DeepView Snapshot Handheld (DV-H) Comparison Study

Burns Clinical Trial

— DHA  

Official title:

DeepView Snapshot Handheld (DV-H) Comparison Study

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT06024512
• Other study ID #: CLA-PR-03
• Status: Completed
• Start date: June 13, 2023
• Est. completion date: January 25, 2024

Study information

• Verified date: August 2023
• Source: SpectralMD
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

his study is being done to collect pictures of burns using an investigational device called the Spectral MD Deep View Snapshot Handheld (DV-H), similar to a camera. The data collected will be used to assess the performance of the DV-H device, and to determine the device's ability to differentiate healing versus non-healing burn tissue. This device, if approved, is expected to give caregivers a better understanding of what parts of burn wounds will likely not heal on their own and as a tool used by the military in the field. This current study involves the collection of images over the course of your clinical treatment and follow-up according to your routine standard of care. The device will not be used to diagnose or prescribe treatment for your burn

Recruitment information / eligibility

• Status: Completed
• Enrollment: 18
• Est. completion date: January 25, 2024
• Est. primary completion date: January 25, 2024
• Gender: All
• Age group: 18 Years to 75 Years

Eligibility

Inclusion Criteria:

.Age >18 years and able to give informed consent or have a Legally Authorized Representative (LAR) able to do so;

• Life expectancy > 6 months;

• Thermal burn mechanism (flame, scald, or contact);

• The Study Burn(s) occurred less than 72 hours prior to the time of first imaging;

• Minimum burn wound size for patients is 0.5% TBSA per region

• Have 2 - 4 regions of their clinical burn(s) that meet the criteria for a Study Burn; and

Exclusion Criteria:

• Patients will be excluded if any of the following conditions apply:

• Burn pattern distribution isolated to head, face, neck, hands, feet, genitalia, and/or joints;

• Subject has burns involving > 50% total body surface area (TBSA);

• Sepsis at the time of enrollment determined by diagnosis made by Principal Investigator or Sub-Investigator;

• Immunosuppression/radiation/chemotherapy < 3 months prior to enrollment;

• Concurrent use of investigational products with a known effect on the burn sites; and/or

• Any condition that in the opinion of the Investigator may prevent compliance with the study requirements or compromise subject safety.

Related Conditions & MeSH terms

• Burns

Intervention

Device:
• Burn
This study is being done to collect pictures of burns using an investigational device called the Spectral MD Deep View Snapshot Handheld (DV-H), similar to a camera. The data collected will be used to assess the performance of the DV-H device, and to determine the device's ability to differentiate healing versus non-healing burn tissue. This device, if approved, is expected to give caregivers a better understanding of what parts of burn wounds will likely not heal on their own and as a tool used by the military in the field. This current study involves the collection of images over the course of your clinical treatment and follow-up according to your routine standard of care. The device will not be used to diagnose or prescribe treatment for your burn.

Locations

Country	Name	City	State
United States	LSU Health New Orleans University Medical Center New Orleans	New Orleans	Louisiana

Sponsors (1)

Lead Sponsor	Collaborator
SpectralMD

Country where clinical trial is conducted

United States, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	DeepView Snapshot Handheld (DV-SSH) Comparison Study Protocol	The primary objective of this study is to demonstrate that the proposed SA-MSI sensor is equivalent or better than the current LC-MSI sensor.; To conduct this test, we will compare the performance of the burn assessment AI algorithm using the image sensor as input data to the same Algorithm using the lens cluster data as an input.	3 months