ABSTRACT
BACKGROUND: The precise mechanism of bitemporal hemianopia is still not clear. Our study investigated the mechanism of bitemporal hemianopia by studying the biomechanics of chiasmal compression caused by a pituitary tumor growing below the optic chiasm. METHODS: Chiasmal compression and nerve fiber interaction in the chiasm were simulated numerically using finite element modeling software. Detailed mechanical strain distributions in the chiasm were obtained to help understand the mechanical behavior of the optic chiasm. Nerve fiber models were built to determine the relative difference in strain experienced by crossed and uncrossed nerve fibers. RESULTS: The central aspect of the chiasm always experienced higher strains than the peripheral aspect when the chiasm was loaded centrally from beneath. Strains in the nasal (crossed) nerve fibers were dramatically higher than in temporal (uncrossed) nerve fibers. CONCLUSIONS: The simulation results of the macroscopic chiasmal model are in agreement with the limited experimental results available, suggesting that the finite element method is an appropriate tool for analyzing chiasmal compression. Although the microscopic nerve fiber model was unvalidated because of lack of experimental data, it provided useful insights into a possible mechanism of bitemporal hemianopia. Specifically, it showed that the strain difference between crossed and uncrossed nerve fibers may account for the selective nerve damage, which gives rise to bitemporal hemianopia.
Subject(s)
Models, Neurological , Nerve Compression Syndromes/pathology , Optic Chiasm/pathology , Optic Nerve Diseases/pathology , Computer Simulation , Humans , Optic Nerve Diseases/physiopathology , Reproducibility of ResultsABSTRACT
The precise mechanism of bitemporal hemianopia (a type of partial visual field defect) is still not clear. Previous work has investigated this problem by studying the biomechanics of chiasmal compression caused by a pituitary tumour growing up from below the optic chiasm. A multi-scale analysis was performed using finite element models to examine both the macro-scale behaviour of the chiasm and the micro-scale interactions of the nerve fibres within it using representative volume elements. Possible effects of large deflection and non-linear material properties were incorporated. Strain distributions in the optic chiasm and optic nerve fibres were obtained from these models. The results of the chiasmal model agreed well with the limited experimental results available, indicating that the finite element modelling can be a useful tool for analysing chiasmal compression. Simulation results showed that the strain distribution in nasal (crossed) nerve fibres was much more nonuniform and locally higher than in temporal (uncrossed) nerve fibres. This strain difference between nasal and temporal nerve fibres may account for the phenomenon of bitemporal hemianopia.
Subject(s)
Hemianopsia/physiopathology , Optic Chiasm/physiology , Vision, Ocular/physiology , Axons/physiology , Biomechanical Phenomena , Computer Simulation , Finite Element Analysis , Humans , Imaging, Three-Dimensional , Models, Anatomic , Nerve Fibers/pathology , PressureABSTRACT
The association between bitemporal hemianopia and chiasmal compression is well recognized. The majority of chiasmal syndromes are caused by extrinsic compression from pituitary tumors, suprasellar meningiomas, craniopharyngiomas, and aneurysms. However, it is not clear why compressive lesions of the chiasm show a predilection for damage to nasal fibers with bitemporal hemianopia. Few experimental attempts at elucidating these mysteries have been reported and none has provided an adequate explanation. The authors postulate that the susceptibility of nasal fibers to preferential damage is explained by structural collapse theories as applied to crossing and noncrossing cylinders. By constructing a simplified mathematical model, the authors demonstrate that nasal fibers are subject to relatively greater pressures for any given external compressive force acting on the chiasm.