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Richter D, Beck M, Müller SK, Iro H, Koch M, Sievert M. [Thyroid nodules as an incidental finding : Value of sonography and scintigraphy in primary diagnostics]. HNO 2024:10.1007/s00106-024-01502-2. [PMID: 39078487 DOI: 10.1007/s00106-024-01502-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/24/2024] [Indexed: 07/31/2024]
Abstract
Due to the widespread use of high-resolution sonography, numerous thyroid nodules are diagnosed, often as incidental findings. The challenge lies in evaluating various criteria such as size, shape, and echogenicity to assess the nodules' malignancy risk. Risk stratification systems have been developed to enable systematic assessment as well as to avoid unnecessary medical interventions and malignant findings being overlooked. This article provides an overview of the current diagnostic standards in primary assessment of thyroid nodules.
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Affiliation(s)
- Daniel Richter
- Hals-Nasen-Ohrenklinik, Kopf- und Hals-Chirurgie, Universitätskliniken Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Deutschland
| | - Michael Beck
- Nuklearmedizinische Klinik, Universitätskliniken Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Deutschland
| | - Sarina Katrin Müller
- Hals-Nasen-Ohrenklinik, Kopf- und Hals-Chirurgie, Universitätskliniken Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Deutschland
| | - Heinrich Iro
- Hals-Nasen-Ohrenklinik, Kopf- und Hals-Chirurgie, Universitätskliniken Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Deutschland
| | - Michael Koch
- Hals-Nasen-Ohrenklinik, Kopf- und Hals-Chirurgie, Universitätskliniken Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Deutschland
| | - Matti Sievert
- Hals-Nasen-Ohrenklinik, Kopf- und Hals-Chirurgie, Universitätskliniken Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Deutschland.
- Abteilung für Hals-Nasen-Ohren-Heilkunde, Kopf- und Hals-Chirurgie, Universität Erlangen-Nürnberg, Waldstraße 1, 91054, Erlangen, Deutschland.
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David E, Grazhdani H, Tattaresu G, Pittari A, Foti PV, Palmucci S, Spatola C, Lo Greco MC, Inì C, Tiralongo F, Castiglione D, Mastroeni G, Gigli S, Basile A. Thyroid Nodule Characterization: Overview and State of the Art of Diagnosis with Recent Developments, from Imaging to Molecular Diagnosis and Artificial Intelligence. Biomedicines 2024; 12:1676. [PMID: 39200141 PMCID: PMC11351886 DOI: 10.3390/biomedicines12081676] [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: 05/29/2024] [Revised: 07/09/2024] [Accepted: 07/18/2024] [Indexed: 09/01/2024] Open
Abstract
Ultrasound (US) is the primary tool for evaluating patients with thyroid nodules, and the risk of malignancy assessed is based on US features. These features help determine which patients require fine-needle aspiration (FNA) biopsy. Classification systems for US features have been developed to facilitate efficient interpretation, reporting, and communication of thyroid US findings. These systems have been validated by numerous studies and are reviewed in this article. Additionally, this overview provides a comprehensive description of the clinical and laboratory evaluation of patients with thyroid nodules, various imaging modalities, grayscale US features, color Doppler US, contrast-enhanced US (CEUS), US elastography, FNA biopsy assessment, and the recent introduction of molecular testing. The potential of artificial intelligence in thyroid US is also discussed.
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Affiliation(s)
- Emanuele David
- Department of Medical Surgical Sciences and Advanced Technologies “GF Ingrassia”, University Hospital Policlinic “G. Rodolico-San Marco”, 95123 Catania, Italy; (G.T.); (A.P.); (P.V.F.); (S.P.); (C.S.); (M.C.L.G.); (C.I.); (F.T.); (D.C.); (A.B.)
- Department of Translational and Precision Medicine, “Sapienza” University of Rome, 00185 Rome, Italy
| | | | - Giuliana Tattaresu
- Department of Medical Surgical Sciences and Advanced Technologies “GF Ingrassia”, University Hospital Policlinic “G. Rodolico-San Marco”, 95123 Catania, Italy; (G.T.); (A.P.); (P.V.F.); (S.P.); (C.S.); (M.C.L.G.); (C.I.); (F.T.); (D.C.); (A.B.)
| | - Alessandra Pittari
- Department of Medical Surgical Sciences and Advanced Technologies “GF Ingrassia”, University Hospital Policlinic “G. Rodolico-San Marco”, 95123 Catania, Italy; (G.T.); (A.P.); (P.V.F.); (S.P.); (C.S.); (M.C.L.G.); (C.I.); (F.T.); (D.C.); (A.B.)
| | - Pietro Valerio Foti
- Department of Medical Surgical Sciences and Advanced Technologies “GF Ingrassia”, University Hospital Policlinic “G. Rodolico-San Marco”, 95123 Catania, Italy; (G.T.); (A.P.); (P.V.F.); (S.P.); (C.S.); (M.C.L.G.); (C.I.); (F.T.); (D.C.); (A.B.)
| | - Stefano Palmucci
- Department of Medical Surgical Sciences and Advanced Technologies “GF Ingrassia”, University Hospital Policlinic “G. Rodolico-San Marco”, 95123 Catania, Italy; (G.T.); (A.P.); (P.V.F.); (S.P.); (C.S.); (M.C.L.G.); (C.I.); (F.T.); (D.C.); (A.B.)
| | - Corrado Spatola
- Department of Medical Surgical Sciences and Advanced Technologies “GF Ingrassia”, University Hospital Policlinic “G. Rodolico-San Marco”, 95123 Catania, Italy; (G.T.); (A.P.); (P.V.F.); (S.P.); (C.S.); (M.C.L.G.); (C.I.); (F.T.); (D.C.); (A.B.)
| | - Maria Chiara Lo Greco
- Department of Medical Surgical Sciences and Advanced Technologies “GF Ingrassia”, University Hospital Policlinic “G. Rodolico-San Marco”, 95123 Catania, Italy; (G.T.); (A.P.); (P.V.F.); (S.P.); (C.S.); (M.C.L.G.); (C.I.); (F.T.); (D.C.); (A.B.)
| | - Corrado Inì
- Department of Medical Surgical Sciences and Advanced Technologies “GF Ingrassia”, University Hospital Policlinic “G. Rodolico-San Marco”, 95123 Catania, Italy; (G.T.); (A.P.); (P.V.F.); (S.P.); (C.S.); (M.C.L.G.); (C.I.); (F.T.); (D.C.); (A.B.)
| | - Francesco Tiralongo
- Department of Medical Surgical Sciences and Advanced Technologies “GF Ingrassia”, University Hospital Policlinic “G. Rodolico-San Marco”, 95123 Catania, Italy; (G.T.); (A.P.); (P.V.F.); (S.P.); (C.S.); (M.C.L.G.); (C.I.); (F.T.); (D.C.); (A.B.)
| | - Davide Castiglione
- Department of Medical Surgical Sciences and Advanced Technologies “GF Ingrassia”, University Hospital Policlinic “G. Rodolico-San Marco”, 95123 Catania, Italy; (G.T.); (A.P.); (P.V.F.); (S.P.); (C.S.); (M.C.L.G.); (C.I.); (F.T.); (D.C.); (A.B.)
| | | | - Silvia Gigli
- Department of Diagnostic Imaging, Sandro Pertini Hospital, 00157 Rome, Italy;
| | - Antonio Basile
- Department of Medical Surgical Sciences and Advanced Technologies “GF Ingrassia”, University Hospital Policlinic “G. Rodolico-San Marco”, 95123 Catania, Italy; (G.T.); (A.P.); (P.V.F.); (S.P.); (C.S.); (M.C.L.G.); (C.I.); (F.T.); (D.C.); (A.B.)
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Lin Y, Khurelsukh K, Li IG, Wu CT, Wu YM, Lin G, Toh CH, Wan YL. Incidental Findings in Lung Cancer Screening. Cancers (Basel) 2024; 16:2600. [PMID: 39061238 PMCID: PMC11274500 DOI: 10.3390/cancers16142600] [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: 06/27/2024] [Revised: 07/18/2024] [Accepted: 07/19/2024] [Indexed: 07/28/2024] Open
Abstract
While low-dose computed tomography (LDCT) for lung cancer screening (LCS) has been recognized for its effectiveness in reducing lung cancer mortality, it often simultaneously leads to the detection of incidental findings (IFs) unrelated to the primary screening indication. These IFs present diagnostic and management challenges, potentially causing unnecessary anxiety and further invasive diagnostic procedures for patients. This review article provides an overview of IFs encountered in LDCT, emphasizing their clinical significance and recommended management strategies. We categorize IFs based on their anatomical locations (intrathoracic-intrapulmonary, intrathoracic-extrapulmonary, and extrathoracic) and discuss the most common findings. We highlight the importance of utilizing guidelines and standardized reporting systems by the American College of Radiology (ACR) to guide appropriate follow-ups. For each category, we present specific IF examples, their radiologic features, and the suggested management approach. This review aims to provide radiologists and clinicians with a comprehensive understanding of IFs in LCS for accurate assessment and management, ultimately enhancing patient care. Finally, we outline a few key aspects for future research and development in managing IFs.
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Affiliation(s)
- Yenpo Lin
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan City 333, Taiwan; (Y.L.); (K.K.); (C.-T.W.); (Y.-M.W.); (G.L.); (C.-H.T.)
| | - Khulan Khurelsukh
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan City 333, Taiwan; (Y.L.); (K.K.); (C.-T.W.); (Y.-M.W.); (G.L.); (C.-H.T.)
| | - I-Gung Li
- Department of Medical Imaging and Intervention, New Taipei Municipal Tucheng Hospital, New Taipei City 236, Taiwan;
| | - Chen-Te Wu
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan City 333, Taiwan; (Y.L.); (K.K.); (C.-T.W.); (Y.-M.W.); (G.L.); (C.-H.T.)
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan City 333, Taiwan
| | - Yi-Ming Wu
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan City 333, Taiwan; (Y.L.); (K.K.); (C.-T.W.); (Y.-M.W.); (G.L.); (C.-H.T.)
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan City 333, Taiwan
| | - Gigin Lin
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan City 333, Taiwan; (Y.L.); (K.K.); (C.-T.W.); (Y.-M.W.); (G.L.); (C.-H.T.)
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan City 333, Taiwan
| | - Cheng-Hong Toh
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan City 333, Taiwan; (Y.L.); (K.K.); (C.-T.W.); (Y.-M.W.); (G.L.); (C.-H.T.)
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan City 333, Taiwan
| | - Yung-Liang Wan
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan City 333, Taiwan; (Y.L.); (K.K.); (C.-T.W.); (Y.-M.W.); (G.L.); (C.-H.T.)
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan City 333, Taiwan
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Bozer A, Daungsupawong H, Wiwanitkit V. Ultrasonographic Characteristics of Thyroid Nodules with Nondiagnostic and Atypia of Undetermined Significance in Fine-Needle Aspiration Cytology: Correspondence. J Belg Soc Radiol 2024; 108:70. [PMID: 39070605 PMCID: PMC11276472 DOI: 10.5334/jbsr.3680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2024] [Accepted: 07/02/2024] [Indexed: 07/30/2024] Open
Affiliation(s)
- Ahmet Bozer
- Department of Radiology, Izmir City Hospital, Laka, 35040 Bayraklı/Izmir, Turkey
| | | | - Viroj Wiwanitkit
- Saveetha Medical College and Hospital, Saveetha Institute of Medical and Technical Sciences, Thandaram, Kancheepuram, Chennai, Tamil Nadu, India
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Leoncini A, Curti M, Ruinelli L, Gamarra E, Trimboli P. Performance of ACR-TIRADS in assessing thyroid nodules does not vary according to patient age. Hormones (Athens) 2024:10.1007/s42000-024-00585-4. [PMID: 39028415 DOI: 10.1007/s42000-024-00585-4] [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: 03/19/2024] [Accepted: 07/09/2024] [Indexed: 07/20/2024]
Abstract
AIMS A few studies have evaluated the performance of the American College of Radiology Thyroid Imaging Reporting And Data System (ACR-TIRADS) in pediatric and elderly patients and found differences between the latter two age groups and middle adulthood. Thus, the present study was undertaken to explore the possible variation of ACR-TIRADS performance across different ages of patients. METHODS A retrospective population undergoing thyroidectomy was selected to use histology as the reference standard. Ultrasound images were reviewed, and alignment of ACR-TIRADS with the corresponding histological diagnosis was made afterwards. Results of the age groups were compared. The ACR-TIRADS diagnostic performance was calculated considering the assessment of nodules across risk categories (i.e., from TR1 to TR5), rate of unnecessary FNAC (UN-FNAC), and rate of necessary but non-performed FNAC (NNP-FNAC). RESULTS Overall, 114 patients with a total of 220 nodules (46 carcinomas) were included. The rate of UN-FNAC was 66.3%, being 93.1% in TR3, 82.1% in TR4, and 31.4% in TR5. There were 15 NNP-FNACs. No significant difference was observed between age groups in terms of sample size, nodule, cancer, and FNAC. The nodule assessment according to ACR-TIRADS categories did not vary across ages. Sensitivity and specificity recorded in three age tertiles were not significantly different. CONCLUSIONS The present study shows that the performance of ACR-TIRADS is not significantly influenced by patient age.
