Ganglion cell layer segmentation and the two-flash multifocal electroretinogram improve structure function analysis...

Area of Science:

• Ophthalmology
• Neuroscience
• Medical Imaging

Background:

• Primary open-angle glaucoma (POAG) diagnosis and monitoring rely on structure-function analysis.
• Current methods may not fully capture early glaucomatous changes, particularly in the macula.
• Integrating advanced electrophysiological and imaging techniques can improve diagnostic accuracy.

Purpose of the Study:

• To enhance structure-function analysis in POAG by incorporating the two-global flash multifocal electroretinogram (2F-mfERG).
• To evaluate the utility of macular ganglion cell-inner plexiform layer (GCIPL) segmentation in glaucoma assessment.
• To compare the diagnostic capabilities of 2F-mfERG and GCIPL thickness with standard automated perimetry (SAP).

Main Methods:

• Twenty-five glaucoma patients (pre-perimetric and POAG) and 16 controls underwent 2F-mfERG, optical coherence tomography (OCT), and SAP.
• Calculated root mean square for 2F-mfERG responses (DC, IC1, IC2) and analyzed macular total thickness (mT) and GCIPL thickness via OCT.
• Compared central 10° and 15° 2F-mfERG values with corresponding OCT and visual field data.

Main Results:

• Both pre-perimetric glaucoma (PPG) and POAG groups showed significantly reduced mfERG responses compared to controls.
• A subset of glaucoma patients exhibited reduced central mfERG and GCIPL thickness without SAP defects.
• MfERG responses (DC, IC2) and GCIPL thickness correlated positively with macular thickness (mT); GCIPL thickness correlated with IC2.
• DC, IC2, and GCIPL thickness demonstrated high accuracy in differentiating glaucoma from controls (AUC > 0.89).

Conclusions:

• Including GCIPL thickness and 2F-mfERG significantly improves structure-function analysis in glaucoma.
• These measures provide complementary information to standard automated perimetry (SAP).
• The combined approach offers a more comprehensive assessment of glaucomatous damage.