Comparison of the Visual Scoring Method and Semi-Automatic Image Analysis for Evaluating Staining Intensity of Human Cartilage Sections
DOI:
https://doi.org/10.5566/ias.3171Keywords:
Bern score, cartilage, histology, postmorterm interval, semi-automatic analysis, visual scoring methodAbstract
Accurate estimation of postmortem interval (PMI) is crucial in forensic medicine. The hyaline cartilage, being predominantly composed of a dense extracellular matrix and partly resistant to factors influencing protein degradation, can be utilized for analyzing PMI intervals. Various staining methods are available for cartilage staining for PMI evaluation; however, the conventional visual scoring method for assessing staining intensity is susceptible to evaluator bias. This study compared the visual scoring method with a modified Bern score with semi-automatic image analysis. The cartilage samples were obtained from three cadavers with known time of death. Forty-five histological slices were prepared and stained using Alcian blue, Safranin-O with Fast green, Safranin-O without Fast green, Masson trichrome, and Sirius red. Ten evaluators visually scored each sample on a scale of 0 to 3. A semi-automatic analysis was conducted on the same images using the deconvolution plugin of the ImageJ software. Linear regression was used to assess the correlation between the mean grey value and the mean Bern score from all evaluators. The results showed strong correlations across all evaluated staining techniques, with Masson trichrome staining exhibiting the highest correlation. Accordingly, semi-automatic image analysis can be a suitable replacement for the visual scoring method, particularly when no procedural artifacts are present.
References
Alibegović, Armin. 2014. “Cartilage: A New Parameter for the Determination of the Postmortem Interval?” Journal of Forensic and Legal Medicine 27 (October): 39–45. https://doi.org/10.1016/j.jflm.2014.08.005.
Alibegović, Armin, Rok Blagus, and Inigo Zubiavrre Martinez. 2020. “Safranin O without Fast Green Is the Best Staining Method for Testing the Degradation of Macromolecules in a Cartilage Extracellular Matrix for the Determination of the Postmortem Interval.” Forensic Science, Medicine, and Pathology 16 (2): 252–58. https://doi.org/10.1007/s12024-019-00208-0.
Chang, Lou-Ren, Geoffrey Marston, and Andrew Martin. 2024. Anatomy, Cartilage.
Choi, Kyoung-Min, Angela Zissler, Eunjung Kim, Bianca Ehrenfellner, Eunji Cho, Se-in Lee, Peter Steinbacher, et al. 2019. “Postmortem Proteomics to Discover Biomarkers for Forensic PMI Estimation.” International Journal of Legal Medicine 133 (3): 899–908. https://doi.org/10.1007/s00414-019-02011-6.
Dell’Aquila, M, A De Matteis, A Scatena, A Costantino, M C Camporeale, and A De Filippis. 2021. “Estimation of the Time of Death: Where We Are Now?” La Clinica Terapeutica 172 (2): 109–12. https://doi.org/10.7417/CT.2021.2294.
Ehrenfellner, Bianca, Angela Zissler, Peter Steinbacher, Fabio C. Monticelli, and Stefan Pittner. 2017. “Are Animal Models Predictive for Human Postmortem Muscle Protein Degradation?” International Journal of Legal Medicine 131 (6): 1615–21. https://doi.org/10.1007/s00414-017-1643-1.
Hayman, Jarvis, and Marc Oxenham. 2016. “Supravital Reactions in the Estimation of the Time Since Death (TSD).” In Human Body Decomposition, 1–12. Elsevier. https://doi.org/10.1016/B978-0-12-803691-4.00001-7.
Madea, Burkhard, Christoph Kreuser, and Sibylle Banaschak. 2001. “Postmortem Biochemical Examination of Synovial Fluid — a Preliminary Study.” Forensic Science International 118 (1): 29–35. https://doi.org/10.1016/S0379-0738(00)00372-8.
Pigaiani, Nicola, Anna Bertaso, Elio Franco De Palo, Federica Bortolotti, and Franco Tagliaro. 2020. “Vitreous Humor Endogenous Compounds Analysis for Post-Mortem Forensic Investigation.” Forensic Science International 310 (May): 110235. https://doi.org/10.1016/j.forsciint.2020.110235.
Pittner, Stefan, Veronika Merold, Sven Anders, Larissa Lohner, Jens Amendt, Miriam Klinger, Roland Hausmann, et al. 2022. “A Standard Protocol for the Analysis of Postmortem Muscle Protein Degradation: Process Optimization and Considerations for the Application in Forensic PMI Estimation.” International Journal of Legal Medicine 136 (6): 1913–23. https://doi.org/10.1007/s00414-022-02849-3.
