Bone Enhanced Ultrasound (BEUS) Data Library Development Project
A common treatment for low back pain involves fluoroscopy-guided spinal facet joint injections and/or medial branch nerve blocks. Unfortunately, fluoroscopy requires expensive equipment and personnel and exposes patients and healthcare providers to ionizing radiation. Ultrasound offers a safer, lower-cost alternative, but the traditional 2-dimensional (2D) ultrasound systems are limited due to poor image quality, particularly in patients with higher body mass index (BMI).
As an alternative, a novel Bone Enhanced Ultrasound (BEUS) technology uses artificial intelligence (AI) to create real-time 3-dimensional (3D) images of the spine to guide needle placement for these injections. The AI software is trained by overlaying computed tomography (CT) and ultrasound images from a patient dataset to recognize anatomical landmarks. BEUS aims to ultimately replace fluoroscopy for spinal injections, reducing radiation exposure, lowering healthcare costs, and improving accessibility, especially in rural settings where CT and fluoroscopy are unavailable.
A key limitation, however, is that the current AI system is trained based primarily on patients (mostly pediatric) undergoing perioperative assessment of scoliosis. To address this, the current study aims to develop a new, more clinically relevant training AI dataset by collecting spinal ultrasounds from up to 100 adult participants (most/all of whom are followed at the local chronic pain clinic for low back pain) with existing spinal CT or magnetic resonance imaging (MRI) scans. This dataset will be used to retrain the current AI model to enhance the accuracy of 3D spinal reconstructions, thereby improving the clinical relevance of the BEUS system.
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Study Type
Study Type
Enrollment (Estimated)
Enrollment
Contacts and Locations
Study Contact
Study Contact
- Name: Eileen S Kim, Dr.
- Phone Number: 613-850-3282
- Email: eileenseungmin.kim@kingstonhsc.ca
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- Individuals who have had previous CT or MRI scans of their spine in the past 5 years
Exclusion Criteria:
- < 18 years old
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
Study group
Individuals who have had a CT or MRI scans of their spine in the past 5 years
|
Coronal, axial, sagittal scans of the spine using ultrasound
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Time Frame |
|---|---|
|
Accuracy of 3D ultrasound spine reconstruction in adults with chronic low back pain
Time Frame: From enrollment to end of US scan (30 days)
|
From enrollment to end of US scan (30 days)
|
Collaborators and Investigators
Sponsor
Sponsor
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
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- 6043729
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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