Pub Date : 2025-09-01Epub Date: 2025-06-03DOI: 10.1016/j.fri.2025.200641
E. Pefferkorn , L. Pestourie , F. Savall , N. Telmon , F. Dedouit , C. Guilbeau-Frugier
In the expanding field of post-mortem imaging, post-mortem computed tomography (PMCT) has emerged as an essential tool for forensic pathologists. It is particularly valuable for detecting and accurately localizing metallic foreign bodies, thereby assisting the forensic pathologist during the autopsy. This study presents a case of an accidental finding of a foreign body during a PMCT, initially misinterpreted as a potential ballistic foreign body by the forensic pathologist who had quickly reviewed the scan prior to the autopsy, due to its metallic appearance and the victim’s history of involvement in armed conflicts. The forensic pathologist, unaware of a miniaturized pacemaker, specifically a Transcatheter Pacing System (TPS), initially suspected a cardiac bullet but ruled this out upon autopsy, as there were no signs of trauma or cutaneous entry wounds and the discovery of the TPS. Advanced processing techniques allowed the identification of the characteristic anchoring tines of the TPS, confirming its nature and distinguishing it from a bullet. This highlights the importance of precise post-mortem images’ interpretation.
{"title":"Fortuitous discovery of a metallic foreign body on post-mortem CT scan: bullet or not bullet?","authors":"E. Pefferkorn , L. Pestourie , F. Savall , N. Telmon , F. Dedouit , C. Guilbeau-Frugier","doi":"10.1016/j.fri.2025.200641","DOIUrl":"10.1016/j.fri.2025.200641","url":null,"abstract":"<div><div>In the expanding field of post-mortem imaging, post-mortem computed tomography (PMCT) has emerged as an essential tool for forensic pathologists. It is particularly valuable for detecting and accurately localizing metallic foreign bodies, thereby assisting the forensic pathologist during the autopsy. This study presents a case of an accidental finding of a foreign body during a PMCT, initially misinterpreted as a potential ballistic foreign body by the forensic pathologist who had quickly reviewed the scan prior to the autopsy, due to its metallic appearance and the victim’s history of involvement in armed conflicts. The forensic pathologist, unaware of a miniaturized pacemaker, specifically a Transcatheter Pacing System (TPS), initially suspected a cardiac bullet but ruled this out upon autopsy, as there were no signs of trauma or cutaneous entry wounds and the discovery of the TPS. Advanced processing techniques allowed the identification of the characteristic anchoring tines of the TPS, confirming its nature and distinguishing it from a bullet. This highlights the importance of precise post-mortem images’ interpretation.</div></div>","PeriodicalId":40763,"journal":{"name":"Forensic Imaging","volume":"42 ","pages":"Article 200641"},"PeriodicalIF":0.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144263820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-01Epub Date: 2025-07-17DOI: 10.1016/j.fri.2025.200644
Jamie Elifritz , Micillo Andrea , Fabrice Dedouit , Laura Filograna , ISFRI Guidelines Working Group
{"title":"Withdrawal notice to “ISFRI Guidelines Working Group: Best Practice Standards for Non-Contrast Postmortem Computed Tomography (PMCT) of Overdose” [Forensic Imaging (2025) 200633]","authors":"Jamie Elifritz , Micillo Andrea , Fabrice Dedouit , Laura Filograna , ISFRI Guidelines Working Group","doi":"10.1016/j.fri.2025.200644","DOIUrl":"10.1016/j.fri.2025.200644","url":null,"abstract":"","PeriodicalId":40763,"journal":{"name":"Forensic Imaging","volume":"42 ","pages":"Article 200644"},"PeriodicalIF":1.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144924710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Assessing skeletal maturity using epiphyseal and morphological features with modern, reliable evaluation protocols is crucial for human identification efforts and paediatric growth monitoring. This study aims to develop and validate a scoring system for knee skeletal development on post-mortem computed tomography (PMCT) and magnetic resonance imaging (MRI) acquired from Australian and New Mexican children.
