Precision of MRI-based body composition measurements of postmenopausal women

Abstract

ObjectivesTo determine precision of magnetic resonance imaging (MRI) based fat and muscle quantification in a group of postmenopausal women. Furthermore, to extend the method to individual muscles relevant to upper-body exercise.Materials and methodsThis was a sub-study to a randomized control trial investigating effects of resistance training to decrease hot flushes in postmenopausal women. Thirty-six women were included, mean age 56 ± 6 years. Each subject was scanned twice with a 3.0T MR-scanner using a whole-body Dixon protocol. Water and fat images were calculated using a 6-peak lipid model including R2*-correction. Body composition analyses were performed to measure visceral and subcutaneous fat volumes, lean volumes and muscle fat infiltration (MFI) of the muscle groups’ thigh muscles, lower leg muscles, and abdominal muscles, as well as the three individual muscles pectoralis, latissimus, and rhomboideus. Analysis was performed using a multi-atlas, calibrated water-fat separated quantification method. Liver-fat was measured as average proton density fat-fraction (PDFF) of three regions-of-interest. Precision was determined with Bland-Altman analysis, repeatability, and coefficient of variation.ResultsAll of the 36 included women were successfully scanned and analysed. The coefficient of variation was 1.1% to 1.5% for abdominal fat compartments (visceral and subcutaneous), 0.8% to 1.9% for volumes of muscle groups (thigh, lower leg, and abdomen), and 2.3% to 7.0% for individual muscle volumes (pectoralis, latissimus, and rhomboideus). Limits of agreement for MFI was within ± 2.06% for muscle groups and within ± 5.13% for individual muscles. The limits of agreement for liver PDFF was within ± 1.9%.ConclusionWhole-body Dixon MRI could characterize a range of different fat and muscle compartments with high precision, including individual muscles, in the study-group of postmenopausal women. The inclusion of individual muscles, calculated from the same scan, enables analysis for specific intervention programs and studies.

Body Composition Profiling in the UK Biobank Imaging Study

“…Each predicted probability, calculated using the log odds from the model outputs including BCP, was divided by that from the model including only sex and age. Subjects from three BMI intervals, 24 (normal weight), 28 (overweight), and 32 (obesity), all approximately 65 years old, were used to exemplify.…”

Automated assessment of regional muscle volume and hypertrophy using MRI

“…Water, fat, in-phase and out-of-phase images were calculated at the scanner. All datasets were exported to AMRA ® Researcher where quantification of the fat-free muscle volume and the proportion of intra-muscular fat of the bilateral m. quadriceps using a non-rigid multi-atlas segmentation technique was performed 13,14,16 . A manual quality assurance step was thereafter applied where five datasets failed due to image distortion.…”

“…The last step is to quantify the muscle tissue volume based on the tissue classification and the local fat signal 14 . Despite this major advancement and the report of excellent test-retest reliability and correlation with manual segmentation 13,15,16 , the method has not yet been developed to distinguish between specific muscle groups of the lower limbs. This is important in the sports science setting where interventions often target specific muscles that are vital for performance in a specific context.…”

Update on Whole-body MRI in Musculoskeletal Applications

“…7 STIR is the preferred fluid-sensitive sequence because it yields more consistent fat saturation than frequency-selective (chemical) fat suppression acquisition, especially in some anatomical areas such as the convexities in the cervical and thoracic regions. 9,10 Anatomical WB-MRI sequences should be combined with DWI using high b-values (b > 800 s/mm 2 ) that provide both qualitative and quantitative information through the apparent diffusion coefficient (ADC).…”