|dc.description.abstract||Background: Quantifying lean tissue or muscle mass in aging and clinical populations is of increasing importance due to emerging associations between low muscle mass and poor physical function, as well as increased rates of morbidity and mortality. Lean tissue or muscle mass can be quantified using accurate and precise modalities, such as dual-energy x-ray absorptiometry (DXA), computerized tomography (CT), and magnetic resonance imaging (MRI) scans; but these modalities have a number of practical limitations, including limited accessibility in clinical settings for body composition analysis, high cost and in some cases, radiation exposure. Ultrasound is emerging as a modality that can accurately predict muscle mass from measures of muscle thickness and may circumvent many of these limitations associated with DXA, CT and MRI. Numerous ultrasound protocols for acquiring muscle thickness measures, such as a previously developed 9-site protocol, utilize several anatomical landmarks to enhance the accuracy in prediction of muscle mass. However, these protocols: 1) may be a time-burden for clinical staff and patients, and 2) are performed in a standing posture and include posterior muscle thickness measures, which may not be feasible in many hospitalized patients who may be less mobile. Viable bedside ultrasound protocols, such as the 4-site protocol (measures the quadriceps muscle thickness), have been developed and utilized in the intensive care unit, but have yet to comprehensively assessed for accuracy in predicting muscle mass.
Objectives: The primary objectives of this thesis were to: 1) compare the agreement between the 4-site ultrasound protocol and appendicular lean tissue mass measured by DXA, 2) develop an optimized bedside-friendly protocol to predict appendicular lean tissue, using the 4-site protocol and additional accessible muscle thicknesses and easily obtained covariates, and 3) assess the ability of the optimized ultrasound protocol to identify individuals with lower than normal lean tissue mass. The secondary objectives were to: 1) compare the accuracy of predicting lean tissue mass using minimal and maximal compression of the 4-site protocol, 2) apply the 9-site protocol in a supine posture to obtain additional accessible muscle thicknesses and to compare the accuracy of lean tissue predictions to the 4-site and optimized ultrasound protocols, and 3) assess the reliability of the 4-site protocol.
Methods: Healthy adults (≥18 years) were recruited for whole body DXA scans and ultrasound assessments on a single day. Whole body DXA scans were used to quantify appendicular lean tissue mass, the lean soft tissue in the upper and lower limbs, for each participant. Participants were identified as having lower than normal lean tissue if their appendicular lean tissue mass (kg) divided by their height (m) squared, was below previously established cut-points of 7.26 kg/m2 and 5.45 kg/m2 for males and females respectively. The 4-site and 9-site ultrasound protocols were performed on participants in a supine or prone position, depending on the muscle thickness measured. The 4-site protocol quantifies the muscle thickness of the rectus femoris and vastus intermedialis, at the mid-point and lower third, between the anterior superior iliac spine and the upper pole of the patella. The 9-site protocol quantifies anterior and posterior muscle thicknesses of the upper arm, trunk, upper leg and lower leg and the anterior surface of the forearm. Inter-rater and intra-rater reliability of the 4-site protocol was performed in a subset of participants.
Results: We recruited 96 participants (57% females), with a median (interquartile range) age of 36.5 (24.0-72.0) years, BMI of 24.3 (22.3-27.3) kg/m2 and body fat of 30.2 (24.3-36.8) %. Significant differences for appendicular lean tissue mass and the 4-site muscle thicknesses were observed between males and females (p<0.001) and young and older adults (p<0.001). Regression analysis revealed a strong association between the 4-site muscle thickness and appendicular lean tissue mass, r2=0.72 (p<0.001), but accounting for age, sex and the additional muscle thickness of the anterior upper arm, improved the association to r2=0.91 (p<0.001). Using DXA based low lean tissue mass, 18% of participants were identified as below their sex specific cut-points. The optimized ultrasound protocol demonstrated a strong ability (area under the curve=0.89) to identify individuals with lower than normal lean tissue mass.
Conclusions: This thesis demonstrated that a previously developed 4-site protocol strongly predicts appendicular lean tissue mass, but accounting for additional muscle thicknesses of the anterior upper arm and age and sex, greatly improves the predictive accuracy. Furthermore the optimized protocol strongly identifies individuals with lower than normal lean tissue mass. These results demonstrate that this viable bedside protocol may be useful for assessing lean tissue mass in clinical settings, but external validation in clinical populations is necessary to ensure the robustness of these findings.||en