Cytomorphological traits of fine-needle aspirates of hyalinizing trabecular tumor of the thyroid gland: A brief report.

IF 3.1 2区 社会学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Artificial Intelligence and Law Pub Date : 2024-01-01 DOI:10.4103/ijpm.ijpm_405_22
Fei Wang, Yufei Liu
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Abstract

Background: The incidence of thyroid tumor is increasing, and preoperative diagnosis of hyalinizing trabecular tumor (HTT) is difficult.

Aim: To investigate the cytological features of HTT of the thyroid gland.

Settings and design: A retrospective observational study.

Materials and methods: Ultrasonography, preoperative needle aspiration cytology, postoperative histopathology, immunohistochemistry, and BRAF V600E gene test were performed in five patients with HTT to analyze the pathological characteristics of the patients and review the relevant literature.

Results: Four female and one male patients with HTT were recruited. Fine-needle aspiration cytology (FNAC) showed bloodstained background tumor cells with multiple morphologies. The tumor cells exhibited ovoid nuclei, abundant cytoplasm, fine chromatin, nuclear crowding and overlapping, and small nucleoli. Focal nuclear pseudoinclusions and grooves were present. No papillary structures or psammoma bodies were observed. In all cases, tumor cells were radially distributed around the eosinophilic extracellular matrix. In 40% (2 in 5) of cases, trabecular patterns of elongated tumor cells were present, with their nuclei staggered along the longitudinal axis of tumor cells in the trabeculae. FNAC suggested two cases of HTT and three cases of papillary thyroid cancer. Post-operational biopsy indicated they were HTT cases.

Conclusion: HTT is a rare thyroid tumor with non-specific clinical manifestations. It can be misinterpreted as papillary thyroid carcinoma by FNAC. However, its cytomorphological traits are helpful in the diagnosis. In combination with FNAC, immunohistochemistry, and molecular testing, HTT can be accurately diagnosed.

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甲状腺透明小梁瘤细针穿刺细胞形态学特征:简要报告。
背景:甲状腺肿瘤的发病率越来越高,而透明小梁瘤(HTT)的术前诊断非常困难。目的:研究甲状腺HTT的细胞学特征:材料与方法:超声波检查、术前小梁瘤细胞学检查:对5例HTT患者进行超声波检查、术前针吸细胞学检查、术后组织病理学检查、免疫组化检查和BRAF V600E基因检测,分析患者的病理特征并回顾相关文献:结果:共招募了四名女性和一名男性 HTT 患者。细针穿刺细胞学检查(FNAC)显示血染的背景肿瘤细胞具有多种形态。肿瘤细胞核呈卵圆形,胞浆丰富,染色质细腻,核拥挤和重叠,核小。存在局灶性核假包涵体和核沟纹。未观察到乳头状结构或脓肿体。在所有病例中,肿瘤细胞围绕嗜酸性细胞外基质呈放射状分布。40%的病例(每5例中有2例)存在细长的肿瘤细胞小梁形态,细胞核沿小梁中肿瘤细胞的纵轴交错分布。FNAC提示2例为HTT,3例为甲状腺乳头状癌。术后活检结果显示它们均为HTT病例:HTT是一种罕见的甲状腺肿瘤,具有非特异性临床表现。结论:HTT是一种罕见的甲状腺肿瘤,临床表现无特异性,可通过FNAC误诊为甲状腺乳头状癌。不过,其细胞形态学特征有助于诊断。结合FNAC、免疫组化和分子检测,可以准确诊断HTT。
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来源期刊
CiteScore
9.50
自引率
26.80%
发文量
33
期刊介绍: Artificial Intelligence and Law is an international forum for the dissemination of original interdisciplinary research in the following areas: Theoretical or empirical studies in artificial intelligence (AI), cognitive psychology, jurisprudence, linguistics, or philosophy which address the development of formal or computational models of legal knowledge, reasoning, and decision making. In-depth studies of innovative artificial intelligence systems that are being used in the legal domain. Studies which address the legal, ethical and social implications of the field of Artificial Intelligence and Law. Topics of interest include, but are not limited to, the following: Computational models of legal reasoning and decision making; judgmental reasoning, adversarial reasoning, case-based reasoning, deontic reasoning, and normative reasoning. Formal representation of legal knowledge: deontic notions, normative modalities, rights, factors, values, rules. Jurisprudential theories of legal reasoning. Specialized logics for law. Psychological and linguistic studies concerning legal reasoning. Legal expert systems; statutory systems, legal practice systems, predictive systems, and normative systems. AI and law support for legislative drafting, judicial decision-making, and public administration. Intelligent processing of legal documents; conceptual retrieval of cases and statutes, automatic text understanding, intelligent document assembly systems, hypertext, and semantic markup of legal documents. Intelligent processing of legal information on the World Wide Web, legal ontologies, automated intelligent legal agents, electronic legal institutions, computational models of legal texts. Ramifications for AI and Law in e-Commerce, automatic contracting and negotiation, digital rights management, and automated dispute resolution. Ramifications for AI and Law in e-governance, e-government, e-Democracy, and knowledge-based systems supporting public services, public dialogue and mediation. Intelligent computer-assisted instructional systems in law or ethics. Evaluation and auditing techniques for legal AI systems. Systemic problems in the construction and delivery of legal AI systems. Impact of AI on the law and legal institutions. Ethical issues concerning legal AI systems. In addition to original research contributions, the Journal will include a Book Review section, a series of Technology Reports describing existing and emerging products, applications and technologies, and a Research Notes section of occasional essays posing interesting and timely research challenges for the field of Artificial Intelligence and Law. Financial support for the Journal of Artificial Intelligence and Law is provided by the University of Pittsburgh School of Law.
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