Comparison of cone-beam computed tomography and panoramic radiography in estimating the 18-year age threshold with the third molar maturity index: a retrospective study

Comparison of cone-beam computed tomography and panoramic radiography in estimating the 18-year age threshold with the third molar maturity index: a retrospective study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Comparison of cone-beam computed tomography and panoramic radiography in estimating the 18-year age threshold with the third molar maturity index: a retrospective study Münevver Gamze Diricanlı, Nursel Akkaya, Hatice Yağmur Zengin This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7621082/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Dec, 2025 Read the published version in BMC Oral Health → Version 1 posted 17 You are reading this latest preprint version Abstract Background The third molar maturity index (I3M) method, introduced for application on panoramic radiographs, is used to assess whether an individual has reached the legal 18-year age threshold. This study aimed to evaluate the applicability of the I3M method to cone-beam computed tomography (CBCT) scans and to compare the results with those obtained from panoramic radiographs of the same patients. Methods Patients who had already received both CBCT scans and panoramic radiographs were selected retrospectively. The maturity index values of 418 mandibular third molars were obtained via measurements via both CBCT scans and panoramic radiographs. The accuracy of the I3M method for both radiological methods was evaluated via receiver operating characteristic (ROC) curve analysis. The sensitivity, specificity, misclassification rate, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (PLR), negative likelihood ratio (NLR), and overall area under the ROC curve (AUROC) at the 95% confidence interval (CI) level were calculated as performance measures for both imaging modalities. Results Both imaging modalities showed excellent diagnostic performance, with AUROC values of 0.928 for CBCT and 0.932 for panoramic radiography. The sensitivity of CBCT was 82.0%, the specificity was 89.7%, and the misclassification rate was 14.1%. For panoramic radiography, the sensitivity was 85.1%, the specificity was 86.8%, and the misclassification rate was 18.1%. The PLR and NLR values for CBCT were 7.96 and 0.20, respectively, whereas those for panoramic radiography were 6.43 and 0.17, respectively. Additionally, the PPV and NPV values for CBCT were 0.943 and 0.705, respectively, and those for panoramic radiography were 0.930 and 0.738, respectively. Conclusions The results indicated that the accuracy of the I3M method for CBCT scans was similar to that for panoramic radiographs from the same individuals. Importantly, the I3M method used to estimate the legal 18-year age threshold can also be used for CBCT scans, as it enables the use of existing CBCT images in age estimation studies. Forensic dentistry age estimation third molar maturity index CBCT panoramic radiography Figures Figure 1 Figure 2 Figure 3 Figure 4 INTRODUCTION In the domain of forensic dentistry, the estimation of age is of paramount importance both in the postmortem identification process and in living individuals. It is useful for unidentified human remains, including those who have fallen victim to war or disaster, as well as those unearthed during archaeological studies. In the context of legal and social affairs, the assessment of age may be necessary, particularly in cases involving asylum seekers and refugees who lack official identification. Its use is frequently required in a variety of contexts, including military service, civil employment, marriage, adoption, participation in sports competitions, and criminal cases where legal responsibility must be determined ( 1 ). Dental age estimation can be conducted via methods based on developmental features, such as the degree of mineralization or the eruption stage of the teeth, as well as age-related changes that occur throughout life, including attrition, secondary dentin deposition, periodontosis, cementum apposition, root resorption, and root transparency. Further techniques include the analysis of aspartic acid racemization in dentin, telomere shortening in pulpal DNA, and radiocarbon levels in enamel ( 2 , 3 ). The stages of tooth development offer reliable indicators of an individual’s biological age, enabling age estimation in children with a relatively low margin of error ( 4 ). However, because physical maturation is complete, several age indicators, including skeletal development, secondary sexual characteristics, height, weight, and dental development, become less reliable in people who are close to the legal age threshold of 18. In such cases, the focus shifts from estimating the exact chronological age to determining whether the individual falls above or below the legally defined age threshold ( 5 , 6 ). The apical closure of the third molar is completed at approximately 20 ± 2 years of age, although interpopulational variations are recognized ( 7 – 9 ). Therefore, evaluating the degree of apical closure of the third molar can be useful for determining whether an individual is under or over the 18-year age threshold. Dental development staging approaches, such as the Demirjian method, can be used for this purpose. A significant correlation exists between the age and development of third molars, as determined by the Demirjian mineralization stages ( 10 , 11 ). In 2008, Cameriere et al. ( 6 ) created a new approach that measures the open apices of the mandibular third molar as an alternative to staging systems to assess the 18-year-old threshold in living individuals. They compared this measurement-based method with the Demirjian stages and obtained better sensitivity and specificity than did the Demirjian method. The third molar maturity index (I3M) is one such method used to assess whether an individual has reached the age of 18 ( 6 ). In this method, the sum of the apical opening measures is normalized by dividing it by the tooth's length to solve the magnification issue, which can impair measurement accuracy and is one of the disadvantages of panoramic radiography ( 12 ). Notwithstanding the issue of geometric distortion in the resulting image, panoramic radiography is frequently used in forensic age estimation studies because it is a widely preferred imaging technique in clinical practice because of the comfort it provides for patients, ease of use for physicians, and low degree of radiation exposure. The I3M method has been validated across many populations. ( 13 ). Compared with traditional CT, cone beam computed tomography (CBCT) generates high-resolution images of superior diagnostic quality, with brief scanning durations and less radiation exposure ( 14 ). Technological advancements have significantly reduced irradiation, resulting in improved information quality for diagnostic tasks. Compared with conventional scanners, low-dose and ultralow-dose CBCT scanners can reduce radiation exposure by as much as 87% ( 15 ). This reduction holds particular significance for younger patients and individuals, necessitating multiple scans ( 16 ). The use of CBCT imaging is increasing throughout various fields of dentistry, including maxillofacial surgery, implantology, orthodontics, endodontics, periodontics, and evaluation of the temporomandibular joints. Considering the current rise in the use of CBCT scans in dentistry, it is necessary to evaluate the relevance of the third molar maturity index method alongside CBCT imaging. Therefore, we aimed to examine the applicability of the I3M method for CBCT scans compared with panoramic radiographs. METHODS The study protocol (research number SBA 23/248) was conducted in accordance with the ethical standards of the Declaration of Helsinki and received approval from the Hacettepe University Health Sciences Research Ethics Committee on October 24, 2023 (Approval No: 2023/05–13). This study is one of the two work packages that constitute the speciality thesis in Dentomaxillofacial Radiology. Ethical approval was obtained for each component of the study. The study population comprised CBCT and panoramic radiographic records obtained for various clinical indications between January 2018 and September 2023 at the Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, Hacettepe University. The required sample size was 138 third molar teeth from individuals aged ≥ 18 years and 276 third molar teeth from individuals aged < 18 years. This sample size provides 80% power to detect a difference of 0.06 between the area under the ROC curve (AUROC) under the null hypothesis (0.84, obtained from a reference study [17]) and the AUROC under the alternative hypothesis (0.90), using a two-sided z test at a significance level of 0.05. Power analysis was carried out via PASS 15 software. The inclusion criteria for the study were as follows: the individuals were between 15 and 23 years of age; the presence of at least one lower third molar tooth; the absence of any pathology, trauma, or developmental anomaly in the region of interest; and no previous surgical intervention in this region. To compare the efficacy of CBCT and panoramic imaging, patients whose images were taken within a six-month period were identified. To ensure optimal image quality, CBCT scans obtained with a wide field of view (FOV), CBCT images with motion or metal artifacts, and panoramic radiographs with artifacts and inadequate density and contrast were excluded from the study. Initially, researchers reviewed the radiologic images of a total of 1,249 patients aged 15–23 years. Images that fulfilled the inclusion criteria were selected. In total, 418 third molar regions from 232 patients were included in the study. Imaging procedures and measurements CBCT scans were acquired via the i-CAT Next Generation device (Imaging Sciences International, Hatfield, PA, USA) with the following exposure parameters: 120 kVp tube voltage; tube current ranging from 3–7 mA depending on the FOV and voxel size; and adjusted exposure times. The images were analyzed via i-CAT Vision software, versions 17–19. Panoramic radiographs were obtained via an Orthophos XG 5 (Sirona Dental Company, Bensheim, Germany; 60–90 kVp, 3–16 mA, 14 s) and a Veraview IC5 (Morita Corporation, Kyoto, Japan; 60–70 kVp, 1–7.5 mA, 5.5–10 s), with exposure parameters adjusted according to the patient’s size. The measurements on panoramic radiographs were performed via ImageJ software, version 1.54 g (National Institutes of Health, Bethesda, MD, USA; https://imagej.org ). The I3M value is calculated by dividing the sum of the widths of the open apices of the mandibular third molar roots by the tooth length. This index is used to estimate whether an individual is above or below the legal age threshold of 18 years. According to the recommended cutoff value of 0.08, individuals with an I3M value < 0.08 are considered likely older than 18, whereas those with an I3M value ≥ 0.08 are considered likely younger than 18. For CBCT measurements, volumetric data were examined in multiplanar reconstruction (MPR) views displaying coronal, sagittal, and axial sections. The axial plane was adjusted to