Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Practical issues in assessing nailfold capillaroscopic images: a summary
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics and Logistics.ORCID iD: 0000-0001-7320-2306
Isfahan Univ Med Sci, Med Image & Signal Proc Res Ctr, Esfahan, Iran..ORCID iD: 0000-0002-7309-1105
Isfahan Univ Med Sci, Sch Med, Dept Internal Med, Rheumatol Sect, Esfahan, Iran..
Isfahan Univ Med Sci, Sch Med, Dept Med Phys, Esfahan, Iran..
Show others and affiliations
2019 (English)In: Clinical Rheumatology, ISSN 0770-3198, E-ISSN 1434-9949, Vol. 38, no 9, p. 2343-2354Article, review/survey (Refereed) Published
Abstract [en]

Nailfold capillaroscopy (NC) is a highly sensitive, safe, and non-invasive technique to assess involvement rate of microvascularity in dermatomyositis and systemic sclerosis. A large number of studies have focused on NC pattern description, classification, and scoring system validation, but minimal information has been published on the accuracy and precision of the measurement. The objective of this review article is to identify different factors affecting the reliability and validity of the assessment in NC. Several factors can affect the reliability of the examination, e.g., physiological artifacts, the nailfold imaging instrument, human factors, and the assessment rules and standards. It is impossible to avoid all artifacts, e.g., skin transparency, physically injured fingers, and skin pigmentation. However, minimization of the impact of some of these artifacts by considering some protocols before the examination and by using specialized tools, training, guidelines, and software can help to reduce errors in the measurement and assessment of NC images. Establishing guidelines and instructions for automatic characterization and measurement based on machine learning techniques also may reduce ambiguities and the assessment time.

Place, publisher, year, edition, pages
SPRINGER LONDON LTD , 2019. Vol. 38, no 9, p. 2343-2354
Keywords [en]
Assessment, Measurement, Nailfold capillaroscopy
National Category
Clinical Medicine
Identifiers
URN: urn:nbn:se:kth:diva-260182DOI: 10.1007/s10067-019-04644-9ISI: 000483770400007PubMedID: 31278512Scopus ID: 2-s2.0-85068831307OAI: oai:DiVA.org:kth-260182DiVA, id: diva2:1355371
Note

QC 20190927

Available from: 2019-09-27 Created: 2019-09-27 Last updated: 2019-09-27Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textPubMedScopus

Authority records BETA

Karbalaie, AbdolamirErlandsson, Björn-Erik

Search in DiVA

By author/editor
Karbalaie, AbdolamirEmrani, ZahraErlandsson, Björn-Erik
By organisation
Health Informatics and LogisticsBiomedical Engineering and Health Systems
In the same journal
Clinical Rheumatology
Clinical Medicine

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 82 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf