Δημοσιεύσεις
2021 |
Chandrinos, A. The challenge of predicting OAG Progression from the initial visual field test Journal Article In: Asian Journal of Research and Reports in Ophthalmology, vol. 4, no. 1, pp. 10-28, 2021. Abstract | Links | BibTeX | Ετικέτες: filters, noise, open angle glaucoma, visual field signal @article{Chandrinos2021d,Purpose: The aim of this study was the development of a critical code in order to combine statistics with a workable diagnostic system for open angle glaucoma that could predict improvement or deterioration of the tested visual field of a glaucoma suspect, most likely after the first or second visit for the visual field test. Methods: The study plan was to apply a set of different filters in order to select the most efficient one that could remove the most of the noise of the test printout, of which probably the greater part of this removed noise could be the component of the learning effect, as it was expected to be at the first or second session. The common mean and median filters were initially used and later on an adapted or Hybrid filter was designed in MatLab© environment and in a similar philosophy to Gardiner’s Predictor filter. Taking into account the details of the study data, an Adaptive or Hybrid filter following the deployment of the optic nerve fibre layers of the retina was tested and selecting different weight depending on the locations of possible glaucoma defects. Results: Initially, the used mean and median filters, used to remove noise of visual field provided ambitious results. The first filter blurred the edges and the overall appearance looked fuzzy or blurry. The second one calculated the values of the neighbourhood and set these in ascending array. Then selected the median of these values to replace the original one. The result in general looks misleading. Next, applying the Hybrid Adapted filter, the end results illustrated elimination of measured noise in the visual field tests and likely the first visit outcome could predict the third or the fifth visit one. Conclusion: This is a promising approach to identify and eliminate measurement noise in the visual field tests and to predict, after filtering the first examination outcome, the likely visual field outcome of the third or the fifth visit. The challenge of predicting the progression of open angle glaucoma from the initial visit nowadays is even more than any other the “Holy Grail” of Perimetry. |
2020 |
Chandrinos, A.; Tzamouranis, D. D. A Review of Learning Effect in Perimetry Journal Article In: Ophthalmology Research: An International Journal, vol. 12, pp. 23-30, 2020. Abstract | Links | BibTeX | Ετικέτες: filters, learning effect, learning index, perimetry, visual fields loss @article{Chandrinos2020b,Glaucoma is the second most common cause of visual impairment in the UK, with visual impairment registrations have increased by 22% since 2010. Glaucoma refers to a group of optic neuropathies leading to visual impairment and blindness. If glaucoma remains untreated, it may produce optic nerve damage, leading to vision loss. Consequently, visual field tests can be extremely valuable for glaucoma. At the same time, visual field assessment should be performed at baseline and periodically in the glaucoma follow-up or monitor the effectiveness of adopted therapeutic schemes. Any visual field test can be masked by one or more artefacts, which can either lead to the incorrect result of visual field loss or to the possible deterioration of existing loss. One of the most important factors is the perimetric learning effect that is present in almost all types of perimetry. To minimize the learning effect, we either have to conduct a practice test procedure, as a demonstration for the patient without collecting data, or to calculate and establish a learning index of the specific patient. By the establishment of such an index, assist the clinician in detecting possible masked or overestimated visual field defects or progression of glaucoma damage. Potentially, the intense data collection at a large number of locations throughout the field in a larger cohort of subjects (visually healthy and glaucomatous) would be required for a better index establishment. The incorporation of fatigue also may be required to form a robust index enough to simulate procedures of glaucoma prognosis. The low signal to noise ratio associated with perimetric testing suggests that improvements will always be difficult to make. |