obtain the widest and tallest mesiodistal section of the mandibular third molar in a nonorthogonal projection. In cases where root development was incomplete, the distance between the inner surfaces of the open apices was measured. If the tooth had two roots, the total distance between the inner surfaces of both open apices was summed and divided by the tooth length to calculate the I3M value (Fig. 1 ). If root development was complete, I3M was recorded as 0. I3M = A8/L8 (sum of open apex widths/tooth length) To evaluate intra- and interobserver reliability, two observers repeated the measurements on approximately 10%-15% of the randomly selected CBCT scans and panoramic radiographs at least two weeks after the initial assessments (Table 1 ). Table 1 Intraclass correlation coefficient (ICC) values and 95% confidence intervals (CIs) for intra- and interobserver agreement Imaging Method Intra-Observer Agreement (95% CI) Inter-Observer Agreement (95% CI) CBCT 0.984 (0.974–0.990) 0.983 (0.973–0.990) Panoramic 0.966 (0.936–0.982) 0.983 (0.968–0.991) The chronological age of each patient was calculated by subtracting the date of birth from the radiograph acquisition date and was expressed in decimal years. The I3M values for each tooth, along with the calculated decimal age values and the subjects' sex data, were recorded. Statistical analysis The intraclass correlation coefficient (ICC) based on a two-way mixed effects model was calculated to evaluate the intra- and interobserver reliability of the I3M measurements obtained from the CBCT and panoramic radiographs ( 17 ). The normality of the numerical variables was assessed via the Kolmogorov–Smirnov test. For normally distributed variables, descriptive statistics were presented as mean ± standard deviation, while categorical variables were summarized as frequencies and percentages (n, %). The agreement between the CBCT and panoramic I3M measurements was evaluated via Spearman’s rho correlation coefficient and Bland–Altman analysis. Age was subsequently categorized into two groups: <18 years and ≥ 18 years. The association between age and sex was examined via Pearson’s chi-square test. Studies concerning the estimation of age thresholds use sensitivity, specificity, PPV, NPV, LR (both positive and negative), and AUROC values as measures of classification performance for I3M. In this study, sensitivity, or the true positive rate, measures how well the I3M method can classify true adults. In other words, sensitivity represents the proportion of individuals classified as true positive/adult by the I3M method compared with the total number of adults in the sample. Specificity, or the true negative rate, indicates how well the I3M method identifies minors. In our study, it represents the proportion of individuals classified as negative/minor by the I3M method to all children in the sample. The AUROC value measures the overall performance of the I3M. This value determines the ability of the test to discriminate between adults and minors. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the performance of CBCT and panoramic I3M measurements in predicting age categories. Afterwards, the differences between the areas under the ROC curves (AUROCs) were tested via DeLong’s test for two correlated ROC curves. The sensitivity, specificity, PPV, NPV, PLR, NLR, and misclassification rates were calculated with 95% confidence intervals (CIs) for the assessment of the predictive performance of I3M measurements in age classification. Likelihood ratio values remain unaffected by prevalence and serve as indicators of the probability of a diagnostic test result for an individual. A higher PLR value indicates greater accuracy of the cutoff score. The NLR ranges from 0 to 1. A proximity to zero increases the likelihood that the I3M method will accurately classify an individual as minor at the specified cutoff score. All the analyses were conducted via IBM SPSS Statistics v29.0 for Windows. The significance level was set at 0.05. RESULTS The intra- and interobserver agreements for the panoramic and CBCT imaging modalities, as assessed by the ICC and corresponding 95% CI, are presented in Table 1 . The ICC values indicate excellent intra- and interobserver reliability for measurements performed on both panoramic and CBCT images ( 18 ). A total of 418 mandibular third molars meeting the inclusion criteria were evaluated. The mean age ± standard deviation was 19.57 ± 2.47 years. The sample consisted of 222 females and 196 males. The age and sex distributions of the sample are presented in Table 2 , and the distribution by sex according to the 18-year age category is shown in Table 3 . When the sex distribution across age groups was examined (Table 3 ), the age distribution was found to be homogeneous between sexes (p = 0.274). The correlation coefficient between the CBCT and panoramic measurements was 0.898 (p < 0.001). The Bland–Altman analysis results obtained for the two imaging methods, i.e., CBCT and panoramic imaging, are presented below (Fig. 2 ). Overall, the measurements obtained by the different methods were consistent, and no systematic bias was observed. Although some observations fell outside the limits of agreement, the proportion of these cases remained below 5%, and such observations reflect possible situations encountered in clinical practice (Fig. 2 ). Table 2 Age and sex distributions of the sample Age Groups Sex Total Female Male 15.00–15.99 20 20 40 16.00–16.99 28 23 51 17.00–17.99 19 26 45 18.00–18.99 17 18 35 19.00–19.99 19 18 37 20.00–20.99 18 23 41 21.00–21.99 41 29 79 22.00–22.99 60 39 99 Total 222 196 418 Table 3 Sample distribution by sex and the 18-year age threshold Sex ≥ 18 Years < 18 Years Total Female 155 67 222 Male 127 69 196 Total 282 136 418 Before conducting the comparative analysis of imaging modalities, the potential effect of sex on classification performance was assessed by generating sex-specific ROC curves. The ROC curves stratified by sex are presented below (Fig. 3 ). The AUROC values were 0.958 (95% CI: 0.934–0.982) for females and 0.914 (95% CI: 0.871–0.958) for males. These values indicate that the method has excellent classification accuracy for both sexes ( 19 , 20 ). The AUROC values demonstrated that the method has high discriminative power for both females and males, indicating that it can be reliably applied regardless of sex. Therefore, the subsequent analyses were conducted independently of sex. The frequencies of true positives (TPs), false positives (FPs), true negatives (TNs), and false negatives (FNs) used to calculate sensitivity and specificity according to the I3M cutoff value < 0.08 are presented in Table 4 . On the basis of these values, key performance metrics for both imaging methods—sensitivity, specificity, PPV, NPV, PLR, NLR, and overall AUROC—are provided in Table 5 . Table 4 Classification performance of the I3M method based on panoramic and CBCT imaging Imaging Method I3M Value ≥ 18 Years < 18 Years Total Panoramic I3M < 0.08 240 TP 18 FP 258 I3M ≥ 0.08 42 FN 118 TN 160 Total 282 136 418 CBCT I3M < 0.08 231 TP 14 FP 245 I3M ≥ 0.08 51 FN 122 TN 173 Total 282 136 418 * TP = true positive, FP = false positive, TN = true negative, FN = false negative Table 5 Performance metrics and 95% CI values of I3M < 0.08 according to imaging methods Metric Panoramic Radiography CBCT Sensitivity 0.851 (0.804–0.890) 0.819 (0.769–0.862) Specificity 0.868 (0.799–0.920) 0.897 (0.833–0.943) LR+ 6.43 (4.17–9.92) 7.96 (4.83–13.11) LR– 0.17 (0.13–0.23) 0.20 (0.16–0.26) PPV 0.930 (0.896–0.954) 0.943 (0.909–0.965) NPV 0.738 (0.678–0.789) 0.705 (0.650–0.755) AUROC 0.932 (0.907–0.958) 0.928 (0.901–0.954) The ROC curves illustrating the classification performance of the I3M index for both panoramic and CBCT images are shown in Fig. 4 . DISCUSSION In many countries, the age of majority represents a critical legal threshold for determining criminal responsibility, civil rights, and access to social policies. The United Nations Convention on the Rights of the Child (1989) defines anyone under the age of 18 as a child, which emphasizes the value of identity verification and birth registration. However, in some countries or communities, the absence of official birth records renders children legally 'invisible', increasing their vulnerability to human rights violations. Children without valid identification documents face an elevated risk of being recruited for the military at a young age, engaging in hazardous labor, entering early marriages, or being prosecuted as adults in criminal proceedings. Undocumented, displaced, and migrant children are vulnerable to various forms of abuse and exploitation ( 21 ). Owing to the recent global increase in migration, there is a growing demand for reliable age estimation methods—particularly to determine whether an individual has reached the legal age of majority. The I3M method is a radiographic method used for age estimation and is based on panoramic radiographs ( 6 ). This method evaluates whether an individual has reached the age of the majority. A cutoff value of 0.08 was proposed to distinguish legal adulthood. The applicability of the I3M method using panoramic radiographs has been evaluated across various populations, with a consensus supporting its reliability and feasibility ( 13 , 22 – 24 ). In the original study by Cameriere et al. ( 6 ), only the left mandibular third molars were assessed. Subsequent studies have indicated that there are no statistically significant differences in third molar development between the right and left sides ( 25 – 27 ). Angelakopoulos et al. ( 28 ) reported no significant difference between right and left mandibular third molars when the age of the majority was assessed via the I3M method, which is based on a large multiethnic sample of 10,181 panoramic radiographs collected from various countries in Africa, North and South America, Asia, and Europe. On the basis of these findings, both right and left mandibular third molars were included in the present study. Nevertheless, if a notable disparity is observed between the development of the left and right third molars in any case under consideration, taking into account the less developed tooth in accordance with the principle of the “best interests of the child” is beneficial ( 29 ). To investigate the potential influence of sex before the imaging methods were compared, ROC curves were generated separately for male and female subjects. The difference between the areas under the ROC curves (AUROCs) was not statistically significant (p ˃ 0.05). High AUROC values (≥ 0.9) for females and males indicate excellent classification accuracy ( 30 ). Our findings demonstrate that the method has strong discriminative ability for both sexes, suggesting that it can be reliably applied irrespective of sex. Similarly, Cameriere et al. ( 6 ), De Luca et al. ( 31 ) and Araújo et al. ( 32 ) reported that the predictive accuracy of the method is unaffected by sex. However, some studies have suggested that sex is a factor to be considered in the evaluation of third molar development ( 33 – 35 ). Nevertheless, in a recent meta-analysis, Santiago et al. ( 13 ) concluded that the I3M method is an effective and appropriate tool for