Literature DB >> 29256985

Novel Image-Based Analysis for Reduction of Clinician-Dependent Variability in Measurement of the Corneal Ulcer Size.

Tapan P Patel1, N Venkatesh Prajna2, Sina Farsiu3, Nita G Valikodath1, Leslie M Niziol1, Lakshey Dudeja2, Kyeong Hwan Kim1,4, Maria A Woodward1,5.   

Abstract

PURPOSE: To assess variability in corneal ulcer measurements between ophthalmologists and reduce clinician-dependent variability using semiautomated segmentation of the ulcer from photographs.
METHODS: Three ophthalmologists measured 50 patients' eyes for epithelial defects (EDs) and the stromal infiltrate (SI) size using slit-lamp (SL) calipers. SL photographs were obtained. An algorithm was developed for semiautomatic segmenting of the ED and SI in the photographs. Semiautomatic segmentation was repeated 3 times by different users (2 ophthalmologists and 1 trainee). Clinically significant variability was assessed with intraclass correlation coefficients (ICCs) and the percentage of pairwise measurements differing by ≥0.5 mm. Semiautomatic segmentation measurements were compared with manual delineation of the image by a corneal specialist (gold standard) using Dice similarity coefficients.
RESULTS: Ophthalmologists' reliability in measurements by SL calipers had an ICC from 0.84 to 0.88 between examiners. Measurements by semiautomatic segmentation had an ICC from 0.96 to 0.98. SL measures of ulcers by clinical versus semiautomatic segmentation measures differed by ≥0.5 mm in 24% to 38% versus 8% to 28% (ED height); 30% to 52% versus 12% to 34% (ED width); 26% to 38% versus 10% to 32% (SI height); and 38% to 58% versus 14% to 34% (SI width), respectively. Average Dice similarity coefficients between manual and repeated semiautomatic segmentation ranged from 0.83 to 0.86 for the ED and 0.78 to 0.83 for the SI.
CONCLUSIONS: Variability exists when measuring corneal ulcers, even among ophthalmologists. Photography and computerized methods for quantifying the ulcer size could reduce variability while remaining accurate and impact quantitative measurement endpoints.

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Year:  2018        PMID: 29256985      PMCID: PMC5799030          DOI: 10.1097/ICO.0000000000001488

Source DB:  PubMed          Journal:  Cornea        ISSN: 0277-3740            Impact factor:   2.651


  34 in total

1.  Technique of area measurement of epithelial defects.

Authors:  Nitin Mukerji; Rasik B Vajpayee; Namrata Sharma
Journal:  Cornea       Date:  2003-08       Impact factor: 2.651

2.  Engineering and algorithm design for an image processing Api: a technical report on ITK--the Insight Toolkit.

Authors:  Terry S Yoo; Michael J Ackerman; William E Lorensen; Will Schroeder; Vikram Chalana; Stephen Aylward; Dimitris Metaxas; Ross Whitaker
Journal:  Stud Health Technol Inform       Date:  2002

3.  Quantitative classification of eyes with and without intermediate age-related macular degeneration using optical coherence tomography.

Authors:  Sina Farsiu; Stephanie J Chiu; Rachelle V O'Connell; Francisco A Folgar; Eric Yuan; Joseph A Izatt; Cynthia A Toth
Journal:  Ophthalmology       Date:  2013-08-29       Impact factor: 12.079

4.  Technician Consistency in Specular Microscopy Measurements: A "Real-World" Retrospective Analysis of a United States Eye Bank.

Authors:  Gabriel M Rand; Ji Won Kwon; Patrick K Gore; Mitchell D McCartney; Roy S Chuck
Journal:  Cornea       Date:  2017-10       Impact factor: 2.651

5.  Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs.

Authors:  Varun Gulshan; Lily Peng; Marc Coram; Martin C Stumpe; Derek Wu; Arunachalam Narayanaswamy; Subhashini Venugopalan; Kasumi Widner; Tom Madams; Jorge Cuadros; Ramasamy Kim; Rajiv Raman; Philip C Nelson; Jessica L Mega; Dale R Webster
Journal:  JAMA       Date:  2016-12-13       Impact factor: 56.272

6.  Quantification of nerve fiber layer thickness in normal and glaucomatous eyes using optical coherence tomography.

Authors:  J S Schuman; M R Hee; C A Puliafito; C Wong; T Pedut-Kloizman; C P Lin; E Hertzmark; J A Izatt; E A Swanson; J G Fujimoto
Journal:  Arch Ophthalmol       Date:  1995-05

7.  Interobserver agreement in the interpretation of single-field digital fundus images for diabetic retinopathy screening.

