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N/A N=1,903 Randomized Diagnostic

Validation of an Artificial Intelligence-based Algorithm for Skeletal Age Assessment

Bone Age

Enrolled (actual)
1,903
Serious AEs
0.0%
Results posted
Oct 2020
Primary outcome: Primary: Paired Difference of Skeletal Age Estimate — 5.95; 5.36 months — p=0.04

Study Design & Population

Study type
Interventional
Phase
N/A
Interventions
BoneAgeModel (Device)
Age
Pediatric, Adult, Older Adult
Sex
All
Sponsor
Stanford University
Primary completion
Aug 2019

Outcome Measures

OutcomeResultp-value
PRIMARY
Paired Difference of Skeletal Age Estimate
5.95; 5.36 0.04 sig
SECONDARY
Time for Diagnosis
142; 102 0.001 sig

Summary

The purpose of this study is to understand the effects of using an Artificial Intelligence algorithm for skeletal age estimation as a computer-aided diagnosis (CADx) system. In this prospective real-time study, the investigators will send de-identified hand radiographs to the Artificial Intelligence algorithm and surface the output of this algorithm to the radiologist, who will incorporate this information with their normal workflows to make an estimation of the bone age. All radiologists involved in the study will be trained to recognize the surfaced prediction to be the output of the Artificial Intelligence algorithm. The radiologists' diagnosis will be final and considered independent to the output of the algorithm.

Eligibility Criteria

Exams that meet the following inclusion criteria will be included: (1) exams read by radiologists who interpret pediatric skeletal age exams and verbally consent to participate (2) exams that contain a procedure code or study description indicative of a skeletal age exam. Exams containing more than one radiograph will not be included. Exams for which a trainee provides a preliminary interpretation will be excluded. No further exclusion criteria will be applied on the basis of image quality metrics or manufacturers. No exclusion criteria will be applied on the basis of patient chronological age.
View full record on ClinicalTrials.gov →

Data sourced from ClinicalTrials.gov (NCT03530098). Outcome figures and adverse-event rates are extracted automatically from the registry's posted results and are provided for clinician reference, not as a substitute for the primary publication.

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