Literature DB >> 26325414

Assessment of Different Sampling Methods for Measuring and Representing Macular Cone Density Using Flood-Illuminated Adaptive Optics.

Shu Feng, Michael J Gale, Jonathan D Fay, Ambar Faridi, Hope E Titus, Anupam K Garg, Keith V Michaels, Laura R Erker, Dawn Peters, Travis B Smith, Mark E Pennesi.   

Abstract

PURPOSE: To describe a standardized flood-illuminated adaptive optics (AO) imaging protocol suitable for the clinical setting and to assess sampling methods for measuring cone density.
METHODS: Cone density was calculated following three measurement protocols: 50 × 50-μm sampling window values every 0.5° along the horizontal and vertical meridians (fixed-interval method), the mean density of expanding 0.5°-wide arcuate areas in the nasal, temporal, superior, and inferior quadrants (arcuate mean method), and the peak cone density of a 50 × 50-μm sampling window within expanding arcuate areas near the meridian (peak density method). Repeated imaging was performed in nine subjects to determine intersession repeatability of cone density.
RESULTS: Cone density montages could be created for 67 of the 74 subjects. Image quality was determined to be adequate for automated cone counting for 35 (52%) of the 67 subjects. We found that cone density varied with different sampling methods and regions tested. In the nasal and temporal quadrants, peak density most closely resembled histological data, whereas the arcuate mean and fixed-interval methods tended to underestimate the density compared with histological data. However, in the inferior and superior quadrants, arcuate mean and fixed-interval methods most closely matched histological data, whereas the peak density method overestimated cone density compared with histological data. Intersession repeatability testing showed that repeatability was greatest when sampling by arcuate mean and lowest when sampling by fixed interval.
CONCLUSIONS: We show that different methods of sampling can significantly affect cone density measurements. Therefore, care must be taken when interpreting cone density results, even in a normal population.

Mesh:

Year:  2015        PMID: 26325414      PMCID: PMC4559213          DOI: 10.1167/iovs.15-16954

Source DB:  PubMed          Journal:  Invest Ophthalmol Vis Sci        ISSN: 0146-0404            Impact factor:   4.799


  57 in total

1.  In vivo imaging of the photoreceptor mosaic in retinal dystrophies and correlations with visual function.

Authors:  Stacey S Choi; Nathan Doble; Joseph L Hardy; Steven M Jones; John L Keltner; Scot S Olivier; John S Werner
Journal:  Invest Ophthalmol Vis Sci       Date:  2006-05       Impact factor: 4.799

2.  Variation of cone photoreceptor packing density with retinal eccentricity and age.

Authors:  Hongxin Song; Toco Yuen Ping Chui; Zhangyi Zhong; Ann E Elsner; Stephen A Burns
Journal:  Invest Ophthalmol Vis Sci       Date:  2011-09-21       Impact factor: 4.799

3.  Interocular symmetry of parafoveal photoreceptor cone density distribution.

Authors:  Marco Lombardo; Giuseppe Lombardo; Domenico Schiano Lomoriello; Pietro Ducoli; Mario Stirpe; Sebastiano Serrao
Journal:  Retina       Date:  2013-09       Impact factor: 4.256

4.  Pre-processing, registration and selection of adaptive optics corrected retinal images.

Authors:  Gomathy Ramaswamy; Nicholas Devaney
Journal:  Ophthalmic Physiol Opt       Date:  2013-04-29       Impact factor: 3.117

5.  High-resolution imaging with adaptive optics in patients with inherited retinal degeneration.

Authors:  Jacque L Duncan; Yuhua Zhang; Jarel Gandhi; Chiaki Nakanishi; Mohammad Othman; Kari E H Branham; Anand Swaroop; Austin Roorda
Journal:  Invest Ophthalmol Vis Sci       Date:  2007-07       Impact factor: 4.799

6.  Outer retinal structure in best vitelliform macular dystrophy.

Authors:  David B Kay; Megan E Land; Robert F Cooper; Adam M Dubis; Pooja Godara; Alfredo Dubra; Joseph Carroll; Kimberly E Stepien
Journal:  JAMA Ophthalmol       Date:  2013-09       Impact factor: 7.389

7.  Assessing the cone photoreceptor mosaic in eyes with pseudodrusen and soft Drusen in vivo using adaptive optics imaging.

