Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
To propose a new method of identifying clusters in multifocal electrophysiology (multifocal electroretinogram: mfERG; multifocal visual-evoked potential: mfVEP) that conserve the maximum capacity to discriminate between patients and control subjects.
The theoretical framework proposed creates arbitrary N-size clusters of sectors. The capacity to discriminate between patients and control subjects is assessed by analysing the area under the receiver operator characteristic curve (AUC). As proof of concept, the method is validated using mfERG recordings taken from both eyes of control subjects (n = 6) and from patients with multiple sclerosis (n = 15).
Considering the amplitude of wave P1 as the analysis parameter, the maximum value of AUC = 0.7042 is obtained with N = 9 sectors. Taking into account the AUC of the amplitudes and latencies of waves N1 and P1, the maximum value of the AUC = 0.6917 with N = 8 clustered sectors. The greatest discriminant capacity is obtained by analysing the latency of wave P1: AUC = 0.8854 with a cluster of N = 12 sectors.
This paper demonstrates the effectiveness of a method able to determine the arbitrary clustering of multifocal responses that possesses the greatest capacity to discriminate between control subjects and patients when applied to the visual field of mfERG or mfVEP recordings. The method may prove helpful in diagnosing any disease that is identifiable in patients’ mfERG or mfVEP recordings and is extensible to other clinical tests, such as optical coherence tomography.
Stiefelmeyer S, Neubauer AS, Berninger T et al (2004) The multifocal pattern electroretinogram in glaucoma. Vis Res 44:103–112. https://doi.org/10.1016/j.visres.2003.08.012 CrossRefPubMed
Laron M, Cheng H, Zhang B, Frishman LJ (2009) The effect of eccentricity on the contrast response function of multifocal visual evoked potentials (mfVEPs). Vis Res 49:1711–1716. https://doi.org/10.1016/j.visres.2009.03.021 CrossRefPubMed
De Santiago L, Ortiz del Castillo M, Blanco R et al (2016) A signal-to-noise-ratio-based analysis of multifocal visual-evoked potentials in multiple sclerosis risk assessment. Clin Neurophysiol 127:1574–1580. https://doi.org/10.1016/j.clinph.2015.09.129 CrossRefPubMed
de Santiago L, Sánchez Morla EM, Ortiz M et al (2019) A computer-aided diagnosis of multiple sclerosis based on mfVEP recordings. PLoS ONE 14:e0214662. https://doi.org/10.1371/journal.pone.0214662 CrossRefPubMedPubMedCentral
Qiao N, Zhang Y, Ye Z et al (2015) Comparison of multifocal visual evoked potential, static automated perimetry, and optical coherence tomography findings for assessing visual pathways in patients with pituitary adenomas. Pituitary 18:598–603. https://doi.org/10.1007/s11102-014-0613-6 CrossRefPubMed
Sousa RM, Oyamada MK, Cunha LP, Monteiro MLR (2017) Multifocal visual evoked potential in eyes with temporal hemianopia from chiasmal compression: correlation with standard automated perimetry and OCT findings. Invest Ophthalmol Vis Sci 58:4436–4449. https://doi.org/10.1167/iovs.17-21529 CrossRefPubMed
Garcia-Martin E, Ara JR, Martin J et al (2017) Retinal and optic nerve degeneration in patients with multiple sclerosis followed up for 5 years. Ophthalmology 124:688–696. https://doi.org/10.1016/j.ophtha.2017.01.005 CrossRefPubMed
Larrosa JM, Polo V, Ferreras A et al (2015) Neural network analysis of different segmentation strategies of nerve fiber layer assessment for glaucoma diagnosis. J Glaucoma 24:672–678. https://doi.org/10.1097/IJG.0000000000000071 CrossRefPubMed
- Identification of clusters in multifocal electrophysiology recordings to maximize discriminant capacity (patients vs. control subjects)
M. Ortiz del Castillo
E. M. Sánchez Morla
M. J. Rodrigo
- Springer Berlin Heidelberg
The Journal of Clinical Electrophysiology and Vision - The Official Journal of the International Society for Clinical Electrophysiology and Vision
Print ISSN: 0012-4486
Elektronische ISSN: 1573-2622