Burns MultipleAMBUSHNCT05167461
AutoMated BUrn Diagnostic System for Healthcare (AMBUSH)
An observational study of Burns Multiple and Burns, run by Indiana University at 1 site in United States.
Trial summary
The primary objective of this study is to develop a high accuracy and automated system that can provide early assessment of burn injuries with at least 90% accuracy in absence of burn experts, using AI and FDA cleared harmonic ultrasound TDI data based on the analysis of mechanical and hemodynamic properties of the… Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Burns Multiple, Burns, Thermal Burn
- What is being tested?
- Collection of imaging by ultrasonography
- How many people
- 30 participants
- Where
- 1 siteUnited States
- Study dates
- 24 May 2022to 25 May 2023
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Subjects aged 18 years and above, male and female, with a thermal burn injury will be considered for participation in this study. Enrollment of 30 subjects is planned
Subjects must meet all the following enrollment criteria to be eligible for participation in the study:
- Male or female patients aged 18 years and above.
- The patient has a thermal burn injury
- Antibiotic use allowed
- Patient does not need to have the ability to communicate
- Inpatient or outpatient
- Within 7 days of burn
- No prior surgical debridement
- Burn ≤ 75% of body surface
- The patient or their legal representative agrees to comply with all compulsory study procedures and visit schedule
- The patient or their legal representative agrees to abstain from enrollment in any other clinical trial for the duration of the study.
- In the opinion of the investigator, the patient or their legal representative must be able to:
- Understand the full nature and purpose of the study, including possible risks and adverse events,
- Understand instruction, and
- Provide voluntary informed written consent/assent as appropriate for study participation.
Exclusion Criteria: Subjects who meet any of the following criteria are not eligible for participation in the study:
- Unable to provide informed consent
- Age <18 years
- Burn ≥ 75% of body surface
- Burns caused by chemicals, electricity or radiation.
- Patients presenting with only 3rd-degree/full-thickness wounds which require immediate autografting.
- Burn injury has had prior surgical treatment.
- Prisoners
- Pregnant individuals
- Unable to follow study schedule or understand study instructions
Trial locations and contacts
1 site in 1 country.
About this study
Official title: AutoMated Burn Diagnostic System for Healthcare
The primary objective of this study is to develop a high accuracy and automated system that can provide early assessment of burn injuries with at least 90% accuracy in absence of burn experts, using AI and FDA cleared harmonic ultrasound TDI data based on the analysis of mechanical and hemodynamic properties of the subcutaneous burned tissue. Data collected in this study will lead to the development of better diagnostic tools that could inform clinical burn practices by enabling doctors to determine burn depth and the need for surgery with greater speed and accuracy, resulting in better clinical outcomes.
Read the detailed description
Burn injuries are considered as one of the most complex type of traumatic injuries. In the United States (US), about 1.25 million people are treated each year for burns, and 40,000 are hospitalized for the treatment of these injuries resulting in high medical costs, approximately $7.9 billion per year. Early and accurate treatment of burns is critical to prevent infections and improve the possible outcomes of the patient, decreasing the mortality rate by about 36% In this regard, prioritizing burns that require a surgical procedure to heal, i.e. burn excision and skin grafting, is critical. This constitutes a challenging task because it involves the determination of the burn depth, for which experienced burn surgeons achieve an accuracy of 67-76%, value that decreases to 50% for inexperienced surgeons. Assessment of the burn depth is one of the most important aspects of burn care. It is a predictor of pathological scarring that occurs in 30%-91% of burn injuries. However, it continues to be an open clinical challenge for which an accurate solution has yet to be found. Burns are classified into three different categories: superficial burns, which involve only epidermis; partial-thickness burns, which affect epidermis and dermis; and full-thickness burns, which include deep structures such as subcutaneous, muscles, and bone. The first two are expected