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Affiliation(s)
- Andrea Leoncini
- Servizio Di Radiologia E Radiologia Interventistica, Istituto Di Imaging Della Svizzera Italiana (IIMSI), Ente Ospedaliero Cantonale (EOC), 6900, Lugano, Switzerland
| | - Marco Curti
- Servizio Di Radiologia E Radiologia Interventistica, Istituto Di Imaging Della Svizzera Italiana (IIMSI), Ente Ospedaliero Cantonale (EOC), 6900, Lugano, Switzerland
| | - Lorenzo Ruinelli
- Servizio Di Endocrinologia E Diabetologia, Ospedale Regionale Di Lugano, Ente Ospedaliero Cantonale (EOC), 6900, Lugano, Switzerland
- Team Data Science & Research, Ente Ospedaliero Cantonale, Area ICT, 6500, Bellinzona, Switzerland
- Clinical Trial Unit, Ente Ospedaliero Cantonale (EOC), Bellinzona, Switzerland
| | - Elena Gamarra
- Servizio Di Endocrinologia E Diabetologia, Ospedale Regionale Di Lugano, Ente Ospedaliero Cantonale (EOC), 6900, Lugano, Switzerland
| | - Pierpaolo Trimboli
- Servizio Di Endocrinologia E Diabetologia, Ospedale Regionale Di Lugano, Ente Ospedaliero Cantonale (EOC), 6900, Lugano, Switzerland.
- Facoltà Di Scienze Biomediche, Università Della Svizzera Italiana (USI), 6900, Lugano, Switzerland.
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Xu D, Sui L, Zhang C, Xiong J, Wang VY, Zhou Y, Zhu X, Chen C, Zhao Y, Xie Y, Kong W, Yao J, Xu L, Zhai Y, Wang L. The clinical value of artificial intelligence in assisting junior radiologists in thyroid ultrasound: a multicenter prospective study from real clinical practice. BMC Med 2024; 22:293. [PMID: 38992655 PMCID: PMC11241898 DOI: 10.1186/s12916-024-03510-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2024] [Accepted: 07/01/2024] [Indexed: 07/13/2024] Open
Abstract
BACKGROUND This study is to propose a clinically applicable 2-echelon (2e) diagnostic criteria for the analysis of thyroid nodules such that low-risk nodules are screened off while only suspicious or indeterminate ones are further examined by histopathology, and to explore whether artificial intelligence (AI) can provide precise assistance for clinical decision-making in the real-world prospective scenario. METHODS In this prospective study, we enrolled 1036 patients with a total of 2296 thyroid nodules from three medical centers. The diagnostic performance of the AI system, radiologists with different levels of experience, and AI-assisted radiologists with different levels of experience in diagnosing thyroid nodules were evaluated against our proposed 2e diagnostic criteria, with the first being an arbitration committee consisting of 3 senior specialists and the second being cyto- or histopathology. RESULTS According to the 2e diagnostic criteria, 1543 nodules were classified by the arbitration committee, and the benign and malignant nature of 753 nodules was determined by pathological examinations. Taking pathological results as the evaluation standard, the sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC) of the AI systems were 0.826, 0.815, 0.821, and 0.821. For those cases where diagnosis by the Arbitration Committee were taken as the evaluation standard, the sensitivity, specificity, accuracy, and AUC of the AI system were 0.946, 0.966, 0.964, and 0.956. Taking the global 2e diagnostic criteria as the gold standard, the sensitivity, specificity, accuracy, and AUC of the AI system were 0.868, 0.934, 0.917, and 0.901, respectively. Under different criteria, AI was comparable to the diagnostic performance of senior radiologists and outperformed junior radiologists (all P < 0.05). Furthermore, AI assistance significantly improved the performance of junior radiologists in the diagnosis of thyroid nodules, and their diagnostic performance was comparable to that of senior radiologists when pathological results were taken as the gold standard (all p > 0.05). CONCLUSIONS The proposed 2e diagnostic criteria are consistent with real-world clinical evaluations and affirm the applicability of the AI system. Under the 2e criteria, the diagnostic performance of the AI system is comparable to that of senior radiologists and significantly improves the diagnostic capabilities of junior radiologists. This has the potential to reduce unnecessary invasive diagnostic procedures in real-world clinical practice.
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Affiliation(s)
- Dong Xu
- Department of Diagnostic Ultrasound Imaging & Interventional Therapy, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, 310022, China
- Wenling Institute of Big Data and Artificial Intelligence in Medicine, Taizhou, 317502, China
- Zhejiang Provincial Research Center for Cancer Intelligent Diagnosis and Molecular Technology, Hangzhou, 310022, China
- Taizhou Key Laboratory of Minimally Invasive Interventional Therapy & Artificial Intelligence, Taizhou Campus of Zhejiang Cancer Hospital (Taizhou Cancer Hospital), Taizhou, 317502, China
| | - Lin Sui
- Department of Diagnostic Ultrasound Imaging & Interventional Therapy, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, 310022, China
- Wenling Institute of Big Data and Artificial Intelligence in Medicine, Taizhou, 317502, China
- Zhejiang Provincial Research Center for Cancer Intelligent Diagnosis and Molecular Technology, Hangzhou, 310022, China
- Taizhou Key Laboratory of Minimally Invasive Interventional Therapy & Artificial Intelligence, Taizhou Campus of Zhejiang Cancer Hospital (Taizhou Cancer Hospital), Taizhou, 317502, China
| | - Chunquan Zhang
- Department of Ultrasound, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, China
| | - Jing Xiong
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Vicky Yang Wang
- Wenling Institute of Big Data and Artificial Intelligence in Medicine, Taizhou, 317502, China
- Taizhou Key Laboratory of Minimally Invasive Interventional Therapy & Artificial Intelligence, Taizhou Campus of Zhejiang Cancer Hospital (Taizhou Cancer Hospital), Taizhou, 317502, China
| | - Yahan Zhou
- Wenling Institute of Big Data and Artificial Intelligence in Medicine, Taizhou, 317502, China
- Taizhou Key Laboratory of Minimally Invasive Interventional Therapy & Artificial Intelligence, Taizhou Campus of Zhejiang Cancer Hospital (Taizhou Cancer Hospital), Taizhou, 317502, China
| | - Xinying Zhu
- Department of Diagnostic Ultrasound Imaging & Interventional Therapy, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, 310022, China
- Zhejiang Provincial Research Center for Cancer Intelligent Diagnosis and Molecular Technology, Hangzhou, 310022, China
| | - Chen Chen
- Department of Diagnostic Ultrasound Imaging & Interventional Therapy, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, 310022, China
- Wenling Institute of Big Data and Artificial Intelligence in Medicine, Taizhou, 317502, China
- Zhejiang Provincial Research Center for Cancer Intelligent Diagnosis and Molecular Technology, Hangzhou, 310022, China
- Taizhou Key Laboratory of Minimally Invasive Interventional Therapy & Artificial Intelligence, Taizhou Campus of Zhejiang Cancer Hospital (Taizhou Cancer Hospital), Taizhou, 317502, China
| | - Yu Zhao
- Department of Ultrasound, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, China
| | - Yiting Xie
- Demetics Medical Technology Co. Ltd., Hangzhou, 310022, China
| | - Weizhen Kong
- Department of Mathematics, The University of Hong Kong, Hong Kong, 999077, China
| | - Jincao Yao
- Department of Diagnostic Ultrasound Imaging & Interventional Therapy, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, 310022, China
- Zhejiang Provincial Research Center for Cancer Intelligent Diagnosis and Molecular Technology, Hangzhou, 310022, China
| | - Lei Xu
- Zhejiang Qiushi Institute for Mathematical Medicine, Hangzhou, 310022, China.
- Present address: Division of Medical Imaging and Technology, Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Stockholm, Sweden.
| | - Yuxia Zhai
- The Second Affiliated Hospital of Shantou University Medical College, Guangdong, 515041, China.
| | - Liping Wang
- Department of Diagnostic Ultrasound Imaging & Interventional Therapy, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, 310022, China.
- Zhejiang Provincial Research Center for Cancer Intelligent Diagnosis and Molecular Technology, Hangzhou, 310022, China.
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Zhou B, Liu J, Yang Y, Ye X, Liu Y, Mao M, Sun X, Cui X, Zhou Q. Ultrasound-based nomogram to predict the recurrence in papillary thyroid carcinoma using machine learning. BMC Cancer 2024; 24:810. [PMID: 38972977 PMCID: PMC11229345 DOI: 10.1186/s12885-024-12546-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 06/20/2024] [Indexed: 07/09/2024] Open
Abstract
BACKGROUND AND AIMS The recurrence of papillary thyroid carcinoma (PTC) is not unusual and associated with risk of death. This study is aimed to construct a nomogram that combines clinicopathological characteristics and ultrasound radiomics signatures to predict the recurrence in PTC. METHODS A total of 554 patients with PTC who underwent ultrasound imaging before total thyroidectomy were included. Among them, 79 experienced at least one recurrence. Then 388 were divided into the training cohort and 166 into the validation cohort. The radiomics features were extracted from the region of interest (ROI) we manually drew on the tumor image. The feature selection was conducted using Cox regression and least absolute shrinkage and selection operator (LASSO) analysis. And multivariate Cox regression analysis was used to build the combined nomogram using radiomics signatures and significant clinicopathological characteristics. The efficiency of the nomogram was evaluated by receiver operating characteristic (ROC) curves, calibration curves and decision curve analysis (DCA). Kaplan-Meier analysis was used to analyze the recurrence-free survival (RFS) in different radiomics scores (Rad-scores) and risk scores. RESULTS The combined nomogram demonstrated the best performance and achieved an area under the curve (AUC) of 0.851 (95% CI: 0.788 to 0.913) in comparison to that of the radiomics signature and the clinical model in the training cohort at 3 years. In the validation cohort, the combined nomogram (AUC = 0.885, 95% CI: 0.805 to 0.930) also performed better. The calibration curves and DCA verified the clinical usefulness of combined nomogram. And the Kaplan-Meier analysis showed that in the training cohort, the cumulative RFS in patients with higher Rad-score was significantly lower than that in patients with lower Rad-score (92.0% vs. 71.9%, log rank P < 0.001), and the cumulative RFS in patients with higher risk score was significantly lower than that in patients with lower risk score (97.5% vs. 73.5%, log rank P < 0.001). In the validation cohort, patients with a higher Rad-score and a higher risk score also had a significantly lower RFS. CONCLUSION We proposed a nomogram combining clinicopathological variables and ultrasound radiomics signatures with excellent performance for recurrence prediction in PTC patients.
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Affiliation(s)
- Binqian Zhou
- Department of Ultrasound, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430014, China
| | - Jianxin Liu
- Department of Ultrasound, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430014, China
| | - Yaqin Yang
- Department of Ultrasound, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430014, China
| | - Xuewei Ye
- Department of Ultrasound, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430014, China
| | - Yang Liu
- Department of Ultrasound, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430014, China
| | - Mingfeng Mao
- Department of Ultrasound, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430014, China
| | - Xiaofeng Sun
- Department of Ultrasound, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430014, China
| | - Xinwu Cui
- Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430014, China.
| | - Qin Zhou
- Department of Ultrasound, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430014, China.
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Kim MK, Park H, Oh YL, Shin JH, Kim TH, Hahn SY. Role of ultrasound in predicting telomerase reverse transcriptase (TERT) promoter mutation in follicular thyroid carcinoma. Sci Rep 2024; 14:15323. [PMID: 38961252 PMCID: PMC11222544 DOI: 10.1038/s41598-024-66351-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Accepted: 07/01/2024] [Indexed: 07/05/2024] Open
Abstract
Telomerase reverse transcriptase (TERT) promoter mutations are associated with tumor aggressiveness. This study aimed to demonstrate the ultrasonographic (US) features of TERT promoter-mutated follicular thyroid cancer (FTC) and evaluate their predictive performance. A total of 63 patients with surgically confirmed FTC between August 1995 and April 2021 were included. All data were available for analysis of preoperative US findings and TERT promoter mutation results. Genomic DNA was extracted from the archived surgical specimens to identify TERT promoter mutations. Logistic regression analysis was performed to compare US findings between TERT promoter-mutated and wild-type FTCs. Of the 63 patients with FTC, 10 (15.9%) had TERT promoter mutations. TERT promoter-mutated FTCs demonstrated significantly different US suspicion categories compared to wild-type FTCs (Ps = 0.0054 for K-TIRADS and 0.0208 for ACR-TIRADS), with a trend toward an increasing prevalence of the high suspicion category (40.0% for both K-TIRADS and ACR-TIRADS; Ps for trend = 0.0030 for K-TIRADS and 0.0032 for ACR-TIRADS). Microlobulated margins and punctate echogenic foci were independent risk factors associated with TERT promoter mutation in FTC (odds ratio = 9.693, 95% confidence interval = 1.666-56.401, p = 0.0115 for margins; odds ratio = 8.033, 95% confidence interval = 1.424-45.309, p = 0.0182 for punctate echogenic foci). There were no significant differences in the composition and echogenicity of the TERT promoter-mutated and wild-type FTCs. TERT promoter-mutated FTCs were categorized more frequently as high suspicion by the K-TIRADS and ACR-TIRADS. Based on US findings, the independent risk factors for TERT promoter mutations in FTC are microlobulated margins and punctate echogenic foci.
