Literature DB >> 31741167

Interobserver agreement and efficacy of consensus reading in Kwak-, EU-, and ACR-thyroid imaging recording and data systems and ATA guidelines for the ultrasound risk stratification of thyroid nodules.

Philipp Seifert1, Rainer Görges2,3, Michael Zimny4, Michael C Kreissl5, Simone Schenke4,5.   

Abstract

PURPOSE: To investigate the interobserver agreement (IA) and the impact of consensus reading using four risk stratification systems for thyroid nodules (TN).
METHODS: Four experienced specialists independently rated US images of 80 TN according to the Kwak-TIRADS, EU-TIRADS, ACR TI-RADS, and ATA Guidelines. The cases were randomly extracted from a prospectively acquired database (n > 1500 TN). The observers were blinded to clinical data. This study was divided into two sessions (S1 and S2) with 40 image sets each. After every session, a consensus reading was carried out (C1, C2). Subsequently, the effect of C1 was tested in S2 with 40 new cases followed by C2. Fleiss' kappa (κ) was calculated for S1 and S2 to estimate the IA and learning curves. The results of C1 and C2 were used as reference for diagnostic accuracy calculations.
RESULTS: IA significantly increased (p < 0.01) after C1 with κ values of 0.375 (0.615), 0.411 (0.596), 0.321 (0.569), and 0.410 (0.583) for the Kwak-TIRADS, EU-TIRADS, ACR TI-RADS, and ATA Guidelines in S1 (S2), respectively. ROC analysis (C1 + C2) revealed similar areas under the curve (AUC) for the Kwak-TIRADS, EU-TIRADS, ACR TI-RADS, and ATA Guidelines (0.635, 0.675, 0.694, and 0.654, respectively, n.s.). AUC did not increase from C1 (0.677 ± 0.010) to C2 (0.632 ± 0.052, n.s.). ATA Guidelines were not applicable in five cases.
CONCLUSIONS: IA and diagnostic accuracy were very similar for the four investigated risk stratification systems. Consensus reading sessions significantly improved the IA but did not affect the diagnostic accuracy.

Entities:  

Keywords:  Consensus; Head and neck neoplasms; Interobserver agreement; TI-RADS; Thyroid nodule; Ultrasonography

Mesh:

Year:  2019        PMID: 31741167     DOI: 10.1007/s12020-019-02134-1

Source DB:  PubMed          Journal:  Endocrine        ISSN: 1355-008X            Impact factor:   3.633


  57 in total

1.  Characterization of thyroid nodules using the proposed thyroid imaging reporting and data system (TI-RADS).

Authors:  Shih-Ping Cheng; Jie-Jen Lee; Jiun-Lu Lin; Shih-Ming Chuang; Ming-Nan Chien; Chien-Liang Liu
Journal:  Head Neck       Date:  2012-04-19       Impact factor: 3.147

2.  Variability in Interpretation of Ultrasound Elastography and Gray-Scale Ultrasound in Assessing Thyroid Nodules.

Authors:  Jieun Koh; Hee Jung Moon; Jeong Seon Park; Soo Jin Kim; Ha Yan Kim; Eun-Kyung Kim; Jin Young Kwak
Journal:  Ultrasound Med Biol       Date:  2015-09-19       Impact factor: 2.998

3.  TIRADS score is of limited clinical value for risk stratification of indeterminate cytological results.

Authors:  E Chaigneau; G Russ; B Royer; C Bigorgne; M Bienvenu-Perrard; A Rouxel; L Leenhardt; L Belin; C Buffet
Journal:  Eur J Endocrinol       Date:  2018-04-27       Impact factor: 6.664

4.  Diagnostic performance of ATA, BTA and TIRADS sonographic patterns in the prediction of malignancy in histologically proven thyroid nodules.

Authors:  Chiaw Ling Chng; Hong Chang Tan; Chow Wei Too; Wei Ying Lim; Priscilla Pei Sze Chiam; Ling Zhu; Nivedita Vikas Nadkarni; Adoree Yi Ying Lim
Journal:  Singapore Med J       Date:  2018-05-18       Impact factor: 1.858

5.  Interobserver Variability of Sonographic Features Used in the American College of Radiology Thyroid Imaging Reporting and Data System.

Authors:  Jenny K Hoang; William D Middleton; Alfredo E Farjat; Sharlene A Teefey; Nicole Abinanti; Fernando J Boschini; Abraham J Bronner; Nirvikar Dahiya; Barbara S Hertzberg; Justin R Newman; Daniel Scanga; Robert C Vogler; Franklin N Tessler
Journal:  AJR Am J Roentgenol       Date:  2018-04-27       Impact factor: 3.959

6.  Thyroid imaging reporting and data system for US features of nodules: a step in establishing better stratification of cancer risk.

Authors:  Jin Young Kwak; Kyung Hwa Han; Jung Hyun Yoon; Hee Jung Moon; Eun Ju Son; So Hee Park; Hyun Kyung Jung; Ji Soo Choi; Bo Mi Kim; Eun-Kyung Kim
Journal:  Radiology       Date:  2011-07-19       Impact factor: 11.105

7.  Grey-Scale Analysis Improves the Ultrasonographic Evaluation of Thyroid Nodules.

Authors:  Giorgio Grani; Mimma D'Alessandri; Giovanni Carbotta; Angela Nesca; Marianna Del Sordo; Stefania Alessandrini; Carmela Coccaro; Roberta Rendina; Marta Bianchini; Natalie Prinzi; Angela Fumarola
Journal:  Medicine (Baltimore)       Date:  2015-07       Impact factor: 1.889

8.  Ultrasonographic characteristics of medullary thyroid carcinoma: a comparison with papillary thyroid carcinoma.

Authors:  Mei-Juan Liu; Zhong-Feng Liu; Yuan-Yuan Hou; Yan-Ming Men; Yu-Xi Zhang; Ling-Yun Gao; Hao Liu
Journal:  Oncotarget       Date:  2017-04-18

Review 9.  Evaluation and Management of Indeterminate Thyroid Nodules: The Revolution of Risk Stratification Beyond Cytological Diagnosis.

