Literature DB >> 32775255

The analysis of differential diagnosis of benign and malignant thyroid nodules based on ultrasound reports.

Shumei Miao1,2, Mang Jing1,2, Rongrong Sheng1,2, Dai Cui3, Shan Lu4, Xin Zhang1,2, Shenqi Jing1,2, Xiaoliang Zhang1,2, Tao Shan1,2, Hongwei Shan1,2, Tingyu Xu1, Bing Wang1, Zhongmin Wang2, Yun Liu2.   

Abstract

BACKGROUND: Thyroid cancer is a common endocrine tumor, the incidence of which is increasing each year. Early diagnosis and treatment can effectively prevent thyroid cancer. This article uses Chinese's ultrasound reports to determine the value of early diagnosis.
METHODS: The clinical data center of the First Affiliated Hospital of Nanjing Medical University was screened for patients diagnosed with a thyroid nodule, who had undergone a thyroid function test, ultrasound records and pathological assessment. A total of 811 patients with a total of 1,290 pathologically confirmed nodules (506 benign and 784 malignant) were enrolled. Logistic regression was used to analyze the variables that significantly affected malignant nodules. The sensitivity and specificity of ultrasound thyroid imaging-reporting and data system (TI-RADS) classification results for benign and malignant tumors were calculated.
RESULTS: The age of the patients had a very significant difference in the classification of benign and malignant nodules (P<0.001), and the marital status was significantly different (P<0.05). Gender and medical insurance had no significant effect (P>0.05). Thyroglobulin (TG), free thyroxine (FT4), and free triiodothyronine (FT3) had significant effects (P=0.003) on the incidence of malignant nodules in patients, while thyroid-stimulating hormone (TSH) had no significant effect (P>0.05). Ultrasound analysis showed a Youden's index of 78.97%, a positive predictive value of 93.20%, and a negative predicted value of 84.10% at the most excellent classification effect. The sensitivity was 89.0%, the specificity was 89.9%; much greater than the classification model based on the thyroid function test (sensitivity =80.6%, specificity =55.8%).
CONCLUSIONS: The present study verifies the effectiveness of using TI-RADS classification for diagnosis of benign and malignant thyroid nodules, and explores the use of new analysis methods for clinical data. To reduce dependence on the doctors, ultrasound image data and clinical phenotypic data can be further used to assist clinical decision making. 2020 Gland Surgery. All rights reserved.

Entities:  

Keywords:  Pathological; thyroid; thyroid imaging-reporting and data system (TI-RADS); ultrasound

Year:  2020        PMID: 32775255      PMCID: PMC7347809          DOI: 10.21037/gs.2020.04.03

Source DB:  PubMed          Journal:  Gland Surg        ISSN: 2227-684X


  23 in total

1.  Correlation analysis of ultrasonic characteristics, pathological type, and molecular markers of thyroid nodules.

Authors:  J J Su; L Z Hui; C J Xi; G Q Su
Journal:  Genet Mol Res       Date:  2015-01-15

Review 2.  Current controversies and future directions in the diagnosis and management of differentiated thyroid cancers.

Authors:  Timothy M Ullmann; Katherine D Gray; Maureen D Moore; Rasa Zarnegar; Thomas J Fahey
Journal:  Gland Surg       Date:  2018-10

3.  Ultrasonography scoring systems can rule out malignancy in cytologically indeterminate thyroid nodules.

Authors:  Giorgio Grani; Livia Lamartina; Valeria Ascoli; Daniela Bosco; Francesco Nardi; Ferdinando D'Ambrosio; Antonello Rubini; Laura Giacomelli; Marco Biffoni; Sebastiano Filetti; Cosimo Durante; Vito Cantisani
Journal:  Endocrine       Date:  2016-10-31       Impact factor: 3.633

4.  Nomenclature Revision for Encapsulated Follicular Variant of Papillary Thyroid Carcinoma: A Paradigm Shift to Reduce Overtreatment of Indolent Tumors.