forensic age estimation, regardless of sex. In studies comparing the performance of diagnostic tests, several factors may influence measurement accuracy, including the diagnostic method itself, the imaging tools employed, and the observers conducting the evaluations ( 36 ). The validity and reliability of the I3M method have been shown in various prior investigations involving diverse ethnic groups ( 13 ). Prior to comparing the imaging modalities, both intra- and interobserver reliability were assessed, as observer consistency represents a critical variable that may affect outcomes. The results demonstrated excellent agreement for both panoramic and CBCT imaging modalities ( 18 ). In this study, the sensitivity, specificity and AUROC values were 85.1%, 86.8%, and 0.932, respectively, for panoramic radiography and 81.9%, 89.7%, and 0.928, respectively, for CBCT. Although panoramic radiography presented a marginally higher AUROC, both imaging modalities exhibited excellent classification performance ( 30 ). The sensitivity and specificity values obtained for the two radiological techniques are quite close to each other. Our findings revealed that the specificity is greater than the sensitivity for both imaging modalities. In accordance with the initial study ( 6 ), specificity generally appears higher than sensitivity in investigations evaluating the I3M method, with pooled estimates from the latest meta-analysis showing a sensitivity of 0.86 and a specificity of 0.93 ( 13 ). This is probably because the ethical priority of minimizing false-positive results rather than false-negative results was considered when determining the cutoff for the I3M method. Garamendi et al. ( 37 ) argue that errors implying that children are over 18 are ethically unacceptable because they violate the rights of minors. Consequently, testing methodologies used in forensic age assessment should reduce the technically unacceptable type of error that misclassifies adults as children; however, eliminating ethically unacceptable errors is crucial, especially in regard to the criminal responsibility of minors. In the literature, only a few studies have applied the I3M method via three-dimensional imaging techniques ( 38 – 40 ). Mazieres et al. ( 40 ) applied Camerière's method to computed tomography (CT) scans and panoramic radiographs taken from the same individuals either at short intervals or through a double sampling approach, as in the methodology of our study. Çakan et al. ( 38 ) compared periapical, panoramic, and CBCT imaging modalities via the I3M technique and reported AUROC values of 0.831 for panoramic images and 0.727 for CBCT. They reported that the sensitivity and specificity values were 61.9% and 100%, respectively, for CBCT and 71% and 97%, respectively, for panoramic radiography. Our study revealed higher AUROC values for both imaging modalities than did their study. In addition, the sensitivity and specificity values in both studies differ, despite the testing samples being Turkish individuals. This difference may be attributed to a spectrum effect, likely resulting from their study testing each imaging method on different groups of patients. Yurdabakan et al. ( 39 ) reported that the sensitivity, specificity and accuracy were 93.5%, 97.4%, and 95.9%, respectively, in their CBCT study. While specificity values are generally high, sensitivity values vary among these studies and radiological methods. All these values, which are performance measures, are higher than those in our study. Differences in equipment used or interobserver variability in measurement techniques may also have contributed to this variation in results. Although Yurdabakan et al. ( 39 ) did not compare CBCT with panoramic imaging in the same subjects and the sample size of the study was small, their results are still promising, indicating that the method can produce satisfactory outcomes. Mazieres et al. ( 40 ), who compared the I3M method on panoramic radiographs and CT scans, reported high ICCs of 94.8% (95% CI: 90.7–97.1) for tooth 38 and 97.4% (95% CI: 94.9–98.7) for tooth 48. Our findings align closely with the level of agreement reported by Mazieres et al. ( 40 ). Although their study utilized CT imaging and ours employed CBCT, the similarity of outcomes between the two studies supports the applicability of the I3M method across three-dimensional imaging modalities. This consistency is especially relevant for forensic practice, reinforcing the potential of using existing dental images for determining the legal age of the majority. Mazieres et al. ( 40 ) reported a sensitivity of 77.8% and specificity of 94.1% for tooth 38 and a sensitivity of 75% and specificity of 93.8% for tooth 48 on CT scans. The minor differences between the findings of our study and those of Mazieres et al. ( 40 ) may be due to technical differences between the imaging modalities, even though both are three-dimensional in nature. The LR + value for the 18-year-old threshold indicates that the test has a chance of producing false positives, with approximately one in seven trials resulting in a false-positive outcome for panoramic radiography (LR + = 6.43). The LR + value of the CBCT scans suggested that there were at least eight true positives for every false positive; a minor was inaccurately detected in approximately one out of every nine instances (LR + = 7.96). The LR − score for both CBCT (LR− = 0.20) and panoramic radiography (LR− = 0.17) demonstrated that one false negative occurred for every five true negatives, indicating moderate reliability. However, no CBCT or CT studies have reported LR values as a performance metric for the I3M technique. However, a study conducted by Angelakopoulos et al. ( 28 ), which examined the difference between the right and left sides on panoramic radiographs, reported LR values similar to ours. Our PLR value for panoramic radiographs was similar to that of the American sample in this multiethnic study, whereas our negative LR value was similar to that of the American and European samples. Angelakopoulos et al. ( 28 ) reported mean LR + values of 8.59 for the left mandibular third molar and 8.51 for the right, whereas the LR- values were 0.31 for the left and 0.30 for the right. The retrospective nature of the study primarily limits the availability of detailed patient information. Furthermore, because the study took place at a single center, the analysis failed to include images from different imaging devices. In future studies, evaluating the I3M method via a sample of images obtained from various CBCT devices would be useful. Individuals are particularly sensitive to radiation during late adolescence and early adulthood, particularly during periods when age estimation is necessary to determine the age of the majority of individuals ( 41 ). While the CBCT radiation dose can be reduced by measures such as selecting a small field of view, panoramic radiography should be the preferred imaging modality for age estimation in children and adolescents ( 42 ). Furthermore, the use of existing CBCT images for age estimation eliminates the need for additional radiation doses. Therefore, the results of our study are important because they enable the use of existing images for age estimation. Consequently, the findings of our research are significant since they enable the use of available CBCT images for age estimates. Our study concluded that the I3M method demonstrates comparable accuracy when applied to both CBCT and panoramic radiography. Consequently, CBCT images may be used for the I3M method to estimate the 18-year threshold. Abbreviations I3M third molar maturity index CBCT cone-beam computed tomography CT computed tomography ROC:receiver operating characteristic PPV positive predictive value NPV negative predictive value PLR positive likelihood ratio NLR negative likelihood ratio AUROC area under the ROC curve CI confidence interval MPR multiplanar reconstruction ICC intraclass correlation coefficient TP true positive FP false positive TN true negative FN false negative Declarations Ethics approval and consent to participate This study (Research Number: SBA 23/248) was conducted in accordance with the ethical standards of the Declaration of Helsinki and was approved by the Hacettepe University Health Sciences Research Ethics Committee (Session Date: October 24, 2023; Session No: 2023/05; Decision No: 2023/05–13). This is a retrospective archive study. However, informed consent is obtained from all patients examined in our clinic. Consent for publication Not applicable Competing interests The authors declare that they have no competing interests. Clinical trial number Not applicable. Funding Not applicable. Author Contribution Conception and design of study: M.G.D., N.A. Acquisition of data: M.G.D., N.A. Analysis and/or interpretation of data: M.G.D., N.A., H.Y.Z. Drafting the manuscript: M.G.D., N.A. Revising the manuscript: M.G.D., N.A., H.Y.Z. Approval of the version of the manuscript to be published: M.G.D., N.A. Acknowledgements Not applicable. Data Availability The datasets generated and/or analyzed during the current study are not publicly available due to confidentiality of personal information but are available from the corresponding author on reasonable request. References Greene D, Williams D, Senn DR, Weems RA. Manual of Forensic Odontology: CRC Press; 2013. Available from: https://doi.org/10.1201/b13744 Verma M, Verma N, Sharma R, Sharma A. 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Uygulamalı istatistik ve geçerlik-güvenirlik: spor, sağlık ve eğitim bilimlerinden örneklerle. Detay Yayıncılık; 2010. Kılıç S. Klinik karar vermede ROC analizi. J Mood Disorders. 2013;3(3):135–40. Taşdemir F. ROC analizi ve R yazılımı ile verilerin sınıflama doğruluklarının karşılaştırılması. Ulusal Eğitim Akademisi Dergisi. 2022;6(2):230–41. Smith T, Brownlees L. Age assessment practices: a literature review & annotated bibliography. New York: United Nations Children’s Fund (UNICEF); 2011. AlQahtani S, Kawthar A, AlAraik A, AlShalan A. Third molar cut-off value in assessing the legal age of 18 in Saudi population. Forensic Sci Int. 2017;272:64–7. De Luca S, Pacifici A, Pacifici L, Polimeni A, Fischetto SG, Velandia Palacio LA, et al. Third molar development by measurements of open apices in an Italian sample of living subjects. J Forensic Leg Med. 2016;38:36–42. Nóbrega JBMd, Protasio APL, Ribeiro ILA, Valença AMG, Santiago BM, Cameriere R. Validation of the Third Molar Maturation Index to estimate the age of criminal responsibility in Northeastern Brazil. Forensic Sci Int. 2019;304:109917. Prieto JL, Barbería E, Ortega R, Magaña C. Evaluation of chronological age based on third molar development in the Spanish population. Int J Legal Med. 2005;119(6):349–54. Olze A, Niekerk Pv, Schulz R, Ribbecke S, Schmeling A. The influence of impaction on the rate of third molar mineralisation in male black Africans. Int J Legal Med. 2012;126:869–74. Karataş OH, Öztürk F, Dedeoğlu N, Çolak C, Altun O. Radiographic evaluation of third-molar development in relation to the chronological age of Turkish children in the southwest eastern Anatolia region. Forensic Sci Int. 2013;232(1):238. .e1-.e5 . Angelakopoulos N, Galić I, Balla S, Kiş H, Gómez Jiménez L, Zolotenkova G, et al. Comparison of the third molar maturity index (I3M) between left and right lower third molars to assess the age of majority: a multi-ethnic study sample. Int J Legal Med. 2021;135(6):2423–36. Giannitto N, Militi A, Sapienza D, Scurria S, Gualniera P, Mondello C, et al. Application of Third Molar Maturity Index (I3M) for Assessing Adult Age of 18 Years in a Southern Italian Population Sample. Eur J Dentistry. 