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Shen Z, Zhong Y, Wang Y, Zhu H, Liu R, Yu S, Zhang H, Wang M, Yang T, Zhang M. A computational approach to estimate postmortem interval using postmortem computed tomography of multiple tissues based on animal experiments. Int J Legal Med 2024; 138:1093-1107. [PMID: 37999765 DOI: 10.1007/s00414-023-03127-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 10/27/2023] [Indexed: 11/25/2023]
Abstract
The estimation of postmortem interval (PMI) is a complex and challenging problem in forensic medicine. In recent years, many studies have begun to use machine learning methods to estimate PMI. However, research combining postmortem computed tomography (PMCT) with machine learning models for PMI estimation is still in early stages. This study aims to establish a multi-tissue machine learning model for PMI estimation using PMCT data from various tissues. We collected PMCT data of seven tissues, including brain, eyeballs, myocardium, liver, kidneys, erector spinae, and quadriceps femoris from 10 rabbits after death. CT images were taken every 12 h until 192 h after death, and HU values were extracted from the CT images of each tissue as a dataset. Support vector machine, random forest, and K-nearest neighbors were performed to establish PMI estimation models, and after adjusting the parameters of each model, they were used as first-level classification to build a stacking model to further improve the PMI estimation accuracy. The accuracy and generalized area under the receiver operating characteristic curve of the multi-tissue stacking model were able to reach 93% and 0.96, respectively. Results indicated that PMCT detection could be used to obtain postmortem change of different tissue densities, and the stacking model demonstrated strong predictive and generalization abilities. This approach provides new research methods and ideas for the study of PMI estimation.
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Affiliation(s)
- Zefang Shen
- Key Laboratory of Evidence Science (China University of Political Science and Law), Ministry of Education, No. 25 Xitucheng Road, Haidian District, Beijing, 100088, China
| | - Yue Zhong
- Key Laboratory of Evidence Science (China University of Political Science and Law), Ministry of Education, No. 25 Xitucheng Road, Haidian District, Beijing, 100088, China
| | - Yucong Wang
- Key Laboratory of Evidence Science (China University of Political Science and Law), Ministry of Education, No. 25 Xitucheng Road, Haidian District, Beijing, 100088, China
| | - Haibiao Zhu
- Key Laboratory of Evidence Science (China University of Political Science and Law), Ministry of Education, No. 25 Xitucheng Road, Haidian District, Beijing, 100088, China
| | - Ran Liu
- Forensic Science Center of Beijing Huatong Junjian Science and Technology Company Limited, Beijing, 100016, China
| | - Shengnan Yu
- Key Laboratory of Evidence Science (China University of Political Science and Law), Ministry of Education, No. 25 Xitucheng Road, Haidian District, Beijing, 100088, China
| | - Haidong Zhang
- Key Laboratory of Evidence Science (China University of Political Science and Law), Ministry of Education, No. 25 Xitucheng Road, Haidian District, Beijing, 100088, China
| | - Min Wang
- Key Laboratory of Evidence Science (China University of Political Science and Law), Ministry of Education, No. 25 Xitucheng Road, Haidian District, Beijing, 100088, China
| | - Tiantong Yang
- Key Laboratory of Evidence Science (China University of Political Science and Law), Ministry of Education, No. 25 Xitucheng Road, Haidian District, Beijing, 100088, China.
| | - Mengzhou Zhang
- Key Laboratory of Evidence Science (China University of Political Science and Law), Ministry of Education, No. 25 Xitucheng Road, Haidian District, Beijing, 100088, China.
