Diagnostic accuracy of an artificial intelligence-based platform in detecting periapical radiolucencies on cone-beam computed tomography scans of molars

IF 4.8 2区医学 Q1 DENTISTRY, ORAL SURGERY & MEDICINE

Journal of dentistry Pub Date : 2025-05-31 DOI:10.1016/j.jdent.2025.105854

Marwa Allihaibi , Garrit Koller , Francesco Mannocci

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引用次数: 0

Abstract

Objective

This study aimed to evaluate the diagnostic performance of an artificial intelligence (AI)-based platform (Diagnocat) in detecting periapical radiolucencies (PARLs) in cone-beam computed tomography (CBCT) scans of molars. Specifically, we assessed Diagnocat’s performance in detecting PARLs in non-root-filled molars and compared its diagnostic performance between preoperative and postoperative scans.

Methods

This retrospective study analyzed preoperative and postoperative CBCT scans of 134 molars (327 roots). PARLs detected by Diagnocat were compared with assessments independently performed by two experienced endodontists, serving as the reference standard. Diagnostic performance was assessed at both tooth and root levels using sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), F1 score, and the area under the receiver operating characteristic curve (AUC-ROC).

Results

In preoperative scans of non-root-filled molars, Diagnocat demonstrated high sensitivity (teeth: 93.9 %, roots: 86.2 %), moderate specificity (teeth: 65.2 %, roots: 79.9 %), accuracy (teeth: 79.1 %, roots: 82.6 %), PPV (teeth: 71.8 %, roots: 75.8 %), NPV (teeth: 91.8 %, roots: 88.8 %), and F1 score (teeth: 81.3 %, roots: 80.7 %) for PARL detection. The AUC was 0.76 at the tooth level and 0.79 at the root level. Postoperative scans showed significantly lower PPV (teeth: 54.2 %; roots: 46.9 %) and F1 scores (teeth: 67.2 %; roots: 59.2 %).

Conclusion

Diagnocat shows promise in detecting PARLs in CBCT scans of non-root-filled molars, demonstrating high sensitivity but moderate specificity, highlighting the need for human oversight to prevent overdiagnosis. However, diagnostic performance declined significantly in postoperative scans of root-filled molars. Further research is needed to optimize the platform’s performance and support its integration into clinical practice.

Clinical significance

AI-based platforms such as Diagnocat can assist clinicians in detecting PARLs in CBCT scans, enhancing diagnostic efficiency and supporting decision-making. However, human expertise remains essential to minimize the risk of overdiagnosis and avoid unnecessary treatment.

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基于人工智能的磨牙锥形束计算机断层扫描根尖周辐射率检测平台的诊断准确性。

目的：本研究旨在评估基于人工智能（AI）的诊断平台（diagnostic）在检测磨牙锥形束计算机断层扫描（CBCT）的根尖周辐射率（PARLs）方面的诊断性能。具体而言，我们评估了诊断在非根填充磨牙中检测parl的性能，并比较了其术前和术后扫描的诊断性能。方法：回顾性分析134颗磨牙（327根）术前和术后的CBCT扫描结果。将诊断检测到的parl与两位经验丰富的牙髓医生独立评估的结果进行比较，作为参考标准。通过敏感性、特异性、准确性、阳性预测值（PPV）、阴性预测值（NPV）、F1评分和受试者工作特征曲线下面积（AUC-ROC）在牙齿和牙根水平评估诊断效果。结果：在非根填充磨牙的术前扫描中，诊断对PARL的检测灵敏度高（牙齿：93.9%，牙根：86.2%），特异性中等（牙齿：65.2%，牙根：79.9%），准确性高（牙齿：79.1%，牙根：82.6%），PPV（牙齿：71.8%，牙根：75.8%），NPV（牙齿：91.8%，牙根：88.8%），F1评分高（牙齿：81.3%，牙根：80.7%）。牙根水平AUC为0.79，牙水平AUC为0.76。术后扫描显示PPV明显降低(牙齿：54.2%；牙根：46.9%)和F1评分(牙齿：67.2%；根:59.2%)。结论：在非根填充磨牙的CBCT扫描中，诊断显示出parl的前景，显示出高灵敏度但中等特异性，强调需要人为监督以防止过度诊断。然而，诊断性能在术后扫描的根填充磨牙显著下降。需要进一步的研究来优化该平台的性能并支持其融入临床实践。临床意义：Diagnocat等基于人工智能的平台可以帮助临床医生发现CBCT扫描中的parl，提高诊断效率，支持决策。然而，人类的专业知识对于尽量减少过度诊断的风险和避免不必要的治疗仍然至关重要。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of dentistry 医学-牙科与口腔外科

CiteScore

7.30

自引率

11.40%

发文量

349

审稿时长

35 days

期刊介绍： The Journal of Dentistry has an open access mirror journal The Journal of Dentistry: X, sharing the same aims and scope, editorial team, submission system and rigorous peer review. The Journal of Dentistry is the leading international dental journal within the field of Restorative Dentistry. Placing an emphasis on publishing novel and high-quality research papers, the Journal aims to influence the practice of dentistry at clinician, research, industry and policy-maker level on an international basis. Topics covered include the management of dental disease, periodontology, endodontology, operative dentistry, fixed and removable prosthodontics, dental biomaterials science, long-term clinical trials including epidemiology and oral health, technology transfer of new scientific instrumentation or procedures, as well as clinically relevant oral biology and translational research. The Journal of Dentistry will publish original scientific research papers including short communications. It is also interested in publishing review articles and leaders in themed areas which will be linked to new scientific research. Conference proceedings are also welcome and expressions of interest should be communicated to the Editor.