Authors:  Yuri E Nikiforov; Raja R Seethala; Giovanni Tallini; Zubair W Baloch; Fulvio Basolo; Lester D R Thompson; Justine A Barletta; Bruce M Wenig; Abir Al Ghuzlan; Kennichi Kakudo; Thomas J Giordano; Venancio A Alves; Elham Khanafshar; Sylvia L Asa; Adel K El-Naggar; William E Gooding; Steven P Hodak; Ricardo V Lloyd; Guy Maytal; Ozgur Mete; Marina N Nikiforova; Vania Nosé; Mauro Papotti; David N Poller; Peter M Sadow; Arthur S Tischler; R Michael Tuttle; Kathryn B Wall; Virginia A LiVolsi; Gregory W Randolph; Ronald A Ghossein
Journal:  JAMA Oncol       Date:  2016-08-01       Impact factor: 31.777

5.  Machine Learning-Assisted System for Thyroid Nodule Diagnosis.

Authors:  Bin Zhang; Jie Tian; Shufang Pei; Yubing Chen; Xin He; Yuhao Dong; Lu Zhang; Xiaokai Mo; Wenhui Huang; Shuzhen Cong; Shuixing Zhang
Journal:  Thyroid       Date:  2019-04-27       Impact factor: 6.568

Review 6.  Thyroid disorders in polycystic ovary syndrome.

Authors:  K Kowalczyk; G Franik; D Kowalczyk; D Pluta; Ł Blukacz; P Madej
Journal:  Eur Rev Med Pharmacol Sci       Date:  2017-01       Impact factor: 3.507

Review 7.  The accuracy of thyroid nodule ultrasound to predict thyroid cancer: systematic review and meta-analysis.

Authors:  Juan P Brito; Michael R Gionfriddo; Alaa Al Nofal; Kasey R Boehmer; Aaron L Leppin; Carl Reading; Matthew Callstrom; Tarig A Elraiyah; Larry J Prokop; Marius N Stan; M Hassan Murad; John C Morris; Victor M Montori
Journal:  J Clin Endocrinol Metab       Date:  2013-11-25       Impact factor: 5.958

8.  Utility of gray-scale ultrasound to differentiate benign from malignant thyroid nodules.

Authors:  Manju Bala Popli; Ashita Rastogi; Pjs Bhalla; Yachna Solanki
Journal:  Indian J Radiol Imaging       Date:  2012-01

9.  Computer-aided assessment of regional vascularity of thyroid nodules for prediction of malignancy.

Authors:  Faisal N Baig; Jurgen T J van Lunenburg; Shirley Y W Liu; Shea-Ping Yip; Helen K W Law; Michael Ying
Journal:  Sci Rep       Date:  2017-10-30       Impact factor: 4.379

10.  Worldwide increasing incidence of thyroid cancer: update on epidemiology and risk factors.

Authors:  Gabriella Pellegriti; Francesco Frasca; Concetto Regalbuto; Sebastiano Squatrito; Riccardo Vigneri
Journal:  J Cancer Epidemiol       Date:  2013-05-07
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  4 in total

1.  Analysis of the Application Value of Ultrasound Imaging Diagnosis in the Clinical Staging of Thyroid Cancer.

Authors:  Fengying Zhang; Yunxuan Sun; Xijiang Wu; Chunrong Meng; Meiling Xiang; Tingting Huang; Wenping Duan; Fangfang Wang; Zhaolan Sun
Journal:  J Oncol       Date:  2022-06-08       Impact factor: 4.501

2.  Diagnosis of Thyroid Nodules Based on Image Enhancement and Deep Neural Networks.

Authors:  Xuesi Ma; Lina Zhang
Journal:  Comput Intell Neurosci       Date:  2022-02-15

3.  Knockdown of long non‑coding RNA CCAT2 suppresses the progression of thyroid cancer by inhibiting the Wnt/β‑catenin pathway.

Authors:  Suping Xin; Xinhua Ye
Journal:  Int J Mol Med       Date:  2020-10-19       Impact factor: 4.101

4.  Prediction of thyroid nodule histopathology by expert ultrasound evaluation.

Authors:  Olav Inge Håskjold; Henrik Stenestø Foshaug; Therese Benedikte Iversen; Helga Charlotte Kjøren; Vegard Heimly Brun
Journal:  Endocr Connect       Date:  2021-07-17       Impact factor: 3.335

  4 in total

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