to heal without scarring by 14-21 days after the burn injury, while the last one will heal with scarring resulting in significant morbidity to the patient, including pain, loss of joint mobility, loss of function, and social isolation. For this reason, full-thickness burns are excised, and exposed body parts are covered with skin grafts to prevent further complications with scarring Currently, burn depth is determined by clinical assessment, based on appearance, blanching to pressure, sensation to pin prick, and bleeding on needle prick. This visual and tactile inspection approach introduces inter-subject variability, especially when partial-thickness burns are involved. Overestimation of burn depth leads to unnecessary surgery of excision of viable skin and replacement with skin grafts that look different from surrounding skin. These grafts are less pliable with lack of the ability to sweat for thermoregulation, while underestimation leads to surgical delay, long length of hospital stays, high treatment costs, scarring, and poor functional and aesthetic outcomes. This issue is exacerbated by a phenomenon known as burn conversion, which is not fully understood yet, and it is usually not accounted for in the assessment process or in the clinical decision support technologies. Burn injury is a dynamic process, the longer the delay in intervening, the more abundant the scar tissue formation and the more likely the patient is to have deformity with loss of mobility and function. Thus, early prediction of burn conversion is critical for surgical decision making and burn follow up. Several non-invasive light-based imaging technologies have been developed to support clinical assessment, which is currently the most common technique for burn depth assessment. They operate based on the existing correlation among blood perfusion, functional blood vessels, and burn depth. However, Laser Doppler Imaging (LDI) is the only one approved by FDA. It is the most widely adopted non-invasive technology in burn treatment facilities in the US, but it is used as the preferred modality in only 6% of them. Considering the many limitations of this technology, this is not unexpected. It uses light/optic principles to detect the active blood flow in the damaged tissue of the patient, and the results can be greatly altered by the curvature of tissues, ambient light and temperature, motion artifacts, topical wound dressings, non-debrided tissue, skin color, pigment from tattoos, and blisters. In addition, LDI performance is poor when burn injuries are less than 24 hours old and can be difficult to interpret for inexperienced users. To overcome the limitations of light-based technologies, the investigators will integrate novel techniques in Artificial Intelligence (AI), Computer Vision, with FDA approved Harmonic B-mode ultrasound (HUSD B-mode) and Harmonic Ultrasound Tissue Doppler Elastography imaging (TDI), medical expertise in the wound care, tissue injury management, and burn surgery domains. This will enhance the burn assessment accuracy, improving the patient's prognosis.
- Conditions
- Burns Multiple, Burns, Thermal Burn, Burn Infection
- Being tested
- Collection of imaging by ultrasonography
- Keywords
- burns, thermal burn
- Medical subject headings
- Burns
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Collection of imaging by ultrasonographyOther
Also called deep machine learning
The investigators will collect burn image data to be processed through the software combined with the deep machine learning to find automated diagnostic burn assessment with accuracy of >95% compared to human assessment
What is being measured
The primary outcome is the main question the study is designed to answer.
Compare human assessment of burn depth to AI assessment
Compare human assessment of burn depth to the technology output (Artificial Intelligence and TDI) as determined by need for surgery (time points include day 0 +/- 3 days). Biopsy collected from patients that go to OR (one-time collection) to verify the burn depth via histological analysis.
Measured: 2 year
Secondary outcomes (1)
Confirm burn conversion
: Confirm burn conversion by the presence of infection as found in the electronic medical record (EMR). Confirm burn infection by sending one tissue biopsy from OR (one-time collection)
Measured: 2 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted22 Dec 2021
- Study start24 May 2022
- Primary completion25 May 2023
- Study completion25 May 2023
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Burns MultipleStudies of the same condition, open and under way.
