Fast and robust analysis of dynamic contrast enhanced MRI datasets.
A fully automated method for quantitative analysis of dynamic contrast-enhanced MRI data acquired with low and high field scanners, using spin echo and gradient echo sequences, depicting various joints is presented. The method incorporates efficient pre-processing techniques and a robust algorithm for quantitative assessment of dynamic signal intensity vs. time curves. It provides differentiated information to the reader regarding areas with the most active perfusion and permits depiction of different disease activity in separate compartments of a joint. Additionally, it provides information on the speed of contrast agent uptake by various tissues. The method delivers objective and easily reproducible results, which have been favourably viewed by a number of medical experts.
Kubassova
Olga
O
School of Computing, University of Leeds, UK. olga@comp.leeds.ac.uk
Boesen
Mikael
M
Boyle
Roger D
RD
Cimmino
Marco A
MA
Jensen
Karl E
KE
Bliddal
Henning
H
Radjenovic
Alexandra
A
D000465:Algorithms; D001172:Arthritis, Rheumatoid / Q000175:diagnosis*; D001185:Artificial Intelligence; D003287:Contrast Media; D016208:Databases, Factual; D019786:Gadolinium DTPA; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013997:Time Factors
D003287:Contrast Media; D019786:Gadolinium DTPA