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用于评估第三磨牙手术后面部肿胀的线性和体积的自动化流程。

Automated pipeline for linear and volumetric assessment of facial swelling after third molar surgery.

机构信息

School of Dentistry, Department of Health Sciences, Magna Graecia University of Catanzaro, Viale Europa, Catanzaro, 88100, Italy.

Department of Experimental and Clinical Medicine, Magna Graecia University of Catanzaro, Viale Europa, Catanzaro, 88100, Italy.

出版信息

BMC Oral Health. 2024 Nov 19;24(1):1404. doi: 10.1186/s12903-024-05193-7.

DOI:10.1186/s12903-024-05193-7
PMID:39563399
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11575084/
Abstract

BACKGROUND

Extraction of mandibular third molars (M3Ms) is a routine procedure in oral and maxillofacial surgery, often associated with postoperative symptoms like pain, facial swelling, and trismus. This study aimed to introduce a standardized and automated protocol for swelling analysis following M3M surgery, presenting results regarding clinical conditions immediately and one-week after surgery.

METHODS

In a prospective study, 35 patients were enrolled (mean age: 24.4 ± 5.8 years) for removal of 54 M3Ms. Facial swelling was evaluated through 3D facial scans before surgery (T0), at three days (T1), and seven days (T2) post-surgery. The open-source software 3DSlicer facilitated automated analysis, including data anonymization, orientation, surface registration, qualitative comparisons, linear measurements, and volumetric quantification. Pairwise superimposition of facial models enabled qualitative, vectorial, and quantitative assessments, comparing initial conditions with swelling development at T1 and T2. Additionally, changes between T1 and T2 were also evaluated. Secondary outcomes encompassed clinical evaluations of pain, trismus (maximum mouth opening), and surgery time. Statistical analysis involved the paired Student t-test to assess longitudinal changes and analysis of variance to evaluate outcome variables concerning difficulty scores. Linear regression models correlated primary outcome variables with secondary study variables (α < 0.05).

RESULTS

Longitudinal analysis demonstrated significant but variable facial swelling, pain, and trismus at T1, followed by improvement at T2 (p < 0.001). Linear and volumetric differences correlated positively with surgery time (p < 0.05). A direct proportionality between linear and volume differences was observed, higher values at T1 correlated with higher values at T2 (p < 0.05).

CONCLUSIONS

An innovative digital workflow for precise quantification of postoperative facial changes was implemented, incorporating volumetric measurements that surpass linear assessments. Clinical conditions demonstrated a direct correlation with surgery time, deteriorating immediately and improving one-week after surgery.

摘要

背景

下颌第三磨牙(M3M)的拔除是口腔颌面外科的常规手术,常伴有术后疼痛、面部肿胀和牙关紧闭等症状。本研究旨在介绍一种下颌第三磨牙拔除术后肿胀分析的标准化和自动化方案,报告术后即刻和一周时的临床情况。

方法

在一项前瞻性研究中,共纳入 35 例(平均年龄:24.4±5.8 岁)患者,接受 54 颗 M3M 的拔除。术前(T0)、术后 3 天(T1)和 7 天(T2)通过 3D 面部扫描评估面部肿胀。开源软件 3DSlicer 实现了自动分析,包括数据匿名化、定向、表面配准、定性比较、线性测量和容积量化。面部模型的逐对叠加实现了定性、向量和定量评估,比较了初始状态与 T1 和 T2 时的肿胀发展情况。此外,还评估了 T1 和 T2 之间的变化。次要结局包括疼痛、牙关紧闭(最大张口度)和手术时间的临床评估。统计学分析采用配对学生 t 检验评估纵向变化,方差分析评估与难度评分相关的结局变量。线性回归模型将主要结局变量与次要研究变量相关联(α<0.05)。

结果

纵向分析显示 T1 时存在显著但变化的面部肿胀、疼痛和牙关紧闭,随后 T2 时有所改善(p<0.001)。线性和容积差异与手术时间呈正相关(p<0.05)。线性和容积差异之间存在直接比例关系,T1 时的高值与 T2 时的高值相关(p<0.05)。

结论

本研究实施了一种用于精确量化术后面部变化的创新数字化工作流程,纳入了超越线性评估的容积测量。临床情况与手术时间直接相关,术后即刻恶化,一周后改善。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb37/11575084/0ad777a18a2a/12903_2024_5193_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb37/11575084/d723948d05d2/12903_2024_5193_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb37/11575084/8a8a85b76b23/12903_2024_5193_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb37/11575084/d85bdc181089/12903_2024_5193_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb37/11575084/3c5781cc940c/12903_2024_5193_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb37/11575084/fcfb9063d4ad/12903_2024_5193_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb37/11575084/0ad777a18a2a/12903_2024_5193_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb37/11575084/d723948d05d2/12903_2024_5193_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb37/11575084/8a8a85b76b23/12903_2024_5193_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb37/11575084/d85bdc181089/12903_2024_5193_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb37/11575084/3c5781cc940c/12903_2024_5193_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb37/11575084/fcfb9063d4ad/12903_2024_5193_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb37/11575084/0ad777a18a2a/12903_2024_5193_Fig6_HTML.jpg

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