Development and validation of a Web‐based malignancy risk‐stratification system of thyroid nodules

2020 ◽  
Vol 93 (6) ◽  
pp. 729-738
Author(s):  
Bin Zhang ◽  
Shufang Pei ◽  
Qiuying Chen ◽  
Yuhao Dong ◽  
Lu Zhang ◽  
...  
Keyword(s):  
Risk Stratification ◽  
Thyroid Nodules ◽  
Web Based ◽  
Malignancy Risk ◽  
Stratification System ◽  
Development And Validation ◽  
Risk Stratification System

scholarly journals A Novel Risk Stratification System for Thyroid Nodules With Indeterminate Cytology—A Pilot Cohort Study

2020 ◽  
Vol 11 ◽  
Author(s):  
Cristiane J. Gomes-Lima ◽  
Sungyoung Auh ◽  
Shilpa Thakur ◽  
Marina Zemskova ◽  
Craig Cochran ◽  
...  
Keyword(s):  
Cohort Study ◽  
Risk Stratification ◽  
Thyroid Nodules ◽  
Stratification System ◽  
Indeterminate Cytology ◽  
Risk Stratification System

Web-Based Malignancy Risk Estimation for Thyroid Nodules Using Ultrasonography Characteristics: Development and Validation of a Predictive Model

Thyroid ◽  
2015 ◽  
Vol 25 (12) ◽  
pp. 1306-1312 ◽  
Author(s):  
Young Jun Choi ◽  
Jung Hwan Baek ◽  
Seung Hee Baek ◽  
Woo Hyun Shim ◽  
Kang Dae Lee ◽  
...  
Keyword(s):  
Predictive Model ◽  
Thyroid Nodules ◽  
Risk Estimation ◽  
Web Based ◽  
Malignancy Risk ◽  
Characteristics Development ◽  
Development And Validation

scholarly journals OR27-3 A Novel Risk Stratification System for Thyroid Nodules with Indeterminate Cytology: A Pilot Cohort Study

2019 ◽  
Vol 3 (Supplement_1) ◽  
Author(s):  
Cristiane Gomes-Lima ◽  
Sungyoung Auh ◽  
Shilpa Thakur ◽  
Marina Zemskova ◽  
Craig Cochran ◽  
...  
Keyword(s):  
Cohort Study ◽  
Risk Stratification ◽  
Thyroid Nodules ◽  
Stratification System ◽  
Indeterminate Cytology ◽  
Risk Stratification System

Development and validation of an improved classification and risk stratification system for carotid body tumors: Multinational collaborative cohort study

Head & Neck ◽  
2021 ◽  
Vol 43 (11) ◽  
pp. 3448-3458
Author(s):  
Hisham Mehanna ◽  
Pankaj Mistry ◽  
Pawel Golusinski ◽  
Pasquale Di Maio ◽  
Paul Nankivell ◽  
...  
Keyword(s):  
Cohort Study ◽  
Risk Stratification ◽  
Carotid Body ◽  
Carotid Body Tumors ◽  
Stratification System ◽  
Development And Validation ◽  
Risk Stratification System

scholarly journals Nodules with nonspecific ultrasound pattern according to the 2015 American Thyroid Association malignancy risk stratification system

Medicine ◽  
2019 ◽  
Vol 98 (44) ◽  
pp. e17657
Author(s):  
Pingping Xiang ◽  
Xiaoqiu Chu ◽  
Guofang Chen ◽  
Binbin Liu ◽  
Wenbo Ding ◽  
...  
Keyword(s):  
Risk Stratification ◽  
American Thyroid Association ◽  
Malignancy Risk ◽  
Stratification System ◽  
Risk Stratification System

scholarly journals A Preliminary Study of Quantitative Ultrasound for Cancer-Risk Assessment of Thyroid Nodules

2021 ◽  
Vol 12 ◽  
Author(s):  
Poorani N. Goundan ◽  
Jonathan Mamou ◽  
Daniel Rohrbach ◽  
Jason Smith ◽  
Harshal Patel ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Risk Stratification ◽  
Papillary Thyroid Cancer ◽  
Quantitative Ultrasound ◽  
Thyroid Nodules ◽  
Papillary Thyroid ◽  
Gray Scale ◽  
Preliminary Study ◽  
Stratification System ◽  
Risk Stratification System

BackgroundGray-scale, B-mode ultrasound (US) imaging is part of the standard clinical procedure for evaluating thyroid nodules (TNs). It is limited by its instrument- and operator-dependence and inter-observer variability. In addition, the accepted high-risk B-mode US TN features are more specific for detecting classic papillary thyroid cancer rather than the follicular variant of papillary thyroid cancer or follicular thyroid cancer. Quantitative ultrasound (QUS) is a technique that can non-invasively assess properties of tissue microarchitecture by exploiting information contained in raw ultrasonic radiofrequency (RF) echo signals that is discarded in conventional B-mode imaging. QUS provides quantitative parameter-value estimates that are a function of the properties of US scatterers and microarchitecture of the tissue. The purpose of this preliminary study was to assess the performance of QUS parameters in evaluating benign and malignant thyroid nodules.MethodsPatients from the Thyroid Health Center at the Boston Medical Center were recruited to participate. B-mode and RF data were acquired and analyzed in 225 TNs (24 malignant and 201 benign) from 208 patients. These data were acquired either before (167 nodules) or after (58 nodules) subjects underwent fine-needle biopsy (FNB). The performance of a combination of QUS parameters (CQP) was assessed and compared with the performance of B-mode risk-stratification systems.ResultsCQP produced an ROC AUC value of 0.857 ± 0.033 compared to a value of 0.887 ± 0.033 (p=0.327) for the American College of Radiology Thyroid Imaging, Reporting and Data System (ACR TI-RADS) and 0.880 ± 0.041 (p=0.367) for the American Thyroid Association (ATA) risk-stratification system. Furthermore, using a CQP threshold of 0.263 would further reduce the number of unnecessary FNBs in 44% of TNs without missing any malignant TNs. When CQP used in combination with ACR TI-RADS, a potential additional reduction of 49 to 66% in unnecessary FNBs was demonstrated.ConclusionThis preliminary study suggests that QUS may provide a method to classify TNs when used by itself or when combined with a conventional gray-scale US risk-stratification system and can potentially reduce the need to biopsy TNs.

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