Spectral AI Announces Successful Results from its Burn Validation Study of the DeepView System

Rhea-AI Summary

Spectral AI (NASDAQ: MDAI) has announced successful results from its Burn Validation Study of the DeepView® System, a revolutionary AI-driven device that predicts burn healing potential using multi-spectral imaging. The study, one of the largest burn trials in U.S. history, involved 164 patients (115 adult, 49 pediatric) across multiple burn centers.

The DeepView System significantly outperformed burn physicians in identifying non-healing tissue, demonstrating:

• 86.6% image-wise sensitivity vs. 40.8% for physicians
• 81.9% pixel-wise sensitivity vs. 38.8% for physicians
• 68.5% Dice Score vs. 39.2% for physicians
• 61.2% image-wise specificity vs. anticipated 36.0%

The company plans to submit these results to the FDA by Q2 2025, targeting De Novo Classification approval in early 2026, followed by immediate commercialization upon approval.

Positive

• DeepView System significantly outperformed physicians in burn assessment accuracy
• Large-scale validation study completed with 164 patients
• Technology ready for FDA submission by Q2 2025
• Immediate commercialization preparedness upon potential FDA approval
• Federal funding support from BARDA under contract

Negative

• FDA approval not guaranteed
• Commercialization timeline dependent on regulatory approval
• Lower specificity (61.2%) compared to physicians (79.1%)

Insights

Financial Analyst

Spectral AI's successful completion of its Burn Validation Study represents a significant clinical milestone that substantially derisks the company's path to commercialization. The study's results demonstrating the DeepView System's superior performance over burn physicians—with 86.6% versus 40.8% sensitivity in identifying non-healing tissue—provides compelling evidence of the technology's value proposition.

The clear regulatory timeline with FDA submission expected by Q2 2025 and potential De Novo clearance in early 2026 establishes a concrete pathway to market. Investors should note that government backing through BARDA funding (contract 75A50123C00049) adds credibility and financial support for Spectral AI's development efforts.

For a company with a market cap of only $31.9 million, this validation study significantly reduces technical risk. The DeepView System's proprietary database of 340 billion clinically validated data points creates a substantial intellectual property moat. If approved, this AI-driven diagnostic tool could transform the standard of care in burn assessment while creating new revenue streams through both equipment sales and potentially recurring revenue from each use case.

The De Novo regulatory pathway indicates this is a novel device without predicates, which while presenting some regulatory uncertainty, also underscores the innovative nature of the technology and potential first-mover advantages in the marketplace. Spectral AI's statement about being prepared to commercialize immediately upon approval suggests manufacturing arrangements are already in place, reducing operational risk.

Medical Device Expert

The DeepView System's performance metrics in the Burn Validation Study reveal impressive technological capabilities with profound clinical implications. The system achieved more than double the sensitivity of experienced burn physicians (81.9% vs 38.8% at pixel level) in identifying non-healing tissue, which addresses a critical clinical challenge in burn assessment.

While physicians demonstrated higher specificity (79.1% vs 61.2%), this reflects their traditionally conservative approach. The superior Dice Score (68.5% vs 39.2%) indicates better overall accuracy in wound area assessment. These performance differentials could translate to significant improvements in clinical decision-making, potentially reducing unnecessary treatments while ensuring appropriate intervention for tissues unlikely to heal.

The system's non-invasive, cart-based design offers considerable workflow advantages in acute care settings. The technology's ability to provide objective assessment on day one of injury could dramatically compress the assessment timeline, enabling faster treatment decisions and potentially reducing complications from delayed interventions.

The inclusion of 49 pediatric patients in the study is particularly noteworthy, as burn assessment in children presents unique challenges due to anatomical and physiological differences. The study's comprehensive design across multiple burn centers strengthens the validity of its findings and suggests the technology could be deployed across various healthcare settings, from specialized burn units to emergency departments, expanding its potential market reach.

• DeepView^® System outperforms burn physicians in identifying non-healing tissue
• Landmark Burn Validation Study, one of the largest in U.S. history, confirms DeepView’s performance
• Spectral AI plans FDA submission by mid-2025, targeting De Novo Clearance and rapid commercialization to transform burn care
  

DALLAS, March 17, 2025 (GLOBE NEWSWIRE) -- Spectral AI (NASDAQ: MDAI) (“Spectral AI” or the “Company”), developer of the AI-driven DeepView^® System, that uses multi-spectral imaging and AI algorithms to predict burn healing potential, announced the successful results of the performance of its DeepView System in connection with the completion of its Burn Validation Study. Spectral AI’s DeepView System is being developed as a predictive device to offer clinicians an immediate and objective assessment of a burn wound’s healing potential prior to treatment or other medical intervention. The image processing algorithm employed by the DeepView System utilizes multispectral imaging that is trained and tested against a proprietary database of more than 340 billion clinically validated data points. The DeepView System is non-invasive and cart-based, allowing for exceptional mobility within the healthcare setting.

The Burn Validation Study, which began in January 2024 and concluded in March 2025, represented one of the largest burn trials ever conducted in the United States. The Company enrolled and analyzed data obtained from 164 total patients comprised of 115 adult and 49 pediatric patients in burn centers and emergency departments across the U. S. in its Burn Validation Study. The goal of the Burn Validation Study was to further demonstrate the innovative and versatile nature of Spectral AI’s DeepView technology, as well as its ability to predict burn wound healing potential on the first day of injury with greater performance and speed than the methods currently used today. The Burn Validation Study results, together with rigorous statistical analysis, illustrate that the DeepView System continues to outperform the clinical judgment of burn physicians by a large margin.

