Real‐time motion and retrospective coil sensitivity correction for CEST using volumetric navigators (vNavs) at 7T

Rodriguez, Esau Poblador; Moser, Philipp; Auno, Sami; Eckstein, Korbinian; Dymerska, Barbara; Kouwe, André van der; Gruber, Stephan; Trattnig, Siegfried; Bogner, Wolfgang

doi:10.1002/mrm.28555

Cited by 11 publications

(5 citation statements)

References 61 publications

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“…1) Motion correction [118,119], which is challenging due to the difference in contrast between images acquired far off-resonance and images close to on-resonance. It is, therefore, strongly advised to prevent motion during acquisition by immobilizing the head.…”

Section: Parameters and Processingmentioning

confidence: 99%

A guide to advanced MRI processing for clinical glioma research

Clement,

Beun,

Arzanforoosh

et al. 2024

Preprint

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BackgroundTo date, multiple advanced magnetic resonance imaging (MRI) methods beyond conventional qualitative structural imaging for the diagnosis, prognosis, and treatment follow-up of glioma have demonstrated their utility for clinical studies. However, these methods often rely on complex off-scanner processing to yield the most information and to extract quantitative biomarkers, limiting their practical use for studies, as well as their clinical translation.While community-driven software solutions exist for these advanced MRI methods, many aspiring clinical researchers face challenges in acquiring the necessary knowledge to effectively apply these tools. This guide, an initiative of the Glioma MR imaging 2.0 network (GliMR), aims to provide an overview of existing solutions, communities, and repositories with the ultimate goal of enabling standardization, open science, and reproducible quantitative imaging studies of gliomas. Yet, most of the reviewed tools and approaches to image data analyses may also be used in the context of studies on diseases other than glioma.ContentThis guide summarizes the state-of-the-art processing software solutions and the repositories/communities for the following advanced MRI methods: DSC; DCE; ASL; diffusion MRI; relaxometry; MRF; MRS; CEST; SWI; QSM; MRE; and task-based and resting-state fMRI. For each of those, after a short introduction about the method and output parameters, the required and recommended image processing steps and quality control measures are described, and we point to further literature for more details. In addition, an overview of openly available software tools that provide these functionalities for MRI processing and exemplify workflows is given. Wherever possible, the readers are guided toward existing inventories, repositories, and communities, which offer not only a collection of these tools, but also more in-depth guidance. Each part concludes with an appraisal of the estimated required expertise and future development needs.ConclusionThis guide provides an extensive overview of the currently available processing tools that can help aspiring clinical researchers to obtain high-quality reproducible imaging data from advanced MRI scans of gliomas. While GliMR n is focused on glioma research, this guide will also be helpful for other clinical neuroimaging topics as general processing steps may not be specific to glioma only.

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Section: Parameters and Processingmentioning

confidence: 99%

A guide to advanced MRI processing for clinical glioma research

Clement,

Beun,

Arzanforoosh

et al. 2024

Preprint

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“…Volumetric navigators (vNavs), a sequence block that is applied before the saturation pulses, can help to perform real-time motion correction for CEST [ 92 ]. As yet, vNavs have not been translated to body imaging, which may be studied in the future.…”

Section: Technical Issues For Non-brain Tumor Imagingmentioning

confidence: 99%

A Brief History and Future Prospects of CEST MRI in Clinical Non-Brain Tumor Imaging

Gao

Zou

et al. 2021

IJMS

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Chemical exchange saturation transfer (CEST) MRI is a promising molecular imaging tool which allows the specific detection of metabolites that contain exchangeable amide, amine, and hydroxyl protons. Decades of development have progressed CEST imaging from an initial concept to a clinical imaging tool that is used to assess tumor metabolism. The first translation efforts involved brain imaging, but this has now progressed to imaging other body tissues. In this review, we summarize studies using CEST MRI to image a range of tumor types, including breast cancer, pelvic tumors, digestive tumors, and lung cancer. Approximately two thirds of the published studies involved breast or pelvic tumors which are sites that are less affected by body motion. Most studies conclude that CEST shows good potential for the differentiation of malignant from benign lesions with a number of reports now extending to compare different histological classifications along with the effects of anti-cancer treatments. Despite CEST being a unique ‘label-free’ approach with a higher sensitivity than MR spectroscopy, there are still some obstacles for implementing its clinical use. Future research is now focused on overcoming these challenges. Vigorous ongoing development and further clinical trials are expected to see CEST technology become more widely implemented as a mainstream imaging technology.

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“…For example, low-resolution images acquired throughout the scan, denoted volumetric navigators (VNAVs), can provide this motion information using image registration 7,8 ; however, relatively long acquisition and processing times (hundreds of milliseconds) make them more appropriate for application in long TR sequences. 9,10 Using the properties of the Fourier transform, k-space navigators enable shorter acquisition and processing times. Orbital navigators (ONAVs) use a circular trajectory in k-space to measure in-plane rotation and translation, 11 and can fully characterize rigid motion using three orthogonal trajectories.…”

Section: Introductionmentioning

confidence: 99%

“…Imaging or k‐space data obtained with the scanner itself can also inform motion estimates for PMC. For example, low‐resolution images acquired throughout the scan, denoted volumetric navigators (VNAVs), can provide this motion information using image registration 7,8 ; however, relatively long acquisition and processing times (hundreds of milliseconds) make them more appropriate for application in long TR sequences 9,10 …”

Section: Introductionmentioning

confidence: 99%

Prospective motion correction for brain MRI using spherical navigators

Hewlett,

Oran,

Liu

et al. 2024

Magnetic Resonance in Med

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PurposeTo demonstrate for the first time the feasibility of performing prospective motion correction using spherical navigators (SNAVs).MethodsSNAVs were interleaved in a 3D FLASH sequence with an additional short baseline scan (6.8 s) for fast rotation estimation. Assessment of SNAV‐based prospective motion correction was performed in six volunteers. Participant motion was guided using randomly generated stepwise prompts as well as prompts derived from real motion cases. Experiments were performed on a 3 T MRI scanner using a 32‐channel head coil.ResultsWhen optimized for real‐time application, SNAV‐based motion estimates were computed in 25.8 ± 1.3 ms. Phantom‐based quantification of rotation and translation accuracy indicated mean absolute errors of 0.10 ± 0.09° and 0.25 ± 0.14 mm, respectively. Implementing SNAV‐based motion estimates for prospective motion correction led to a clear improvement in image quality with minimal increase in scan time (<5%).ConclusionOptimization of SNAV processing for real‐time application enables prospective motion correction with low latency and minimal scan time requirements.

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Real‐time motion and retrospective coil sensitivity correction for CEST using volumetric navigators (vNavs) at 7T

Abstract: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 11 publications

References 61 publications

A guide to advanced MRI processing for clinical glioma research

A guide to advanced MRI processing for clinical glioma research

A Brief History and Future Prospects of CEST MRI in Clinical Non-Brain Tumor Imaging

Prospective motion correction for brain MRI using spherical navigators

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