Evidence map›Paper›PMID 42889896›Full record

ArticleBiomedical optics express2026

Erythema and hyperpigmentation delineation for cutaneous chronic graft-versus-host disease using hyperspectral reconstruction.

Mayaank Pillai, Ruijing E Han, Inga Saknite, Eric Tkaczyk, Audrey K Bowden

Abstract read
In one paragraph

Article in Biomedical optics express, 2026. 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Mayaank PillaiVanderbilt University, Department of Computer Science, Nashville, TN, USA.ORCID https://orcid.org/0009-0004-3611-7865
Ruijing E HanVanderbilt University, Department of Biomedical Engineering, Nashville, TN, USA.
Inga SakniteUniversity of Latvia, Riga, Latvia.ORCID https://orcid.org/0000-0002-4000-5485
Eric TkaczykVanderbilt University Medical Center, Nashville, TN, USA.ORCID https://orcid.org/0000-0002-2850-4740
Audrey K BowdenVanderbilt University, Department of Biomedical Engineering, Nashville, TN, USA.ORCID https://orcid.org/0000-0002-5412-3976

Funding

Vanderbilt Institute for Clinical and Translational Research (VICTR) -Identifying correlates of functional immunity in SARS-CoV-2 convalescent plasmaUL1TR002243 · NCATS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Paul A. Harris, Wesley H Self · 2017 to 2026
$130.7M
Cystoscopy-augmenting tools to improve the sensitivity and specificity of detection of urothelial carcinoma in situR01CA301464 · NCI · VANDERBILT UNIVERSITY · PI BOWDEN, AUDREY KYNSELLA · 2025 to 2025
$3.0M
Artificial intelligence to estimate extent of cGVHD from patient photosR01HL169944 · NHLBI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Eric R Tkaczyk · 2024 to 2026
$2.3M
CSRD VA IK2 CX001785NCATS NIH HHS UL1 TR002243NCI NIH HHS R01 CA301464NHLBI NIH HHS R01 HL169944
6 · The paper itself

Abstract

Erythema body surface area is a key indicator of cutaneous chronic graft-versus-host disease (cGVHD) status, but clinician estimation is unreliable and confounded by hyperpigmentation. Existing automated methods either fit predictive algorithms to subjective human annotations or require costly hyperspectral imagers. To our knowledge, we present the first annotation-free method to delineate both erythema and hyperpigmentation from standard RGB images. Our pipeline (i) reconstructs hyperspectral images from RGB input and (ii) unmixes these into hemoglobin and melanin abundance maps, which predict erythema and hyperpigmentation, respectively. Trained only on synthetic images, the method achieved a median binary classification accuracy above 0.70 across both conditions and both synthetic images and clinical photographs, demonstrating generalizability to the clinical environment.

Identifiers

PMID42889896
PMCPMC13671688

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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.