- More trials run by Indiana UniversityThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case crossover
- Time perspective
- Prospective
- Enrolment
- 30 participants (actual)
Sponsor and investigators
- Lead sponsor
- Indiana University
- Sponsor type
- University, hospital or other
- Collaborators
- Eskenazi Health
- Responsible party
- Principal investigator, Gayle Gordillo, Indiana University
- Investigators
- Gayle Gordillo, MD, Principal investigator, Indiana University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05167461
- Sponsor's protocol ID
- 12689
- Acronym
- AMBUSH
- Status last verified
- Oct 2023
- First submitted
- 5 Nov 2021
- Last updated
- 23 Oct 2023
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: We will share the artificial intelligence data regarding how the AI performed in comparison to the human evaluators
Publications
Rahman MM, Masry ME, Gnyawali SC, Xue Y, Gordillo G, Wachs JP. AI-Driven Integrated System for Burn Depth Prediction With Electronic Medical Records: Algorithm Development and Validation. JMIR Med Inform. 2025 Aug 15;13:e68366. doi: 10.2196/68366.
PubMed 40815778
Study at a glance
From the registry record, last updated by the sponsor on 23 Oct 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- AutoMated Burn Diagnostic System for Healthcare
- ClinicalTrials.gov ID
- NCT05167461
- Acronym / sponsor ID
- AMBUSH / 12689
- Conditions
- Burns Multiple, Burns, Thermal Burn, Burn Infection
- Keywords
- burns, thermal burn
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 30 participants (actual)
- Lead sponsor
- Indiana UniversityUniversity, hospital or other
- Collaborators
- Eskenazi Health
- Study start
- 24 May 2022 (actual)
- Primary completion
- 25 May 2023 (actual)
- Study completion
- 25 May 2023 (actual)
- First posted
- 22 Dec 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The primary objective of this study is to develop a high accuracy and automated system that can provide early assessment of burn injuries with at least 90% accuracy in absence of burn experts, using AI and FDA cleared harmonic ultrasound TDI data based on the analysis of mechanical and hemodynamic properties of the subcutaneous burned tissue. Data collected in this study will lead to the development of better diagnostic tools that could inform clinical burn practices by enabling doctors to determine burn depth and the need for surgery with greater speed and accuracy, resulting in better clinical outcomes.
Detailed description
Burn injuries are considered as one of the most complex type of traumatic injuries. In the United States (US), about 1.25 million people are treated each year for burns, and 40,000 are hospitalized for the treatment of these injuries resulting in high medical costs, approximately $7.9 billion per year. Early and accurate treatment of burns is critical to prevent infections and improve the possible outcomes of the patient, decreasing the mortality rate by about 36% In this regard, prioritizing burns that require a surgical procedure to heal, i.e. burn excision and skin grafting, is critical. This constitutes a challenging task because it involves the determination of the burn depth, for which experienced burn surgeons achieve an accuracy of 67-76%, value that decreases to 50% for inexperienced surgeons. Assessment of the burn depth is one of the most important aspects of burn care. It is a predictor of pathological scarring that occurs in 30%-91% of burn injuries. However, it continues to be an open clinical challenge for which an accurate solution has yet to be found. Burns are classified into three different categories: superficial burns, which involve only epidermis; partial-thickness burns, which affect epidermis and dermis; and full-thickness burns, which include deep structures such as subcutaneous, muscles, and bone. The first two are expected to heal without scarring by 14-21 days after the burn injury, while the last one will heal with scarring resulting in significant morbidity to the patient, including pain, loss of joint mobility, loss of function, and social isolation. For this reason, full-thickness burns are excised, and exposed body parts are covered with skin grafts to prevent further complications with scarring Currently, burn depth is determined by clinical assessment, based on appearance, blanching to pressure, sensation to pin prick, and bleeding on needle prick. This visual and tactile inspection approach introduces inter-subject variability, especially when partial-thickness burns are involved. Overestimation of burn depth leads to unnecessary surgery of excision of viable skin and replacement with skin grafts that look different from surrounding skin. These grafts are less pliable with lack of the ability to sweat for thermoregulation, while underestimation leads to surgical delay, long length of hospital stays, high treatment costs, scarring, and poor functional and aesthetic outcomes. This issue is exacerbated by a phenomenon known as burn conversion, which