Pixel-by-pixel analysis of DCE-MRI curve shape patterns in knees of active and inactive juvenile idiopathic arthritis patients

Objectives To compare DCE-MRI parameters and the relative number of time–intensity curve (TIC) shapes as derived from pixel-by-pixel DCE-MRI TIC shape analysis between knees of clinically active and inactive juvenile idiopathic arthritis (JIA) patients. Methods DCE-MRI data sets were prospectively o...

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Bibliographic Details
Published in:European radiology 2014-07, Vol.24 (7), p.1686-1693
Main Authors: Hemke, Robert, Lavini, Cristina, Nusman, Charlotte M., van den Berg, J. Merlijn, Dolman, Koert M., Schonenberg-Meinema, Dieneke, van Rossum, Marion A. J., Kuijpers, Taco W., Maas, Mario
Format: Article
Language:English
Subjects:
Adolescent
Arthritis
Arthritis, Juvenile - diagnosis
Cartilage
Contrast Media
Diagnostic Radiology
Female
Humans
Image Processing, Computer-Assisted
Imaging
Inflammation
Internal Medicine
Interventional Radiology
Knee
Knee Joint - pathology
Magnetic resonance imaging
Magnetic Resonance Imaging - methods
Male
Medicine
Medicine & Public Health
Neuroradiology
Osteoarthritis, Knee - diagnosis
Pediatric
Pediatrics
Prospective Studies
Radiology
Reproducibility of Results
Rheumatology
Ultrasound
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Summary:Objectives To compare DCE-MRI parameters and the relative number of time–intensity curve (TIC) shapes as derived from pixel-by-pixel DCE-MRI TIC shape analysis between knees of clinically active and inactive juvenile idiopathic arthritis (JIA) patients. Methods DCE-MRI data sets were prospectively obtained. Patients were classified into two clinical groups: active disease ( n  = 43) and inactive disease ( n  = 34). Parametric maps, showing seven different TIC shape types, were created per slice. Statistical measures of different TIC shapes, maximal enhancement (ME), maximal initial slope (MIS), initial area under the curve (iAUC), time-to-peak (TTP), enhancing volume (EV), volume transfer constant ( K trans ), extravascular space fractional volume ( V e ) and reverse volume transfer constant ( k ep ) of each voxel were calculated in a three-dimensional volume-of-interest of the synovial membrane. Results Imaging findings from 77 JIA patients were analysed. Significantly higher numbers of TIC shape 4 ( P  = 0.008), median ME ( P  = 0.015), MIS ( P  = 0.001) and iAUC ( P  = 0.002) were observed in clinically active compared with inactive patients. TIC shape 5 showed higher presence in the clinically inactive patients ( P  = 0.036). Conclusions The pixel-by-pixel DCE-MRI TIC shape analysis method proved capable of differentiating clinically active from inactive JIA patients by the difference in the number of TIC shapes, as well as the descriptive parameters ME, MIS and iAUC. Key Points • The pixel-by-pixel TIC shape method differentiates clinically active and inactive JIA patients • Significantly higher numbers of TIC shape 4 were observed in clinically active patients • DCE-MRI parameters ME, MIS and iAUC differ between active and inactive patients • The pixel-by-pixel analysis method allows direct visualization of the heterogeneously distributed disease • The DCE-MRI TIC shape method may serve as a quantitative outcome measure
ISSN:0938-7994
1432-1084
DOI:10.1007/s00330-014-3168-z