Myocardial tagging with steady state free precession techniques and semi-automatic postprocessing--impact on diagnostic value.
Our aim was to determine the diagnostic value of myocardial tagging sequences with regard to the evaluable share of the cardiac cycle. Thirty-three patients were examined at 1.5 T using tagging sequences with gradient-echo (GRE) readout, 18 patients at 1.5 T with steady-state free precession (SSFP), and 11 patients at 3 T using GRE. Two observers graded image quality and determined the share of the cardiac cycle for which postprocessing could be performed (1, optimal; 2, little interaction; 3, whole cycle assessable; 4, diastole non-assessable; 5, systole incomplete; 6, non-diagnostic). With GRE at 1.5 T, median image quality was 4.0 (95% CI 4.0-5.0), while it was significantly better with 2.0 (2.0-3.0) using the SSFP technique and similar at 3 T with 2.9 (1.7-3.5). With GRE at 1.5 T, systole could be assessed in 69% of patients, and an evaluation of the whole cardiac cycle was not possible. With the SSFP sequence at 1.5 T and GRE at 3 T, an evaluation of the whole cardiac cycle was possible in 71% and 70% of the patients, respectively, and systole was assessable in all patients. Tagging sequences with SSFP readout at 1.5 T make a semi-automatic evaluation of the whole cardiac cycle feasible in a large share of patients.
Johnson
Thorsten R C
TR
Department of Clinical Radiology, Grosshadern Hospital, Ludwig-Maximilians-University, Munich, Germany. thorsten.johnson@med.uni-muenchen.de
Bayrhof
Nicole
N
Huber
Armin
A
Kuijer
Joost P A
JP
Luechinger
Roger
R
Dietrich
Olaf
O
Stoevesandt
Dietrich
D
Pedersen
Dorthe
D
Reiser
Maximilian F
MF
Schoenberg
Stefan O
SO
D005260:Female; D006331:Heart Diseases / Q000175:diagnosis* / Q000503:physiopathology; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D019028:Magnetic Resonance Imaging, Cine / Q000379:methods*; D008297:Male; D009200:Myocardial Contraction / Q000502:physiology; D012189:Retrospective Studies; D018709:Statistics, Nonparametric