Literature DB >> 31268499

A Quantitative Severity Scale for Retinopathy of Prematurity Using Deep Learning to Monitor Disease Regression After Treatment.

Kishan Gupta1, J Peter Campbell1, Stanford Taylor1, James M Brown2, Susan Ostmo1, R V Paul Chan3, Jennifer Dy4, Deniz Erdogmus4, Stratis Ioannidis4, Jayashree Kalpathy-Cramer2,5, Sang J Kim1,6, Michael F Chiang1,7.   

Abstract

IMPORTANCE: Retinopathy of prematurity (ROP) is a leading cause of childhood blindness worldwide, but treatment failure and disease recurrence are important causes of adverse outcomes in patients with treatment-requiring ROP (TR-ROP).
OBJECTIVES: To apply an automated ROP vascular severity score obtained using a deep learning algorithm and to assess its utility for objectively monitoring ROP regression after treatment. DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort study used data from the Imaging and Informatics in ROP consortium, which comprises 9 tertiary referral centers in North America that screen high volumes of at-risk infants for ROP. Images of 5255 clinical eye examinations from 871 infants performed between July 2011 and December 2016 were assessed for eligibility in the present study. The disease course was assessed with time across the numerous examinations for patients with TR-ROP. Infants born prematurely meeting screening criteria for ROP who developed TR-ROP and who had images captured within 4 weeks before and after treatment as well as at the time of treatment were included. MAIN OUTCOMES AND MEASURES: The primary outcome was mean (SD) ROP vascular severity score before, at time of, and after treatment. A deep learning classifier was used to assign a continuous ROP vascular severity score, which ranged from 1 (normal) to 9 (most severe), at each examination. A secondary outcome was the difference in ROP vascular severity score among eyes treated with laser or the vascular endothelial growth factor antagonist bevacizumab. Differences between groups for both outcomes were assessed using unpaired 2-tailed t tests with Bonferroni correction.
RESULTS: Of 5255 examined eyes, 91 developed TR-ROP, of which 46 eyes met the inclusion criteria based on the available images. The mean (SD) birth weight of those patients was 653 (185) g, with a mean (SD) gestational age of 24.9 (1.3) weeks. The mean (SD) ROP vascular severity scores significantly increased 2 weeks prior to treatment (4.19 [1.75]), peaked at treatment (7.43 [1.89]), and decreased for at least 2 weeks after treatment (4.00 [1.88]) (all P < .001). Eyes requiring retreatment with laser had higher ROP vascular severity scores at the time of initial treatment compared with eyes receiving a single treatment (P < .001). CONCLUSIONS AND RELEVANCE: This quantitative ROP vascular severity score appears to consistently reflect clinical disease progression and posttreatment regression in eyes with TR-ROP. These study results may have implications for the monitoring of patients with ROP for treatment failure and disease recurrence and for determining the appropriate level of disease severity for primary treatment in eyes with aggressive disease.

Entities:  

Year:  2019        PMID: 31268499      PMCID: PMC6613298          DOI: 10.1001/jamaophthalmol.2019.2442

Source DB:  PubMed          Journal:  JAMA Ophthalmol        ISSN: 2168-6165            Impact factor:   7.389


  40 in total

1.  Interexpert agreement in the identification of macular location in infants at risk for retinopathy of prematurity.

Authors:  Michael F Chiang; Preeti J Thyparampil; Daniel Rabinowitz
Journal:  Arch Ophthalmol       Date:  2010-09

Review 2.  The International Classification of Retinopathy of Prematurity revisited.

Authors: 
Journal:  Arch Ophthalmol       Date:  2005-07

3.  Computer-assisted quantification of vascular tortuosity in retinopathy of prematurity (an American Ophthalmological Society thesis).

Authors:  David K Wallace
Journal:  Trans Am Ophthalmol Soc       Date:  2007

4.  Clinical Management of Recurrent Retinopathy of Prematurity after Intravitreal Bevacizumab Monotherapy.

Authors:  Helen A Mintz-Hittner; Megan M Geloneck; Alice Z Chuang
Journal:  Ophthalmology       Date:  2016-05-27       Impact factor: 12.079

5.  Very Late Reactivation of Retinopathy of Prematurity After Monotherapy With Intravitreal Bevacizumab.

Authors:  Laura L Snyder; Jose Maria Garcia-Gonzalez; Michael J Shapiro; Michael P Blair
Journal:  Ophthalmic Surg Lasers Imaging Retina       Date:  2016-03       Impact factor: 1.300

6.  Automated Diagnosis of Plus Disease in Retinopathy of Prematurity Using Deep Convolutional Neural Networks.

Authors:  James M Brown; J Peter Campbell; Andrew Beers; Ken Chang; Susan Ostmo; R V Paul Chan; Jennifer Dy; Deniz Erdogmus; Stratis Ioannidis; Jayashree Kalpathy-Cramer; Michael F Chiang
Journal:  JAMA Ophthalmol       Date:  2018-07-01       Impact factor: 7.389

7.  Evaluation of a deep learning image assessment system for detecting severe retinopathy of prematurity.

Authors:  Travis K Redd; John Peter Campbell; James M Brown; Sang Jin Kim; Susan Ostmo; Robison Vernon Paul Chan; Jennifer Dy; Deniz Erdogmus; Stratis Ioannidis; Jayashree Kalpathy-Cramer; Michael F Chiang
Journal:  Br J Ophthalmol       Date:  2018-11-23       Impact factor: 4.638

8.  Plus Disease in Retinopathy of Prematurity: A Continuous Spectrum of Vascular Abnormality as a Basis of Diagnostic Variability.

