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Chen J, Ye D, Lv S, Li X, Ye F, Huang Y, Su Z, Lin Y, Xie T, Wen X. Benign thyroid nodules classified as ACR TI-RADS 4 or 5: Imaging and histological features. Eur J Radiol 2023; 175:111261. [PMID: 38493559 DOI: 10.1016/j.ejrad.2023.111261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 11/15/2023] [Accepted: 12/09/2023] [Indexed: 03/19/2024]
Abstract
BACKGROUND American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) being most widely applied in clinical practice, there is an overlap in US imaging manifestations between benign and malignant thyroid nodules. OBJECTIVES To analyze the imaging and histological characteristics of pathological benign thyroid nodules categorized as American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) 4 or 5, and to explore the correlation between the suspicious sonographic signs resulting in the misdiagnoses and the histopathological features. MATERIALS AND METHODS Overall, 227 benign thyroid nodules (215 patients) in ACR TI-RADS 4 or 5 sampled through surgical excision were analyzed between December 2020 and August 2022. We retrospectively reread the ultrasound (US) images of the pathological discordant cases, after which we performed a systematic analysis focusing on the histopathological characteristics of thyroid lesions and recorded the findings. Qualitative US features and pathological significance of the thyroid nodules were analyzed using the chi-square and Fisher's exact tests. RESULTS The pathological type of 227 thyroid nodules (n = 103 in ACR TI-RADS 4 and n = 124 in ACR TI-RADS 5) was nodular goiter together with other histopathological features, namely, fibrosis (n = 103, 45.4 %), calcification (n = 70, 30.8 %), adenomatous hyperplasia (n = 31, 13.7 %), follicular epithelial hyperplasia (n = 23, 10.1 %), Hashimoto's thyroiditis (n = 18, 7.9 %), and cystic degeneration (n = 16, 7.1 %). Fibrosis was the most common histopathological feature in both ACR TI-RADS 4 (n = 42, 40.8 %) and 5 (n = 61, 49.2 %) categories of benign thyroid nodules. Thyroid nodules with fibrosis demonstrated sonographic features of "taller than wide" (p < 0.05), while lesions with follicular epithelial hyperplasia were likely to be detected with irregular and/or lobulated margins and very hypoechoic on US (p < 0.05 for both). CONCLUSION Benign thyroid nodules with histopathological findings such as fibrosis are associated with suspicious US features, which may give inappropriately higher TIRADS stratification.
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Affiliation(s)
- Jiamin Chen
- The Fifth Affiliated Hospital Sun Yat-Sen University, Zhuhai 519000, China.
| | - Dalin Ye
- The Fifth Affiliated Hospital Sun Yat-Sen University, Zhuhai 519000, China
| | - Shuhui Lv
- The Fifth Affiliated Hospital Sun Yat-Sen University, Zhuhai 519000, China
| | - Xuefeng Li
- The Fifth Affiliated Hospital Sun Yat-Sen University, Zhuhai 519000, China
| | - Feile Ye
- The Fifth Affiliated Hospital Sun Yat-Sen University, Zhuhai 519000, China
| | - Yongquan Huang
- The Fifth Affiliated Hospital Sun Yat-Sen University, Zhuhai 519000, China.
| | - Zhongzhen Su
- The Fifth Affiliated Hospital Sun Yat-Sen University, Zhuhai 519000, China.
| | - Yuhong Lin
- The Fifth Affiliated Hospital Sun Yat-Sen University, Zhuhai 519000, China.
| | - Ting Xie
- The Fifth Affiliated Hospital Sun Yat-Sen University, Zhuhai 519000, China.
| | - Xin Wen
- The Fifth Affiliated Hospital Sun Yat-Sen University, Zhuhai 519000, China.
