• J Magn Reson Imaging · Jun 2020

    Extracting Voxel-Based Cartilage Relaxometry Features in Hip Osteoarthritis Subjects Using Principal Component Analysis.

    • Tzu-Chieh Liao, Valentina Pedoia, Jan Neumann, Thomas M Link, Richard B Souza, and Sharmila Majumdar.
    • Musculoskeletal Quantitative Imaging Research, Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, California, USA.
    • J Magn Reson Imaging. 2020 Jun 1; 51 (6): 1708-1719.

    BackgroundMRI-based relaxation time measurements provide quantitative assessment of cartilage biochemistry. Identifying distinctive relaxometry features in hip osteoarthritis (OA) might provide important information on regional disease variability.PurposeFirst, to incorporate fully automatic voxel-based relaxometry (VBR) with principal component analysis (PCA) to extract distinctive relaxometry features in subjects with radiographic hip OA and nondiseased controls. Second, to use the identified features to further distinguish subjects with cartilage compositional abnormalities.Study TypeCross-sectional.SubjectsThirty-three subjects with radiographic hip OA (20 males; age, 50.2 ± 13.3 years) and 55 controls participated (28 males; 41.3 ± 12.0 years).SequenceA 3.0T scanner using 3D SPGR, combined T1ρ /T2 , and fast spin echo sequences.AssessmentPelvic radiographs, patients' self-reported symptoms, physical function, and cartilage morphology were analyzed. Cartilage relaxation times were quantified using traditional regions of interest and VBR approaches. PCA was performed on VBR data to identify distinctive relaxometry features, and were subsequently used to identify a subgroup of subjects from the controls that exhibited compositional abnormalities.Statistical TestsChi-square and independent t-tests were used to compare group characteristics. Logistic regression models were used to identify the possible principal components (PCs) that were able to predict OA vs. control classification.ResultsIn T1ρ assessment, OA subjects demonstrated higher T1ρ values in the posterior hip region and deep cartilage layer when compared with controls (P = 0.012 and 0.001, respectively). In T2 assessment, OA subjects exhibited higher T2 values in the posterior hip region (P < 0.001). Based on the PC score classification, 16 subjects without radiographic evidence of OA demonstrated relaxometry patterns similar to OA subjects, and exhibited worse physical function (P = 0.003) and cartilage lesions (P = 0.009-0.032) when compared with the remaining controls.Data ConclusionThe study identified distinctive cartilage relaxometry features that were able to discriminate subjects with and without radiographic hip OA effectively.Level Of Evidence1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:1708-1719.© 2019 International Society for Magnetic Resonance in Medicine.

      Pubmed     Full text   Copy Citation     Plaintext  

      Add institutional full text...

    Notes

     
    Knowledge, pearl, summary or comment to share?
    300 characters remaining
    help        
    You can also include formatting, links, images and footnotes in your notes
    • Simple formatting can be added to notes, such as *italics*, _underline_ or **bold**.
    • Superscript can be denoted by <sup>text</sup> and subscript <sub>text</sub>.
    • Numbered or bulleted lists can be created using either numbered lines 1. 2. 3., hyphens - or asterisks *.
    • Links can be included with: [my link to pubmed](http://pubmed.com)
    • Images can be included with: ![alt text](https://bestmedicaljournal.com/study_graph.jpg "Image Title Text")
    • For footnotes use [^1](This is a footnote.) inline.
    • Or use an inline reference [^1] to refer to a longer footnote elseweher in the document [^1]: This is a long footnote..

    hide…