MRI and biomechanics multidimensional data analysis reveals R2‐R1ρ as an early predictor of cartilage lesion progression in knee osteoarthritis
Purpose To couple quantitative compositional MRI, gait analysis, and machine learning multidimensional data analysis to study osteoarthritis (OA). OA is a multifactorial disorder accompanied by biochemical and morphological changes in the articular cartilage, modulated by skeletal biomechanics and g...
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| Veröffentlicht in: | Journal of magnetic resonance imaging Jg. 47; H. 1; S. 78 - 90 |
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| Hauptverfasser: | , , , , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
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01.01.2018
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| ISSN: | 1053-1807, 1522-2586, 1522-2586 |
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| Abstract | Purpose
To couple quantitative compositional MRI, gait analysis, and machine learning multidimensional data analysis to study osteoarthritis (OA). OA is a multifactorial disorder accompanied by biochemical and morphological changes in the articular cartilage, modulated by skeletal biomechanics and gait. While we can now acquire detailed information about the knee joint structure and function, we are not yet able to leverage the multifactorial factors for diagnosis and disease management of knee OA.
Materials and Methods
We mapped 178 subjects in a multidimensional space integrating: demographic, clinical information, gait kinematics and kinetics, cartilage compositional T1ρ and T2 and R2‐R1ρ (1/T2–1/T1ρ) acquired at 3T and whole‐organ magnetic resonance imaging score morphological grading. Topological data analysis (TDA) and Kolmogorov–Smirnov test were adopted for data integration, analysis, and hypothesis generation. Regression models were used for hypothesis testing.
Results
The results of the TDA showed a network composed of three main patient subpopulations, thus potentially identifying new phenotypes. T2 and T1ρ values (T2 lateral femur P = 1.45*10‐8, T1ρ medial tibia P = 1.05*10‐5), the presence of femoral cartilage defects (P = 0.0013), lesions in the meniscus body (P = 0.0035), and race (P = 2.44*10‐4) were key markers in the subpopulation classification. Within one of the subpopulations we observed an association between the composite metric R2‐R1ρ and the longitudinal progression of cartilage lesions.
Conclusion
The analysis presented demonstrates some of the complex multitissue biochemical and biomechanical interactions that define joint degeneration and OA using a multidimensional approach, and potentially indicates that R2‐R1ρ may be an imaging biomarker for early OA.
Level of Evidence: 3
Technical Efficacy: Stage 2
J. Magn. Reson. Imaging 2018;47:78–90. |
|---|---|
| AbstractList | Purpose
To couple quantitative compositional MRI, gait analysis, and machine learning multidimensional data analysis to study osteoarthritis (OA). OA is a multifactorial disorder accompanied by biochemical and morphological changes in the articular cartilage, modulated by skeletal biomechanics and gait. While we can now acquire detailed information about the knee joint structure and function, we are not yet able to leverage the multifactorial factors for diagnosis and disease management of knee OA.
Materials and Methods
We mapped 178 subjects in a multidimensional space integrating: demographic, clinical information, gait kinematics and kinetics, cartilage compositional T1ρ and T2 and R2‐R1ρ (1/T2–1/T1ρ) acquired at 3T and whole‐organ magnetic resonance imaging score morphological grading. Topological data analysis (TDA) and Kolmogorov–Smirnov test were adopted for data integration, analysis, and hypothesis generation. Regression models were used for hypothesis testing.
Results
The results of the TDA showed a network composed of three main patient subpopulations, thus potentially identifying new phenotypes. T2 and T1ρ values (T2 lateral femur P = 1.45*10‐8, T1ρ medial tibia P = 1.05*10‐5), the presence of femoral cartilage defects (P = 0.0013), lesions in the meniscus body (P = 0.0035), and race (P = 2.44*10‐4) were key markers in the subpopulation classification. Within one of the subpopulations we observed an association between the composite metric R2‐R1ρ and the longitudinal progression of cartilage lesions.
Conclusion
The analysis presented demonstrates some of the complex multitissue biochemical and biomechanical interactions that define joint degeneration and OA using a multidimensional approach, and potentially indicates that R2‐R1ρ may be an imaging biomarker for early OA.
