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The Nigerian postgraduate medical journal · 2026

Ultrasound Elastography and Cytological Analysis for Effective Thyroid Nodule Classification.

СтатьяНазвание и аннотация: Перевод в очереди
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Pentakota Lakshmi Bharat, Patil Prakash Sarjerao

Аннотация

BACKGROUND: Traditional methods such as manual palpation and fine-needle aspiration cytology (FNAC) have limitations in differentiating benign and malignant thyroid nodules (TNs).

AIM: This study aimed to evaluate the accuracy of ultrasound elastography (USE) in differentiating benign and malignant TNs in a tertiary care hospital setting.

MATERIALS AND METHODS: A prospective study among patients with TNs who visited the hospital between July 2022 and November 2023. Patients with solitary TNs detected through ultrasonography (USG) were included. All patients underwent USG, USE and FNAC. Quantitative data were presented as mean, while qualitative data were expressed as frequencies and percentages. The diagnostic accuracy, sensitivity and specificity were calculated. A Chi-square test was used to assess the relationship between different methods used for diagnosis. P <0.05 was considered statistically significant.

RESULTS: A total of 33 patients, 84.8% female, mean age of 49.4 ± 19.6 years, were included. Histological evaluation revealed 39.4% of the lesions were malignant with a predominance of papillary carcinoma (61.5%), while 60.6% were benign. Among the benign lesions, majority were identified as colloid nodules (70.0%). Diagnostic efficacy of thyroid imaging reporting and data system (TI-RADS) was 78% and there was a significant correlation between TI-RADS classification and cytological findings (P = 0.00025). USE showed a sensitivity, specificity, positive predictive value and negative predictive value of 80.0%, 92.3%, 94.1% and 75.0%, respectively. There was a significant correlation between the elastography findings and the cytological outcomes (P = 0.0001).

CONCLUSIONS: USE shows great potential as a novel method for differentiating solid TNs and indicating optimal sites for FNAC.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты