Nuclear Morphometry as an Adjunct to Cytomorphology in the Diagnosis of Thyroid Lesions
Introduction: Fine Needle Aspiration Cytology (FNAC) is a reliable and reproducible diagnostic technique for thyroid lesions. Recently, it has been suggested that evaluation of nuclear features may enhance the diagnostic utility of FNAC. However, the evaluation of nuclear morphometry is not well...
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oai:doaj.org-article:4863537c5b57420798f5de6eaed9bdcf2021-11-07T10:07:10ZNuclear Morphometry as an Adjunct to Cytomorphology in the Diagnosis of Thyroid Lesions10.7860/JCDR/2021/49980.153312249-782X0973-709Xhttps://doaj.org/article/4863537c5b57420798f5de6eaed9bdcf2021-09-01T00:00:00Zhttps://www.jcdr.net/articles/PDF/15331/49980_CE[Ra1]_F(SHU)_PF1(AKA_RK_KM)PN(KM).pdfhttps://doaj.org/toc/2249-782Xhttps://doaj.org/toc/0973-709XIntroduction: Fine Needle Aspiration Cytology (FNAC) is a reliable and reproducible diagnostic technique for thyroid lesions. Recently, it has been suggested that evaluation of nuclear features may enhance the diagnostic utility of FNAC. However, the evaluation of nuclear morphometry is not well established in thyroid cytology. Aim: To evaluate the role of nuclear morphometry in cytological evaluation of thyroid lesions. Materials and Methods: This was a cross-sectional study conducted over a period from March 2019-February 2020 at Hamdard Institute of Medical Sciences and Research, New Delhi, India. Morphometry was done on 40 cases of thyroid aspirates which had histopathological concordance. Computerised nuclear morphometry was done by using photographs captured under Motic photomicrography system. Six parameters were measured- nuclear area, nuclear perimeter, minimal nuclear diameter, maximal nuclear diameter, nuclear compactness and LS ratio (Largest to Smallest dimension ratio). Data were entered in spreadsheet and then analysed using Statistical Package for Social Sciences (SPSS) version 20.0. Results: Out of total 40 thyroid aspirates studied, included non neoplastic (19 cases), benign (12 cases) and malignant lesions (9 cases). All nuclear morphometry parameters comprising of nuclear area, nuclear perimeter, minimal nuclear diameter, maximal nuclear diameter showed an increasing trend from non neoplastic to benign to malignant with a statistically significant difference between benign and malignant groups (p-values <0.05) except for LS ratio and nuclear compactness. Conclusion: Nuclear morphometry can aid in cytological diagnosis of thyroid lesions. If used judiciously, quantitative estimation of cytological nuclear features can be helpful in assessing thyroid lesions preoperatively thus complementing its cytomorphological features.Sabina KhanSayika HameedMohd Jaseem HasanMusharraf HusainArun SharmaJCDR Research and Publications Private Limitedarticleaspiration cytologyhistopathologicalphotomicrographythyroid aspiratesMedicineRENJournal of Clinical and Diagnostic Research, Vol 15, Iss 9, Pp EC01-EC04 (2021) |
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aspiration cytology histopathological photomicrography thyroid aspirates Medicine R |
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aspiration cytology histopathological photomicrography thyroid aspirates Medicine R Sabina Khan Sayika Hameed Mohd Jaseem Hasan Musharraf Husain Arun Sharma Nuclear Morphometry as an Adjunct to Cytomorphology in the Diagnosis of Thyroid Lesions |
description |
Introduction: Fine Needle Aspiration Cytology (FNAC) is a reliable
and reproducible diagnostic technique for thyroid lesions. Recently,
it has been suggested that evaluation of nuclear features may
enhance the diagnostic utility of FNAC. However, the evaluation of
nuclear morphometry is not well established in thyroid cytology.
Aim: To evaluate the role of nuclear morphometry in cytological
evaluation of thyroid lesions.
Materials and Methods: This was a cross-sectional study
conducted over a period from March 2019-February 2020 at
Hamdard Institute of Medical Sciences and Research, New
Delhi, India. Morphometry was done on 40 cases of thyroid
aspirates which had histopathological concordance. Computerised
nuclear morphometry was done by using photographs captured
under Motic photomicrography system. Six parameters were
measured- nuclear area, nuclear perimeter, minimal nuclear
diameter, maximal nuclear diameter, nuclear compactness and
LS ratio (Largest to Smallest dimension ratio). Data were entered
in spreadsheet and then analysed using Statistical Package for
Social Sciences (SPSS) version 20.0.
Results: Out of total 40 thyroid aspirates studied, included non
neoplastic (19 cases), benign (12 cases) and malignant lesions
(9 cases). All nuclear morphometry parameters comprising
of nuclear area, nuclear perimeter, minimal nuclear diameter,
maximal nuclear diameter showed an increasing trend from non
neoplastic to benign to malignant with a statistically significant
difference between benign and malignant groups (p-values
<0.05) except for LS ratio and nuclear compactness.
Conclusion: Nuclear morphometry can aid in cytological diagnosis
of thyroid lesions. If used judiciously, quantitative estimation of
cytological nuclear features can be helpful in assessing thyroid
lesions preoperatively thus complementing its cytomorphological
features. |
format |
article |
author |
Sabina Khan Sayika Hameed Mohd Jaseem Hasan Musharraf Husain Arun Sharma |
author_facet |
Sabina Khan Sayika Hameed Mohd Jaseem Hasan Musharraf Husain Arun Sharma |
author_sort |
Sabina Khan |
title |
Nuclear Morphometry as an Adjunct to Cytomorphology in the Diagnosis of Thyroid Lesions |
title_short |
Nuclear Morphometry as an Adjunct to Cytomorphology in the Diagnosis of Thyroid Lesions |
title_full |
Nuclear Morphometry as an Adjunct to Cytomorphology in the Diagnosis of Thyroid Lesions |
title_fullStr |
Nuclear Morphometry as an Adjunct to Cytomorphology in the Diagnosis of Thyroid Lesions |
title_full_unstemmed |
Nuclear Morphometry as an Adjunct to Cytomorphology in the Diagnosis of Thyroid Lesions |
title_sort |
nuclear morphometry as an adjunct to cytomorphology in the diagnosis of thyroid lesions |
publisher |
JCDR Research and Publications Private Limited |
publishDate |
2021 |
url |
https://doaj.org/article/4863537c5b57420798f5de6eaed9bdcf |
work_keys_str_mv |
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1718443543462150144 |