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Yang L, Li C, Chen Z, He S, Wang Z, Liu J. Diagnostic efficiency among Eu-/C-/ACR-TIRADS and S-Detect for thyroid nodules: a systematic review and network meta-analysis. Front Endocrinol (Lausanne) 2023; 14:1227339. [PMID: 37720531 PMCID: PMC10501732 DOI: 10.3389/fendo.2023.1227339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 08/16/2023] [Indexed: 09/19/2023] Open
Abstract
Background The performance in evaluating thyroid nodules on ultrasound varies across different risk stratification systems, leading to inconsistency and uncertainty regarding diagnostic sensitivity, specificity, and accuracy. Objective Comparing diagnostic performance of detecting thyroid cancer among distinct ultrasound risk stratification systems proposed in the last five years. Evidence acquisition Systematic search was conducted on PubMed, EMBASE, and Web of Science databases to find relevant research up to December 8, 2022, whose study contents contained elucidation of diagnostic performance of any one of the above ultrasound risk stratification systems (European Thyroid Imaging Reporting and Data System[Eu-TIRADS]; American College of Radiology TIRADS [ACR TIRADS]; Chinese version of TIRADS [C-TIRADS]; Computer-aided diagnosis system based on deep learning [S-Detect]). Based on golden diagnostic standard in histopathology and cytology, single meta-analysis was performed to obtain the optimal cut-off value for each system, and then network meta-analysis was conducted on the best risk stratification category in each system. Evidence synthesis This network meta-analysis included 88 studies with a total of 59,304 nodules. The most accurate risk category thresholds were TR5 for Eu-TIRADS, TR5 for ACR TIRADS, TR4b and above for C-TIRADS, and possible malignancy for S-Detect. At the best thresholds, sensitivity of these systems ranged from 68% to 82% and specificity ranged from 71% to 81%. It identified the highest sensitivity for C-TIRADS TR4b and the highest specificity for ACR TIRADS TR5. However, sensitivity for ACR TIRADS TR5 was the lowest. The diagnostic odds ratio (DOR) and area under curve (AUC) were ranked first in C-TIRADS. Conclusion Among four ultrasound risk stratification options, this systemic review preliminarily proved that C-TIRADS possessed favorable diagnostic performance for thyroid nodules. Systematic review registration https://www.crd.york.ac.uk/prospero, CRD42022382818.
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Affiliation(s)
- Longtao Yang
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Cong Li
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Zhe Chen
- Department of Thoracic Surgery, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Shaqi He
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Zhiyuan Wang
- Department of Ultrasound, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, Hunan, China
| | - Jun Liu
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
- Clinical Research Center for Medical Imaging in Hunan Province, Changsha, China
- Department of Radiology Quality Control Center in Hunan Province, Changsha, China
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Negro R, Greco G. Patients undergoing endocrine consultation and first diagnosis of nodular disease: Indications of thyroid ultrasound and completeness of ultrasound reports. Endocrine 2023; 80:600-605. [PMID: 36622626 DOI: 10.1007/s12020-023-03301-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Accepted: 01/03/2023] [Indexed: 01/10/2023]
Abstract
PURPOSE To evaluate reasons for performing ultrasonography (US) and completeness of US reports in patients undergoing endocrine consultation with the first diagnosis of nodular disease. METHODS Since January 1 to June 30, 2021, we prospectively collected patient data (age and thyroid-stimulating hormone concentrations), reasons for performing thyroid US, and completeness of reports regarding the description of the thyroid gland and nodules. In the case of multiple nodules, we considered the nodule suspected of malignancy and the largest one. To evaluate the accuracy of thyroid nodule description, we referred to the five characteristics suggested by the ACR TI-RADS system. RESULTS A total of 341 patients with thyroid nodules received endocrine consultation (female, 78%). The most frequent reasons for performing thyroid US were unrelated to a suspected thyroid disease (31.7%), followed by incidentaloma (23.5%), dysfunction or positivity for thyroid antibodies (19.1%), symptomatic or visible nodules (17.6%), and family history of any thyroid disease (8.2%). Gland texture was not reported in 41.9%. The depth of the lobes was the dimension reported most frequently (42.2%), but any diameter was not reported in 57.8% of the cases. As regards the description of the most relevant nodule, length was reported more frequently (75.9%). Margins and echogenicity were more frequently described (54.5% and 44.3%, respectively) than other characteristics (composition: 27%; shape: 8.8%; echogenic foci: 6.7%). No reports had indicated the malignancy risk stratification. CONCLUSIONS The results of the study demonstrate that in patients undergoing endocrine consultation with first detected thyroid nodules, US was mostly performed in asymptomatic cases, US reports were incomplete, and no risk stratification system was reported.
