Ramschütz Constanze, Sollmann Nico, El Husseini Malek, Kupfer Karina, Paprottka Karolin J, Löffler Maximilian T, Petzsche Moritz R Hernandez, Schwarting Julian, Bodden Jannis, Baum Thomas, Kim Su Hwan, Wostrack Maria, Zimmer Claus, Kirschke Jan S, Rühling Sebastian
Department of Diagnostic and Interventional Neuroradiology, Klinikum Rechts Der Isar, TUM School of Medicine and Health, Technical University of Munich, Ismaninger Str 22, 81675, Munich, Germany.
TUM-Neuroimaging Center, Klinikum Rechts Der Isar, Technical University of Munich, Munich, Germany.
Osteoporos Int. 2025 Mar;36(3):423-433. doi: 10.1007/s00198-024-07373-1. Epub 2024 Dec 31.
This study aimed to validate the correlation between volumetric bone mineral density in the cervicothoracic and lumbar spine using measurements from opportunistic CT scans. The bone density assessment proved feasible, allowing us to propose optimal cut-off values for diagnosing osteoporosis and predicting vertebral fractures in the cervical and thoracic spine.
To investigate the performance of cervicothoracic volumetric bone mineral density (vBMD), obtained through opportunistic quantitative computed tomography (QCT), in discriminating patients with/without osteoporosis and with/without vertebral fractures (VFs), using lumbar vBMD as the reference.
Three hundred twenty-five patients (65.3 ± 19.2 years, 140 women) with routine non-contrast or contrast-enhanced multi-detector CT (MDCT) scans were included. Trabecular vBMD was automatically extracted from each vertebra using a convolutional neural network (CNN)-based framework (SpineQ software v1.0) with asynchronous calibration and contrast phase correction. The correlations of vBMD between each vertebra spanning C2-T12 and the averaged lumbar spine (L1-L3, or L4 and L5) vBMD values were analyzed, considering fracture status and degeneration. Vertebra-specific linear regression equations were used to approximate lumbar vBMD at the cervicothoracic spine.
Cervicothoracic vBMD correlated well with lumbar vBMD (r = 0.79), with significant improvement after excluding degenerated vertebrae (p < 0.05; r = 0.89), except for C7-T3 and T9. Cervical (AUC = 0.94) and thoracic vBMD (AUC = 0.97) showed strong discriminatory ability for osteoporosis (vBMD < 80 mg/cm). Excluding degenerated vertebrae at the cervical spine increased the AUC to 0.97. Cervical and thoracic vBMD (AUC = 0.74, AUC = 0.72) were comparable to lumbar vBMD (AUC = 0.72) in differentiating patients with and without prevalent VFs. Trabecular vBMD < 190 mg/cm for the cervical spine and < 100 mg/cm for the thoracic spine were potential indicators of osteoporosis, similar to < 80 mg/cm at the lumbar spine.
Cervicothoracic vBMD may allow for determination of osteoporosis and prediction of VFs.
本研究旨在通过机会性CT扫描测量，验证颈胸椎和腰椎体积骨密度之间的相关性。骨密度评估被证明是可行的，这使我们能够提出用于诊断骨质疏松症和预测颈椎和胸椎椎体骨折的最佳临界值。
以腰椎体积骨密度为参考，研究通过机会性定量计算机断层扫描（QCT）获得的颈胸段体积骨密度（vBMD）在鉴别有无骨质疏松症及有无椎体骨折（VFs）患者中的表现。
纳入325例（65.3±19.2岁，140名女性）接受常规非增强或增强多排CT（MDCT）扫描的患者。使用基于卷积神经网络（CNN）的框架（SpineQ软件v1.0）并进行异步校准和对比相校正，自动从每个椎体中提取小梁骨vBMD。分析C2-T12各椎体与平均腰椎（L1-L3或L4和L5）vBMD值之间的vBMD相关性，同时考虑骨折状态和退变情况。使用特定椎体的线性回归方程来估算颈胸段脊柱的腰椎vBMD。
颈胸段vBMD与腰椎vBMD相关性良好（r = 0.79），排除退变椎体后相关性显著改善（p < 0.05；r = 0.89），C7-T3和T9除外。颈椎（AUC = 0.94）和胸椎vBMD（AUC = 0.97）对骨质疏松症（vBMD < 80mg/cm）显示出很强的鉴别能力。排除颈椎退变椎体后，AUC增加到了0.97。在鉴别有无既往椎体骨折的患者方面，颈椎和胸椎vBMD（AUC = 0.74，AUC = 0.72）与腰椎vBMD（AUC = 0.72）相当。颈椎小梁骨vBMD < 190mg/cm和胸椎小梁骨vBMD < 100mg/cm是骨质疏松症的潜在指标，类似于腰椎的< 80mg/cm。
颈胸段vBMD可用于确定骨质疏松症和预测椎体骨折。