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Affiliation(s)
- Myoung Kyoung Kim
- Department of Radiology and Center for Imaging Science, Thyroid Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Hyunju Park
- Department of Internal Medicine, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Republic of Korea
| | - Young Lyun Oh
- Department of Pathology, Thyroid Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Jung Hee Shin
- Department of Radiology and Center for Imaging Science, Thyroid Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Tae Hyuk Kim
- Department of Medicine, Thyroid Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Soo Yeon Hahn
- Department of Radiology and Center for Imaging Science, Thyroid Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
- Department of Radiology and Center for Imaging Science, Thyroid Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-Gu, Seoul, 06351, Republic of Korea.
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Lee SE, Kim HJ, Jung HK, Jung JH, Jeon JH, Lee JH, Hong H, Lee EJ, Kim D, Kwak JY. Improving the diagnostic performance of inexperienced readers for thyroid nodules through digital self-learning and artificial intelligence assistance. Front Endocrinol (Lausanne) 2024; 15:1372397. [PMID: 39015174 PMCID: PMC11249553 DOI: 10.3389/fendo.2024.1372397] [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: 01/18/2024] [Accepted: 06/12/2024] [Indexed: 07/18/2024] Open
Abstract
Background Data-driven digital learning could improve the diagnostic performance of novice students for thyroid nodules. Objective To evaluate the efficacy of digital self-learning and artificial intelligence-based computer-assisted diagnosis (AI-CAD) for inexperienced readers to diagnose thyroid nodules. Methods Between February and August 2023, a total of 26 readers (less than 1 year of experience in thyroid US from various departments) from 6 hospitals participated in this study. Readers completed an online learning session comprising 3,000 thyroid nodules annotated as benign or malignant independently. They were asked to assess a test set consisting of 120 thyroid nodules with known surgical pathology before and after a learning session. Then, they referred to AI-CAD and made their final decisions on the thyroid nodules. Diagnostic performances before and after self-training and with AI-CAD assistance were evaluated and compared between radiology residents and readers from different specialties. Results AUC (area under the receiver operating characteristic curve) improved after the self-learning session, and it improved further after radiologists referred to AI-CAD (0.679 vs 0.713 vs 0.758, p<0.05). Although the 18 radiology residents showed improved AUC (0.7 to 0.743, p=0.016) and accuracy (69.9% to 74.2%, p=0.013) after self-learning, the readers from other departments did not. With AI-CAD assistance, sensitivity (radiology 70.3% to 74.9%, others 67.9% to 82.3%, all p<0.05) and accuracy (radiology 74.2% to 77.1%, others 64.4% to 72.8%, all p <0.05) improved in all readers. Conclusion While AI-CAD assistance helps improve the diagnostic performance of all inexperienced readers for thyroid nodules, self-learning was only effective for radiology residents with more background knowledge of ultrasonography. Clinical Impact Online self-learning, along with AI-CAD assistance, can effectively enhance the diagnostic performance of radiology residents in thyroid cancer.
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Affiliation(s)
- Si Eun Lee
- Department of Radiology, Yongin Severance Hospital, College of Medicine, Yonsei University, Yongin-si, Republic of Korea
| | - Hye Jung Kim
- Department of Radiology, Kyungpook National University Chilgok Hospital, Daegu, Republic of Korea
| | - Hae Kyoung Jung
- Department of Radiology, CHA University Bundang Medical Center, Seongnam-si, Republic of Korea
| | - Jing Hyang Jung
- Department of Surgery, Kyungpook National University Chilgok Hospital, Daegu, Republic of Korea
| | - Jae-Han Jeon
- Department of Endocrinology, Kyungpook National University Chilgok Hospital, Daegu, Republic of Korea
| | - Jin Hee Lee
- Department of Radiology, Keimyung University Dongsan Hospital, Daegu, Republic of Korea
| | - Hanpyo Hong
- Department of Radiology, Yongin Severance Hospital, College of Medicine, Yonsei University, Yongin-si, Republic of Korea
| | - Eun Jung Lee
- Department of Computational Science and Engineering, Yonsei University, Seoul, Republic of Korea
| | - Daham Kim
- Department of Endocrinology, College of Medicine, Yonsei University, Seoul, Republic of Korea
| | - Jin Young Kwak
- Department of Radiology, College of Medicine, Yonsei University, Seoul, Republic of Korea
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Lv X, Lu JJ, Song SM, Hou YR, Hu YJ, Yan Y, Yu T, Ye DM. Prediction of lymph node metastasis in patients with papillary thyroid cancer based on radiomics analysis and intraoperative frozen section analysis: A retrospective study. Clin Otolaryngol 2024; 49:462-474. [PMID: 38622816 DOI: 10.1111/coa.14162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 01/28/2024] [Accepted: 03/24/2024] [Indexed: 04/17/2024]
Abstract
INTRODUCTION To evaluate the diagnostic efficiency among the clinical model, the radiomics model and the nomogram that combined radiomics features, frozen section (FS) analysis and clinical characteristics for the prediction of lymph node (LN) metastasis in patients with papillary thyroid cancer (PTC). METHODS A total of 208 patients were randomly divided into two groups randomly with a proportion of 7:3 for the training groups (n = 146) and the validation groups (n = 62). The Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for the selection of radiomics features extracted from ultrasound (US) images. Univariate and multivariate logistic analyses were used to select predictors associated with the status of LN. The clinical model, radiomics model and nomogram were subsequently established by logistic regression machine learning. The area under the curve (AUC), sensitivity and specificity were used to evaluate the diagnostic performance of the different models. The Delong test was used to compare the AUC of the three models. RESULTS Multivariate analysis indicated that age, size group, Adler grade, ACR score and the psammoma body group were independent predictors of lymph node metastasis (LNM). The results showed that in both the training and validation groups, the nomogram showed better performance than the clinical model, albeit not statistically significant (p > .05), and significantly outperformed the radiomics model (p < .05). However, the nomogram exhibits a slight improvement in sensitivity that could reduce the incidence of false negatives. CONCLUSION We propose that the nomogram holds substantial promise as an effective tool for predicting LNM in patients with PTC.
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Affiliation(s)
- Xin Lv
- Department of Oncology, Yingkou Central Hospital, Yingkou, People's Republic of China
| | - Jing-Jing Lu
- Department of Medical Imaging, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang, People's Republic of China
| | - Si-Meng Song
- Department of Medical Imaging, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang, People's Republic of China
| | - Yi-Ru Hou
- Department of Medical Imaging, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang, People's Republic of China
| | - Yan-Jun Hu
- Department of Medical Imaging, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang, People's Republic of China
| | - Yan Yan
- Department of Medical Imaging, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang, People's Republic of China
| | - Tao Yu
- Department of Medical Imaging, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang, People's Republic of China
| | - Dong-Man Ye
- Department of Medical Imaging, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang, People's Republic of China
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Li T, Zhang Y, Li Z, Mei F, Zhai J, Zhang M, Wang S. Bilateral papillary thyroid cancer: pitfalls of ACR TI-RADS and evaluation of modified parameters. Endocrine 2024; 85:295-303. [PMID: 37987970 DOI: 10.1007/s12020-023-03593-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Accepted: 10/30/2023] [Indexed: 11/22/2023]
Abstract
PURPOSE To explore modified parameters of the American College of Radiology Thyroid Imaging Reporting and Data System (TI-RADS) for evaluating contralateral nodules based on preoperative ultrasound features of papillary thyroid carcinoma (PTC) in the suspected lobe, thus guiding the management of bilateral PTC. METHODS We retrospectively analyzed 389 consecutive patients with PTC (272 in training set, 117 in validation set) who underwent total thyroidectomy from March 2020 to March 2022. According to their postoperative pathological data, the patients were divided into unilateral and bilateral PTC groups. The clinicopathological features and sonographic characteristics of suspected nodules were compared between the groups, and further ultrasonic characteristics of TI-RADS grade (TR grade)-underestimated nodules were analyzed. RESULTS Patients with a body mass index of ≥25 kg/m2 (P < 0.001), multifocality in the suspected lobe (P < 0.001), and TR > 3 isthmus nodules (P = 0.003) tended to have bilateral PTC. After modifying the TI-RADS classification for contralateral nodules using these three parameters, the area under the curve for diagnosing contralateral lesions increased from 0.79 (95% confidence interval, 0.74-0.84) to 0.83 (0.78-0.87) in the training set. The missed diagnosis rate of contralateral PTC decreased in both the training set [21.1% (28/133) to 4.5% (6/133)] and validation set [11.4% (8/70) to 2.9% (2/70)]. Preoperative ultrasound tended to underestimate the contralateral nodules with the presence of cystic components [100% (6/6)] and halo sign [73.3% (11/15)]. CONCLUSION The modified TI-RADS classification based on the suspected lobe may facilitate effective preoperative malignant risk stratification of contralateral nodules in bilateral PTC.
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Affiliation(s)
- Tingting Li
- Department of Ultrasound, Peking University Third Hospital, Beijing, 100191, China
- Department of Ultrasound, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, 030032, China
| | - Yongyue Zhang
- Department of Ultrasound, Peking University Third Hospital, Beijing, 100191, China
| | - Zhiqiang Li
- Department of Ultrasound, Peking University Third Hospital, Beijing, 100191, China
| | - Fang Mei
- Department of Pathology, Peking University Third Hospital, Beijing, 100191, China
| | - Junsha Zhai
- Department of Ultrasound, Peking University Third Hospital, Beijing, 100191, China
| | - Min Zhang
- Department of Ultrasound, Peking University Third Hospital, Beijing, 100191, China
- Department of Ultrasound, Second Hospital of Shanxi Medical University, Taiyuan, 030001, China
| | - Shumin Wang
- Department of Ultrasound, Peking University Third Hospital, Beijing, 100191, China.
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Ren JY, Lin JJ, Lv WZ, Zhang XY, Li XQ, Xu T, Peng YX, Wang Y, Cui XW. A Comparative Study of Two Radiomics-Based Blood Flow Modes with Thyroid Imaging Reporting and Data System in Predicting Malignancy of Thyroid Nodules and Reducing Unnecessary Fine-Needle Aspiration Rate. Acad Radiol 2024; 31:2739-2752. [PMID: 38453602 DOI: 10.1016/j.acra.2024.02.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 02/02/2024] [Accepted: 02/04/2024] [Indexed: 03/09/2024]
Abstract
RATIONALE AND OBJECTIVES We aimed to compare superb microvascular imaging (SMI)-based radiomics methods, and contrast-enhanced ultrasound (CEUS)-based radiomics methods to the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) for classifying thyroid nodules (TNs) and reducing unnecessary fine-needle aspiration biopsy (FNAB) rate. MATERIALS AND METHODS This retrospective study enrolled a dataset of 472 pathologically confirmed TNs. Radiomics characteristics were extracted from B-mode ultrasound (BMUS), SMI, and CEUS images, respectively. After eliminating redundant features, four radiomics scores (Rad-scores) were constructed. Using multivariable logistic regression analysis, four radiomics prediction models incorporating Rad-score and corresponding US features were constructed and validated in terms of discrimination, calibration, decision curve analysis, and unnecessary FNAB rate. RESULTS The diagnostic performance of the BMUS + SMI radiomics method was better than ACR TI-RADS (area under the curve [AUC]: 0.875 vs. 0.689 for the training cohort, 0.879 vs. 0.728 for the validation cohort) (P < 0.05), and comparable with BMUS + CEUS radiomics method (AUC: 0.875 vs. 0.878 for the training cohort, 0.879 vs. 0.865 for the validation cohort) (P > 0.05). Decision curve analysis showed that the BMUS+SMI radiomics method could achieve higher net benefits than the BMUS radiomics method and ACR TI-RADS when the threshold probability was between 0.13 and 0.88 in the entire cohort. When applying the BMUS+SMI radiomics method, the unnecessary FNAB rate reduced from 43.4% to 13.9% in the training cohort and from 45.6% to 18.0% in the validation cohorts in comparison to ACR TI-RADS. CONCLUSION The dual-modal SMI-based radiomics method is convenient and economical and can be an alternative to the dual-modal CEUS-based radiomics method in helping radiologists select the optimal clinical strategy for TN management.
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Affiliation(s)
- Jia-Yu Ren
- Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jian-Jun Lin
- Department of Medical Ultrasound, The First People's Hospital of Qinzhou, Qinzhou, China
| | - Wen-Zhi Lv
- Britton Chance Center and MoE Key Laboratory for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China
| | - Xian-Ya Zhang
- Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xue-Qin Li
- Department of Medical Ultrasound, Minda Hospital of Hubei Minzu University, Enshi, China
| | - Tong Xu
- Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yue-Xiang Peng
- Department of Medical Ultrasound, Wuhan Third Hospital, Tongren Hospital of WuHan University, Wuhan, China
| | - Yu Wang
- Department of Medical Ultrasound, Xiangyang First People's Hospital, affiliated with Hubei University of Medicine, Xiangyang, China
| | - Xin-Wu Cui
- Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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Giovanella L, Tuncel M, Aghaee A, Campenni A, De Virgilio A, Petranović Ovčariček P. Theranostics of Thyroid Cancer. Semin Nucl Med 2024; 54:470-487. [PMID: 38503602 DOI: 10.1053/j.semnuclmed.2024.01.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2024] [Revised: 01/29/2024] [Accepted: 01/30/2024] [Indexed: 03/21/2024]
Abstract
Molecular imaging is pivotal in evaluating and managing patients with different thyroid cancer histotypes. The existing, pathology-based, risk stratification systems can be usefully refined, by incorporating tumor-specific molecular and molecular imaging biomarkers with theranostic value, allowing patient-specific treatment decisions. Molecular imaging with different radioactive iodine isotopes (ie, I131, I123, I124) is a central component of differentiated carcinoma (DTC)'s risk stratification while [18F]F-fluorodeoxyglucose ([18F]FDG) PET/CT is interrogated about disease aggressiveness and presence of distant metastases. Moreover, it is particularly useful to assess and risk-stratify patients with radioiodine-refractory DTC, poorly differentiated, and anaplastic thyroid cancers. [18F]F-dihydroxyphenylalanine (6-[18F]FDOPA) PET/CT is the most specific and accurate molecular imaging procedure for patients with medullary thyroid cancer (MTC), a neuroendocrine tumor derived from thyroid C-cells. In addition, [18F]FDG PET/CT can be used in patients with more aggressive clinical or biochemical (ie, serum markers levels and kinetics) MTC phenotypes. In addition to conventional radioiodine therapy for DTC, new redifferentiation strategies are now available to restore uptake in radioiodine-refractory DTC. Moreover, peptide receptor theranostics showed promising results in patients with advanced and metastatic radioiodine-refractory DTC and MTC, respectively. The current appropriate role and future perspectives of molecular imaging and theranostics in thyroid cancer are discussed in our present review.
