Predicting visual outcomes after decompression of pituitary tumours based on stratified inner-retinal layer thickness and age.

Abstract

The purpose of the study was to evaluate the potential role of stratified preoperative optical coherence tomography (OCT) measurements and age in predicting postoperative visual field (VF) improvement among adult patients with chiasmal compression due to pituitary tumours after decompression surgery. Postoperative visual outcomes were analysed using mean deviation of the VF test. Eyes were divided into three groups based on preoperative OCT parameters including peripapillary retinal nerve fibre layer (pRNFL) and ganglion cell-inner plexiform layer (GCIPL) thickness: groups 1, 2 and 3 with pRNFL thickness <65 μm, 65 μm or morebut <85 μm, and 85 μm or more, respectively. The GCIPL thickness was also divided into three groups based on values ranging from 55 to 77 μm. Each group was further categorized according to age: 20 years or older but younger than 40 years, 40 years or older but younger than 60, and 60 years or older. This study included 197 eyes of 197 patients with chiasmal compression due to pituitary tumours. No patient showed complete VF recovery in group 1 with a preoperative pRNFL thickness <65 μm or a GCIPL thickness <55 μm regardless of age. These groups showed the worst VF outcome (pRNFL, p = 0.0001; GCIPL, p < 0.0001). However, a significant recovery in VF (greater than 2dB) was observed in 45% of group 1 patients based on pRNFL thickness and in 61.54% of group 1 patients according to GCIPL thickness. In groups 2 and 3 with a preoperative pRNFL thickness of 65 μm or more and a GCIPL thickness of 55 μm or more, the rate of complete VF recovery decreased as subjects' ages increased. Group 3 with a preoperative pRNFL thicknessof 85 μm or more and a GCIPL thickness of 77 μm or more were 2.5-fold and 4.0-fold more likely to completely recover VF, respectively, compared with group 2. Stratified preoperative pRNFL and GCIPL thicknesses measured via OCT in different age categories are effective biomarkers for predicting visual functional outcomes.