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研究影响鼻窦底提升术中 CBCT 检测牙槽嵴顶动脉的术前因素。

Study of factors influencing preoperative detection of alveolar antral artery by CBCT in sinus floor elevation.

机构信息

C.S. Praza Do Ferrol. EOXI Lugo, Cervo, e Monforte de Lemos, Galician Health Service, 27001, Lugo, Spain.

Department of Surgery and Medical-Surgical Specialities, School of Medicine and Dentistry, University of Santiago de Compostela, 15782, Santiago de Compostela, A Coruña, Spain.

出版信息

Sci Rep. 2020 Jul 2;10(1):10820. doi: 10.1038/s41598-020-67644-9.

Abstract

This study aimed at assessing the prevalence of alveolar antral artery (AAA) detection by CBCT, its related variables, and at describing explanatory models useful in surgical planning, by retrospective evaluation of CBCT explorations. The modelling of the probability for detecting AAA was undertaken using logistic generalized additive models (GAM). The capacity for discriminating detection/no detection was assessed by receiver operating characteristic curves. A total of 466 sinuses were studied. Univariate models showed detection probability was linked to sinus width and thickness of the lateral bony wall, together with the shape and height of the osseous crest. AAA detection probability increased steadily until the thickness of the bony wall reached 6 mm. Multivariate models resulted good discriminators for AAA detection, particularly for females, showing an area under the curve (AUC) of 0.85. Models considering patients altogether, and those including only males offered slightly lower values (AUC = 0.79). The probability of AAA detection by CBCT was influenced by gender (higher in males and for narrow sinuses) and increases with the thickness of the sinus lateral bony wall and the height of the residual alveolar ridge. Besides, and particularly for women, the thickness of the ridge at the basal level seems to improve the explanatory model for AAA detection.

摘要

本研究旨在通过回顾性评估 CBCT 检查,评估牙槽嵴顶动脉(AAA)在 CBCT 中的检出率、相关变量,并描述有助于手术规划的解释模型。使用逻辑广义加性模型(GAM)对 AAA 检测概率进行建模。通过接收者操作特征曲线评估检测/未检测的区分能力。共研究了 466 个鼻窦。单变量模型显示,检测概率与鼻窦宽度和外侧骨壁厚度、骨嵴形状和高度有关。AAA 检测概率随着骨壁厚度的增加而稳步增加,直到达到 6mm。多变量模型对 AAA 检测具有良好的判别能力,特别是对女性,曲线下面积(AUC)为 0.85。考虑所有患者的模型和仅包括男性的模型提供的 AUC 值略低(AUC=0.79)。CBCT 检测 AAA 的概率受性别影响(男性和鼻窦较窄时较高),并随鼻窦外侧骨壁厚度和剩余牙槽嵴高度的增加而增加。此外,特别是对于女性,基底水平嵴的厚度似乎可以提高 AAA 检测的解释模型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a73/7331631/947bc66a5f4f/41598_2020_67644_Fig1_HTML.jpg

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