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Affiliation(s)
- Luca Giovanella
- Department of Nuclear Medicine, Gruppo Ospedaliero Moncucco, Lugano, Switzerland; Clinic for Nuclear Medicine, University Hospital Zürich, Zürich, Switzerland.
| | - Murat Tuncel
- Department of Nuclear Medicine, Hacettepe University, Ankara, Turkey
| | - Atena Aghaee
- Department of Nuclear Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Alfredo Campenni
- Nuclear Medicine Unit, Department of Biomedical and Dental Sciences and Morpho-Functional Imaging, University of Messina, Messina, Italy
| | - Armando De Virgilio
- Department of Head and Neck Surgery Humanitas Research Hospital, Rozzano, Italy
| | - Petra Petranović Ovčariček
- Department of Oncology and Nuclear Medicine, University Hospital Center Sestre Milosrdnice, Zagreb, Croatia; School of Medicine, University of Zagreb, Zagreb, Croatia
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Suzuki A, Hirokawa M, Otsuka I, Miyauchi A, Akamizu T. Calcium oxalate crystals as a cause of multiple punctate echogenic foci in benign thyroid lesions. J Med Ultrason (2001) 2024; 51:517-523. [PMID: 38664308 PMCID: PMC11272687 DOI: 10.1007/s10396-024-01448-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Accepted: 02/16/2024] [Indexed: 07/26/2024]
Abstract
PURPOSE Multiple punctate echogenic foci (MPEF) on thyroid ultrasonography reflects psammoma bodies in papillary thyroid carcinomas. However, MPEF is also observed in benign thyroid lesions. The aim of this study was to determine the origin of MPEF in patients with benign thyroid lesions. METHODS We enrolled 26 patients with Graves' disease (GD) and 24 with follicular nodular disease (FND) who exhibited MPEF and underwent surgery. As controls, we enrolled 40 patients with GD and 32 with FND, but without MPEF, who underwent surgery. RESULTS MPEF was observed in both lobes in 80.8% of GDs with MPEF, but was limited to a single lobe in the remaining cases. MPEF was diffusely distributed in 72.3% of the cases and focally distributed in the remaining cases. On ultrasonography, most (92.3%) FNDs with MPEF were solid lesions, and seven nodules (26.9%) were interpreted as intermediate suspicion and their frequencies were higher than in those without MPEF (p < 0.01). Microscopically, calcium oxalate (CaOx) crystals were observed more frequently in GDs and FNDs with MPEF (100% and 88.5%, respectively) than in those without MPEF (p < 0.001). These differences were particularly significant for CaOx crystals > 100 μm. In GD cases, large CaOx crystals were observed more frequently in the lobes with MPEF than in those without (p < 0.05). No psammoma bodies were present in any of the cases. CONCLUSION Appearance of MPEF in GDs and FNDs is not because of psammoma bodies; it is attributable to CaOx crystals larger than 100 μm. Therefore, MPEF is not an indicator of malignancy.
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Affiliation(s)
- Ayana Suzuki
- Department of Diagnostic Pathology and Cytology, Kuma Hospital, 8-2-35 Shimoyamate-Dori, Chuo-Ku, Kobe, Hyogo, 650-0011, Japan.
| | - Mitsuyoshi Hirokawa
- Department of Diagnostic Pathology and Cytology, Kuma Hospital, 8-2-35 Shimoyamate-Dori, Chuo-Ku, Kobe, Hyogo, 650-0011, Japan
| | - Izumi Otsuka
- Secretary Section, Kuma Hospital, 8-2-35 Shimoyamate-Dori, Chuo-Ku, Kobe, Hyogo, 650-0011, Japan
| | - Akira Miyauchi
- Department of Surgery, Kuma Hospital, 8-2-35 Shimoyamate-Dori, Chuo-Ku, Kobe, Hyogo, 650-0011, Japan
| | - Takashi Akamizu
- Department of Internal Medicine, Kuma Hospital, 8-2-35 Shimoyamate-Dori, Chuo-Ku, Kobe, Hyogo, 650-0011, Japan
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Petranović Ovčariček P, Calderoni L, Campenni A, Fanti S, Giovanella L. Molecular imaging of thyroid and parathyroid diseases. Expert Rev Endocrinol Metab 2024; 19:317-333. [PMID: 38899737 DOI: 10.1080/17446651.2024.2365776] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/24/2024] [Accepted: 06/05/2024] [Indexed: 06/21/2024]
Abstract
INTRODUCTION Molecular imaging of thyroid and parathyroid diseases has changed in recent years due to the introduction of new radiopharmaceuticals and new imaging techniques. Accordingly, we provided an clinicians-oriented overview of such techniques and their indications. AREAS COVERED A review of the literature was performed in the PubMed, Web of Science, and Scopus without time or language restrictions through the use of one or more fitting search criteria and terms as well as through screening of references in relevant selected papers. Literature up to and including December 2023 was included. Screening of titles/abstracts and removal of duplicates was performed and the full texts of the remaining potentially relevant articles were retrieved and reviewed. EXPERT OPINION Thyroid and parathyroid scintigraphy remains integral in patients with thyrotoxicosis, thyroid nodules, differentiated thyroid cancer and, respectively, hyperparathyroidism. In the last years positron-emission tomography with different tracers emerged as a more accurate alternative in evaluating indeterminate thyroid nodules [18F-fluorodeoxyglucose (FDG)], differentiated thyroid cancer [124I-iodide, 18F-tetrafluoroborate, 18F-FDG] and hyperparathyroidism [18F-fluorocholine]. Other PET tracers are useful in evaluating relapsing/advanced forms of medullary thyroid cancer (18F-FDOPA) and selecting patients with advanced follicular and medullary thyroid cancers for theranostic treatments (68Ga/177Ga-somatostatin analogues).
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Affiliation(s)
- Petra Petranović Ovčariček
- Department of Oncology and Nuclear Medicine, University Hospital Center Sestre Milosrdnice, Zagreb, Croatia
- School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Letizia Calderoni
- Nuclear Medicine Division, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Policlinico S. Orsola, Bologna, Italy
- Nuclear Medicine, Alma Mater Studiorum, University of Bologna, Bologna, Italy
| | - Alfredo Campenni
- Department of Biomedical and Dental Sciences and Morpho-Functional Imaging, Unit of Nuclear Medicine, University of Messina, Messina, Italy
| | - Stefano Fanti
- Nuclear Medicine Division, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Policlinico S. Orsola, Bologna, Italy
- Nuclear Medicine, Alma Mater Studiorum, University of Bologna, Bologna, Italy
| | - Luca Giovanella
- Department of Nuclear Medicine, Gruppo Ospedaliero Moncucco, Lugano, Switzerland
- Clinic for Nuclear Medicine, University Hospital of Zürich, Zürich, Switzerland
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Huang SS, Yang Z, Li B, Jiang ZH, Tan Y, Hao DD, Chen CQ, Wang YW, Liang JY, Pan FS, Liu YH, Xie XY, Zhu YF, Wang Z. Radiating blood flow signal: A new ultrasound feature of thyroid carcinoma. Eur J Radiol 2024; 176:111502. [PMID: 38759544 DOI: 10.1016/j.ejrad.2024.111502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 03/25/2024] [Accepted: 05/12/2024] [Indexed: 05/19/2024]
Abstract
OBJECTIVE To summary radiating blood flow signals and evaluate their diagnostic value in differentiating benign and malignant thyroid nodules. MATERIALS AND METHODS We retrospectively recruited consecutive patients undergoing US at 4 hospitals from 2018 to 2022. In a training dataset, the correlations of US features with malignant thyroid nodules were assessed by multivariate logistic analysis. Multivariate logistic regression models involving the ACR TI-RADS score, radiating blood flow signals and their combination were built and validated internally and externally. The AUC with 95% asymptotic normal confidence interval as well as sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) with 95% exact binomial confidence intervals were calculated. RESULTS Among 2475 patients (1818 women, age: 42.47 ± 11.57; 657 men, age: 42.16 ± 11.69), there were 3187 nodules (2342 malignant nodules and 845 benign nodules). Radiating blood flow signals were an independent risk factor for diagnosing thyroid carcinoma. In the training set, the AUC of the model using the combination of radiating blood flow signals and the ACR TI-RADS score (0.95 95 % CI: [0.94, 0.97]; P < 0.001) was significantly higher than that of the ACR TI-RADS model (0.91 [0.89, 0.93]). In the two internal validation sets and the external validation set, the AUCs of the combination model were 0.97 [0.96, 0.98], 0.92 [0.88, 0.96], and 0.91 [0.86, 0.95], respectively, and were all significantly higher than that of the ACR TI-RADS score (0.92 [0.90, 0.95], 0.86 [0.81, 0.91], 0.84 [0.79, 0.89]; P < 0.001). CONCLUSION Radiating blood flow is a new US feature of thyroid carcinomas that can significantly improve the diagnostic performance vs. the ACR TI-RADS score.
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Affiliation(s)
- Sha-Sha Huang
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Zheng Yang
- Department of Pathology, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, Guangdong, China
| | - Bin Li
- Clinical Trials Unit, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Zhi-Hao Jiang
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Yang Tan
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Duo-Duo Hao
- Department of Medical Ultrasonics, Shenzhen Bao'an District Songgang People's Hospital, Shenzhen, Guangdong, China
| | - Chun-Qiao Chen
- Department of Medical Ultrasonics, Bao'an Central Hospital, Shenzhen, Guangdong, China
| | - Ying-Wei Wang
- Department of Medical Ultrasonics, Guangzhou Concord Cancer Center, Guangzhou, China
| | - Jin-Yu Liang
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Fu-Shun Pan
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Yi-Hao Liu
- Clinical Trials Unit, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Xiao-Yan Xie
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Yi-Fan Zhu
- Department of Thyroid Surgery, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
| | - Zhu Wang
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
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Lin S, Gao M, Yang Z, Yu R, Dai Z, Jiang C, Yao Y, Xu T, Chen J, Huang K, Lin D. CT-Based Radiomics Models for Differentiation of Benign and Malignant Thyroid Nodules: A Multicenter Development and Validation Study. AJR Am J Roentgenol 2024; 223:e2431077. [PMID: 38691415 DOI: 10.2214/ajr.24.31077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/03/2024]
Abstract
BACKGROUND. CT is increasingly detecting thyroid nodules. Prior studies indicated a potential role of CT-based radiomics models in characterizing thyroid nodules, although these studies lacked external validation. OBJECTIVE. The purpose of this study was to develop and validate a CT-based radiomics model for the differentiation of benign and malignant thyroid nodules. METHODS. This retrospective study included 378 patients (mean age, 46.3 ± 13.9 [SD] years; 86 men, 292 women) with 408 resected thyroid nodules (145 benign, 263 malignant) from two centers (center 1: 293 nodules, January 2018 to December 2022; center 2: 115 nodules, January 2020 to December 2022) who underwent preoperative multiphase neck CT (noncontrast, arterial, and venous phases). Nodules from center 1 were divided into training (n = 206) and internal validation (n = 87) sets; all nodules from center 2 formed an external validation set. Radiologists assessed nodules for morphologic CT features. Nodules were manually segmented on all phases, and radiomic features were extracted. Conventional (clinical and morphologic CT), noncontrast CT radiomics, arterial phase CT radiomics, venous phase CT radiomics, multiphase CT radiomics, and combined (clinical, morphologic CT, and multiphase CT radiomics) models were established using feature selection methods and evaluated by ROC curve analysis, calibration-curve analysis, and decision-curve analysis. RESULTS. The combined model included patient age, three morphologic features (cystic change, "edge interruption" sign, abnormal cervical lymph nodes), and 28 radiomic features (from all three phases). In the external validation set, the combined model had an AUC of 0.923, and, at an optimal threshold derived in the training set, sensitivity of 84.0%, specificity of 94.1%, and accuracy of 87.0%. In the external validation set, the AUC was significantly higher for the combined model than for the conventional model (0.827), noncontrast CT radiomics model (0.847), arterial phase CT radiomics model (0.826), venous phase CT radiomics model (0.773), and multiphase CT radiomics model (0.824) (all p < .05). In the external validation set, the calibration curves indicated the lowest (i.e., best) Brier score for the combined model; in the decision-curve analysis, the combined model had the highest net benefit for most of the range of threshold probabilities. CONCLUSION. A combined model incorporating clinical, morphologic CT, and multiphase CT radiomics features exhibited robust performance in differentiating benign and malignant thyroid nodules. CLINICAL IMPACT. The combined radiomics model may help guide further management for thyroid nodules detected on CT.
