Paper
13 March 2013 Automatic measurement of wrist synovitis from contrast-enhanced MRI: a registration-centered approach
Peter Mysling, Sune Darkner, Jon Sporring, Erik Dam, Martin Lillholm
Author Affiliations +
Proceedings Volume 8669, Medical Imaging 2013: Image Processing; 86692U (2013) https://doi.org/10.1117/12.2006201
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States
Abstract
MRI-determined measurement of synovial inflammation (synovitis) from hand MRIs has recently gained considerable popularity as a secondary marker in rheumatoid arthritis (RA) clinical trials. The currently accepted scoring systems are, however, purely semi-quantitative and rely on assessment from a trained radiologist. We propose a novel, fully automatic technique for quantitative wrist synovitis measurement from two MRIs acquired before and after contrast agent injection. The technique estimates the volume of the synovial inflammation in three steps. First, the wrist synovial membrane is segmented using multi-atlas B-spline based freeform registration. Second, positioning differences between the pre- and post-contrast acquisitions are corrected by rigid registration. Finally, wrist synovitis is quantified from the difference between the pre- and post-contrast sequences in the region of the segmented synovium. We evaluate the proposed technique on a data set of nineteen patients with acquisitions at two time points in a leave-one-patient-out fashion. Our experiments show that we are able to perform synovitis measurement with good correlation to manual semi-quantitative RAMRIS scores for both static (r=0.84) and longitudinal (r=0.87) scoring. These results compare favorably to the RAMRIS inter-observer variability.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Peter Mysling, Sune Darkner, Jon Sporring, Erik Dam, and Martin Lillholm "Automatic measurement of wrist synovitis from contrast-enhanced MRI: a registration-centered approach", Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 86692U (13 March 2013); https://doi.org/10.1117/12.2006201
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Cited by 2 scholarly publications.
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KEYWORDS
Magnetic resonance imaging

Bone

Image segmentation

Tissues

Inflammation

Clinical trials

Neodymium

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