## 4 Discussion  
Osteoporosis is a common skeletal disorder that is associated with increased morbidity and mortality worldwide. It is characterized by reduced bone density and increased risk of fracture, and its diagnosis and management require accurate assessment of bone mineral density (BMD). Dual-energy X-ray absorptiometry (DXA) is currently the gold standard for BMD assessment and osteoporosis diagnosis. DXA is a non-invasive imaging technique that uses low-dose X-rays to measure BMD at specific sites, particularly the distal forearm, the hip, and the lumbar spine for the diagnosis of osteoporosis [7]. Spinal disorders have a significant impact on radiology work and, as a result, on the entire healthcare system. MRI of the lumbar spine is currently ranked second (USD 686 million per year), after mammography (USD 718 million per year), in terms of total charges for imaging examinations in the United States [8]. Due to this, the application of a textural analyses for BMD assessment in lumbosacral MRI would have a huge impact on clinical practice, possibly avoiding further unnecessary examinations. Texture analysis (TA) is a computerized method for quantifying the spatial distribution and heterogeneity of image intensities in MRI images. In the context of bone mineral density (BMD) assessment, TA can be used to analyze the texture of the trabecular bone and bone marrow in MRI images of the lumbar spine. One of the main challenges in using MRI for TA is the presence of noise in the images. MRI is inherently noisy due to several factors, including the low signal-to-noise ratio (SNR) of the images and the presence of artifacts such as motion and susceptibility artifacts. This noise can affect the accuracy of TA parameters, particularly those that rely on the spatial distribution of image intensities. In contrast, CT images typically have higher SNR and less noise, which can make TA analysis more robust and accurate [9]. Another challenge in using MRI for TA is the complex nature of the MRI signal. Unlike CT, which provides a direct measure of X-ray attenuation, MRI measures the relaxation times of protons in tissue. This signal can be influenced by numerous factors, including the tissue composition, magnetic field inhomogeneities, and imaging parameters. These factors can affect the accuracy and reproducibility of TA parameters derived from MRI [10]. Furthermore, the acquisition and processing of MRI images can be more time-consuming and technically challenging compared to CT. MRI typically requires longer acquisition times, and the images must be processed to correct for motion artifacts and other sources of image distortion. This processing can introduce additional variability and noise into the images, which can affect the accuracy of TA parameters [10]. To increase the reliability of texture analysis (TA) features derived from magnetic resonance imaging (MRI) for bone mineral density (BMD) assessment, several approaches can be employed. The following include some of these:  
1. Image quality control: It is important to ensure that the MRI images used for TA analysis are of high quality and free of artifacts such as motion or susceptibility artifacts. This can be achieved by implementing quality control measures such as visual inspection, automated motion correction algorithms, and coil sensitivity correction. \begin{table}
\begin{tabular}{c c c c c} \hline
**Feature** & **T1** & **T2** & **T2 FS** & **Shape** & **\%** \\ \hline GLZLM\_HGZE & 37.3\% & 50.9\% & 50.9\% & \\ \hline GLZLM\_SZLGE & 27.6\% & 35.6\% & 35.6\% & \\ \hline GLZLM\_SZHGE & 48.9\% & 32.3\% & 32.3\% & \\ \hline GLZLM\_LZLGE & 27.4\% & 28.8\% & 28.8\% & \\ \hline GLZLM\_LZHGE & 20.3\% & 59.1\% & 59.1\% & \\ \hline GLZLM\_GLNU & 36.3\% & 31.8\% & 31.8\% & \\ \hline GLZLM\_ZLNU & 47.6\% & 54.1\% & 54.1\% & \\ \hline GLZLM\_ZP & 54.9\% & 39.5\% & 39.5\% & \\ \hline \end{tabular}
\end{table} 
Table 5: _Cont._2 Reproducible image acquisition: Reproducibility of MRI acquisition is critical for reliable TA analysis.