# Current Applications and Development of Radiomics in Osteoporosis: A Narrative Review
## 1 Introduction  
Osteoporosis is a widespread global disease that substantially increases the risk of fractures, resulting in fractures that place considerable burdens on both patients and healthcare systems [1]. Data from 19 countries and regions covering hospitalized hip fracture patients between 2005 and 2018 revealed one-year all-cause mortality rates for hip fractures ranging from 14.4% in Singapore to 28.3% in the United Kingdom, yielding a median mortality rate of 22.4%. Mortality in men was particularly high, ranging from 19.2% to 35.8% [2]. It was essential to diagnose osteoporosis early and assess fracture risk accurately to prevent osteoporometric fractures and reduce related mortality. The T-score, derived from bone mineral density (BMD) measurement obtained by dual-energy X-ray absorptiometry (DXA), was considered the gold standard for diagnosing osteoporosis, with a score below \(-2.5\). However, DXA could be sensitive to artifacts from surrounding tissue, leading to an overestimation of BMD and inadequate diagnosis of osteoporosis [3, 4]. Similarly, the fracture risk assessment tool (FRAX), widely employed in clinical practice to evaluate fracture risk, has demonstrated limitations by either overestimating or underestimating fracture risk acrossdifferent populations [5]. These discrepancies primarily arose from variations in calibration methods, inaccuracies in the assessment of clinical risk factors, and the lack of BMD [5]. The limitations in these techniques have spurred the investigation of additional image features and the development of novel imaging methods. For example, the trabecular bone score (TBS) extracted gray-scale texture features from 2D DXA images of the lumbar spine to represent 3D bone microarchitecture, thereby providing an independent perspective for fracture risk assessment distinct from traditional DXA and FRAX methods [6]. As an adjunct to DXA and/or FRAX methods, TBS has been incorporated into clinical guidelines to enhance fracture risk assessment [7]. Furthermore, the Radiofrequency Ultrasound Multispectral Analysis (REMS) represented an emerging non-ionizing imaging modality that provided a portable and radiation-free approach for BMD. The performance of REMS was comparable to that of DXA [8]. Additionally, biomechanical computed tomography analysis utilized opportunistic clinical computed tomography (CT) images to calculate bone strength and equivalent BMD for osteoporosis screening and fracture risk assessment. It has been shown to enhance the accuracy of osteoporosis diagnosis and fracture risk assessment in various populations [9; 10]. However, it could only be implemented in specialized laboratories by trained technicians, limiting its widespread clinical application [11]. Therefore, there was an urgent need for convenient and accurate methods to diagnose osteoporosis and assess fracture risk. Radiomics, an advanced image analysis technique, has demonstrated potential in quantitative, comprehensive, and automated high-throughput extraction of features from clinical images [12; 13]. It excelled in mining image information and capturing disease characteristics that may not be readily detectable by the human eye [14]. Radiomics, as a quantitative analytical tool, has facilitated improved diagnostic and prognostic modeling in musculoskeletal disorders, from metabolic bone diseases like osteoporosis to degenerative and neoplastic conditions such as osteoarthritis and bone tumors [15; 16; 17]. Radiomics features extracted from bone images provided detailed insights into bone-quality-related information such as bone geometry, material distribution, and microstructure. Specifically, in the application of osteoporosis, these radiomics features have been employed to build classification and prediction models, facilitating bone strength assessment, osteoporosis diagnosis, and fracture risk prediction [17; 18; 19]. Currently, radiomics has demonstrated considerable advantages in osteoporosis.