Clinical Validation of RBfracture for Diagnosing Trauma-related Musculoskeletal Injuries

Clinical Validation of RBfracture to Demonstrate Improved Diagnostic Performance of the Intended Users

The goal of this study is to determine if the computer software, RBfracture, developed by Radiobotics, helps primary care, emergency, and radiology clinicians more easily identify bone injuries caused by a traumatic impact (such as a fall or car collision). RBfracture uses artificial intelligence (AI) to analyze X-ray images of patients to identify fractures and joint dislocations visible on the X-ray images. RBfracture also identifies fluid buildup in the elbow and knee joints resulting from a fracture or dislocation.

Sixteen clinicians will review X-ray images from 415 adult patients, who may have sustained a bone injury, to diagnose any injuries visible on their X-ray images. First, the clinicians will review half of the images with and half of the images without the help of the RBfracture software. After a 4-week break, the clinicians will once again review the same images. This time, the software's help will be switched, so it is unavailable for the images the clinicians previously reviewed with it, and available for the images they reviewed without it.

The number of correct and incorrect diagnoses made by the clinicians when they were helped by the software will be compared to the number of correct and incorrect diagnoses made by the clinicians when they did not receive any help from the software. This comparison will reveal if using the software helps clinicians to diagnose more injuries and miss less injuries.

Study Overview

• Status: Not yet recruiting
• Conditions: Joint Effusion; Fracture; Joint Dislocation; Knee Lipohemarthrosis
• Intervention / Treatment: Diagnostic test: RBfracture

Detailed Description

RBfracture, developed by Radiobotics (Copenhagen, Denmark), is a decision-support software solution for computerized detection and diagnosis of acute fractures, joint dislocations, joint effusion, and lipohemarthrosis. To demonstrate improved diagnostic performance of the intended users when assisted by RBfracture, a fully-crossed multi-reader multi-case (MRMC) study will be conducted. 415 study exams will be retrospectively obtained through stratified sampling with enrichment to represent all anatomical regions supported by the software. Sixteen independent clinicians representing various clinical roles and years of experience will participate as study readers.

The reference standard will be established by American Board of Radiology (ABR)-certified radiologists with a minimum of 3 years of experience post certification. All exams will be reviewed and annotated by two musculoskeletal (MSK) radiologists, independently. Annotations will be done in a medical-grade reading environment, using diagnostic quality monitors. If required, any disagreement will be adjudicated by a third specialized radiologist.

In both assisted and unassisted sessions, readers will localize every unique fracture, joint dislocation, joint effusion, and lipohemarthrosis. For each finding, readers will provide a bounding box and a confidence score (1-5). Additionally, at the exam level, readers will indicate the presence or absence of each injury type along with a confidence score (0-100).

At the case level, ROC curves will be generated for each reader under both device-assisted and unassisted reading scenarios. The AUC of the ROC curve per reader in each reading scenario, and the difference in the reader-averaged AUC between device-assisted and unassisted reading scenarios will be calculated. The difference in reader-averaged AUC between the two reading scenarios will be reported as the primary outcome to demonstrate improved diagnostic performance of the intended users. Exam-level sensitivity, specificity, and average false positives, and injury-level sensitivity and AUC-AFROC will be presented as secondary outcomes.

• Study Type: Observational
• Enrollment (Estimated): 415

Contacts and Locations

• Study Contact: Name: Janitha M Mudannayake, PhD; Phone Number: +46708412511; Email: jm@radiobotics.com

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: Yes

• Sampling Method: Probability Sample

Study Population

X-ray exams of adult patients suspected of having trauma-related musculoskeletal injuries.

Description

Inclusion Criteria:

• XR exams of a patient ≥22 years of age following a recent acute musculoskeletal trauma.
• Modality is digitally acquired radiographs (Computed Radiography or Digital Radiography)

Exclusion Criteria:

• XR exam types that are outside of the intended use (e.g., chest, abdomen, facial bones, cervical spine).
• Exams with missing patient age.
• Exams from follow-up patient examinations, e.g., post-surgical controls or evaluation of fracture healing.
• Any exams containing radiographs previously used in software development.
• Exams containing additional radiographs that are incoherent with the XR exam type (e.g., wrist radiograph in a hip and pelvis exam type).
• Radiograph views that are unsupported.
• Poor radiographic image quality, rendering radiograph clinically unsuitable (e.g., inappropriate selection of technical exposure factors, patient motion, presence of artefacts, and improper collimation of the radiographic beam).

Study Plan

How is the study designed?

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
device-assisted; In the device-assisted modality, study readers will interpret patient X-ray exams with RBfracture assistance.	Diagnostic test: RBfracture; RBfracture is a decision support software designed to assist the intended user in diagnosing fracture, joint dislocation, joint effusion, and lipohemarthrosis.
device-unassisted; In the device-unassisted modality, study readers will interpret patient X-ray exams without RBfracture assistance.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Change in diagnostic accuracy between device-assisted and device-unassisted readers at the exam level.	The difference in the reader-averaged AUC between device-assisted and device-unassisted readers is significant at a one-sided p value of 0.025.	one month

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Change in diagnostic accuracy between device-assisted and device-unassisted readers at the exam level.	The difference in reader-averaged sensitivity and specificity between device-assisted and device-unassisted readers.	one month
Change in diagnostic accuracy between device-assisted and device-unassisted readers at the injury level.	The difference in reader-averaged AUC-AFROC, sensitivity, and false positives per exam between device-assisted and device-unassisted readers.	one month
Generalizability of device performance across demographic and technical factors	At the exam level, the difference in AUC, sensitivity, and specificity between device-assisted and device-unassisted readers, with data stratified by reader qualification, patient sex, patient ethnicity (if available), and radiographic machine manufacturer.	one month

Collaborators and Investigators

• Sponsor: Radiobotics

Study record dates

Study Major Dates

• Study Start (Estimated): February 1, 2026
• Primary Completion (Estimated): April 1, 2026
• Study Completion (Estimated): April 1, 2026

Study Registration Dates

• First Submitted: February 12, 2026
• First Submitted That Met QC Criteria: February 12, 2026
• First Posted (Actual): February 19, 2026

Study Record Updates

• Last Update Posted (Actual): February 27, 2026
• Last Update Submitted That Met QC Criteria: February 24, 2026
• Last Verified: February 1, 2026

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Musculoskeletal Diseases; Wounds and Injuries; Joint Diseases; Fractures, Bone; Joint Dislocations; Hydrarthrosis
• Other Study ID Numbers: 20254568

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No