## 4 Discussion  
This study compared lumbar (L1-L4) BMD measurements by DXA, including TBS, with volumetric BMD values obtained via QCT. On one hand, we found that QCT with asynchronous calibration was able to provide vBMD values that most of the time were comparable with those of DXA-aBMD in diagnosing patients with osteoporosis. In fact, all patients classified with osteoporosis by DXA were similarly classified by QCT, except for four participants classified as osteoporotic by DXA and osteogenic by QCT. One possible explanation is that the ACR thresholds for QCT are linear and do not represent a standard deviation, as seen with the T-score. In all these cases, the values were very close to a change in the diagnosis (from osteopenia to osteoporosis). On the other hand, our results showed that QCT can offer a more accurate diagnosis of osteopenia/osteoporosis in patients where DXA-aBMD values were altered and overestimated due to artifacts caused by vertebral degenerative changes. In fact, we must consider that DXA-based parameters (aBMD and TBS) acquired during posteroanterior DXA at the lumbar spine, are influenced by the vertebral posterior elements [19]. Previous studies showed that the posterior elements accounted for about half of the bone mineral content in the DXA lumbar spine scan region [20]. On the contrary, when analyzing QCT images, an elliptical ROI is placed within the axial vertebral plane in the trabecular region of each vertebral body, to exclude any cortical and sub-cortical bone: this allows QCT to provide a direct measure of the trabecular vBMD of the vertebral body only [21]. This can explain why in most of mismatching cases of our study where DXA-aBMD underestimated the disease, patients showed signs of advanced spondylarthosis or degenerative scoliosis at the lumbar spine, which generated a fictitious increase in aBMD values. In general, this is also confirmed by the results from the Bland-Altman analysis, which highlight the systematic overestimation by QCT, reinforcing the need for caution when comparing bone density measurements obtained with different imaging modalities. The presence of a proportional bias suggests that the discrepancy between methods increases at higher bone density values, which may have implications for clinical decision-making and fracture risk assessment. Similar results were already reported by a 2019 study from [PERSON] et al., where the authors found significant differences in lumbar spine measurement variables between fractured and non-fractured groups. In particular, QCT-derived vBMD values were significantly lower in all groups compared to DXA-aBMD. It was also shown that vBMD was the only parameter that could discriminate between postmenopausal women with low aBMD values associated with fragility fractures from those with isolated low aBMD values [21]. More recently, a study by [PERSON] et al. showed that the diagnostic discordance of DXA and QCT was 34.5%, which is lower compared to our findings (60% of DXA-QCT mismatching) [14]. This may be attributed to the slightly younger age of their patients compared to ours, resulting in a lower impact of degenerative changes that can overestimate BMD. Similarly to our study, one strength is that both are focused on a direct comparison of level-specific BMD measurements in patients who underwent both DXA and QCT. Still, no information about TBS is provided by [PERSON] et colleagues. To understand why vBMD from QCT demonstrates a better ability to discriminate participants with vertebral fractures compared to other variables (aBMD and TBS), it is essential to examine both the underlying fracture mechanisms but also the distinct imaging techniques used to study the lumbar spine. Studies have shown that adult lumbar vertebrae are primarily composed of trabecular bone [22], and vertebral fractures are a consequence of a poor trabecular microarchitecture due to progressive loss of trabecular bone caused by the thinning or disruption of some bony trabeculae [23].