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Affiliation(s)
- Shaofan Lin
- Department of Radiology, Shantou Central Hospital, No. 114 Waima Rd, Shantou 515031, People's Republic of China
| | - Ming Gao
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, People's Republic of China
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, People's Republic of China
| | - Zehong Yang
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, People's Republic of China
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, People's Republic of China
| | - Ruihuan Yu
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, People's Republic of China
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, People's Republic of China
| | - Zhuozhi Dai
- Department of Radiology, Shantou Central Hospital, No. 114 Waima Rd, Shantou 515031, People's Republic of China
| | - Chuling Jiang
- Department of Radiology, Shantou Central Hospital, No. 114 Waima Rd, Shantou 515031, People's Republic of China
| | - Yubin Yao
- Department of Radiology, Shantou Central Hospital, No. 114 Waima Rd, Shantou 515031, People's Republic of China
| | - Tingting Xu
- Department of Radiology, Shantou Central Hospital, No. 114 Waima Rd, Shantou 515031, People's Republic of China
| | - Jiali Chen
- Department of Radiology, Shantou Central Hospital, No. 114 Waima Rd, Shantou 515031, People's Republic of China
| | - Kainan Huang
- Department of Radiology, Shantou Central Hospital, No. 114 Waima Rd, Shantou 515031, People's Republic of China
| | - Daiying Lin
- Department of Radiology, Shantou Central Hospital, No. 114 Waima Rd, Shantou 515031, People's Republic of China
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Castilla Villanueva MÁ, Solis Cano DG, Amador Martínez A, Téliz Meneses MA, Baquera-Heredia J, Vallin Orozco CE, Loya Ceballos M. Individual Ultrasonographic Characteristics of Thyroid Nodules and Their Cytopathological Correlation to Determine Malignancy Risk. Cureus 2024; 16:e63918. [PMID: 39105015 PMCID: PMC11299551 DOI: 10.7759/cureus.63918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/05/2024] [Indexed: 08/07/2024] Open
Abstract
Background Ultrasonographic evaluation of thyroid nodules is challenging due to their high frequency and low malignancy rate. The risk stratification system developed by the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) focuses on addressing the primary contemporary objectives for these lesions, aiming to decrease unnecessary biopsies while maintaining a similar specificity compared with other risk stratification systems. Generally, when indicative of malignancy by ultrasound findings, the next best step in management is an evaluation by fine needle aspiration biopsy (FNAB) and cytological analysis with The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) results that determine further evaluation requirements, actions that are based on the risk of malignancy (ROM) of the assigned category, which could include surgical intervention. Objectives To validate and analyze the individual impact of each ultrasonographic finding indicative of malignancy in the ACR TI-RADS guidelines based on their respective correlation with results obtained by TBSRTC. Materials and method Reports for 212 thyroid ultrasound-guided FNABs from 2018 to 2020 were assessed. Only 117 had both ACR TI-RADS and TBSRTC reports available and were analyzed. Nodules were divided into two groups: ROM < 5% (Bethesda 1, 2; n = 58), and ROM > 5% (Bethesda 3, 4, 5, 6; n = 59). Statistical analysis was performed using the x2 test and bivariate logistic regression model for each characteristic included in ACR TI-RADS. Results Individual ultrasound characteristics with a more pronounced distribution towards the Bethesda > 5% malignancy group were: solid or almost completely solid composition (n=53, 62.3%), very hypoechoic echogenicity (n=3, 75%), wider-than-tall shape (n=50, 50.5%), lobulated or irregular margin (n=23, 65.7%), punctate echogenic foci (n=18, 72%), and thyroid isthmus location (n=6, 75%). Statistically significant individual ultrasonographic characteristics indicative of malignancy included solid or almost completely solid (p = 0.005), very hypoechoic echogenicity (p = 0.046), margin lobulated or irregular (p = 0.031), and punctate echogenic foci (p = 0.015). No significant association was found in the taller-than-wide shape for differentiating malignant from benign lesions (p = 0.969). Conclusions Specific ultrasound characteristics identified in the ACR TI-RADS system demonstrate a stronger correlation with an increased risk of malignancy when compared with cytologic evaluation results. These characteristics include a solid composition, lobulated or irregular margins, punctate echogenic foci, and very hypoechoic echogenicity. Our findings revealed that the scale points for the taller-than-wide characteristic do not adequately represent its true influence on the risk of malignancy.
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Nguyen TA, Brito JP, Singh Ospina N. Defining inappropriate thyroid biopsy?-Proposed definition based on clinical evidence and stakeholder engagement. Endocrine 2024; 85:146-151. [PMID: 38407695 PMCID: PMC11246802 DOI: 10.1007/s12020-024-03727-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Accepted: 02/02/2024] [Indexed: 02/27/2024]
Abstract
PURPOSE Identify factors that can be used to assess the appropriateness of a thyroid biopsy and propose a pathway to define inappropriate thyroid biopsies in practice. METHODS We identified factors utilized in clinical guidelines and existing literature to determine the clinical indications for a thyroid biopsy. Subsequently, we assembled a multidisciplinary panel of experts, including patients, clinicians, researchers, and quality experts, to integrate these factors and develop a pathway for assessing the appropriateness of thyroid biopsies. RESULTS Through literature review and stakeholder engagement, we identified multiple factors to determine if a thyroid biopsy is necessary: ultrasound risk assessment, presence of compressive symptoms and/or clinical suspicion of high-risk thyroid cancer, life expectancy, comorbidity burden, surgical risk, personal risk factors for thyroid cancer, thyroid function levels, local resources and medical expertise and patient values and preferences. We proposed a multiple-tier classification for the appropriateness of thyroid biopsy that begins with ultrasound findings (e.g., size, thyroid cancer risk) and encompasses the evaluation of additional patient-specific factors. CONCLUSION Assessment of the appropriateness of a thyroid biopsy is possible. Although, thyroid nodule ultrasound risk assessment is a pivotal factor for this assessment, additional factors should be considered (e.g., life expectancy, personal risk factors for thyroid cancer, patient preferences). Yet, additional efforts are needed to operationalize the objective implementation of these factors in clinical practice.
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Affiliation(s)
- Thao A Nguyen
- Department of Medicine, University of Florida, Gainesville, FL, USA
| | - Juan P Brito
- Knowledge and Evaluation Research Unit in Endocrinology (KER_Endo), Mayo Clinic, Rochester, MN, USA
| | - Naykky Singh Ospina
- Division of Endocrinology, Department of Medicine, University of Florida, Gainesville, FL, USA.
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Teodoriu L, Ungureanu MC, Matei M, Grierosu I, Saviuc AI, Wael J, Ivanov I, Dragos L, Danila R, Cristian V, Costandache MA, Iftene A, Preda C, Stefanescu C. BRAF Detection in FNAC Combined with Semi-Quantitative 99mTc-MIBI Technique and AI Model, an Economic and Efficient Predicting Tool for Malignancy in Thyroid Nodules. Diagnostics (Basel) 2024; 14:1398. [PMID: 39001288 PMCID: PMC11241294 DOI: 10.3390/diagnostics14131398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2024] [Revised: 06/22/2024] [Accepted: 06/27/2024] [Indexed: 07/16/2024] Open
Abstract
BACKGROUND Technology allows us to predict a histopathological diagnosis, but the high costs prevent the large-scale use of these possibilities. The current liberal indication for surgery in benign thyroid conditions led to a rising frequency of incidental thyroid carcinoma, especially low-risk papillary micro-carcinomas. METHODS We selected a cohort of 148 patients with thyroid nodules by ultrasound characteristics and investigated them by fine needle aspiration cytology (FNAC)and prospective BRAF collection for 70 patients. Also, we selected 44 patients with thyroid nodules using semi-quantitative functional imaging with an oncological, 99mTc-methoxy-isobutyl-isonitrile (99mTc-MIBI) radiotracer. RESULTS Following a correlation with final histopathological reports in patients who underwent thyroidectomy, we introduced the results in a machine learning program (AI) in order to obtain a pattern. For semi-quantitative functional visual pattern imaging, we found a sensitivity of 33%, a specificity of 66.67%, an accuracy of 60% and a negative predicting value (NPV) of 88.6%. For the wash-out index (WOind), we found a sensitivity of 57.14%, a specificity of 50%, an accuracy of 70% and an NPV of 90.06%.The results of BRAF in FNAC included 87.50% sensitivity, 75.00% specificity, 83.33% accuracy, 75.00% NPV and 87.50% PPV. The prevalence of malignancy in our small cohort was 11.4%. CONCLUSIONS We intend to continue combining preoperative investigations such as molecular detection in FNAC, 99mTc-MIBI scanning and AI training with the obtained results on a larger cohort. The combination of these investigations may generate an efficient and cost-effective diagnostic tool, but confirmation of the results on a larger scale is necessary.
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Affiliation(s)
- Laura Teodoriu
- Endocrinology Department, "Grigore T. Popa" University of Medicine and Pharmacy, 700111 Iasi, Romania
| | - Maria-Christina Ungureanu
- Endocrinology Department, "Grigore T. Popa" University of Medicine and Pharmacy, 700111 Iasi, Romania
| | - Mioara Matei
- Preventive Medicine and Interdisciplinarity Department, "Grigore T. Popa" University of Medicine and Pharmacy, 700111 Iasi, Romania
| | - Irena Grierosu
- Biophysics and Medical Physics-Nuclear Medicine Department, "Grigore T. Popa" University of Medicine and Pharmacy, 700111 Iasi, Romania
| | - Alexandra Iuliana Saviuc
- Biophysics and Medical Physics-Nuclear Medicine Department, "Grigore T. Popa" University of Medicine and Pharmacy, 700111 Iasi, Romania
| | - Jalloul Wael
- Biophysics and Medical Physics-Nuclear Medicine Department, "Grigore T. Popa" University of Medicine and Pharmacy, 700111 Iasi, Romania
| | - Iuliu Ivanov
- Center of Fundamental Research and Experimental Development in Translational Medicine, Regional Institute of Oncology, 700483 Iasi, Romania
| | - Loredana Dragos
- Center of Fundamental Research and Experimental Development in Translational Medicine, Regional Institute of Oncology, 700483 Iasi, Romania
| | - Radu Danila
- Department of Surgery, Faculty of Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, 700111 Iasi, Romania
| | - Velicescu Cristian
- Department of Surgery, Faculty of Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, 700111 Iasi, Romania
| | | | - Adrian Iftene
- Faculty of Computer Science, "Alexandru Ioan Cuza" University, 700506 Iasi, Romania
| | - Cristina Preda
- Endocrinology Department, "Grigore T. Popa" University of Medicine and Pharmacy, 700111 Iasi, Romania
| | - Cipriana Stefanescu
- Biophysics and Medical Physics-Nuclear Medicine Department, "Grigore T. Popa" University of Medicine and Pharmacy, 700111 Iasi, Romania
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Chuanke S, Ming L, Zhideng Y, Huan L. A 6-year single-center prospective follow-up study of the efficacy of radiofrequency ablation for thyroid nodules. Front Endocrinol (Lausanne) 2024; 15:1402380. [PMID: 38982991 PMCID: PMC11231197 DOI: 10.3389/fendo.2024.1402380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2024] [Accepted: 06/10/2024] [Indexed: 07/11/2024] Open
Abstract
Background Radiofrequency ablation (RFA) is an alternative modality for thyroid nodules (TNs) and many studies have also confirmed its favorable efficacy and safety. The scope of RFA increases in clinical practice and the aim of our study was to evaluate the efficacy of RFA. Methods We conducted a prospective study to evaluate the efficacy of RFA for thyroid nodules between January 2017 and December 2022 at our institution. We assessed the change in nodal volume, volume reduction ratio (VRR), technique effective (TE) rate, complete ablation (CA) rate, and nodal regrowth rate and time after RFA. Results We performed RFA for 1703 patients with TNs between January 2017 and December 2022, of which a total of 970 eligible patients were enrolled in the study. The preoperative volume of TNs was 6.23 ± 8.11ml, with 821 benign and 149 malignant nodules. The post-RFA TE and adjusted TE rate were 80% and 88.8%, respectively. CA was achieved in 145 (14.9%) patients with a mean time of 18.32± 12.98 months; nodal regrowth occurred in 15 (1.5%) patients with a mean time of 29.80 ± 12.47 months. TNs volume and VRR changed significantly at years 1 and 2 after RFA and stabilized after 5 years. A serious postoperative adverse event occurred in one patient with cervical sympathetic chain injury resulting in Horner's syndrome. A transient or permanent damage of the recurrent laryngeal nerve could not be evaluated due to the lack of postoperative laryngoscopy, and this is a significant limitation of the study. Conclusion The expanded RFA indications were also effective for TNs, with no significant change in long-term efficacy.
