Skip to main content
SpringerLink
Log in

An evaluation of the objectivity and reproducibility of shear wave elastography in estimating the post-mortem interval: a tissue biomechanical perspective

  • Original Article
  • Published:
International Journal of Legal Medicine Aims and scope Submit manuscript

Abstract

Cadaveric rigidity—also referred to as rigor mortis—is a valuable source of information for estimating the time of death, which is a fundamental and challenging task in forensic sciences. Despite its relevance, assessing the level of cadaveric rigidity still relies on qualitative and often subjective observations, and the development of a more quantitative approach is highly demanded. In this context, ultrasound shear wave elastography (US SWE) appears to be a particularly well-suited technique for grading cadaveric rigidity, as it allows non-invasive quantification of muscle stiffness in terms of Young’s modulus (E), which is a widely used parameter in tissue biomechanics. In this pilot study, we measured, for the first time in the literature, changes in the mechanical response of muscular tissues from 0 to 60 h post-mortem (hpm) using SWE, with the aim of investigating its applicability to forensic practice. For this purpose, 26 corpses were included in the study, and the muscle mechanical response was measured at random times in the 0–60 hpm range. Despite the preliminary nature of this study, our data indicate a promising role of SWE in the quantitative determination of cadaveric rigidity, which is still currently based on qualitative and semiquantitative methods. A more in-depth study is required to confirm SWE applicability in this field in order to overcome some of the inherent limitations of the present work, such as the rather low number of cases and the non-systematic approach of the measurements.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Abbreviations

PMI:

Post-mortem interval

SWE:

Shear wave elastography

hpm:

Hours post-mortem

References

  1. Madea B (2016) Methods for determining time of death. Forensic Sci Med Pathol 12(4):451–485

    Article  PubMed  Google Scholar 

  2. Henssge C, Madea B (2004) Estimation of the time since death in the early post-mortem period. Forensic Sci Int 144(2–3):167–175

    Article  CAS  PubMed  Google Scholar 

  3. Rosa MF, Scano P, Noto A, Nioi M, Sanna R, Paribello F, De-Giorgio F, Locci E, d'Aloja E (2015) Monitoring the modifications of the vitreous humor metabolite profile after death: an animal model. Biomed Res Int:627201–627207. https://doi.org/10.1155/2015/627201

  4. Locci E, Scano P, Rosa MF, Nioi M, Noto A, Atzori L, Demontis R, De-Giorgio F, d’Aloja E A metabolomic approach to animal vitreous humor topographical composition: a pilot study. PLoS One 9(5):e97773. https://doi.org/10.1371/journal.pone.0097773 eCollection 2014

  5. Locci E, Stocchero M, Noto A, Chighine A, Natali L, Napoli PE, Caria R, De-Giorgio F, Nioi M, d'Aloja E (2019) A (1)H NMR metabolomic approach for the estimation of the time since death using aqueous humour: an animal model. Metabolomics. 15(5):76. https://doi.org/10.1007/s11306-019-1533-2.6

    Article  PubMed  Google Scholar 

  6. Ferreira PG, Muñoz-Aguirre M, Reverter F, Sá Godinho CP, Sousa A, Amadoz A, Sodaei R, Hidalgo MR, Pervouchine D, Carbonell-Caballero J, Nurtdinov R, Breschi A, Amador R, Oliveira P, Çubuk C, Curado J, Aguet F, Oliveira C, Dopazo J, Sammeth M, Ardlie KG, Guigó R (2018) The effects of death and post-mortem cold ischemia on human tissue transcriptomes. Nat Commun 9(1):490. https://doi.org/10.1038/s41467-017-02772-x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Zhu Y, Wang L, Yin Y, Yang E (2017) Systematic analysis of gene expression patterns associated with postmortem interval in human tissues. Sci Rep 7(1):5435. https://doi.org/10.1038/s41598-017-05882-0

