Evidence map›Paper›PMID 41184970›Full record

ArticleJournal of translational medicine2025

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

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 and 4 more

Abstract read
In one paragraph

Article in Journal of translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors.

Rohil JainCenter for Engineering in Medicine and Surgery, Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, USA.ORCID 0000-0002-3001-0192
Yanis BerkaneCenter for Engineering in Medicine and Surgery, Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, USA.
Emmanuella O AjenuCenter for Engineering in Medicine and Surgery, Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, USA.
Khanh T NguyenCenter for Engineering in Medicine and Surgery, Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, USA.ORCID 0000-0003-1233-7527
Austin Alana ShamlouShriners Children's Hospital, Boston, USA.
Alona MuzikanskyDepartment of Biostatistics, Massachusetts General Hospital, Boston, USA.
Jonathan CornacchiniShriners Children's Hospital, Boston, USA.
Alexandre G LellouchVascularized Composite Allotransplantation Laboratory, Center for Transplantation Sciences, Massachusetts General Hospital, Harvard Medical School, Boston, USA.
Basak E UygunCenter for Engineering in Medicine and Surgery, Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, USA.
Curtis L CetruloVascularized Composite Allotransplantation Laboratory, Center for Transplantation Sciences, Massachusetts General Hospital, Harvard Medical School, Boston, USA.
Mark A RandolphShriners Children's Hospital, Boston, USA.
Korkut UygunCenter for Engineering in Medicine and Surgery, Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, USA.
Padraic RomfhPendar Technologies, Cambridge, MA, USA.
Shannon N TessierCenter for Engineering in Medicine and Surgery, Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, USA. sntessier@mgh.harvard.edu.ORCID 0000-0003-2373-232X

Funding

High subzero heart preservation: from zebrafish to mammalsR01HL157803 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI Shannon Noella Tessier · 2021 to 2026
$2.8M
Cryopreservation of zebrafish larvae and embryos for biomedical researchR24OD034189 · OD · MASSACHUSETTS GENERAL HOSPITAL · PI Shannon Noella Tessier · 2023 to 2026
$2.6M
A quantitative viability metric for liver transplantation using Resonance Raman SpectroscopyR01DK134590 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI Shannon Noella Tessier · 2023 to 2026
$1.9M
American Association for the Study of Liver Diseases 23-263034Massachusetts General Hospital fund for medical discoveryNational Science Foundation EEC1941543NHLBI NIH HHS R01 HL157803NHLBI NIH HHS R01HL157803NIDCR NIH HHS R24OD034189NIDDK NIH HHS R01 DK134590NIDDK NIH HHS R01DK134590NIH HHS R24 OD034189Shriners Hospitals for Children 85115
6 · The paper itself

Abstract

backgroundAccurate 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.

methodsWe 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.

resultsWe 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.

conclusionsNon-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.

Indexed as

BurnsSpectrum Analysis, RamanAnimalsDisease Models, AnimalHemoglobinsSwineSwine, MiniatureWound HealingHemoglobinsDiagnosis of burn depthPig model of burnsRaman spectroscopy

Identifiers

PMID41184970
PMCPMC12581261

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.