Evidence map›Paper›PMID 38878217›Full record

ArticleArchives of dermatological research2024

Vascular feature identification in actinic keratosis grades I-III using dynamic optical coherence tomography with automated, quantitative analysis.

Gabriella Fredman, Stine R Wiegell, Merete Haedersdal, Gavrielle R Untracht

Abstract read
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Article in Archives of dermatological research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Gabriella FredmanDepartment of Dermatology, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Copenhagen, NV, 2400, Denmark. gabriella.louise.fredman@regionh.dk.ORCID http://orcid.org/0000-0003-3903-2651
Stine R WiegellDepartment of Dermatology, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Copenhagen, NV, 2400, Denmark.
Merete HaedersdalDepartment of Dermatology, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Copenhagen, NV, 2400, Denmark.
Gavrielle R UntrachtDepartment of Dermatology, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Copenhagen, NV, 2400, Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clinical grading of actinic keratosis (AK) is based on skin surface features, while subclinical alterations are not taken into consideration. Dynamic optical coherence tomography (D-OCT) enables quantification of the skin´s vasculature, potentially helpful to improve the link between clinical and subclinical features. We aimed to compare microvascular characteristics across AK grades using D-OCT with automated vascular analysis. This explorative study examined AK and photodamaged skin (PD) on the face or scalp. AKs were clinically graded according to the Olsen Classification scheme before D-OCT assessment. Using an open-source software tool, the OCT angiographic analyzer (OCTAVA), we quantified vascular network features, including total and mean vessel length, mean vessel diameter, vessel area density (VAD), branchpoint density (BD), and mean tortuosity from enface maximum intensity projection images. Additionally, we performed subregional analyses on selected scans to overcome challenges associated with imaging through hyperkeratosis (each lesion group; n = 18). Our study included 45 patients with a total of 205 AKs; 93 grade I lesions, 65 grade II, 47 grade III and 89 areas with PD skin. We found that all AK grades were more extensively vascularized relative to PD, as shown by greater total vessel length and VAD (p ≤ 0.009). Moreover, AKs displayed a disorganized vascular network, with higher BD in AK I-II (p < 0.001), and mean tortuosity in AK II-III (p ≤ 0.001) than in PD. Vascularization also increased with AK grade, showing significantly greater total vessel length in AK III than AK I (p = 0.029). Microvascular quantification of AK unveiled subclinical, quantitative differences among AK grades I-III and PD skin. D-OCT-based microvascular assessment may serve as a supplement to clinical AK grading, potentially raising perspectives to improve management strategies.

Indexed as

Keratosis, ActinicSkinTomography, Optical CoherenceAgedAged, 80 and overFaceFemaleHumansMaleMiddle AgedScalpSeverity of Illness IndexSkin AgingActinic keratosisAngiographyDynamic optical coherence tomographyNon-invasive imagingOCTAVASkin microvasculature

Identifiers

PMID38878217
PMCPMC11180023

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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.