Arthritis & Rheumatism, Volume 60,
October 2009 Abstract Supplement

The 2009 ACR/ARHP Annual Scientific Meeting
Philadelphia October 16-21, 2009.


Automatic Computer Aided Quantification of Synovitis in Rheumatoid Arthritis Using Dynamic MRI and the Impact of Movement Correction On Signal to Noise Ratio (SNR) and Region of Interest (ROI) Analysis

Boesen1,  Mikael, Kubassova2,  Olga, Cimmino3,  Marco A., Ostergaard4,  Mikkel, Danneskiold-Samsoe1,  Bente, Bliddal1,  Henning

Parker Institute, Frederiksberg, Denmark
Image Analysis, Leeds, England
University of Genova, Genova, Italy
University Hospitals Hvidovre and Gentofte, Copenhagen, Denmark

Background:

Dynamic Contrast Enhanced MRI (DCE-MRI), based on repeated imaging of the same few MRI slices with a few seconds' interval after intravenous contrast injection, correlates closely to histological inflammatory activity and is a promising tool to asses the early response to treatment, potentially before volume changes and changes in OMERACT RAMRIS scores occur. Analysis of DCE-MRI is usually done by manual selection of areas with most enhancement (regions of interest, ROIs), but variable ROI positioning and movements during imaging, introduce large variation in the results obtained from the dynamic curves using the ROI method (1–2).

Purpose:

To analyse DCE-MRI data from RA patients using a newly developed algorithm that eliminate motion artefacts and to evaluate the impact of motion on SNR and ROI results

Methods:

DCE-MRI data were acquired in wrists of 50 RA patients and 5 controls, by repeatedly obtaining 3 axial or coronal T1-weighted images every 10–15 seconds immediately after iv 0.1 mmol/kg Gd-DTPA, using a 0.2T Esaote C-scan or E-scan (22–30 repetitions). Motion artefacts were eliminated using an intensity-based algorithm which corrects for movements and changes in brightness and contrast in every pixel. ROIs of 25mm2 were positioned automatically in the area of most enhancement using a custom made computer programme. Maximum enhancement (ME) and initial rate of enhancement (IRE) were calculated from the ROIs.

Results:

Motion artefacts in all 3 planes were reduced from 1.3mm±7mm to 1mm±1.5mm shift and 7±6degree to 1±0.4degree rotation. This increased SNR by a factor 3 on average, removed image blurring and reduced the variations in the shape of dynamic curves extracted from the ROIs. This consequently reduced variation in measurements of ME and IRE (statistical f-test was applied). In controls, the IRE was reduced from 0.21±0.1 to 0.12±0.02 [%/sec] and in ME from 0.35±0.23 to 0.1±0.01 [%]. In patients, IRE increased from 0.5±0.16 to 0.6±0.02 [%/sec] and ME from 0.53±0.3 to 0.7±0.02 [%].

Conclusion:

Elimination of motion artefacts significantly reduced artefactual enhancement and increased SNR. Reduced variation in ROI measurements significantly influenced the accuracy of quantitative analysis of inflammation. This supports the use of DCE-MRI augmented by motion reduction algorithms for more robust and valid analysis of synovitis in RA patients.

1. McQueen, FM, et al.Arthritis Rheum 2004;50:674–5.

2. Kubassova, , et al.Medical Image Computing and Computer Assisted Intervention 2008

To cite this abstract, please use the following information:
Boesen, Mikael, Kubassova, Olga, Cimmino, Marco A., Ostergaard, Mikkel, Danneskiold-Samsoe, Bente, Bliddal, Henning; Automatic Computer Aided Quantification of Synovitis in Rheumatoid Arthritis Using Dynamic MRI and the Impact of Movement Correction On Signal to Noise Ratio (SNR) and Region of Interest (ROI) Analysis [abstract]. Arthritis Rheum 2009;60 Suppl 10 :773
DOI: 10.1002/art.25853

Abstract Supplement

Meeting Menu

2009 ACR/ARHP