[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"trial:NCT04420156":3,"trial-entities:NCT04420156":155,"trial-summary:NCT04420156":158},{"id":4,"nct_id":4,"org_study_id":5,"brief_title":6,"official_title":7,"overall_status":8,"completion_date":9,"status_verified_date":10,"last_update_date":11,"start_date":12,"sponsor_name":13,"lead_sponsor_class":14,"has_dmc":15,"brief_summary":16,"detailed_description":17,"conditions":18,"keywords":20,"study_type":24,"primary_purpose":25,"phases":26,"enrollment_info":27,"interventions":30,"primary_outcomes":36,"secondary_outcomes":41,"sex":42,"minimum_age":25,"maximum_age":43,"healthy_volunteers":15,"eligibility_criteria":44,"std_ages":50,"locations":52,"central_contacts":146,"overall_officials":150,"references":153,"see_also_links":154},"NCT04420156","STUDY21403","Clinical and Genetic Analysis of ROP","Clinical and Genetic Analysis of Retinopathy of Prematurity","RECRUITING","2030-05-31","2022-04","2022-04-20","2011-07-01","Oregon Health and Science University","OTHER",true,"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.\n\nParticipants 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.\n\nThe 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.","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.\n\nThis 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).\n\nThe 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.\n\nAll 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.\n\nMost 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.\n\nIn 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.\n\nWhile 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.\n\nProspective 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.\n\nProspective 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.",[19],"Retinopathy of Prematurity",[21,22,23],"ophthalmology","neonatology","prematurity","OBSERVATIONAL",null,[],{"count":28,"type":29},2000,"ESTIMATED",[31],{"type":14,"name":32,"description":33,"armGroupLabels":34},"No intervention administered.","Eye exams are standard of care and would be performed regardless of participation in this study.",[35],"i-ROP cohort",[37],{"measure":38,"description":39,"timeFrame":40},"Evaluate diagnostic accuracy of an AI system for ROP diagnosis","Premature babies are examined for retinopathy of prematurity (ROP), a potentially blinding diesese. As a standard of care, retinal images are taken during ROP examinations. This research group has collected a repository of images over the past 9 years and with those images, the investigators have developed an artificial intelligence (AI) system that has the ability to diagnose severe ROP with high accuracy. The primary outcome measure in continuing to recruit subjects for this study is to collect more images to improve the existing AI system and expand the ability to diagnose ROP.","4 years",[],"ALL","1 Year",{"inclusion":45,"exclusion":47,"raw_text":49},[46],"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).",[48],"Patients will be excluded if they have structural ocular anomalies, or if they are considered unstable for examintion by their attending neonatologist.","Inclusion Criteria:\n\n* 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).\n\nExclusion Criteria:\n\n* Patients will be excluded if they have structural ocular anomalies, or if they are considered unstable for examintion by their attending neonatologist.",[51],"CHILD",[53,72,89,106,128],{"facility":54,"status":55,"city":56,"state":57,"zip":58,"country":59,"contacts":60,"geoPoint":69},"Stanford University","NOT_YET_RECRUITING","Palo Alto","California","94303","United States",[61,66],{"name":62,"role":63,"phone":64,"email":65},"Darius Moshfeghi, M.D.","CONTACT","650-723-6995","dariusm@stanford.edu",{"name":67,"role":63,"phone":64,"email":68},"Mariana Nunez","mnunez1@stanford.edu",{"lat":70,"lon":71},37.44188,-122.14302,{"facility":73,"status":8,"city":74,"state":75,"zip":76,"country":59,"contacts":77,"geoPoint":86},"University of Illinois Chicago","Chicago","Illinois","60607",[78,82],{"name":79,"role":63,"phone":80,"email":81},"Robison Vernon P Chan, M.D.","312-996-6660","rvpchan@uic.edu",{"name":83,"role":63,"phone":84,"email":85},"Bhavana Kolli","630-863-1487","bkolli2@uic.edu",{"lat":87,"lon":88},41.85003,-87.65005,{"facility":90,"status":8,"city":91,"state":92,"zip":93,"country":59,"contacts":94,"geoPoint":103},"William Beaumont Hospital","Royal Oak","Michigan","48073",[95,99],{"name":96,"role":63,"phone":97,"email":98},"Kimberly Drenser, M.D.","248-288-2280","kdrenser@arcpc.net",{"name":100,"role":63,"phone":101,"email":102},"Mary Zajechowski","248-330-7649","mary.zajechowski@beaumont.org",{"lat":104,"lon":105},42.48948,-83.14465,{"facility":107,"status":8,"city":108,"state":109,"zip":110,"country":59,"contacts":111,"geoPoint":125},"Oregon Health & Science University","Portland","Oregon","97239",[112,116,120,123],{"name":113,"role":63,"phone":114,"email":115},"John P Campbell, M.D.","503-494-7891","campbelp@ohsu.edu",{"name":117,"role":63,"phone":118,"email":119},"Susan R Osmto, M.S.","503-494-7450","ostmo@ohsu.edu",{"name":121,"role":122},"Aaron Coyner, PhD","SUB_INVESTIGATOR",{"name":124,"role":122},"Kemal Sonmez, PhD",{"lat":126,"lon":127},45.52345,-122.67621,{"facility":129,"status":55,"city":130,"state":131,"zip":132,"country":59,"contacts":133,"geoPoint":143},"University of Utah","Salt Lake City","Utah","84132",[134,138,141],{"name":135,"role":63,"phone":136,"email":137},"Mary E Hartnett, M.D.","801-581-2352","me.hartnett@hsc.utah.edu",{"name":139,"role":63,"phone":136,"email":140},"Deborah Harrison","deborah.harrison@hsc.utah.edu",{"name":142,"role":122},"Leah Owen, M.D.",{"lat":144,"lon":145},40.76078,-111.89105,[147,148],{"name":113,"role":63,"phone":114,"email":115},{"name":149,"role":63,"phone":118,"email":119},"Susan R Ostmo, M.S.",[151],{"name":113,"affiliation":13,"role":152},"PRINCIPAL_INVESTIGATOR",[],[],{"nct_id":4,"conditions":156,"biomarkers":157},[19],[],{"nct_id":4,"found":15,"summary":159,"prompt_version":169},{"design":160,"status":161,"heading":162,"summary":163,"follow_up":164,"word_count":165,"commitments":166,"compensation":167,"drugs_mentioned":168},"This is an observational study, meaning no new interventions are given. It aims to enroll 2000 eye exams from 375 participants.","completed","Observational Study of Retinopathy of Prematurity (ROP) and AI Diagnosis","This study is looking at Retinopathy of Prematurity (ROP), an eye condition affecting premature babies, which can lead to blindness if not caught early. Researchers are not testing a new treatment, but instead are evaluating how well an artificial intelligence (AI) system can diagnose ROP by looking at eye images. You or your baby would be eligible if your baby is hospitalized in a participating Neonatal Intensive Care Unit (NICU) and meets standard criteria for ROP screening. The goal is to improve how ROP is diagnosed and managed using AI and image data. This study is currently recruiting and aims to include 2000 eye exams from 375 babies.","The diagnostic accuracy of the AI system will be evaluated at 4 years.",108,"Eye exams are standard of care and would be performed regardless of participation. The study will collect wide-angle retinal images during these exams.","Not stated in the trial record.",[],"v2"]