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Affiliation(s)
- Roberto Negro
- Division of Endocrinology, "V. Fazzi" Hospital, Lecce, Italy.
| | - Gabriele Greco
- Division of Endocrinology, "V. Fazzi" Hospital, Lecce, Italy
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Abstract
Clinical evidence supports the association of ultrasound features with benign or malignant thyroid nodules and serves as the basis for sonographic stratification of thyroid nodules, according to an estimated thyroid cancer risk. Contemporary guidelines recommend management strategies according to thyroid cancer risk, thyroid nodule size, and the clinical scenario. Yet, reproducible and accurate thyroid nodule risk stratification requires expertise, time, and understanding of the weight different ultrasound features have on thyroid cancer risk. The application of artificial intelligence to overcome these limitations is promising and has the potential to improve the care of patients with thyroid nodules.
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Affiliation(s)
- Nydia Burgos
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, University of Puerto Rico, Medical Sciences Campus, Paseo Dr. Jose Celso Barbosa, San Juan 00921, Puerto Rico
| | - Naykky Singh Ospina
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, University of Florida, 1600 SW Archer Road, Gainesville, FL 32610, USA
| | - Jennifer A Sipos
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, The Ohio State University Wexner Medical Center, 1581 Dodd Drive, Columbus, OH 43210, USA.
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Li W, Sun Y, Xu H, Shang W, Dong A. Systematic Review and Meta-Analysis of American College of Radiology TI-RADS Inter-Reader Reliability for Risk Stratification of Thyroid Nodules. Front Oncol 2022; 12:840516. [PMID: 35646667 PMCID: PMC9136001 DOI: 10.3389/fonc.2022.840516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 04/11/2022] [Indexed: 11/13/2022] Open
Abstract
Purpose To investigate the inter-reader agreement of using the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) for risk stratification of thyroid nodules. Methods A literature search of Web of Science, PubMed, Cochrane Library, EMBASE, and Google Scholar was performed to identify eligible articles published from inception until October 31, 2021. We included studies reporting inter-reader agreement of different radiologists who applied ACR TI-RADS for the classification of thyroid nodules. Quality assessment of the included studies was performed with the Quality Assessment of Diagnostic Accuracy Studies-2 tool and Guidelines for Reporting Reliability and Agreement Studies. The summary estimates of the inter-reader agreement were pooled with the random-effects model, and multiple subgroup analyses and meta-regression were performed to investigate various clinical settings. Results A total of 13 studies comprising 5,238 nodules were included in the current meta-analysis and systematic review. The pooled inter-reader agreement for overall ACR TI-RADS classification was moderate (κ = 0.51, 95% CI 0.42–0.59). Substantial heterogeneity was presented throughout the studies, and meta-regression analyses suggested that the malignant rate was the significant factor. Regarding the ultrasound (US) features, the best inter-reader agreement was composition (κ = 0.58, 95% CI 0.53–0.63), followed by shape (κ = 0.57, 95% CI 0.41–0.72), echogenicity (κ = 0.50, 95% CI 0.40–0.60), echogenic foci (κ = 0.44, 95% CI 0.36–0.53), and margin (κ = 0.34, 95% CI 0.24–0.44). Conclusions The ACR TI-RADS demonstrated moderate inter-reader agreement between radiologists for the overall classification. However, the US feature of margin only showed fair inter-reader reliability among different observers.
