法医学杂志Pub Date : 2025-02-25DOI: 10.12116/j.issn.1004-5619.2024.241202
Dan-Yang Li, Hui-Ming Zhou, Lei Wan, Tai-Ang Liu, Yuan-Zhe Li, Mao-Wen Wang, Ya-Hui Wang
{"title":"Bone Age Estimation of Chinese Han Adolescents's and Children's Elbow Joint X-rays Based on Multiple Deep Convolutional Neural Network Models.","authors":"Dan-Yang Li, Hui-Ming Zhou, Lei Wan, Tai-Ang Liu, Yuan-Zhe Li, Mao-Wen Wang, Ya-Hui Wang","doi":"10.12116/j.issn.1004-5619.2024.241202","DOIUrl":"10.12116/j.issn.1004-5619.2024.241202","url":null,"abstract":"<p><strong>Objectives: </strong>To explore a deep learning-based automatic bone age estimation model for elbow joint X-ray images of Chinese Han adolescents and children and evaluate its performance.</p><p><strong>Methods: </strong>A total of 943 (517 males and 426 females) elbow joint frontal view X-ray images of Chinese Han adolescents and children aged 6.00 to <16.00 years were collected from East, South, Central and Northwest China. Three experimental schemes were adopted for bone age estimation. Scheme 1: Directly input preprocessed images into the regression model; Scheme 2: Train a segmentation network using \"key elbow joint bone annotations\" as labels, then input segmented images into the regression model; Scheme 3: Train a segmentation network using \"full elbow joint bone annotations\" as labels, then input segmented images into the regression model. For segmentation, the optimal model was selected from U-Net, UNet++ and TransUNet. For regression, VGG16, VGG19, InceptionV2, InceptionV3, ResNet34, ResNet50, ResNet101 and DenseNet121 models were selected for bone age estimation. The dataset was randomly split into 80% (754 samples) for training and validation for model fitting and hyperparameter tuning, and 20% (189 samples) as an internal test set to test the performance of the trained model. An additional 104 elbow joint X-ray images from the same demographic and age group were collected and used as an external test set. Model performance was evaluated by comparing the mean absolute error (MAE), root mean square error (RMSE), accuracies within ±0.7 years (<i>P</i><sub>±0.7 years</sub>) and ±1.0 years (<i>P</i><sub>±1.0 years</sub>) between the estimated age and the actual age, and by drawing radar charts, scatter plots, and heatmaps.</p><p><strong>Results: </strong>When segmented with Scheme 3, the UNet++ model achieved good segmentation performance with a segmentation loss of 0.000 4 and an accuracy of 93.8% at a learning rate of 0.000 1. In the internal test set, the DenseNet121 model with Scheme 3 yielded the best results with MAE, <i>P</i><sub>±0.7 years</sub> and <i>P</i><sub>±1.0 years</sub> being 0.83 years, 70.03%, and 84.30%, respectively. In the external test set, the DenseNet121 model with Scheme 3 also performed best, with an average MAE of 0.89 years and an average RMSE of 1.00 years.</p><p><strong>Conclusions: </strong>When performing automatic bone age estimation using elbow joint X-ray images in Chinese Han adolescents and children, it is recommended to use the UNet++ model for segmentation. The DenseNet121 model with Scheme 3 achieves optimal performance. Using segmentation networks, especially that trained with annotation areas encompassing the full elbow joint including the distal humerus, proximal radius, and proximal ulna, can improve the accuracy of bone age estimation based on elbow joint X-ray images.</p>","PeriodicalId":12317,"journal":{"name":"法医学杂志","volume":"41 1","pages":"48-58"},"PeriodicalIF":0.0,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144119296","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}
法医学杂志Pub Date : 2024-12-25DOI: 10.12116/j.issn.1004-5619.2024.340202
Zhu-Tao Guo, Qian-Ya Deng, Si-Yang He, Shui-Qing Zheng, Rong Wang, Wen-Juan Sun, Chen Liang, Chun-Fang Ni
{"title":"Rapid Screening of 60 Types of Natural Toxins in Whole Blood by UPLC-Q/Orbitrap HRMS.","authors":"Zhu-Tao Guo, Qian-Ya Deng, Si-Yang He, Shui-Qing Zheng, Rong Wang, Wen-Juan Sun, Chen Liang, Chun-Fang Ni","doi":"10.12116/j.issn.1004-5619.2024.340202","DOIUrl":"10.12116/j.issn.1004-5619.2024.340202","url":null,"abstract":"<p><strong>Objectives: </strong>To establish a rapid screening method for 60 types of natural toxins in whole blood by ultra-high performance liquid chromatography-quadrupole/electrostatic field orbitrap high resolution mass spectrometry (UPLC-Q/Orbitrap HRMS).</p><p><strong>Methods: </strong>The chromatographic and mass spectrometric information of 60 standard samples of natural toxins were analyzed and recorded, and a screening database was built. Whole blood was pretreated by protein precipitation method combined with ultrasonic-assisted dispersion, and then a Hypersil GOLD<sup>TM</sup> C<sub>18</sub> column was used with 5 mmol/L ammonium formate aqueous solution (containing 0.1% formic acid) and acetonitrile as mobile phase for gradient elution. In the positive ion mode, the data were collected in full scan/data-dependent secondary scan (Full MS/dd-MS<sup>2</sup>) mode. Based on the established screening library, the rapid screening of 60 types of natural toxins in whole blood was realized by TraceFinder software.