Comparative Analysis of AI-SONICTM Thyroid System and Six Thyroid Risk Stratification Guidelines in Papillary Thyroid Cancer: A Retrospective Cohort Study.

IF 2.8 3区医学 Q1 Pharmacology, Toxicology and Pharmaceutics

Therapeutics and Clinical Risk Management Pub Date : 2024-08-23 eCollection Date: 2024-01-01 DOI:10.2147/TCRM.S458576

Mingyan Wang, Siyuan Yang, Linxin Yang, Ning Lin

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引用次数: 0

Abstract

Aim: The study aimed to compare the diagnostic performance of AI-SONICTM Thyroid System (AI-SONICTM) with six thyroid nodule ultrasound risk stratification systems, as well as the interobserver agreement among different-year ultrasound examiners using the same diagnostic approach.

Methods: This retrospective study included patients who underwent thyroid ultrasound examination and surgery between 2010 and 2022. Three ultrasound examiners with 2, 5, and 10 years of experience, respectively, used AI-SONICTM and six guidelines to risk-stratify the nodules. The diagnostic performance and interobserver agreement were assessed.

Results: A total of 370 thyroid nodules were included, including 195 papillary thyroid carcinomas (PTC) and 175 benign nodules. For physicians of varying seniority from low to high, AI-SONICTM had a moderate sensitivities of 82.56%, 83.08%, 84.62%, respectively, while AACE/ACE/AME had the highest diagnostic sensitivities (96.41%, 95.38%, 96.41%, respectively); And relatively higher specificities were 85.14%, 85.71%, 85.71% for KSThR, while moderate specificities with values of 84.0%, 85.14%, and 85.71%, respectively were found for AI-SONICTM; The accuracy was highest for ATA (excluding non-classifiable nodules), with values of 87.26%, 87.93%, and 88.82%, respectively, while the accuracy for AI-SONICTM were 83.24%, 84.05%, and 85.14%, respectively. The Kendall's tau coefficient indicated strong or moderate interobserver agreement among all examiners using different diagnostic methods (Kendall's tau coefficient >0.6, P<0.001). AI-SONICTM showed the highest interobserver agreement (Kendall's tau coefficient=0.995, P<0.001). A binary probit regression analysis showed that nodules with cystic components had a significantly higher regression coefficient value of 0.983 (P=0.002), indicating that AI-SONICTM may have higher accuracy for nodules with cystic components.

Conclusion: AI-SONICTM and the six thyroid nodule ultrasound risk stratification systems showed high diagnostic performance for papillary thyroid carcinoma. All examiners showed strong or moderate interobserver agreement when using different diagnostic methods. AI-SONICTM may have higher accuracy for nodules with cystic components.

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AI-SONICTM 甲状腺系统与六种甲状腺乳头状癌风险分层指南的比较分析：回顾性队列研究

目的：该研究旨在比较AI-SONICTM甲状腺系统（AI-SONICTM）与六种甲状腺结节超声风险分层系统的诊断性能，以及使用相同诊断方法的不同年份超声检查者之间的观察者间一致性：这项回顾性研究纳入了2010年至2022年间接受甲状腺超声检查和手术的患者。三位分别拥有 2 年、5 年和 10 年经验的超声检查员使用 AI-SONICTM 和六项指南对结节进行风险分级。结果：结果：共纳入370个甲状腺结节，包括195个甲状腺乳头状癌（PTC）和175个良性结节。对于从低到高不同资历的医生，AI-SONICTM 的灵敏度中等，分别为 82.56%、83.08% 和 84.62%，而 AACE/ACE/AME 的诊断灵敏度最高（分别为 96.41%、95.38% 和 96.41%）；特异性相对较高，分别为 85.14%、85.71% 和 85.71%。KSThR 的特异性分别为 85.14%、85.71% 和 85.71%，而 AI-SONICTM 的特异性适中，分别为 84.0%、85.14% 和 85.71%；ATA（不包括不可分类的结节）的准确性最高，分别为 87.26%、87.93% 和 88.82%，而 AI-SONICTM 的准确性分别为 83.24%、84.05% 和 85.14%。Kendall's tau 系数表明，使用不同诊断方法的所有检查者之间的观察者间一致性很强或中等（Kendall's tau 系数大于 0.6，PC 结论：AI-SONICTM和六种甲状腺结节超声风险分层系统对甲状腺乳头状癌的诊断率很高。在使用不同诊断方法时，所有检查者都表现出较强或中等程度的观察者间一致性。对于有囊性成分的结节，AI-SONICTM 的准确性可能更高。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Therapeutics and Clinical Risk Management HEALTH CARE SCIENCES & SERVICES-

CiteScore

5.30

自引率

3.60%

发文量

139

审稿时长

16 weeks

期刊介绍： Therapeutics and Clinical Risk Management is an international, peer-reviewed journal of clinical therapeutics and risk management, focusing on concise rapid reporting of clinical studies in all therapeutic areas, outcomes, safety, and programs for the effective, safe, and sustained use of medicines, therapeutic and surgical interventions in all clinical areas. The journal welcomes submissions covering original research, clinical and epidemiological studies, reviews, guidelines, expert opinion and commentary. The journal will consider case reports but only if they make a valuable and original contribution to the literature. As of 18th March 2019, Therapeutics and Clinical Risk Management will no longer consider meta-analyses for publication. The journal does not accept study protocols, animal-based or cell line-based studies.