In this article, we derive a generalized expression for the least significant change (LSC), which we call the generalized LSC (GLSC), to be used when an individual is measured on 2 different systems. The commonly used LSC is defined as the least amount of change between 2 measurements over time that must be exceeded before a change can be considered true (with 95% confidence). The LSC has clinical applications in monitoring disease progression or treatment effects in bone mineral density (BMD) and bone mineral content. Mathematically, the "ideal" LSC (ILSC) is 2.77 times the precision errors for measures on a single system. When BMD values of an individual are measured by 2 different systems, the LSC will depend not only on the precision errors of both systems but also on the calibration relationship between the systems. Like the ILSC, the GLSC is a simple equation applicable for inter machine comparisons. The GLSC can be defined for any 2 systems with measures obtained from cross-calibration and precision studies using the protocols recommended by the International Society for Clinical Densitometry. We validated the GLSC using 10,000 simulated measurements taken between 2 systems and offer several common uses of the GLSC such as system upgrades within a single manufacturer and replacement of 1 manufacturer by another. We found that when upgrading a Hologic QDR-2000 to a QDR-4500, GLSC was twice as large as the QDR-2000 LSC (0.0432 and 0.0215 g/cm2, respectively). The GLSC was 2.6 (spine) to 3.6 (total hip) times larger than the LSC when comparing scans between the Hologic Delphi and the GE Lunar Prodigy. We also explore how the magnitude of the correlation coefficient and sample size change the GLSC and show that a correlation coefficient less than 0.95 increases the %GLSC to above 10%, and that increasing study sample sizes beyond 30 in the cross-calibration studies can only decrease the magnitude of the GLSC accuracy by 4%. We conclude that the GLSC, defined using commonly used clinical cross-calibration and precision assessments, is the most accurate method to compare scans between dual-energy X-ray absorptiometry systems.