Biomechanical models and human movement data largely relies on obtained segmental values to estimate and replicate the true anatomical structure of its subjects (Durkin et al., 2002; Lee et al., 2009a; Pearsall and Costigan, 1999; Pearsall and Reid, 1994; Rao et al., 2006). In particular, body segment parameters and body composition components provide important data for biomechanists and exercise physiologists in the analysis of human movement and health status in both sporting and clinical contexts (Lee et al., 2009a; Pfeiffer et al., 2010; Pearsall and Reid, 1994; Rao et al., 2006). Biomechanically, segmental anthropometric parameters are routinely estimated for use within inverse dynamics equations in order to calculate intersegmental forces and net joint moments during gait, kicking, throwing and striking actions (Davids et al., 2000; Ganley and Powers, 2004a; 2004b; Lee et al., 2009b; Pearsall and Costigan, 1999; Putnam, 1991; 1993; Rao et al., 2006). Physiologically, body composition and tissue mass assessments of bone, muscle and fat are used to diagnose and monitor health status and changes in paediatric, athletic, adult and geriatric populations, while also used to examine the interventional efficacy of exercise, pharmacology or nutritional programs (Abrahamyan et al., 2008; Beaumesnil et al., 2011; Bridge et al., 2009;Fawzy et al., 2011; Pfeiffer et al., 2010; Veale et al., 2010; Miller et al., 2009).

Dual energy x-ray absorptiometry (DXA) is a commonly used two-dimensional in-vivo imaging technique which is able to capture full body projections of mass densities through x-ray technology (Pfeiffer et al., 2010; Durkin et al., 2002). In comparison with other imaging techniques, it is inexpensive, exposes the participant to substantially less radiation, is widely available for use, and produces minimal error when employed to ascertain body segment parameter measures (Durkin and Dowling, 2006; Heymsfield et al., 1990; Lee et al., 2009a; Pietrobelli et al., 1996). Specifically, DXA functions by emitting two collimated x-ray beams of alternating frequencies which pass through the individual being scanned (Durkin et al., 2002; Hologic, 2004), the resulting attenuation coefficients are used within a three-compartment model to differentiate between bone, fat and lean tissue mass (Ganley and Powers, 2001; 2004a; Pietrobelli et al., 1996). On completion, the scan creates a pixel-by-pixel, two-dimensional image reconstruction of the participant, allowing whole-body and regional analyses to be performed thereafter (Lee et al., 2009b; Ganley and Powers, 2004b).

Presently, full-body DXA scans generate automated and mandatory regions of interest in accordance with a standardised whole body model which separates the subject into basic axial and appendicular sections (Durkin et al., 2002; Heymsfield et al., 1990). While this provides useful diagnostic information in clinical applications, more specific detail is usually required under scientific research and rehabilitative contexts to determine body segment parameters and provide localised composite measures (Ganley and Powers, 2004a; Lee et al., 2009a). Specifically, the reliable quantification of upper and lower extremity segmental masses is highly important for use in sensitive biomechanical models and human movement research when examining normal and abnormal gait (Lee et al. 2009b; Holmes et al., 2005; Pearsall and Costigan, 1999; Rossi et al., 2013), or to objectively examine more specific and localised changes in composition during longitudinal exercise interventions as a mechanism to assess program effectiveness (Mueller et al., 2013; Sillanpää et al., 2013; Wood et al., 2010).

Unfortunately, no definitive boundaries have been reliably described to manually and uniformly distinguish between individual segments of the upper and lower extremities using scan technology. While several authors have attempted to define individual segments using DXA (Burkhart et al., 2009; Chambers et al., 2011; Hart et al., 2013; 2014; Rossi et al., 2013), numerous methodological inconsistencies exist. Variations in subject positioning and segmental boundaries employed during the scan and analysis process leads to further complications when interpreting and comparing data sets in the literature, and may exacerbate other inherent limitations of DXA. Due to DXA’s capability to accurately quantify the mass of defined regions (Glickman et al., 2004; Haarbo et al., 1991; Kohrt, 1998; Lee et al., 2009b), it is the purpose of this paper to: 1) present a standardised methodological approach to assess and analyse in-vivo appendicular segmental mass through positioning and analysis considerations; and 2) determine the between-day intra-tester and inter-tester reliability of the proposed regional boundaries and segmental cross-sections using DXA technology.

Despite biomechanical and physiological relevance, precise quantifications of segmental inertial properties and composite measures of the appendicular skeleton remain largely inadequate (Durkin and Dowling, 2006; Heymsfield et al., 1990; Wells, 2009). While current in-vivo techniques provide broad insight into axial and appendicular regions (Fuller et al., 1992; Heysmfield et al., 1990; Visser et al., 1999), no definitive boundaries have been reliably described to further distinguish between individual segments of the upper and lower extremities using scan technology. Several authors have attempted to further define appendicular segments (Durkin and Dowling, 2006; Lee et al., 2009a; 2009b; Ganley and Powers, 2004a; 2004b; Visser et al., 1999). Unfortunately, numerous methodological irregularities exist in the literature pertaining to frontal plane subject positioning and segmental analyses employed during scan procedures, with scarce procedural reliability data reported. This study therefore aimed to: 1) present a standardised methodological approach to assess and analyse in-vivo appendicular segmental mass through positioning and analysis considerations; and 2) determine the between-day intra-tester and inter-tester reliability of the proposed regional boundaries and segmental cross-sections using DXA technology.