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Schmidt VM, Zelger P, Wöss C, Fodor M, Hautz T, Schneeberger S, Huck CW, Arora R, Brunner A, Zelger B, Schirmer M, Pallua JD. Handheld hyperspectral imaging as a tool for the post-mortem interval estimation of human skeletal remains. Heliyon 2024; 10:e25844. [PMID: 38375262 PMCID: PMC10875450 DOI: 10.1016/j.heliyon.2024.e25844] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 01/30/2024] [Accepted: 02/02/2024] [Indexed: 02/21/2024] Open
Abstract
In forensic medicine, estimating human skeletal remains' post-mortem interval (PMI) can be challenging. Following death, bones undergo a series of chemical and physical transformations due to their interactions with the surrounding environment. Post-mortem changes have been assessed using various methods, but estimating the PMI of skeletal remains could still be improved. We propose a new methodology with handheld hyperspectral imaging (HSI) system based on the first results from 104 human skeletal remains with PMIs ranging between 1 day and 2000 years. To differentiate between forensic and archaeological bone material, the Convolutional Neural Network analyzed 65.000 distinct diagnostic spectra: the classification accuracy was 0.58, 0.62, 0.73, 0.81, and 0.98 for PMIs of 0 week-2 weeks, 2 weeks-6 months, 6 months-1 year, 1 year-10 years, and >100 years, respectively. In conclusion, HSI can be used in forensic medicine to distinguish bone materials >100 years old from those <10 years old with an accuracy of 98%. The model has adequate predictive performance, and handheld HSI could serve as a novel approach to objectively and accurately determine the PMI of human skeletal remains.
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Affiliation(s)
- Verena-Maria Schmidt
- Institute of Forensic Medicine, Medical University of Innsbruck, Muellerstraße 44, 6020 Innsbruck, Austria
| | - Philipp Zelger
- University Clinic for Hearing, Voice and Speech Disorders, Medical University of Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria
| | - Claudia Wöss
- Institute of Forensic Medicine, Medical University of Innsbruck, Muellerstraße 44, 6020 Innsbruck, Austria
| | - Margot Fodor
- OrganLifeTM, Department of Visceral, Transplant and Thoracic Surgery, Medical University of Innsbruck, Innsbruck, Austria
| | - Theresa Hautz
- OrganLifeTM, Department of Visceral, Transplant and Thoracic Surgery, Medical University of Innsbruck, Innsbruck, Austria
| | - Stefan Schneeberger
- OrganLifeTM, Department of Visceral, Transplant and Thoracic Surgery, Medical University of Innsbruck, Innsbruck, Austria
| | - Christian Wolfgang Huck
- Institute of Analytical Chemistry and Radiochemistry, University of Innsbruck, 6020 Innsbruck, Austria
| | - Rohit Arora
- Department of Orthopaedics and Traumatology, Medical University of Innsbruck, Anichstraße 35, 6020 Innsbruck, Austria
| | - Andrea Brunner
- Institute of Pathology, Neuropathology, and Molecular Pathology, Medical University of Innsbruck, Muellerstrasse 44, 6020 Innsbruck, Austria
| | - Bettina Zelger
- Institute of Pathology, Neuropathology, and Molecular Pathology, Medical University of Innsbruck, Muellerstrasse 44, 6020 Innsbruck, Austria
| | - Michael Schirmer
- Department of Internal Medicine, Clinic II, Medical University of Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria
| | - Johannes Dominikus Pallua
- Department of Orthopaedics and Traumatology, Medical University of Innsbruck, Anichstraße 35, 6020 Innsbruck, Austria
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Locci E, Stocchero M, Gottardo R, Chighine A, De-Giorgio F, Ferino G, Nioi M, Demontis R, Tagliaro F, d'Aloja E. PMI estimation through metabolomics and potassium analysis on animal vitreous humour. Int J Legal Med 2023; 137:887-895. [PMID: 36799966 PMCID: PMC10085955 DOI: 10.1007/s00414-023-02975-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2022] [Accepted: 02/08/2023] [Indexed: 02/18/2023]
Abstract
INTRODUCTION The estimation of post-mortem interval (PMI) remains a major challenge in forensic science. Most of the proposed approaches lack the reliability required to meet the rigorous forensic standards. OBJECTIVES We applied 1H NMR metabolomics to estimate PMI on ovine vitreous humour comparing the results with the actual scientific gold standard, namely vitreous potassium concentrations. METHODS Vitreous humour samples were collected in a time frame ranging from 6 to 86 h after death. Experiments were performed by using 1H NMR metabolomics and ion capillary analysis. Data were submitted to multivariate statistical data analysis. RESULTS A multivariate calibration model was built to estimate PMI based on 47 vitreous humour samples. The model was validated with an independent test set of 24 samples, obtaining a prediction error on the entire range of 6.9 h for PMI < 24 h, 7.4 h for PMI between 24 and 48 h, and 10.3 h for PMI > 48 h. Time-related modifications of the 1H NMR vitreous metabolomic profile could predict PMI better than potassium up to 48 h after death, whilst a combination of the two is better than the single approach for higher PMI estimation. CONCLUSION The present study, although in a proof-of-concept animal model, shows that vitreous metabolomics can be a powerful tool to predict PMI providing a more accurate estimation compared to the widely studied approach based on vitreous potassium concentrations.