2023;17(01):200–9. Çorbacıoğlu ŞK, Aksel G. Receiver operating characteristic curve analysis in diagnostic accuracy studies: A guide to interpreting the area under the curve value. Turkish J Emerg Med. 2023;23(4):195–8. De Luca S, Biagi R, Begnoni G, Farronato G, Cingolani M, Merelli V, et al. Accuracy of Cameriere's cut-off value for third molar in assessing 18 years of age. Forensic Sci Int. 2014;235:102. e1-. e6. Araújo AMMd P, KPd MLAFrança, Beltrão RV, Pontual AA. Association between mineralization of third molars and chronological age in a Brazilian sample. Revista Odonto Ciência. 2010;25:391–4. Deitos AR, Costa C, Michel-Crosato E, Galić I, Cameriere R, Biazevic MGH. Age estimation among Brazilians: younger or older than 18? J Forensic Leg Med. 2015;33:111–5. Blankenship JA, Mincer HH, Anderson KM, Woods MA, Burton EL, editors. Third molar development in the estimation of chronologic age in American blacks as compared with whites. Journal of Forensic Sciences; 2007. Akkaya N, Yilanci HÖ. Assessment of third molar maturity index for legal age threshold of 18 in a sample of Turkish individuals. Australian J Forensic Sci. 2021;53(3):314–24. Oakley C, Brunette DM. The use of diagnostic data in clinical dental practice. Dent Clin. 2002;46(1):87–115. Garamendi PM, Landa MI, Ballesteros J, Solano MA. Reliability of the methods applied to assess age minority in living subjects around 18 years old: A survey on a Moroccan origin population. Forensic Sci Int. 2005;154(1):3–12. Çakan KN, Yalçın Yeler D, Eninanç İ. Comparative assessment of the accuracy of Cameriere’s third molar maturation index method among three different radiographic techniques in a Turkish population. Australian J Forensic Sci. 2023;55(5):594–604. Yurdabakan ZZ, Karadayı B, Yetimoğlu N. Evaluation of Third Molar Maturity Index by Cone Beam Computed Tomography in Legal Age Estimation: A Preliminary Study. Am J Forensic Med Pathol. 2023;44(2):103–10. Mazières O, Blanchard-Muller M, Vidal C, Cyteval C, Baccino E, Martrille L. Applicability of Cameriere's third molar maturity index on orthopantomograms and computed tomography scans from a French population. Forensic Sci Int. 2024;359:112024. Pauwels R, Cockmartin L, Ivanauskaité D, Urbonienė A, Gavala S, Donta C, et al. Estimating cancer risk from dental cone-beam CT exposures based on skin dosimetry. Phys Med Biol. 2014;59(14):3877. Merdietio Boedi R, Shepherd S, Mânica S, Franco A. CBCT in dental age estimation: A systematic review and meta analysis. Dentomaxillofacial Radiol. 2022;51(4). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 03 Dec, 2025 Read the published version in BMC Oral Health → Version 1 posted Editorial decision: Revision requested 28 Oct, 2025 Reviews received at journal 25 Oct, 2025 Reviews received at journal 22 Oct, 2025 Reviews received at journal 21 Oct, 2025 Reviews received at journal 21 Oct, 2025 Reviews received at journal 18 Oct, 2025 Reviewers agreed at journal 12 Oct, 2025 Reviewers agreed at journal 11 Oct, 2025 Reviewers agreed at journal 10 Oct, 2025 Reviewers agreed at journal 07 Oct, 2025 Reviewers agreed at journal 07 Oct, 2025 Reviewers agreed at journal 07 Oct, 2025 Reviewers invited by journal 07 Oct, 2025 Editor invited by journal 06 Oct, 2025 Editor assigned by journal 03 Oct, 2025 Submission checks completed at journal 03 Oct, 2025 First submitted to journal 15 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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01:21:44","extension":"html","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":120966,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7621082/v1/2d386547355d6b581d454d79.html"},{"id":93976730,"identity":"b45c979c-e500-4daf-90f0-dc456d1028c6","added_by":"auto","created_at":"2025-10-21 01:21:44","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":85854,"visible":true,"origin":"","legend":"\u003cp\u003eSample measurementsof A8 and L8 in the third molar via the I3M method. \u003cstrong\u003eA.\u003c/strong\u003e Illustrative representation. \u003cstrong\u003eB.\u003c/strong\u003e Measurement on a sagittal CBCT image. \u003cstrong\u003eC.\u003c/strong\u003e Measurement on a panoramic radiograph.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7621082/v1/ed6c04552c1b281af9548f78.png"},{"id":93976729,"identity":"3faf645e-bf6a-4e67-91ab-c361e26df458","added_by":"auto","created_at":"2025-10-21 01:21:44","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":87239,"visible":true,"origin":"","legend":"\u003cp\u003eBland‒Altman graphic for CBCT and panoramic measurements\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7621082/v1/33aacbf543f5aeea76ebbedc.png"},{"id":93976732,"identity":"bc829d21-5160-4d6a-bc1d-10cebacd94f8","added_by":"auto","created_at":"2025-10-21 01:21:44","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":189756,"visible":true,"origin":"","legend":"\u003cp\u003eROC curves demonstrating the accuracy of the maturity index in estimating the 18-year age threshold by sex.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7621082/v1/151fba3916878a279820ed6f.jpeg"},{"id":93977603,"identity":"f2e301e0-c617-4494-a247-9b8624055e84","added_by":"auto","created_at":"2025-10-21 01:29:44","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":27373,"visible":true,"origin":"","legend":"\u003cp\u003eROC curves demonstrating the classification performance of the panoramic and CBCT imaging methods via the I3M index.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7621082/v1/b536b658ab2d3c5dbb67d93c.jpeg"},{"id":97723808,"identity":"5737d6e1-ade0-4dbf-a172-451d7e80f48b","added_by":"auto","created_at":"2025-12-08 16:07:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1105833,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7621082/v1/d0da2755-94c8-4bfb-8346-c4e2a6ce7701.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparison of cone-beam computed tomography and panoramic radiography in estimating the 18-year age threshold with the third molar maturity index: a retrospective study","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eIn the domain of forensic dentistry, the estimation of age is of paramount importance both in the postmortem identification process and in living individuals. It is useful for unidentified human remains, including those who have fallen victim to war or disaster, as well as those unearthed during archaeological studies. In the context of legal and social affairs, the assessment of age may be necessary, particularly in cases involving asylum seekers and refugees who lack official identification. Its use is frequently required in a variety of contexts, including military service, civil employment, marriage, adoption, participation in sports competitions, and criminal cases where legal responsibility must be determined (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDental age estimation can be conducted via methods based on developmental features, such as the degree of mineralization or the eruption stage of the teeth, as well as age-related changes that occur throughout life, including attrition, secondary dentin deposition, periodontosis, cementum apposition, root resorption, and root transparency. Further techniques include the analysis of aspartic acid racemization in dentin, telomere shortening in pulpal DNA, and radiocarbon levels in enamel (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe stages of tooth development offer reliable indicators of an individual\u0026rsquo;s biological age, enabling age estimation in children with a relatively low margin of error (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). However, because physical maturation is complete, several age indicators, including skeletal development, secondary sexual characteristics, height, weight, and dental development, become less reliable in people who are close to the legal age threshold of 18. In such cases, the focus shifts from estimating the exact chronological age to determining whether the individual falls above or below the legally defined age threshold (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe apical closure of the third molar is completed at approximately 20\u0026thinsp;\u0026plusmn;\u0026thinsp;2 years of age, although interpopulational variations are recognized (\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Therefore, evaluating the degree of apical closure of the third molar can be useful for determining whether an individual is under or over the 18-year age threshold. Dental development staging approaches, such as the Demirjian method, can be used for this purpose. A significant correlation exists between the age and development of third molars, as determined by the Demirjian mineralization stages (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). In 2008, Cameriere et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) created a new approach that measures the open apices of the mandibular third molar as an alternative to staging systems to assess the 18-year-old threshold in living individuals. They compared this measurement-based method with the Demirjian stages and obtained better sensitivity and specificity than did the Demirjian method.\u003c/p\u003e\u003cp\u003eThe third molar maturity index (I3M) is one such method used to assess whether an individual has reached the age of 18 (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). In this method, the sum of the apical opening measures is normalized by dividing it by the tooth's length to solve the magnification issue, which can impair measurement accuracy and is one of the disadvantages of panoramic radiography (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Notwithstanding the issue of geometric distortion in the resulting image, panoramic radiography is frequently used in forensic age estimation studies because it is a widely preferred imaging technique in clinical practice because of the comfort it provides for patients, ease of use for physicians, and low degree of radiation exposure. The I3M method has been validated across many populations. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eCompared with traditional CT, cone beam computed tomography (CBCT) generates high-resolution images of superior diagnostic quality, with brief scanning durations and less radiation exposure (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Technological advancements have significantly reduced irradiation, resulting in improved information quality for diagnostic tasks. Compared with conventional scanners, low-dose and ultralow-dose CBCT scanners can reduce radiation exposure by as much as 87% (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). This reduction holds particular significance for younger patients and individuals, necessitating multiple scans (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). The use of CBCT imaging is increasing throughout various fields of dentistry, including maxillofacial surgery, implantology, orthodontics, endodontics, periodontics, and evaluation of the temporomandibular joints. Considering the current rise in the use of CBCT scans in dentistry, it is necessary to evaluate the relevance of the third molar maturity index method alongside CBCT imaging. Therefore, we aimed to examine the applicability of the I3M method for CBCT scans compared with panoramic radiographs.