Materials & Methods
A protocol for the skeletal knee was developed on 30 PMCT and 30 T2-weighted MRI scans of subadults aged eight- to- 22 years. DICOM image stacks from a Brisbane children’s hospital and the New Mexico Decedent Image Database (NMDID) underwent multiplanar reconstruction and anatomical alignment. The protocol comprised a three- to- six stage scoring process at four epiphyseal fusion and seven maturity indicator sites. Three observers of varying experience levels assessed the images across three days, with reliability quantified using an intraclass correlation coefficient (ICC).
Results
The protocol demonstrated high reliability and consistency, with excellent intraobserver agreement for CT (ICC = 0.985 (95 % CI: 0.93-1.00)) and MRI (ICC = 0.979 (95 % CI: 0.85-1.00)). Mean inter-observer reliability measures were good for CT (ICC = 0.886 (95 % CI: 0.75-0.95)) and MRI (ICC = 0.852 (95 % CI: 0.68-0.95)). The tibial tubercle demonstrated the most variability and long-bone epiphyseal union the least
Conclusions
This research presents a highly reproducible method for assessing skeletal development of the knee in subadults, aligned with modern imaging standards. The methodology will have application in forensic human identification, age confirmation and clinical growth assessment
{"title":"Assessment of knee ossification timings: Development and validation of an ordinal scoring protocol for age estimation using medical imaging","authors":"Taliah Swart , Samantha K. Rowbotham , Soren Blau , Nicolene Lottering","doi":"10.1016/j.fri.2025.200625","DOIUrl":"10.1016/j.fri.2025.200625","url":null,"abstract":"<div><h3>Objectives</h3><div>Assessing skeletal maturity using epiphyseal and morphological features with modern, reliable evaluation protocols is crucial for human identification efforts and paediatric growth monitoring. This study aims to develop and validate a scoring system for knee skeletal development on post-mortem computed tomography (PMCT) and magnetic resonance imaging (MRI) acquired from Australian and New Mexican children.</div></div><div><h3>Materials & Methods</h3><div>A protocol for the skeletal knee was developed on 30 PMCT and 30 T2-weighted MRI scans of subadults aged eight- to- 22 years. DICOM image stacks from a Brisbane children’s hospital and the New Mexico Decedent Image Database (NMDID) underwent multiplanar reconstruction and anatomical alignment. The protocol comprised a three- to- six stage scoring process at four epiphyseal fusion and seven maturity indicator sites. Three observers of varying experience levels assessed the images across three days, with reliability quantified using an intraclass correlation coefficient (ICC).</div></div><div><h3>Results</h3><div>The protocol demonstrated high reliability and consistency, with excellent intraobserver agreement for CT (ICC = 0.985 (95 % CI: 0.93-1.00)) and MRI (ICC = 0.979 (95 % CI: 0.85-1.00)). Mean inter-observer reliability measures were good for CT (ICC = 0.886 (95 % CI: 0.75-0.95)) and MRI (ICC = 0.852 (95 % CI: 0.68-0.95)). The tibial tubercle demonstrated the most variability and long-bone epiphyseal union the least</div></div><div><h3>Conclusions</h3><div>This research presents a highly reproducible method for assessing skeletal development of the knee in subadults, aligned with modern imaging standards. The methodology will have application in forensic human identification, age confirmation and clinical growth assessment</div></div>","PeriodicalId":40763,"journal":{"name":"Forensic Imaging","volume":"41 ","pages":"Article 200625"},"PeriodicalIF":0.8,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143868383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Identifying the cause of death using postmortem CT images is crucial since it provides a non-invasive, objective approach for forensic investigations while offering significant advantages in terms of time efficiency and cost-effectiveness compared to traditional autopsy methods. However, due to varied lung conditions in the postmortem CT images, a standardized method to diagnose drowning using CT images has not been established. This study aimed to devise a deep-learning-aided framework for diagnosing drowning from postmortem lung CT images. First, to find the suitable convolutional neural network (CNN) architecture for classifying lung CT images into drowning and non-drowning cases, three well-known CNNs, AlexNet, VGG16, and MobileNet, were trained with a single-institute postmortem CT image dataset and the performance and generalizability were also evaluated using images extracted from a public decedent CT image database. The results showed that VGG16 architecture outperformed the three models with the highest mean AUC-ROC and accuracy values of 88.42 % and 80.56 % respectively for drowning image classification, as well as the highest generalizability with an AUC-ROC of 71.79 % on a public image dataset. Additionally, the case-based diagnosis was performed using probability scores given from the model to each slice taken in the same subject. The final diagnosis accuracy was 96 % on the original dataset and 79 % on the public dataset, showing the strong potential that the devised framework can be used as a screening tool to identify drowning cases using postmortem CT images.
