[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"trial:NCT06200116":3,"trial-entities:NCT06200116":148,"trial-summary:NCT06200116":153},{"id":4,"nct_id":4,"org_study_id":5,"brief_title":6,"official_title":6,"overall_status":7,"completion_date":8,"status_verified_date":9,"last_update_date":10,"start_date":11,"sponsor_name":12,"lead_sponsor_class":13,"has_dmc":14,"brief_summary":15,"detailed_description":16,"conditions":17,"keywords":20,"study_type":21,"primary_purpose":22,"phases":23,"enrollment_info":24,"interventions":27,"primary_outcomes":33,"secondary_outcomes":38,"sex":39,"minimum_age":22,"maximum_age":22,"healthy_volunteers":40,"eligibility_criteria":41,"std_ages":47,"locations":51,"central_contacts":139,"overall_officials":141,"references":143,"see_also_links":144},"NCT06200116","ROR2272","Evaluation of a Novel Auto Segmentation Algorithm for Normal Structure Delineation in Radiation Treatment Planning","RECRUITING","2027-11-30","2026-07","2026-07-08","2024-12-02","Mayo Clinic","OTHER",false,"This study measures the utility of a novel artificial intelligence (AI) algorithm for performing auto-segmentation of computed tomography (CT) scans for radiation therapy planning.","PRIMARY OBJECTIVE:\n\nI. To measure the observed utility of an AI algorithm for normal segmentation by recording study subjects' observations of its function.\n\nOUTLINE: This is an observational study.\n\nParticipants complete surveys about the performance\u002Ffunctionality of the auto-segmentation algorithm on study.",[18,19],"Malignant Solid Neoplasm","Hematopoietic and Lymphatic System Neoplasm",[],"OBSERVATIONAL",null,[],{"count":25,"type":26},200,"ESTIMATED",[28],{"type":13,"name":29,"description":30,"armGroupLabels":31},"Non-Interventional Study","Non-interventional study",[32],"Observational",[34],{"measure":35,"description":36,"timeFrame":37},"Proportion of success","Will be evaluated by question 1 of the end user survey, which evaluates the level of modification to the artificial intelligence generated auto-segmentation structures that was required (no modification, minor modification, or major modification). Auto-segmentation algorithm data will be collected through an electronic data collection form.","Baseline",[],"ALL",true,{"inclusion":42,"exclusion":44,"raw_text":46},[43],"Employment at Mayo Clinic Arizona, Florida, or Rochester (which includes Regional Practice sites located at Mayo Clinic Health System locations) as train clinical staff that participate in normal tissue segmentation",[45],"Inability to complete study surveys","Inclusion Criteria:\n\n* Employment at Mayo Clinic Arizona, Florida, or Rochester (which includes Regional Practice sites located at Mayo Clinic Health System locations) as train clinical staff that participate in normal tissue segmentation\n\nExclusion Criteria:\n\n* Inability to complete study surveys",[48,49,50],"CHILD","ADULT","OLDER_ADULT",[52,70,82,94,105,116,128],{"facility":53,"status":7,"city":54,"state":55,"zip":56,"country":57,"contacts":58,"geoPoint":67},"Mayo Clinic in Arizona","Scottsdale","Arizona","85259","United States",[59,64],{"name":60,"role":61,"phone":62,"email":63},"Clinical Trials Referral Office","CONTACT","855-776-0015","mayocliniccancerstudies@mayo.edu",{"name":65,"role":66},"Carlos E. Vargas, M.D.","PRINCIPAL_INVESTIGATOR",{"lat":68,"lon":69},33.50921,-111.89903,{"facility":71,"status":7,"city":72,"state":73,"zip":74,"country":57,"contacts":75,"geoPoint":79},"Mayo Clinic in Florida","Jacksonville","Florida","32224-9980",[76,77],{"name":60,"role":61,"phone":62,"email":63},{"name":78,"role":66},"Byron C. May, M.D.",{"lat":80,"lon":81},30.33218,-81.65565,{"facility":83,"status":7,"city":84,"state":85,"zip":86,"country":57,"contacts":87,"geoPoint":91},"Mayo Clinic Health System in Albert Lea","Albert Lea","Minnesota","56007",[88,89],{"name":60,"role":61,"phone":62,"email":63},{"name":90,"role":66},"Timothy F. Kozelsky, M.D.",{"lat":92,"lon":93},43.64801,-93.36827,{"facility":95,"status":7,"city":96,"state":85,"zip":97,"country":57,"contacts":98,"geoPoint":102},"Mayo Clinic Health Systems-Mankato","Mankato","56001",[99,100],{"name":60,"role":61,"phone":62,"email":63},{"name":101,"role":66},"Ron S. Smith, M.D.",{"lat":103,"lon":104},44.15906,-94.00915,{"facility":106,"status":7,"city":107,"state":85,"zip":108,"country":57,"contacts":109,"geoPoint":113},"Mayo Clinic in Rochester","Rochester","55905",[110,111],{"name":60,"role":61,"phone":62,"email":63},{"name":112,"role":66},"Doug J. Moseley, PhD",{"lat":114,"lon":115},44.02163,-92.4699,{"facility":117,"status":7,"city":118,"state":119,"zip":120,"country":57,"contacts":121,"geoPoint":125},"Mayo Clinic Health System-Eau Claire Clinic","Eau Claire","Wisconsin","54701",[122,123],{"name":60,"role":61,"phone":62,"email":63},{"name":124,"role":66},"Zachary C. Wilson, M.D.",{"lat":126,"lon":127},44.81135,-91.49849,{"facility":129,"status":7,"city":130,"state":119,"zip":131,"country":57,"contacts":132,"geoPoint":136},"Mayo Clinic Health System-Franciscan Healthcare","La Crosse","54601",[133,134],{"name":60,"role":61,"phone":62,"email":63},{"name":135,"role":66},"Abigail L. Stockham, M.D.",{"lat":137,"lon":138},43.80136,-91.23958,[140],{"name":60,"role":61,"phone":62,"email":63},[142],{"name":112,"affiliation":106,"role":66},[],[145],{"label":146,"url":147},"Mayo Clinic Clinical Trials","https:\u002F\u002Fwww.mayo.edu\u002Fresearch\u002Fclinical-trials",{"nct_id":4,"conditions":149,"biomarkers":152},[150,151],"Hematologic Neoplasm","Solid Neoplasm",[],{"nct_id":4,"found":40,"summary":154,"prompt_version":164},{"design":155,"status":156,"heading":157,"summary":158,"follow_up":159,"word_count":160,"commitments":161,"compensation":162,"drugs_mentioned":163},"This is an observational study with a planned enrollment of 200 participants. It is not a randomized or blinded study.","completed","Observational Study of AI for Radiation Treatment Planning","This study is looking at a new artificial intelligence (AI) tool that helps with radiation treatment planning for people with cancer. Specifically, it's testing how well this AI tool can automatically outline normal body parts (organs and tissues) on CT scans. The goal is to see how useful this AI algorithm is in practice. This is an observational study, meaning researchers will watch and record how the AI tool works without directly intervening. The study aims to enroll 200 participants who are clinical staff at Mayo Clinic locations and involved in normal tissue segmentation. Success for this study is measured by the proportion of times the AI tool is observed to work well. The current status of this study is unclear.","The primary success is measured at Baseline, implying no long-term follow-up after initial observation.",121,"You would complete surveys about how well the auto-segmentation algorithm performs and functions.","Not stated in the trial record.",[],"v2"]