[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100655349":3},{"organization":4,"outcomesModule":7,"designInfo":37,"detailedDescription":40,"studyPopulation":41,"armGroups":42,"interventions":48,"overallOfficials":53,"centralContacts":58,"locations":64,"responsibleParty":81,"collaborators":84,"id":91,"slug":92,"hasResults":93,"nctId":94,"briefTitle":95,"officialTitle":96,"acronym":97,"eligibilityCriteria":98,"healthyVolunteers":99,"sex":100,"minAge":101,"maxAge":36,"enrollmentInfo":102,"targetDuration":36,"studyType":105,"phases":36,"briefSummary":106,"conditions":107,"keywords":109,"overallStatus":118,"whyStopped":36,"lastUpdateSubmitDate":119,"lastUpdatePostDateStruct":120,"startDateStruct":123,"completionDateStruct":125,"leadSponsor":127,"locationsCount":128},{"fullName":5,"class":6},"University of British Columbia","OTHER",{"primaryOutcomes":8,"secondaryOutcomes":13,"otherOutcomes":36},[9],{"measure":10,"description":11,"timeFrame":12},"Artificial Intelligence-Generated Bowel Wall Thickness Measurement Agreement","Agreement between bowel wall thickness measurements generated by the artificial intelligence computer-vision algorithm and manual bowel wall thickness measurements performed by experienced sonographers using de-identified intestinal ultrasound images and cine loops. Agreement will be assessed using the pre-specified performance metric in the statistical analysis plan.","Day 1, after completion of the intestinal ultrasound examination",[14,17,20,23,26,29,32],{"measure":15,"description":16,"timeFrame":12},"Bowel Wall Layer Stratification Feasibility","Proportion of de-identified intestinal ultrasound images and cine loops for which the artificial intelligence algorithm generates an interpretable bowel wall layer stratification.",{"measure":18,"description":19,"timeFrame":12},"Luminal Diameter Measurement Feasibility","Proportion of de-identified intestinal ultrasound images and cine loops for which the artificial intelligence algorithm generates an interpretable luminal diameter measurement.",{"measure":21,"description":22,"timeFrame":12},"Bowel Wall Flow Assessment Feasibility","Proportion of de-identified intestinal ultrasound images and cine loops for which the artificial intelligence algorithm generates an interpretable bowel wall flow assessment.",{"measure":24,"description":25,"timeFrame":12},"Bowel Wall Scarring Assessment Feasibility","Proportion of de-identified intestinal ultrasound images and cine loops for which the artificial intelligence algorithm generates an interpretable bowel wall scarring assessment.",{"measure":27,"description":28,"timeFrame":12},"Gastrointestinal Motility Assessment Feasibility","Proportion of de-identified intestinal ultrasound images and cine loops for which the artificial intelligence algorithm generates an interpretable gastrointestinal motility assessment.",{"measure":30,"description":31,"timeFrame":12},"Mesenteric Fat Proliferation Assessment Feasibility","Proportion of de-identified intestinal ultrasound images and cine loops for which the artificial intelligence algorithm generates an interpretable assessment of mesenteric fat proliferation.",{"measure":33,"description":34,"timeFrame":35},"Proportion of Cine Loops Suitable for AI Development","Percentage of collected de-identified cine loops that meet all pre-specified completeness, image-quality, and required-metadata criteria for artificial intelligence algorithm training, tuning, and testing.","At completion of dataset preparation",null,{"allocation":36,"interventionModel":36,"interventionModelDescription":36,"primaryPurpose":36,"observationalModel":38,"timePerspective":39,"maskingInfo":36},"COHORT","PROSPECTIVE","Inflammatory bowel disease, including Crohn disease and ulcerative colitis, requires reliable assessment of intestinal inflammation to support clinical monitoring and treatment decisions. Intestinal ultrasound is a non-invasive, point-of-care imaging method that can assess bowel inflammation without radiation exposure. However, its interpretation may vary by operator experience and local scanning practice.