{"title":"A deep-learning-aided diagnosis of drowning using post-mortem lung computed tomography","authors":"Amber Habib Qureshi, Takuro Ishii, Yoshifumi Saijo","doi":"10.1016/j.fri.2025.200629","DOIUrl":"10.1016/j.fri.2025.200629","url":null,"abstract":"<div><div>Identifying the cause of death using postmortem CT images is crucial since it provides a non-invasive, objective approach for forensic investigations while offering significant advantages in terms of time efficiency and cost-effectiveness compared to traditional autopsy methods. However, due to varied lung conditions in the postmortem CT images, a standardized method to diagnose drowning using CT images has not been established. This study aimed to devise a deep-learning-aided framework for diagnosing drowning from postmortem lung CT images. First, to find the suitable convolutional neural network (CNN) architecture for classifying lung CT images into drowning and non-drowning cases, three well-known CNNs, AlexNet, VGG16, and MobileNet, were trained with a single-institute postmortem CT image dataset and the performance and generalizability were also evaluated using images extracted from a public decedent CT image database. The results showed that VGG16 architecture outperformed the three models with the highest mean AUC-ROC and accuracy values of 88.42 % and 80.56 % respectively for drowning image classification, as well as the highest generalizability with an AUC-ROC of 71.79 % on a public image dataset. Additionally, the case-based diagnosis was performed using probability scores given from the model to each slice taken in the same subject. The final diagnosis accuracy was 96 % on the original dataset and 79 % on the public dataset, showing the strong potential that the devised framework can be used as a screening tool to identify drowning cases using postmortem CT images.</div></div>","PeriodicalId":40763,"journal":{"name":"Forensic Imaging","volume":"41 ","pages":"Article 200629"},"PeriodicalIF":0.8,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143886972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Estimating hemothorax volume via postmortem computed tomography (PMCT) remains challenging because of postmortem artifacts that can impact interpretation and accuracy. This study aimed to evaluate the accuracy of PMCT in estimating hemothorax volume compared with standard autopsy.
Methods
Forty deceased individuals who underwent both PMCT and autopsy were examined. PMCT volumes were manually segmented, and the results were compared with autopsy findings. Spearman's rank correlation and paired t-tests were used to assess accuracy.
Results
PMCT showed a high diagnostic accuracy for hemothorax, with correlation coefficients of 0.859 and 0.794 on the left and right sides, respectively. However, the mean absolute percentage error (MAPE) for volume estimation was relatively high, suggesting caution when relying solely on PMCT for volume estimation.
Conclusion
PMCT is a reliable tool for diagnosing hemothorax; however, its accuracy in volume estimation remains limited for manual segmentation methods. Further refinement of the imaging techniques is required for more precise volume measurements.
