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Although dual-energy X-ray absorptiometry (DXA) is widely used in clinical research as a means of quantifying body composition, there remains at present little published information that reviews the method's underlying physical basis. Because a clear understanding of DXA physical concepts is integral to appropriate use and interpretation, we present here a three-section review that includes both relevant in vitro and in vivo experimental demonstrations. In the first section we describe the main physical principles on which DXA is based. The section that follows presents a step-by-step analysis of the DXA two-component soft tissue model. In the final section we demonstrate how knowledge of physical concepts can lead to resolution of important methodological concerns, such as the influence of hydration changes on DXA fat estimates. A thorough understanding of DXA physical concepts provides a basis for appropriate interpretation of measurement results and stimulates many new and important research questions.

Gender differences in fractures may be related to body size, bone size, geometry, or density. We studied this in 18-year-old males (n = 36) and females (n = 36) matched for height and weight. Despite comparable body size, males have greater BMC and BMD at the hip and distal tibia and greater tibial cortical thickness. This may confer greater skeletal integrity in males.Introduction: Gender differences in fractures may be related to body size, bone size, geometry, or density. We studied this in males (n ‫ס‬ 36) and females (n ‫ס‬ 36; mean age ‫ס‬ 18 years) pair-matched for height and weight. Materials and Methods: BMC, bone area (BA), and BMD were measured in the spine and hip using DXA. Distal tibia was measured by pQCT. Results and Conclusions: Males had a higher lean mass (92%) compared with females (79%). No gender differences were observed for vertebral BMC or vertebral height, although males had greater width and thus BA at the spine. Males had greater BMC and BA at the femoral neck and total femur (p < 0.02). Geometric variables of the hip including neck diameter and neck-axis length were also greater in males (p < 0.02). There was greater cross-sectional moment of inertia, safety factor, and fall index in males (all p < 0.02). Males had greater tibial BMC, volumetric BMD, and cortical area and thickness compared with females (p < 0.01), with both greater periosteal circumference (p ‫ס‬ 0.011) and smaller endosteal circumference (p ‫ס‬ 0.058). Statistically controlling for lean mass reduced gender differences, but males still had 8% higher hip BMD (p ‫ס‬ 0.24) and 5.3% higher total tibial BMD (p ‫ס‬ 0.05). A subset of males and females were matched (n ‫ס‬ 14 pairs) for total hip BA. Males in this subset still had greater BMC and BMD at the total hip (p < 0.05) than females, despite similar BA. In summary, despite comparable body size, males have greater BMC and BMD than females at the hip and distal tibia but not at the spine. Differences in BMC and BMD were related to greater cortical thickness in the tibia. We conclude that differences in bone mass and geometry confer greater skeletal integrity in males, which may contribute to the lower incidence of stress and osteoporotic fractures in males.

Our best pharmacologic agents for osteoporosis treatment prevent no more than 40 -60% of osteoporotic fractures in patients at highest risk. Thus, there is a need for agents that can further augment bone mass and reduce fracture risk more substantially. To this end, we investigated the utility of parathyroid hormone (PTH) in combination with established hormone-replacement therapy (HRT) in women with osteoporosis. Fifty-two women who had been on HRT for at least 2 years were enrolled in this trial in which 25 were assigned randomly to remain on HRT alone and 27 were assigned to remain on HRT and also receive daily subcutaneous PTH(1-34) 400 U (25 g) per day for 3 years. Bone mineral density (BMD) measurements at the spine, hip, and total body as well as biochemical determinations of bone turnover and calcium homeostasis were obtained every 6 months. Lateral thoracic and lumbar spine X-rays were obtained at baseline and annually. Subjects also had measurements of bone density and biochemical indices of bone turnover 1 year after discontinuation of PTH, while HRT was continued. In the group receiving HRT alone, bone density and biochemical variables of bone turnover remained stable throughout the 3-year treatment trial and 1-year follow-up. In the PTH ؉ HRT group, biochemical variables of bone formation and resorption peaked at 6 months and subsequently remained elevated until 30 months at which time levels were indistinguishable from baseline. Subjects in the PTH ؉ HRT group increased bone mass by 13.4 ؎ 1.4% in the spine, 4.4 ؎ 1.0% in the total hip, and 3.7 ؎ 1.4% in the total body. Bone density measurements remained stable 1 year after discontinuation of PTH without any significant loss while women continued HRT. Biochemical variables did not change significantly after cessation of PTH through the 1-year follow-up period. PTH ؉ HRT reduced the percent of women who had vertebral fractures from 37.5% to 8.3% (using a 15% height reduction criterion) and from 25% to 0% (using a 20% height reduction criterion) compared with women receiving HRT alone (p < 0.02 for both). We conclude that ongoing HRT maintains almost all of the PTH-induced bone mass increment for 1 year after discontinuation of PTH.