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Nioi M, Napoli PE, Demontis R, Locci E, Fossarello M, d'Aloja E (2018) Morphological analysis of corneal findings modifications after death: a preliminary OCT study on an animal model. Exp Eye Res 169:20–27. https://doi.org/10.1016/j.exer.2018.01.013

    Article  CAS  PubMed  Google Scholar 

  9. Pittner S, Ehrenfellner B, Monticelli FC, Zissler A, Sänger AM, Stoiber W, Steinbacher P (2016) Postmortem muscle protein degradation in humans as a tool for PMI delimitation. Int J Legal Med 130(6):1547–1555

    Article  PubMed  PubMed Central  Google Scholar 

  10. Vain A, Kauppila R, Humal LH, Vuori E (1992) Grading rigor mortis with myotonometry--a new possibility to estimate time of death. Forensic Sci Int 56(2):147–150

    Article  CAS  PubMed  Google Scholar 

  11. Vain A, Kauppila R, Vuori E (1996) Estimation of the breaking of rigor mortis by myotonometry. Forensic Sci Int 79(2):155–161

    Article  CAS  PubMed  Google Scholar 

  12. Martins PA, Ferreira F, Natal Jorge R, Parente M, Santos A (2015) Necromechanics: death-induced changes in the mechanical properties of human tissues. Proc Inst Mech Eng H 229(5):343–349. https://doi.org/10.1177/0954411915581409

    Article  PubMed  Google Scholar 

  13. De-Giorgio F, Nardini M, Foti F, Minelli E, Papi M, d’Aloja E, Pascali VL, De Spirito M, Ciasca G (2019) A novel method for post-mortem interval estimation based on tissue nano-mechanics. Int J Legal Med 133(4):1133–1139. https://doi.org/10.1007/s00414-019-02034-z

    Article  PubMed  Google Scholar 

  14. Tian M, Li Y, Liu W, Jin L, Jiang X, Wang X, Ding Z, Peng Y, Zhou J, Fan J, Cao Y, Wang W, Shi Y (2015) The nanomechanical signature of liver cancer tissues and its molecular origin. Nanoscale 7(30):12998–13010. https://doi.org/10.1039/c5nr02192h

    Article  CAS  PubMed  Google Scholar 

  15. Suresh S (2007) Biomechanics and biophysics of cancer cells. Acta Biomater 3(4):413–438

    Article  PubMed  PubMed Central  Google Scholar 

  16. Plodinec M, Loparic M, Monnier CA, Obermann EC, Zanetti-Dallenbach R, Oertle P, Hyotyla JT, Aebi U, Bentires-Alj M, Lim RY, Schoenenberger CA (2012) The nanomechanical signature of breast cancer. Nat Nanotechnol 7(11):757–765. https://doi.org/10.1038/nnano.2012.167

    Article  CAS  PubMed  Google Scholar 

  17. Minelli E, Sassun TE, Papi M, Palmieri V, Palermo F, Perini G, Antonelli M, Gianno F, Maulucci G, Ciasca G, De Spirito M (2018) Nanoscale mechanics of brain abscess: an atomic force microscopy study. Micron. 113:34–40. https://doi.org/10.1016/j.micron.2018.06.012

    Article  PubMed  Google Scholar 

  18. Minelli E, Ciasca G, Sassun TE, Antonelli M, Palmieri V, Papi M, Maulucci G, Santoro A, Giangaspero F, Delfini R, Campi G, De Spirito M (2017) A fully automated neural network analysis of AFM force-distance curves for cancer tissue diagnosis. Appl Ohys Lett. https://doi.org/10.10603/1.4996300

  19. Kuznetsova TG, Starodubtseva MN, Yegorenkov NI, Chizhik SA, Zhdanov RI (2007) Atomic force microscopy probing of cell elasticity. Micron. 38(8):824–833