is not fully understood yet, and it is usually not accounted for in the assessment process or in the clinical decision support technologies. Burn injury is a dynamic process, the longer the delay in intervening, the more abundant the scar tissue formation and the more likely the patient is to have deformity with loss of mobility and function. Thus, early prediction of burn conversion is critical for surgical decision making and burn follow up. Several non-invasive light-based imaging technologies have been developed to support clinical assessment, which is currently the most common technique for burn depth assessment. They operate based on the existing correlation among blood perfusion, functional blood vessels, and burn depth. However, Laser Doppler Imaging (LDI) is the only one approved by FDA. It is the most widely adopted non-invasive technology in burn treatment facilities in the US, but it is used as the preferred modality in only 6% of them. Considering the many limitations of this technology, this is not unexpected. It uses light/optic principles to detect the active blood flow in the damaged tissue of the patient, and the results can be greatly altered by the curvature of tissues, ambient light and temperature, motion artifacts, topical wound dressings, non-debrided tissue, skin color, pigment from tattoos, and blisters. In addition, LDI performance is poor when burn injuries are less than 24 hours old and can be difficult to interpret for inexperienced users. To overcome the limitations of light-based technologies, the investigators will integrate novel techniques in Artificial Intelligence (AI), Computer Vision, with FDA approved Harmonic B-mode ultrasound (HUSD B-mode) and Harmonic Ultrasound Tissue Doppler Elastography imaging (TDI), medical expertise in the wound care, tissue injury management, and burn surgery domains. This will enhance the burn assessment accuracy, improving the patient's prognosis.
Study design
- Observational model
- Case crossover
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Subjects aged 18 years and above, male and female, with a thermal burn injury will be considered for participation in this study. Enrollment of 30 subjects is planned
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Collection of imaging by ultrasonographyAlso: deep machine learningThe investigators will collect burn image data to be processed through the software combined with the deep machine learning to find automated diagnostic burn assessment with accuracy of >95% compared to human assessment | Other | – |
Primary outcome
Compare human assessment of burn depth to AI assessment
Time frame: 2 year
Compare human assessment of burn depth to the technology output (Artificial Intelligence and TDI) as determined by need for surgery (time points include day 0 +/- 3 days). Biopsy collected from patients that go to OR (one-time collection) to verify the burn depth via histological analysis.
1 secondary outcome
Confirm burn conversion
Time frame: 2 years
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 23 Oct 2023.
- Derived from this study: PubMed 40815778Rahman MM, Masry ME, Gnyawali SC, Xue Y, Gordillo G, Wachs JP. AI-Driven Integrated System for Burn Depth Prediction With Electronic Medical Records: Algorithm Development and Validation. JMIR Med Inform. 2025 Aug 15;13:e68366. doi: 10.2196/68366.
- Individual participant dataSharing planned: Yes. We will share the artificial intelligence data regarding how the AI performed in comparison to the human evaluators
Related trials for Burns Multiple
Enrolling by invitationObservational study
Evaluating the Accuracy of Multiple Blood Tests to Diagnose Sepsis in Adult Burn Patients
Sepsis - to Reduce Mortality in the Intensive Care Unit, Burns Involving 20% or More of Body Surface
Not yet recruiting
Response of Muscle Mechanical Properties to Early Multi-angles Isometric Exercises in Acute Burn Patients
Burns
Not yet recruitingObservational study
Project PHOENIX: Molecular Signatures of Burn Pit Exposure
Burn Pit Exposure, Airborne Hazard Exposure
Not yet recruiting
Reduction of Muscle Catabolism Through Brain Activation in Burn Patients
Burns - Multiple, Critical Illness
Not yet recruitingObservational study
Surgical Critical Care Initiative (SC2i) Tissue and Data Acquisition Protocol (TDAP) in Burn Patients Improving the Robustness and Generalizability of Post-burn Sepsis Prediction With the Post-Burn Sepsis Digital Twin. Group 1
Sepsis, Burn Injury
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Gayle Gordillo, MD principal investigator
Indiana University
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Burns Multiple and Burns, run by Indiana University at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 23 Oct 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Compare human assessment of burn depth to AI assessment (time frame: 2 year). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05167461, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 23 Oct 2023.