MS patients have more frequent fractures and lose bone mass more rapidly than do their healthy age- and gender-matched peers, in part related to insufficient vitamin D. Vitamin D repletion in MS patients who are deficient might reduce, to some extent, the rate of bone loss and decrease osteoporosis-related fractures.

Are the associations between muscle strength, lean mass, and bone mineral density (BMD) genetically determined? Based on within-pair differences in 56 monozygotic (MZ) and 56 dizygotic (DZ) female twin pairs, mean age 45 yr (range 24-67), BMD was associated with lean mass, independent of fat mass and height (P < 0.05). A 10% increment in femoral neck (FN) BMD was associated with a 15% increment in lean mass (approximately 6 kg). BMD was associated with muscle strength (measured in 35 pairs) before, but not after, adjusting for lean mass. Based on age-adjusted cross-sectional analyses, same-trait correlations (+/- SE) in MZ pairs were double those in DZ pairs: FN BMD (0.62 +/- 0.08, 0.33 +/- 0.12) and lean mass (0.87 +/- 0.03, 0.30 +/- 0.11; all P < 0.001), consistent with a genetic hypothesis. The cross-trait correlation (r) between lean mass and FN BMD in the same individual was 0.43 +/- 0.06. The cross-trait cross-twin correlation between lean mass in one twin and FN BMD in the other was 0.31 +/- 0.07 in MZ pairs, approximately 75% of the cross-trait correlation (r) and 0.19 +/- 0.09 in DZ paris (P < 0.001). After adjusting for height and fat mass, the MZ and DZ cross-trait cross-twin correlations were no different (0.16 +/- 0.08 and 0.13 +/- 0.09, respectively). Therefore, genetic factors account for 60-80% of the individual variances of both FN BMD and lean mass, and > 50% of their covariance. The association between greater muscle mass and greater BMD is likely to be determined by genes regulating size.

Dual-energy X-ray absorptiometry (DXA) is rapidly gaining acceptance as a reference method for analyzing body composition. An important and unresolved concern is whether and to what extent variation in soft tissue hydration causes errors in DXA fat estimates. The present study aim was to develop and validate a DXA physical hydration model and then to apply this model by simulating errors arising from hypothetical overhydration states. The DXA physical hydration model was developed by first linking biological substance elemental content with photon attenuation. The validated physical model was next extended to describe photon attenuation changes anticipated when predefined amounts of two known composition components are mixed, as would occur when overhydration develops. Two overhydration models were developed in the last phase of study, formulated on validated physical models, and error was simulated for fluid surfeit states. Results indicate that systematic errors in DXA percent fat arise with added fluids when fractional masses are varied as a percentage of combined fluid + soft tissue mass. Three independent determinants of error magnitude were established: elemental content of overhydration fluid, fraction of combined fluid + soft tissue as overhydration fluid, and initial soft tissue composition. Small but systematic and predictable errors in DXA soft tissue composition analysis thus can arise with fluid balance changes.

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