Rigueur, Diana, and Karen M. Lyons. 2014. “Whole-Mount Skeletal Staining.” In , 113–21. https://doi.org/10.1007/978-1-62703-989-5_9.
Rizzardi, Anthony E, Arthur T Johnson, Rachel Isaksson Vogel, Stefan E Pambuccian, Jonathan Henriksen, Amy Pn Skubitz, Gregory J Metzger, and Stephen C Schmechel. 2012. “Quantitative Comparison of Immunohistochemical Staining Measured by Digital Image Analysis versus Pathologist Visual Scoring.” http://www.diagnosticpathology.org/content/7/1/42.
Rogers, Christopher J., Kirsty Clark, Barbara J. Hodson, Michael P. Whitehead, Raul Sutton, and Wera M. Schmerer. 2011. “Postmortem Degradation of Porcine Articular Cartilage.” Journal of Forensic and Legal Medicine 18 (2): 52–56. https://doi.org/10.1016/j.jflm.2010.11.006.
Ruifrok, Arnout C, and Dennis A Johnston. 2001. “Quantification of Histochemical Staining by Color Deconvolution.” Anal Quant Cytol Histol. Vol. 23.
Sacco, Matteo Antonio, Fabrizio Cordasco, Carmen Scalise, Pietrantonio Ricci, and Isabella Aquila. 2022. “Systematic Review on Post-Mortem Protein Alterations: Analysis of Experimental Models and Evaluation of Potential Biomarkers of Time of Death.” Diagnostics 12 (6): 1490. https://doi.org/10.3390/diagnostics12061490.
Schindelin, Johannes, Ignacio Arganda-Carreras, Erwin Frise, Verena Kaynig, Mark Longair, Tobias Pietzsch, Stephan Preibisch, et al. 2012. “Fiji: An Open-Source Platform for Biological-Image Analysis.” Nature Methods. https://doi.org/10.1038/nmeth.2019.
Shrestha, Rijen, Tanuj Kanchan, and Kewal Krishan. 2024. Methods of Estimation of Time Since Death.
Tomsia, Marcin, Julia Cieśla, Joanna Pilch-Kowalczyk, Przemysław Banaszek, and Elżbieta Chełmecka. 2022. “Cartilage Tissue in Forensic Science—State of the Art and Future Research Directions.” Processes 10 (11): 2456. https://doi.org/10.3390/pr10112456.
Wei, Wang, Qi Michu, Dong Wenjuan, Wen Jianrong, Han Zhibing, Yang Ming, Jin Bo, and Lin Xia. 2020. “Histological Changes in Human Skin 32 Days after Death and the Potential Forensic Significance.” Scientific Reports 10 (1): 18753. https://doi.org/10.1038/s41598-020-76040-2.
Zhang, Youyou, Liang Liu, and Liang Ren. 2020. “Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) Determination of Cantharidin in Biological Specimens and Application to Postmortem Interval Estimation in Cantharidin Poisoning.” Scientific Reports 10 (1): 10438. https://doi.org/10.1038/s41598-020-67278-x.
Zissler, Angela, Walter Stoiber, Peter Steinbacher, Janine Geissenberger, Fabio C. Monticelli, and Stefan Pittner. 2020. “Postmortem Protein Degradation as a Tool to Estimate the PMI: A Systematic Review.” Diagnostics 10 (12): 1014. https://doi.org/10.3390/diagnostics10121014.
Zupančič, Barbara, Chiedozie Kenneth Ugwoke, Mohamed Elwy Abdelhamed Abdelmonaem, Armin Alibegović, Erika Cvetko, Jože Grdadolnik, Anja Šerbec, and Nejc Umek. 2023. “Exploration of Macromolecular Phenotype of Human Skeletal Muscle in Diabetes Using Infrared Spectroscopy.” Frontiers in Endocrinology 14 (December). https://doi.org/10.3389/fendo.2023.1308373.
Zupančič, Barbara, Nejc Umek, Chiedozie Kenneth Ugwoke, Erika Cvetko, Simon Horvat, and Jože Grdadolnik. 2022. “Application of FTIR Spectroscopy to Detect Changes in Skeletal Muscle Composition Due to Obesity with Insulin Resistance and STZ-Induced Diabetes.” International Journal of Molecular Sciences 23 (20): 12498. https://doi.org/10.3390/ijms232012498.
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Copyright (c) 2024 Armin Alibegović, Nejc Umek, Luka Pušnik, Inigo Zubiavrre Martinez
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