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003e The study protocol (research number SBA 23/248) was conducted in accordance with the ethical standards of the Declaration of Helsinki and received approval from the Hacettepe University Health Sciences Research Ethics Committee on October 24, 2023 (Approval No: 2023/05\u0026ndash;13). This study is one of the two work packages that constitute the speciality thesis in Dentomaxillofacial Radiology. Ethical approval was obtained for each component of the study.\u003c/p\u003e\u003cp\u003eThe study population comprised CBCT and panoramic radiographic records obtained for various clinical indications between January 2018 and September 2023 at the Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, Hacettepe University.\u003c/p\u003e\u003cp\u003eThe required sample size was 138 third molar teeth from individuals aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years and 276 third molar teeth from individuals aged\u0026thinsp;\u0026lt;\u0026thinsp;18 years. This sample size provides 80% power to detect a difference of 0.06 between the area under the ROC curve (AUROC) under the null hypothesis (0.84, obtained from a reference study [17]) and the AUROC under the alternative hypothesis (0.90), using a two-sided z test at a significance level of 0.05. Power analysis was carried out via PASS 15 software.\u003c/p\u003e\u003cp\u003eThe inclusion criteria for the study were as follows: the individuals were between 15 and 23 years of age; the presence of at least one lower third molar tooth; the absence of any pathology, trauma, or developmental anomaly in the region of interest; and no previous surgical intervention in this region.\u003c/p\u003e\u003cp\u003eTo compare the efficacy of CBCT and panoramic imaging, patients whose images were taken within a six-month period were identified. To ensure optimal image quality, CBCT scans obtained with a wide field of view (FOV), CBCT images with motion or metal artifacts, and panoramic radiographs with artifacts and inadequate density and contrast were excluded from the study. Initially, researchers reviewed the radiologic images of a total of 1,249 patients aged 15\u0026ndash;23 years. Images that fulfilled the inclusion criteria were selected. In total, 418 third molar regions from 232 patients were included in the study.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eImaging procedures and measurements\u003c/h2\u003e\u003cp\u003eCBCT scans were acquired via the i-CAT Next Generation device (Imaging Sciences International, Hatfield, PA, USA) with the following exposure parameters: 120 kVp tube voltage; tube current ranging from 3\u0026ndash;7 mA depending on the FOV and voxel size; and adjusted exposure times. The images were analyzed via i-CAT Vision software, versions 17\u0026ndash;19. Panoramic radiographs were obtained via an Orthophos XG 5 (Sirona Dental Company, Bensheim, Germany; 60\u0026ndash;90 kVp, 3\u0026ndash;16 mA, 14 s) and a Veraview IC5 (Morita Corporation, Kyoto, Japan; 60\u0026ndash;70 kVp, 1\u0026ndash;7.5 mA, 5.5\u0026ndash;10 s), with exposure parameters adjusted according to the patient\u0026rsquo;s size. The measurements on panoramic radiographs were performed via ImageJ software, version 1.54 g (National Institutes of Health, Bethesda, MD, USA; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://imagej.org\u003c/span\u003e\u003cspan address=\"https://imagej.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe I3M value is calculated by dividing the sum of the widths of the open apices of the mandibular third molar roots by the tooth length. This index is used to estimate whether an individual is above or below the legal age threshold of 18 years. According to the recommended cutoff value of 0.08, individuals with an I3M value\u0026thinsp;\u0026lt;\u0026thinsp;0.08 are considered likely older than 18, whereas those with an I3M value\u0026thinsp;\u0026ge;\u0026thinsp;0.08 are considered likely younger than 18.\u003c/p\u003e\u003cp\u003eFor CBCT measurements, volumetric data were examined in multiplanar reconstruction (MPR) views displaying coronal, sagittal, and axial sections. The axial plane was adjusted to obtain the widest and tallest mesiodistal section of the mandibular third molar in a nonorthogonal projection. In cases where root development was incomplete, the distance between the inner surfaces of the open apices was measured. If the tooth had two roots, the total distance between the inner surfaces of both open apices was summed and divided by the tooth length to calculate the I3M value (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). If root development was complete, I3M was recorded as 0.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eI3M\u0026thinsp;=\u0026thinsp;A8/L8 (sum of open apex widths/tooth length)\u003c/p\u003e\u003cp\u003eTo evaluate intra- and interobserver reliability, two observers repeated the measurements on approximately 10%-15% of the randomly selected CBCT scans and panoramic radiographs at least two weeks after the initial assessments (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eIntraclass correlation coefficient (ICC) values and 95% confidence intervals (CIs) for intra- and interobserver agreement\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eImaging Method\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIntra-Observer Agreement\u003c/p\u003e\u003cp\u003e(95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInter-Observer Agreement\u003c/p\u003e\u003cp\u003e(95% CI)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCBCT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.984 (0.974\u0026ndash;0.990)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.983 (0.973\u0026ndash;0.990)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePanoramic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.966 (0.936\u0026ndash;0.982)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.983 (0.968\u0026ndash;0.991)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe chronological age of each patient was calculated by subtracting the date of birth from the radiograph acquisition date and was expressed in decimal years. The I3M values for each tooth, along with the calculated decimal age values and the subjects' sex data, were recorded.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eThe intraclass correlation coefficient (ICC) based on a two-way mixed effects model was calculated to evaluate the intra- and interobserver reliability of the I3M measurements obtained from the CBCT and panoramic radiographs (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe normality of the numerical variables was assessed via the Kolmogorov\u0026ndash;Smirnov test. For normally distributed variables, descriptive statistics were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation, while categorical variables were summarized as frequencies and percentages (n, %). The agreement between the CBCT and panoramic I3M measurements was evaluated via Spearman\u0026rsquo;s rho correlation coefficient and Bland\u0026ndash;Altman analysis. Age was subsequently categorized into two groups: \u0026lt;18 years and \u0026ge;\u0026thinsp;18 years. The association between age and sex was examined via Pearson\u0026rsquo;s chi-square test.\u003c/p\u003e\u003cp\u003eStudies concerning the estimation of age thresholds use sensitivity, specificity, PPV, NPV, LR (both positive and negative), and AUROC values as measures of classification performance for I3M. In this study, sensitivity, or the true positive rate, measures how well the I3M method can classify true adults. In other words, sensitivity represents the proportion of individuals classified as true positive/adult by the I3M method compared with the total number of adults in the sample. Specificity, or the true negative rate, indicates how well the I3M method identifies minors. In our study, it represents the proportion of individuals classified as negative/minor by the I3M method to all children in the sample. The AUROC value measures the overall performance of the I3M. This value determines the ability of the test to discriminate between adults and minors.\u003c/p\u003e\u003cp\u003eReceiver operating characteristic (ROC) curve analysis was performed to evaluate the performance of CBCT and panoramic I3M measurements in predicting age categories. Afterwards, the differences between the areas under the ROC curves (AUROCs) were tested via DeLong\u0026rsquo;s test for two correlated ROC curves. The sensitivity, specificity, PPV, NPV, PLR, NLR, and misclassification rates were calculated with 95% confidence intervals (CIs) for the assessment of the predictive performance of I3M measurements in age classification. Likelihood ratio values remain unaffected by prevalence and serve as indicators of the probability of a diagnostic test result for an individual. A higher PLR value indicates greater accuracy of the cutoff score. The NLR ranges from 0 to 1. A proximity to zero increases the likelihood that the I3M method will accurately classify an individual as minor at the specified cutoff score. All the analyses were conducted via IBM SPSS Statistics v29.0 for Windows. The significance level was set at 0.05.\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eThe intra- and interobserver agreements for the panoramic and CBCT imaging modalities, as assessed by the ICC and corresponding 95% CI, are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The ICC values indicate excellent intra- and interobserver reliability for measurements performed on both panoramic and CBCT images (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eA total of 418 mandibular third molars meeting the inclusion criteria were evaluated. The mean age\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation was 19.57\u0026thinsp;\u0026plusmn;\u0026thinsp;2.47 years. The sample consisted of 222 females and 196 males. The age and sex distributions of the sample are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, and the distribution by sex according to the 18-year age category is shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. When the sex distribution across age groups was examined (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), the age distribution was found to be homogeneous between sexes (p\u0026thinsp;=\u0026thinsp;0.274). The correlation coefficient between the CBCT and panoramic measurements was 0.898 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The Bland\u0026ndash;Altman analysis results obtained for the two imaging methods, i.e., CBCT and panoramic imaging, are presented below (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Overall, the measurements obtained by the different methods were consistent, and no systematic bias was observed. Although some observations fell outside the limits of agreement, the proportion of these cases remained below 5%, and such observations reflect possible situations encountered in clinical practice (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAge and sex distributions of the sample\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eAge Groups\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15.00\u0026ndash;15.