A Multi-Parametric Investigation on Waterlogged Wood Using a Magnetic Resonance Imaging Clinical Scanner

Longo S., Egizi F., Stagno V., Di Trani M. G., Marchelletta G., Gili T., Fazio E., Favero G., Capuani S.

magnetic resonance imaging; waterlogged wood; archaeological wood; multiparametric MRI; CT; 3D rendering; relaxation times 

In cultural heritage conservation science, moisture content (MC) is an essential factor to determine. At the same time, it is essential to choose non-destructive and non-invasive approaches for more sustainable investigations and make them safe for the environment and the sample. The question addressed in this work concerns the possibility and the opportunity to investigate waterlogged wood by using nuclear magnetic resonance imaging (MRI) clinical scanners to carry out non-destructive volumetric diagnostics. In this study, MRI, the most important non-invasive medical imaging technique for human tissue analysis, was applied to study archaeological waterlogged wood samples. This type of archaeological material has a very high moisture content (400%-800%), thus, it is an ideal investigative subject for MRI which detects water molecules inside matter. By following this methodology, it was possible to obtain information about water content and conservation status through a T1, T2, and T2* weighted image analysis, without any sampling or handling, and the samples were directly scanned in the water where they were stored. Furthermore, it permited processing 3D reconstruction, which could be an innovative tool for the digitalization of marine archaeological collections. In this work, 16 modern species of wood and a waterlogged archaeological wood sample were studied and investigated using a clinical NMR scanner operating at 3T. The results were compared with X-ray computed tomography (CT) images, as they had already been used for dendrochronology. The comparison highlights the similar, different, and complementary information about moisture content and conservation status in an all-in-one methodology obtainable from both MRI and CT techniques.

Source: Forests 14 (2023): 276-1–276-22. doi:10.3390/f14020276

Publisher: MDPI, Basel

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