{"title":"Prediction of Skeletal Age Through Cervical Vertebral Measurements Using Different Machine Learning Regression Methods.","authors":"İrem Yılmaz, Merve Gonca","doi":"10.4274/TurkJOrthod.2025.2024.30","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>To compare skeletal ages determined using three different regression methods from measurements made on cervical vertebrae from lateral cephalometric radiographs (LCRs) with the skeletal age determined from hand-wrist radiographs (HWRs).</p><p><strong>Methods: </strong>LCRs and HWRs of 794 individuals (329 boys, 465 girls) aged 7-18 years were examined. The hand-wrist skeletal age of the participants was determined using the Greulich-Pyle (GP) atlas. Forty-four linear and nine angular morphometric measurements in the C2-C5 vertebrae were made in LCRs. Vertebral skeletal age (VSA) was determined in both sexes using Ridge, the least absolute shrinkage and selection operator (LASSO), and ElasticNet regression methods. The study results were evaluated using R2 (explainability power). Bland-Altman analysis was performed to determine the consistency of chronologic age (CA), GP age, and VSAs.</p><p><strong>Results: </strong>LASSO regression showed the highest explainability power for VSA, with boys at 0.783 and girls at 0.741. In both sexes, the vertebral depth of concavities had high beta coefficients, and the posterior height of C3 vertebrae (TVup-TVlp) had the highest beta coefficient in boys in LASSO regression. The width of the limits of agreement in both CA and VSA graphs of GP age was wider in boys than in girls. The width of the limits of agreement of CA-VSAs was wider in girls than in boys.</p><p><strong>Conclusion: </strong>Although high R2 values were obtained, VSA showed no superiority over CA in the assessment of skeletal age, and no significant clinical advantage was observed. For the Turkish population, using GP age may be more accurate for determining skeletal age in orthodontic treatment planning.</p>","PeriodicalId":37013,"journal":{"name":"Turkish Journal of Orthodontics","volume":"38 1","pages":"36-48"},"PeriodicalIF":0.8000,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Turkish Journal of Orthodontics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4274/TurkJOrthod.2025.2024.30","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"DENTISTRY, ORAL SURGERY & MEDICINE","Score":null,"Total":0}
引用次数: 0
摘要
目的比较根据头颅侧位X光片(LCR)对颈椎的测量结果用三种不同的回归方法确定的骨骼年龄与根据手-腕X光片(HWR)确定的骨骼年龄:检查了 794 名 7-18 岁儿童(329 名男孩,465 名女孩)的头颅侧位X光片和手-腕位X光片。采用格雷利希-派尔(Greulich-Pyle,GP)地图册确定了参与者的手-腕骨骼年龄。在 LCR 中对 C2-C5 椎体进行了 44 次线性和 9 次角度形态测量。使用 Ridge、最小绝对收缩和选择算子(LASSO)以及 ElasticNet 回归方法确定了男女的椎体骨骼年龄(VSA)。研究结果使用 R2(解释力)进行评估。进行了Bland-Altman分析,以确定年代学年龄(CA)、GP年龄和VSAs的一致性:结果:LASSO 回归结果显示,VSA 的可解释力最高,男孩为 0.783,女孩为 0.741。在两性中,椎体凹陷深度的贝塔系数都很高,而在 LASSO 回归中,C3 椎体后方高度(TVup-TVlp)在男孩中的贝塔系数最高。在 GP 年龄的 CA 和 VSA 曲线图中,男孩的一致性界限宽度比女孩宽。结论:结论:虽然获得了较高的 R2 值,但在评估骨骼年龄方面,VSA 并未显示出优于 CA,也未观察到明显的临床优势。对于土耳其人来说,在正畸治疗计划中使用 GP 年龄来确定骨骼年龄可能更准确。
Prediction of Skeletal Age Through Cervical Vertebral Measurements Using Different Machine Learning Regression Methods.
Objective: To compare skeletal ages determined using three different regression methods from measurements made on cervical vertebrae from lateral cephalometric radiographs (LCRs) with the skeletal age determined from hand-wrist radiographs (HWRs).
Methods: LCRs and HWRs of 794 individuals (329 boys, 465 girls) aged 7-18 years were examined. The hand-wrist skeletal age of the participants was determined using the Greulich-Pyle (GP) atlas. Forty-four linear and nine angular morphometric measurements in the C2-C5 vertebrae were made in LCRs. Vertebral skeletal age (VSA) was determined in both sexes using Ridge, the least absolute shrinkage and selection operator (LASSO), and ElasticNet regression methods. The study results were evaluated using R2 (explainability power). Bland-Altman analysis was performed to determine the consistency of chronologic age (CA), GP age, and VSAs.
Results: LASSO regression showed the highest explainability power for VSA, with boys at 0.783 and girls at 0.741. In both sexes, the vertebral depth of concavities had high beta coefficients, and the posterior height of C3 vertebrae (TVup-TVlp) had the highest beta coefficient in boys in LASSO regression. The width of the limits of agreement in both CA and VSA graphs of GP age was wider in boys than in girls. The width of the limits of agreement of CA-VSAs was wider in girls than in boys.
Conclusion: Although high R2 values were obtained, VSA showed no superiority over CA in the assessment of skeletal age, and no significant clinical advantage was observed. For the Turkish population, using GP age may be more accurate for determining skeletal age in orthodontic treatment planning.