[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"cephalometry\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:cephalometry":44},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,1,0,[8],{"id":9,"slug":4,"hasResults":10,"nctId":11,"briefTitle":12,"officialTitle":13,"acronym":4,"eligibilityCriteria":14,"healthyVolunteers":10,"sex":15,"minAge":4,"maxAge":4,"enrollmentInfo":16,"targetDuration":4,"studyType":19,"phases":4,"briefSummary":20,"conditions":21,"keywords":26,"overallStatus":32,"whyStopped":4,"lastUpdateSubmitDate":33,"lastUpdatePostDateStruct":34,"startDateStruct":37,"completionDateStruct":39,"leadSponsor":41,"locationsCount":5},"100644086",false,"NCT07664488","Comparison of Digital Analysis and Artificial Intelligence for Cephalometric Tracing","Cephalometric Tracing: A Comparison Between Digital Analysis and Artificial Intelligence","Inclusion Criteria:\n\n* Availability of digital lateral cephalometric radiographs of adequate diagnostic quality\n* Radiographs acquired with patients in centric occlusion and proper head positioning using a cephalostat\n* Patients of any age and sex\n* Absence of congenital or acquired craniofacial anomalies\n* No previous orthodontic treatment\n* No previous orthognathic surgical treatment\n* Absence of agenesis of incisors or first molars\n* Absence of supernumerary teeth overlapping the region of interest\n\nExclusion Criteria:\n\n* Radiographs presenting artifacts or inadequate visualization of anatomical structures\n* History of significant craniofacial trauma\n* Radiographs acquired without a cephalostat\n* Presence of severe skeletal asymmetries\n* Incomplete clinical or radiographic records\n* Radiographs unsuitable for manual or AI-based cephalometric landmark identification","ALL",{"count":17,"type":18},100,"ESTIMATED","OBSERVATIONAL","This study aims to evaluate the accuracy and reliability of artificial intelligence (AI)-based cephalometric analysis compared with digital manual tracing. A total of 100 standardized lateral cephalometric radiographs will be analyzed using Delta-Dent software with manual landmark identification and three fully automated AI-based systems (WebCeph, QuantX, and Smartee). Sagittal, vertical, dental, and soft tissue cephalometric parameters will be compared among the different methods. Statistical analysis will assess inter-method agreement and the clinical relevance of any observed discrepancies. The study seeks to determine whether AI-based systems provide measurements comparable to conventional digital tracing and whether they can be considered reliable adjunctive tools in orthodontic diagnosis and treatment planning.",[22,23,24,25],"Cephalometric Analysis","Cephalometry","Artificial Intelligence (AI)","Artificial Intelligence (AI) in Diagnosis",[27,28,29,30,31],"artificial intelligence","cephalometric analysis","lateral cephalogram","landmark identification","automated cephalometric tracing","RECRUITING","2026-06-17",{"date":35,"type":36},"2026-06-24","ACTUAL",{"date":38,"type":36},"2026-06-01",{"date":40,"type":18},"2026-09-30",{"name":42,"class":43},"University of Pavia","OTHER",""]