Positioning and analysis methodologies presented in this paper resulted in very high, nearly perfect reliability within and between researchers when examining hard- and soft- tissue masses across all segments of the upper and lower extremity (CV ≤ 2.4%; R ≥ 0.980). While no observable difference in reliability was evident between upper-body and lower-body segments; hard-tissue (CV ≤ 1.5%; R ≥ 0.990) achieved greater reliability than soft-tissue (CV ≤ 2.4%; R ≥ 0.980) masses through-out. In addition, the scan-rescan coefficient of variation for this subject positioning procedure has routinely produced a score below 1% (Hologic, 2004; Pfeiffer et al, 2010), with our reported manual segmentation procedure producing an average coefficient of variation below 1.6% across all appendicular segments and tissue masses. This is important as body segment parameters obtained using DXA technology are routinely used in biomechanical models that are highly sensitive to data input fluctuations (Ganley and Powers, 2004a; Lenzi et al., 2003; Lee et al., 2009b; Pearsall and Costigan, 1999; Rao et al., 2006); and are further used to measure and monitor physiological changes in segmental mass during cross-sectional investigations and longitudinal interventions.

Patient positioning prior to scan commencement requires considerable attention as DXA is only capable of uniplanar measurement (Rossi et al, 2013; Wells, 2009), thus limited to quantifying frontal mass distribution. As a result, any limb rotations, or lack thereof can influence the scan re-scan accuracy of DXA (Wells, 2009), and subsequently also influence the visibility of joints required by practitioners to accurately apply regional segmentations during post-scan analysis (Lee and Gallagher, 2008). While upper body positioning has been satisfactorily described in the literature (Durkin and Dowling, 2002; 2003), substantially different lower body scan positions have been used with various levels of external (Ganley and Powers, 2004a; 2004b), neutral (Durkin and Dowling, 2006; Rossi et al, 2013) or internal rotations (Hart et al, 2013; Hart et al, 2014; Lee et al, 2009a; 2009b) of the thigh in conjunction with neutral or plantar-flexed feet. The very low error provided by our standardised methodological approach stems from the careful consideration given to subject positioning prior to scan commencement. This study explicitly prescribes internal rotation of the thigh with neutral foot position. The advantages of internally rotating the thigh whilst maintaining neutral foot position is three-fold: 1) It maximises the available surface area of fat and fat-free mass of the thigh, shank and foot segments viewable in the frontal plane, 2) provides greater visibility of the calcaneus (heel) and talocrural joint (ankle) required for lower-body segmentation precision, and 3) allows the operator to fixate the subjects feet together within the scanning zone in order to prevent unwarranted or incidental movement or disruption during the scanning process. This positioning and segmentation protocol is in agreement with numerous recent papers in the field (Hart et al, 2013; 2014; Lee et al, 2009a; 2009b) who did not report methodological reliability.

Scan analysis and regional segmentations are reliant upon image quality which is a product of subject positioning during the scanning process. As composite mass is assigned to the scanned image on a pixel-by-pixel basis (Ganley and Powers, 2004b; Lee et al., 2009a), outcomes are influenced by the quantity and distribution of mass viewable in the frontal plane (Durkin et al., 2002; Lee et al., 2009b). Regional boundaries are applied to the resultant two dimensional scan image to define the limits of each area for analysis. Presently, no model exists for appendicular segmental analyses of the upper and lower extremities using DXA. Several authors have attempted to differentiate between segments of the extremities (Durkin and Dowling, 2006; Ganley and Powers, 2004a; 2004b; Lee et al., 2009a; 2009b; Visier et al., 1999). However, anatomical inconsistencies exist in regarding locations for body segmentation, further confounded by inadequate descriptions for the purpose of reproduction in practical or research contexts. Our reported methodology provides clear graphical and written guidance for practitioners to adequately and consistently produce segmental appendicular musculoskeletal examinations with very high reliability and very low error. This study explicitly defined appendicular boundaries using clear anatomical descriptors that: 1) are easily visible and accessible through images produced by DXA; 2) capture the maximum amount of segmental tissue as possible; and 3) are consistently reproducible through scan re-scan, and analysis re-analysis procedures. The anatomical and segmental boundaries recommended by this study are largely in agreement with two recent papers in the field (Burkhart et al., 2009; Chambers et al., 2011).

Positioning and analysis methodologies presented in this paper provide practitioners with a standardised, reproducible and robust procedure to quantify appendicular segmental masses using DXA technology (CV ≤ 2.4%; ICC ≥ 0.980). Owing to the uniplanar, two-dimensional nature of DXA, careful consideration of patient positioning specific to limb rotations is necessary to optimise tissue mass accessibility in the frontal plane during measurement, and joint visibility for segmentation during regional analysis. Practitioners are encouraged to use this methodological procedure to examine localised appendicular segmental information. It is recommended that familiarisation and training is provided prior to using this methodological approach to ensure very high reliability and very low error produced by this standardised protocol. Practitioners wishing to cross-sectionally examine or longitudinally monitor changes in appendicular musculoskeletal segmental masses are encouraged to use this standardised methodological procedure, and to provide detailed methodological illustrations and descriptions of subject positioning and scan analysis when disseminating research outcomes.