Evidence map›Paper›PMID 39224267›Full record

ArticleHeliyon2024

Ultrasonographic features and diagnostic accuracy of FNA and CNB in secondary thyroid malignancies: A retrospective study.

Zhen Xia, Xiaochen Huang, Ting Zhang, Zhigang Gao, Xiuliang Tang, Wei Zhang, Qing Miao

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Zhen XiaDepartment of Ultrasound, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China.
Xiaochen HuangDepartment of Pathology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China.
Ting ZhangDepartment of Ultrasound, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China.
Zhigang GaoDepartment of Ultrasound, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China.
Xiuliang TangDepartment of Ultrasound, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China.
Wei ZhangDepartment of Ultrasound, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China.
Qing MiaoDepartment of Ultrasound, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aims to examine the ultrasonographic features of secondary thyroid malignancies and compare the diagnostic efficacy of fine-needle aspiration (FNA) and core needle biopsy (CNB) in this condition. Methods: A retrospective analysis was conducted on 29 patients with secondary thyroid malignancies treated at our center between July 2011 and October 2022. Ultrasound images and clinical data were analyzed, and the lesions were classified according to the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS). Results: Among the 29 patients studied, primary tumor sites were predominantly the esophagus, lung, and nasopharynx. Comprehensive ultrasound data was available for 28 of these patients, revealing nodular lesions in 24 cases and diffuse lesions in 4 cases. Nodular lesions were predominantly solid or nearly solid hypoechoic nodules with parallel growth and extrathyroidal extension features, with a few showing macrocalcifications. Most patients had varying degrees of metastasis to neck lymph nodes. FNA accurately diagnosed 31.6 % of the lesions as secondary thyroid malignancies, while 5.3 % were misdiagnosed as papillary thyroid carcinoma (PTC). However, CNB demonstrated 100 % reliability in diagnosing secondary thyroid malignancies. Conclusion: This study's categorization of secondary thyroid malignancy ultrasonographic features identifies nodular and diffuse patterns, with the application of ACR TI-RADS proving effective for nodular types. In detecting these lesions, CNB demonstrates superior sensitivity compared to FNA. Thus, in cases of thyroid lesions suspected to be malignant, particularly with enlarged neck lymph nodes and in patients with a history of malignancy, CNB is recommended as the diagnostic method of choice.

Indexed as

Core needle biopsyFine-needle aspirationSecondary thyroid malignancyUltrasound

Identifiers

PMID39224267
PMCPMC11367495

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.