{"title":"High diagnostic accuracy of postmortem CT for hemothorax with volume estimation challenges: A comparative study with autopsy","authors":"Punpramepree Yeesakhorn , Wanlapha Tungsub , Nitima Saksobhavivat , Wisarn Worasuwannarak","doi":"10.1016/j.fri.2025.200626","DOIUrl":"10.1016/j.fri.2025.200626","url":null,"abstract":"<div><h3>Background</h3><div>Estimating hemothorax volume via postmortem computed tomography (PMCT) remains challenging because of postmortem artifacts that can impact interpretation and accuracy. This study aimed to evaluate the accuracy of PMCT in estimating hemothorax volume compared with standard autopsy.</div></div><div><h3>Methods</h3><div>Forty deceased individuals who underwent both PMCT and autopsy were examined. PMCT volumes were manually segmented, and the results were compared with autopsy findings. Spearman's rank correlation and paired t-tests were used to assess accuracy.</div></div><div><h3>Results</h3><div>PMCT showed a high diagnostic accuracy for hemothorax, with correlation coefficients of 0.859 and 0.794 on the left and right sides, respectively. However, the mean absolute percentage error (MAPE) for volume estimation was relatively high, suggesting caution when relying solely on PMCT for volume estimation.</div></div><div><h3>Conclusion</h3><div>PMCT is a reliable tool for diagnosing hemothorax; however, its accuracy in volume estimation remains limited for manual segmentation methods. Further refinement of the imaging techniques is required for more precise volume measurements.</div></div>","PeriodicalId":40763,"journal":{"name":"Forensic Imaging","volume":"41 ","pages":"Article 200626"},"PeriodicalIF":0.8,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143855481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01Epub Date: 2025-04-17DOI: 10.1016/j.fri.2025.200624
Deepa Jatti Patil, Chandramani B. More, Rashmi Venkatesh
The study aimed to determine age by assessing the discernibility of the periodontal ligament (PDL) and root canal (RC) on panoramic radiographs of mandibular third molars. In this retrospective study, 2000 panoramic radiographs of individuals aged between 16 to 40 were analysed, including both males and females. The radiographic discernibility of PDL and RC in mandibular third molars was assessed according to the study by Olze et al. which was categorised into four stages. At each stage, the minimum, maximum, and standard deviation were assessed. Statistical analysis was conducted to examine the relationship between age, sex, and PDL/RC stage. There was a notable disparity in the average age of individuals at different stages of PDL and RC. There was a considerable increase in the average age from PDL & RC stage 0 to stage 3. By considering the minimum and maximum values for each stage, individuals can be classified as being older than 17 years if they are in stage 1, and older than 20 years if they are in stages 2 and 3. These classifications are determined based on the combined results of the PDL and RC stages. The radiographic discernibility of PDL and RC can be utilised as a promising method to determine age in the western Indian population.
{"title":"Dental age estimation based on imaging of lower third molars in Western Indian population","authors":"Deepa Jatti Patil, Chandramani B. More, Rashmi Venkatesh","doi":"10.1016/j.fri.2025.200624","DOIUrl":"10.1016/j.fri.2025.200624","url":null,"abstract":"<div><div>The study aimed to determine age by assessing the discernibility of the periodontal ligament (PDL) and root canal (RC) on panoramic radiographs of mandibular third molars. In this retrospective study, 2000 panoramic radiographs of individuals aged between 16 to 40 were analysed, including both males and females. The radiographic discernibility of PDL and RC in mandibular third molars was assessed according to the study by Olze et al. which was categorised into four stages. At each stage, the minimum, maximum, and standard deviation were assessed. Statistical analysis was conducted to examine the relationship between age, sex, and PDL/RC stage. There was a notable disparity in the average age of individuals at different stages of PDL and RC. There was a considerable increase in the average age from PDL & RC stage 0 to stage 3. By considering the minimum and maximum values for each stage, individuals can be classified as being older than 17 years if they are in stage 1, and older than 20 years if they are in stages 2 and 3. These classifications are determined based on the combined results of the PDL and RC stages. The radiographic discernibility of PDL and RC can be utilised as a promising method to determine age in the western Indian population.