{"title":"一种用于法医年龄估计的射线照片角度数字化测量方法","authors":"Ashith B. Acharya","doi":"10.1016/j.jofri.2017.09.002","DOIUrl":null,"url":null,"abstract":"<div><h3>Objective</h3><p>Age estimation has important legal ramifications and assessing it, particularly in living adults, can prove challenging on occasion. This paper explores the use of gonial angle in age estimation, applying a new digital method which may be suitable in elderly subjects when many/all teeth are missing.</p></div><div><h3>Materials and methods</h3><p>A commercially available and ubiquitous software was used to measure the gonial angle on digital orthopantomographs from 100 subjects (48 males and 52 females; age range 18–89 years) which was subjected to linear regression analysis.</p></div><div><h3>Results</h3><p>The correlation coefficient for the gonial angle on the right side (<em>r</em> = 0.25) was greater than that for the left side (<em>r</em> = 0.23). Both correlations were statistically significant (<em>p</em> < 0.05). The regression equations derived were tested on a holdout sample (<em>n</em> = 17; age range 21–71 years) and revealed a mean absolute difference of approximately ± 14 years for the two regression equations.</p></div><div><h3>Conclusion</h3><p>Although the gonial angle may not consistently change with an increase in chronologic age, the digital method proposed here may be one of few options available for use in the elderly with minimal or no teeth seeking retirement benefits, and may be applied as a method of last resort in geriatric age prediction.</p></div>","PeriodicalId":45371,"journal":{"name":"Journal of Forensic Radiology and Imaging","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.jofri.2017.09.002","citationCount":"7","resultStr":"{\"title\":\"A digital method of measuring the gonial angle on radiographs for forensic age estimation\",\"authors\":\"Ashith B. Acharya\",\"doi\":\"10.1016/j.jofri.2017.09.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objective</h3><p>Age estimation has important legal ramifications and assessing it, particularly in living adults, can prove challenging on occasion. This paper explores the use of gonial angle in age estimation, applying a new digital method which may be suitable in elderly subjects when many/all teeth are missing.</p></div><div><h3>Materials and methods</h3><p>A commercially available and ubiquitous software was used to measure the gonial angle on digital orthopantomographs from 100 subjects (48 males and 52 females; age range 18–89 years) which was subjected to linear regression analysis.</p></div><div><h3>Results</h3><p>The correlation coefficient for the gonial angle on the right side (<em>r</em> = 0.25) was greater than that for the left side (<em>r</em> = 0.23). Both correlations were statistically significant (<em>p</em> < 0.05). The regression equations derived were tested on a holdout sample (<em>n</em> = 17; age range 21–71 years) and revealed a mean absolute difference of approximately ± 14 years for the two regression equations.</p></div><div><h3>Conclusion</h3><p>Although the gonial angle may not consistently change with an increase in chronologic age, the digital method proposed here may be one of few options available for use in the elderly with minimal or no teeth seeking retirement benefits, and may be applied as a method of last resort in geriatric age prediction.</p></div>\",\"PeriodicalId\":45371,\"journal\":{\"name\":\"Journal of Forensic Radiology and Imaging\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.jofri.2017.09.002\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Forensic Radiology and Imaging\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2212478017300023\",\"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 Forensic Radiology and Imaging","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2212478017300023","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A digital method of measuring the gonial angle on radiographs for forensic age estimation
Objective
Age estimation has important legal ramifications and assessing it, particularly in living adults, can prove challenging on occasion. This paper explores the use of gonial angle in age estimation, applying a new digital method which may be suitable in elderly subjects when many/all teeth are missing.
Materials and methods
A commercially available and ubiquitous software was used to measure the gonial angle on digital orthopantomographs from 100 subjects (48 males and 52 females; age range 18–89 years) which was subjected to linear regression analysis.
Results
The correlation coefficient for the gonial angle on the right side (r = 0.25) was greater than that for the left side (r = 0.23). Both correlations were statistically significant (p < 0.05). The regression equations derived were tested on a holdout sample (n = 17; age range 21–71 years) and revealed a mean absolute difference of approximately ± 14 years for the two regression equations.
Conclusion
Although the gonial angle may not consistently change with an increase in chronologic age, the digital method proposed here may be one of few options available for use in the elderly with minimal or no teeth seeking retirement benefits, and may be applied as a method of last resort in geriatric age prediction.