S-DETECT SOFTWARE AS A TOOL FOR ULTRASOUND DIAGNOSIS OF THYROID LESIONS

A. Kultaev, I. Zakiryarov, D. Abdieva, A. Imambetova, A. Akhmetbayeva
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Abstract

Relevance: Thyroid cancer (TC) is the most common oncological pathology of the endocrine organs. According to the International Agency for Research on Cancer (IARC), 567,233 new cases of thyroid cancer were registered worldwide in 2018. According to IARC, in 2018, 486 new cases were detected in Kazakhstan, which accounted for 1.4% of all cases in Asian countries. TC ranks 10th in the overall structure of cancer incidence globally; TC accounts for 3.1% of all cases of primary malignant tumors. Despite the relatively low incidence, the problems of pathogenesis have been extremely relevant in recent decades due to the increasing prevalence of thyroid cancer. Samsung Medison introduced AI-based S-Detect to improve sensitivity, specificity, and accuracy in the differential diagnosis of thyroid masses. The study aimed to explore the S-Detect program capacities in differential diagnostics of thyroid masses. Methods: 75 patients with focal lesions in the thyroid gland were examined using the Samsung Medison RS85 ultrasound machine equipped with the S-Detect program; additionally, Doppler and non-Doppler methods were used. Results: The S-Detect program made it possible to make a correct diagnosis in 97% of patients (73 of 75), which was confirmed by the results of morphological verification (histology, cytology). The sonoelastography method showed correct results in 91% of patients (68 of 75). Conclusion: The use of the S-Detect program for thyroid examination positively affects the diagnostic value of ultrasound in the differential diagnosis of thyroid masses, increasing the sensitivity, specificity, and accuracy of diagnosis, as well as avoiding redundant biopsies.
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S-detect软件作为超声诊断甲状腺病变的工具
相关性:甲状腺癌(TC)是内分泌器官最常见的肿瘤病理。根据国际癌症研究机构(IARC)的数据,2018年全球新登记的甲状腺癌病例为567,233例。据国际癌症研究机构称,2018年,哈萨克斯坦发现了486例新病例,占亚洲国家所有病例的1.4%。TC在全球癌症发病率总体结构中排名第10位;TC占所有原发性恶性肿瘤病例的3.1%。尽管发病率相对较低,但近几十年来,由于甲状腺癌的发病率不断上升,发病机制的问题已经非常重要。三星麦迪森推出了基于人工智能的S-Detect,以提高甲状腺肿块鉴别诊断的敏感性、特异性和准确性。本研究旨在探讨S-Detect程序在甲状腺肿块鉴别诊断中的能力。方法:对75例甲状腺局灶性病变患者,采用安装S-Detect程序的三星麦迪森RS85超声机进行检查;此外,采用多普勒和非多普勒方法。结果:S-Detect程序使97%的患者(75例中的73例)能够做出正确的诊断,这得到了形态学验证(组织学、细胞学)结果的证实。超声弹性成像方法在91%的患者(75例中的68例)中显示正确结果。结论:应用S-Detect程序进行甲状腺检查,可积极影响超声在甲状腺肿块鉴别诊断中的诊断价值,提高诊断的敏感性、特异性和准确性,避免重复活检。
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