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Affiliation(s)
- Wei Li
- Department of Medical Imaging, Jiangsu Vocational College of Medicine, Yancheng, China
| | - Yuan Sun
- Department of Burn and Plastic Surgery, Affiliate Huaihai Hospital of Xuzhou Medical University, Xuzhou, China
| | - Haibing Xu
- Department of Medical Imaging, Jiangsu Vocational College of Medicine, Yancheng, China
| | - Wenwen Shang
- Department of Medical Imaging, Jiangsu Vocational College of Medicine, Yancheng, China
| | - Anding Dong
- Department of Medical Imaging, Jiangsu Vocational College of Medicine, Yancheng, China
- *Correspondence: Anding Dong,
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Abou Shaar B, Meteb M, Awad El-Karim G, Almalki Y. Reducing the Number of Unnecessary Thyroid Nodule Biopsies With the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS). Cureus 2022; 14:e23118. [PMID: 35425684 PMCID: PMC9004328 DOI: 10.7759/cureus.23118] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/13/2022] [Indexed: 12/02/2022] Open
Abstract
Introduction Thyroid nodules are exceedingly common, occurring in up to 76% of adults. Less than 10% are palpable, and the majority are detected incidentally with an estimated prevalence of 68%, 25%, and 18% using ultrasound (US), CT, and MRI, respectively. The rising use of imaging over the last four decades has led to a significant increase in nodule detection or ‘over-identification,’ fine-needle aspiration (FNA), a higher reported incidence of thyroid cancer, and thyroidectomy. The purpose of this study is to provide a descriptive experience with thyroid nodule FNAs one year prior and one year after the implementation of the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) at a prototypical community hospital. Methods A total of 104 patients with 114 thyroid nodules underwent US-guided FNA at Bluewater Health from January 1, 2018, to March 31, 2020, with available cytological results (The Bethesda System). The study population was divided into two cohorts (January 1, 2018, to December 31, 2018 - ‘local best practice cohort’, and March 1, 2019, to March 31, 2020 - ‘ACR TI-RADS cohort’) based on the implementation of the ACR TI-RADS guidelines in March 2019. Results The local best practice cohort (January 1, 2018, to December 31, 2018) comprised 57 thyroid nodules in 52 patients (mean age 66 ± 12; 40 Women). The ACR TI-RADS cohort (March 1, 2019, to March 31, 2020) comprised 57 thyroid nodules in 52 patients (mean age 61 ± 16; 41 Women). There were no statistical differences with respect to age, gender, or thyroid nodule location. Our results show a dramatic decrease in the number of unnecessary FNAs if ACR TI-RADS was implemented from January to December 2018. Thirty (52.6%) of the previously sampled thyroid nodules using the local best practice guidelines would have been followed as per ACR TI-RADS. Conclusion ACR TI-RADS is a reliable classification system in routine practice that significantly reduces the number of unnecessary thyroid FNAs with higher specificity compared to local best practice guidelines.
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Chen F, Sun Y, Chen G, Luo Y, Xue G, Luo K, Ma H, Yao J, Zhu Z, Li G, Li Q. 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. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022; 2022:9995962. [PMID: 35075371 PMCID: PMC8783731 DOI: 10.1155/2022/9995962] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 12/21/2021] [Accepted: 12/24/2021] [Indexed: 11/28/2022]
Abstract
BACKGROUND This study is aimed at evaluating the diagnostic efficacy of ultrasound-based risk stratification for thyroid nodules in the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) and the American Thyroid Association (ATA) risk stratification systems. METHODS 286 patients with thyroid cancer were included in the tumor group, with 259 nontumor cases included in the nontumor group. The ACR TI-RADS and ATA risk stratification systems assessed all thyroid nodules for malignant risks. The diagnostic effect of ACR and ATA risk stratification system for thyroid nodules was evaluated by receiver operating characteristic (ROC) analysis using postoperative pathological diagnosis as the gold standard. RESULTS The distributions and mean scores of ACR and ATA rating risk stratification were significantly different between the tumor and nontumor groups. The lesion diameter > 1 cm subgroup had higher malignant ultrasound feature rates detected and ACR and ATA scores. A significant difference was not found in the ACR and ATA scores between patients with or without Hashimoto's disease. The area under the receiver operating curve (AUC) for the ACR TI-RADS and the ATA systems was 0.891 and 0.896, respectively. The ACR had better specificity (0.90) while the ATA system had higher sensitivity (0.92), with both scenarios having almost the same overall diagnostic accuracy (0.84). CONCLUSION Both the ACR TI-RADS and the ATA risk stratification systems provide a clinically feasible thyroid malignant risk classification, with high thyroid nodule malignant risk diagnostic efficacy.