</p><p><strong>Results: </strong>A UPLC-Q/Orbitrap HRMS method was developed for the screening of 60 types of natural toxins in whole blood. Except for the limit of detection (LOD) of oxymatrine (20 ng/mL) and strophanthidin (40 ng/mL), the LOD for the other 58 natural toxins was in the range of 0.05-5 ng/mL.</p><p><strong>Conclusions: </strong>This method has a simple and efficient pretreatment process and can achieve rapid screening of 60 types of natural toxins in whole blood.</p>","PeriodicalId":12317,"journal":{"name":"法医学杂志","volume":"40 6","pages":"564-568"},"PeriodicalIF":0.0,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143624030","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}
引用次数: 0
法医学杂志Pub Date : 2024-12-25DOI: 10.12116/j.issn.1004-5619.2023.230902
法医学杂志Pub Date : 2024-12-25DOI: 10.12116/j.issn.1004-5619.2023.231203
Zhi-Lu Zhou, Dong-Fei Zhang, Jie-Min Chen, Ya-Hui Wang, Hong-Xia Hao, Tai-Ang Liu, Yu-Heng He, Ding-Nian Long, Rui-Jue Liu, Lei Wan
{"title":"MRI Application in Quantification of Epiphyseal Development in the Wrist and Bone Age Estimation of Han Male Adolescents in East China.","authors":"Zhi-Lu Zhou, Dong-Fei Zhang, Jie-Min Chen, Ya-Hui Wang, Hong-Xia Hao, Tai-Ang Liu, Yu-Heng He, Ding-Nian Long, Rui-Jue Liu, Lei Wan","doi":"10.12116/j.issn.1004-5619.2023.231203","DOIUrl":"10.12116/j.issn.1004-5619.2023.231203","url":null,"abstract":"<p><strong>Objectives: </strong>To investigate the value of wrist MRI in bone age estimation for male adolescents in Shanghai, Zhejiang and Jiangsu.</p><p><strong>Methods: </strong>A total of 124 Han male adolescents aged 6.0 to 18.0 years from Shanghai, Zhejiang and Jiangsu were selected as subjects. Their weight and height were measured, and T1WI and T2WI sequences of the wrist were scanned. The distal ends of the radius and ulna, and the first to five metacarpal epiphyses and corresponding metaphyses were selected as observational indexes after MRI images of the wrist were obtained. The development of each index was classified (0-2 grades) by a deputy senior imaging expert, then the maximum width of each index was measured by another deputy senior expert. Height, weight, classification and maximum width of indexes were used as input variables, and age was used as the target variable. Support vector machine, random forest, current reality tree, and linear regression models were established to estimate the bone age, and the model with the highest accuracy was selected.</p><p><strong>Results: </strong>The height, weight, classification of wrist bone epiphysis development, maximum width of each bone metaphysis and epiphysis were all correlated with age (<i>P</i><0.05). The accuracies of the support vector machine were the highest when the differences between bone age and actual chronological age were within 1.0 and 1.5 years (88.7% and 96.0%, respectively).</p><p><strong>Conclusions: </strong>It is feasible to estimate bone age by using MRI images. Quantifying the maximum width of the epiphysis and corresponding metaphysis of bone and combining it with MRI image classification can effectively reduce the estimation error.</p>","PeriodicalId":12317,"journal":{"name":"法医学杂志","volume":"40 6","pages":"589-596"},"PeriodicalIF":0.0,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143624029","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}
引用次数: 0
法医学杂志Pub Date : 2024-12-25DOI: 10.12116/j.issn.1004-5619.2023.230603
法医学杂志Pub Date : 2024-12-25DOI: 10.12116/j.issn.1004-5619.2024.340704
Guo-Qing Gao, Shuo Yang, Li-Ying Zhou, Shi-Bei DU, Yan Shi
{"title":"<i>In Vivo</i> Analysis of New Psychoactive Substances： Nitazenes.","authors":"Guo-Qing Gao, Shuo Yang, Li-Ying Zhou, Shi-Bei DU, Yan Shi","doi":"10.12116/j.issn.1004-5619.2024.340704","DOIUrl":"10.12116/j.issn.1004-5619.2024.340704","url":null,"abstract":"<p><p>Nitazenes are a class of synthetic opioids that have recently emerged in the illegal drug market. They are characterized by high potency and a narrow therapeutic window. Compared with traditional opioids, these substances are more likely to cause severe respiratory depression. In recent years, the abuse of nitazenes has occurred frequently, causing hundreds of overdose deaths worldwide, and posing a serious threat to individual health and public safety. As more nitazenes continue to emerge, research on the identification of these substances has received increasing attention. This paper reviews the structural characteristics, <i>in vivo</i> and <i>in vitro</i> pharmacological characterizations and analysis methods of common nitazenes, aiming to provide a basis and reference for the study of these substances in forensic toxicology.</p>","PeriodicalId":12317,"journal":{"name":"法医学杂志","volume":"40 6","pages":"597-607"},"PeriodicalIF":0.0,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143624024","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}
引用次数: 0
法医学杂志Pub Date : 2024-12-25DOI: 10.12116/j.issn.1004-5619.2024.440401
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