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e16.00\u0026ndash;16.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e51\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e17.00\u0026ndash;17.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e18.00\u0026ndash;18.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e19.00\u0026ndash;19.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e37\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e20.00\u0026ndash;20.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e41\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e21.00\u0026ndash;21.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e79\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e22.00\u0026ndash;22.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e99\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e222\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e196\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e418\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSample distribution by sex and the 18-year age threshold\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;18 Years\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;18 Years\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFemale\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e222\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMale\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e127\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e196\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e282\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e136\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e418\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eBefore conducting the comparative analysis of imaging modalities, the potential effect of sex on classification performance was assessed by generating sex-specific ROC curves. The ROC curves stratified by sex are presented below (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The AUROC values were 0.958 (95% CI: 0.934\u0026ndash;0.982) for females and 0.914 (95% CI: 0.871\u0026ndash;0.958) for males. These values indicate that the method has excellent classification accuracy for both sexes (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). The AUROC values demonstrated that the method has high discriminative power for both females and males, indicating that it can be reliably applied regardless of sex. Therefore, the subsequent analyses were conducted independently of sex.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe frequencies of true positives (TPs), false positives (FPs), true negatives (TNs), and false negatives (FNs) used to calculate sensitivity and specificity according to the I3M cutoff value\u0026thinsp;\u0026lt;\u0026thinsp;0.08 are presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. On the basis of these values, key performance metrics for both imaging methods\u0026mdash;sensitivity, specificity, PPV, NPV, PLR, NLR, and overall AUROC\u0026mdash;are provided in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eClassification performance of the I3M method based on panoramic and CBCT imaging\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eImaging Method\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eI3M Value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;18 Years\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;18 Years\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003ePanoramic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eI3M\u0026thinsp;\u0026lt;\u0026thinsp;0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e240\u003csup\u003eTP\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18\u003csup\u003eFP\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e258\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eI3M\u0026thinsp;\u0026ge;\u0026thinsp;0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e42\u003csup\u003eFN\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e118\u003csup\u003eTN\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e160\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e282\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e136\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e418\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eCBCT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eI3M\u0026thinsp;\u0026lt;\u0026thinsp;0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e231\u003csup\u003eTP\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14\u003csup\u003eFP\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e245\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eI3M\u0026thinsp;\u0026ge;\u0026thinsp;0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e51\u003csup\u003eFN\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e122\u003csup\u003eTN\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e173\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e282\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e136\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e418\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003e*\u003c/b\u003eTP\u0026thinsp;=\u0026thinsp;true positive, FP\u0026thinsp;=\u0026thinsp;false positive, TN\u0026thinsp;=\u0026thinsp;true negative, FN\u0026thinsp;=\u0026thinsp;false negative\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePerformance metrics and 95% CI values of I3M\u0026thinsp;\u0026lt;\u0026thinsp;0.08 according to imaging methods\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMetric\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePanoramic Radiography\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCBCT\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSensitivity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.851 (0.804\u0026ndash;0.890)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.819 (0.769\u0026ndash;0.862)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSpecificity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.868 (0.799\u0026ndash;0.920)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.897 (0.833\u0026ndash;0.943)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLR+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.43 (4.17\u0026ndash;9.92)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7.96 (4.83\u0026ndash;13.11)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLR\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.17 (0.13\u0026ndash;0.23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.20 (0.16\u0026ndash;0.26)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePPV\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.930 (0.896\u0026ndash;0.954)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.943 (0.909\u0026ndash;0.965)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNPV\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.738 (0.678\u0026ndash;0.789)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.705 (0.650\u0026ndash;0.755)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAUROC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.932 (0.907\u0026ndash;0.958)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.928 (0.901\u0026ndash;0.954)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe ROC curves illustrating the classification performance of the I3M index for both panoramic and CBCT images are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn many countries, the age of majority represents a critical legal threshold for determining criminal responsibility, civil rights, and access to social policies. The United Nations Convention on the Rights of the Child (1989) defines anyone under the age of 18 as a child, which emphasizes the value of identity verification and birth registration. However, in some countries or communities, the absence of official birth records renders children legally 'invisible', increasing their vulnerability to human rights violations. Children without valid identification documents face an elevated risk of being recruited for the military at a young age, engaging in hazardous labor, entering early marriages, or being prosecuted as adults in criminal proceedings. Undocumented, displaced, and migrant children are vulnerable to various forms of abuse and exploitation (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Owing to the recent global increase in migration, there is a growing demand for reliable age estimation methods\u0026mdash;particularly to determine whether an individual has reached the legal age of majority.\u003c/p\u003e\u003cp\u003eThe I3M method is a radiographic method used for age estimation and is based on panoramic radiographs (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). This method evaluates whether an individual has reached the age of the majority. A cutoff value of 0.08 was proposed to distinguish legal adulthood. The applicability of the I3M method using panoramic radiographs has been evaluated across various populations, with a consensus supporting its reliability and feasibility (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn the original study by Cameriere et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e), only the left mandibular third molars were assessed. Subsequent studies have indicated that there are no statistically significant differences in third molar development between the right and left sides (\u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Angelakopoulos et al. (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) reported no significant difference between right and left mandibular third molars when the age of the majority was assessed via the I3M method, which is based on a large multiethnic sample of 10,181 panoramic radiographs collected from various countries in Africa, North and South America, Asia, and Europe. On the basis of these findings, both right and left mandibular third molars were included in the present study. Nevertheless, if a notable disparity is observed between the development of the left and right third molars in any case under consideration, taking into account the less developed tooth in accordance with the principle of the \u0026ldquo;best interests of the child\u0026rdquo; is beneficial (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTo investigate the potential influence of sex before the imaging methods were compared, ROC curves were generated separately for male and female subjects. The difference between the areas under the ROC curves (AUROCs) was not statistically significant (p ˃ 0.05). High AUROC values (\u0026ge;\u0026thinsp;0.9) for females and males indicate excellent classification accuracy (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Our findings demonstrate that the method has strong discriminative ability for both sexes, suggesting that it can be reliably applied irrespective of sex. Similarly, Cameriere et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e), De Luca et al. