[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100592117":3},{"organization":4,"armGroups":7,"interventions":10,"overallOfficials":12,"centralContacts":33,"locations":42,"responsibleParty":126,"collaborators":10,"id":128,"slug":129,"hasResults":130,"nctId":131,"briefTitle":132,"officialTitle":133,"acronym":134,"eligibilityCriteria":135,"healthyVolunteers":130,"sex":136,"minAge":137,"maxAge":10,"enrollmentInfo":138,"targetDuration":10,"studyType":141,"phases":10,"briefSummary":142,"conditions":143,"keywords":145,"overallStatus":45,"whyStopped":10,"lastUpdateSubmitDate":150,"lastUpdatePostDateStruct":151,"startDateStruct":154,"completionDateStruct":156,"leadSponsor":158,"locationsCount":159},{"fullName":5,"class":6},"ThrombUS+","OTHER",[8],{"label":9,"type":10,"description":11,"interventionNames":10},"Patients with suspected DVT referred for a DVT ultrasound scan.",null,"Patients with suspected DVT referred for a DVT ultrasound scan will be consecutively selected to account for demographics, medical condition and ultrasound operator diversity in the sample; data selected will be anonymized and included in the data set.\n\nIn and out-patients referred for an ultrasound scan for suspected DVT will be asked to participate (informed consent process).",[13,17,21,24,27,30],{"name":14,"affiliation":15,"role":16},"Eleni Kaldoudi, Prof.","ATHENA Research Center, Greece","STUDY_DIRECTOR",{"name":18,"affiliation":19,"role":20},"Andrius Macas, Prof. Dr.","Lithuanian University of Health Science [Lietuvos Sveikatos Mokslu Universitetas], Lithuania","PRINCIPAL_INVESTIGATOR",{"name":22,"affiliation":23,"role":20},"Michail Potoupnis, Prof.","School of Medicine, Aristotle University of Thessaloniki and Papageorgiou General Hospital, Greece",{"name":25,"affiliation":26,"role":20},"Elvira Grandone, Prof.","Home Relief of Suffering Hospital [Fondazione Casa Sollievo Della Sofferenza], Italy",{"name":28,"affiliation":29,"role":20},"Maxime Gautier, Dr.","Simon Veil Hospital, France",{"name":31,"affiliation":32,"role":20},"Savvas Defteraios, Prof.","University General Hospital of Alexandroupoli, Greece",[34,38],{"name":14,"role":35,"phone":36,"phoneExt":10,"email":37},"CONTACT","+306937124358","kaldoudi@athenarc.gr",{"name":39,"role":35,"phone":40,"phoneExt":10,"email":41},"Stelios Didaskalou, Dr.","+30 697 163 5361","stelios.didaskalou@athenarc.gr",[43,62,78,93,109],{"facility":44,"status":45,"city":46,"state":10,"zip":47,"country":48,"countryCode":49,"cosmosGeoPoint":50,"geoPoint":55,"contacts":56},"Groupement Hospitalier Eaubonne Montmorency Simone Veil","RECRUITING","Montmorency","95160","France","FR",{"type":51,"coordinates":52},"Point",[53,54],2.3434,48.98826,{"lat":54,"lon":53},[57,61],{"name":58,"role":35,"phone":59,"phoneExt":10,"email":60},"Maxime Gautier","+33 134066763","maxime.gautier@ch-simoneveil.fr",{"name":28,"role":20,"phone":10,"phoneExt":10,"email":10},{"facility":63,"status":45,"city":64,"state":10,"zip":65,"country":66,"countryCode":67,"cosmosGeoPoint":68,"geoPoint":72,"contacts":73},"University General Hospital of Alexandroupoli","Alexandroupoli","GR 68100","Greece","GR",{"type":51,"coordinates":69},[70,71],25.87644,40.84995,{"lat":71,"lon":70},[74,77],{"name":31,"role":35,"phone":75,"phoneExt":10,"email":76},"+30 6948054408","sdefter@med.duth.gr",{"name":31,"role":20,"phone":10,"phoneExt":10,"email":10},{"facility":79,"status":45,"city":80,"state":10,"zip":81,"country":66,"countryCode":67,"cosmosGeoPoint":82,"geoPoint":86,"contacts":87},"Papageorgiou General Hospital","Thessaloniki","54603",{"type":51,"coordinates":83},[84,85],22.93493,40.64072,{"lat":85,"lon":84},[88,92],{"name":89,"role":35,"phone":90,"phoneExt":10,"email":91},"Maria Bigaki, Mrs","+30 