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基于X光片和机器学习分类的儿童骨折愈合的死后和生前法医评估

Postmortem and Antemortem Forensic Assessment of Pediatric Fracture Healing from Radiographs and Machine Learning Classification.

作者信息

Kyllonen Kelsey M, Monson Keith L, Smith Michael A

机构信息

FBI Laboratory, Quantico, VA 22135, USA.

出版信息

Biology (Basel). 2022 May 13;11(5):749. doi: 10.3390/biology11050749.

DOI:10.3390/biology11050749
PMID:35625477
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9138832/
Abstract

A timeline of pediatric bone healing using fracture healing characteristics that can be assessed solely using radiographs would be practical for forensic casework, where the fracture event may precede death by days, months, or years. However, the dating of fractures from radiographs is difficult, imprecise, and lacks consensus, as only a few aspects of the healing process are visible on radiographs. Multiple studies in both the clinical and forensic literature have attempted to develop a usable scale to assess pediatric bone healing on radiographs using various healing characteristics. In contrast to the orthopedic definition, a fracture in forensic casework is only considered to be healed when the area around the fracture has been remodeled to the point that the fracture is difficult to detect on a radiograph or on the surface of the bone itself, a process that can take several years. We subjectively assessed visible characteristics of healing in radiograms of fractures occurring in 942 living children and adolescents. By dividing these assessments into learning and test (validation) sets, the accuracy of a newly proposed fracture healing scale was compared to a previous study. Two machine learning models were used to test predictions of the new scale. All three models produced similar estimates with substantial imprecision. Results corroborate the Malone model with an independent dataset and support the efficacy of using less complex models to estimate fracture age in children.

摘要

利用仅通过X线片就能评估的骨折愈合特征制定一份小儿骨愈合时间线,对于法医案件工作将是实用的,在这类案件中,骨折事件可能发生在死亡前几天、几个月或几年。然而,通过X线片确定骨折时间很困难、不准确且缺乏共识,因为在X线片上只能看到愈合过程的几个方面。临床和法医文献中的多项研究都试图制定一个可用的量表,利用各种愈合特征在X线片上评估小儿骨愈合情况。与骨科定义不同,在法医案件工作中,只有当骨折周围区域重塑到在X线片或骨表面本身难以检测到骨折的程度时,骨折才被认为愈合,这一过程可能需要数年时间。我们主观评估了942名在世儿童和青少年骨折X线片上可见的愈合特征。通过将这些评估分为学习集和测试(验证)集,将新提出的骨折愈合量表的准确性与之前的一项研究进行了比较。使用了两种机器学习模型来测试新量表的预测。所有三种模型都产生了类似的估计,但存在很大的不精确性。结果用一个独立数据集证实了马龙模型,并支持使用不太复杂的模型来估计儿童骨折年龄的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40d2/9138832/0c3500cd6d79/biology-11-00749-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40d2/9138832/638d08395695/biology-11-00749-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40d2/9138832/9eee9fe504be/biology-11-00749-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40d2/9138832/229821114996/biology-11-00749-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40d2/9138832/a2a57845c398/biology-11-00749-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40d2/9138832/c6c874563149/biology-11-00749-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40d2/9138832/0c3500cd6d79/biology-11-00749-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40d2/9138832/638d08395695/biology-11-00749-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40d2/9138832/9eee9fe504be/biology-11-00749-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40d2/9138832/229821114996/biology-11-00749-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40d2/9138832/a2a57845c398/biology-11-00749-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40d2/9138832/c6c874563149/biology-11-00749-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40d2/9138832/0c3500cd6d79/biology-11-00749-g006.jpg

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