</div></div>","PeriodicalId":40763,"journal":{"name":"Forensic Imaging","volume":"41 ","pages":"Article 200624"},"PeriodicalIF":0.8,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143879410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01Epub Date: 2025-04-29DOI: 10.1016/j.fri.2025.200637
Muhammad Faiz Mohd Fauad , Aspalilah Alias , Ker Woon Choy , Helmi Mohd Hadi Pritam , Eric Chung , Arofi Kurniawan , Khalid Ayidh Alqahtani
Sexual identification is the most crucial step in the forensic anthropology field. Traditional morphometric techniques, involving caliper-based measurements, are often labor-intensive and time-consuming. In contrast, the geometric morphometric method (GMM) offers a more efficient approach, integrating qualitative and quantitative assessments of biological forms based on precise geometric characterizations of their shape. This study aimed to assess sexual dimorphism of the Atlas (C1) bone on lateral cervical radiographs using GMM. A cross-sectional design was employed, utilizinglateral cervical radiographs from a sample of 413 individuals, including 208 males and 205 females, age ranged between 35 and 45 years old. Six 2D landmarks were identified and marked on the digitalized radiographs using TPSDig2 (Version 2.31) software. GMM analysis conducted by MorphoJ software. Eight principal components (PC) accounted for 100 % of the shape variability produced. Procrustes ANOVA showed that centroid size and shape were significantly different between different sexes. Discriminant function analysis (DFA) revealed a correct classification rate for 87.9 % of cases, with an identification accuracy of 87.0 % for males and 88.8 % for females. There were significant differences among males and females in the height of the C1 vertebral body with p < 0.05 via independent t-test. In conclusion, there was a significant sexual dimorphism of the C1 vertebra by GMM, which could serve as an alternative method in physical anthropology and forensic medicine.
性别鉴定是法医人类学领域最关键的一步。传统的形态测量技术，包括基于卡尺的测量，通常是劳动密集型和耗时的。相比之下，几何形态测量法（GMM）提供了一种更有效的方法，基于生物形态的精确几何特征，将生物形态的定性和定量评估整合在一起。本研究旨在利用GMM评估颈椎侧位片上寰椎（C1）骨的性别二态性。采用横断面设计，利用413人的侧位颈椎x线片样本，包括208名男性和205名女性，年龄在35至45岁之间。使用TPSDig2 （Version 2.31）软件在数字化x线片上识别并标记6个二维地标。采用MorphoJ软件进行GMM分析。8个主成分（PC）占产生的形状变异性的100%。Procrustes方差分析显示，不同性别间质心大小和形状存在显著差异。判别函数分析（Discriminant function analysis， DFA）的分类正确率为87.9%，其中男性的识别正确率为87.0%，女性为88.8%。男性和女性在C1椎体高度p <上有显著差异；经独立t检验0.05。综上所述，GMM对C1椎体有明显的性别二态性，可作为体质人类学和法医学的替代方法。
{"title":"Unlocking sexual dimorphism: geometric morphometrics analysis of the Atlas (C1) bone in Malaysian populations","authors":"Muhammad Faiz Mohd Fauad , Aspalilah Alias , Ker Woon Choy , Helmi Mohd Hadi Pritam , Eric Chung , Arofi Kurniawan , Khalid Ayidh Alqahtani","doi":"10.1016/j.fri.2025.200637","DOIUrl":"10.1016/j.fri.2025.200637","url":null,"abstract":"<div><div>Sexual identification is the most crucial step in the forensic anthropology field. Traditional morphometric techniques, involving caliper-based measurements, are often labor-intensive and time-consuming. In contrast, the geometric morphometric method (GMM) offers a more efficient approach, integrating qualitative and quantitative assessments of biological forms based on precise geometric characterizations of their shape. This study aimed to assess sexual dimorphism of the Atlas (C1) bone on lateral cervical radiographs using GMM. A cross-sectional design was employed, utilizinglateral cervical radiographs from a sample of 413 individuals, including 208 males and 205 females, age ranged between 35 and 45 years old. Six 2D landmarks were identified and marked on the digitalized radiographs using TPSDig2 (Version 2.31) software. GMM analysis conducted by MorphoJ software. Eight principal components (PC) accounted for 100 % of the shape variability produced. Procrustes ANOVA showed that centroid size and shape were significantly different between different sexes. Discriminant function analysis (DFA) revealed a correct classification rate for 87.9 % of cases, with an identification accuracy of 87.0 % for males and 88.8 % for females. There were significant differences among males and females in the height of the C1 vertebral body with <em>p</em> < 0.05 via independent t-test. In conclusion, there was a significant sexual dimorphism of the C1 vertebra by GMM, which could serve as an alternative method in physical anthropology and forensic medicine.