6932478047","pmo@papageorgiou-hospital.gr",{"name":22,"role":20,"phone":10,"phoneExt":10,"email":10},{"facility":94,"status":45,"city":95,"state":10,"zip":96,"country":97,"countryCode":98,"cosmosGeoPoint":99,"geoPoint":103,"contacts":104},"Home Relief of Suffering Hospital","San Giovanni Rotondo","FG 71013","Italy","IT",{"type":51,"coordinates":100},[101,102],15.7277,41.70643,{"lat":102,"lon":101},[105,108],{"name":25,"role":35,"phone":106,"phoneExt":10,"email":107},"+39 0882416286","e.grandone@operapadrepio.it",{"name":25,"role":20,"phone":10,"phoneExt":10,"email":10},{"facility":110,"status":45,"city":111,"state":10,"zip":112,"country":113,"countryCode":114,"cosmosGeoPoint":115,"geoPoint":119,"contacts":120},"Lithuanian University of Health Science","Kaunas","44307","Lithuania","LT",{"type":51,"coordinates":116},[117,118],23.90909,54.90156,{"lat":118,"lon":117},[121,125],{"name":122,"role":35,"phone":123,"phoneExt":10,"email":124},"Andrius Macas, Prof.","+ 37 037327305","andrius.macas@lsmu.lt",{"name":122,"role":20,"phone":10,"phoneExt":10,"email":10},{"type":127,"investigatorFullName":10,"investigatorTitle":10,"investigatorAffiliation":10,"oldNameTitle":10,"oldOrganization":10},"SPONSOR","100592117","a-multi-center-cohort-study-for-conventional-ultrasound-image-set-collection-to-create-a-data-set-for-research-purposes-100592117",false,"NCT06989255","A Multi-center Cohort Study for Conventional Ultrasound Image Set Collection to Create a Data Set for Research Purposes.","A Multi-center Cohort Study for Conventional Ultrasound Image Set Collection to Create a Training Data Set for Research Purposes (Image Processing and Analysis, AI Model Training).","ThrombUS_A","Inclusion Criteria:\n\n* Age ≥18 years.\n* The participant has the capacity to consent, and consent is obtained prior to any study-specific procedures.\n* The conventional diagnostic DVT algorithm indicates that an ultrasound is needed, or the patient has been referred for a scan on suspicion of DVT.\n\nExclusion Criteria:\n\n* Patients with a known condition or reason that may potentially result in interrupting or stopping the ultrasound examination before its completion.\n* Patients considered by their treating physician or the ultrasound operator as non-suitable for a standard ultrasound scan.\n* Patients who have not signed the informed consent.","ALL","18 Years",{"count":139,"type":140},3000,"ESTIMATED","OBSERVATIONAL","This study aims to collect and create a labelled ultrasound image data set containing ultrasound image series and video clips of patients that undergo routine ultrasound scans on lower limbs, because of suspected deep vein thrombosis.\n\nThe data will be used to train an AI model within ThrombUS+ project to achieve automated detection of deep vein thrombosis on conventional ultrasound scans.\n\nPrimary objectives:\n\n1. Collect and curate imaging data from ultrasound scans of patients suspected for DVT.\n2. Collect accompanying metadata on patient demographics, referral note, existing known medical conditions at the time of scan, diagnosis based on the scan, operator anonymized ID, metadata on the ultrasound equipment used.\n3. Anonymize the data set according to established regulations to be used for research purposes and in specific for training an artificial intelligence model to achieve automated DVT detection.\n\nSecondary objectives:\n\n1\\. Describe the data set in the Argos\u002FOpenAIRE tool and make it publicly available through the European Open Science Cloud (EOSC) portal via OpenAIRE, to be used by other researchers for image processing, analysis, and artificial intelligence (AI) model training.",[144],"Deep Vein Thrombosis",[146,147,148,149],"deep vein thrombosis","ultrasound scan","lower limb","compression ultrasound","2025-05-16",{"date":152,"type":153},"2025-05-25","ACTUAL",{"date":155,"type":153},"2024-11-06",{"date":157,"type":140},"2025-12-31",{"name":5,"class":6},5]