Evidence map›Paper›PMID 35258670›Full record

ArticleInternational journal of legal medicine2022

Forensic age prediction and age classification for critical age thresholds via 3.0T magnetic resonance imaging of the knee in the Chinese Han population.

Xiao-Dong Deng, Ting Lu, Guang-Feng Liu, Fei Fan, Zhao Peng, Xiao-Qian Chen, Tian-Wu Chen, Meng-Jun Zhan, Lei Shi, Shuai Luo and 5 more

Abstract read
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In one paragraph

Article in International journal of legal medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
12.9field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 11 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors at 4 institutions in 1 country.

Xiao-Dong DengDepartment of Forensic Pathology, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, Sichuan, 610041, People's Republic of China.
Ting LuDepartment of Forensic Pathology, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, Sichuan, 610041, People's Republic of China.
Guang-Feng LiuDepartment of Forensic Pathology, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, Sichuan, 610041, People's Republic of China.
Fei FanDepartment of Forensic Pathology, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, Sichuan, 610041, People's Republic of China.
Zhao PengDepartment of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, People's Republic of China.
Xiao-Qian ChenSichuan Key Laboratory of Medical Imaging, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, 637000, People's Republic of China.
Tian-Wu ChenSichuan Key Laboratory of Medical Imaging, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, 637000, People's Republic of China.
Meng-Jun ZhanDepartment of Forensic Pathology, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, Sichuan, 610041, People's Republic of China.
Lei ShiDepartment of Forensic Pathology, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, Sichuan, 610041, People's Republic of China.
Shuai LuoDepartment of Forensic Pathology, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, Sichuan, 610041, People's Republic of China.
Xing-Tao ZhangDepartment of Forensic Pathology, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, Sichuan, 610041, People's Republic of China.
Meng LiuDepartment of Forensic Pathology, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, Sichuan, 610041, People's Republic of China.
Shi-Wen QiuDepartment of Forensic Pathology, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, Sichuan, 610041, People's Republic of China.
Bin CongDepartment of Forensic Pathology, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, Sichuan, 610041, People's Republic of China. hbydbincong@126.com.
Zhen-Hua DengDepartment of Forensic Pathology, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, Sichuan, 610041, People's Republic of China. dengzhenhua@scu.edu.cn.
West China Medical Center of Sichuan University · CNNorth Sichuan Medical University · CNHebei Medical University · CNSichuan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo assess the performance of knee MRI for forensic age prediction and classification for 12-, 14-, 16-, and 18-year thresholds.

methodsThe ossification stages of distal femoral epiphyses and proximal tibial epiphyses were assessed using an integrated staging system by Schmeling et al. and Kellinghaus et al. for knee 3.0T MRI with T1-weighted turbo spin-echo (T1-TSE) in sagittal orientation among 852 Chinese Han individuals (483 males and 369 females) aged 7-30 years. Regression models for age prediction were constructed and their performances were evaluated based on mean absolute deviation (MAD) values. In addition, the performances of age classification were assessed using receiver operating characteristic (ROC) analyses.

resultsThe intra- and inter-observer agreement levels were very good (κ > 0.80). The complete fusion of those two types of epiphyses took place before 18.0 years in our study participants. The minimum MAD values were 2.51 years (distal femur) and 2.69 years (proximal tibia) in males, and 2.75 years (distal femur) and 2.87 years (proximal tibia) in females. The specificity values of constructed prediction models were all above 90% for the 12-, 14-, and 16-year thresholds, compared to the 74.8-84.6% for the 18-year threshold. Better performances of age prediction and classification were observed in males by distal femoral epiphyses.

conclusionsOssification stages via 3.0T MRI of the knee with T1-TSE sequence using an integrated staging system could be a reliable noninvasive method for age prediction or for age classification for 12-, 14-, and 16-year thresholds, especially in males by distal femoral epiphyses. However, assessments based on the full bony fusion of the distal femoral epiphysis and proximal tibial epiphysis seemed not reliable for age classification for the 18-year threshold in the Chinese Han population.

Indexed as

Age Determination by SkeletonEpiphysesChinaFemaleFemurHumansMagnetic Resonance ImagingMaleOsteogenesisTibiaAge estimationDistal femoral epiphysisMagnetic resonance imagingProximal tibial epiphysis

Identifiers

PMID35258670
OpenAlexW4220726091

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.