</div></div>","PeriodicalId":40763,"journal":{"name":"Forensic Imaging","volume":"41 ","pages":"Article 200637"},"PeriodicalIF":0.8,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143895414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01Epub Date: 2025-04-17DOI: 10.1016/j.fri.2025.200627
Kirthika Ravi , Siddhartha Das , Ambika Prasad Patra , Deepak Barathi Subramania , Harichandrakumar Kottyen Thazhath
Background
Stature estimation contributes to the identification of an individual which is one of the objectives of a medicolegal autopsy. Stature can be estimated by measuring various landmarks of the cranium. Owing to the geographical variations, the regression formula used for one population may not be applicable to other populations. This CT scan study was conducted with an aim to develop regression formulas for the different cranial parameters in a South Indian adult population.
Methodology
511 patients scheduled for elective CT scans of the head and neck were recruited. Twenty-nine cranial variables were studied in each of these patients. Simple and multivariate linear regression was performed to establish a predictive stature estimation model. Pearson correlation and the predictive stature estimation model were considered significant if the P value was ≤ 0.05.
Results
All the cranial measurements showed a statistically significant correlation with stature in the overall population except for right orbital height, left orbital height and minimum distance between the condyles. The proportion of variance of stature explained by the model was found to be 27 % for the overall population, whereas it was 20 % and 21 % respectively for the males and females.
Conclusion
Our results suggest that the studied cranial measurements have a positive correlation with stature and can be used to estimate the stature, but the R2 values are not so encouraging.
{"title":"Stature estimation and craniometry–a computed tomography scan based study in South Indian adult population","authors":"Kirthika Ravi , Siddhartha Das , Ambika Prasad Patra , Deepak Barathi Subramania , Harichandrakumar Kottyen Thazhath","doi":"10.1016/j.fri.2025.200627","DOIUrl":"10.1016/j.fri.2025.200627","url":null,"abstract":"<div><h3>Background</h3><div>Stature estimation contributes to the identification of an individual which is one of the objectives of a medicolegal autopsy. Stature can be estimated by measuring various landmarks of the cranium. Owing to the geographical variations, the regression formula used for one population may not be applicable to other populations. This CT scan study was conducted with an aim to develop regression formulas for the different cranial parameters in a South Indian adult population.</div></div><div><h3>Methodology</h3><div>511 patients scheduled for elective CT scans of the head and neck were recruited. Twenty-nine cranial variables were studied in each of these patients. Simple and multivariate linear regression was performed to establish a predictive stature estimation model. Pearson correlation and the predictive stature estimation model were considered significant if the <em>P</em> value was ≤ 0.05.</div></div><div><h3>Results</h3><div>All the cranial measurements showed a statistically significant correlation with stature in the overall population except for right orbital height, left orbital height and minimum distance between the condyles. The proportion of variance of stature explained by the model was found to be 27 % for the overall population, whereas it was 20 % and 21 % respectively for the males and females.</div></div><div><h3>Conclusion</h3><div>Our results suggest that the studied cranial measurements have a positive correlation with stature and can be used to estimate the stature, but the R<sup>2</sup> values are not so encouraging.