\n\nThis prospective, multicentre, observational study will collect de-identified intestinal ultrasound images, cine loops, and limited associated metadata from adults aged 18 years and older. Eligible participants may be healthy individuals with no known inflammatory bowel disease or individuals undergoing intestinal ultrasound for inflammatory bowel disease screening, monitoring, or another clinical reason. Intestinal ultrasound examinations will be performed as part of routine clinical care. The study does not add a treatment intervention, investigational drug, experimental device, or clinically directed diagnostic procedure.\n\nFollowing informed consent, ultrasound images and cine loops generated during the routine examination will be exported in de-identified DICOM format. Limited information relevant to artificial intelligence development and validation, such as age, sex, self-reported race, pregnancy status, eligibility confirmation, and relevant scan-related or pre-existing clinical information, may also be recorded. Direct personal identifiers and personal health information will be removed before the data are transferred outside the clinical site.\n\nThe de-identified data will be reviewed for appropriate de-identification and formatting before secure transfer to Dova Health Intelligence Inc. The data will be annotated and used to develop, train, tune, and test computer vision algorithms designed to identify bowel structures and measure bowel wall thickness on intestinal ultrasound. The study will also assess the feasibility of developing algorithms to evaluate bowel wall layer stratification, luminal diameter, bowel wall flow, bowel wall scarring, gastrointestinal motility, and mesenteric fat proliferation.\n\nThe primary objective is to evaluate whether the computer vision algorithm prototype can measure bowel wall thickness with performance comparable to manual measurements by experienced sonographers. Secondary objectives include evaluating the quality, diversity, and usability of the collected ultrasound data for artificial intelligence development and assessing the feasibility of measuring additional intestinal ultrasound features.\n\nThe algorithms developed in this study are investigational and will not be used in routine clinical care during the study. No participant-level algorithm findings will be returned to participants, and participation is not expected to provide a direct clinical benefit. The primary foreseeable risk is a loss of confidentiality; this risk is mitigated through de-identification at the study site, verification of de-identification before transfer, secure file transfer, controlled access, and secure cloud-based storage. The study plans to enroll up to 95 participants internationally, including up to 30 participants at the British Columbia site.","The study population will consist of adults aged 18 years and older who are either healthy or undergoing intestinal ultrasound for inflammatory bowel disease screening, monitoring, or another clinical reason. Participants will be recruited through the IBD Centre of BC and other participating study sites. The study may include individuals with inflammatory bowel disease and healthy volunteers. The study aims to include a diverse participant population to support evaluation of artificial intelligence algorithm performance across different participant characteristics.",[43],{"label":44,"type":36,"description":45,"interventionNames":46},"Intestinal Ultrasound Participants","This cohort includes adults aged 18 years and older who are either healthy or undergoing intestinal ultrasound for inflammatory bowel disease screening, monitoring, or another clinical reason. Participants will undergo intestinal ultrasound as part of routine clinical care. With informed consent, de-identified ultrasound images and cine loops, along with limited associated information such as age, sex, self-reported race, and relevant scan-related details, will be collected for artificial intelligence algorithm development. No study drug, experimental treatment, or experimental device will be administered. The artificial intelligence algorithms will not be used to guide participant care or provide individual diagnostic results during the study.",[47],"Other: De-identified Intestinal Ultrasound Data Collection",[49],{"type":6,"name":50,"description":51,"armGroupLabels":52,"otherNames":36},"De-identified Intestinal Ultrasound Data Collection","Intestinal ultrasound images and cine loops will be collected from adults undergoing