Belzunce, MA;
Henckel, J;
Fotiadou, A;
Di Laura, A;
Hart, A;
(2020)
Automated measurement of fat infiltration in the hip abductors from Dixon magnetic resonance imaging.
Magnetic Resonance Imaging
, 72
pp. 61-70.
10.1016/j.mri.2020.06.019.
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Abstract
PURPOSE: Intramuscular fat infiltration is a dynamic process, in response to exercise and muscle health, which can be quantified by estimating fat fraction (FF) from Dixon MRI. Healthy hip abductor muscles are a good indicator of a healthy hip and an active lifestyle as they have a fundamental role in walking. The automated measurement of the abductors' FF requires the challenging task of segmenting them. We aimed to design, develop and evaluate a multi-atlas based method for automated measurement of fat fraction in the main hip abductor muscles: gluteus maximus (GMAX), gluteus medius (GMED), gluteus minimus (GMIN) and tensor fasciae latae (TFL). METHOD: We collected and manually segmented Dixon MR images of 10 healthy individuals and 7 patients who underwent MRI for hip problems. Twelve of them were selected to build an atlas library used to implement the automated multi-atlas segmentation method. We compared the FF in the hip abductor muscles for the automated and manual segmentations for both healthy and patients groups. Measures of average and spread were reported for FF for both methods. We used the root mean square error (RMSE) to quantify the method accuracy. A linear regression model was used to explain the relationship between FF for automated and manual segmentations. RESULTS: The automated median (IQR) FF was 20.0(16.0-26.4) %, 14.3(10.9-16.5) %, 15.5(13.9-18.6) % and 16.2(13.5-25.6) % for GMAX, GMED, GMIN and TFL respectively, with a FF RMSE of 1.6%, 0.8%, 2.1%, 2.7%. A strong linear correlation (R2 = 0.93, p < .001, m = 0.99) was found between the FF from automated and manual segmentations. The mean FF was higher in patients than in healthy subjects. CONCLUSION: The automated measurement of FF of hip abductor muscles from Dixon MRI had good agreement with FF measurements from manually segmented images. The method was accurate for both healthy and patients groups.
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