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Background <p>Accurate diagnosis of burn depth in the early post-burn phase is critical for guiding treatment decisions and optimal healing outcomes in patients. Current clinical assessment methods are often subjective, delayed, and prone to low diagnostic accuracy. A rapid and objective method of assessment to distinguish burn depths could significantly improve the standard of care.</p> Methods <p>We developed a non-invasive Resonance Raman Spectroscopic (RRS) protocol to assess burn depth using a compact and portable device. It provides Hemoglobin Index (HI), a metric of hemoglobin concentration in the wound bed. Since blood supply to the wound can depend on the severity of vascular damage, HI can be used to categorize burns by depth. We tested this approach in a clinically relevant Yucatan mini-pig model of multi-depth burns, where we created a total of 24 wounds of different depths over three animals to perform this analysis. We also performed visual and histological analysis of the wound damage in the acute phase. Additionally, we performed a histological analysis of wound healing up to post-burn day 64 and observed changes in Raman-associated Fluorescence Index between different wound categories.</p> Results <p>We successfully created superficial, superficial partial-thickness, deep partial-thickness, and full-thickness burns in Yucatan mini-pigs, as confirmed with the visual and histological analysis. With HI-based analysis, we found a high accuracy of diagnosis on post-burn day 3 in a binary classifier model for superficial partial-thickness and deep partial-thickness burns (AUC: 0.85, 95% CI: 0.56-1, <i>n</i> = 4–5), with nearly perfect classification in the broader categories (AUC: 1, 95% CI: 1–1, <i>n</i> = 4–9). Simultaneously, we observed histological features of healing that were consistent with the burn depth categories, along with trends in Resonance Raman-associated Fluorescence Index that might suggest a role in longitudinal wound monitoring with further development.</p> Conclusions <p>Non-invasive measurements with our device showed a high accuracy of burn depth classification using the Hemoglobin Index by post-burn 3. These results indicate a high potential for clinical translation of our approach for burn depth diagnosis in patients.</p>

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Non-invasive Resonance Raman Spectroscopy provides an early estimation of depth in a pig model of multi-depth burns

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月3日

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  • Rohil Jain,
  • Yanis Berkane,
  • Emmanuella O. Ajenu,
  • Khanh T. Nguyen,
  • Austin Alana Shamlou,
  • Alona Muzikansky,
  • Jonathan Cornacchini,
  • Alexandre G. Lellouch,
  • Basak E. Uygun,
  • Curtis L. Cetrulo Jr.,
  • Mark A. Randolph,
  • Korkut Uygun,
  • Padraic Romfh,
  • Shannon N. Tessier

摘要

Background

Accurate diagnosis of burn depth in the early post-burn phase is critical for guiding treatment decisions and optimal healing outcomes in patients. Current clinical assessment methods are often subjective, delayed, and prone to low diagnostic accuracy. A rapid and objective method of assessment to distinguish burn depths could significantly improve the standard of care.

Methods

We developed a non-invasive Resonance Raman Spectroscopic (RRS) protocol to assess burn depth using a compact and portable device. It provides Hemoglobin Index (HI), a metric of hemoglobin concentration in the wound bed. Since blood supply to the wound can depend on the severity of vascular damage, HI can be used to categorize burns by depth. We tested this approach in a clinically relevant Yucatan mini-pig model of multi-depth burns, where we created a total of 24 wounds of different depths over three animals to perform this analysis. We also performed visual and histological analysis of the wound damage in the acute phase. Additionally, we performed a histological analysis of wound healing up to post-burn day 64 and observed changes in Raman-associated Fluorescence Index between different wound categories.

Results

We successfully created superficial, superficial partial-thickness, deep partial-thickness, and full-thickness burns in Yucatan mini-pigs, as confirmed with the visual and histological analysis. With HI-based analysis, we found a high accuracy of diagnosis on post-burn day 3 in a binary classifier model for superficial partial-thickness and deep partial-thickness burns (AUC: 0.85, 95% CI: 0.56-1, n = 4–5), with nearly perfect classification in the broader categories (AUC: 1, 95% CI: 1–1, n = 4–9). Simultaneously, we observed histological features of healing that were consistent with the burn depth categories, along with trends in Resonance Raman-associated Fluorescence Index that might suggest a role in longitudinal wound monitoring with further development.

Conclusions

Non-invasive measurements with our device showed a high accuracy of burn depth classification using the Hemoglobin Index by post-burn 3. These results indicate a high potential for clinical translation of our approach for burn depth diagnosis in patients.