Authors:  J Peter Campbell; Jayashree Kalpathy-Cramer; Deniz Erdogmus; Peng Tian; Dharanish Kedarisetti; Chace Moleta; James D Reynolds; Kelly Hutcheson; Michael J Shapiro; Michael X Repka; Philip Ferrone; Kimberly Drenser; Jason Horowitz; Kemal Sonmez; Ryan Swan; Susan Ostmo; Karyn E Jonas; R V Paul Chan; Michael F Chiang
Journal:  Ophthalmology       Date:  2016-08-31       Impact factor: 12.079

9.  Evidence-based screening criteria for retinopathy of prematurity: natural history data from the CRYO-ROP and LIGHT-ROP studies.

Authors:  James D Reynolds; Velma Dobson; Graham E Quinn; Alistair R Fielder; Earl A Palmer; Richard A Saunders; Robert J Hardy; Dale L Phelps; John D Baker; Michael T Trese; David Schaffer; Betty Tung
Journal:  Arch Ophthalmol       Date:  2002-11

10.  Telemedical diagnosis of retinopathy of prematurity intraphysician agreement between ophthalmoscopic examination and image-based interpretation.

Authors:  Karen E Scott; David Y Kim; Lu Wang; Steven A Kane; Osode Coki; Justin Starren; John T Flynn; Michael F Chiang
Journal:  Ophthalmology       Date:  2008-05-23       Impact factor: 12.079

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  17 in total

1.  Telemedicine for Retinopathy of Prematurity in 2020.

Authors:  Theodore Bowe; Cindy Ung; J Peter Campbell; Yoshihiro Yonekawa
Journal:  J Vitreoretin Dis       Date:  2019-09-05

2.  Cost-effectiveness of Artificial Intelligence-Based Retinopathy of Prematurity Screening.

Authors:  Steven L Morrison; Dmitry Dukhovny; R V Paul Chan; Michael F Chiang; J Peter Campbell
Journal:  JAMA Ophthalmol       Date:  2022-04-01       Impact factor: 8.253

3.  Federated Learning for Multicenter Collaboration in Ophthalmology: Implications for Clinical Diagnosis and Disease Epidemiology.

Authors:  Adam Hanif; Charles Lu; Ken Chang; Praveer Singh; Aaron S Coyner; James M Brown; Susan Ostmo; Robison V Paul Chan; Daniel Rubin; Michael F Chiang; Jayashree Kalpathy-Cramer; John Peter Campbell
Journal:  Ophthalmol Retina       Date:  2022-03-16

4.  Artificial Intelligence for Retinopathy of Prematurity: Validation of a Vascular Severity Scale against International Expert Diagnosis.

Authors:  J Peter Campbell; Michael F Chiang; Jimmy S Chen; Darius M Moshfeghi; Eric Nudleman; Paisan Ruambivoonsuk; Hunter Cherwek; Carol Y Cheung; Praveer Singh; Jayashree Kalpathy-Cramer; Susan Ostmo; Malvina Eydelman; R V Paul Chan; Antonio Capone
Journal:  Ophthalmology       Date:  2022-02-12       Impact factor: 14.277

5.  Aggressive Posterior Retinopathy of Prematurity: Clinical and Quantitative Imaging Features in a Large North American Cohort.

Authors:  Kellyn N Bellsmith; James Brown; Sang Jin Kim; Isaac H Goldstein; Aaron Coyner; Susan Ostmo; Kishan Gupta; R V Paul Chan; Jayashree Kalpathy-Cramer; Michael F Chiang; J Peter Campbell
Journal:  Ophthalmology       Date:  2020-02-07       Impact factor: 12.079

Review 6.  Artificial intelligence for retinopathy of prematurity.

Authors:  Rebekah H Gensure; Michael F Chiang; John P Campbell
Journal:  Curr Opin Ophthalmol       Date:  2020-09       Impact factor: 3.761

7.  Monitoring Disease Progression With a Quantitative Severity Scale for Retinopathy of Prematurity Using Deep Learning.

Authors:  Stanford Taylor; James M Brown; Kishan Gupta; J Peter Campbell; Susan Ostmo; R V Paul Chan; Jennifer Dy; Deniz Erdogmus; Stratis Ioannidis; Sang J Kim; Jayashree Kalpathy-Cramer; Michael F Chiang
Journal:  JAMA Ophthalmol       Date:  2019-07-03       Impact factor: 7.389

8.  Evaluation of pediatric ophthalmologists' perspectives of artificial intelligence in ophthalmology.

Authors:  Nita G Valikodath; Tala Al-Khaled; Emily Cole; Daniel S W Ting; Elmer Y Tu; J Peter Campbell; Michael F Chiang; Joelle A Hallak; R V Paul Chan
Journal:  J AAPOS       Date:  2021-06-01       Impact factor: 1.325

9.  Impact of Artificial Intelligence on Medical Education in Ophthalmology.

Authors:  Nita G Valikodath; Emily Cole; Daniel S W Ting; J Peter Campbell; Louis R Pasquale; Michael F Chiang; R V Paul Chan
Journal:  Transl Vis Sci Technol       Date:  2021-06-01       Impact factor: 3.283

10.  Evaluation of a Deep Learning-Derived Quantitative Retinopathy of Prematurity Severity Scale.

Authors:  J Peter Campbell; Sang Jin Kim; James M Brown; Susan Ostmo; R V Paul Chan; Jayashree Kalpathy-Cramer; Michael F Chiang
Journal:  Ophthalmology       Date:  2020-10-27       Impact factor: 14.277

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