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Affiliation(s)
- Fei Chen
- General Surgery Center Department of Thyroid Surgery, Zhujiang Hospital, Southern Medical University, 253 Gongye Middle Avenue, Haizhu District, Guangzhou, Guangdong, China 510280
| | - Yungang Sun
- Department of Nuclear Medicine Zhujiang Hospital, Southern Medical University, 253 Gongye Middle Avenue, Haizhu District, Guangzhou, Guangdong, China 510280
| | - Guanqi Chen
- School of Data and Computer Science, Sun Yat-sen University, No. 132, Outer Ring East Road, Guangzhou Higher Education Mega Center, Guangzhou, Guangdong, China 510006
| | - Yuqian Luo
- Department of Laboratory Medicine, Nanjing Drum Tower Hospital and Jiangsu Key Laboratory for Molecular Medicine, Nanjing University Medical School, 321 Zhong Shan Road, Nanjing 210008, China
| | - Guifang Xue
- General Surgery Center Department of Thyroid Surgery, Zhujiang Hospital, Southern Medical University, 253 Gongye Middle Avenue, Haizhu District, Guangzhou, Guangdong, China 510280
| | - Kongmei Luo
- General Surgery Center Department of Thyroid Surgery, Zhujiang Hospital, Southern Medical University, 253 Gongye Middle Avenue, Haizhu District, Guangzhou, Guangdong, China 510280
| | - Haoyuan Ma
- General Surgery Center Department of Thyroid Surgery, Zhujiang Hospital, Southern Medical University, 253 Gongye Middle Avenue, Haizhu District, Guangzhou, Guangdong, China 510280
| | - Jiaxin Yao
- General Surgery Center Department of Thyroid Surgery, Zhujiang Hospital, Southern Medical University, 253 Gongye Middle Avenue, Haizhu District, Guangzhou, Guangdong, China 510280
| | - Zhangtian Zhu
- General Surgery Center Department of Thyroid Surgery, Zhujiang Hospital, Southern Medical University, 253 Gongye Middle Avenue, Haizhu District, Guangzhou, Guangdong, China 510280
| | - Guanbin Li
- School of Data and Computer Science, Sun Yat-sen University, No. 132, Outer Ring East Road, Guangzhou Higher Education Mega Center, Guangzhou, Guangdong, China 510006
| | - Qiang Li
- General Surgery Center Department of Thyroid Surgery, Zhujiang Hospital, Southern Medical University, 253 Gongye Middle Avenue, Haizhu District, Guangzhou, Guangdong, China 510280
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Leni D, Seminati D, Fior D, Vacirca F, Capitoli G, Cazzaniga L, Di Bella C, L’Imperio V, Galimberti S, Pagni F. Diagnostic Performances of the ACR-TIRADS System in Thyroid Nodules Triage: A Prospective Single Center Study. Cancers (Basel) 2021; 13:cancers13092230. [PMID: 34066485 PMCID: PMC8124822 DOI: 10.3390/cancers13092230] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 04/09/2021] [Accepted: 04/27/2021] [Indexed: 01/21/2023] Open
Abstract