Authors:  Paisan Ruamviboonsuk; Khemawan Teerasuwanajak; Montip Tiensuwan; Kanokwan Yuttitham
Journal:  Ophthalmology       Date:  2006-05       Impact factor: 12.079

8.  Evaluation of fungal keratitis using a newly developed computer program, Optscore, for grading digital corneal photographs.

Authors:  Christine M Toutain-Kidd; Travis C Porco; Eric M Kidd; M Srinivasan; Namperumalsamy V Prajna; Nisha Acharya; Thomas Lietman; Michael E Zegans
Journal:  Ophthalmic Epidemiol       Date:  2014-02       Impact factor: 1.648

9.  Corneal ulceration in South East Asia. I: a model for the prevention of bacterial ulcers at the village level in rural Bhutan.

Authors:  K Getshen; M Srinivasan; M P Upadhyay; B Priyadarsini; R Mahalaksmi; J P Whitcher
Journal:  Br J Ophthalmol       Date:  2006-03       Impact factor: 4.638

Review 10.  Algorithms for the Automated Analysis of Age-Related Macular Degeneration Biomarkers on Optical Coherence Tomography: A Systematic Review.

Authors:  Maximilian W M Wintergerst; Thomas Schultz; Johannes Birtel; Alexander K Schuster; Norbert Pfeiffer; Steffen Schmitz-Valckenberg; Frank G Holz; Robert P Finger
Journal:  Transl Vis Sci Technol       Date:  2017-07-18       Impact factor: 3.283

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  7 in total

1.  Open-Source Automatic Segmentation of Ocular Structures and Biomarkers of Microbial Keratitis on Slit-Lamp Photography Images Using Deep Learning.

Authors:  Jessica Loo; Matthias F Kriegel; Megan M Tuohy; Kyeong Hwan Kim; Venkatesh Prajna; Maria A Woodward; Sina Farsiu
Journal:  IEEE J Biomed Health Inform       Date:  2021-01-05       Impact factor: 5.772

2.  A novel approach to anterior segment imaging with smartphones in the COVID-19 era.

Authors:  Sreetama Dutt; Siva S Vadivel; Shanmuganathan Nagarajan; Amrutha Galagali; Josephine S Christy; Anand Sivaraman; Divya Parthasarathy Rao
Journal:  Indian J Ophthalmol       Date:  2021-05       Impact factor: 1.848

3.  Case report: Utilization of neutral density filters for densitometry analysis of dense corneal opacities.

Authors:  Akhil Meka; Cody Moezzi; Daniel Brocks
Journal:  Am J Ophthalmol Case Rep       Date:  2022-07-31

4.  Algorithm Variability in Quantification of Epithelial Defect Size in Microbial Keratitis Images.

Authors:  Matthias F Kriegel; Jennifer Huang; Hamza A Ashfaq; Leslie M Niziol; Mohana Preethi; Huan Tan; Megan M Tuohy; Tapan P Patel; Venkatesh Prajna; Maria A Woodward
Journal:  Cornea       Date:  2020-05       Impact factor: 3.152

5.  Measurement Reliability for Keratitis Morphology.

Authors:  Matthias F Kriegel; Jessica Loo; Sina Farsiu; Venkatesh Prajna; Megan Tuohy; Kyeong Hwan Kim; Autumn N Valicevic; Leslie M Niziol; Huan Tan; Hamza A Ashfaq; Dena Ballouz; Maria A Woodward
Journal:  Cornea       Date:  2020-12       Impact factor: 3.152

6.  Could telehealth help eye care practitioners adapt contact lens services during the COVID-19 pandemic?

Authors:  Manbir Nagra; Marta Vianya-Estopa; James S Wolffsohn
Journal:  Cont Lens Anterior Eye       Date:  2020-04-18       Impact factor: 3.077

7.  Use of 'U-shaped tool for follow up of corneal ulcer cases in the COVID-19 pandemic.

Authors:  Rahul K Bafna; Abhijeet Beniwal; Nidhi Kalra; Suman Lata; Mohamed Ibrahime Asif; Namrata Sharma
Journal:  Indian J Ophthalmol       Date:  2020-10       Impact factor: 1.848

  7 in total

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