The Burn Validation Study results assessed the sensitivity, specificity and Dice score of the DeepView System at both a pixel-level and image-wise level against the clinical judgment of burn physicians. Key findings included the following:

• Sensitivity: The DeepView System demonstrated a statistically significant improvement in identifying non-healing tissue compared to burn physicians, as judged on sensitivity. At the image-wise level, the DeepView System scored 86.6% while clinical judgment annotation (CJA) of burn physicians scored 40.8%. At the pixel-wise level, the DeepView System scored 81.9% and CJA of burn physicians scored 38.8%.
• Dice Score: The DeepView System achieved statistically significant higher Dice Scores when compared to those derived from burn physicians’ CJA, representing the improved pixel-wise evaluation between predicated and true segmented wound areas with the DeepView System performing at 68.5% and burn physician’s CJA at 39.2%.
• Specificity: The Deepview System significantly outperformed the anticipated results for image-wise specificity in segmenting non-healing wound areas with a result of 61.2% (versus an anticipated result of 36.0%) and CJA of 79.1% reflecting burn physician’s conversative assessment of burn areas.
  

“We believe these are excellent results and we are thrilled with the analysis of our DeepView System in our Burn Validation Study,” said Dr J. Michael DiMaio, M.D. “The DeepView System exceeded our expectations in terms of predictive performance. Following the FDA’s review, if authorized by the agency, our hope is that this tool will provide an objective and immediate prediction of non-healing burn tissue to expedite patient care and reduce system costs across the board. I would like to thank Jeffrey C. Carter, MD, FACS, the principal investigator for the Burn Validation Study, our entire team at Spectral AI, and especially the patients and esteemed clinicians who participated in this Study. We look forward to bringing this predictive diagnostic tool to the United States marketplace as soon as possible.”

Spectral AI plans to submit these results to the FDA as part of its regulatory submission by the end of the second quarter of 2025 and hopes to have the FDA grant the De Novo Classification Request of the DeepView System in early 2026. Based on its current manufacturing arrangements, Spectral AI will be prepared to commercialize the DeepView System in the United States, if ultimately approved, as soon as approval is obtained.  

This project is being supported in whole or in part with federal funds from the Department of Health and Human Services; Administration for Strategic Preparedness and Response; BARDA, under contract number 75A50123C00049.

About Spectral AI

Spectral AI, Inc. is a Dallas-based predictive AI company focused on medical diagnostics for faster and more accurate treatment decisions in wound care, with initial applications involving patients with burns. The Company is working to revolutionize the management of wound care by “Seeing the Unknown^®” with its DeepView^® System. The DeepView^® System is being developed as a predictive device to offer clinicians an objective and immediate assessment of a burn wound’s healing potential prior to treatment or other medical intervention. With algorithm-driven results and a goal of exceeding the current standard of care in the future, the DeepView^® System is expected to provide fast and accurate treatment insight towards value care by improving patient outcomes and reducing healthcare costs. For more information about the DeepView^® System, visit www.spectral-ai.com.

Forward-Looking Statements

Certain statements made in this release are “forward looking statements” within the meaning of the “safe harbor” provisions of the United States Private Securities Litigation Reform Act of 1995, including statements regarding the Company’s strategy, plans, objectives, initiatives and financial outlook. When used in this press release, the words “estimates,” “projected,” “expects,” “anticipates,” “forecasts,” “plans,” “intends,” “believes,” “seeks,” “may,” “will,” “should,” “future,” “propose” and variations of these words or similar expressions (or the negative versions of such words or expressions) are intended to identify forward-looking statements. These forward-looking statements are not guarantees of future performance, conditions or results, and involve a number of known and unknown risks, uncertainties, assumptions and other important factors, many of which are outside Company’s control, that could cause actual results or outcomes to differ materially from those discussed in the forward-looking statements. As such, readers are cautioned not to place undue reliance on any forward-looking statements.

Investors should carefully consider the foregoing factors, and the other risks and uncertainties described in the “Risk Factors” sections of the Company’s filings with the SEC, including the Registration Statement and the other documents filed by the Company. These filings identify and address other important risks and uncertainties that could cause actual events and results to differ materially from those contained in the forward-looking statements.

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FAQ

What were the key performance metrics of Spectral AI's (MDAI) DeepView System in the Burn Validation Study?

The DeepView System achieved 86.6% image-wise sensitivity, 81.9% pixel-wise sensitivity, 68.5% Dice Score, and 61.2% image-wise specificity, significantly outperforming burn physicians' clinical judgment.

How many patients were included in Spectral AI's (MDAI) Burn Validation Study?

The study included 164 total patients: 115 adult and 49 pediatric patients across U.S. burn centers and emergency departments.

When does Spectral AI (MDAI) expect FDA approval for the DeepView System?

Spectral AI plans FDA submission by Q2 2025 and expects De Novo Classification approval in early 2026.

What is the technological basis of Spectral AI's (MDAI) DeepView System?

DeepView uses multi-spectral imaging and AI algorithms trained on over 340 billion clinically validated data points to predict burn healing potential non-invasively.