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Postmortem lung features in drowning cases on computed tomography

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Abstract

Purpose

We sought to compare postmortem chest computed tomography (CT) features of drowning cases with autopsy findings, and to classify these features.

Materials and method

We performed a retrospective analysis of high-resolution and multi-planar reconstruction chest CT images of drowning in 92 adults (54 men, 38 women; mean age 65.4 years) scanned before forensic autopsy. The average lung CT number was calculated from whole-lung images reconstructed on a 3D workstation. The statistically significant differences of CT numbers were assessed with an alpha level of 0.05.

Results

Postmortem chest CT image patterns were classified into six types: the two main types were ground-glass opacities with thickened pulmonary interstitium (n = 31), and a centrilobular distribution of ill-defined nodules along the airways (n = 38). Some cases were mixed type (n = 10). There were significant differences in CT numbers between each type. The remaining three types were consolidation (n = 5), emphysema and/or fibrosis (n = 4), and unclassifiable (n = 4).

Conclusion

Postmortem CT images of drowning cases can be classified into three major types with a few exceptions.

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Conflict of interest

No potential conflicts of interest were disclosed.

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Authors and Affiliations

  1. Department of Diagnostic Image Analysis, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Sendai, 980-8575, Japan

    Akihito Usui & Haruo Saito

  2. Department of Clinical Imaging, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Sendai, 980-8575, Japan

    Yusuke Kawasumi

  3. Department of Forensic Medicine, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Sendai, 980-8575, Japan

    Masato Funayama

Authors
  1. Akihito Usui
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  2. Yusuke Kawasumi
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  3. Masato Funayama
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  4. Haruo Saito
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Corresponding author

Correspondence to Akihito Usui.

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Usui, A., Kawasumi, Y., Funayama, M. et al. Postmortem lung features in drowning cases on computed tomography. Jpn J Radiol 32, 414–420 (2014). https://doi.org/10.1007/s11604-014-0326-9

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  • DOI: https://doi.org/10.1007/s11604-014-0326-9

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