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Affiliation(s)
- Shi Chuanke
- Department of General Surgery, Zhongshan Hospital of Traditional Chinese Medicine, Zhongshan, Guangdong, China
| | - Luo Ming
- Department of General Surgery, Zhongshan Hospital of Traditional Chinese Medicine, Zhongshan, Guangdong, China
| | - Yan Zhideng
- Department of General Surgery, Zhongshan Hospital of Traditional Chinese Medicine, Zhongshan, Guangdong, China
| | - Liu Huan
- Department of General Surgery, Zhongshan Hospital of Traditional Chinese Medicine, Zhongshan, Guangdong, China
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Cheng J, Han B, Chen Y, Li Q, Xia W, Wang N, Lu Y. Clinical risk factors and cancer risk of thyroid imaging reporting and data system category 4 A thyroid nodules. J Cancer Res Clin Oncol 2024; 150:327. [PMID: 38914743 PMCID: PMC11196368 DOI: 10.1007/s00432-024-05847-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2024] [Accepted: 06/10/2024] [Indexed: 06/26/2024]
Abstract
PURPOSE Beyond the Thyroid Imaging Reporting and Data System (TIRADS) classification of thyroid nodules, additional factors must be weighed in the decision to perform fine needle aspiration (FNA). In this study, we aimed to identify risk factors for malignancy in patients with ultrasound-classified Chinese-TIRADS (C-TIRADS) 4 A nodules. METHODS Patients who underwent thyroid FNA at our institution between May 2021 and September 2022 were enrolled. We collected demographic data, including age, sex, previous radiation exposure, and family history. An in-person questionnaire was used to collect lifestyle data, such as smoking habits and alcohol consumption. Body mass index (BMI) was calculated. The serum levels of thyroid stimulating hormone (TSH), thyroid peroxidase antibody (TPOAb), and thyroglobulin antibody (TGAb) were measured. Prior to FNA, ultrasonic inspection reports were reviewed. The cytologic diagnoses for FNA of thyroid nodules followed the Bethesda System for Reporting Thyroid Cytopathology (2017). RESULTS Among the 252 C-TIRADS 4 A nodules, 103 were malignant. Compared to those in the benign group, the patients in the malignant group had a younger age (42.2 ± 13.6 vs. 51.5 ± 14.0 years, P < 0.001). Logistic regression showed that advanced age was associated with a lower risk of malignancy in C-TIRADS 4 A nodules (OR = 0.95, 95% CI 0.93 ~ 0.97, P < 0.001). We demonstrated a decreased risk of malignancy in patients with 48.5 years or older. CONCLUSION Advanced age was associated with a decreased risk of malignancy in patients with C-TIRADS 4 A nodules. This study indicated that in addition to sonographic characteristics, patient age should be considered when assessing the risk of malignancy.
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Affiliation(s)
- Jing Cheng
- Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200011, China
| | - Bing Han
- Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200011, China
| | - Yingchao Chen
- Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200011, China
| | - Qin Li
- Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200011, China
| | - Wenwen Xia
- Department of Pathology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China
| | - Ningjian Wang
- Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200011, China
| | - Yingli Lu
- Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200011, China.
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Vahdati S, Khosravi B, Robinson KA, Rouzrokh P, Moassefi M, Akkus Z, Erickson BJ. A Multi-View Deep Learning Model for Thyroid Nodules Detection and Characterization in Ultrasound Imaging. Bioengineering (Basel) 2024; 11:648. [PMID: 39061730 PMCID: PMC11273835 DOI: 10.3390/bioengineering11070648] [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: 04/25/2024] [Revised: 05/27/2024] [Accepted: 06/13/2024] [Indexed: 07/28/2024] Open
Abstract
Thyroid Ultrasound (US) is the primary method to evaluate thyroid nodules. Deep learning (DL) has been playing a significant role in evaluating thyroid cancer. We propose a DL-based pipeline to detect and classify thyroid nodules into benign or malignant groups relying on two views of US imaging. Transverse and longitudinal US images of thyroid nodules from 983 patients were collected retrospectively. Eighty-one cases were held out as a testing set, and the rest of the data were used in five-fold cross-validation (CV). Two You Look Only Once (YOLO) v5 models were trained to detect nodules and classify them. For each view, five models were developed during the CV, which was ensembled by using non-max suppression (NMS) to boost their collective generalizability. An extreme gradient boosting (XGBoost) model was trained on the outputs of the ensembled models for both views to yield a final prediction of malignancy for each nodule. The test set was evaluated by an expert radiologist using the American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS). The ensemble models for each view achieved a mAP0.5 of 0.797 (transverse) and 0.716 (longitudinal). The whole pipeline reached an AUROC of 0.84 (CI 95%: 0.75-0.91) with sensitivity and specificity of 84% and 63%, respectively, while the ACR-TIRADS evaluation of the same set had a sensitivity of 76% and specificity of 34% (p-value = 0.003). Our proposed work demonstrated the potential possibility of a deep learning model to achieve diagnostic performance for thyroid nodule evaluation.
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Affiliation(s)
- Sanaz Vahdati
- Artificial Intelligence Laboratory, Department of Radiology, Mayo Clinic, 200 1st Street, SW, Rochester, MN 55905, USA
| | - Bardia Khosravi
- Artificial Intelligence Laboratory, Department of Radiology, Mayo Clinic, 200 1st Street, SW, Rochester, MN 55905, USA
| | - Kathryn A. Robinson
- Department of Radiology, Mayo Clinic, 200 1st Street, SW, Rochester, MN 55905, USA
| | - Pouria Rouzrokh
- Artificial Intelligence Laboratory, Department of Radiology, Mayo Clinic, 200 1st Street, SW, Rochester, MN 55905, USA
| | - Mana Moassefi
- Artificial Intelligence Laboratory, Department of Radiology, Mayo Clinic, 200 1st Street, SW, Rochester, MN 55905, USA
| | - Zeynettin Akkus
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Bradley J. Erickson
- Artificial Intelligence Laboratory, Department of Radiology, Mayo Clinic, 200 1st Street, SW, Rochester, MN 55905, USA
- Department of Radiology, Mayo Clinic, 200 1st Street, SW, Rochester, MN 55905, USA
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Seitel A, Groener D, Eisenmann M, Aguilera Saiz L, Pekdemir B, Sridharan P, Nguyen CT, Häfele S, Feldmann C, Everitt B, Happel C, Herrmann E, Sabet A, Grünwald F, Franz AM, Maier-Hein L. Miniaturized electromagnetic tracking enables efficient ultrasound-navigated needle insertions. Sci Rep 2024; 14:14161. [PMID: 38898086 PMCID: PMC11187124 DOI: 10.1038/s41598-024-64530-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Accepted: 06/10/2024] [Indexed: 06/21/2024] Open
Abstract
Ultrasound (US) has gained popularity as a guidance modality for percutaneous needle insertions because it is widely available and non-ionizing. However, coordinating scanning and needle insertion still requires significant experience. Current assistance solutions utilize optical or electromagnetic tracking (EMT) technology directly integrated into the US device or probe. This results in specialized devices or introduces additional hardware, limiting the ergonomics of both the scanning and insertion process. We developed the first ultrasound (US) navigation solution designed to be used as a non-permanent accessory for existing US devices while maintaining the ergonomics during the scanning process. A miniaturized EMT source is reversibly attached to the US probe, temporarily creating a combined modality that provides real-time anatomical imaging and instrument tracking at the same time. Studies performed with 11 clinical operators show that the proposed navigation solution can guide needle insertions with a targeting accuracy of about 5 mm, which is comparable to existing approaches and unaffected by repeated attachment and detachment of the miniaturized tracking solution. The assistance proved particularly helpful for non-expert users and needle insertions performed outside of the US plane. The small size and reversible attachability of the proposed navigation solution promises streamlined integration into the clinical workflow and widespread access to US navigated punctures.
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Affiliation(s)
- Alexander Seitel
- Division of Intelligent Medical Systems, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany.
- National Center for Tumor Diseases (NCT), a partnership between DKFZ and Heidelberg University Hospital, 69120, Heidelberg, Germany.
| | - Daniel Groener
- Department of Nuclear Medicine, Clinic for Radiology and Nuclear Medicine, University Hospital, Goethe University Frankfurt, 60596, Frankfurt, Germany
| | - Matthias Eisenmann
- Division of Intelligent Medical Systems, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Laura Aguilera Saiz
- Division of Intelligent Medical Systems, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Bünyamin Pekdemir
- Division of Intelligent Medical Systems, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Patmaa Sridharan
- Division of Intelligent Medical Systems, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Cam Tu Nguyen
- Department of Nuclear Medicine, Clinic for Radiology and Nuclear Medicine, University Hospital, Goethe University Frankfurt, 60596, Frankfurt, Germany
| | - Sebastian Häfele
- Department of Nuclear Medicine, Clinic for Radiology and Nuclear Medicine, University Hospital, Goethe University Frankfurt, 60596, Frankfurt, Germany
| | - Carolin Feldmann
- Division of Intelligent Medical Systems, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Brittaney Everitt
- Division of Intelligent Medical Systems, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Christian Happel
- Department of Nuclear Medicine, Clinic for Radiology and Nuclear Medicine, University Hospital, Goethe University Frankfurt, 60596, Frankfurt, Germany
| | - Eva Herrmann
- Department of Medicine, Institute for Biostatistics, Goethe University Frankfurt, 60596, Frankfurt, Germany
| | - Amir Sabet
- Department of Nuclear Medicine, Clinic for Radiology and Nuclear Medicine, University Hospital, Goethe University Frankfurt, 60596, Frankfurt, Germany
| | - Frank Grünwald
- Department of Nuclear Medicine, Clinic for Radiology and Nuclear Medicine, University Hospital, Goethe University Frankfurt, 60596, Frankfurt, Germany
| | - Alfred Michael Franz
- Division of Intelligent Medical Systems, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany.
- Institute for Computer Science, Ulm University of Applied Sciences, 89075, Ulm, Germany.
| | - Lena Maier-Hein
- Division of Intelligent Medical Systems, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
- National Center for Tumor Diseases (NCT), a partnership between DKFZ and Heidelberg University Hospital, 69120, Heidelberg, Germany
- Faculty of Mathematics and Computer Science, Heidelberg University, 69120, Heidelberg, Germany
- Medical Faculty, Heidelberg University, 69120, Heidelberg, Germany
- Helmholtz Information and Data Science School for Health, Karlsruhe/Heidelberg, Germany
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Ye BB, Liu YY, Zhang Y, Liu BJ, Guo LH, Wei Q, Zhang YF, Xu HX. Predicting tall-cell subtype of papillary thyroid carcinomas independently with preoperative multimodal ultrasound. Br J Radiol 2024; 97:1311-1319. [PMID: 38775639 PMCID: PMC11186555 DOI: 10.1093/bjr/tqae103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2023] [Revised: 05/09/2024] [Accepted: 05/14/2024] [Indexed: 06/21/2024] Open
Abstract
OBJECTIVES This study aimed to explore the differences between tall-cell subtype of papillary thyroid carcinoma (TCPTC) and classical papillary thyroid carcinoma (cPTC) using multimodal ultrasound, and identify independent risk factors for TCPTC to compensate the deficiency of preoperative cytological and molecular diagnosis on PTC subtypes. METHODS Forty-six TCPTC patients and 92 cPTC patients were included. Each patient received grey-scale ultrasound, colour Dopplor flow imaging (CDFI) and shear-wave elastography (SWE) preoperatively. Clinicopathologic information, grey-scale ultrasound features, CDFI features and SWE features of 98 lesions were compared using univariate analysis to find out predictors of TCPTC, based on which, a predictive model was built to differentiate TCPTC from cPTC and validated with 40 patients. RESULTS Univariate and multivariate analyses identified that extra-thyroidal extension (odds ratio [OR], 15.12; 95% CI, 2.26-115.44), aspect ratio (≥0.91) (OR, 29.34; 95% CI, 1.29-26.23), and maximum diameter ≥14.6 mm (OR, 20.79; 95% CI, 3.87-111.47) were the independent risk factors for TCPTC. Logistic regression equation: P = 1/1+ExpΣ[-5.099 + 3.004 × (if size ≥14.6 mm) + 2.957 × (if aspect ratio ≥ 0.91) + 2.819 × (if extra-thyroidal extension). The prediction model had a good discrimination performance for TCPTC: the area under the receiver-operator-characteristic curve, sensitivity, and specificity were 0.928, 0.848, and 0.954 in cohort 1, and the corresponding values in cohort 2 were 0.943, 0.923, and 0.926, respectively. CONCLUSION Ultrasound has the potential for differential diagnosis of TCPTC from cPTC. A prediction model based on ultrasound characteristics (extra-thyroidal extension, aspect ratio ≥0.91, and maximum diameter ≥14.6 mm) was useful in predicting TCPTC. ADVANCES IN KNOWLEDGE Multimodal ultrasound prediction of TCPTC was a supplement to preoperative cytological diagnosis and molecular diagnosis of PTC subtypes.
