Detection and quantification of valvular heart disease with dynamic cardiac MR imaging.
Magnetic resonance (MR) imaging is rapidly gaining acceptance as an accurate, reproducible, noninvasive method for optimal assessment of structural and functional parameters in patients with valvular heart disease. The severity of valvular regurgitation can be evaluated with cine gradient-echo MR imaging, which allows measurement of the area of the signal void corresponding to the abnormal flow jet. Alternatively, this modality can be used to obtain ventricular volumetric measurements and calculate the regurgitant fraction, or velocity-encoded cine (VEC) MR imaging can be used to quantify regurgitant blood flow. The severity of valvular stenosis can be determined by evaluating the flow jet and associated findings with either modality or by using VEC MR imaging to calculate the transvalvular pressure gradient and valve area. Dynamic MR imaging allows accurate assessment of ventricular function and comprehensive evaluation of pathophysiologic changes. In addition, good interstudy reproducibility suggests a role for VEC MR imaging in assessing the effects of therapeutic intervention and monitoring regurgitant fraction, thereby helping in surgical planning and the prevention of ventricular dysfunction. With greater cost-effectiveness and the increasing availability of new hardware and more advanced techniques, MR imaging will become a routine procedure in valvular heart disease.
Didier
D
D
Department of Radiology, Hôpital Cantonal Universitaire de Genève, 24 rue Micheli du Crest, 1211 Geneva 14, Switzerland. didier@dim.hcuge.ch
Ratib
O
O
Lerch
R
R
Friedli
B
B
D001783:Blood Flow Velocity; D003937:Diagnosis, Differential; D006349:Heart Valve Diseases / Q000175:diagnosis* / Q000503:physiopathology; D006351:Heart Valves / Q000473:pathology*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D019028:Magnetic Resonance Imaging, Cine; D009200:Myocardial Contraction; D015203:Reproducibility of Results; D012720:Severity of Illness Index