Literature DB >> 28091724

Automatic CT-based finite element model generation for temperature-based death time estimation: feasibility study and sensitivity analysis.

Sebastian Schenkl1, Holger Muggenthaler1, Michael Hubig2, Bodo Erdmann3, Martin Weiser3, Stefan Zachow3, Andreas Heinrich4, Felix Victor Güttler4, Ulf Teichgräber4, Gita Mall1.   

Abstract

Temperature-based death time estimation is based either on simple phenomenological models of corpse cooling or on detailed physical heat transfer models. The latter are much more complex but allow a higher accuracy of death time estimation, as in principle, all relevant cooling mechanisms can be taken into account.Here, a complete workflow for finite element-based cooling simulation is presented. The following steps are demonstrated on a CT phantom: Computer tomography (CT) scan Segmentation of the CT images for thermodynamically relevant features of individual geometries and compilation in a geometric computer-aided design (CAD) model Conversion of the segmentation result into a finite element (FE) simulation model Computation of the model cooling curve (MOD) Calculation of the cooling time (CTE) For the first time in FE-based cooling time estimation, the steps from the CT image over segmentation to FE model generation are performed semi-automatically. The cooling time calculation results are compared to cooling measurements performed on the phantoms under controlled conditions. In this context, the method is validated using a CT phantom. Some of the phantoms' thermodynamic material parameters had to be determined via independent experiments.Moreover, the impact of geometry and material parameter uncertainties on the estimated cooling time is investigated by a sensitivity analysis.

Keywords:  Cooling experiments; Finite element method; Semi-automatic CT segmentation and FE model generation; Sensitivity analysis; Temperature-based death time estimation; Validation

Mesh:

Year:  2017        PMID: 28091724     DOI: 10.1007/s00414-016-1523-0

Source DB:  PubMed          Journal:  Int J Legal Med        ISSN: 0937-9827            Impact factor:   2.686


  16 in total

1.  Estimators of tissue proportions from X-ray CT images.

Authors:  C A Glasbey; C D Robinson
Journal:  Biometrics       Date:  2002-12       Impact factor: 2.571

2.  CT-based geometry analysis and finite element models of the human and ovine bronchial tree.

Authors:  Merryn H Tawhai; Peter Hunter; Juerg Tschirren; Joseph Reinhardt; Geoffrey McLennan; Eric A Hoffman
Journal:  J Appl Physiol (1985)       Date:  2004-08-20

3.  Estimation of time since death by heat-flow Finite-Element model. Part I: method, model, calibration and validation.

Authors:  Gita Mall; Wolfgang Eisenmenger
Journal:  Leg Med (Tokyo)       Date:  2005-01       Impact factor: 1.376

4.  Multi-detector row CT attenuation measurements: assessment of intra- and interscanner variability with an anthropomorphic body CT phantom.

Authors:  Bernard A Birnbaum; Nicole Hindman; Julie Lee; James S Babb
Journal:  Radiology       Date:  2007-01       Impact factor: 11.105

5.  Automated quantification of body fat distribution on volumetric computed tomography.

Authors:  Binsheng Zhao; Jane Colville; John Kalaigian; Sean Curran; Li Jiang; Peter Kijewski; Lawrence H Schwartz
Journal:  J Comput Assist Tomogr       Date:  2006 Sep-Oct       Impact factor: 1.826

6.  Development of an automated 3D segmentation program for volume quantification of body fat distribution using CT.

Authors:  Shunsuke Ohshima; Shuji Yamamoto; Taiki Yamaji; Masahiro Suzuki; Michihiro Mutoh; Motoki Iwasaki; Shizuka Sasazuki; Ken Kotera; Shoichiro Tsugane; Yukio Muramatsu; Noriyuki Moriyama
Journal:  Nihon Hoshasen Gijutsu Gakkai Zasshi       Date:  2008-09-20

7.  A new approach for assigning bone material properties from CT images into finite element models.

Authors:  G Chen; B Schmutz; D Epari; K Rathnayaka; S Ibrahim; M A Schuetz; M J Pearcy
Journal:  J Biomech       Date:  2009-11-25       Impact factor: 2.712

8.  Death time estimation in case work. I. The rectal temperature time of death nomogram.

Authors:  C Henssge
Journal:  Forensic Sci Int       Date:  1988-09       Impact factor: 2.395

9.  Post-mortem limitations of body composition analysis by computed tomography.

Authors:  V Janssens; P Thys; J P Clarys; H Kvis; B Chowdhury; E Zinzen; J Cabri
Journal:  Ergonomics       Date:  1994-01       Impact factor: 2.778

10.  Body fat assessment method using CT images with separation mask algorithm.

Authors:  Young Jae Kim; Seung Hyun Lee; Tae Yun Kim; Jeong Yun Park; Seung Hong Choi; Kwang Gi Kim
Journal:  J Digit Imaging       Date:  2013-04       Impact factor: 4.056

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  5 in total

1.  Fully automatic CT-histogram-based fat estimation in dead bodies.

Authors:  Michael Hubig; Sebastian Schenkl; Holger Muggenthaler; Felix Güttler; Andreas Heinrich; Ulf Teichgräber; Gita Mall
Journal:  Int J Legal Med       Date:  2018-01-15       Impact factor: 2.686

2.  Reconstructing the time since death using noninvasive thermometry and numerical analysis.

Authors:  Leah S Wilk; Richelle J M Hoveling; Gerda J Edelman; Huub J J Hardy; Sebastiaan van Schouwen; Harry van Venrooij; Maurice C G Aalders
Journal:  Sci Adv       Date:  2020-05-29       Impact factor: 14.136

Review 3.  Current state and progress of research on forensic biomechanics in China.

Authors:  Yijiu Chen
Journal:  Forensic Sci Res       Date:  2021-05-04

4.  Next-generation time of death estimation: combining surrogate model-based parameter optimization and numerical thermodynamics.

Authors:  Leah S Wilk; Gerda J Edelman; Maurice C G Aalders
Journal:  R Soc Open Sci       Date:  2022-07-27       Impact factor: 3.653

5.  CT-based thermometry with virtual monoenergetic images by dual-energy of fat, muscle and bone using FBP, iterative and deep learning-based reconstruction.

Authors:  Andreas Heinrich; Sebastian Schenkl; David Buckreus; Felix V Güttler; Ulf K-M Teichgräber
Journal:  Eur Radiol       Date:  2021-07-29       Impact factor: 5.315

  5 in total

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