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ACR TI-RADS 4-5类伴有粗大钙化的甲状腺结节的Hounsfield单位值:一项有助于诊断的重要影像特征

Hounsfield Unit Values in ACR TI-RADS 4-5 Thyroid Nodules with Coarse Calcifications: An Important Imaging Feature Helpful for Diagnosis.

作者信息

Wei Pei-Ying, Jiang Nian-Dong, Xiang Jing-Jing, Xu Chen-Ke, Ding Jin-Wang, Wang Hai-Bin, Luo Ding-Cun, Han Zhi-Jiang

机构信息

Department of Radiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China.

Department of Radiology, Chunan County Hospital of Traditional Chinese Medicine, Hangzhou, People's Republic of China.

出版信息

Cancer Manag Res. 2020 Apr 22;12:2711-2717. doi: 10.2147/CMAR.S242524. eCollection 2020.

DOI:10.2147/CMAR.S242524
PMID:32368148
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7184120/
Abstract

PURPOSE

The purpose of this study is to investigate the diagnostic role of Hounsfield unit (HU) values on noncontrast computed tomography (CT) for differentiating benignity from malignancy in the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) 4-5 nodules with coarse calcifications.

PATIENTS AND METHODS

CT images of 216 ACR TI-RADS 4-5 nodules with coarse calcifications from 207 patients who underwent surgery in our hospital between 2017 and 2019 were retrospectively reviewed. The average HU values (AHUVs) and maximum HU values (MHUVs) of the nodules were measured on noncontrast CT. The distribution of AHUVs and MHUVs in benign and malignant nodules with coarse calcifications was analyzed using the Mann-Whitney test. Receiver operating characteristic (ROC) curves were used to identify the best cut-off values. Diagnostic performances were assessed according to the area under the ROC curve (AUC), sensitivity and specificity.

RESULTS

Of the 216 ACR TI-RADS 4-5 nodules with coarse calcifications, 170 were benign and 46 were malignant. The AHUVs of benign and malignant nodules were 791 HU [interquartile range (IQR), 543-1025 HU] and 486 HU (IQR, 406-670 HU), respectively ( < 0.001). The MHUVs of benign and malignant nodules were 1084 HU (IQR, 717-1477 HU) and 677 HU (IQR, 441-986 HU), respectively ( < 0.001). The AUCs for AHUVs and MHUVs for predicting benign nodules with coarse calcifications were 0.759 and 0.732, and the cut-off values were 627.5 HU and 806.0 HU, with sensitivities of 67.6% and 68.8% and specificities of 73.9% and 67.4%, respectively. The sensitivity and specificity of the combination were 68.8% and 76.1%.

CONCLUSION

AHUVs and MHUVs were helpful in differentiating benignity from malignancy in ACR TI-RADS 4-5 nodules with coarse calcifications. This may provide an important basis for reducing misdiagnosis and unnecessary aspiration or surgical trauma.

摘要

目的

本研究旨在探讨美国放射学会(ACR)甲状腺影像报告和数据系统(TI-RADS)4-5类伴有粗大钙化的结节在非增强计算机断层扫描(CT)上的Hounsfield单位(HU)值对鉴别良恶性的诊断作用。

患者与方法

回顾性分析2017年至2019年在我院接受手术的207例患者的216个ACR TI-RADS 4-5类伴有粗大钙化的结节的CT图像。在非增强CT上测量结节的平均HU值(AHUVs)和最大HU值(MHUVs)。采用Mann-Whitney检验分析AHUVs和MHUVs在伴有粗大钙化的良性和恶性结节中的分布情况。使用受试者操作特征(ROC)曲线确定最佳截断值。根据ROC曲线下面积(AUC)、敏感性和特异性评估诊断性能。

结果

在216个ACR TI-RADS 4-5类伴有粗大钙化的结节中,170个为良性,46个为恶性。良性和恶性结节的AHUVs分别为791 HU [四分位数间距(IQR),543 - 1025 HU]和486 HU(IQR,406 - 670 HU)(<0.001)。良性和恶性结节的MHUVs分别为1084 HU(IQR,717 - 1477 HU)和677 HU(IQR,441 - 986 HU)(<0.001)。AHUVs和MHUVs预测伴有粗大钙化的良性结节的AUC分别为0.759和0.732,截断值分别为627.5 HU和806.0 HU,敏感性分别为67.6%和68.8%,特异性分别为73.9%和67.4%。联合检测的敏感性和特异性分别为68.8%和76.1%。

结论

AHUVs和MHUVs有助于鉴别ACR TI-RADS 4-5类伴有粗大钙化的结节的良恶性。这可能为减少误诊以及避免不必要的穿刺或手术创伤提供重要依据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e692/7184120/8cdcc6dced2c/CMAR-12-2711-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e692/7184120/dff42199061d/CMAR-12-2711-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e692/7184120/3d298868feee/CMAR-12-2711-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e692/7184120/dea1d5bb9e53/CMAR-12-2711-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e692/7184120/556e8d03d781/CMAR-12-2711-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e692/7184120/8cdcc6dced2c/CMAR-12-2711-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e692/7184120/dff42199061d/CMAR-12-2711-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e692/7184120/3d298868feee/CMAR-12-2711-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e692/7184120/dea1d5bb9e53/CMAR-12-2711-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e692/7184120/556e8d03d781/CMAR-12-2711-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e692/7184120/8cdcc6dced2c/CMAR-12-2711-g0005.jpg

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