ultrasound as part of routine clinical care. Following informed consent, the images and cine loops will be de-identified and used for artificial intelligence algorithm development, training, tuning, and testing. The study does not assign participants to receive an intervention, and the ultrasound is not performed solely for research purposes. The artificial intelligence algorithms developed using the data will not be used to guide participant care or provide individual diagnostic results during the study.",[44],[54],{"name":55,"affiliation":56,"role":57},"Matthew J Smyth, MD","University of British Columbia, IBD Centre of BC","PRINCIPAL_INVESTIGATOR",[59],{"name":60,"role":61,"phone":62,"phoneExt":36,"email":63},"Cristian A Massaro, MSc","CONTACT","587-223-5248","iusresearch@ibdcentrebc.ca",[65],{"facility":66,"status":36,"city":67,"state":68,"zip":69,"country":70,"countryCode":71,"cosmosGeoPoint":72,"geoPoint":77,"contacts":78},"IBD Centre of BC","Vancouver","British Columbia","V6Z 2L2","Canada","CA",{"type":73,"coordinates":74},"Point",[75,76],-123.11934,49.24966,{"lat":76,"lon":75},[79,80],{"name":60,"role":61,"phone":62,"phoneExt":36,"email":63},{"name":55,"role":57,"phone":36,"phoneExt":36,"email":36},{"type":57,"investigatorFullName":82,"investigatorTitle":83,"investigatorAffiliation":5,"oldNameTitle":36,"oldOrganization":36},"Matthew Smyth","Assistant Clinical Professor",[85,87,89],{"name":66,"class":86},"UNKNOWN",{"name":88,"class":86},"Providence Health Care Ventures",{"name":90,"class":86},"Dova Health Intelligence Inc","100655349","prospective-intestinal-ultrasound-study-for-artificial-intelligence-algorithm-development-100655349",false,"NCT07814274","Prospective Intestinal Ultrasound Study for Artificial Intelligence Algorithm Development","Prospective Study for Intestinal Ultrasound Algorithm Development","PSIUSAD","Inclusion Criteria:\n\n* Adults aged 18 years or older.\n* Individuals who are either healthy with no known finding of inflammatory bowel disease before the ultrasound examination or undergoing intestinal ultrasound for inflammatory bowel disease screening, monitoring, or another clinical reason.\n* Individuals who are able and willing to provide informed consent for the collection and use of de-identified study data.\n\nExclusion Criteria:\n\n* Individuals who do not meet the study demographic requirements.\n* Individuals unable or unwilling to provide informed consent.\n* Pregnant individuals.\n* Individuals with health conditions managed using drugs or medical-device intervention, or with unmanaged conditions or conditions requiring monitoring, that could affect study eligibility or the ultrasound assessment.\n* Individuals who have recently taken contrast-enhancing compounds.",true,"ALL","18 Years",{"count":103,"type":104},95,"ESTIMATED","OBSERVATIONAL","This observational study will use intestinal ultrasound images to help develop computer programs that may make it easier to assess bowel inflammation.\n\nThe study will include adults who are healthy or who are having an intestinal ultrasound as part of care for inflammatory bowel disease, such as Crohn disease or ulcerative colitis. Researchers want to find out whether a computer program can measure bowel wall thickness from ultrasound images as accurately as experienced ultrasound clinicians. They will also explore whether the program can identify other changes in the bowel.\n\nParticipants will have an intestinal ultrasound as part of their usual care. People who agree to take part will allow the research team to use de-identified ultrasound images and a small amount of related health information. No medication, experimental treatment, or additional ultrasound procedure will be given for this study. The computer program will not be used to make decisions about a participant's care, and participants will not receive individual results from the program.",[108],"Inflammatory Bowel Disease (IBD)",[110,111,112,113,114,115,116,117],"Intestinal Ultrasound","Artificial Intelligence","Machine Learning","Bowel Wall Thickness","Crohn Disease","Ulcerative Colitis","Inflammatory Bowel Disease","Ultrasound","NOT_YET_RECRUITING","2026-09-09",{"date":121,"type":122},"2026-09-10","ACTUAL",{"date":124,"type":104},"2026-09-15",{"date":126,"type":104},"2027-02-01",{"name":5,"class":6},1]