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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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Franceschetti L, Amadasi A, Bugelli V, Bolsi G, Tsokos M. Estimation of Late Postmortem Interval: Where Do We Stand? A Literature Review. BIOLOGY 2023; 12:783. [PMID: 37372068 DOI: 10.3390/biology12060783] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2023] [Revised: 05/26/2023] [Accepted: 05/27/2023] [Indexed: 06/29/2023]
Abstract
Estimating time since death can be challenging for forensic experts, and is one of the most challenging activities concerning the forensic world. Various methods have been assessed to calculate the postmortem interval on dead bodies in different stages of decomposition and are currently widely used. Nowadays, the only well-recognized dating technique is carbon-14 radioisotope measurement, whereas other methods have been tested throughout the years involving different disciplines with different and sometimes not univocal results. Today, there is no precise and secure method to precisely determine time since death, and late postmortem interval estimation remains one of the most debated topics in forensic pathology. Many proposed methods have shown promising results, and it is desirable that with further studies some of them might become acknowledged techniques to resolve such a difficult and important challenge. The present review aims at presenting studies about the different techniques that have been tested in order to find a valuable method for estimating time since death for skeletal remains. By providing a comprehensive overview, the purpose of this work is to offer readers new perspectives on postmortem interval estimation and to improve current practice in the management of skeletal remains and decomposed bodies.
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Affiliation(s)
- Lorenzo Franceschetti
- Istituto di Medicina Legale, Dipartimento di Scienze Biomediche per la Salute, Università degli Studi di Milano, via Luigi Mangiagalli 37, 20133 Milan, Italy
| | - Alberto Amadasi
- Institute of Legal Medicine and Forensic Sciences, Charité-Universitätsmedizin Berlin, Turmstr. 21 (Haus M), 10559 Berlin, Germany
| | - Valentina Bugelli
- South-East Tuscany Local Health Unit, Department of Legal Medicine, via Cimabue 109, 58100 Grosseto, Italy
| | - Giulia Bolsi
- Istituto di Medicina Legale, Dipartimento di Scienze Biomediche per la Salute, Università degli Studi di Milano, via Luigi Mangiagalli 37, 20133 Milan, Italy
| | - Michael Tsokos
- Institute of Legal Medicine and Forensic Sciences, Charité-Universitätsmedizin Berlin, Turmstr. 21 (Haus M), 10559 Berlin, Germany
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Unterberger SH, Berger C, Schirmer M, Pallua AK, Zelger B, Schäfer G, Kremser C, Degenhart G, Spiegl H, Erler S, Putzer D, Arora R, Parson W, Pallua JD. Morphological and Tissue Characterization with 3D Reconstruction of a 350-Year-Old Austrian Ardea purpurea Glacier Mummy. BIOLOGY 2023; 12:biology12010114. [PMID: 36671806 PMCID: PMC9855678 DOI: 10.3390/biology12010114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 01/06/2023] [Accepted: 01/09/2023] [Indexed: 01/12/2023]
Abstract
Glaciers are dwindling archives, releasing animal mummies preserved in the ice for centuries due to climate changes. As preservation varies, residual soft tissues may differently expand the biological information content of such mummies. DNA studies have proven the possibility of extracting and analyzing DNA preserved in skeletal residuals and sediments for hundreds or thousands of years. Paleoradiology is the method of choice as a non-destructive tool for analyzing mummies, including micro-computed tomography (micro-CT) and magnetic resonance imaging (MRI). Together with radiocarbon dating, histo-anatomical analyses, and DNA sequencing, these techniques were employed to identify a 350-year-old Austrian Ardea purpurea glacier mummy from the Ötztal Alps. Combining these techniques proved to be a robust methodological concept for collecting inaccessible information regarding the structural organization of the mummy. The variety of methodological approaches resulted in a distinct picture of the morphological patterns of the glacier animal mummy. The BLAST search in GenBank resulted in a 100% and 98.7% match in the cytb gene sequence with two entries of the species Purple heron (Ardea purpurea; Accession number KJ941160.1 and KJ190948.1) and a 98% match with the same species for the 16 s sequence (KJ190948.1), which was confirmed by the anatomic characteristics deduced from micro-CT and MRI.
