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

Not Recruiting

Trial ID: NCT03530098

Purpose

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.

Official Title

Prospective, Multi-Center, Randomized Controlled Trial for Skeletal Age Assessment AI Model

Stanford Investigator(s)

Curtis Langlotz
Curtis Langlotz

Professor of Radiology (Thoracic Imaging), of Medicine (Biomedical Informatics Research), of Biomedical Data Science and Senior Fellow at the Stanford Institute for HAI

Eligibility


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.

Intervention(s):

device: BoneAgeModel

Not Recruiting

Contact Information

Stanford University
School of Medicine
300 Pasteur Drive
Stanford, CA 94305
Safwan Halabi, M.D.
(650) 721-2850