</div></div>","PeriodicalId":40763,"journal":{"name":"Forensic Imaging","volume":"41 ","pages":"Article 200627"},"PeriodicalIF":0.8,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143865102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We aimed to evaluate the correlation between stature and vertical skull measurements based on three-dimensional (3D) computed tomography (CT) images, develop a stature estimation formula, and validate it in a Japanese population. The “training” and “validation” datasets consisted of 275 and 49 identified individuals who underwent postmortem CT. Two skull measurements, the linear distances from the basion to the bregma (Basion–Bregma) and the posterior nasal spine to the bregma (PNS–Bregma), were obtained from 3D CT images that solely extracted cranial data. Pearson product-moment correlation coefficients assessed stature-skull correlations. Multiple regression analysis was performed to assess whether stature was dependent on sex. A stature estimation formula was developed based on the regression analysis. Validation tests were performed for each formula. Significant correlations were observed between stature and skull measurements. The correlation coefficients were 0.790 for stature and Basion–Bregma, and 0.782 for stature and PNS–Bregma. Sex status was statistically significant as an independent variable in regression analysis and influences the estimation of stature. For the stature estimation formula, the coefficient of determination adjusted for the degree of freedom (R*2) was 0.730, and the standard error of estimation (SEE) was 5.55 cm when using three variables: sex status, Basion–Bregma, and PNS–Bregma. The validation test exhibited high reliability; mean error (MA) = 0.10 cm and mean absolute error (MAE) = 4.64 cm. Vertical skull measurements from 3D CT images may be helpful for stature estimation in Japanese individuals, particularly in cases where better predictors are unavailable.
{"title":"Stature estimation based on vertical measurements of the skull using three-dimensional images from postmortem computed tomography in a Japanese population","authors":"Shoken Suzuki , Maki Ohtani , Yuhei Matsuo , Masayuki Fukuda , Sohtaro Mimasaka","doi":"10.1016/j.fri.2025.200628","DOIUrl":"10.1016/j.fri.2025.200628","url":null,"abstract":"<div><div>We aimed to evaluate the correlation between stature and vertical skull measurements based on three-dimensional (3D) computed tomography (CT) images, develop a stature estimation formula, and validate it in a Japanese population. The “training” and “validation” datasets consisted of 275 and 49 identified individuals who underwent postmortem CT. Two skull measurements, the linear distances from the basion to the bregma (Basion–Bregma) and the posterior nasal spine to the bregma (PNS–Bregma), were obtained from 3D CT images that solely extracted cranial data. Pearson product-moment correlation coefficients assessed stature-skull correlations. Multiple regression analysis was performed to assess whether stature was dependent on sex. A stature estimation formula was developed based on the regression analysis. Validation tests were performed for each formula. Significant correlations were observed between stature and skull measurements. The correlation coefficients were 0.790 for stature and Basion–Bregma, and 0.782 for stature and PNS–Bregma. Sex status was statistically significant as an independent variable in regression analysis and influences the estimation of stature. For the stature estimation formula, the coefficient of determination adjusted for the degree of freedom (<em>R</em>*<sup>2</sup>) was 0.730, and the standard error of estimation (SEE) was 5.55 cm when using three variables: sex status, Basion–Bregma, and PNS–Bregma. The validation test exhibited high reliability; mean error (MA) = 0.10 cm and mean absolute error (MAE) = 4.64 cm. Vertical skull measurements from 3D CT images may be helpful for stature estimation in Japanese individuals, particularly in cases where better predictors are unavailable.</div></div>","PeriodicalId":40763,"journal":{"name":"Forensic Imaging","volume":"41 ","pages":"Article 200628"},"PeriodicalIF":0.8,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143868382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号