[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100517439":3},{"organization":4,"armGroups":7,"interventions":14,"overallOfficials":21,"centralContacts":25,"locations":36,"responsibleParty":59,"collaborators":20,"id":61,"slug":62,"hasResults":63,"nctId":64,"briefTitle":65,"officialTitle":66,"acronym":67,"eligibilityCriteria":68,"healthyVolunteers":63,"sex":69,"minAge":70,"maxAge":20,"enrollmentInfo":71,"targetDuration":20,"studyType":74,"phases":75,"briefSummary":77,"conditions":78,"keywords":20,"overallStatus":39,"whyStopped":20,"lastUpdateSubmitDate":81,"lastUpdatePostDateStruct":82,"startDateStruct":85,"completionDateStruct":87,"leadSponsor":89,"locationsCount":90},{"fullName":5,"class":6},"Fondazione Policlinico Universitario Agostino Gemelli IRCCS","OTHER",[8],{"label":9,"type":10,"description":11,"interventionNames":12},"Clinical Stage III-IV Ovarian Cancer","EXPERIMENTAL","individuals who have been diagnosed or are suspected to have Clinical Stage III-IV Ovarian Cancer and CT and MRI have most commonly been used to identify sites and amounts of tumors in the abdomen and can help determine if these tumors can be safely removed by surgery. However, these imaging methods are only a prediction, and sometimes a diagnostic laparoscopy (putting a camera in the abdomen to look at all sites of disease) is performed to help this decision process.",[13],"Diagnostic Test: Artificial Intelligence",[15],{"type":16,"name":17,"description":18,"armGroupLabels":19,"otherNames":20},"DIAGNOSTIC_TEST","Artificial Intelligence","With the introduction of artificial intelligence and machine learning, there is a possibility to create more precise prediction models using images from these diagnostic laparoscopy videos. In particular, it would like to use images from the diagnostic laparoscopy to create machine-learning models to help predict if the tumors can be successfully taken out at primary surgery, or if chemotherapy before surgery would be needed. During surgery time the surgical team takes images however, what makes this different is that these images will be used to help create an algorithm to predict surgical outcomes. These images will be stored in a secure database with an anonymous number not linking these pictures to any of the participants.",[9],null,[22],{"name":23,"affiliation":5,"role":24},"Anna Fagotti, Prof","PRINCIPAL_INVESTIGATOR",[26,32],{"name":27,"role":28,"phone":29,"phoneExt":30,"email":31},"Liat Hogen, MD","CONTACT","416-946-4501","2242","liat.hogen@uhn.ca",{"name":33,"role":28,"phone":29,"phoneExt":34,"email":35},"Ferdous Parveen, MBBS","3329","ferdous.parveen@uhn.ca",[37],{"facility":38,"status":39,"city":40,"state":20,"zip":41,"country":42,"countryCode":43,"cosmosGeoPoint":44,"geoPoint":49,"contacts":50},"Fondazione Policlinico Universitario A. Gemelli IRCCS, UOC Ginecologia Oncologica","RECRUITING","Roma","00168","Italy","IT",{"type":45,"coordinates":46},"Point",[47,48],11.10642,44.99364,{"lat":48,"lon":47},[51,54,57],{"name":23,"role":28,"phone":52,"phoneExt":20,"email":53},"+390630155701","anna.fagotti@policlinicogemelli.it",{"name":55,"role":28,"phone":20,"phoneExt":20,"email":56},"Riccardo Oliva","riccardo.oliva@policlinicogemelli.it",{"name":58,"role":24,"phone":20,"phoneExt":20,"email":20},"Anna Fagotti",{"type":60,"investigatorFullName":20,"investigatorTitle":20,"investigatorAffiliation":20,"oldNameTitle":20,"oldOrganization":20},"SPONSOR","100517439","predicting-outcome-of-cytoreduction-in-advanced-ovarian-cancer-100517439",false,"NCT06017557","Predicting Outcome of Cytoreduction in Advanced Ovarian Cancer","Predicting Outcome of Cytoreduction in Advanced Ovarian Cancer, Using a Machine Learning Algorithm and Patterns of Disease Distribution at Laparoscopy (PREDAtOOR)","PREDAtOOR","Inclusion Criteria:\n\n* Patients treated at Fondazione Policlinico Gemelli Hospital, Rome Italy, Trillium -Credit Valley Hospital, Mississauga, Ontario and Princess Margaret Cancer Centre, Toronto, Canada\n* Patients fit for cytoreductive surgery\n* Patients with a primary diagnosis of suspect Stage III-IV ovarian cancer\n* Patients selected for interval cytoreductive surgery after NACT\n\nExclusion Criteria:\n\n* Patients with pre-operative Stage I-II disease confined to the pelvis\n* Patients unfit for surgery\n* Lack of information about patients' surgical outcomes and clinicopathological characteristics\n* LGSOC, Clear cell and mucinous, non-epithelial histologic subtypes (if available)","FEMALE","18 Years",{"count":72,"type":73},151,"ESTIMATED","INTERVENTIONAL",[76],"NA","PREDAtOOR is a pilot study and this study aims at improving the selection of the best treatment strategy for patients with advanced ovarian cancer by using Camera Vision (CV) to predict outcomes of cyto reduction at the time of Diagnostic laparoscopy.",[79,80],"Ovarian Cancer Stage III","Ovarian Cancer Stage IV","2025-12-15",{"date":83,"type":84},"2025-12-19","ACTUAL",{"date":86,"type":84},"2023-01-02",{"date":88,"type":73},"2026-09-01",{"name":5,"class":6},1]