Validating Osteoporosis Detection in Rho AI Software

University of Wisconsin (UW)

Status: Completed

Conditions: Osteopenia or Osteoporosis

Treatments: Device: Rho AI software

Study type: Interventional

Funder types: Other

Identifiers

NCT06830005

Protocol Version (Other Identifier)

A536100 (Other Identifier)

2024-1832

Details and patient eligibility

About

To assess the effectiveness of 16bit's Rho AI (artificial intelligence) software at identifying known cases of osteoporosis. 800 de-identified images from January 2007 to January 2024 will be accessed to test the software prospectively.

Full description

Osteoporosis is underrecognized and undertreated in the orthopedic surgery patient population. Osteoporosis is diagnosed by dual-energy x-ray absorptiometry which is costly and imparts radiation. Preoperative radiographs are universally obtained in orthopedic surgery patients, however up to this point radiographs have not been able to diagnose osteoporosis. This software program is a new technology that is able to leverage radiographs to opportunistically screen for osteoporosis.

The study team will identify applicable patient records from medical record review, and Radius will de-identify the x-ray images. The de-identified images will be run through the Rho AI program to identify osteoporosis or osteopenia, and a report will be generated to summarize the program's findings.

Enrollment: 800 patients

Sex: All

Ages: 50 to 90 years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• images from people who have undergone total joint arthroplasty
• images from people who have undergone spine fusion

Exclusion criteria

-

Trial design

Primary purpose: Basic Science

Allocation: N/A

Interventional model: Single Group Assignment

Masking: None (Open label)

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800 participants in 1 patient group

Experimental Detection of Osteoporosis

Experimental group

Treatment:

Device: Rho AI software