Literature DB >> 20532781

Single breath-hold magnetic resonance cine imaging for fast assessment of global and regional left ventricular function in clinical routine.

Kai Nassenstein1, Holger Eberle, Stefan Maderwald, Christoph J Jensen, Christina Heilmaier, Thomas Schlosser, Oliver Bruder.   

Abstract

OBJECTIVE: To evaluate a TGRAPPA (temporal parallel acquisition technique)-accelerated, single breath-hold multi-slice cine imaging approach for the assessment of left ventricular (LV) function.
METHODS: One hundred eleven patients were examined at 1.5 T. Cine imaging was performed with single-slice breath-hold acquisitions in short-axis orientation using a SSFP (TR 2.63 ms, TE 1.12 ms, FA 72°) sequence and a TGRAPPA SSFP (TR 2.66 ms, TE 1.11 ms, FA 72°, AF 3) sequence, which covered the entire LV in multiple short-axis slices during a single breath-hold. End-diastolic (EDV), end-systolic (ESV), stroke volumes (SV), ejection fraction (EF), muscle mass (MM) and regional wall motion were assessed for both data sets.
RESULTS: Single breath-hold imaging was feasible in 108 patients. Excellent correlations were observed for all volumetric parameters derived from both data sets (all r > 0.97). While EDV and ESV showed marginally lower values for single breath-hold imaging (EDV: -1.6 ± 7.9 ml; ESV: -1.8 ± 6.0 ml, p < 0.05), no differences were observed for SV, EF, MM and regional wall motion assessment. Single breath-hold imaging required significant shorter acquisition times (28 ± 6 s vs. 335 ± 87 s).
CONCLUSION: TGRAPPA-accelerated multi-slice SSPF imaging allows for fast and accurate assessment of regional and global LV function within a single breath-hold.

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Year:  2010        PMID: 20532781     DOI: 10.1007/s00330-010-1827-2

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  23 in total

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3.  Single-Breath-Hold Evaluation of Cardiac Function with Use of Time-Resolved Parallel Cardiac Magnetic Resonance.

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6.  Quantification of Right and Left Ventricular Function in Cardiac MR Imaging: Comparison of Semiautomatic and Manual Segmentation Algorithms.

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