Level of Evidence: 3
Technical Efficacy: Stage 2
J. Magn. Reson. Imaging 2018;47:78–90. To couple quantitative compositional MRI, gait analysis, and machine learning multidimensional data analysis to study osteoarthritis (OA). OA is a multifactorial disorder accompanied by biochemical and morphological changes in the articular cartilage, modulated by skeletal biomechanics and gait. While we can now acquire detailed information about the knee joint structure and function, we are not yet able to leverage the multifactorial factors for diagnosis and disease management of knee OA.PURPOSETo couple quantitative compositional MRI, gait analysis, and machine learning multidimensional data analysis to study osteoarthritis (OA). OA is a multifactorial disorder accompanied by biochemical and morphological changes in the articular cartilage, modulated by skeletal biomechanics and gait. While we can now acquire detailed information about the knee joint structure and function, we are not yet able to leverage the multifactorial factors for diagnosis and disease management of knee OA.We mapped 178 subjects in a multidimensional space integrating: demographic, clinical information, gait kinematics and kinetics, cartilage compositional T1ρ and T2 and R2 -R1ρ (1/T2 -1/T1ρ ) acquired at 3T and whole-organ magnetic resonance imaging score morphological grading. Topological data analysis (TDA) and Kolmogorov-Smirnov test were adopted for data integration, analysis, and hypothesis generation. Regression models were used for hypothesis testing.MATERIALS AND METHODSWe mapped 178 subjects in a multidimensional space integrating: demographic, clinical information, gait kinematics and kinetics, cartilage compositional T1ρ and T2 and R2 -R1ρ (1/T2 -1/T1ρ ) acquired at 3T and whole-organ magnetic resonance imaging score morphological grading. Topological data analysis (TDA) and Kolmogorov-Smirnov test were adopted for data integration, analysis, and hypothesis generation. Regression models were used for hypothesis testing.The results of the TDA showed a network composed of three main patient subpopulations, thus potentially identifying new phenotypes. T2 and T1ρ values (T2 lateral femur P = 1.45*10-8 , T1ρ medial tibia P = 1.05*10-5 ), the presence of femoral cartilage defects (P = 0.0013), lesions in the meniscus body (P = 0.0035), and race (P = 2.44*10-4 ) were key markers in the subpopulation classification. Within one of the subpopulations we observed an association between the composite metric R2 -R1ρ and the longitudinal progression of cartilage lesions.RESULTSThe results of the TDA showed a network composed of three main patient subpopulations, thus potentially identifying new phenotypes. T2 and T1ρ values (T2 lateral femur P = 1.45*10-8 , T1ρ medial tibia P = 1.05*10-5 ), the presence of femoral cartilage defects (P = 0.0013), lesions in the meniscus body (P = 0.0035), and race (P = 2.44*10-4 ) were key markers in the subpopulation classification. Within one of the subpopulations we observed an association between the composite metric R2 -R1ρ and the longitudinal progression of cartilage lesions.The analysis presented demonstrates some of the complex multitissue biochemical and biomechanical interactions that define joint degeneration and OA using a multidimensional approach, and potentially indicates that R2 -R1ρ may be an imaging biomarker for early OA.CONCLUSIONThe analysis presented demonstrates some of the complex multitissue biochemical and biomechanical interactions that define joint degeneration and OA using a multidimensional approach, and potentially indicates that R2 -R1ρ may be an imaging biomarker for early OA.3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:78-90.LEVEL OF EVIDENCE3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:78-90. |
| Author | Morioka, Kazuhito Majumdar, Sharmila Souza, Richard B. Nardo, Lorenzo Ferguson, Adam R. Pedoia, Valentina Teng, Hsiang‐Ling Haefeli, Jenny |
| AuthorAffiliation | 4 San Francisco Veterans Affairs Medical Center, San Francisco, California, USA 2 Weill Institute for Neurosciences, Department of Neurological Surgery, Brain and Spinal Injury Center, University of California, San Francisco, California, USA 3 Department of Physical Therapy and Rehabilitation Science, University of California, San Francisco, California, USA 1 Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA |
| AuthorAffiliation_xml | – name: 3 Department of Physical Therapy and Rehabilitation Science, University of California, San Francisco, California, USA – name: 1 Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA – name: 4 San Francisco Veterans Affairs Medical Center, San Francisco, California, USA – name: 2 Weill Institute for Neurosciences, Department of Neurological Surgery, Brain and Spinal Injury Center, University of California, San Francisco, California, USA |