    Article  CAS  PubMed  Google Scholar 

  20. Ciasca G, Papi M, Di Claudio S, Chiarpotto M, Palmieri V, Maulucci G, Nocca G, Rossi C, De Spirito M (2015) Mapping viscoelastic properties of healthy and pathological red blood cells at the nanoscale level. Nanoscale. 7(40):17030–17037. https://doi.org/10.1039/c5nr03145a

    Article  CAS  PubMed  Google Scholar 

  21. Ciasca G, Papi M, Minelli E, Palmieri V, De Spirito M (2016) Changes in cellular mechanical properties during onset or progression of colorectal cancer. World J Gastroenterol 22(32):7203–7214. https://doi.org/10.3748/wjg.v22.i32.7203

    Article  PubMed  PubMed Central  Google Scholar 

  22. Perini G, Ciasca G, Minelli E, Papi M, Palmieri V, Maulucci G, Nardini M, Latina V, Corsetti V, Florenzano F, Calissano P, De Spirito M, Amadoro G (2019) Dynamic structural determinants underlie the neurotoxicity of the N-terminal tau 26-44 peptide in Alzheimer’s disease and other human tauopathies. Int J Biol Macromol 141:278–289. https://doi.org/10.1016/j.ijbiomac.2019.08.220

    Article  CAS  PubMed  Google Scholar 

  23. Ciasca G, Pagliei V, Minelli E, Palermo F, Nardini M, Pastore V, Papi M, Caporossi A, De Spirito M, Minnella AM (2019) Nanomechanical mapping helps explain differences in outcomes of eye microsurgery: a comparative study of macular pathologies. PLoS One 14(8):e0220571. https://doi.org/10.1371/journal.pone.0220571

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Ciasca G, Sassun TE, Minelli E, Antonelli M, Papi M, Santoro A, Giangaspero F, Delfini R, De Spirito M (2016) Nano-mechanical signature of brain tumours. Nanoscale. 8(47):19629–19643

    Article  CAS  PubMed  Google Scholar 

  25. Ciasca G, Mazzini A, Sassun TE, Nardini M, Minelli E, Papi M, Palmieri V, de Spirito M (2019) Efficient spatial sampling for AFM-based cancer diagnostics: a comparison between neural networks and conventional data analysis. Condens Matter 4. https://doi.org/10.3390/condmat4020058

  26. (2013) Introductory biomechanics: from cells to organisms. Choice Rev Online. https://doi.org/10.5860/choice.45-1476

  27. Choi YJ, Lee JH, Baek JH (2015) Ultrasound elastography for evaluation of cervical lymph nodes. Ultrasonography 34(3):157–164. https://doi.org/10.14366/usg.15007

    Article  PubMed  PubMed Central  Google Scholar 

  28. Domenichini R, Pialat JB, Podda A, Aubry S (2017) Ultrasound elastography in tendon pathology: state of the art. Skelet Radiol 46(12):1643–1655. https://doi.org/10.1007/s00256-017-2726-2 Review

    Article  Google Scholar 

  29. Felicani C, De Molo C, Stefanescu H, Conti F, Mazzotta E, Gabusi V, Nardi E, Morselli-Labate AM, Andreone P, Serra C (2018) Point quantification elastography in the evaluation of liver elasticity in healthy volunteers: a reliability study based on operator expertise. J Ultrasound 21(2):89–98. https://doi.org/10.1007/s40477-018-0300-y

    Article  PubMed  PubMed Central  Google Scholar 

  30. Piscaglia F, Salvatore V, Mulazzani L, Cantisani V, Schiavone C (2016) Ultrasound shear wave elastography for liver disease. A critical appraisal of the many actors on the stage. Ultraschall Med 37(1):1–5. https://doi.org/10.1055/s-0035-1567037

    Article  CAS  PubMed  Google Scholar 

  31. Correas JM, Drakonakis E, Isidori AM, Hélénon O, Pozza C, Cantisani V, Di Leo N, Maghella F, Rubini A, Drudi FM, D'ambrosio F (2014) Reprint of “Update on ultrasound elastography: miscellanea. Prostate, testicle, musculo-skeletal”. Eur J Radiol 83(3):442–449. https://doi.org/10.1016/j.ejrad.2014.01.018

