ArticleJournal of pathology informatics2014
A nuclear circularity-based classifier for diagnostic distinction of desmoplastic from spindle cell melanoma in digitized histological images.
Article in Journal of pathology informatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed, 31 citations in OpenAlex.
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- High-throughput gene screen reveals modulators of nuclear shape.Molecular biology of the cell · 2020Article
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- Extreme nuclear branching in healthy epidermal cells of theJournal of cell science · 2018Article
- Desmoplastic melanoma versus spindle cell melanoma: Incidence and survival, 1973 to 2017.Medicine · 2018Observational
- Principles and approaches for reproducible scoring of tissue stains in research.Laboratory investigation; a journal of technical methods and pathology · 2018Review
- p63 Transcription Factor Regulates Nuclear Shape and Expression of Nuclear Envelope-Associated Genes in Epidermal Keratinocytes.The Journal of investigative dermatology · 2017Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
contextDistinction of spindle cell melanoma (SM) and desmoplastic melanoma (DM) is clinically important due to differences in metastatic rate and prognosis; however, histological distinction is not always straightforward. During a routine review of cases, we noted differences in nuclear circularity between SM and DM.
aimThe primary aim in our study was to determine whether these differences in nuclear circularity, when assessed using a basic ImageJ-based threshold extraction, can serve as a diagnostic classifier to distinguish DM from SM. SETTINGS AND
designOur retrospective analysis of an established patient cohort (SM n = 9, DM n = 9) was employed to determine discriminatory power. SUBJECTS AND
methodsRegions of interest (total n = 108; 6 images per case) were selected from scanned H and E-stained histological sections, and nuclear circularity was extracted and quantified by computational image analysis using open source tools (plugins for ImageJ). STATISTICAL ANALYSIS: Using analysis of variance, t-tests, and Fisher's exact tests, we compared extracted quantitative shape measures; statistical significance was defined as P < 0.05.
resultsClassifying circularity values into four shape categories (spindled, elongated, oval, round) demonstrated significant differences in the spindled and round categories. Paradoxically, DM contained more spindled nuclei than SM (P = 0.011) and SM contained more round nuclei than DM (P = 0.026). Performance assessment using a combined shape-classification of the round and spindled fractions showed 88.9% accuracy and a Youden index of 0.77.
conclusionsSpindle cell melanoma and DM differ significantly in their nuclear morphology with respect to fractions of round and spindled nuclei. Our study demonstrates that quantifying nuclear circularity can be used as an adjunct diagnostic tool for distinction of DM and SM.
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