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

NCT03530098 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 1903

Last updated 2021-06-09

Study results available
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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.

Conditions

  • Bone Age

Interventions

DEVICE

BoneAgeModel

BoneAgeModel is an Artificial Intelligence tool that takes in a hand radiograph and gender, and outputs the skeletal (bone) age. The intervention involves using this tool as a factor in the clinical decision making process of the participating radiologists. The radiologist's decision will be considered final.

Sponsors & Collaborators

Principal Investigators

  • Curtis Langlotz, M.D. Ph.D. · Stanford University

  • David Eng, B.S. · Stanford University

  • Nishith Khandwala, B.S. · Stanford University

  • Safwan Halabi, M.D. · Stanford University

Study Design

Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
NONE
Model
PARALLEL

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2018-07-12
Primary Completion
2019-08-31
Completion
2019-08-31
FDA Device
Yes

Countries

  • United States

Study Locations

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Entities

Companies

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT03530098 on ClinicalTrials.gov