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PURPOSE: To investigate whether there is transsynaptic degeneration in the human optic tract in hemianopia. To consider how the degeneration varies with duration of hemianopia and location of insult. METHODS: Seven patients with damage to the primary visual cortex (V1), the lateral geniculate nucleus (LGN), or the optic tract were scanned with structural MRI. The volume and cross-sectional area of the left and right optic tracts were computed based on the intensity values of the T1-weighted image. High values correspond to voxels with high white matter content, and the values decrease as the white matter content drops (indicating degeneration). A laterality index to compare the tract size in the two hemispheres was calculated at different intensity values. RESULTS: The three hemianopic patients with longstanding damage to either V1 or LGN showed laterality indices greater than 0.5 at the highest intensity values, indicating significant optic tract degeneration. Those with recent damage to the optic tract had even higher laterality indices due to direct degeneration. Even 18 months after V1 lesion, there was a significant correlation between the cross-section and volume indices at different intensity thresholds, whereas no control subject showed any correlation. CONCLUSIONS: Transsynaptic degeneration had already begun 18 months after lesion. Although there was no visible decrease in volume at this stage, the white matter integrity was compromised. Significant decrease in volume could be visualized at longer durations of hemianopia. This method of objectively assessing structural images provides an effective, noninvasive approach to monitor the timescale of optic tract degeneration.

Original publication




Journal article


Invest Ophthalmol Vis Sci

Publication Date





382 - 388


Adult, Aged, Geniculate Bodies, Hemianopsia, Humans, Magnetic Resonance Imaging, Middle Aged, Nerve Degeneration, Nerve Fibers, Optic Nerve, Optic Nerve Diseases, Retinal Ganglion Cells, Synaptic Transmission, Visual Cortex, Visual Fields, Visual Pathways