Computational Assessment of Skull Base Osteomyelitis due to Post-Covid Mucormycosis

Abstract

The purpose of this study is to explore colored visualization of grey-scale CT data as a viable method for early detection of skull base degeneration caused by the cerebral progression of Mucormycosis. In addition, the work also aims to assess the pattern of such degeneration from the retrospective data of subjects. CT data of five Mucormycosis patients and five subjects with intact skull bases are used, and grey-scale-based 3D modelling and material characterization of the skull base are performed. Colored contours of Young's modulus over the skull base are generated. The visualized results are corroborated with the help of a numerical comparison of material properties in the different sub-regions of all the skull bases. Both deficiency and degeneration of the bone were visualized, which were primarily confined to the median skull base in all five cases. The observations were corroborated by the comparison of the mean modulus of the median sub-regions with their lateral counterparts (Case #1-5: 84.2%, 72.1%, 58%, 34.7%, and 35%). On the contrary, the material properties were largely uniform in the control group data. The study highlights the aspect of significant silent bone degeneration of the skull base and its effective visualization using material property contours. It elucidates that the medial skull base, which is in proximity to paranasal sinuses is the most vulnerable target for Mucormycosis.