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




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BMC Musculoskeletal Disorders

, 6:10

First Online: 20 February 2005Received: 10 September 2004Accepted: 20 February 2005

Abstract

BackgroundMRI 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.

MethodsA 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 and Altman plots.

ResultsCompared 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.

ConclusionSampling 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.

Electronic supplementary materialThe online version of this article doi:10.1186-1471-2474-6-10 contains supplementary material, which is available to authorized users.

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Author: Guangju Zhai - Changhai Ding - Flavia Cicuttini - Graeme Jones

Source: https://link.springer.com/







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