The number of the Asbestos Bodies (AB), i.e. asbestos that developed an iron-protein coating during its permanence in biological tissues, is one of the most accessible markers of asbestos exposure in individuals. The approaches developed to perform AB count in biological tissues are based on the manual examination of tissue digests or histological sections by means of light or electron microscopies. Although these approaches are well established and relatively accessible, manual examination is time-consuming and can be reader-dependent. Besides, approximations are applied because of the limitations of 2D readings and to speed up manual counts. In addition, sample preparation using tissue digests require an amount of tissue that can only be obtained by invasive surgery or post-mortem sampling. In this paper, we propose a new approach to AB counting based on non-destructive 3D imaging, which has the potential to overcome most of the limitations of conventional approaches. This method allows automating the AB count and determining their morphometry distribution in bulk tissue samples (ideally non-invasive needle biopsies), with minimal sample preparation and avoiding approximations. Although the results are promising, additional testing on a larger number of AB-containing biological samples would be required to fully validate the method.
Asbestos bodies count and morphometry in bulk lung tissue samples by non-invasive X-ray micro-tomography
Brun F.;
2021-01-01
Abstract
The number of the Asbestos Bodies (AB), i.e. asbestos that developed an iron-protein coating during its permanence in biological tissues, is one of the most accessible markers of asbestos exposure in individuals. The approaches developed to perform AB count in biological tissues are based on the manual examination of tissue digests or histological sections by means of light or electron microscopies. Although these approaches are well established and relatively accessible, manual examination is time-consuming and can be reader-dependent. Besides, approximations are applied because of the limitations of 2D readings and to speed up manual counts. In addition, sample preparation using tissue digests require an amount of tissue that can only be obtained by invasive surgery or post-mortem sampling. In this paper, we propose a new approach to AB counting based on non-destructive 3D imaging, which has the potential to overcome most of the limitations of conventional approaches. This method allows automating the AB count and determining their morphometry distribution in bulk tissue samples (ideally non-invasive needle biopsies), with minimal sample preparation and avoiding approximations. Although the results are promising, additional testing on a larger number of AB-containing biological samples would be required to fully validate the method.File | Dimensione | Formato | |
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