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Demetics 超声辅助诊断系统在甲状腺良恶性结节鉴别诊断中的价值及影响因素分析。

The value of the Demetics ultrasound-assisted diagnosis system in the differential diagnosis of benign from malignant thyroid nodules and analysis of the influencing factors.

机构信息

Department of Ultrasound, Institute of Ultrasound in Musculoskeletal Sports Medicine, Guangdong Second Provincial General Hospital, Guangzhou, 510317, Guangdong, People's Republic of China.

Second School of Clinical Medicine, Southern Medical University, Guangzhou, Guangdong, People's Republic of China.

出版信息

Eur Radiol. 2021 Oct;31(10):7936-7944. doi: 10.1007/s00330-021-07884-z. Epub 2021 Apr 15.

DOI:10.1007/s00330-021-07884-z
PMID:33856523
Abstract

OBJECTIVES

To evaluate the value of Demetics and to explore whether Demetics can help radiologists with varying years of experience in the differential diagnosis of benign from malignant thyroid nodules.

METHODS

The clinical application value of Demetics was assessed by comparing the diagnostic accuracy of radiologists before and after applying Demetics. This retrospective analysis included 284 thyroid nodules that underwent pathological examinations. Two different combined methods were applied. Using method 1: the original TI-RADS classification was forcibly upgraded or downgraded by one level when Demetics classified the thyroid nodules as malignant or benign. Using method 2: the TI-RADS and benign or malignant classification of the thyroid nodules were flexibly adjusted after the physician learned the Demetics' results.

RESULTS

Demetics exhibited a higher sensitivity than did junior radiologist 1 (p = 0.029) and was similar in sensitivity to the two senior radiologists. Demetics had a higher AUC than both junior radiologists (p = 0.042, p = 0.038) and an AUC similar to that of the senior radiologists. The sensitivity (p = 0.035) and AUC (p = 0.031) of junior radiologist 1 and the specificity (p < 0.001) and AUC (p = 0.026) of junior radiologist 2 improved with combined method 1. The AUC of junior radiologist 2 improved with combined method 2 (p = 0.045). The factors influencing the diagnostic results of Demetics include sonographic signs (echogenicity and echogenic foci), contrast of the image, and nodule size.

CONCLUSION

Demetics exhibited high sensitivity and accuracy in the differential diagnosis of benign from malignant thyroid nodules. Demetics could improve the diagnostic accuracy of junior radiologists.

KEY POINTS

• Demetics exhibited a high sensitivity and accuracy in the differential diagnosis of benign from malignant thyroid nodules. • Demetics could improve the diagnostic accuracy of junior radiologists in the differential diagnosis of benign from malignant thyroid nodules. • Factors influencing the diagnostic results of Demetics include the sonographic signs (echogenicity and echogenic foci), contrast of the image, and nodule size.

摘要

目的

评估 Demetics 的价值,并探讨 Demetics 是否可以帮助不同经验年限的放射科医生对甲状腺良恶性结节进行鉴别诊断。

方法

通过比较应用 Demetics 前后放射科医生的诊断准确性来评估 Demetics 的临床应用价值。本回顾性分析纳入了 284 个经病理检查的甲状腺结节。应用了两种不同的联合方法。方法 1:当 Demetics 将甲状腺结节分类为恶性或良性时,强制将原始 TI-RADS 分类向上或向下升级一级。方法 2:在医生了解 Demetics 结果后,灵活调整 TI-RADS 和甲状腺结节的良性或恶性分类。

结果

Demetics 的敏感性高于初级放射科医生 1(p = 0.029),与两位高级放射科医生的敏感性相似。Demetics 的 AUC 高于两位初级放射科医生(p = 0.042,p = 0.038),与高级放射科医生的 AUC 相似。初级放射科医生 1 的敏感性(p = 0.035)和 AUC(p = 0.031)以及初级放射科医生 2 的特异性(p < 0.001)和 AUC(p = 0.026)随着联合方法 1 的应用而提高。随着联合方法 2 的应用,初级放射科医生 2 的 AUC 得到改善(p = 0.045)。影响 Demetics 诊断结果的因素包括超声征象(回声和回声灶)、图像对比度和结节大小。

结论

Demetics 在甲状腺良恶性结节的鉴别诊断中具有较高的敏感性和准确性。Demetics 可以提高初级放射科医生的诊断准确性。

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2
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Breast. 2020 Feb;49:25-32. doi: 10.1016/j.breast.2019.10.001. Epub 2019 Oct 11.
计算机辅助诊断在住院医师乳腺影像报告和数据系统超声培训中的应用——一项随机对照研究。
Transl Cancer Res. 2024 Apr 30;13(4):1969-1979. doi: 10.21037/tcr-23-2122. Epub 2024 Apr 22.
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Front Endocrinol (Lausanne). 2023 Aug 31;14:1227339. doi: 10.3389/fendo.2023.1227339. eCollection 2023.
5
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JAMA Netw Open. 2023 May 1;6(5):e2313674. doi: 10.1001/jamanetworkopen.2023.13674.
6
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