[{"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":24},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,1,0,[8],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":14,"acronym":4,"eligibilityCriteria":15,"healthyVolunteers":11,"sex":16,"minAge":4,"maxAge":4,"enrollmentInfo":17,"targetDuration":4,"studyType":20,"phases":4,"briefSummary":21,"conditions":22,"keywords":27,"overallStatus":33,"whyStopped":4,"lastUpdateSubmitDate":34,"lastUpdatePostDateStruct":35,"startDateStruct":38,"completionDateStruct":40,"leadSponsor":42,"locationsCount":5},"100644086","comparison-of-digital-analysis-and-artificial-intelligence-for-cephalometric-tracing-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":18,"type":19},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.",[23,24,25,26],"Cephalometric Analysis","Cephalometry","Artificial Intelligence (AI)","Artificial Intelligence (AI) in Diagnosis",[28,29,30,31,32],"artificial intelligence","cephalometric analysis","lateral cephalogram","landmark identification","automated cephalometric tracing","RECRUITING","2026-06-17",{"date":36,"type":37},"2026-06-24","ACTUAL",{"date":39,"type":37},"2026-06-01",{"date":41,"type":19},"2026-09-30",{"name":43,"class":44},"University of Pavia","OTHER"]