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Advantages of an Automated Method Compared With Manual Methods for the Quantification of Intraepidermal Nerve Fiber in Skin Biopsy

dc.contributor.authorCorrà, Marta
dc.contributor.authorSousa, Mafalda
dc.contributor.authorReis, Inês
dc.contributor.authorTanganelli, Fabiana
dc.contributor.authorVila-Chã, Nuno
dc.contributor.authorSousa, Ana Paula
dc.contributor.authorMagalhães, Rui
dc.contributor.authorSampaio, Paula
dc.contributor.authorTaipa, Ricardo
dc.contributor.authorMaia, Luis
dc.date.accessioned2023-11-14T11:07:22Z
dc.date.available2023-11-14T11:07:22Z
dc.date.issued2021-08
dc.description.abstractIntraepidermal nerve fiber density (IENFD) measurements in skin biopsy are performed manually by 1-3 operators. To improve diagnostic accuracy and applicability in clinical practice, we developed an automated method for fast IENFD determination with low operator-dependency. Sixty skin biopsy specimens were stained with the axonal marker PGP9.5 and imaged using a widefield fluorescence microscope. IENFD was first determined manually by 3 independent observers. Subsequently, images were processed in their Z-max projection and the intradermal line was delineated automatically. IENFD was calculated automatically (fluorescent images automated counting [FIAC]) and compared with manual counting on the same fluorescence images (fluorescent images manual counting [FIMC]), and with classical manual counting (CMC) data. A FIMC showed lower variability among observers compared with CMC (interclass correlation [ICC] = 0.996 vs 0.950). FIMC and FIAC showed high reliability (ICC = 0.999). A moderate-to-high (ICC = 0.705) was observed between CMC and FIAC counting. The algorithm process took on average 15 seconds to perform FIAC counting, compared with 10 minutes for FIMC counting. This automated method rapidly and reliably detects small nerve fibers in skin biopsies with clear advantages over the classical manual technique.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationCorrà MF, Sousa M, Reis I, et al. Advantages of an Automated Method Compared With Manual Methods for the Quantification of Intraepidermal Nerve Fiber in Skin Biopsy. J Neuropathol Exp Neurol. 2021;80(7):685-694. doi:10.1093/jnen/nlab045pt_PT
dc.identifier.doi10.1093/jnen/nlab045pt_PT
dc.identifier.issn0022-3069
dc.identifier.issn1554-6578
dc.identifier.urihttp://hdl.handle.net/10400.16/2883
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherOxford University Presspt_PT
dc.relation.publisherversionhttps://academic.oup.com/jnen/article/80/7/685/6285568?login=falsept_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectAutomated methodpt_PT
dc.subjectIntraepidermal nerve fiber densitypt_PT
dc.subjectSkin biopsypt_PT
dc.titleAdvantages of an Automated Method Compared With Manual Methods for the Quantification of Intraepidermal Nerve Fiber in Skin Biopsypt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.conferencePlaceEnglandpt_PT
oaire.citation.endPage694pt_PT
oaire.citation.issue7pt_PT
oaire.citation.startPage685pt_PT
oaire.citation.titleJournal of Neuropathology & Experimental Neurologypt_PT
oaire.citation.volume80pt_PT
person.familyNameCorrà
person.familyNameCalado Reis
person.familyNameFerreira Taipa
person.familyNameMaia
person.givenNameMarta Francisca
person.givenNameInês
person.givenNameRicardo Jorge
person.givenNameLuis
person.identifier.ciencia-id0A12-811C-0517
person.identifier.ciencia-idB81C-48AC-407A
person.identifier.ciencia-idE316-D53D-8537
person.identifier.ciencia-id9F1E-51AF-C38B
person.identifier.orcid0000-0002-9260-0227
person.identifier.orcid0000-0002-8140-3471
person.identifier.ridJ-1742-2014
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublicationf689aee6-8536-465d-b59c-7b1ad34e42a9
relation.isAuthorOfPublication28d5938c-edb2-4b1b-9d45-4da640b4d669
relation.isAuthorOfPublication97a7bf34-226a-4dc2-ae31-d0f86030cb52
relation.isAuthorOfPublication2b17a107-4559-498c-82f9-559a1ded4cac
relation.isAuthorOfPublication.latestForDiscoveryf689aee6-8536-465d-b59c-7b1ad34e42a9

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