Validating Osteoporosis Detection in Rho AI Software

NCT ID: NCT06830005

Last Updated: 2026-01-15

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

800 participants

Study Classification

INTERVENTIONAL

Study Start Date

2025-06-01

Study Completion Date

2025-12-01

Brief Summary

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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.

Detailed Description

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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.

Conditions

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Osteopenia or Osteoporosis

Study Design

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Allocation Method

NA

Intervention Model

SINGLE_GROUP

Primary Study Purpose

BASIC_SCIENCE

Blinding Strategy

NONE

Study Groups

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Experimental Detection of Osteoporosis

Group Type EXPERIMENTAL

Rho AI software

Intervention Type DEVICE

Rho is a AI enabled opportunistic pre-screening computer-aided detection and notification software for low bone mineral density.

Interventions

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Rho AI software

Rho is a AI enabled opportunistic pre-screening computer-aided detection and notification software for low bone mineral density.

Intervention Type DEVICE

Eligibility Criteria

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Inclusion Criteria

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

Exclusion Criteria

\-
Minimum Eligible Age

50 Years

Maximum Eligible Age

90 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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University of Wisconsin, Madison

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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James Bernatz, MD

Role: PRINCIPAL_INVESTIGATOR

UW School of Medicine and Public Health

Locations

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UW School of Medicine and Public Health

Madison, Wisconsin, United States

Site Status

Countries

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United States

Other Identifiers

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A536100

Identifier Type: OTHER

Identifier Source: secondary_id

Protocol Version

Identifier Type: OTHER

Identifier Source: secondary_id

2024-1832

Identifier Type: -

Identifier Source: org_study_id

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