Zaia Annamaria, Rossi Roberto, Galeazzi Roberta, Sallei Manuela, Maponi Pierluigi, Scendoni Pietro
Centre of Innovative Models for Ageing Care and Technology, Scientific Direction, IRCCS INRCA, Via S. Margherita 5, I-60121, Ancona, Italy.
Medical Imaging Division, Geriatric Hospital, IRCCS INRCA, 60124, Ancona, Italy.
BMC Musculoskelet Disord. 2021 Jan 23;22(1):108. doi: 10.1186/s12891-021-03966-7.
Osteoporotic fractures are a major cause of morbidity in the elderly. Menopausal women represent the population with the highest risk of early osteoporosis onset, often accompanied by vertebral fractures (VF). Bone mineral density (BMD) is commonly assessed by dual-energy X-ray absorptiometry (DXA) for osteoporosis diagnosis; however, BMD alone does not represent a significant predictor of fracture risk. Bone microarchitecture, instead, arises as a determinant of bone fragility independent of BMD. High-resolution magnetic resonance imaging (MRI) is an effective noninvasive/nonionizing tool for in vivo characterisation of trabecular bone microarchitecture (TBA). We have previously set up an MRI method able to characterise TBA changes in aging and osteoporosis by one parameter, trabecular bone lacunarity parameter β (TBLβ). Fractal lacunarity was used for TBA texture analysis as it describes discontinuity of bone network and size of bone marrow spaces, changes of which increase the risk of bone fracture. This study aims to assess the potential of TBLβ method as a tool for osteoporotic fracture risk.
An observational, cross-sectional, and prospective study on over-50s women at risk for VF was designed. TBLβ, our index of osteoporotic fracture risk, is the main outcome measure. It was calculated on lumbar vertebra axial images, acquired by 1.5 T MRI spin-echo technique, from 279 osteopenic/osteoporotic women with/without prior VF. Diagnostic power of TBLβ method, by Receiver Operating Characteristics (ROC) curve and other diagnostic accuracy measurements were compared with lumbar spine DXA-BMD.
Baseline results show that TBLβ is able to discriminate patients with/without prevalent VF (p = 0.003). AUC (area under the curve from ROC) is 0.63 for TBLβ, statistically higher (p = 0.012) than BMD one (0.53). Contribution of TBLβ to prevalent VF is statistically higher (p < 0.001) than BMD (sensitivity: 66% vs. 52% respectively; OR: 3.20, p < 0.0001 for TBLβ vs. 1.31, p = 0.297 for BMD). Preliminary 1-year prospective results suggest that TBA contribution to incident VF is even higher (sensitivity: 73% for TBLβ vs. 55% for BMD; RR: 3.00, p = 0.002 for TBLβ vs. 1.31, p = 0.380 for BMD).
Results from this study further highlight the usefulness of TBLβ as a biomarker of TBA degeneration and an index of osteoporotic fracture risk.
骨质疏松性骨折是老年人发病的主要原因。绝经后女性是早期骨质疏松症发病风险最高的人群，常伴有椎体骨折（VF）。骨密度（BMD）通常通过双能X线吸收法（DXA）进行评估以诊断骨质疏松症；然而，仅骨密度并不能显著预测骨折风险。相反，骨微结构是独立于骨密度的骨脆性决定因素。高分辨率磁共振成像（MRI）是一种有效的非侵入性/非电离工具，用于体内小梁骨微结构（TBA）的表征。我们之前建立了一种MRI方法，能够通过一个参数——小梁骨孔隙率参数β（TBLβ）来表征衰老和骨质疏松症中的TBA变化。分形孔隙率用于TBA纹理分析，因为它描述了骨网络的不连续性和骨髓腔的大小，这些变化会增加骨折风险。本研究旨在评估TBLβ方法作为骨质疏松性骨折风险评估工具的潜力。
设计了一项针对50岁以上有椎体骨折风险女性的观察性、横断面和前瞻性研究。TBLβ是我们评估骨质疏松性骨折风险的指标，是主要的观察指标。它是根据通过1.5 T MRI自旋回波技术获取的腰椎轴向图像，对279名有/无既往椎体骨折的骨质减少/骨质疏松女性进行计算得出的。通过受试者工作特征（ROC）曲线和其他诊断准确性测量方法，将TBLβ方法的诊断能力与腰椎DXA-BMD进行比较。
基线结果表明，TBLβ能够区分有/无既往椎体骨折的患者（p = 0.003）。TBLβ的ROC曲线下面积（AUC）为0.63，在统计学上高于骨密度的AUC（0.53，p = 0.012）。TBLβ对既往椎体骨折的贡献在统计学上高于骨密度（p < 0.001）（敏感性：分别为66%对52%；OR：TBLβ为3.20，p < 0.0001，骨密度为1.31，p = 0.297）。初步的1年前瞻性结果表明，TBA对新发椎体骨折的贡献甚至更高（敏感性：TBLβ为73%，骨密度为55%；RR：TBLβ为3.00，p = 0.002，骨密度为1.31，p = 0.380）。
本研究结果进一步突出了TBLβ作为TBA退变生物标志物和骨质疏松性骨折风险指标的有用性。
