Artificial Intelligence-assisted Ultrasound Diagnosis of Musculoskeletal Injuries. (ECO-IA)
Artificial Intelligence-assisted Ultrasound Diagnosis of Musculoskeletal Injuries for Physiotherapy, Traumatology and Orthopaedic Practice (ECO-IA).
The proposal combines clinical research in physiotherapy, traumatology and orthopaedics with artificial intelligence, computer vision and health-data science.
Study Overview
Status
Status
Conditions
Conditions
Detailed Description
ECO-IA is submitted as an individual research project under the "Non-oriented research" modality. The project addresses a relevant gap in clinical musculoskeletal care: ultrasound is widely available, safe, radiation-free and useful for the assessment of tendons, muscles, ligaments and joints, but its diagnostic value depends strongly on operator training, image-acquisition protocol and interpretative experience.
The proposal combines clinical research in physiotherapy, traumatology and orthopaedics with artificial intelligence, computer vision and health-data science. It aims to develop, validate and prepare for clinical translation an AI-based decision-support system capable of assisting healthcare professionals in the identification and characterisation of common musculoskeletal injuries from ultrasound images. This is consistent with the purpose of the call: generating new knowledge while creating opportunities for predoctoral research training.
Study Type
Study Type
Enrollment (Estimated)
Enrollment
Contacts and Locations
Study Contact
Study Contact
- Name: JORGE VELÁZQUEZ SAORNIL, PhD.
- Phone Number: 923277100
- Email: jvelazquezsa@upsa.es
Study Contact Backup
- Name: Jorge Velázquez, PhD.
- Email: jvelazquezsa@upsa.es
Study Locations
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-
Salamanca
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Salamanca, Salamanca, Spain, 37002
- Universidad Pontificia de Salamanca
-
Contact:
- Jorge Velázquez Saornil, PhD.
- Phone Number: 923277100
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
Patients with musculoskeletal pain affecting tendons, muscles, ligaments or bursae
Description
Inclusion Criteria:
- Patients with musculoskeletal pain affecting tendons, muscles, ligaments or bursae
Exclusion Criteria:
- Patients with severe, acute pain consistent with an open fracture; surgical procedures in the area under examination and diagnosis. Uncooperative patients who do not sign the informed consent form.
Study Plan
How is the study designed?
Design Details
- Observational Models: COHORT
- Time Perspectives: CROSS_SECTIONAL
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
|---|
|
IA Group
Diagnosis by IA |
|
Medical Expert Group
Diagnosis by a medical expert |
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Diagnostic imaging
Time Frame: 1 day
|
Ability to carry out a medical diagnosis based on imaging findings |
1 day
|
Collaborators and Investigators
Sponsor
Sponsor
Investigators
Investigators
- Principal Investigator: Jorge Velázquez Saornil, Principal investigator, Universidad Pontíficia de Salamanca
Publications and helpful links
General Publications
- Humphries MP, Kaye D, Stankeviciute G, Halliwell J, Wright AI, Bansal D, Brettle D, Treanor D. Development of a multi-scanner facility for data acquisition for digital pathology artificial intelligence. J Pathol. 2024 Sep;264(1):80-89. doi: 10.1002/path.6326. Epub 2024 Jul 10.
- Berezowska S, Cathomas G, Grobholz R, Henkel M, Jochum W, Koelzer VH, Kreutzfeldt M, Mertz KD, Rossle M, Soldini D, Zlobec I, Janowczyk A. Digital image analysis and artificial intelligence in pathology diagnostics-the Swiss view. Pathologie (Heidelb). 2023 Dec;44(Suppl 3):222-224. doi: 10.1007/s00292-023-01262-w. Epub 2023 Nov 21.
- Shafi S, Parwani AV. Artificial intelligence in diagnostic pathology. Diagn Pathol. 2023 Oct 3;18(1):109. doi: 10.1186/s13000-023-01375-z.
Study record dates
Study Major Dates
Study Start (Estimated)
Study Start
Primary Completion (Estimated)
Primary Completion
Study Completion (Estimated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Other Study ID Numbers
Other Study ID Numbers
- UPSA05112026
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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