| Author_xml | – sequence: 1 givenname: Valentina surname: Pedoia fullname: Pedoia, Valentina email: valentina.pedoia@ucsf.edu organization: University of California – sequence: 2 givenname: Jenny surname: Haefeli fullname: Haefeli, Jenny organization: University of California – sequence: 3 givenname: Kazuhito surname: Morioka fullname: Morioka, Kazuhito organization: University of California – sequence: 4 givenname: Hsiang‐Ling surname: Teng fullname: Teng, Hsiang‐Ling organization: University of California – sequence: 5 givenname: Lorenzo surname: Nardo fullname: Nardo, Lorenzo organization: University of California – sequence: 6 givenname: Richard B. surname: Souza fullname: Souza, Richard B. organization: University of California – sequence: 7 givenname: Adam R. surname: Ferguson fullname: Ferguson, Adam R. email: adam.ferguson@ucsf.edu organization: San Francisco Veterans Affairs Medical Center – sequence: 8 givenname: Sharmila surname: Majumdar fullname: Majumdar, Sharmila organization: University of California |
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| Copyright | 2017 International Society for Magnetic Resonance in Medicine 2017 International Society for Magnetic Resonance in Medicine. |
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| References_xml | – volume: 3 start-page: 1236 year: 2013 article-title: Extracting insights from the shape of complex data using topology publication-title: Sci Rep – volume: 130 start-page: 144115 year: 2009 article-title: Topological methods for exploring low‐density states in biomolecular folding pathways publication-title: J Chem Phys – volume: 33 start-page: 38 year: 2015 end-page: 42 article-title: Chemical exchange in knee cartilage assessed by R1rho (1/T1rho) dispersion at 3T publication-title: Magn Reson Imaging – volume: 58 start-page: 26 year: 2008 end-page: 35 article-title: Estimates of the prevalence of arthritis and other rheumatic conditions in the United States. Part II publication-title: Arthritis Rheum – volume: 21 start-page: 10 year: 2013 end-page: 15 article-title: Osteoarthritis as a disease of mechanics publication-title: Osteoarthritis Cartilage – volume: 33 start-page: 38 year: 2015 end-page: 42 article-title: Chemical exchange in knee cartilage assessed by R1rho (1/T1rho) dispersion at 3 T publication-title: J Magn Reson Imaging – volume: 3 start-page: 3043 year: 2005 end-page: 3046 article-title: Combined image processing techniques for characterization of MRI cartilage of the knee publication-title: Conf Proc IEEE Eng Med Biol Soc – volume: 20 start-page: 533 year: 2015 end-page: 539 article-title: Applying computation biology and “big data” to develop multiplex diagnostics for complex chronic diseases such as osteoarthritis publication-title: Biomarkers – volume: 23 start-page: 525 year: 2015 end-page: 531 article-title: Association of cartilage degeneration with four year weight gain—3T MRI data from the Osteoarthritis Initiative publication-title: Osteoarthritis Cartilage – volume: 52 start-page: 1103 year: 2004 end-page: 1109 article-title: Reduction of residual dipolar interaction in cartilage by spin‐lock technique publication-title: Magn Reson Med – volume: 6 start-page: 8581 year: 2015 article-title: Topological data analysis for discovery in preclinical spinal cord injury and traumatic brain injury publication-title: Nat Commun – volume: 22 start-page: 1367 year: 2014 end-page: 1376 article-title: Response of knee cartilage T1rho and T2 relaxation times to in vivo mechanical loading in individuals with and without knee osteoarthritis publication-title: Osteoarthritis Cartilage – volume: 84 start-page: 351 year: 1994 end-page: 358 article-title: The effects of specific medical conditions on the functional limitations of elders in the Framingham Study publication-title: Am J Public Health – volume: 58 start-page: 15 year: 2008 end-page: 25 article-title: Estimates of the prevalence of arthritis and other rheumatic conditions in the United States. Part I publication-title: Arthritis Rheum – volume: 38 start-page: 991 year: 2013 end-page: 1008 article-title: Quantitative MRI of articular cartilage and its clinical applications publication-title: J Magn Reson Imaging – volume: 46 start-page: 487 year: 2001 end-page: 493 article-title: T2 relaxation reveals spatial collagen architecture in articular cartilage: a comparative quantitative MRI and polarized light microscopic study publication-title: Magn Reson Med – volume: 43 start-page: 970 year: 2016 end-page: 980 article-title: Fully automatic analysis of the knee articular cartilage T1rho relaxation time using voxel‐based relaxometry publication-title: J Magn Reson Imaging – year: 2016 article-title: Composite metric R2‐R1rho (1/T2–1/T1rho) as a potential MR imaging biomarker associated with changes in pain