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Optimal sampling of MRI slices for the assessment of knee cartilage volume for cross-sectional and longitudinal studies


Zhai, G and Ding, C and Cicuttini, F and Jones, G, Optimal sampling of MRI slices for the assessment of knee cartilage volume for cross-sectional and longitudinal studies, BMC Musculoskeletal Disorders, 6, (10) EJ ISSN 1471-2474 (2005) [Refereed Article]

DOI: doi:10.1186/1471-2474-6-10


Background: MRI slices of 1.5 mm thickness have been used in both cross sectional and longitudinal studies of osteoarthritis, but is difficult to apply to large studies as most techniques used in measuring knee cartilage volumes require substantial post-image processing. The aim of this study was to determine the optimal sampling of 1.5 mm thick slices of MRI scans to estimate knee cartilage volume in males and females for cross-sectional and longitudinal studies. Methods: A total of 150 subjects had a sagittal T1-weighted fat-suppressed MRI scan of the right knee at a partition thickness of 1.5 mm to determine their cartilage volume. Fifty subjects had both baseline and 2-year follow up MRI scans. Lateral, medial tibial and patellar cartilage volumes were calculated with different samples from 1.5 mm thick slices by extracting one in two, one in three, and one in four to compare to cartilage volume and its rate of change. Agreement was assessed by means of intraclass correlation coefficient (ICC) and Bland & Altman plots. Results: Compared to the whole sample of 1.5 mm thick slices, measuring every second to fourth slice led to very little under or over estimation in cartilage volume and its annual change. At all sites and subgroups, measuring every second slice had less than 1% mean difference in cartilage volume and its annual rate of change with all ICCs ≥ 0.98. Conclusion: Sampling alternate 1.5 mm thick MRI slices is sufficient for knee cartilage volume measurement in cross-sectional and longitudinal epidemiological studies with little increase in measurement error. This approach will lead to a substantial decrease in post-scan processing time. © 2005 Zhai et al; licensee BioMed Central Ltd.

Item Details

Item Type:Refereed Article
Research Division:Health Sciences
Research Group:Epidemiology
Research Field:Epidemiology not elsewhere classified
Objective Division:Health
Objective Group:Clinical health
Objective Field:Clinical health not elsewhere classified
UTAS Author:Zhai, G (Dr Guangju Zhai)
UTAS Author:Ding, C (Professor Chang-Hai Ding)
UTAS Author:Jones, G (Professor Graeme Jones)
ID Code:37901
Year Published:2005
Web of Science® Times Cited:6
Deposited By:Menzies Institute for Medical Research
Deposited On:2005-08-01
Last Modified:2012-03-05

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