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Abstract：
Background: This study evaluates the diagnostic accuracy of an AI-assisted tool in assessing the proximity of the mandibular canal (MC) to the root apices (RAs) of mandibular teeth using computed tomography (CT). Methods: This study involved 57 patients aged 18-30 whose CT scans were analyzed by both AI and human experts. The primary aim was to measure the closest distance between the MC and RAs and to assess the AI tool\'s diagnostic performance. The results indicated significant variability in RA-MC distances, with third molars showing the smallest mean distances and first molars the greatest. Diagnostic accuracy metrics for the AI tool were assessed at three thresholds (0 mm, 0.5 mm, and 1 mm). Results: The AI demonstrated high specificity but generally low diagnostic accuracy, with the highest metrics at the 0.5 mm threshold with 40.91% sensitivity and 97.06% specificity. Conclusions: This study underscores the limited potential of tested AI programs in reducing iatrogenic damage to the inferior alveolar nerve (IAN) during dental procedures. Significant differences in RA-MC distances between evaluated teeth were found.
摘要：
背景：本研究使用计算机断层扫描（CT）评估AI辅助工具在评估下颌管（MC）与下颌牙齿根尖（RA）的接近度方面的诊断准确性。方法：这项研究涉及57例年龄在18-30岁之间的患者，其CT扫描由AI和人类专家进行分析。主要目的是测量MC和RA之间的最近距离，并评估AI工具的诊断性能。结果表明RA-MC距离的显着变异性，第三磨牙的平均距离最小，第一磨牙的平均距离最大。AI工具的诊断准确性指标在三个阈值(0毫米，0.5mm,和1毫米）。结果：AI表现出很高的特异性，但通常诊断准确性较低，在0.5mm阈值处具有最高指标，敏感性为40.91%，特异性为97.06%。结论：这项研究强调了经过测试的AI程序在减少牙科手术过程中对下牙槽神经（IAN）的医源性损伤方面的潜力有限。发现评估牙齿之间的RA-MC距离存在显着差异。
