An observational study in Trauma (Including Fractures), sponsored by Hôpital Universitaire Sahloul. Active, not recruiting at 1 site in Tunisia. Per ClinicalTrials.gov, last updated 2026-01-09.
Sponsored by Hôpital Universitaire Sahloul · Observational
Help build ClinicalTrials.gg — short surveys, remote interviews or testing, in your language. Take part →
This diagnostic study aims to compare the performance of an artificial intelligence (AI) algorithm designed to assist in the interpretation of traumatic bone radiographs (all anatomical regions excluding the thorax) with that of human readers, including emergency medicine and family medicine residents as well as senior physicians (one emergency medicine specialist and one orthopedic surgeon).
The study follows a paired reader study design: identical anonymized radiographic images are independently interpreted by the AI system and by human readers. The reference standard ("gold standard") will be defined by the consensus reading of the two senior physicians. Inter-observer agreement (kappa statistics) between the AI, residents, and senior reference readings will be estimated, and false negatives and false positives will be analyzed by lesion type and anatomical location.
This diagnostic accuracy study is designed to evaluate and compare the performance of an artificial intelligence (AI) algorithm with that of human readers in the interpretation of traumatic bone radiographs. The study focuses on radiographs of all skeletal anatomical regions except the thorax (e.g., skull, upper limbs, pelvis, and lower limbs) obtained in the context of acute trauma.
Study Design
The investigation will employ a paired reader design, meaning that each radiographic image will be interpreted independently by both the AI system and multiple human readers. This design allows direct, within-case comparison of diagnostic performance between the AI algorithm and human interpreters, minimizing variability related to case mix.
Study Population and Image Selection
Radiographs will be retrospectively collected from the hospital's Picture Archiving and Communication System (PACS). Eligible cases will include all conventional radiographs performed for suspected bone trauma over a defined inclusion period. Images must meet adequate technical quality standards and contain no patient-identifiable information. Exclusion criteria include incomplete imaging studies, thoracic images, and cases lacking definitive follow-up or diagnostic confirmation.
Image Preparation and Anonymization
All selected radiographs will be anonymized and assigned a random identification code. The dataset will be organized by anatomical region and then randomized to prevent recognition bias among readers.
Readers and Reading Procedure
Interpretations will be performed by:
Artificial Intelligence (AI) system: A deep learning algorithm trained to detect bone fractures and other traumatic findings on plain radiographs.
Human readers:
Two groups of resident physicians (emergency medicine and family medicine residents) with varying levels of training.
Two senior physicians, one emergency medicine specialist and one orthopedic surgeon, who will serve as expert readers.
Each image will be read independently by the AI algorithm and by each human reader, without access to clinical information or to the interpretations of others.
Reference Standard (Gold Standard)
The reference standard diagnosis for each radiograph will be established through a consensus review by the two senior physicians. In cases of initial disagreement, consensus will be reached through joint discussion, with review of clinical or additional imaging data if necessary.
Outcome Measures
The primary outcome measure will be the diagnostic accuracy of the AI algorithm compared with human readers for detecting bone fractures and other traumatic lesions, using the expert consensus as the gold standard.
Secondary Outcomes
Inter-observer agreement between the AI system and each human reader will be quantified using Cohen's kappa (κ) statistics.
Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) will be calculated for all readers and the AI.
Error analysis will be performed to characterize false negatives and false positives according to lesion type (e.g., cortical break, avulsion, dislocation) and anatomical location (e.g., wrist, ankle, pelvis).
Subgroup analyses will assess differences in performance by anatomical region and by reader experience level.
Statistical Analysis
Continuous variables will be expressed as means ± standard deviation or medians with interquartile ranges. Categorical data will be summarized as frequencies and percentages. Diagnostic performance metrics will be compared using appropriate statistical tests (e.g., McNemar's test for paired proportions). Confidence intervals (95%) will be calculated for all main estimates. A p-value \< 0.05 will be considered statistically significant.
Ethical Considerations
The study will be conducted in accordance with institutional and ethical guidelines for retrospective diagnostic research. Since all radiographs will be anonymized and analyzed retrospectively, informed consent requirements may be waived by the ethics committee.
2,217 studies on the registry are indexed under Wounds and Injuries; 441 are open to participants now.
This study's planned enrollment of 500 is above the median of 169 across 690 observational studies indexed under Wounds and Injuries.
Browse Wounds and Injuries studies →Hôpital Universitaire Sahloul is the lead sponsor of 17 studies on the registry; 2 are open to participants now.
Counted across the registry records on this site, refreshed daily.
Study Population and Eligibility Criteria
Inclusion Criteria:
Standard radiographs performed for suspected bone trauma (upper limbs, lower limbs, pelvis/hip, cervical/thoracolumbar spine) in the emergency setting.
Adult and pediatric patients (informed consent by patient or legal guardian for minors).
Acute trauma context.
Exclusion Criteria:
Poor-quality images (motion artifact, underexposure preventing diagnostic interpretation).
Cases lacking senior interpretation for gold standard reference.
Patients referred with radiographs performed outside the hospital (external facilities).
Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.
Exclusion Criteria:
Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Informed consent
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Residents (human readers)
Artificial Intelligence (AI) algorithm
Diagnostic sensitivity and specificity of the AI algorithm compared to human readers
Sensitivity and specificity for detection of traumatic bone lesions on radiographs, using the senior physicians' consensus reading as the reference standard (gold standard).
Time frame: At the end of image interpretation for each reader (expected within 1 month after image collection).
Plan to share: No
No publications or documents are linked to this record.
Started Nov 2025 (actual). Primary completion is estimated for Mar 2026, 4 months after the start.
Of 265 non-industry observational studies under Wounds and Injuries, half reached primary completion within 28 months of starting (the median), counting those still running; a quarter within 12 and three quarters within 60. This study's planned 4 months is below that.
Counting every sponsor, half of 312 studies reached it within 28 months; a quarter within 12 and three quarters within 60.
Wounds and Injuries covers many different conditions, not one, so the studies compared here vary widely. Read these figures as a rough guide.
How these figures are worked out, and which studies are left out of them.
This study is active, not recruiting, as verified in Nov 2025. You cannot join it, but the record below documents what was studied.
Get an email when the registry record changes — status, dates, results — or when someone posts here.
Sign in to followQuestions and observations about this study, from anyone following it. Not medical advice, and not a channel to the study team — their contact details are on the registry record.
Sign in to join the discussion. Reading takes no account; posting does. You choose a display name, and a pseudonym is the default.
Nothing here yet. If you are running this trial, taking part in it, or weighing whether to, this is the place to say so.
Hôpital Universitaire Sahloul