Validation of an Artificial Intelligence-based Algorithm for Skeletal Age Assessment
| Status: | Enrolling by invitation |
|---|---|
| Healthy: | No |
| Age Range: | 1 - 18 |
| Updated: | 2/22/2019 |
| Start Date: | July 12, 2018 |
| End Date: | July 2019 |
Prospective Clinical Validation of an Artificial Intelligence-based Algorithm for Skeletal Age Assessment
The purpose of this study is to understand the effects of using a 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 a
diagnosis of the patient's 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.
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 a
diagnosis of the patient's 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.
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 patients' radiographic images and health records. As part of this
study, the radiologists will make diagnoses about their patients using the patients'
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) and Root-Mean-Square (RMS) error. 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 hope to recruit and analyze data from a sample size of 1000 patients.The
patients will not undergo any research procedures that deviate from the current standard
practices.
algorithm on the radiologists' estimation of skeletal age. Currently, radiologists make the
estimation using only the patients' radiographic images and health records. As part of this
study, the radiologists will make diagnoses about their patients using the patients'
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) and Root-Mean-Square (RMS) error. 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 hope to recruit and analyze data from a sample size of 1000 patients.The
patients will not undergo any research procedures that deviate from the current standard
practices.
Inclusion Criteria:
- Patients between the age of 1 years and 18 years
- Patients referred to get a hand radiograph taken for skeletal age assessment
Exclusion Criteria:
- Patients with age less than 1 year or greater than 18 years
- Patients not referred to get a hand radiograph taken for skeletal age assessment
We found this trial at
6
sites
New York University More than 175 years ago, Albert Gallatin, the distinguished statesman who served...
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Emory University Emory University, recognized internationally for its outstanding liberal artscolleges, graduate and professional schools,...
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3333 Burnet Avenue # Mlc3008
Cincinnati, Ohio 45229
Cincinnati, Ohio 45229
1-513-636-4200
Cincinnati Children's Hospital Medical Center Patients and families from across the region and around the...
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Boston Children's Hospital Boston Children's Hospital is a 395-bed comprehensive center for pediatric health care....
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Stanford University Stanford University, located between San Francisco and San Jose in the heart of...
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