Introduction: Fine needle aspiration (FNA) of the thyroid gland is an effective diagnostic method. The Bethesda system for reporting thyroid cytopathology classifies them into six categories and gives implied risk for malignancy and management protocol in each category. Though the system gives specific criteria, diagnostic dilemma still exists. Using nuclear morphometry, we can quantify the number of parameters, such as those related to nuclear size and shape. The evaluation of nuclear morphometry is not well established in thyroid cytology.
Objective: To classify thyroid lesions on fine needle aspiration cytology (FNAC) using Bethesda system and to evaluate the significance of nuclear parameters in improving the prediction of thyroid malignancy.
Materials And Methods: In the present study, 120 FNAC cases of thyroid lesions with histological diagnosis were included. Computerized nuclear morphometry was done on 81 cases which had confirmed cytohistological correlation, using Aperio computer software. One hundred nuclei from each case were outlined and eight nuclear parameters were analyzed.
Results: In the present study, thyroid lesions were common in female with M: F ratio of 1:5 and most commonly in 40-60 yrs. Under Bethesda system, 73 (60.83%) were category II; 14 (11.6%) were category III, 3 (2.5%) were category IV, 8 (6.6%) were category V, and 22 (18.3%) were category VI, which were malignant on histopathological correlation. Sensitivity, specificity, and diagnostic accuracy of Bethesda reporting system are 62.5, 84.38, and 74.16%, respectively. Minimal nuclear diameter, maximal nuclear diameter, nuclear perimeter, and nuclear area were higher in malignant group compared to nonneoplastic and benign group.
Conclusion: The Bethesda system is a useful standardized system of reporting thyroid cytopathology. It gives implied risk of malignancy. Nuclear morphometry by computerized image analysis can be utilized as an additional diagnostic tool.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5655656 | PMC |
| http://dx.doi.org/10.4103/JOC.JOC_87_16 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Spatial Distribution of Genetic, Ploidy, and Morphological Variation of the Edaphic Steno-Endemic (Brassicaceae) from the Western Balkans.
Plants (Basel)
January 2025
Faculty of Forestry, University of Sarajevo, Zmaja od Bosne 8, 71 000 Sarajevo, Bosnia and Herzegovina.
Polyploidy is a powerful mechanism driving genetic, physiological, and phenotypic changes among cytotypes of the same species across both large and small geographic scales. These changes can significantly shape population structure and increase the evolutionary and adaptation potential of cytotypes. , an edaphic steno-endemic species with a narrow distribution in the Balkan Peninsula, serves as an intriguing case study.
View Article and Find Full Text PDFMicrostructural and functional connectivity changes of decision-related brain networks in end-stage kidney disease patients undergoing peritoneal dialysis.
Kidney Res Clin Pract
January 2025
Department of Radiology, The First Affiliated Hospital of Shantou University Medical College, Shantou, China.
Background: We aimed to explore changes in decision-related brain microstructure, brain functional activities, and functional connectivity, and their correlations with cognitive function in end-stage kidney disease (ESKD) patients undergoing peritoneal dialysis (PD). Furthermore, the impact of dialysis on these changes was examined.
Methods: Thirty ESKD patients undergoing PD, 20 chronic kidney disease (CKD) stage 5 patients without dialysis (predialysis CKD stage 5), and 30 healthy controls (HC) were recruited for the study.
Clinical validation of artificial intelligence-based single-subject morphometry without normative reference database.
J Alzheimers Dis
January 2025
Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Background: Single-subject voxel-based morphometry (VBM) is a powerful technique for reader-independent detection of brain atrophy in structural magnetic resonance imaging (MRI) to support the (differential) diagnosis and staging of neurodegenerative diseases in individual patients. However, VBM is sensitive to the MRI scanner platform and details of the acquisition sequence. To mitigate this limitation, we recently proposed and validated a convolutional neural network (CNN)-based VBM which does not rely on a normative reference database.
View Article and Find Full Text PDFThe association among individual gray matter volume of frontal-limbic circuitry, fatigue susceptibility, and comorbid neuropsychiatric symptoms following COVID-19.
Neuroimage
February 2025
Department of Medical Imaging, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi Province, China. Electronic address:
Article Synopsis
- The study investigates the neurobiological factors that make individuals susceptible to fatigue after a mild COVID-19 infection, aiming to understand the link between brain structure and post-COVID neuropsychiatric symptoms.
- Researchers used neuropsychiatric assessments and MRI scans on individuals who had COVID-19 and a control group to analyze brain regions related to fatigue.
- Results indicate that specific brain areas, particularly the right dorsolateral prefrontal cortex, are linked to fatigue severity and can predict ongoing fatigue symptoms months after the infection, shedding light on the neural underpinnings of post-COVID conditions.
Predicting Antidepressant Treatment Response From Cortical Structure on MRI: A Mega-Analysis From the ENIGMA-MDD Working Group.
Hum Brain Mapp
January 2025
Amsterdam UMC, Department of Radiology and Nuclear Medicine, University of Amsterdam, Amsterdam, the Netherlands.
Accurately predicting individual antidepressant treatment response could expedite the lengthy trial-and-error process of finding an effective treatment for major depressive disorder (MDD). We tested and compared machine learning-based methods that predict individual-level pharmacotherapeutic treatment response using cortical morphometry from multisite longitudinal cohorts. We conducted an international analysis of pooled data from six sites of the ENIGMA-MDD consortium (n = 262 MDD patients; age = 36.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!