Use of multispectral magnetic resonance imaging analysis to quantify erosive changes in the hands of patients with RA

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Arthritis Rheum. 2004 Mar;50(3):716-24.

Use of multispectral magnetic resonance imaging analysis to quantify

erosive changes in the hands of patients with rheumatoid arthritis:

short-term and long-term longitudinal studies.

Ostrowitzki S, Redei J, Lynch JA, Carano RA, Zaim S, Miaux Y, Genant HK.

University of California, San Francisco, 94143, USA.

OBJECTIVE: Magnetic resonance imaging (MRI) has been shown to be more

sensitive than radiography for detecting bone erosions in rheumatoid

arthritis (RA). Semiquantitative scoring based on visual image

assessment has been introduced. However, there is considerable interest

in true quantitative measures, particularly in the context of clinical

trials designed to show differences between treatment groups. This study

was undertaken to investigate the use of a new quantitative approach,

multispectral (MS) image analysis, for assessing erosive change.

METHODS: T1-weighted spin-echo (SE) and fat-suppressed gradient-echo

(GE) sequences of metacarpophalangeal joints of the dominant hand were

acquired at various time points throughout a 2-year period. MS analysis

was applied to all images, resulting in segmentation into a generalized

bone and a soft tissue class. Voxel changes from one to the other class

identified apparent bone lesion volume change (Delta BLV). MR images

were also visually scored for erosions (E score). All analyses were

performed separately, on a per-joint basis, for short-term and long-term

data sets. RESULTS: Analysis of variance with adjustment for individual

effect revealed similar results in the short-term and the long-term

studies, using either GE or SE images for visual assessment. Patients

with an increase in E score on visual assessment had a significantly

higher Delta BLV than those without.

CONCLUSION: Temporal MS analysis of MRIs can be used to detect and

quantify erosive changes in RA. This semiautomated method may be useful

for demonstrating differences between treatment groups in clinical

trials.

PMID: 15022310

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