颞下颌疾病患者下颌髁的分形分析。

Esra Yavuz, Selmi Yardimci Tunc, Humeyra Tercanli
{"title":"颞下颌疾病患者下颌髁的分形分析。","authors":"Esra Yavuz, Selmi Yardimci Tunc, Humeyra Tercanli","doi":"10.1007/s10278-025-01669-2","DOIUrl":null,"url":null,"abstract":"<p><p>Fractal analysis (FA) is a mathematical method used to evaluate irregular and complex shapes. The numerical result obtained from FA is called fractal dimension (FD). FA can detect subtle bone changes in diseases that affect bone microstructures such as temporomandibular disorder (TMD), even when these changes are not visible on radiographs. It provides objective results that can improve clinical diagnosis without creating extra burden for patients. This study aimed to evaluate the relationship between FD values and both the severity of TMD and degenerative changes in temporomandibular joints (TMJ). Specifically, we aimed to assess the diagnostic capacity of FA for TMD. This study included 161 participants. The presence and severity of TMD in the participants were evaluated using the Fonseca Anamnestic Index (FAI). Degenerative bone changes in the participants' mandibular condyles were categorized as flattening, osteophytes, and erosion on panoramic radiographic Images. FA was performed using ImageJ 1.49 software on panoramic radiographs. Data were analyzed using independent samples t-test and one-way ANOVA. Post hoc multiple comparisons were evaluated with the least significant difference test (LSD). Statistical significance was considered at p < 0.05. The severe TMD group had the lowest mean FD value (1.36 ± 0.11), whereas the group with no TMD (1.48 ± 0.11) had the highest mean FD value. In each case, the mean FD value was found to be statistically significantly lower in participants with flattening, osteophyte, or erosion than in those without (p < 0.001 for each comparison). Our main findings suggest that FD values were significantly associated with both the severity of TMD and with each type of degenerative bone changes we investigated. FA may provide valuable, quantitative information to improve the diagnosis of TMD. As such, FA may support clinicians in making early and accurate diagnoses and treatment decisions.</p>","PeriodicalId":516858,"journal":{"name":"Journal of imaging informatics in medicine","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fractal Analysis of Mandibular Condyles in Patients with Temporomandibular Disorder.\",\"authors\":\"Esra Yavuz, Selmi Yardimci Tunc, Humeyra Tercanli\",\"doi\":\"10.1007/s10278-025-01669-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Fractal analysis (FA) is a mathematical method used to evaluate irregular and complex shapes. The numerical result obtained from FA is called fractal dimension (FD). FA can detect subtle bone changes in diseases that affect bone microstructures such as temporomandibular disorder (TMD), even when these changes are not visible on radiographs. It provides objective results that can improve clinical diagnosis without creating extra burden for patients. This study aimed to evaluate the relationship between FD values and both the severity of TMD and degenerative changes in temporomandibular joints (TMJ). Specifically, we aimed to assess the diagnostic capacity of FA for TMD. This study included 161 participants. The presence and severity of TMD in the participants were evaluated using the Fonseca Anamnestic Index (FAI). Degenerative bone changes in the participants' mandibular condyles were categorized as flattening, osteophytes, and erosion on panoramic radiographic Images. FA was performed using ImageJ 1.49 software on panoramic radiographs. Data were analyzed using independent samples t-test and one-way ANOVA. Post hoc multiple comparisons were evaluated with the least significant difference test (LSD). Statistical significance was considered at p < 0.05. The severe TMD group had the lowest mean FD value (1.36 ± 0.11), whereas the group with no TMD (1.48 ± 0.11) had the highest mean FD value. In each case, the mean FD value was found to be statistically significantly lower in participants with flattening, osteophyte, or erosion than in those without (p < 0.001 for each comparison). Our main findings suggest that FD values were significantly associated with both the severity of TMD and with each type of degenerative bone changes we investigated. FA may provide valuable, quantitative information to improve the diagnosis of TMD. As such, FA may support clinicians in making early and accurate diagnoses and treatment decisions.</p>\",\"PeriodicalId\":516858,\"journal\":{\"name\":\"Journal of imaging informatics in medicine\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-09-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of imaging informatics in medicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s10278-025-01669-2\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of imaging informatics in medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s10278-025-01669-2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

分形分析(FA)是一种用于评价不规则和复杂形状的数学方法。由FA得到的数值结果称为分形维数(FD)。FA可以在影响骨微结构的疾病(如颞下颌紊乱(TMD))中发现细微的骨变化,即使这些变化在x光片上不可见。它提供客观的结果,可以提高临床诊断,而不会给患者带来额外的负担。本研究旨在评估FD值与颞下颌关节(TMJ)严重程度和退行性改变之间的关系。具体来说,我们旨在评估FA对TMD的诊断能力。这项研究包括161名参与者。使用Fonseca记忆指数(FAI)评估参与者TMD的存在和严重程度。参与者下颌骨髁的退行性骨变化在全景x线摄影图像上被分类为扁平,骨赘和侵蚀。采用ImageJ 1.49软件对全景x线片进行FA分析。数据分析采用独立样本t检验和单因素方差分析。采用最小显著性差异检验(LSD)评价事后多重比较。p为统计学显著性
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fractal Analysis of Mandibular Condyles in Patients with Temporomandibular Disorder.

Fractal analysis (FA) is a mathematical method used to evaluate irregular and complex shapes. The numerical result obtained from FA is called fractal dimension (FD). FA can detect subtle bone changes in diseases that affect bone microstructures such as temporomandibular disorder (TMD), even when these changes are not visible on radiographs. It provides objective results that can improve clinical diagnosis without creating extra burden for patients. This study aimed to evaluate the relationship between FD values and both the severity of TMD and degenerative changes in temporomandibular joints (TMJ). Specifically, we aimed to assess the diagnostic capacity of FA for TMD. This study included 161 participants. The presence and severity of TMD in the participants were evaluated using the Fonseca Anamnestic Index (FAI). Degenerative bone changes in the participants' mandibular condyles were categorized as flattening, osteophytes, and erosion on panoramic radiographic Images. FA was performed using ImageJ 1.49 software on panoramic radiographs. Data were analyzed using independent samples t-test and one-way ANOVA. Post hoc multiple comparisons were evaluated with the least significant difference test (LSD). Statistical significance was considered at p < 0.05. The severe TMD group had the lowest mean FD value (1.36 ± 0.11), whereas the group with no TMD (1.48 ± 0.11) had the highest mean FD value. In each case, the mean FD value was found to be statistically significantly lower in participants with flattening, osteophyte, or erosion than in those without (p < 0.001 for each comparison). Our main findings suggest that FD values were significantly associated with both the severity of TMD and with each type of degenerative bone changes we investigated. FA may provide valuable, quantitative information to improve the diagnosis of TMD. As such, FA may support clinicians in making early and accurate diagnoses and treatment decisions.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信