and low field systems have increased the sensitivity of qMRI or decreased the effect of confounders in qMRI parameter extraction. Novel sensing, acquisition and reconstruction methods are on the horizon to minimise the effect of motion on body qMRI enabling the significant shortening of protocols. Validation studies are ongoing to assess the accuracy and reproducibility of body qMRI biomarkers in-vitro and in multi-centre and multi-vendor settings. New biophysical signal models have been proposed to reduce the effect of confounders on body qMRI. These and other developments make qMRI of the body a rapidly growing research field with a wide range of impactful clinical applications. We invite submissions of original research on solutions for tackling the methodological challenges in the acquisition, reconstruction, and analysis of qMRI data in the abdomen and the pelvis. Contributions on qMRI methodology (e.g. relaxometry, diffusion MRI, perfusion MRI, MR elastography, fat quantification) for liver, pancreas, kidney, gut/colon and prostate imaging are of particular interest, including the following: · Acquisition and reconstruction methods for body qMRI · Methods for motion correction and compensation in body qMRI · Methods for accelerated multi-parametric body qMRI · Machine learning and deep learning methods for body qMRI · Development and validation of phantoms for body qMRI parameters · Techniques leveraging low/high fields to improve body qMRI sensitivity/reproducibility · Signal models for analysing qMRI data and improving accuracy/reproducibility of body qMRI · Standardisation and harmonisation of body qMRI protocols across scanner platforms · Open-source hardware and software for body qMRI We invite manuscripts on topics pertinent to the scope of the Special Issue. In order to meet the timeline, papers should be submitted not later than December 1st, 2023.

Editors

  • Wu Holden Wu Holden , 

    Wu Holden

    Wu Holden is an Assiciate Professor at UCLA Department of Radiology, Los Angeles, USA. He is interested in developing rapid and robust magnetic resonance imaging (MRI) techniques for improving diagnosis and treatment in oncologic and cardiovascular applications.

  • Octavia Bane Octavia Bane , 

    Octavia Bane

    Ocatvia Bane is an Assistant Professor and Instructor in the BioMedical Engineering and Imaging Institute (BMEII) and the Department of Radiology at the Icahn School of Medicine at Mount Sinai, New York, USA.

  • Dimitrios Karampinos Dimitrios Karampinos , 

    Dimitrios Karampinos

    Dimitrios Karampinos is a Professor for Experimental Magnetic Resonance Imaging at the Technical University of Munich, Germany. Prof. Karampinos’ research focuses on the development of new methods for magnetic resonance imaging (MRI). His research group develops MRI acquisition, image reconstruction and signal modeling techniques in order to generate new quantitative MRI biomarkers and to increase the robustness and effectiveness of quantitative MRI biomarkers.

  • Susan Francis Susan Francis , 

    Susan Francis

    Susan Francis is a Professor of Physics at the University of Nottingham, UK. Her research interest is to develop advanced quantitative MRI techniques for studies of physiology, clinical imaging and neuroscience applications. This includes the development of imaging methods, such as ASL-based perfusion, oxygenation and relaxometry. She also works at ultra-high (7 T) on developing and applying high resolution functional MRI techniques and arterial spin labelling (ASL) methods to measure blood flow and blood volume non-invasively to study basic neuroscience.

  • Durgesh Dwivedi Durgesh Dwivedi  &

    Durgesh Dwivedi

    Durgesh Dwivedi is an Associate Professor in the Department of Radiodiagnosis at King George's Medical University (KGMU) in Lucknow, UP, India. His research is focused on various applications of biomedical magnetic resonance techniques. His esearch interests are in MRI; 3D-MRSI; ASL; Radiomics; Radiogenomics; PET/CT in Oncology; Dosimetry.

  • Takeshi Yokoo Takeshi Yokoo

    Takeshi Yokoo

    Takeshi Yokoo is an Associate Professor of Radiology at UT Southwestern Medical Center, Dallas, Texas, USA and a member of its Magnetic Resonance Imaging (MRI) Division. He also serves as the Lead Radiologist for Body Intervention at Parkland Hospital. His clinical interests include imaging of liver cancer, as well as image-guided biopsies and drainages.

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