Quantitative 3D imaging parameters improve prediction of hip osteoarthritis outcome

Autor: T Turmezei, H. Jonsson, Thor Aspelund, Kenneth E. S. Poole, Andrew H. Gee, Graham M. Treece, Vilmundur Gudnason, Sigurdur Sigurdsson
Přispěvatelé: Turmezei, T D [0000-0003-0365-8054], Treece, G M [0000-0003-0047-6845], Aspelund, T [0000-0002-7998-5433], Apollo - University of Cambridge Repository, Læknadeild (HÍ), Faculty of Medicine (UI), Heilbrigðisvísindasvið (HÍ), School of Health Sciences (UI), Háskóli Íslands, University of Iceland, Turmezei, T. D. [0000-0003-0365-8054], Treece, G. M. [0000-0003-0047-6845], Aspelund, T. [0000-0002-7998-5433], Turmezei, TD [0000-0003-0365-8054], Treece, GM [0000-0003-0047-6845]
Rok vydání: 2020
Předmět:
Male
Computer science
123
medicine.medical_treatment
Radiography
lcsh:Medicine
Osteoarthritis
Osteoarthritis
Hip

030218 nuclear medicine & medical imaging
0302 clinical medicine
Odds Ratio
692/4023/1670/407
lcsh:Science
Multidisciplinary
Statistics
article
Middle Aged
Liðamót
Outcome (probability)
3. Good health
Slitgigt
639/166/985
Female
Hip Joint
139
Biomedical engineering
3D
Adult
141
musculoskeletal diseases
medicine.medical_specialty
Joint replacement
639/705/531
Statistical parametric mapping
Predictive markers
03 medical and health sciences
Physical medicine and rehabilitation
Imaging
Three-Dimensional

692/53/2423
Therapy development
medicine
Hip osteoarthritis
Humans
Joint (geology)
Aged
030203 arthritis & rheumatology
Þrívídd
business.industry
lcsh:R
Gold standard (test)
medicine.disease
Case-Control Studies
lcsh:Q
business
Zdroj: Scientific Reports
Scientific Reports, Vol 10, Iss 1, Pp 1-11 (2020)
Popis: Publisher's version (útgefin grein)
Osteoarthritis is an increasingly important health problem for which the main treatment remains joint replacement. Therapy developments have been hampered by a lack of biomarkers that can reliably predict disease, while 2D radiographs interpreted by human observers are still the gold standard for clinical trial imaging assessment. We propose a 3D approach using computed tomography—a fast, readily available clinical technique—that can be applied in the assessment of osteoarthritis using a new quantitative 3D analysis technique called joint space mapping (JSM). We demonstrate the application of JSM at the hip in 263 healthy older adults from the AGES-Reykjavík cohort, examining relationships between 3D joint space width, 3D joint shape, and future joint replacement. Using JSM, statistical shape modelling, and statistical parametric mapping, we show an 18% improvement in prediction of joint replacement using 3D metrics combined with radiographic Kellgren & Lawrence grade (AUC 0.86) over the existing 2D FDA-approved gold standard of minimum 2D joint space width (AUC 0.73). We also show that assessment of joint asymmetry can reveal significant differences between individuals destined for joint replacement versus controls at regions of the joint that are not captured by radiographs. This technique is immediately implementable with standard imaging technologies.
K.P. acknowledges the support of Cambridge NIHR Biomedical Research Centre. T.T. thanks the Wellcome Trust for funding support (100676/Z/12/Z) for part of this work. All authors acknowledge funding support grants from the National Institute on Aging (NO1-AG-1-2100), Bethesda, USA, and the Icelandic Government. All authors thank Dr Ilya Burkov, formerly PhD student at the University of Cambridge, for his work on segmentation of the proximal femur from CT data, Professor Lee Shepstone, University of East Anglia, for guidance with generalised estimating equation analysis, and Professor Karl Friston, University College London, for guidance with statistical parametric mapping analysis.
Databáze: OpenAIRE