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Affiliation(s)
- Bei-Bei Ye
- Department of Medical Ultrasound, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai 200072, China
- Shanghai Engineering Research Center of Ultrasound Diagnosis and Treatment, Shanghai 200072, China
| | - Yun-Yun Liu
- Department of Medical Ultrasound, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai 200072, China
- Shanghai Engineering Research Center of Ultrasound Diagnosis and Treatment, Shanghai 200072, China
| | - Ying Zhang
- Department of Medical Ultrasound, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai 200072, China
- Shanghai Engineering Research Center of Ultrasound Diagnosis and Treatment, Shanghai 200072, China
| | - Bo-Ji Liu
- Department of Medical Ultrasound, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai 200072, China
- Shanghai Engineering Research Center of Ultrasound Diagnosis and Treatment, Shanghai 200072, China
| | - Le-Hang Guo
- Department of Medical Ultrasound, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai 200072, China
- Shanghai Engineering Research Center of Ultrasound Diagnosis and Treatment, Shanghai 200072, China
- Ultrasound Research and Education Institute, Clinical Research Center for Interventional Medicine, School of Medicine, Tongji University, Shanghai 200072, China
| | - Qing Wei
- Department of Pathology, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai 200072, China
| | - Yi-Feng Zhang
- Department of Medical Ultrasound, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai 200072, China
- Shanghai Engineering Research Center of Ultrasound Diagnosis and Treatment, Shanghai 200072, China
- Ultrasound Research and Education Institute, Clinical Research Center for Interventional Medicine, School of Medicine, Tongji University, Shanghai 200072, China
| | - Hui-Xiong Xu
- Shanghai Engineering Research Center of Ultrasound Diagnosis and Treatment, Shanghai 200072, China
- Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai 200032, China
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Scappaticcio L, Di Martino N, Caruso P, Ferrazzano P, Marino FZ, Clery E, Cioce A, Cozzolino G, Maiorino MI, Docimo G, Trimboli P, Franco R, Esposito K, Bellastella G. The value of ACR, European, Korean, and ATA ultrasound risk stratification systems combined with RAS mutations for detecting thyroid carcinoma in cytologically indeterminate and suspicious for malignancy thyroid nodules. Hormones (Athens) 2024:10.1007/s42000-024-00573-8. [PMID: 38884926 DOI: 10.1007/s42000-024-00573-8] [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: 03/02/2024] [Accepted: 06/05/2024] [Indexed: 06/18/2024]
Abstract
PURPOSE The aim of this study was to evaluate the diagnostic value of four commonly utilized ultrasound (US) RSSs, namely, the American College of Radiology [ACR], European [EU], Korean [K] TI-RADSs and American Thyroid Association [ATA] US-based RSS criteria, in combination with activating point mutations of the RAS genes (NRAS, HRAS, and KRAS) for detection of thyroid carcinoma in cytologically indeterminate and suspicious for malignancy thyroid nodules. METHODS We retrospectively analyzed cytologically indeterminate and suspicious for malignancy thyroid nodules which underwent US, molecular testing and surgery between September 1, 2018, and December 31, 2023. Receiver operating characteristic (ROC) curves were generated, and the area under the curve (AUC, 95% confidence interval [CI]) was calculated. RESULTS A total of 100 cytologically indeterminate and 24 suspicious for malignancy thyroid nodules were analyzed. Compared to the four US-based RSSs alone, the diagnostic value of the four US-based RSSs combined with RAS mutations did not significantly improved (cytologically indeterminate, AUC [95% CI] 0.6 [0.5-0.7] and 0.6 [0.5-0.7], respectively, p = 0.70; cytologically suspicious for malignancy, AUC [95% CI] 0.7 [0.5-0.9] and 0.8 [0.6-0.9], respectively, p = 0.23). CONCLUSIONS The diagnostic value of the four main US-based RSSs (ACR, EU, K, and ATA) was not improved in conjunction with the evaluation of RAS mutations for preoperative risk stratification of cytologically indeterminate thyroid nodules. CLINICAL RELEVANCE STATEMENT In cytologically indeterminate nodules categorized according to US-based RSSs, isolated RAS positivity does not reliably distinguish between benignity and malignancy.
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Affiliation(s)
- Lorenzo Scappaticcio
- Unit of Endocrinology and Metabolic Diseases, AOU University of Campania "Luigi Vanvitelli", Naples, 80138, Italy
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Nicole Di Martino
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Paola Caruso
- Unit of Endocrinology and Metabolic Diseases, AOU University of Campania "Luigi Vanvitelli", Naples, 80138, Italy.
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy.
| | - Pamela Ferrazzano
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy
| | | | - Eduardo Clery
- Pathology Unit, AOU University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Alessandro Cioce
- Pathology Unit, AOU University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Giovanni Cozzolino
- Unit of Thyroid Surgery, AOU University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Maria Ida Maiorino
- Unit of Endocrinology and Metabolic Diseases, AOU University of Campania "Luigi Vanvitelli", Naples, 80138, Italy
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Giovanni Docimo
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy
- Unit of Thyroid Surgery, AOU University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Pierpaolo Trimboli
- Clinic of Endocrinology and Diabetology, Lugano and Mendrisio Regional Hospital, Ente Ospedaliero Cantonale, Bellinzona, Switzerland
- Faculty of Biomedical Sciences, Università della Svizzera Italiana, Lugano, Switzerland
| | - Renato Franco
- Pathology Unit, AOU University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Katherine Esposito
- Unit of Endocrinology and Metabolic Diseases, AOU University of Campania "Luigi Vanvitelli", Naples, 80138, Italy
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Giuseppe Bellastella
- Unit of Endocrinology and Metabolic Diseases, AOU University of Campania "Luigi Vanvitelli", Naples, 80138, Italy
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy
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Parsa AA, Gharib H. Thyroid Nodules: Past, Present, and Future. Endocr Pract 2024:S1530-891X(24)00558-5. [PMID: 38880348 DOI: 10.1016/j.eprac.2024.05.016] [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: 01/12/2024] [Revised: 05/09/2024] [Accepted: 05/29/2024] [Indexed: 06/18/2024]
Abstract
BACKGROUND Over the past millennia, the evaluation and management of thyroid nodules has essentially remained the same with thyroidectomy as the only reliable method to identify malignancy. However, in the last 30 years, technological advances have significantly improved diagnostic management of thyroid nodules. Advances in imaging have allowed development of a reliable risk- based stratification system to identify nodules at increased risk of malignancy. At the same time, sensitive imaging has caused collateral damage to the degree that we are now identifying and treating many small, low risk nodules with little to no clinical relevance. OBJECTIVE To review the history of thyroid nodule evaluation with emphasis on recent changes and future pathways. METHODS Literature review and discussion. RESULTS Thyroid ultrasound remains the best initial method to evaluate the thyroid gland for nodules. Different risk-of-malignancy protocols have been developed and introduced by different societies, reporting methods have been developed and improved each, with goals of improving the ability to recognize nodules requiring further intervention and minimizing excessive monitoring of those who do not. Once identified, cytological evaluation of nodules further enhances malignancy identification with molecular markers assisting in ruling out malignancies in indeterminate nodules preventing unneeded intervention. And all societies have urged avoidance of overdiagnosis and overtreatment of low-risk cancers of little to no clinical relevance. CONCLUSION In this review, we describe advancements in nodule evaluation and management, while emphasizing caution in overdiagnosing and overtreating low-risk lesions without clinical importance.
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Affiliation(s)
- Alan A Parsa
- John A. Burns School of Medicine, University of Hawai'i at Mānoa, Honolulu, Hawaii.
| | - Hossein Gharib
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic College of Medicine, Rochester, Minnesota
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Zheng T, Zhang Y, Wang H, Tang L, Xie X, Fu Q, Wu PY, Song B. Thyroid imaging reporting and data system with MRI morphological features for thyroid nodules: diagnostic performance and unnecessary biopsy rate. Cancer Imaging 2024; 24:74. [PMID: 38872150 DOI: 10.1186/s40644-024-00721-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Accepted: 06/10/2024] [Indexed: 06/15/2024] Open
Abstract
BACKGROUND To assess MRI-based morphological features in improving the American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS) for categorizing thyroid nodules. METHODS A retrospective analysis was performed on 728 thyroid nodules (453 benign and 275 malignant) that postoperative pathology confirmed. Univariate and multivariate logistic regression analyses were used to find independent predictors of MRI morphological features in benign and malignant thyroid nodules. The improved method involved increasing the ACR-TIRADS level by one when there are independent predictors of MRI-based morphological features, whether individually or in combination, and conversely decreasing it by one. The study compared the performance of conventional ACR-TIRADS and different improved versions. RESULTS Among the various MRI morphological features analyzed, restricted diffusion and reversed halo sign were determined to be significant independent risk factors for malignant thyroid nodules (OR = 45.1, 95% CI = 23.2-87.5, P < 0.001; OR = 38.0, 95% CI = 20.4-70.7, P < 0.001) and were subsequently included in the final assessment of performance. The areas under the receiver operating characteristic curves (AUCs) for both the conventional and four improved ACR-TIRADSs were 0.887 (95% CI: 0.861-0.909), 0.945 (95% CI: 0.926-0.961), 0.947 (95% CI: 0.928-0.962), 0.945 (95% CI: 0.926-0.961) and 0.951 (95% CI: 0.932-0.965), respectively. The unnecessary biopsy rates for the conventional and four improved ACR-TIRADSs were 62.8%, 30.0%, 27.1%, 26.8% and 29.1%, respectively, while the malignant missed diagnosis rates were 1.1%, 2.8%, 3.7%, 5.4% and 1.2%. CONCLUSIONS MRI morphological features with ACR-TIRADS has improved diagnostic performance and reduce unnecessary biopsy rate while maintaining a low malignant missed diagnosis rate.
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Affiliation(s)
- Tingting Zheng
- Department of Radiology, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, Shanghai, 201199, China
| | - Yuan Zhang
- Department of Radiology, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, Shanghai, 201199, China
| | - Hao Wang
- Department of Radiology, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, Shanghai, 201199, China
| | - Lang Tang
- Department of Ultrasound, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, Shanghai, 201199, China
| | - Xiaoli Xie
- Department of Pathology, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, Shanghai, 201199, China
| | - Qingyin Fu
- Department of Ultrasound, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, Shanghai, 201199, China
| | - Pu-Yeh Wu
- GE Healthcare, MR Research China, Beijing, China
| | - Bin Song
- Department of Radiology, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, Shanghai, 201199, China.
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Song B, Zheng T, Wang H, Tang L, Xie X, Fu Q, Liu W, Wu PY, Zeng M. Prediction of Follicular Thyroid Neoplasm and Malignancy of Follicular Thyroid Neoplasm Using Multiparametric MRI. JOURNAL OF IMAGING INFORMATICS IN MEDICINE 2024:10.1007/s10278-024-01102-0. [PMID: 38839672 DOI: 10.1007/s10278-024-01102-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Revised: 03/21/2024] [Accepted: 03/22/2024] [Indexed: 06/07/2024]
Abstract
The study aims to evaluate multiparametric magnetic resonance imaging (MRI) for differentiating Follicular thyroid neoplasm (FTN) from non-FTN and malignant FTN (MFTN) from benign FTN (BFTN). We retrospectively analyzed 702 postoperatively confirmed thyroid nodules, and divided them into training (n = 482) and validation (n = 220) cohorts. The 133 FTNs were further split into BFTN (n = 116) and MFTN (n = 17) groups. Employing univariate and multivariate logistic regression, we identified independent predictors of FTN and MFTN, and subsequently develop a nomogram for FTN and a risk score system (RSS) for MFTN prediction. We assessed performance of nomogram through its discrimination, calibration, and clinical utility. The diagnostic performance of the RSS for MFTN was further compared with the performance of the Thyroid Imaging Reporting and Data System (TIRADS). The nomogram, integrating independent predictors, demonstrated robust discrimination and calibration in differentiating FTN from non-FTN in both training cohort (AUC = 0.947, Hosmer-Lemeshow P = 0.698) and validation cohort (AUC = 0.927, Hosmer-Lemeshow P = 0.088). Key risk factors for differentiating MFTN from BFTN included tumor size, restricted diffusion, and cystic degeneration. The AUC of the RSS for MFTN prediction was 0.902 (95% CI 0.798-0.971), outperforming five TIRADS with a sensitivity of 73.3%, specificity of 95.1%, accuracy of 92.4%, and positive and negative predictive values of 68.8% and 96.1%, respectively, at the optimal cutoff. MRI-based models demonstrate excellent diagnostic performance for preoperative predicting of FTN and MFTN, potentially guiding clinicians in optimizing therapeutic decision-making.
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Affiliation(s)
- Bin Song
- Department of Radiology, Zhongshan Hospital, Shanghai Medical Imaging Institute, Fudan University, No180, Fenglin Road, Xuhui District, 200032, Shanghai, China
- Department of Radiology, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, 201199, Shanghai, China
| | - Tingting Zheng
- Department of Radiology, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, 201199, Shanghai, China
| | - Hao Wang
- Department of Radiology, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, 201199, Shanghai, China
| | - Lang Tang
- Department of Ultrasound, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, 201199, Shanghai, China
| | - Xiaoli Xie
- Department of Pathology, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, 201199, Shanghai, China
| | - Qingyin Fu
- Department of Ultrasound, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, 201199, Shanghai, China
| | - Weiyan Liu
- Department of General Surgery, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, 201199, Shanghai, China
| | - Pu-Yeh Wu
- GE Healthcare, MR Research China, Beijing, China
| | - Mengsu Zeng
- Department of Radiology, Zhongshan Hospital, Shanghai Medical Imaging Institute, Fudan University, No180, Fenglin Road, Xuhui District, 200032, Shanghai, China.
