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Physiological Correlates and Predictors of Functional Recovery After Chiasmal Decompression
Noa Raz1, Atira S Bick, Alexander Klistorner
1Department of Neurology (NR, ASB, TB-H, NL), The Agnes Ginges Center for Human Neurogenetics, Hadassah Hebrew University Medical Center, Jerusalem, Israel; Department of Neurosurgery (SS), Hadassah Hebrew University Medical Center, Jerusalem, Israel; Department of Ophthalmology (AK), Sydney University, Sydney, Australia; and Translational Neuroradiology Unit (DR), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland.
Background:
The intrinsic abilities and limits of the nervous system to repair itself after damage may be assessed using a model of optic chiasmal compression, before and after a corrective surgical procedure.
Methods:
Visual fields (VFs), multifocal visual evoked potentials (mfVEP), retinal nerve fiber layer (RNFL) thickness, and diffusion tensor imaging were used to evaluate a patient before and after removal of a meningioma compressing the chiasm. Normally sighted individuals served as controls. The advantage of each modality to document visual function and predict postoperative outcome (2-year follow-up) was evaluated.
Results:
Postsurgery visual recovery was best explained by critical mass of normally conducting fibers and not associated with average conduction amplitudes. Recovered VF was observed in quadrants in which more than 50% of fibers were identified, characterized by intact mfVEP latencies, but severely reduced amplitudes. Recovery was evident despite additional reduction of RNFL thickness and abnormal optic tract diffusivity. The critical mass of normally conducting fibers was also the best prognostic indicator for functional outcome 2 years later.
Conclusions:
Our results highlight the ability of the remaining normally conductive axons to predict visual recovery after decompression of the optic chiasm. The redundancy in anterior visual pathways may be explained, neuroanatomically, by overlapping receptive fields.