Simple Summary On a prospective series of 480 thyroid nodules, the ACR-TIRADS demonstrated a sensitivity and specificity in performing FNA of 58.9% and 59%, respectively. The execution of FNA on nodules with ACR class ≥3 independently from the dimensional criteria would increase the sensitivity to 95% and reduce the false negatives rate (7.3%, 7/96), prompting a re-evaluation of the size criteria. The need for reduction in inappropriate hospital admissions prompts a rigorous triage of patients, and future prospective studies to improve current performances might be considered. Abstract Ultrasound scores are used to determine whether thyroid nodules should undergo Fine Needle Aspiration (FNA) or simple clinical follow-up. Different scores have been proposed for this task, with the American College of Radiology (ACR) TIRADS system being one of the most widely used. This study evaluates its ability in triaging thyroid nodules deserving FNA on a large prospective monocentric Italian case series of 493 thyroid nodules from 448 subjects. In ACR 1–2, cytology never prompted a surgical indication. In 59% of cases classified as TIR1c-TIR2, the FNA procedure could be ancillary, according to the ACR-TIRADS score. A subset (37.9%) of cases classified as TIR4-5 would not undergo FNA, according to the dimensional thresholds used by the ACR-TIRADS. Applying the ACR score, a total of 46.5% thyroid nodules should be studied with FNA. The ACR system demonstrated a sensitivity and specificity of 58.9% and 59% in the identification of patients with cytology ≥TIR3A, with a particularly high false negative rate for ACR classes ≥3 (44.8%, 43/96), which would dramatically decrease (7.3%, 7/96) if the dimensional criteria were not taken into account. In ACR 3–4–5, a correspondence with the follow-up occurred in 60.3%, 50.2% and 51.9% of cases. The ACR-TIRADS is a useful risk stratification tool for thyroid nodules, although the current dimensional thresholds could lead to an underestimation of malignant lesions. Their update might be considered in future studies to increase the screening performances of the system.
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Affiliation(s)
- Davide Leni
- Department of Radiology, ASST Monza, 20900 Monza, Italy; (D.L.); (D.F.); (F.V.)
| | - Davide Seminati
- Department of Pathology, University of Milan—Bicocca (UNIMIB), 20900 Monza, Italy; (D.S.); (L.C.); (C.D.B.); (V.L.)
| | - Davide Fior
- Department of Radiology, ASST Monza, 20900 Monza, Italy; (D.L.); (D.F.); (F.V.)
| | - Francesco Vacirca
- Department of Radiology, ASST Monza, 20900 Monza, Italy; (D.L.); (D.F.); (F.V.)
| | - Giulia Capitoli
- Bicocca Bioinformatics Biostatistics and Bioimaging B4 Center, School of Medicine and Surgery, University of Milan—Bicocca (UNIMIB), 20900 Monza, Italy; (G.C.); (S.G.)
| | - Laura Cazzaniga
- Department of Pathology, University of Milan—Bicocca (UNIMIB), 20900 Monza, Italy; (D.S.); (L.C.); (C.D.B.); (V.L.)
| | - Camillo Di Bella
- Department of Pathology, University of Milan—Bicocca (UNIMIB), 20900 Monza, Italy; (D.S.); (L.C.); (C.D.B.); (V.L.)
| | - Vincenzo L’Imperio
- Department of Pathology, University of Milan—Bicocca (UNIMIB), 20900 Monza, Italy; (D.S.); (L.C.); (C.D.B.); (V.L.)
| | - Stefania Galimberti
- Bicocca Bioinformatics Biostatistics and Bioimaging B4 Center, School of Medicine and Surgery, University of Milan—Bicocca (UNIMIB), 20900 Monza, Italy; (G.C.); (S.G.)
| | - Fabio Pagni
- Department of Pathology, University of Milan—Bicocca (UNIMIB), 20900 Monza, Italy; (D.S.); (L.C.); (C.D.B.); (V.L.)