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Affiliation(s)
- Seraphin H. Unterberger
- Material-Technology, Leopold-Franzens University Innsbruck, Technikerstraße 13, 6020 Innsbruck, Austria
| | - Cordula Berger
- Institute of Legal Medicine, 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
| | - Anton Kasper Pallua
- Former Institute for Computed Tomography-Neuro CT, Medical University of Innsbruck, Anichstraße 35, 6020 Innsbruck, Austria
| | - Bettina Zelger
- Institute of Pathology, Neuropathology, and Molecular Pathology, Medical University of Innsbruck, Muellerstrasse 44, 6020 Innsbruck, Austria
| | - Georg Schäfer
- Institute of Pathology, Neuropathology, and Molecular Pathology, Medical University of Innsbruck, Muellerstrasse 44, 6020 Innsbruck, Austria
| | - Christian Kremser
- Department of Radiology, Medical University of Innsbruck, Anichstraße 35, 6020 Innsbruck, Austria
| | - Gerald Degenhart
- Department of Radiology, Medical University of Innsbruck, Anichstraße 35, 6020 Innsbruck, Austria
| | - Harald Spiegl
- WESTCAM Datentechnik GmbH, Gewerbepark 38, 6068 Mils, Austria
| | - Simon Erler
- WESTCAM Datentechnik GmbH, Gewerbepark 38, 6068 Mils, Austria
| | - David Putzer
- University Hospital for Orthopaedics and Traumatology, 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
| | - Walther Parson
- Institute of Legal Medicine, Medical University of Innsbruck, Muellerstraße 44, 6020 Innsbruck, Austria
- Forensic Science Program, The Pennsylvania State University, State College, PA 16801, USA
| | - Johannes Dominikus Pallua
- Institute of Legal Medicine, Medical University of Innsbruck, Muellerstraße 44, 6020 Innsbruck, Austria
- Institute of Pathology, Neuropathology, and Molecular Pathology, Medical University of Innsbruck, Muellerstrasse 44, 6020 Innsbruck, Austria
- University Hospital for Orthopaedics and Traumatology, Medical University of Innsbruck, Anichstraße 35, 6020 Innsbruck, Austria
- Correspondence:
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Du QX, Zhang S, Long FH, Lu XJ, Wang L, Cao J, Jin QQ, Ren K, Zhang J, Huang P, Sun JH. Combining with lab-on-chip technology and multi-organ fusion strategy to estimate post-mortem interval of rat. Front Med (Lausanne) 2023; 9:1083474. [PMID: 36703889 PMCID: PMC9871555 DOI: 10.3389/fmed.2022.1083474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Accepted: 12/19/2022] [Indexed: 01/12/2023] Open
Abstract
Background The estimation of post-mortem interval (PMI) is one of the most important problems in forensic pathology all the time. Although many classical methods can be used to estimate time since death, accurate and rapid estimation of PMI is still a difficult task in forensic practice, so the estimation of PMI requires a faster, more accurate, and more convenient method. Materials and methods In this study, an experimental method, lab-on-chip, is used to analyze the characterizations of polypeptide fragments of the lung, liver, kidney, and skeletal muscle of rats at defined time points after death (0, 1, 2, 3, 5, 7, 9, 12, 15, 18, 21, 24, 27, and 30 days). Then, machine learning algorithms (base model: LR, SVM, RF, GBDT, and MLPC; ensemble model: stacking, soft voting, and soft-weighted voting) are applied to predict PMI with single organ. Multi-organ fusion strategy is designed to predict PMI based on multiple organs. Then, the ensemble pruning algorithm determines the best combination of multi-organ. Results The kidney is the best single organ for predicting the time of death, and its internal and external accuracy is 0.808 and 0.714, respectively. Multi-organ fusion strategy dramatically improves the performance of PMI estimation, and its internal and external accuracy is 0.962 and 0.893, respectively. Finally, the best organ combination determined by the ensemble pruning algorithm is all organs, such as lung, liver, kidney, and skeletal muscle. Conclusion Lab-on-chip is feasible to detect polypeptide fragments and multi-organ fusion is more accurate than single organ for PMI estimation.
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Affiliation(s)
- Qiu-xiang Du
- Shanghai Key Laboratory of Forensic Medicine, Academy of Forensic Science, Shanghai, China
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, Shanxi, China
| | - Shuai Zhang
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, Shanxi, China
| | - Fei-hao Long
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, Shanxi, China
| | - Xiao-jun Lu
- Criminal Investigation Detachment, Baotou Public Security Bureau, Baotou, Inner Mongolia, China
| | - Liang Wang
- National Center for Liver Cancer, Second Military Medical University, Shanghai, China
| | - Jie Cao
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, Shanxi, China
| | - Qian-qian Jin
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, Shanxi, China
| | - Kang Ren
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, Shanxi, China
| | - Ji Zhang
- Shanghai Key Laboratory of Forensic Medicine, Academy of Forensic Science, Shanghai, China
| | - Ping Huang
- Shanghai Key Laboratory of Forensic Medicine, Academy of Forensic Science, Shanghai, China
| | - Jun-hong Sun
- Shanghai Key Laboratory of Forensic Medicine, Academy of Forensic Science, Shanghai, China
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, Shanxi, China
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Tozzo P, Amico I, Delicati A, Toselli F, Caenazzo L. Post-Mortem Interval and Microbiome Analysis through 16S rRNA Analysis: A Systematic Review. Diagnostics (Basel) 2022; 12:2641. [PMID: 36359484 PMCID: PMC9689864 DOI: 10.3390/diagnostics12112641] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Revised: 10/26/2022] [Accepted: 10/27/2022] [Indexed: 08/12/2023] Open
Abstract
The determination of the Post-Mortem Interval (PMI) is an issue that has always represented a challenge in the field of forensic science. Different innovative approaches, compared to the more traditional ones, have been tried over the years, without succeeding in being validated as successful methods for PMI estimation. In the last two decades, innovations in sequencing technologies have made it possible to generate large volumes of data, allowing all members of a bacterial community to be sequenced. The aim of this manuscript is to provide a review regarding new advances in PMI estimation through cadaveric microbiota identification using 16S rRNA sequencing, in order to correlate specific microbiome profiles obtained from different body sites to PMI. The systematic review was performed according to PRISMA guidelines. For this purpose, 800 studies were identified through database searching (Pubmed). Articles that dealt with PMI estimation in correlation with microbiome composition and contained data about species, body site of sampling, monitoring time and sequencing method were selected and ultimately a total of 25 studies were considered. The selected studies evaluated the contribution of the various body sites to determine PMI, based on microbiome sequencing, in human and animal models. The results of this systematic review highlighted that studies conducted on both animals and humans yielded results that were promising. In order to fully exploit the potential of the microbiome in the estimation of PMI, it would be desirable to identify standardized body sampling sites and specific sampling methods in order to align data obtained by different research groups.
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Affiliation(s)
- Pamela Tozzo
- Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, 35121 Padova, Italy
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