    Article  CAS  PubMed  Google Scholar 

  32. Caliskan E, Ozturk M, Bayramoglu Z, Comert RG, Adaletli I (2018) Evaluation of parotid glands in healthy children and adolescents using shear wave elastography and superb microvascular imaging. Radiol Med 123(9):710–718. https://doi.org/10.1007/s11547-018-0897-0

    Article  PubMed  Google Scholar 

  33. Vola EA, Albano M, Di Luise C, Servodidio V, Sansone M, Russo S, Corrado B, Servodio Iammarrone C, Caprio MG, Vallone G (2018) Use of ultrasound shear wave to measure muscle stiffness in children with cerebral palsy. J Ultrasound 21(3):241–247. https://doi.org/10.1007/s40477-018-0313-6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Lee SS, Gaebler-Spira D, Zhang LQ, Rymer WZ, Steele KM (2016) Use of shear wave ultrasound elastography to quantify muscle properties in cerebral palsy. Clin Biomech (Bristol, Avon) 31:20–28. https://doi.org/10.1016/j.clinbiomech.2015.10.006

    Article  Google Scholar 

  35. Pichiecchio A, Alessandrino F, Bortolotto C, Cerica A, Rosti C, Raciti MV, Rossi M, Berardinelli A, Baranello G, Bastianello S, Calliada F (2018) Muscle ultrasound elastography and MRI in preschool children with Duchenne muscular dystrophy. Neuromuscul Disord 28(6):476–483. https://doi.org/10.1016/j.nmd.2018.02.007

    Article  PubMed  Google Scholar 

  36. Bortolotto C, Lungarotti L, Fiorina I, Zacchino M, Draghi F, Calliada F (2017) Influence of subjects’ characteristics and technical variables on muscle stiffness measured by shear wave elastosonography. J Ultrasound 20(2):139–146. https://doi.org/10.1007/s40477-017-0242-9 eCollection 2017 Jun

    Article  PubMed  PubMed Central  Google Scholar 

  37. Bortolotto C, Turpini E, Felisaz P, Fresilli D, Fiorina I, Raciti MV, Belloni E, Bottinelli O, Cantisani V, Calliada F (2017) Median nerve evaluation by shear wave elastosonography: impact of “bone-proximity” hardening artifacts and inter-observer agreement. J Ultrasound 20(4):293–299. https://doi.org/10.1007/s40477-017-0267-0 eCollection 2017 Dec

    Article  PubMed  PubMed Central  Google Scholar 

  38. Lucidarme D, Foucher J, Le Bail B, Vergniol J, Castera L, Duburque C, Forzy G, Filoche B, Couzigou P, de Lédinghen V (2009) Factors of accuracy of transient elastography (fibroscan) for the diagnosis of liver fibrosis in chronic hepatitis C. Hepatology. 49(4):1083–1089. https://doi.org/10.1002/hep.22748

    Article  PubMed  Google Scholar 

  39. Choi SY, Jeong WK, Kim Y, Kim J, Kim TY, Sohn JH (2014) Shear-wave elastography: a noninvasive tool for monitoring changing hepatic venous pressure gradients in patients with cirrhosis. Radiology. 273(3):917–926. https://doi.org/10.1148/radiol.14140008

    Article  PubMed  Google Scholar 

  40. Koo TK, Li MY (2016) A guideline of selecting and reporting intraclass correlation coefficients for reliability research. J Chiropr Med 15:155–163. https://doi.org/10.1016/j.jcm.2016.02.012

    Article  PubMed  PubMed Central  Google Scholar 

  41. Team RDC, R Development Core Team R (2016) R: a language and environment for statistical computing. R Found Stat Comput. https://doi.org/10.1007/978-3-540-74686-7