- Correspondence:
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Qi Q, Zhou A, Guo S, Huang X, Chen S, Li Y, Xu P. Explore the Diagnostic Efficiency of Chinese Thyroid Imaging Reporting and Data Systems by Comparing With the Other Four Systems (ACR TI-RADS, Kwak-TIRADS, KSThR-TIRADS, and EU-TIRADS): A Single-Center Study. Front Endocrinol (Lausanne) 2021; 12:763897. [PMID: 34777258 PMCID: PMC8578891 DOI: 10.3389/fendo.2021.763897] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Accepted: 10/11/2021] [Indexed: 01/25/2023] Open
Abstract
PURPOSE To explore the characteristics of C-TIRADS by comparing it with ACR-TIRADS, Kwak-TIRADS, KSThR-TIRADS and EU-TIRADS. METHODS A total of 1096 nodules were collected from 884 patients undergoing thyroidectomy in our center between May 2018 and December 2020. Divided the nodules into two groups: ">10mm" and "≤10mm". Ultrasound characteristics of each nodule were observed and recorded by 2 doctors, then classified based on ACR-TIRADS, Kwak-TIRADS, KSThR-TIRADS, EU-TIRADS, and C-TIRADS. RESULTS A total of 682 benign nodules cases (62.23%) and 414 malignant nodules cases (37.77%) were identified. The ICC value of each guideline was:0.937(ACR-TIRADS), 0.858(EU-IRADS), 0.811(Kwak-TIRADS), 0.835(KTA/KSThR-TIRADS) and 0.854(C-TIRADS). The nodule malignancy rates in the groups(Kwak-TIRADS 4B, C-TIRADS 4B、4C) of two sizes were significantly different (all p<0.05). There was no statistical difference in the other grades of two sizes (all p>0.05). Unnecessary biopsy rates were the lowest in C-TIRADS (49.02% p<0.001). Furthermore, Kwak-TIRADS had the highest sensitivity and NPV (89.9%, 91.0%, all p<0.05), while C-TIRADS had the highest specificity and PPV (82.3%, 69.2%, all p<0.05). C-TIRADS and Kwak-TIRADS had the highest accuracy (76.0%, 72.5%, P=0.071). The AUCs of the 5 guidelines were C-TIRADS(0.816, P<0.05), Kwak-TIRADS(0.789, P<0.05) KTA/KSThR-TIRADS and ACR-TIRADS(0.773, 0.763, P=0.305), EU-TIRADS(0.734, P<0.05). The AUCs of the five guidelines were not statistically different between "nodules>10mm" and "nodules ≤ 10mm" (all P>0.05). CONCLUSIONS All five guides showed excellent interobserver agreement. C-TIRADS was slightly efficient than Kwak-IRADS, KTA/KSThR-TIRADS and ACR-TIRADS, and had greater advantages than EU-TIRADS. The diagnostic abilities of the five guidelines for "nodules ≤ 10mm" were not inferior to that of "nodules> 10mm". C-TIRADS is simple and easy to implement and can provide effective thyroid tumor risk stratification for thyroid nodule diagnosis, especially in China.