Authors:  Pablo Valderrabano; Bryan McIver
Journal:  Cancer Control       Date:  2017 Oct-Dec       Impact factor: 3.302

10.  Calcifications in Thyroid Tumors on Ultrasonography: Calcification Types and Relationship with Histopathological Type.

Authors:  Kaoru Kobayashi; Tomoko Fujimoto; Hisashi Ota; Mitsuyoshi Hirokawa; Tomonori Yabuta; Hiroo Masuoka; Mitsuhiro Fukushima; Takuya Higashiyama; Minoru Kihara; Yasuhiro Ito; Akihiro Miya; Akira Miyauchi
Journal:  Ultrasound Int Open       Date:  2018-07-05
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  15 in total

1.  Strategy to reduce unnecessary surgeries in thyroid nodules with cytology of Bethesda category III (AUS/FLUS): a retrospective analysis of 667 patients diagnosed by surgery.

Authors:  Yong Joon Suh; Yeon Ju Choi
Journal:  Endocrine       Date:  2020-04-15       Impact factor: 3.633

2.  Systematic Review and Meta-Analysis of American College of Radiology TI-RADS Inter-Reader Reliability for Risk Stratification of Thyroid Nodules.

Authors:  Wei Li; Yuan Sun; Haibing Xu; Wenwen Shang; Anding Dong
Journal:  Front Oncol       Date:  2022-05-13       Impact factor: 5.738

3.  Deep Learning Based on ACR TI-RADS Can Improve the Differential Diagnosis of Thyroid Nodules.

Authors:  Ge-Ge Wu; Wen-Zhi Lv; Rui Yin; Jian-Wei Xu; Yu-Jing Yan; Rui-Xue Chen; Jia-Yu Wang; Bo Zhang; Xin-Wu Cui; Christoph F Dietrich
Journal:  Front Oncol       Date:  2021-04-27       Impact factor: 6.244

Review 4.  Contemporary Thyroid Nodule Evaluation and Management.

Authors:  Giorgio Grani; Marialuisa Sponziello; Valeria Pecce; Valeria Ramundo; Cosimo Durante
Journal:  J Clin Endocrinol Metab       Date:  2020-09-01       Impact factor: 5.958

5.  Fusion iENA Scholar Study: Sensor-Navigated I-124-PET/US Fusion Imaging versus Conventional Diagnostics for Retrospective Functional Assessment of Thyroid Nodules by Medical Students.

Authors:  Martin Freesmeyer; Thomas Winkens; Luis Weissenrieder; Christian Kühnel; Falk Gühne; Simone Schenke; Robert Drescher; Philipp Seifert
Journal:  Sensors (Basel)       Date:  2020-06-17       Impact factor: 3.576

6.  Ultrasound Cine Loop Standard Operating Procedure for Benign Thyroid Diseases-Evaluation of Non-Physician Application.

Authors:  Philipp Seifert; Ivonne Maikowski; Thomas Winkens; Christian Kühnel; Falk Gühne; Robert Drescher; Martin Freesmeyer
Journal:  Diagnostics (Basel)       Date:  2021-01-04

7.  Effect of training on resident inter-reader agreement with American College of Radiology Thyroid Imaging Reporting and Data System.

Authors:  Yang Du; Meredith Bara; Prayash Katlariwala; Roger Croutze; Katrin Resch; Jonathan Porter; Medica Sam; Mitchell P Wilson; Gavin Low
Journal:  World J Radiol       Date:  2022-01-28

8.  The Diagnostic Efficacy of the American College of Radiology (ACR) Thyroid Imaging Report and Data System (TI-RADS) and the American Thyroid Association (ATA) Risk Stratification Systems for Thyroid Nodules.

Authors:  Fei Chen; Yungang Sun; Guanqi Chen; Yuqian Luo; Guifang Xue; Kongmei Luo; Haoyuan Ma; Jiaxin Yao; Zhangtian Zhu; Guanbin Li; Qiang Li
Journal:  Comput Math Methods Med       Date:  2022-01-15       Impact factor: 2.238

9.  Diagnostic Performance of Different Thyroid Imaging Reporting and Data Systems (Kwak-TIRADS, EU-TIRADS and ACR TI-RADS) for Risk Stratification of Small Thyroid Nodules (≤10 mm).

Authors:  Simone Schenke; Rigobert Klett; Philipp Seifert; Michael C Kreissl; Rainer Görges; Michael Zimny
Journal:  J Clin Med       Date:  2020-01-16       Impact factor: 4.241

10.  Is patient age associated with risk of malignancy in a ≥4 cm cytologically benign thyroid nodule?

Authors:  Whitney Sutton; Joseph K Canner; Lisa M Rooper; Jason D Prescott; Martha A Zeiger; Aarti Mathur
Journal:  Am J Surg       Date:  2020-06-02       Impact factor: 2.565

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