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Affiliation(s)
- Emanuela Locci
- Department of Medical Sciences and Public Health, Section of Legal Medicine, University of Cagliari, Cittadella Universitaria di Monserrato, 09042, Monserrato, Cagliari, Italy
| | - Matteo Stocchero
- Department of Women's and Children's Health, University of Padova, Padua, Italy
| | - Rossella Gottardo
- Department of Diagnostics and Public Health, Unit of Forensic Medicine, University of Verona, Verona, Italy
| | - Alberto Chighine
- Department of Medical Sciences and Public Health, Section of Legal Medicine, University of Cagliari, Cittadella Universitaria di Monserrato, 09042, Monserrato, Cagliari, Italy.
| | - Fabio De-Giorgio
- Department of Health Surveillance and Bioethics, Section of Legal Medicine, Catholic University of Rome, Rome, Italy.,Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Giulio Ferino
- Department of Medical Sciences and Public Health, Section of Legal Medicine, University of Cagliari, Cittadella Universitaria di Monserrato, 09042, Monserrato, Cagliari, Italy
| | - Matteo Nioi
- Department of Medical Sciences and Public Health, Section of Legal Medicine, University of Cagliari, Cittadella Universitaria di Monserrato, 09042, Monserrato, Cagliari, Italy
| | - Roberto Demontis
- Department of Medical Sciences and Public Health, Section of Legal Medicine, University of Cagliari, Cittadella Universitaria di Monserrato, 09042, Monserrato, Cagliari, Italy
| | - Franco Tagliaro
- Department of Diagnostics and Public Health, Unit of Forensic Medicine, University of Verona, Verona, Italy
| | - Ernesto d'Aloja
- Department of Medical Sciences and Public Health, Section of Legal Medicine, University of Cagliari, Cittadella Universitaria di Monserrato, 09042, Monserrato, Cagliari, Italy
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Fujimoto K, Gonoi W, Ishida M, Okimoto N, Nyunoya K, Abe H, Ushiku T, Abe O. Association between postmortem computed tomography value of cerebrospinal fluid and time after death: A longitudinal study of antemortem and postmortem computed tomography. J Forensic Leg Med 2023; 93:102461. [PMID: 36470057 DOI: 10.1016/j.jflm.2022.102461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 11/16/2022] [Accepted: 11/25/2022] [Indexed: 12/03/2022]
Abstract
This study was designed to examine the antemortem factors affecting cerebrospinal fluid (CSF) Hounsfield Units (HU) on postmortem computed tomography (PMCT) compared to the antemortem CT (AMCT). Fifty-five participants without brain lesions who died at a university hospital and underwent AMCT, PMCT, and an autopsy were enrolled. We recorded age, sex, time after death, the CSF HU on AMCT and PMCT at multiple measuring points, 4-point-scale brain atrophy grade on AMCT, and the cella media index. We tested the effects of CSF HU factors observed on PMCT. No significant differences were observed between CSF HUs at any of the PMCT measurement points. The average CSF HU on PMCT was positively correlated with the natural logarithm of the time after death (Pearson's correlation coefficient, 0.81; p < 0.001). No other factors showed correlative relationships. Up until approximately 12 h after death, the CSF HU on PMCT depended only on the time since death.
