###### Abstract  
Osteoporosis is a common condition characterized by low bone mineral density (BMD) and deterioration of bone microarchitecture, leading to increased risk of fractures. Early diagnosis and treatment of osteoporosis are critical for preventing fractures and their associated morbidity and mortality. Currently, dual-energy X-ray absorptiometry (DXA) is the gold standard for assessing BMD; however, it has limitations such as radiation exposure, cost, and limited availability in certain regions. Magnetic resonance imaging (MRI) of the lumbar spine is routinely performed for various indications, and it provides high-resolution images of the bone and tissue without ionizing radiation. Recently, texture analysis (TA) of MRI images has shown promise in assessing BMD by quantifying the spatial distribution and heterogeneity of bone marrow fat and trabecular bone. In this article, we present our experience with the opportunistic use of lumbar spine MRI for BMD assessment using TA, and we compare the results with DXA measurements. We also discuss the potential clinical implications of this approach, including its use in patients who cannot undergo DXA or in whom BMD assessment is not routinely performed. MRI should provide information in a single examination in regard to degenerative disk pathology and arthritis, with the addition of BMD prediction. texture analysis; radiomics; osteoporosis; MRI; machine learning +
Footnote †: journal: Medical  
thickness, and trabecular separation. Texture analysis can also reveal changes in bone structure that may not be apparent on DXA or QCT [3]. Recent studies have shown that texture analysis has potential as an alternative method for assessing BMD. For example, a study comparing texture analysis performed on lumbar spine MRI scans and DXA measurements found that trabecular bone texture features were significantly associated with DXA-derived BMD values [4]. Despite these promising results, texture analysis is not yet widely used in clinical practice for assessing BMD. More research is needed to validate its use as a diagnostic tool and to optimize the algorithms used to analyze the images. Texture analysis is a method that involves quantitatively characterizing the patterns of intensity, contrast, and homogeneity in an image. These patterns can be used to infer underlying tissue characteristics, such as bone microarchitecture, which may not be readily visible to the naked eye. Texture analysis methods can be broadly categorized into two types: first-order and higher-order features. First-order features are statistical descriptors derived from the distribution of pixel intensity values within an image, such as the mean, standard deviation, and entropy. These features provide an overall characterization of the image without directly capturing the spatial relationships between pixels. Higher-order features, on the other hand, are calculated from spatial relationships between pixel intensities and describe more complex patterns in an image. Examples of higher-order features include gray level co-occurrence matrix (GLCM)-based features, gray level run length matrix (GLRLM)-based features, and gray level size zone matrix (GLSZM)-based features [5]. These features capture information about the spatial arrangement of pixels and can provide more detailed information on the microstructure of bones. Higher-order texture features have shown promising results in characterizing changes in bone microarchitecture due to different bone disease states, such as osteoporosis, and may provide valuable information for early detection and diagnosis of such diseases. Moreover, a study demonstrated that texture analysis can provide a predictive value on pathological fractures independently of BMD [6]. The aim of our study is to report our preliminary experience in the assessment of BMD via MRI-based textural analyses in a cohort of patients who have undergone DXA and lumbosacral MRIs, to assess the possibility of a standard examination to be able to opportunistically raise concern about osteoporosis.