Investigation of subtle Lisfranc injuries using weight-bearing computed tomography




Lisfranc injury, Acquired/diagnostic imaging, midfoot pain, computed tomography


Introduction: Lisfranc ligamentous injuries are common yet remain a diagnostic challenge. Automated analysis of weight-bearing
computed tomography (WBCT) images has been investigated to diagnose various pathologies. However, it has not been studied for
Lisfranc ligament injuries. The objective of the study was to examine whether automated WBCT analysis could demonstrate diagnostic
utility for these injuries. Methods: Serial sectioning of Lisfranc complex ligaments was conducted on 24 cadaveric limbs to simulate Lisfranc injuries. WBCT images were collected at each dissection condition under three loading conditions. Images were automatically segmented, and automated measures of specific angles and distances in the midfoot were calculated using digitally reconstructed radiographs. These were analyzed using repeated measures ANOVA and paired T-tests to identify significant differences between dissections at each loading condition. Results: Overall, minimal differences between dissection conditions were observed in automatically generated measures. Differences in axial angles of the metatarsals in severe dissections were observed, and there were fewer differences in angular measures across dissection conditions in fully loaded than unloaded conditions. Conclusions: Automated analysis of WBCT images may indicate severe Lisfranc ligamentous injury but is insufficient to diagnose ligament injuries without full capsule disruption. This lack of injury markers may be due to the imaging conditions, automated analysis, or biomechanics of Lisfranc injuries. More alignment differences were seen under unloaded conditions, suggesting that weight-bearing imaging may not be appropriate for this injury. Overall, automated analysis shows only minimal changes in alignment measures, and additional study is necessary to improve diagnostic tools for Lisfranc injuries. Evidence Level V; Mechanism-based reasoning.




How to Cite

Elicegui, S., Requist, M., Rogers, T., Lisonbee, R., Sripanich, Y., Krähenbühl, N., & Lenz, A. (2024). Investigation of subtle Lisfranc injuries using weight-bearing computed tomography. Journal of the Foot & Ankle, 18(1), 101–107.