Retrospective cohort study of three-wall orbital resection for treatment of endocrine orbitopathy using 3D tomographic data and biomechanical modeling
2019
Abstract Background Surgical treatment of endocrine orbitopathy can be performed by way of resecting orbital walls, which effectively releases superfluous tissue from the surgically enlarged orbital space allowing the eyeballs to move back. Existing approaches aim to select an optimal surgical strategy based on statistical correlations between the extent of the surgical procedure and the resulting bulbus displacement but do not provide an individual surgery plan or predict surgery outcome. Methods In this retrospective study, we performed a quantitative analysis of pre- and post-surgery 3D tomographic data of six patients and applied explorative biomechanical modeling of orbital mechanics to dissect factors influencing patient-specific outcome. Findings Our experimental results showed a large variability of the backward eyeball displacement in dependency on the amount of orbital volume flow, which could partially be described by computational simulation. Our detailed analysis revealed that patients with regular fat tissue show a good correlation between bulbus displacement and relative volume of decompressed tissue, which, in turn, correlates with decrease in hydrostatic pressure. In contrast, patients with fibrotic tissue exhibit significantly reduced and computationally less predictable eyeball translation in response to surgical tissue decompression. Interpretation Based on the results of this study we see a great potential for quantitative planning of surgical exophthalmos treatment using 3D biomechanical modeling. Conventional approaches to planning of soft tissue interventions consider, however, only the patient’s 3D anatomy and widely disregard individual tissue properties. Further investigations are required to establish reliable procedures for assessment of individual tissue properties and incorporating them into patient-specific models of orbital mechanics.
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