Authors:  Sarah Mrejen; Taku Sato; Christine A Curcio; Richard F Spaide
Journal:  Ophthalmology       Date:  2013-10-30       Impact factor: 12.079

8.  Variability in parafoveal cone mosaic in normal trichromatic individuals.

Authors:  Elise W Dees; Alfredo Dubra; Rigmor C Baraas
Journal:  Biomed Opt Express       Date:  2011-04-26       Impact factor: 3.732

9.  Adaptive optics retinal imaging reveals S-cone dystrophy in tritan color-vision deficiency.

Authors:  Rigmor C Baraas; Joseph Carroll; Karen L Gunther; Mina Chung; David R Williams; David H Foster; Maureen Neitz
Journal:  J Opt Soc Am A Opt Image Sci Vis       Date:  2007-05       Impact factor: 2.129

10.  Analysis of macular cone photoreceptors in a case of occult macular dystrophy.

Authors:  Naoki Tojo; Tomoko Nakamura; Hironori Ozaki; Miyako Oka; Toshihiko Oiwake; Atsushi Hayashi
Journal:  Clin Ophthalmol       Date:  2013-05-08
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  13 in total

1.  Intergrader agreement of foveal cone topography measured using adaptive optics scanning light ophthalmoscopy.

Authors:  Niamh Wynne; Jenna A Cava; Mina Gaffney; Heather Heitkotter; Abigail Scheidt; Jenny L Reiniger; Jenna Grieshop; Kai Yang; Wolf M Harmening; Robert F Cooper; Joseph Carroll
Journal:  Biomed Opt Express       Date:  2022-08-01       Impact factor: 3.562

2.  Comparison of Cone Mosaic Metrics From Images Acquired With the SPECTRALIS High Magnification Module and Adaptive Optics Scanning Light Ophthalmoscopy.

Authors:  Niamh Wynne; Heather Heitkotter; Erica N Woertz; Robert F Cooper; Joseph Carroll
Journal:  Transl Vis Sci Technol       Date:  2022-05-02       Impact factor: 3.048

3.  Repeatability of Adaptive Optics Automated Cone Measurements in Subjects With Retinitis Pigmentosa and Novel Metrics for Assessment of Image Quality.

Authors:  Michael J Gale; Gareth A Harman; Jimmy Chen; Mark E Pennesi
Journal:  Transl Vis Sci Technol       Date:  2019-05-08       Impact factor: 3.283

4.  Agreement in Cone Density Derived from Gaze-Directed Single Images Versus Wide-Field Montage Using Adaptive Optics Flood Illumination Ophthalmoscopy.

Authors:  Avenell L Chew; Danuta M Sampson; Irwin Kashani; Fred K Chen
Journal:  Transl Vis Sci Technol       Date:  2017-12-22       Impact factor: 3.283

5.  Impact of Reference Center Choice on Adaptive Optics Imaging Cone Mosaic Analysis.

Authors:  Danial Roshandel; Danuta M Sampson; David A Mackey; Fred K Chen
Journal:  Invest Ophthalmol Vis Sci       Date:  2022-04-01       Impact factor: 4.925

6.  Parafoveal cone abnormalities and recovery on adaptive optics in posterior uveitis.

Authors:  Kristin Biggee; Michael J Gale; Travis B Smith; Eric B Suhler; Mark E Pennesi; Phoebe Lin
Journal:  Am J Ophthalmol Case Rep       Date:  2016-03-11

Review 7.  Photoreceptor-Based Biomarkers in AOSLO Retinal Imaging.

Authors:  Katie M Litts; Robert F Cooper; Jacque L Duncan; Joseph Carroll
Journal:  Invest Ophthalmol Vis Sci       Date:  2017-05-01       Impact factor: 4.799

8.  Perifoveal interdigitation zone loss in hydroxychloroquine toxicity leads to subclinical bull's eye lesion appearance on near-infrared reflectance imaging.

Authors:  Avenell L Chew; Danuta M Sampson; Enid Chelva; Jane C Khan; Fred K Chen
Journal:  Doc Ophthalmol       Date:  2017-11-09       Impact factor: 2.379

9.  Retinal Differential Light Sensitivity Variation Across the Macula in Healthy Subjects: Importance of Cone Separation and Loci Eccentricity.

Authors:  Danuta M Sampson; Danial Roshandel; Avenell L Chew; Yufei Wang; Paul G Stevenson; Matthew N Cooper; Elaine Ong; Lawrence Wong; Jonathan La; David Alonso-Caneiro; Enid Chelva; Jane C Khan; David D Sampson; Fred K Chen
Journal:  Transl Vis Sci Technol       Date:  2021-05-03       Impact factor: 3.283

10.  Distribution of cone density, spacing and arrangement in adult healthy retinas with adaptive optics flood illumination.

Authors:  Richard Legras; Alain Gaudric; Kelly Woog
Journal:  PLoS One       Date:  2018-01-16       Impact factor: 3.240

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