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Affiliation(s)
- Kotaro Fujimoto
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Wataru Gonoi
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
| | - Masanori Ishida
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Naomasa Okimoto
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Keisuke Nyunoya
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Hiroyuki Abe
- Department of Pathology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Tetsuo Ushiku
- Department of Pathology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Osamu Abe
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
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Schmidt VM, Zelger P, Woess C, Pallua AK, Arora R, Degenhart G, Brunner A, Zelger B, Schirmer M, Rabl W, Pallua JD. Application of Micro-Computed Tomography for the Estimation of the Post-Mortem Interval of Human Skeletal Remains. BIOLOGY 2022; 11:biology11081105. [PMID: 35892961 PMCID: PMC9331256 DOI: 10.3390/biology11081105] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 07/22/2022] [Accepted: 07/22/2022] [Indexed: 12/02/2022]
Abstract
It is challenging to estimate the post-mortem interval (PMI) of skeletal remains within a forensic context. As a result of their interactions with the environment, bones undergo several chemical and physical changes after death. So far, multiple methods have been used to follow up on post-mortem changes. There is, however, no definitive way to estimate the PMI of skeletal remains. This research aimed to propose a methodology capable of estimating the PMI using micro-computed tomography measurements of 104 human skeletal remains with PMIs between one day and 2000 years. The present study indicates that micro-computed tomography could be considered an objective and precise method of PMI evaluation in forensic medicine. The measured parameters show a significant difference regarding the PMI for Cort Porosity p < 0.001, BV/TV p > 0.001, Mean1 p > 0.001 and Mean2 p > 0.005. Using a machine learning approach, the neural network showed an accuracy of 99% for distinguishing between samples with a PMI of less than 100 years and archaeological samples.
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Affiliation(s)
- Verena-Maria Schmidt
- Institute of Legal Medicine, Medical University of Innsbruck, Muellerstraße 44, 6020 Innsbruck, Austria; (V.-M.S.); (C.W.); (W.R.)
| | - Philipp Zelger
- University Clinic for Hearing, Voice and Speech Disorders, Medical University of Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria;
| | - Claudia Woess
- Institute of Legal Medicine, Medical University of Innsbruck, Muellerstraße 44, 6020 Innsbruck, Austria; (V.-M.S.); (C.W.); (W.R.)
| | - Anton K. Pallua
- Former Institute for Computed Tomography-Neuro CT, Medical University of Innsbruck, Anichstraße 35, 6020 Innsbruck, Austria;
| | - Rohit Arora
- University Hospital for Orthopaedics and Traumatology, Medical University of Innsbruck, Anichstraße 35, 6020 Innsbruck, Austria;
| | - Gerald Degenhart
- Department of Radiology, Medical University of Innsbruck, Anichstraße 35, 6020 Innsbruck, Austria;
| | - Andrea Brunner
- Institute of Pathology, Neuropathology, Molecular Pathology, Medical University of Innsbruck, Muellerstrasse 44, 6020 Innsbruck, Austria; (A.B.); (B.Z.)
| | - Bettina Zelger
- Institute of Pathology, Neuropathology, Molecular Pathology, Medical University of Innsbruck, Muellerstrasse 44, 6020 Innsbruck, Austria; (A.B.); (B.Z.)
| | - Michael Schirmer
- Department of Internal Medicine, Clinic II, Medical University of Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria;
| | - Walter Rabl
- Institute of Legal Medicine, Medical University of Innsbruck, Muellerstraße 44, 6020 Innsbruck, Austria; (V.-M.S.); (C.W.); (W.R.)
| | - Johannes D. Pallua
- University Hospital for Orthopaedics and Traumatology, Medical University of Innsbruck, Anichstraße 35, 6020 Innsbruck, Austria;
- Correspondence:
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Post mortem computed tomography meets radiomics: a case series on fractal analysis of post mortem changes in the brain. Int J Legal Med 2022; 136:719-727. [PMID: 35239030 PMCID: PMC9005394 DOI: 10.1007/s00414-022-02801-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Accepted: 02/14/2022] [Indexed: 10/26/2022]
Abstract
Estimating the post-mortem interval is a fundamental, albeit challenging task in forensic sciences. To this aim, forensic practitioners need to assess post-mortem changes through a plethora of different methods, most of which are inherently qualitative, thus providing broad time intervals rather than precise determinations. This challenging problem is further complicated by the influence of environmental factors, which modify the temporal dynamics of post-mortem changes, sometimes in a rather unpredictable fashion. In this context, the search for quantitative and objective descriptors of post-mortem changes is highly demanded. In this study, we used computed tomography (CT) to assess the post-mortem anatomical modifications occurring in the time interval 0-4 days after death in the brain of four corpses. Our results show that fractal analysis of CT brain slices provides a set of quantitative descriptors able to map post-mortem changes over time throughout the whole brain. Although incapable of producing a direct estimation of the PMI, these descriptors could be used in combination with other more established methods to improve the accuracy and reliability of PMI determination.
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