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e) and Ara\u0026uacute;jo et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e) reported that the predictive accuracy of the method is unaffected by sex. However, some studies have suggested that sex is a factor to be considered in the evaluation of third molar development (\u003cspan additionalcitationids=\"CR34\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). Nevertheless, in a recent meta-analysis, Santiago et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) concluded that the I3M method is an effective and appropriate tool for forensic age estimation, regardless of sex.\u003c/p\u003e\u003cp\u003eIn studies comparing the performance of diagnostic tests, several factors may influence measurement accuracy, including the diagnostic method itself, the imaging tools employed, and the observers conducting the evaluations (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). The validity and reliability of the I3M method have been shown in various prior investigations involving diverse ethnic groups (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Prior to comparing the imaging modalities, both intra- and interobserver reliability were assessed, as observer consistency represents a critical variable that may affect outcomes. The results demonstrated excellent agreement for both panoramic and CBCT imaging modalities (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn this study, the sensitivity, specificity and AUROC values were 85.1%, 86.8%, and 0.932, respectively, for panoramic radiography and 81.9%, 89.7%, and 0.928, respectively, for CBCT. Although panoramic radiography presented a marginally higher AUROC, both imaging modalities exhibited excellent classification performance (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). The sensitivity and specificity values obtained for the two radiological techniques are quite close to each other. Our findings revealed that the specificity is greater than the sensitivity for both imaging modalities. In accordance with the initial study (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e), specificity generally appears higher than sensitivity in investigations evaluating the I3M method, with pooled estimates from the latest meta-analysis showing a sensitivity of 0.86 and a specificity of 0.93 (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). This is probably because the ethical priority of minimizing false-positive results rather than false-negative results was considered when determining the cutoff for the I3M method. Garamendi et al. (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e) argue that errors implying that children are over 18 are ethically unacceptable because they violate the rights of minors. Consequently, testing methodologies used in forensic age assessment should reduce the technically unacceptable type of error that misclassifies adults as children; however, eliminating ethically unacceptable errors is crucial, especially in regard to the criminal responsibility of minors. In the literature, only a few studies have applied the I3M method via three-dimensional imaging techniques (\u003cspan additionalcitationids=\"CR39\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Mazieres et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e) applied Cameri\u0026egrave;re's method to computed tomography (CT) scans and panoramic radiographs taken from the same individuals either at short intervals or through a double sampling approach, as in the methodology of our study. \u0026Ccedil;akan et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e) compared periapical, panoramic, and CBCT imaging modalities via the I3M technique and reported AUROC values of 0.831 for panoramic images and 0.727 for CBCT. They reported that the sensitivity and specificity values were 61.9% and 100%, respectively, for CBCT and 71% and 97%, respectively, for panoramic radiography. Our study revealed higher AUROC values for both imaging modalities than did their study. In addition, the sensitivity and specificity values in both studies differ, despite the testing samples being Turkish individuals. This difference may be attributed to a spectrum effect, likely resulting from their study testing each imaging method on different groups of patients. Yurdabakan et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e) reported that the sensitivity, specificity and accuracy were 93.5%, 97.4%, and 95.9%, respectively, in their CBCT study. While specificity values are generally high, sensitivity values vary among these studies and radiological methods. All these values, which are performance measures, are higher than those in our study. Differences in equipment used or interobserver variability in measurement techniques may also have contributed to this variation in results. Although Yurdabakan et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e) did not compare CBCT with panoramic imaging in the same subjects and the sample size of the study was small, their results are still promising, indicating that the method can produce satisfactory outcomes.\u003c/p\u003e\u003cp\u003eMazieres et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e), who compared the I3M method on panoramic radiographs and CT scans, reported high ICCs of 94.8% (95% CI: 90.7\u0026ndash;97.1) for tooth 38 and 97.4% (95% CI: 94.9\u0026ndash;98.7) for tooth 48. Our findings align closely with the level of agreement reported by Mazieres et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Although their study utilized CT imaging and ours employed CBCT, the similarity of outcomes between the two studies supports the applicability of the I3M method across three-dimensional imaging modalities. This consistency is especially relevant for forensic practice, reinforcing the potential of using existing dental images for determining the legal age of the majority. Mazieres et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e) reported a sensitivity of 77.8% and specificity of 94.1% for tooth 38 and a sensitivity of 75% and specificity of 93.8% for tooth 48 on CT scans. The minor differences between the findings of our study and those of Mazieres et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e) may be due to technical differences between the imaging modalities, even though both are three-dimensional in nature.\u003c/p\u003e\u003cp\u003eThe LR\u0026thinsp;+\u0026thinsp;value for the 18-year-old threshold indicates that the test has a chance of producing false positives, with approximately one in seven trials resulting in a false-positive outcome for panoramic radiography (LR\u0026thinsp;+\u0026thinsp;=\u0026thinsp;6.43). The LR\u0026thinsp;+\u0026thinsp;value of the CBCT scans suggested that there were at least eight true positives for every false positive; a minor was inaccurately detected in approximately one out of every nine instances (LR\u0026thinsp;+\u0026thinsp;=\u0026thinsp;7.96). The LR\u0026thinsp;\u0026minus;\u0026thinsp;score for both CBCT (LR\u0026minus; = 0.20) and panoramic radiography (LR\u0026minus; = 0.17) demonstrated that one false negative occurred for every five true negatives, indicating moderate reliability. However, no CBCT or CT studies have reported LR values as a performance metric for the I3M technique. However, a study conducted by Angelakopoulos et al. (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e), which examined the difference between the right and left sides on panoramic radiographs, reported LR values similar to ours. Our PLR value for panoramic radiographs was similar to that of the American sample in this multiethnic study, whereas our negative LR value was similar to that of the American and European samples. Angelakopoulos et al. (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) reported mean LR\u0026thinsp;+\u0026thinsp;values of 8.59 for the left mandibular third molar and 8.51 for the right, whereas the LR- values were 0.31 for the left and 0.30 for the right.\u003c/p\u003e\u003cp\u003eThe retrospective nature of the study primarily limits the availability of detailed patient information. Furthermore, because the study took place at a single center, the analysis failed to include images from different imaging devices. In future studies, evaluating the I3M method via a sample of images obtained from various CBCT devices would be useful.\u003c/p\u003e\u003cp\u003eIndividuals are particularly sensitive to radiation during late adolescence and early adulthood, particularly during periods when age estimation is necessary to determine the age of the majority of individuals (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). While the CBCT radiation dose can be reduced by measures such as selecting a small field of view, panoramic radiography should be the preferred imaging modality for age estimation in children and adolescents (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). Furthermore, the use of existing CBCT images for age estimation eliminates the need for additional radiation doses. Therefore, the results of our study are important because they enable the use of existing images for age estimation. Consequently, the findings of our research are significant since they enable the use of available CBCT images for age estimates.\u003c/p\u003e\u003cp\u003eOur study concluded that the I3M method demonstrates comparable accuracy when applied to both CBCT and panoramic radiography. Consequently, CBCT images may be used for the I3M method to estimate the 18-year threshold.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eI3M\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ethird molar maturity index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCBCT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003econe-beam computed tomography\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ecomputed tomography ROC:receiver operating characteristic\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePPV\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003epositive predictive value\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNPV\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003enegative predictive value\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePLR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003epositive likelihood ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNLR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003enegative likelihood ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAUROC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003earea under the ROC curve\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003econfidence interval\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eMPR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003emultiplanar reconstruction\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eICC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eintraclass correlation coefficient\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTP\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003etrue positive\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eFP\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003efalse positive\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTN\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003etrue negative\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eFN\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003efalse negative\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003cp\u003e This study (Research Number: SBA 23/248) was conducted in accordance with the ethical standards of the Declaration of Helsinki and was approved by the Hacettepe University Health Sciences Research Ethics Committee (Session Date: October 24, 2023; Session No: 2023/05; Decision No: 2023/05\u0026ndash;13). This is a retrospective archive study. However, informed consent is obtained from all patients examined in our clinic.