Abstract
Objective The goal of this study was to compare the semiquantitative Goutallier classification for fat infiltration with quantitative fat-fraction derived from a magnetic resonance imaging (MRI) chemical shift-based water/fat separation technique. Methods Sixty-two women (age 61±6 years), 27 of whom had diabetes, underwent MRI of the calf using a T1- weighted fast spin-echo sequence and a six-echo spoiled gradient-echo sequence at 3 T. Water/fat images and fat fraction maps were reconstructed using the IDEAL algorithm with T2 correction and a multi-peak model for the fat spectrum. Two radiologists scored fat infiltration on the T1- weighted images using the Goutallier classification in six muscle compartments. Spearman correlations between the Goutallier grades and the fat fraction were calculated; in addition, intra-observer and inter-observer agreement were calculated. Results A significant correlation between the clinical grading and the fat fraction values was found for all muscle compartments (P<0.0001, R values ranging from 0.79 to 0.88). Goutallier grades 0-4 had a fat fraction ranging from 3.5 to 19%. Intra-observer and inter-observer agreement values of 0.83 and 0.81 were calculated for the semiquantitative grading. Conclusion Semi-quantitative grading of intramuscular fat and quantitative fat fraction were significantly correlated and both techniques had excellent reproducibility. However, the clinical grading was found to overestimate muscle fat. Key Points ̇ Fat infiltration of muscle commonly occurs in many metabolic and neuromuscular diseases. ̇ Image-based semi-quantitative classifications for assessing fat infiltration are not well validated. ̇ Quantitative MRI techniques provide an accurate assessment of muscle fat.
Original language | English |
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Pages (from-to) | 1592-1600 |
Number of pages | 9 |
Journal | European Radiology |
Volume | 22 |
Issue number | 7 |
DOIs | |
State | Published - Jul 2012 |
Externally published | Yes |
Keywords
- Adipose tissue
- Keywords Skeletal muscle
- Magnetic resonance imaging
- Metabolic syndrome
- Neuromuscular disease
- Sarcopenia