Literature DB >> 10231421

The value of histomorphometric nuclear parameters in the diagnosis of well differentiated follicular carcinomas and follicular adenomas of the thyroid gland.

S Eldar1, E Sabo, A Cohen, I Misselevich, J Abrahamson, O Cohen, J Kelner, J H Boss.   

Abstract

AIMS: To explore the potential of histomorphometric analysis in distinction between follicular adenomas and well differentiated follicular carcinomas of the thyroid gland. Their differentiation on routine histological study may be a challenging exercise, being contingent upon the absence or presence of vascular invasion and penetration of neoplastic follicles through the capsule of the tumour. METHODS AND
RESULTS: Computer-assisted image analysis was performed to gauge the nuclear area, nuclear Ferret diameter, nuclear regularity factor, nuclear elongation factor, number of nuclear vesicles and total area of all nuclear vesicles in the follicles of 37 adenomas and 36 well differentiated carcinomas. By univariate analysis, these nuclear descriptors (with the exception of the elongation factor) were found to correlate with the benign or malignant nature of the tumours. By multivariate analysis, only the nuclear area, Ferret diameter and regularity factor were ascertained to be significant predictors of malignancy. A fitted logit model correctly predicted 91% of the cancers and 87% of the adenomas.
CONCLUSIONS: Histomorphometrically gauged nuclear parameters of the tumour cells may reinforce pathologists' decision-making by adding objective and unbiased criteria to their subjective assessment of follicular neoplasms in cases in which vascular or capsular invasion are not detected.

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Year:  1999        PMID: 10231421     DOI: 10.1046/j.1365-2559.1999.00641.x

Source DB:  PubMed          Journal:  Histopathology        ISSN: 0309-0167            Impact factor:   5.087


  4 in total

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Review 3.  Immunohistochemical Biomarkers in Thyroid Pathology.

Authors:  Zubair Baloch; Ozgur Mete; Sylvia L Asa
Journal:  Endocr Pathol       Date:  2018-06       Impact factor: 3.943

4.  Programmed death-ligand 1 expression by digital image analysis advances thyroid cancer diagnosis among encapsulated follicular lesions.

Authors:  Anne M-Y Hsieh; Olena Polyakova; Guodong Fu; Ronald S Chazen; Christina MacMillan; Ian J Witterick; Ranju Ralhan; Paul G Walfish
Journal:  Oncotarget       Date:  2018-04-13
  4 in total

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