Download references

Author information

Author notes

  1. Fabio De-Giorgio and Gabriele Ciasca contributed equally to this work.

Authors and Affiliations

  1. Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy

    Fabio De-Giorgio, Gabriele Ciasca & Vincenzo L. Pascali

  2. Department of Health Care Surveillance and Bioetics, Section of Legal Medicine, Università Cattolica del Sacro Cuore, Rome, Italy

    Fabio De-Giorgio & Vincenzo L. Pascali

  3. Dipartimento di Neuroscienze, Sezione di Fisica, Università Cattolica del Sacro Cuore, Rome, Italy

    Gabriele Ciasca & Marco De Spirito

  4. Unit of Radiology, Mater Olbia Hospital, SS, Olbia, Italy

    Ronel D’Amico, Pietro Trombatore, Anna D’Angelo, Pierluigi Rinaldi & Cesare Colosimo

  5. Department of Biomedicine and Prevention, University of Rome “Tor Vergata”, Rome, Italy

    Filippo Milano

  6. Department of Medical Sciences and Public Health, Section of Legal Medicine, University of Cagliari, Cagliari, Italy

    Emanuela Locci & Ernesto d’Aloja

Authors
  1. Fabio De-Giorgio
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gabriele Ciasca
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ronel D’Amico
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Pietro Trombatore
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Anna D’Angelo
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Pierluigi Rinaldi
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Filippo Milano
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Emanuela Locci
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Marco De Spirito
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Ernesto d’Aloja
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Cesare Colosimo
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Vincenzo L. Pascali
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Fabio De-Giorgio.

Ethics declarations

Ethics approval

The study was approved by the Institutional Research Ethics Committee (N. 0027029/20).

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Figure S1

QQplot of the ten consecutive measurements carried out by operator 1 at each PMI on each corpse. For the sake of clarity, the corpse and the time are indicated in the grey band. As an example, case26-5PMI indicates the measure carried out by the operator on case 26, 5 hours post mortem (PDF 93 kb)

Figure S2

QQplot of the ten consecutive measurements carried out by operator 2 at each PMI on each corpse. (PDF 88 kb)

Figure S3

box plot analysis of the ten measurements that were acquired by the US spectrometer for each data point. Data are arranged in a matrix of plots. In each plot, we show the single measurements that were performed by the US spectrometer when used by operator 1 (yellow) and operator 2 (cyan). The result of t-tests for unpaired samples between the two operators is shown within the text. (PDF 185 kb)

Figure S4

Young’s modulus (E) as a function of age at the different rigor-mortis stages. A linear curve is fitted to the data, and the corresponding regression equation is reported in the plot inset. (PDF 31 kb)

Figure S5

Time evolution of Young’s modulus (E) of the gluteus muscle from 0 to 60 hpm for the analysed cadavers measured by the two operators, together with the corresponding mean difference curve. (PDF 117 kb)

Figure S6

comparison between BMI-adjusted and BMI- & Age-adjusted E values as a function of the PMI (PDF 64 kb)

Figure S7

figure 5a recoloured to highlight the gender rather than the subject. (PDF 21 kb)

Table S1

results of the Shapiro-Wilk (SW) test for normality of the ten consecutive measurements carried out by operator 1 (left) and 2 (right) at each PMI on each corpse. For the sake of clarity, the corpse and the time are indicated with the same notation used in figure S1 and S2. (DOCX 18 kb)

Table S2

Summary of all ten measures performed by each operator at each time point. (PDF 300 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

De-Giorgio, F., Ciasca, G., D’Amico, R. et al. An evaluation of the objectivity and reproducibility of shear wave elastography in estimating the post-mortem interval: a tissue biomechanical perspective. Int J Legal Med 134, 1939–1948 (2020). https://doi.org/10.1007/s00414-020-02370-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00414-020-02370-5

Keywords

Search

Navigation