Rafieizadeh Sara, Lari Sima, Maleki Mohammad Mahdi, Shokri Abbas, Tapak Leili
Dental Implants Research Centre, Department of Oral and Maxillofacial Radiology, Dental School, Hamadan University of Medical Sciences, Hamadan, Iran.
Department of Oral and Maxillofacial Radiology, Dental School, Shahid Beheshti University of Medical Sciences, Hamadan, Iran.
BMC Med Imaging. 2025 Jun 5;25(1):203. doi: 10.1186/s12880-025-01739-5.
Osteoporosis is a prevalent skeletal disorder characterized by reduced bone mineral density (BMD) and structural deterioration, resulting in increased fracture risk. Early diagnosis is crucial to prevent fractures and improve patient outcomes. This study investigates the diagnostic utility of morphometric and cortical indices derived from cone-beam computed tomography (CBCT) for identifying osteoporotic postmenopausal women who were candidates for dental implant therapy, with dual-energy X-ray absorptiometry (DXA) used as the reference standard.
This cross-sectional study included 71 postmenopausal women, aged 50-79 years, who underwent CBCT imaging at the Oral and Maxillofacial Radiology Department of Hamadan University of Medical Sciences between 2022 and 2024. Participants with systemic conditions affecting bone metabolism were excluded. The morphometric indices-Computed Tomography Mandibular Index (CTMI), Computed Tomography Index Superior (CTI(S)), Computed Tomography Index Inferior (CTI(I)), and Computed Tomography Cortical Index (CTCI)-were measured at the mental foramen and antegonial regions using OnDemand3D Dental software. Bone mineral density (BMD) was assessed by DXA scans of the lumbar spine and femoral neck. In addition to traditional statistical analyses (Pearson's correlation and one-way ANOVA with LSD test), a multilayer perceptron (MLP) neural network model was employed to evaluate the diagnostic power of CBCT indices.
DXA results based on the femoral neck T-scores categorized 38 patients as normal, 32 as osteopenic, and one as osteoporotic, while lumbar spine T-scores identified 38 normal, 22 osteopenic, and 11 osteoporotic patients. Significant differences (p < 0.05) were observed in most CBCT-derived indices, with the CTMI index demonstrating the most marked variation, especially between normal and osteoporotic groups (p < 0.001). Moreover, significant positive correlations were found between the CBCT indices and DXA T-scores across the lumbar spine, femoral neck, and total hip regions. The neural network model achieved an overall diagnostic accuracy of 75%, with the highest predictive importance attributed to antegonial CTCI and CTMI indices.
This study highlights the significant correlation between CBCT-derived radiomorphometric indices such as CTMI, CTI(S), CTI(I), and CTCI at the mental foramen and antegonial regions and bone mineral density (BMD) in postmenopausal women. CBCT, particularly the CTMI index in the antegonial region, offers a cost-effective, non-invasive method for early osteoporosis detection, providing a valuable alternative to traditional screening methods.
骨质疏松症是一种常见的骨骼疾病，其特征是骨矿物质密度（BMD）降低和结构恶化，导致骨折风险增加。早期诊断对于预防骨折和改善患者预后至关重要。本研究调查了锥形束计算机断层扫描（CBCT）得出的形态学和皮质指数在识别适合种植牙治疗的绝经后骨质疏松女性中的诊断效用，并将双能X线吸收法（DXA）用作参考标准。
这项横断面研究纳入了71名年龄在50 - 79岁之间的绝经后女性，她们于2022年至2024年在哈马丹医科大学口腔颌面放射科接受了CBCT成像检查。排除患有影响骨代谢的全身性疾病的参与者。使用OnDemand3D Dental软件在颏孔和下颌角区域测量形态学指数——计算机断层扫描下颌指数（CTMI）、计算机断层扫描上指数（CTI(S)）、计算机断层扫描下指数（CTI(I)）和计算机断层扫描皮质指数（CTCI）。通过腰椎和股骨颈的DXA扫描评估骨矿物质密度（BMD）。除了传统的统计分析（Pearson相关性分析和采用LSD检验的单因素方差分析）外，还采用了多层感知器（MLP）神经网络模型来评估CBCT指数的诊断能力。
基于股骨颈T值的DXA结果将38例患者分类为正常，32例为骨量减少，1例为骨质疏松；而腰椎T值识别出38例正常，22例骨量减少，11例骨质疏松患者。在大多数CBCT衍生指数中观察到显著差异（p < 0.05），CTMI指数显示出最明显的变化，尤其是在正常组和骨质疏松组之间（p < 0.001）。此外，在腰椎、股骨颈和全髋区域，CBCT指数与DXA T值之间发现了显著的正相关。神经网络模型的总体诊断准确率达到75%，其中下颌角CTCI和CTMI指数的预测重要性最高。
本研究强调了在颏孔和下颌角区域，CBCT衍生的放射形态学指数如CTMI、CTI(S)、CTI(I)和CTCI与绝经后女性骨矿物质密度（BMD）之间的显著相关性。CBCT，特别是下颌角区域的CTMI指数，为早期骨质疏松检测提供了一种经济高效、非侵入性的方法，是传统筛查方法的有价值替代方案。
