Evidence map›Paper›PMID 41408126›Full record

ArticleScientific reports2025

Development of a digital image analysis system for objective evaluation of treatment response in cellulitis.

Kazunori Miyata, Jun Yamagami, Yuko Takenaka, Mai Onuki, Tomoaki Sawayanagi, Naoko Ishiguro

Abstract read
In one paragraph

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

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

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

6 authors.

Kazunori MiyataDepartment of Dermatology, Tokyo Women's Medical University Yachiyo Medical Center, 477-96, Ohwada-Shinden, Yachiyo, 276-8524, Chiba, Japan.
Jun YamagamiDepartment of Dermatology, Tokyo Women's Medical University, 8-1, Kawadacho, Shinjuku-ku, 162-0054, Tokyo, Japan. yamagami.jun@twmu.ac.jp.
Yuko TakenakaDepartment of Dermatology, Tokyo Women's Medical University, 8-1, Kawadacho, Shinjuku-ku, 162-0054, Tokyo, Japan.
Mai OnukiDepartment of Dermatology, Tokyo Women's Medical University, 8-1, Kawadacho, Shinjuku-ku, 162-0054, Tokyo, Japan.
Tomoaki SawayanagiRealinite Co., Ltd., 28-2, Oyamahigashicho, Itabashi-ku, 173-0014, Tokyo, Japan.
Naoko IshiguroDepartment of Dermatology, Tokyo Women's Medical University, 8-1, Kawadacho, Shinjuku-ku, 162-0054, Tokyo, Japan.

Funding

Health and Labor Sciences Research Grants for Research on Measures for Intractable Diseases from Ministry of Health, Labor and Welfare of Japan 23FC1039the Ministry of Education, Culture, Sports, Science and Technology of Japan 22K08416Wellcome Trust FC001039
6 · The paper itself

Abstract

Cellulitis is a common skin infection. While changes in lesion color are valuable indicators of treatment efficacy, assessments often rely on subjective judgments. To provide an objective method for evaluating treatment response, we developed a digital imaging system that quantifies red, green, and blue (RGB) values of lesions and calculates the RGB distance between lesions and normal skin. We analyzed 34 patients with cellulitis treated between 2022 and 2025. Clinical images were obtained on days 1 (baseline), 3, 7, and 14. By day 14, the G and B values of lesions increased significantly (G: 115.6 to 135.7, B: 91.8 to 105.5; P < 0.05), while the R values remained stable. The RGB distance decreased significantly from day 3 (64.3 to 53.7; P < 0.05). Patients were classified by Investigator's Global Assessment into Group A (favorable clinical outcome, n = 13) and Group B (delayed clinical improvement, n = 21). Receiver operating characteristic analyses of the RGB distance ratio relative to day 1 showed high accuracy at day 3 (cut-off = 0.62) and day 7 (cut-off = 0.48). A significantly higher proportion of Group B patients had a history of edema. These findings suggest our system provides an objective method for evaluating the clinical course of cellulitis.

Indexed as

CellulitisImage Processing, Computer-AssistedAdultAgedFemaleHumansMaleMiddle AgedROC CurveSkinTreatment OutcomeCellulitisDigital image analysisEdemaRGBTreatment efficacy

Identifiers

PMID41408126
PMCPMC12712028

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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.