For Publishers
DiscoveryMetadataPeer reviewHostingPublishing
For Researchers
JoinPublishReviewCollect
Register
Blog
About
Search
Advanced search
My ScienceOpen
Search
For Publishers
For Researchers
Blog
About
Inviting an author to review:
Literature on Wearable Technology for Connected Health: Scoping Review of Research Trends, Advances, and Barriers
Find an author and click ‘Invite to review selected article’ near their name.
Search for authorsSearch for similar articles
1
views
80
references
 Top references
cited by
1
    
0 reviews
 Review
0
comments
 Comment
0
recommends
+1 Recommend
0 collections
    0
    shares
      6
      similar
       All similar
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Morphological assessment of cartilage and osteoarthritis in clinical practice and research: Intermediate-weighted fat-suppressed sequences and beyond

      review-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Abstract

          Magnetic resonance imaging (MRI) is widely regarded as the primary modality for the morphological assessment of cartilage and all other joint tissues involved in osteoarthritis. 2D fast spin echo fat-suppressed intermediate-weighted (FSE FS IW) sequences with a TE between 30 and 40ms have stood the test of time and are considered the cornerstone of MRI protocols for clinical practice and trials. These sequences offer a good balance between sensitivity and specificity and provide appropriate contrast and signal within the cartilage as well as between cartilage, articular fluid, and subchondral bone. Additionally, FS IW sequences enable the evaluation of menisci, ligaments, synovitis/effusion, and bone marrow edema-like signal changes. This review article provides a rationale for the use of FSE FS IW sequences in the morphological assessment of cartilage and osteoarthritis, along with a brief overview of other clinically available sequences for this indication. Additionally, the article highlights ongoing research efforts aimed at improving FSE FS IW sequences through 3D acquisitions with enhanced resolution, shortened examination times, and exploring the potential benefits of different magnetic field strengths. While most of the literature on cartilage imaging focuses on the knee, the concepts presented here are applicable to all joints.

          Key points

          1. MRI is currently considered the modality of reference for a “whole-joint” morphological assessment of osteoarthritis.

          2. Fat-suppressed intermediate-weighted sequences remain the keystone of MRI protocols for the assessment of cartilage morphology, as well as other structures involved in osteoarthritis.

          3. Trends for further development in the field of cartilage and joint imaging include 3D FSE imaging, faster acquisition including AI-based acceleration, and synthetic imaging providing multi-contrast sequences.

          Related collections

          Most cited references80

          • Record: found
          • Abstract: found
          • Article: not found

          SENSE: Sensitivity encoding for fast MRI

          Klaas Pruessmann, Markus Weiger, Markus Scheidegger … (1999)
          New theoretical and practical concepts are presented for considerably enhancing the performance of magnetic resonance imaging (MRI) by means of arrays of multiple receiver coils. Sensitivity encoding (SENSE) is based on the fact that receiver sensitivity generally has an encoding effect complementary to Fourier preparation by linear field gradients. Thus, by using multiple receiver coils in parallel scan time in Fourier imaging can be considerably reduced. The problem of image reconstruction from sensitivity encoded data is formulated in a general fashion and solved for arbitrary coil configurations and k-space sampling patterns. Special attention is given to the currently most practical case, namely, sampling a common Cartesian grid with reduced density. For this case the feasibility of the proposed methods was verified both in vitro and in vivo. Scan time was reduced to one-half using a two-coil array in brain imaging. With an array of five coils double-oblique heart images were obtained in one-third of conventional scan time. Magn Reson Med 42:952-962, 1999. Copyright 1999 Wiley-Liss, Inc.
          Article 0 comments Cited 740 times – based on 0 reviews     Review now
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Sparse MRI: The application of compressed sensing for rapid MR imaging.

            Michael Lustig, David Donoho, John Pauly (2007)
            The sparsity which is implicit in MR images is exploited to significantly undersample k-space. Some MR images such as angiograms are already sparse in the pixel representation; other, more complicated images have a sparse representation in some transform domain-for example, in terms of spatial finite-differences or their wavelet coefficients. According to the recently developed mathematical theory of compressed-sensing, images with a sparse representation can be recovered from randomly undersampled k-space data, provided an appropriate nonlinear recovery scheme is used. Intuitively, artifacts due to random undersampling add as noise-like interference. In the sparse transform domain the significant coefficients stand out above the interference. A nonlinear thresholding scheme can recover the sparse coefficients, effectively recovering the image itself. In this article, practical incoherent undersampling schemes are developed and analyzed by means of their aliasing interference. Incoherence is introduced by pseudo-random variable-density undersampling of phase-encodes. The reconstruction is performed by minimizing the l(1) norm of a transformed image, subject to data fidelity constraints. Examples demonstrate improved spatial resolution and accelerated acquisition for multislice fast spin-echo brain imaging and 3D contrast enhanced angiography. (c) 2007 Wiley-Liss, Inc.
            Article 0 comments Cited 435 times – based on 0 reviews     Review now
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Generalized autocalibrating partially parallel acquisitions (GRAPPA).