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cp\u003eNot applicable\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eCompeting interests\u003c/h2\u003e\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eClinical trial number\u003c/h2\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConception and design of study: M.G.D., N.A. Acquisition of data: M.G.D., N.A. Analysis and/or interpretation of data: M.G.D., N.A., H.Y.Z. Drafting the manuscript: M.G.D., N.A. Revising the manuscript: M.G.D., N.A., H.Y.Z. Approval of the version of the manuscript to be published: M.G.D., N.A.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and/or analyzed during the current study are not publicly available due to confidentiality of personal information but are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGreene D, Williams D, Senn DR, Weems RA. Manual of Forensic Odontology: CRC Press; 2013. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1201/b13744\u003c/span\u003e\u003cspan address=\"10.1201/b13744\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVerma M, Verma N, Sharma R, Sharma A. 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Eur J Dentistry. 2023;17(01):200\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e\u0026Ccedil;orbacıoğlu ŞK, Aksel G. Receiver operating characteristic curve analysis in diagnostic accuracy studies: A guide to interpreting the area under the curve value. Turkish J Emerg Med. 2023;23(4):195\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDe Luca S, Biagi R, Begnoni G, Farronato G, Cingolani M, Merelli V, et al. Accuracy of Cameriere's cut-off value for third molar in assessing 18 years of age. Forensic Sci Int. 2014;235:102. e1-. e6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAra\u0026uacute;jo AMMd P, KPd MLAFran\u0026ccedil;a, Beltr\u0026atilde;o RV, Pontual AA. Association between mineralization of third molars and chronological age in a Brazilian sample. Revista Odonto Ci\u0026ecirc;ncia. 2010;25:391\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDeitos AR, Costa C, Michel-Crosato E, Galić I, Cameriere R, Biazevic MGH. Age estimation among Brazilians: younger or older than 18? J Forensic Leg Med. 2015;33:111\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBlankenship JA, Mincer HH, Anderson KM, Woods MA, Burton EL, editors. Third molar development in the estimation of chronologic age in American blacks as compared with whites. Journal of Forensic Sciences; 2007.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAkkaya N, Yilanci H\u0026Ouml;. Assessment of third molar maturity index for legal age threshold of 18 in a sample of Turkish individuals. Australian J Forensic Sci. 2021;53(3):314\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOakley C, Brunette DM. The use of diagnostic data in clinical dental practice. Dent Clin. 2002;46(1):87\u0026ndash;115.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGaramendi PM, Landa MI, Ballesteros J, Solano MA. Reliability of the methods applied to assess age minority in living subjects around 18 years old: A survey on a Moroccan origin population. Forensic Sci Int. 2005;154(1):3\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e\u0026Ccedil;akan KN, Yal\u0026ccedil;ın Yeler D, Eninan\u0026ccedil; İ. Comparative assessment of the accuracy of Cameriere\u0026rsquo;s third molar maturation index method among three different radiographic techniques in a Turkish population. Australian J Forensic Sci. 2023;55(5):594\u0026ndash;604.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYurdabakan ZZ, Karadayı B, Yetimoğlu N. Evaluation of Third Molar Maturity Index by Cone Beam Computed Tomography in Legal Age Estimation: A Preliminary Study. Am J Forensic Med Pathol. 2023;44(2):103\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMazi\u0026egrave;res O, Blanchard-Muller M, Vidal C, Cyteval C, Baccino E, Martrille L. Applicability of Cameriere's third molar maturity index on orthopantomograms and computed tomography scans from a French population. Forensic Sci Int. 2024;359:112024.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePauwels R, Cockmartin L, Ivanauskait\u0026eacute; D, Urbonienė A, Gavala S, Donta C, et al. Estimating cancer risk from dental cone-beam CT exposures based on skin dosimetry. Phys Med Biol. 2014;59(14):3877.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMerdietio Boedi R, Shepherd S, M\u0026acirc;nica S, Franco A. CBCT in dental age estimation: A systematic review and meta analysis. Dentomaxillofacial Radiol. 2022;51(4).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-oral-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ohea","sideBox":"Learn more about [BMC Oral Health](http://bmcoralhealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ohea/default.aspx","title":"BMC Oral Health","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Forensic dentistry, age estimation, third molar maturity index, CBCT, panoramic radiography","lastPublishedDoi":"10.21203/rs.3.rs-7621082/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7621082/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eThe third molar maturity index (I3M) method, introduced for application on panoramic radiographs, is used to assess whether an individual has reached the legal 18-year age threshold. This study aimed to evaluate the applicability of the I3M method to cone-beam computed tomography (CBCT) scans and to compare the results with those obtained from panoramic radiographs of the same patients.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003ePatients who had already received both CBCT scans and panoramic radiographs were selected retrospectively. The maturity index values of 418 mandibular third molars were obtained via measurements via both CBCT scans and panoramic radiographs. The accuracy of the I3M method for both radiological methods was evaluated via receiver operating characteristic (ROC) curve analysis. The sensitivity, specificity, misclassification rate, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (PLR), negative likelihood ratio (NLR), and overall area under the ROC curve (AUROC) at the 95% confidence interval (CI) level were calculated as performance measures for both imaging modalities.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eBoth imaging modalities showed excellent diagnostic performance, with AUROC values of 0.928 for CBCT and 0.932 for panoramic radiography. The sensitivity of CBCT was 82.0%, the specificity was 89.7%, and the misclassification rate was 14.1%. For panoramic radiography, the sensitivity was 85.1%, the specificity was 86.8%, and the misclassification rate was 18.1%. The PLR and NLR values for CBCT were 7.96 and 0.20, respectively, whereas those for panoramic radiography were 6.43 and 0.17, respectively. Additionally, the PPV and NPV values for CBCT were 0.943 and 0.705, respectively, and those for panoramic radiography were 0.930 and 0.738, respectively.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThe results indicated that the accuracy of the I3M method for CBCT scans was similar to that for panoramic radiographs from the same individuals. Importantly, the I3M method used to estimate the legal 18-year age threshold can also be used for CBCT scans, as it enables the use of existing CBCT images in age estimation studies.\u003c/p\u003e","manuscriptTitle":"Comparison of cone-beam computed tomography and panoramic radiography in estimating the 18-year age threshold with the third molar maturity index: a retrospective study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-21 01:21:40","doi":"10.21203/rs.3.rs-7621082/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-28T06:34:38+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-25T08:59:15+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-22T09:50:26+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-22T02:20:07+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-21T16:36:19+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-19T02:49:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"93471126840180254928625150599645803578","date":"2025-10-12T05:08:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"65129840583586131166473541919175126298","date":"2025-10-11T15:17:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"15373046830248201429788132077575175915","date":"2025-10-10T09:28:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"336669799483563433185619031319990538290","date":"2025-10-07T10:57:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"333466794548504941547558882585119314430","date":"2025-10-07T09:23:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"94986035852192489508771174941906656700","date":"2025-10-07T09:01:07+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-07T08:49:29+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-10-06T05:42:10+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-03T10:27:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-03T10:26:23+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Oral Health","date":"2025-09-15T13:15:12+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-oral-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ohea","sideBox":"Learn more about [BMC Oral Health](http://bmcoralhealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ohea/default.aspx","title":"BMC Oral Health","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"eb3323ff-f681-4e16-ac08-49454fea7136","owner":[],"postedDate":"October 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-08T16:00:30+00:00","versionOfRecord":{"articleIdentity":"rs-7621082","link":"https://doi.org/10.1186/s12903-025-07428-7","journal":{"identity":"bmc-oral-health","isVorOnly":false,"title":"BMC Oral Health"},"publishedOn":"2025-12-03 15:57:27","publishedOnDateReadable":"December 3rd, 2025"},"versionCreatedAt":"2025-10-21 01:21:40","video":"","vorDoi":"10.1186/s12903-025-07428-7","vorDoiUrl":"https://doi.org/10.1186/s12903-025-07428-7","workflowStages":[]},"version":"v1","identity":"rs-7621082","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7621082","identity":"rs-7621082","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}