Clinical Trial Details
— Status: Completed
Administrative data
| NCT number |
NCT03530098 |
| Other study ID # |
IRB #44764 |
| Secondary ID |
|
| Status |
Completed |
| Phase |
N/A
|
| First received |
|
| Last updated |
|
| Start date |
July 12, 2018 |
| Est. completion date |
August 31, 2019 |
Study information
| Verified date |
May 2021 |
| Source |
Stanford University |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Interventional
|
Clinical Trial 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.
Description:
The investigators are targeting to study the effect of their Artificial Intelligence
algorithm on the radiologists' estimation of skeletal age. Currently, radiologists make the
estimation using only the radiographic images and health records. As part of this study, the
radiologists will estimate skeletal age from radiographic images, health records, and the
output of the CADx algorithm. The investigators wish to understand how radiologists using the
Artificial Intelligence algorithm compare to radiologists who do not for the specific task of
estimating skeletal age.
This study is organized as a multi-institutional randomized control trial with two arms -
experiment (receiving the Artificial Intelligence algorithm's output) and control (no
intervention). Both of these arms will be compared to a clinical reference standard ("gold
standard") composed of a panel of radiologists. The metric of comparison will be Mean
Absolute Distance (MAD). The investigators plan to use statistical tests such as the t-test
to determine any statistically-significant difference in skeletal age estimation between the
two groups.
The investigators have recruited and analyzed data from a sample size of 1600 exams. Patients
getting these exams will not undergo any research procedures that deviate from the current
standard practices.
