Background. Dual-energy X-ray absorptiometry (DXA) is an effective method for bone mineral density (BMD) and subcutaneous fat percentage estimation. The constant development of new densitometry techniques, the demographic change and the higher potential of artificial intelligence in healthcare enhance requirements for the high-quality measurements in DXA. This study aimed to develop a quality control method for DXA scanners and compare four DXA systems with different X-ray geometries and manufacturers when simulating fat-water environments. Methods. We evaluated the accuracy (relative error (%) and precision (CV%)) of the bone mineral density (BMD) measurements, performed by the four DXA scanners: 2 with narrow-angle fan beam (64- and 16-channel detectors (DXA-1, DXA-2)); 1 with wide-angle fan beam (DXA-3); 1 with pencil beam (DXA-4). We used a PHK (PHantom Kalium) designed to imitate spine. The PHK contained four vertebras filled with a K2HPO4 solution in various concentrations (50-200 mg/ml). The PHK also included paraffin patches (thickness 40 mm) to simulate the fat layer. Results. DXA-1 and DXA-2 demonstrated the best CV% ranged from 0.56% to 1.05%. The least % was observed when scanning PHK with fat layer on DXA-1 and DXA-2 (1.74% and 0.85%) and DXA-4 (1.47%). DXA-3 produced significantly lower BMD (= -14.56%, p = 0.000). After removing the fat layer, we observed reduction (p = 0.000) of BMD for DXA- 1 and DXA-2 (= -5.11% and -6.12% respectively) and weak deviation (p = 0.80) for DXA-4 (0.87%). For DXA-3, removal of the fat layer also resulted in a significant reduction in BMD ( = -16.44%, p = 0.000). The subcutaneous fat modeling showed that all these DXA systems automatically determine the percentage of fat in the scanned area with weak underestimation: for DXA-1, DXA-2 and DXA-4 the % were -5,9%, -6,3% and -2,3% respectively. CV% were 0.15%; 0.39%; 1.6%, respectively. Conclusions. We proved a significant underestimation of the BMD measurements across the entire range of simulated parameters for the DXA scanners when the model did not include the subcutaneous fat layer. All models demonstrated high accuracy in measuring the fat layer, with the exception of the DXA-3 model, which was not assessed in these studies.
