Clinical and Genetic Analysis of ROP

NCT ID: NCT04420156

Last Updated: 2022-04-20

Basic Information

• Recruitment Status: RECRUITING
• Total Enrollment: 2000 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2011-07-01
• Study Completion Date: 2030-05-31

Brief Summary

Retinopathy of Prematurity (ROP) is a vascular disease affecting the retinas (back of the eye) of low birth weight infants. Although it can be treated effectively if diagnosed early, it continues to be a leading cause of childhood blindness in the United States and throughout the world. The investigators feel that this study will result in specific knowledge discovery about ROP, as well as general knowledge about how image-based data and genetic data can be combined to better understand clinical disease.

Participants will be recruited from the neonatal intensive care unit (NICU) at OHSU, along with 4 collaborating institutions (William Beaumont Hospital, Stanford University, University of Illinois Chicago and University of Utah). Hospitalized infants who receive ROP screening examinations for routine care will be eligible for this study, and will be offered the opportunity to participate. Subjects who provide informed consent will have clinical data from routine care collected along with demographic characteristics, results from routine ROP screening examinations, presence of systemic disease or risk factors. Retinal photographs will be taken during these routine eye exams, using a commercially-available camera that has been FDA-cleared for taking pictures from retinas of premature infants. These retinal pictures do not contain any identifiable patient information, and are taken as routine standard of care.

The long-term goal of this research is to establish a quantitative framework for retinopathy of prematurity (ROP) care based on clinical, imaging, genetic, and informatics principles. The investigators have previously recruited and rigorously phenotyped and genotyped a large study cohort, including implementation of a novel reference standard diagnosis; and built a world-class research consortium for image, genetic, and bioinformatics analysis.

Detailed Description

This NIH funded multi-center study began July 2011 with 8 study sites approved by their individual IRBs. Recruitment and data was conducted at the following sites: OHSU, Columbia Universtiy, Cornell College, William Beaumont Hospital, Children's Hospital LA, University of Miami, University of Illinois Chicago, Cedars Sinai Medical Center and Asociacion para Evitar la Ceguera (APEC) in Mexico City. For the competitive renewal of the grant which begins 6-01-20, the recruitment sites have been reduced to 5 which include OHSU, William Beaumont, University of Illinois Chicago, University of Utah and Stanford University.

This study will aim to develop a quantitative framework for ROP care using artificial intelligence and analytics to improve clinical disease management. The investigators will evaluate performance of an artificial intelligence system for ROP diagnosis and screening prospectively. This will include: (a) recruit a target of over 2000 eye exams including wide-angle retinal images from 375 subjects at 5 centers, (b) optimize an image quality detection algorithm the investigators have recently developed, and (c) analyze system accuracy for ROP diagnosis (plus vs. pre-plus vs. normal) and screening (using a novel quantitative vascular severity scale).

The proposed work will study infants who will receive routine ophthalmoscopic exams and have retinal images taken at each exam according to the standard of care at each institution. At least one person at each site is trained to capture wide-angle retinal images using a commercially-available camera (RetCam; Natus, Pleasanton, CA). This device is FDA-cleared for premature infants, and has been used throughout the world for 20 years with no known complications.

All participating infants will undergo retinal photography by trained study personnel for up to 3 eye exams, or more if clinically indicated and feasible. "Outborn infants," who were transferred to the study center for specialized ROP care, will have at least one set of images taken if this is clinically indicated and feasible. These coded retinal images will be read and interpreted by remote expert graders using the secure web-based system developed for this study 9 years ago at OHSU. The de-identified images will be housed indefinitely in an OHSU IRB-approved repository for possible future research studies or for other educational purposes.

Most infants recruited from the first 9 years of this study between July 2011 and May 2020 had DNA collected from blood or saliva samples. The coded genetic samples are housed in an OHSU IRB-approved repository and will be analyzed by outside collaborators for specific aim 3 of this study. Note that this current study does not involve new collection of any blood or saliva samples.

In recent years, our team has successfully developed competitive image assessment methods to infer ROP status using (i) engineered image features based on translating descriptive and visual descriptions related to expert assessment . and (ii) deep-learned features based on end-to-end training of neural networks for image analysis. To improve model explainability, the models must not only provide classification (diagnostic) labels or severity scores, but also supplementary information regarding how a model produces its decisions and what about a particular image drives the decision. To this end, it is helpful for a model to (i) visualize its training data; and (ii) illustrate which features of the input image its decision relied heavily on. Visualization can provide an overarching demonstration of how a model produces its decisions across a dataset with known clinical and demographic characteristics, which contributes to overall interpretability of the model's logic. Illustration is essential to gain trust and to facilitate validation when clinicians rely on the model to assess a particular instance for various purposes, including training or regulatory approval.

While training the AI system in previous work, the investigators excluded 5% of images that were rated by the majority of graders as "not acceptable quality". For real-world use, it will be important to balance imageability with diagnostic performance. The investigators propose to evaluate our existing dataset to determine the optimal operating point in the CNN quality algorithm that balances imageability with diagnostic performance of the i-ROP DL classifier. The investigators will continue those studies to systematically examine their impact on improving image quality and diagnostic performance - and maximize rigor and reproducibility of study design. This operating point will then be "locked", and the closed system will be used as below.