              Mark Griswold, Peter Jakob, Robin Heidemann … (2002)
              In this study, a novel partially parallel acquisition (PPA) method is presented which can be used to accelerate image acquisition using an RF coil array for spatial encoding. This technique, GeneRalized Autocalibrating Partially Parallel Acquisitions (GRAPPA) is an extension of both the PILS and VD-AUTO-SMASH reconstruction techniques. As in those previous methods, a detailed, highly accurate RF field map is not needed prior to reconstruction in GRAPPA. This information is obtained from several k-space lines which are acquired in addition to the normal image acquisition. As in PILS, the GRAPPA reconstruction algorithm provides unaliased images from each component coil prior to image combination. This results in even higher SNR and better image quality since the steps of image reconstruction and image combination are performed in separate steps. After introducing the GRAPPA technique, primary focus is given to issues related to the practical implementation of GRAPPA, including the reconstruction algorithm as well as analysis of SNR in the resulting images. Finally, in vivo GRAPPA images are shown which demonstrate the utility of the technique. Copyright 2002 Wiley-Liss, Inc.
              Article 0 comments Cited 363 times – based on 0 reviews     Review now
                Bookmark
                All references

                Author and article information

                Contributors
                Patrick Omoumi:
                ORCID: http://orcid.org/0000-0002-3251-3666
                Patrick.omoumi@chuv.ch
                Journal
                Journal ID (nlm-ta): Skeletal Radiol
                Journal ID (iso-abbrev): Skeletal Radiol
                Title: Skeletal Radiology
                Publisher: Springer Berlin Heidelberg (Berlin/Heidelberg )
                ISSN (Print): 0364-2348
                ISSN (Electronic): 1432-2161
                Publication date (Electronic): 8 May 2023
                Publication date PMC-release: 8 May 2023
                Publication date (Print): 2023
                Volume: 52
                Issue: 11
                Pages: 2185-2198
                Affiliations
                [1 ]Department of Radiology, Lausanne University Hospital and University of Lausanne, ( https://ror.org/019whta54) Lausanne, Switzerland
                [2 ]Department of Diagnostic and Interventional Radiology, Hôpital Libanais Geitaoui CHU, ( https://ror.org/036da3063) Achrafieh, Beyrouth, Lebanon
                [3 ]Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
                [4 ]LTS5, École Polytechnique FÉdÉrale de Lausanne (EPFL), ( https://ror.org/02s376052) Lausanne, Switzerland
                Author information
                http://orcid.org/0000-0002-3251-3666
                Article
                Publisher ID: 4343
                DOI: 10.1007/s00256-023-04343-2
                PMC ID: 10509097
                PubMed ID: 37154871
                SO-VID: fa186aef-497c-4ccb-a8c9-d8dd0203bf5b
                Copyright © © The Author(s) 2023
                License:

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                Date received : 15 November 2022
                Date revision received : 28 March 2023
                Date accepted : 10 April 2023
                Funding
                Funded by: Swiss National Science Foundation
                Award ID: Sinergia grant CRSII5_177155
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100017554, Zhejiang Provincial Government Scholarship;
                Funded by: University of Lausanne
                Open Access :

                Open access funding provided by University of Lausanne

                Categories
                Subject: Review Article
                Custom metadata
                issue-copyright-statement © International Skeletal Society (ISS) 2023

                ScienceOpen disciplines: Radiology & Imaging
                Keywords: osteoarthritis,mri,mri physics,cartilage,qualitative assessment,artificial intelligence
                Data availability:
                ScienceOpen disciplines: Radiology & Imaging
                Keywords: osteoarthritis, mri, mri physics, cartilage, qualitative assessment, artificial intelligence

                Comments

                Comment on this article

                scite_

                Similar content6

                See all similar

                Cited by1

                See all cited by

                Most referenced authors761

                See all reference authors