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Updated: Jul 29, 2025
A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
Published on: April 21, 2023
The Role of Cytomorphometric Image Analysis in the Diagnosis of Thyroid Nodules
Jai K Chaurasia1, Abeer M Ilyas1, Vaishali Walke1
1Pathology and Laboratory Medicine, All India Institute of Medical Sciences, Bhopal, IND.
Insights
Cytomorphometric image analysis quantifies features of thyroid nodules, improving diagnosis accuracy. This method distinguishes benign from malignant nodules and aids in classifying follicular pattern thyroid cancers.
Area of Science:
- Cytopathology
- Digital Image Analysis
- Oncology
Background:
- Fine needle aspiration cytology (FNAC) is crucial for thyroid nodule diagnosis but faces challenges like heterogeneity and interobserver variability.
- Cytomorphometric analysis offers quantitative assessment to complement subjective cytological interpretations.
Purpose of the Study:
- To evaluate the utility of cytomorphometric image analysis in diagnosing thyroid nodules classified by The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC).
- To determine if quantitative nuclear features can differentiate benign and malignant thyroid lesions, including those with follicular patterns.
Main Methods:
- Retrospective analysis of 50 thyroid nodule FNAC smears (Papanicolaou and H&E stained) with histopathology correlation.
- Application of cytomorphometric image analysis to quantify 14 nuclear parameters (e.g., area, roundness, texture) on TBSRTC-categorized nodules.
Main Results:
- Cytomorphometric analysis successfully distinguished between benign and malignant thyroid nodules.
- The method demonstrated significant capability (p<0.001) in categorizing nodules with follicular patterns, including follicular variant of papillary carcinoma, follicular adenoma, and follicular carcinoma.
Conclusions:
- Quantitative cytomorphometric analysis of thyroid nodule cytology, when combined with traditional cytomorphology, enhances diagnostic accuracy.
- This approach holds potential for improved thyroid nodule diagnosis, leading to better treatment decisions and patient prognosis.
Abstract:
Introduction Fine needle aspiration cytology (FNAC) plays a vital role in the diagnosis of thyroid nodules. However, it is challenging due to the heterogeneity of thyroid nodules, overlapping cytomorphological features, and interobserver variability. Cytomorphometric analysis turns subjective observations into quantitative values. In this study, we performed cytomorphometric image analysis on cytological smears of thyroid nodules, classified according to The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC). Materials and methods A retrospective analysis of Papanicolaou (PAP) and Hematoxylin & Eosin (H&E) stained fine needle aspirate smears from 50 patients with thyroid nodules with available follow-up histopathology was performed for a period of two years (March 2021 - March 2023), after obtaining approval from the institutional human ethical committee (IHEC-LOP/2020/IM0355). The nodules were categorized according to TBSRTC and were then subjected to cytomorphometric image analysis. Each nucleus was analyzed for 14 parameters, including aspect ratio, intensity, diameter, perimeter, roundness, area, fractal dimension, feret diameter, circularity, radii, fournier description, and chromatin texture parameters such as heterogeneity and clumpiness. The data obtained was analyzed through relevant statistical methods using SPSS version 23 (IBM Inc., Armonk, New York) and was compared by using the analysis of variance (ANOVA) test and post hoc test. Results Our results revealed that cytomorphometric image analysis not only distinguishes benign and malignant thyroid nodules but also can aid in categorizing thyroid nodules with predominant follicular patterns, such as follicular variant of papillary carcinoma, follicular adenoma and follicular carcinoma (p<0.001). Conclusions Morphometric analysis of cytological smears combined with cytomorphology has the potential to be an important tool in the diagnosis of thyroid nodules. It can improve diagnostic accuracy for better treatment and improved prognosis.
