Multiparametric ultrasound techniques are superior to AI-assisted ultrasound for assessment of solid thyroid nodules: a prospective study.

IF 3.7 3区医学 Q2 Medicine

Endocrine Pub Date : 2025-07-10 DOI:10.1007/s12020-025-04306-8

Yingying Li, Xinyang Li, Lin Yan, Jing Xiao, Zhen Yang, Mingbo Zhang, Yukun Luo

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引用次数: 0

Abstract

Objectives: To evaluate the diagnostic performance of multiparametric ultrasound (mpUS) and AI-assisted B-mode ultrasound (AI-US), and their potential to reduce unnecessary biopsies to B-mode for solid thyroid nodules.

Methods: This prospective study enrolled 226 solid thyroid nodules with 145 malignant and 81 benign pathological results from 189 patients (35 men and 154 women; age range, 19-73 years; mean age, 45 years). Each nodule was examined using B-mode, microvascular flow imaging (MVFI), elastography with elasticity contrast index (ECI), and an AI system. Image data were recorded for each modality. Ten readers with different experience levels independently evaluated the B-mode images of each nodule to make a "benign" or "malignant" diagnosis in both an unblinded and blinded manner to the AI reports. The most accurate ECI value and MVFI mode were selected and combined with the dichotomous prediction of all readers. Descriptive statistics and AUCs were used to evaluate the diagnostic performances of mpUS and AI-US.

Results: Triple mpUS with B-mode, MVFI, and ECI exhibited the highest diagnostic performance (average AUC = 0.811 vs. 0.677 for B-mode, p = 0.001), followed by AI-US (average AUC = 0.718, p = 0.315). Triple mpUS significantly reduced the unnecessary biopsy rate by up to 12% (p = 0.007). AUC and specificity were significantly higher for triple mpUS than for AI-US mode (both p < 0.05).

Conclusions: Compared to AI-US, triple mpUS (B-mode, MVFI, and ECI) exhibited better diagnostic performance for thyroid cancer diagnosis, and resulted in a significant reduction in unnecessary biopsy rate. AI systems are expected to take advantage of multi-modal information to facilitate diagnoses.

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多参数超声技术优于人工智能辅助超声评估甲状腺实性结节：一项前瞻性研究。

目的：评价多参数超声（mpUS）和人工智能辅助b超（AI-US）对甲状腺实性结节的诊断性能，以及它们减少不必要的b超活检的潜力。方法：这项前瞻性研究纳入了226例甲状腺实性结节，其中145例为恶性，81例为良性，来自189例患者(男性35例，女性154例；年龄19-73岁；平均年龄45岁)。每个结节均采用b超、微血管血流成像（MVFI）、弹性对比指数弹性成像（ECI）和人工智能系统进行检查。记录每个模态的图像数据。10名不同经验水平的读者独立评估每个结节的b超图像，对人工智能报告进行非盲和盲两种方式的“良性”或“恶性”诊断。选择最准确的ECI值和MVFI模式与所有读取器的二分类预测相结合。采用描述性统计和auc对mpUS和AI-US的诊断性能进行评价。结果：具有b模式、MVFI和ECI的三重mpUS表现出最高的诊断性能（平均AUC = 0.811， b模式为0.677,p = 0.001），其次是AI-US（平均AUC = 0.718, p = 0.315）。三重mpUS显著降低了12%的不必要活检率（p = 0.007）。结论：与AI-US相比，三重mpUS （B-mode、MVFI和ECI）在甲状腺癌诊断中表现出更好的诊断性能，并显著降低了不必要的活检率。人工智能系统有望利用多模态信息来促进诊断。

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

Endocrine 医学-内分泌学与代谢

CiteScore

6.40

自引率

5.40%

发文量

期刊介绍： Well-established as a major journal in today’s rapidly advancing experimental and clinical research areas, Endocrine publishes original articles devoted to basic (including molecular, cellular and physiological studies), translational and clinical research in all the different fields of endocrinology and metabolism. Articles will be accepted based on peer-reviews, priority, and editorial decision. Invited reviews, mini-reviews and viewpoints on relevant pathophysiological and clinical topics, as well as Editorials on articles appearing in the Journal, are published. Unsolicited Editorials will be evaluated by the editorial team. Outcomes of scientific meetings, as well as guidelines and position statements, may be submitted. The Journal also considers special feature articles in the field of endocrine genetics and epigenetics, as well as articles devoted to novel methods and techniques in endocrinology. Endocrine covers controversial, clinical endocrine issues. Meta-analyses on endocrine and metabolic topics are also accepted. Descriptions of single clinical cases and/or small patients studies are not published unless of exceptional interest. However, reports of novel imaging studies and endocrine side effects in single patients may be considered. Research letters and letters to the editor related or unrelated to recently published articles can be submitted. Endocrine covers leading topics in endocrinology such as neuroendocrinology, pituitary and hypothalamic peptides, thyroid physiological and clinical aspects, bone and mineral metabolism and osteoporosis, obesity, lipid and energy metabolism and food intake control, insulin, Type 1 and Type 2 diabetes, hormones of male and female reproduction, adrenal diseases pediatric and geriatric endocrinology, endocrine hypertension and endocrine oncology.