Prospective evaluation of i-ROP DL classifier: The investigators propose to calculate the weighted kappa between the RSD and the i-ROP DL system, along with sensitivity, specificity, and imageability based on the optimal operating points identified above.

Prospective evaluation of vascular severity score: In a cross sectional analysis, the investigators will test the hypothesis that the ROP vascular severity score, derived from the i-ROP DL classifier, may demonstrate high sensitivity both for detection of plus disease and for identifying treatment-requiring disease in a real-world ROP screening population.

Conditions

Retinopathy of Prematurity

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: PROSPECTIVE

Study Groups

i-ROP cohort

Premature infants who are at risk of retinopathy of prematurity(ROP) at participating study sites. As standard of care, babies who are born less than 31 weeks gestational age or less than 1500 grams are routinely screened for ROP. Families are approached to participate in this study where finding from babies' eye exams and associated retinal images along with demographic and other health data are collected and coded with unique identifier. No intervention is administered. The ROP exams and images obtained are done as a standard of care and would be performed even if there is no consent provided.

No intervention administered.

Intervention Type: OTHER

Eye exams are standard of care and would be performed regardless of participation in this study.

Interventions

No intervention administered.

Eye exams are standard of care and would be performed regardless of participation in this study.

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

• All infants hospitalized at participating Neonatal Intensive Care Units will be eligible for the study if they meet plublished criteria for requiring ROP screening examination, or if they are transferred to the study center for specialized ophthalmic care. These eligibility criteria are identical at each study center, and match what is done in standard clinical practice according to national guidelines published jointly by the American Academy of Pediatrics, American Academy of Ophthalmology, and American Associatioin for Pediatric Ophthalmology and Strabismus (AAP-AAO, Pediatrics, 2013).

Exclusion Criteria

• Patients will be excluded if they have structural ocular anomalies, or if they are considered unstable for examintion by their attending neonatologist.

• Maximum Eligible Age: 1 Year
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

National Institutes of Health (NIH)

NIH

Sponsor Role: collaborator

U.S. National Science Foundation

FED

Sponsor Role: collaborator

Massachusetts General Hospital

OTHER

Sponsor Role: collaborator

Northeastern University

OTHER

Sponsor Role: collaborator

Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center

OTHER

Sponsor Role: collaborator

William Beaumont Hospitals

OTHER

Sponsor Role: collaborator

University of Illinois at Chicago

OTHER

Sponsor Role: collaborator

Stanford University

OTHER

Sponsor Role: collaborator

University of Utah

OTHER

Sponsor Role: collaborator

National Eye Institute (NEI)

NIH

Sponsor Role: collaborator

Oregon Health and Science University

OTHER

Sponsor Role: lead

Responsible Party

Michael Chiang

Principal Investigator

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

John P Campbell, M.D.

Role: PRINCIPAL_INVESTIGATOR

Oregon Health and Science University

Locations

Stanford University

Palo Alto, California, United States

Site Status: NOT_YET_RECRUITING

University of Illinois Chicago

Chicago, Illinois, United States

Site Status: RECRUITING

William Beaumont Hospital

Royal Oak, Michigan, United States

Site Status: RECRUITING

Oregon Health & Science University

Portland, Oregon, United States

Site Status: RECRUITING

University of Utah

Salt Lake City, Utah, United States

Site Status: NOT_YET_RECRUITING

Countries

United States

Central Contacts

John P Campbell, M.D.

Role: CONTACT

campbelp@ohsu.edu

503-494-7891

Susan R Ostmo, M.S.

Role: CONTACT

ostmo@ohsu.edu

503-494-7450

Facility Contacts

Darius Moshfeghi, M.D.

Role: primary

dariusm@stanford.edu

650-723-6995

Mariana Nunez

Role: backup

mnunez1@stanford.edu

650-723-6995

Robison Vernon P Chan, M.D.

Role: primary

rvpchan@uic.edu

312-996-6660

Bhavana Kolli

Role: backup

bkolli2@uic.edu

630-863-1487

Kimberly Drenser, M.D.

Role: primary

kdrenser@arcpc.net

248-288-2280

Mary Zajechowski

Role: backup

mary.zajechowski@beaumont.org

248-330-7649

John P Campbell, M.D.

Role: primary

campbelp@ohsu.edu

503-494-7891

Susan R Osmto, M.S.

Role: backup

ostmo@ohsu.edu

503-494-7450

Mary E Hartnett, M.D.

Role: primary

me.hartnett@hsc.utah.edu

801-581-2352

Deborah Harrison

Role: backup

deborah.harrison@hsc.utah.edu

801-581-2352

Other Identifiers

R01EY019474

Identifier Type: NIH

Identifier Source: secondary_id

View Link

STUDY21403

Identifier Type: -

Identifier Source: org_study_id