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Zhou J, Yin L, Wei X, Zhang S, Song Y, Luo B, Li J, Qian L, Cui L, Chen W, Wen C, Peng Y, Chen Q, Lu M, Chen M, Wu R, Zhou W, Xue E, Li Y, Yang L, Mi C, Zhang R, Wu G, Du G, Huang D, Zhan W. 2020 Chinese guidelines for ultrasound malignancy risk stratification of thyroid nodules: the C-TIRADS. Endocrine 2020; 70:256-279. [PMID: 32827126 DOI: 10.1007/s12020-020-02441-y] [Citation(s) in RCA: 126] [Impact Index Per Article: 31.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/04/2020] [Accepted: 07/28/2020] [Indexed: 02/05/2023]
Abstract
Thyroid nodules are very common all over the world, and China is no exception. Ultrasound plays an important role in determining the risk stratification of thyroid nodules, which is critical for clinical management of thyroid nodules. For the past few years, many versions of TIRADS (Thyroid Imaging Reporting and Data System) have been put forward by several institutions with the aim to identify whether nodules require fine-needle biopsy or ultrasound follow-up. However, no version of TIRADS has been widely adopted worldwide till date. In China, as many as ten versions of TIRADS have been used in different hospitals nationwide, causing a lot of confusion. With the support of the Superficial Organ and Vascular Ultrasound Group of the Society of Ultrasound in Medicine of the Chinese Medical Association, the Chinese-TIRADS that is in line with China's national conditions and medical status was established based on literature review, expert consensus, and multicenter data provided by the Chinese Artificial Intelligence Alliance for Thyroid and Breast Ultrasound.
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Affiliation(s)
- JianQiao Zhou
- Department of Ultrasound, Ruijin Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, 200025, China.
| | - LiXue Yin
- Institute of Ultrasound in Medicine, The Affiliated Sichuan Provincial People's Hospital of Electronic Science and Technology University of China, Chengdu, 610071, China.
| | - Xi Wei
- Department of Diagnostic and Therapeutic Ultrasound, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center of Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, 300060, China
| | - Sheng Zhang
- Department of Diagnostic and Therapeutic Ultrasound, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center of Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, 300060, China
| | - YanYan Song
- Department of Biostatistics, Institute of Medical Sciences, Shanghai Jiaotong University School of Medicine, Shanghai, 200025, China
| | - BaoMing Luo
- Department of Ultrasound, SunYat-sen Memorial Hospital, SunYat-sen University, Guangzhou, 510120, China
| | - JianChu Li
- Department of Ultrasound, Peking Union Medical College Hospital, Beijing, 100730, China
| | - LinXue Qian
- Department of Ultrasound, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, China
| | - LiGang Cui
- Department of Ultrasound, Peking University Third Hospital, Beijing, 100191, China
| | - Wen Chen
- Department of Ultrasound, Peking University Third Hospital, Beijing, 100191, China
| | - ChaoYang Wen
- Department of Ultrasound, Peking University International Hospital, Beijing, 102206, China
| | - YuLan Peng
- Department of Ultrasound, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Qin Chen
- Department of Ultrasound, The Affiliated Sichuan Provincial People's Hospital of Electronic Science and Technology University of China, Chengdu, 610071, China
| | - Man Lu
- Department of Ultrasound, Sichuan Cancer Hospital, Chengdu, 610041, China
| | - Min Chen
- Department of Ultrasound, Fudan University Shanghai Cancer Center, Shanghai, 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China
| | - Rong Wu
- Department of Ultrasound, Shanghai First People's Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, 201620, China
| | - Wei Zhou
- Department of Ultrasound, Ruijin Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, 200025, China
| | - EnSheng Xue
- Department of Ultrasound, Fujian Medical University Union Hospital, Fuzhou, 350001, China
| | - YingJia Li
- Department of Ultrasound, Nanfang Hospital of Southern Medical University, Guangzhou, 510515, China
| | - LiChun Yang
- Department of Ultrasound, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming, 650031, China
| | - ChengRong Mi
- Department of Ultrasound, General Hospital of Ningxia Medical University, Yinchuan, 750021, China
| | - RuiFang Zhang
- Department of Ultrasound, The First Affiliated Hospital, Zhengzhou University, Zhengzhou, 450052, China
| | - Gang Wu
- Department of Ultrasound, Henan Provincial People's Hospital, Zhengzhou, 450003, China
| | - GuoQing Du
- Department of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, China
| | - DaoZhong Huang
- Department of Ultrasound, Tongji Hospital, Tongji Medical Colloge, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - WeiWei Zhan
- Department of Ultrasound, Ruijin Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, 200025, China.
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