Literature DB >> 27432203

Chromatic Multifocal Pupillometer for Objective Perimetry and Diagnosis of Patients with Retinitis Pigmentosa.

Ron Chibel1, Ifat Sher1, Daniel Ben Ner1, Mohamad O Mhajna2, Asaf Achiron3, Soad Hajyahia2, Alon Skaat1, Yakir Berchenko4, Bernice Oberman4, Ofra Kalter-Leibovici5, Laurence Freedman4, Ygal Rotenstreich6.   

Abstract

PURPOSE: To assess visual field (VF) defects and retinal function objectively in healthy participants and patients with retinitis pigmentosa (RP) using a chromatic multifocal pupillometer.
DESIGN: Cross-sectional study. PARTICIPANTS: The right eyes of 16 healthy participants and 13 RP patients.
METHODS: Pupil responses to red and blue light (peak, 485 and 625 nm, respectively) presented by 76 light-emitting diodes, 1.8-mm spot size at different locations of a 16.2° VF were recorded. Subjective VFs of RP patients were determined using chromatic dark-adapted Goldmann VFs (CDA-GVFs). Six healthy participants underwent 2 pupillometer examinations to determine test-retest reliability. MAIN OUTCOME MEASURES: Three parameters of pupil contraction were determined automatically: percentage of change of pupil size (PPC), maximum contraction velocity (MCV; in pixels per second), and latency of MCV (LMCV; in seconds). The fraction of functional VF was determined by CDA-GVF.
RESULTS: In healthy participants, higher PPC and MCV were measured in response to blue compared with red light. The LMCV in response to blue light was relatively constant throughout the VF. Healthy participants demonstrated higher PPC and MCV and shorter LMCV in central compared with peripheral test points in response to red light. Test-retest correlation coefficients were 0.7 for PPC and 0.5 for MCV. In RP patients, test point in which the PPC and MCV were lower than 4 standard errors from the mean of healthy participants correlated with areas that were indicated as nonseeing by CDA-GVF. The mean absolute deviation in LMCV parameter in response to the red light between different test point was significantly higher in RP patients (range, 0.16-0.47) than in healthy participants (range, 0.02-0.16; P < 0.0001) and indicated its usefulness as a diagnostic tool with high sensitivity and specificity (area under the receiver operating characteristic curve (AUC), 0.97, Mann-Whitney-Wilcoxon analysis). Randomly reducing the number of test points to a total of 15 points did not significantly reduce the AUC in RP diagnosis based on this parameter.
CONCLUSIONS: This study demonstrates the feasibility of using a chromatic multifocal pupillometer for objective diagnosis of RP and assessment of VF defects.
Copyright © 2016 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

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Mesh:

Year:  2016        PMID: 27432203     DOI: 10.1016/j.ophtha.2016.05.038

Source DB:  PubMed          Journal:  Ophthalmology        ISSN: 0161-6420            Impact factor:   12.079


  12 in total

1.  Machine learning for comprehensive prediction of high risk for Alzheimer's disease based on chromatic pupilloperimetry.

Authors:  Yael Lustig-Barzelay; Ifat Sher; Inbal Sharvit-Ginon; Yael Feldman; Michael Mrejen; Shada Dallasheh; Abigail Livny; Michal Schnaider Beeri; Aron Weller; Ramit Ravona-Springer; Ygal Rotenstreich
Journal:  Sci Rep       Date:  2022-06-15       Impact factor: 4.996

Review 2.  Standards in Pupillography.

Authors:  Carina Kelbsch; Torsten Strasser; Yanjun Chen; Beatrix Feigl; Paul D Gamlin; Randy Kardon; Tobias Peters; Kathryn A Roecklein; Stuart R Steinhauer; Elemer Szabadi; Andrew J Zele; Helmut Wilhelm; Barbara J Wilhelm
Journal:  Front Neurol       Date:  2019-02-22       Impact factor: 4.003

3.  Chromatic pupilloperimetry for objective diagnosis of Best vitelliform macular dystrophy.

Authors:  Daniel Ben Ner; Ifat Sher; Amit Hamburg; Mohamad O Mhajna; Ron Chibel; Estela Derazne; Inbal Sharvit-Ginon; Eran Pras; Hadas Newman; Jaime Levy; Samer Khateb; Dror Sharon; Ygal Rotenstreich
Journal:  Clin Ophthalmol       Date:  2019-03-05

4.  Effects of low and moderate refractive errors on chromatic pupillometry.

Authors:  A V Rukmini; Milton C Chew; Maxwell T Finkelstein; Eray Atalay; Mani Baskaran; Monisha E Nongpiur; Joshua J Gooley; Tin Aung; Dan Milea; Raymond P Najjar
Journal:  Sci Rep       Date:  2019-03-20       Impact factor: 4.379

5.  Challenges to detect glaucomatous visual field loss with pupil perimetry.

Authors:  Ken Asakawa; Nobuyuki Shoji
Journal:  Clin Ophthalmol       Date:  2019-08-26

6.  Pupillary Light Reflex Induced by Two-Photon Vision.

Authors:  Agnieszka Zielinska; Piotr Ciacka; Maciej Szkulmowski; Katarzyna Komar
Journal:  Invest Ophthalmol Vis Sci       Date:  2021-12-01       Impact factor: 4.799

7.  How lesions at different locations along the visual pathway influence pupillary reactions to chromatic stimuli.

Authors:  Carina Kelbsch; Krunoslav Stingl; Ronja Jung; Melanie Kempf; Paul Richter; Torsten Strasser; Tobias Peters; Barbara Wilhelm; Helmut Wilhelm; Felix Tonagel
Journal:  Graefes Arch Clin Exp Ophthalmol       Date:  2021-12-13       Impact factor: 3.117

8.  Objective Measurement of Local Rod and Cone Function Using Gaze-Controlled Chromatic Pupil Campimetry in Healthy Subjects.

Authors:  Carina Kelbsch; Katarina Stingl; Melanie Kempf; Torsten Strasser; Ronja Jung; Laura Kuehlewein; Helmut Wilhelm; Tobias Peters; Barbara Wilhelm; Krunoslav Stingl
Journal:  Transl Vis Sci Technol       Date:  2019-11-20       Impact factor: 3.283

9.  Chromatic Pupilloperimetry Measures Correlate With Visual Acuity and Visual Field Defects in Retinitis Pigmentosa Patients.

Authors:  Ifat Sher; Yisroel Tucker; Maya Gurevich; Amit Hamburg; Ettel Bubis; Jonathan Kfir; Shlomit Zorani; Estela Derazne; Alon Skaat; Ygal Rotenstreich
Journal:  Transl Vis Sci Technol       Date:  2020-07-08       Impact factor: 3.283

10.  Electrophysiological and Pupillometric Abnormalities in PROM1 Cone-Rod Dystrophy.

Authors:  Jason C Park; Frederick T Collison; Gerald A Fishman; J Jason McAnany
Journal:  Transl Vis Sci Technol       Date:  2020-08-17       Impact factor: 3.283

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