after ACL reconstruction: A six‐month follow‐up publication-title: J Orthop Res – volume: 28 start-page: 88 year: 1998 end-page: 96 article-title: Knee injury and osteoarthritis outcome score (KOOS)—development of a self‐administered outcome measure publication-title: J Orthop Sports Phys Ther – volume: 16 start-page: 494 year: 1957 end-page: 502 article-title: Radiological assessment of osteo‐arthrosis publication-title: Ann Rheum Dis – volume: 37 start-page: 446 year: 2005 end-page: 456 article-title: Bone mineral density and vertebral fracture history are associated with incident and progressive radiographic knee osteoarthritis in elderly men and women: the Rotterdam Study publication-title: Bone – volume: 12 start-page: 120 year: 2008 end-page: 135 article-title: Inter‐subject comparison of MRI knee cartilage thickness publication-title: Med Image Anal – year: 2016 article-title: New insights into rotating frame relaxation at high field publication-title: NMR Biomed – volume: 55 start-page: 213 year: 2009 article-title: Western Ontario and McMaster Universities osteoarthritis index (WOMAC) publication-title: Aust J Physiother – volume: 29 start-page: 324 year: 2011 end-page: 334 article-title: Quantitative MRI using T1rho and T2 in human osteoarthritic cartilage specimens: correlation with biochemical measurements and histology publication-title: Magn Reson Imaging – volume: 74 start-page: 1353 year: 2015 end-page: 1359 article-title: Early T2 changes predict onset of radiographic knee osteoarthritis: data from the osteoarthritis initiative publication-title: Ann Rheum Dis – start-page: 257 year: 2015 end-page: 270 – volume: 12 start-page: 177 year: 2004 end-page: 190 article-title: Whole‐organ magnetic resonance imaging score (WORMS) of the knee in osteoarthritis publication-title: Osteoarthritis Cartilage – volume: 54 start-page: 929 year: 2005 end-page: 936 article-title: In vivo 3T spiral imaging based multi‐slice t1rho mapping of knee cartilage in osteoarthritis publication-title: Magn Reson Med – volume: 19 start-page: 781 year: 2006 end-page: 821 article-title: Sodium and T1rho MRI for molecular and diagnostic imaging of articular cartilage publication-title: NMR Biomed – volume: 16 start-page: 873 year: 2008 end-page: 882 article-title: Joint space narrowing and Kellgren‐Lawrence progression in knee osteoarthritis: an analytic literature synthesis publication-title: Osteoarthritis Cartilage – volume: 39 start-page: 1287 year: 2014 end-page: 1293 article-title: Simultaneous acquisition of T1rho and T2 quantification in knee cartilage: repeatability and diurnal variation publication-title: J Magn Reson Imaging – volume: 66 start-page: 1563 year: 2011 end-page: 1571 article-title: Contributions of chemical exchange to T1rho dispersion in a tissue model publication-title: Magn Reson Med – volume: 69 start-page: 1357 year: 2013 end-page: 1366 article-title: Contributions of chemical and diffusive exchange to T1rho dispersion publication-title: Magn Reson Med – volume: 45 start-page: 653 year: 2016 end-page: 660 article-title: MRI findings associated with development of incident knee pain over 48 months: data from the osteoarthritis initiative publication-title: Skeletal Radiol – volume: 29 start-page: 213 year: 2001 end-page: 218 article-title: Development and evaluation of an activity rating scale for disorders of the knee publication-title: Am J Sports Med – volume: 35 start-page: 4904 year: 2014 end-page: 4915 article-title: Topological methods reveal high and low functioning neuro‐phenotypes within fragile X syndrome publication-title: Hum Brain Mapp – volume: 23 start-page: 2214 year: 2015 end-page: 2223 article-title: Cartilage T1rho and T2 relaxation times: longitudinal reproducibility and variations using different coils, MR systems and sites publication-title: Osteoarthritis Cartilage – volume: 42 start-page: 377 year: 2009 end-page: 381 article-title: Research electronic data capture (REDCap)—a metadata‐driven methodology and workflow process for providing translational research informatics support publication-title: J Biomed Inform |
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To couple quantitative compositional MRI, gait analysis, and machine learning multidimensional data analysis to study osteoarthritis (OA). OA is a... To couple quantitative compositional MRI, gait analysis, and machine learning multidimensional data analysis to study osteoarthritis (OA). OA is a... |
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| SubjectTerms | machine learning MRI osteoarthritis precision medicine R2‐R1ρ T1ρ/T2 topological data analysis |
| Title | MRI and biomechanics multidimensional data analysis reveals R2‐R1ρ as an early predictor of cartilage lesion progression in knee osteoarthritis |
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