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Dimaano KL, Dib VA, Parnall T, Covington A, Kaji AH, Choi P, Chen KT. The Utility of ACR TI-RADS in Predicting False-Negative Fine Needle Aspiration for Thyroid Cancer. Am Surg 2024; 90:1156-1160. [PMID: 38212274 DOI: 10.1177/00031348241227184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2024]
Abstract
BACKGROUND Thyroid nodule fine needle aspiration (FNA) biopsies are associated with a low false-negative rate. There is limited data regarding the predictive value of American College of Radiology Thyroid Imaging Reporting and Data System for false-negative FNA. METHODS This single-center retrospective study evaluated 119 patients who underwent thyroidectomy. The association of TR category, along with other clinical variables, with false-negative FNA was evaluated. RESULTS The overall false-negative rate of FNA was 10.8% (n = 9). False-negative FNAs were associated with younger age (mean 42 years vs 50.6 years, P = .04), larger nodule size (mean 4.4 cm vs 3.2 cm, P = .03), and a lower TR category (median 3 v 4, P = .01). DISCUSSION Lower TR category, younger age, and larger nodule size were associated with false-negative FNA of thyroid nodules. These findings should be taken into context when counseling patients with thyroid nodules who have a benign FNA.
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Affiliation(s)
- Katrina L Dimaano
- Department of Surgery, Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Valerie A Dib
- Department of Radiology, Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Taylor Parnall
- Department of Radiology, Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Audrey Covington
- Department of Surgery, Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Amy H Kaji
- Department of Emergency Medicine, Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Patrick Choi
- Department of Radiology, Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Kathryn T Chen
- Department of Surgery, Harbor-UCLA Medical Center, Torrance, CA, USA
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Tan Y, Zhong J, Zheng T, Fu Y, Liu M, Wang G. Associations of BRAF V600E mutation with the American College of Radiology Thyroid Imaging Reporting and Data System and clinicopathological characteristics in pediatric patients with papillary thyroid carcinoma. Pediatr Radiol 2024; 54:1128-1136. [PMID: 38771344 DOI: 10.1007/s00247-024-05943-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/10/2024] [Revised: 05/01/2024] [Accepted: 05/02/2024] [Indexed: 05/22/2024]
Abstract
BACKGROUND Identifying the associations between BRAFV600E mutation, the American College of Radiology Thyroid Imaging Reporting and Data System (TI-RADS) and clinicopathological characteristics could assist in making appropriate treatment strategies for pediatric patients with papillary thyroid carcinoma. OBJECTIVE To retrospectively assess the associations between BRAFV600E mutation, TI-RADS, and clinicopathological characteristics in pediatric patients with papillary thyroid carcinoma. MATERIALS AND METHODS Between May 2013 and May 2023, pediatric patients with papillary thyroid carcinoma who underwent thyroidectomy were retrospectively evaluated. Univariate and multivariate logistic regression analyses were performed to determine the associations between BRAFV600E mutation, TI-RADS, and clinicopathological characteristics. The diagnostic performance of TI-RADS to predict BRAFV600E mutation was assessed. RESULTS The BRAFV600E mutation was found in 59.1% (39/66) of pediatric patients with papillary thyroid carcinoma. Multivariate analyses showed that hypoechoic/very hypoechoic [odds ratio (OR) = 8.48; 95% confidence interval (CI) = 1.48-48.74); P-value = 0.02] and punctate echogenic foci (OR = 24.3; 95% CI = 3.80-155.84; P-value = 0.001) were independent factors associated with BRAFV600E mutation. In addition, BRAFV600E mutation was significantly associated with TI-RADS 5 (OR = 12.61; 95% CI = 1.28-124.49; P-value = 0.03). There were no associations between BRAFV600E mutation and nodule size, composition, shape, margin, cervical lymph node metastasis, or Hashimoto's thyroiditis (P-value > 0.05). Combined with hypoechoic/very hypoechoic and punctate echogenic foci, the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 89.7%, 85.2%, 89.7%, 85.2%, and 87.9%, respectively. CONCLUSIONS Hypoechoic/very hypoechoic, punctate echogenic foci, and TI-RADS 5 are independently associated with BRAFV600E mutation in pediatric patients with papillary thyroid carcinoma.
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Affiliation(s)
- Yan Tan
- Department of Ultrasound Diagnosis, The Second Xiangya Hospital of Central South University, 139 Renmin Middle Road, Changsha, 410011, China
| | - Jia Zhong
- Department of Ultrasound, Mawangdui District of Hunan Provincial People's Hospital, Hunan Normal University, Changsha, China
| | - Taiqing Zheng
- Department of Pathology, Hunan Children's Hospital, Changsha, China
| | - Yusi Fu
- Department of Ultrasound Diagnosis, The Second Xiangya Hospital of Central South University, 139 Renmin Middle Road, Changsha, 410011, China
| | - Minghui Liu
- Department of Ultrasound Diagnosis, The Second Xiangya Hospital of Central South University, 139 Renmin Middle Road, Changsha, 410011, China
| | - Guotao Wang
- Department of Ultrasound Diagnosis, The Second Xiangya Hospital of Central South University, 139 Renmin Middle Road, Changsha, 410011, China.
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Ebaid NY, Ahmed RN, Assy MM, Amin MI, Alaa Eldin AM, Alsowey AM, Abdelhay RM. Diagnostic validity and reliability of BT-RADS in the management of recurrent high-grade glioma. J Neuroradiol 2024; 51:101190. [PMID: 38492800 DOI: 10.1016/j.neurad.2024.03.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 03/12/2024] [Accepted: 03/13/2024] [Indexed: 03/18/2024]
Abstract
BACKGROUND AND PURPOSE BT-RADS is a new framework system for reporting the treatment response of brain tumors. The aim of the study was to assess the diagnostic performance and reliability of the BT-RADS in predicting the recurrence of high-grade glioma (HGG). MATERIALS AND METHODS This prospective single-center study recruited 81 cases with previously operated and pathologically proven HGG. The patients underwent baseline and follow-up contrast-enhanced MRI (CE-MRI). Two neuro-radiologists with ten years-experience in neuroimaging independently analyzed and interpreted the MRI images and assigned a BT-RADS category for each case. To assess the diagnostic accuracy of the BT-RADS for detecting recurrent HGG, the reference standard was the histopathology for BT-RADS categories 3 and 4, while neurological clinical examination and clinical follow up were used as a reference for BT-RADS categories 1 and 2. The inter-reader agreement was assessed using the Cohen's Kappa test. RESULTS The study included 81 cases of HGG, of which 42 were recurrent and 39 were non-recurrent HGG cases based on the reference test. BT-RADS 3B was the best cutoff for predicting recurrent HGG with a sensitivity of 90.5 % to 92.9 %, specificity of 76.9 % to 84.6 %, and accuracy of 83.9 % to 88.9 %, based on both readers. The BT-RADS showed a substantial inter-reader agreement with a K of 0.710 (P = 0.001). CONCLUSIONS The BT-RADS is a valid and reliable framework for predicting recurrent HGG. Moreover, BT-RADS can help neuro-oncologists make clinical decisions that can potentially improve the patient's outcome.
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Affiliation(s)
- Noha Yahia Ebaid
- Department of Radiology, Faculty of medicine, Zagazig University, Zagazig, Egypt; Negida academy LLC, Arlington, MA, USA
| | - Rasha Nadeem Ahmed
- Department of Surgery, College of medicine, Ninevah University, Mosul, Iraq
| | - Mostafa Mohamad Assy
- Department of Radiology, Faculty of medicine, Zagazig University, Zagazig, Egypt
| | - Mohamed Ibrahim Amin
- Department of Radiology, Faculty of medicine, Zagazig University, Zagazig, Egypt
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Park T, Huber T, Marchak K, Hart J, Walker L. Benign Thyroid Nodule Interventions: A Review and Imaging Considerations for the Interventional Radiologist. Semin Intervent Radiol 2024; 41:293-301. [PMID: 39165655 PMCID: PMC11333111 DOI: 10.1055/s-0044-1788339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/22/2024]
Abstract
Thyroid radiofrequency ablation (RFA) is a minimally invasive procedure that can be used to treat patients with benign thyroid nodules and is a good alternative to thyroidectomy or radioactive iodine. Thyroid RFA is commonly performed with local lidocaine or minimal/moderate sedation and has a minimal risk profile and few side effects. The efficacy of thyroid RFA has been well documented in the literature, with a volume reduction rate of 67 to 75% at 1 year. Another emerging technique for nodule size reduction is thyroid artery embolization which is a minimally invasive procedure that may be performed in patients with nodular goiters, particularly with substernal thyroid nodule extension, and who are either poor surgical candidates or do not want surgery. This article reviews thyroid RFA, focusing on the relevant preprocedural, procedural, and postprocedural imaging, as well as a discussion on the emerging role of thyroid artery embolization.
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Affiliation(s)
- Tyler Park
- University of Colorado, Anschutz School of Medicine, Aurora, Colorado
| | - Timothy Huber
- Jefferson Radiology, Interventional Radiology, East Hartford, Connecticut
| | - Katherine Marchak
- Department of Radiology, Interventional Radiology, University of Colorado, Aurora, Colorado
| | - James Hart
- Department of Radiology, Interventional Radiology, University of Colorado, Aurora, Colorado
| | - Lisa Walker
- Department of Radiology, Interventional Radiology, University of Colorado, Aurora, Colorado
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Şah Ünal FT, Gökçay Canpolat A, Elhan AH, Sevim S, Sak SD, Emral R, Demir Ö, Güllü S, Erdoğan MF, Çorapçıoğlu D, Şahin M. Cancer rates and characteristics of thyroid nodules with macrocalcification. Endocrine 2024; 84:1021-1029. [PMID: 38147262 DOI: 10.1007/s12020-023-03650-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Accepted: 12/08/2023] [Indexed: 12/27/2023]
Abstract
AIMS The aim of this study was to determine the malignant potential of thyroid nodules with macrocalcifications and to evaluate the role of other sonographic findings in the diagnosis of malignancy in thyroid nodules besides macrocalcifications. METHODS The findings of 8250 patients who applied to our outpatient clinic and underwent thyroid ultrasonography(US) between 2008 and 2021 were retrospectively reviewed. We included a total of 296 patients with 296 macrocalcified nodules (macrocalcification group) and an age- and sex matched group of 300 patients (control group) with the cytopathologic and/or histopathologic data of fine-needle aspiration biopsy (FNAB) of thyroid nodules without calcification. Demographic characteristics of these patients, US characteristics of the nodules, and thyroid function tests were recorded. Cytopathological data of FNAB were classified according to BETHESDA. RESULTS The malignancy rate was 14.2% (42/296) in the macrocalcification group and 5.3% (16/300) in the control group (p < 0.001). There was no significant relationship between interrupted peripheral calcification and malignancy. Hypoechoic or markedly hypoechoic appearance, irregular border, solid structure, presence of accompanying pathological lymphadenopathy on sonographic examination and upper and middle zone localization were other sonographic features that increased the risk of malignancy of a nodule. The presence of autoimmunity was not found to be associated with the risk of malignancy. TSH and calcitonin levels of malignant nodules were higher than benign nodules. There was no significant difference between gender and malignancy. In the univariate analysis, it was found that the presence of macrocalcification increased the risk of malignancy 2.935 times. (OR:2.935, p < 0.001.95% CI for OR 1.611-5.349) In addition, being younger, being in the high TIRADS category, and being in the upper and middle zones were factors that increased the risk of malignancy. Gender, TSH level, nodule volume and structure were not associated with malignancy. However, after multivariate analysis, factors that significantly increased the risk of malignancy were younger age, higher TIRADS category, and nodule localization. CONCLUSION In our study, the malignancy rate was higher in the macrocalcification group than in the control group. However, no correlation was found after multivariate analysis. In the multivariate analysis, younger age, higher TIRADS category, and nodules located in the upper and middle zone were other factors associated with malignancy. There was no association between peripheral interrupted calcification and malignancy risk.
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Affiliation(s)
- Fatma Tuğçe Şah Ünal
- Ankara University Faculty of Medicine, Department of Endocrinology and Metabolism, Ankara, Turkey.
| | - Asena Gökçay Canpolat
- Ankara University Faculty of Medicine, Department of Endocrinology and Metabolism, Ankara, Turkey
| | - Atilla Halil Elhan
- Ankara University Faculty of Medicine, Department of Biostatistics, Ankara, Turkey
| | - Selim Sevim
- Ankara University Faculty of Medicine, Department of Pathology, Ankara, Turkey
| | - Serpil Dizbay Sak
- Ankara University Faculty of Medicine, Department of Pathology, Ankara, Turkey
| | - Rıfat Emral
- Ankara University Faculty of Medicine, Department of Endocrinology and Metabolism, Ankara, Turkey
| | - Özgür Demir
- Ankara University Faculty of Medicine, Department of Endocrinology and Metabolism, Ankara, Turkey
| | - Sevim Güllü
- Ankara University Faculty of Medicine, Department of Endocrinology and Metabolism, Ankara, Turkey
| | - Murat Faik Erdoğan
- Ankara University Faculty of Medicine, Department of Endocrinology and Metabolism, Ankara, Turkey
| | - Demet Çorapçıoğlu
- Ankara University Faculty of Medicine, Department of Endocrinology and Metabolism, Ankara, Turkey
| | - Mustafa Şahin
- Ankara University Faculty of Medicine, Department of Endocrinology and Metabolism, Ankara, Turkey
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Trimboli P, Curti M, Colombo A, Scappaticcio L, Leoncini A. Combining TSH measurement with TIRADS assessment to further improve the detection of thyroid cancers. Minerva Endocrinol (Torino) 2024; 49:125-131. [PMID: 39028208 DOI: 10.23736/s2724-6507.24.04207-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/20/2024]
Abstract
BACKGROUND Thyroid Imaging Reporting and Data Systems (TIRADSs) have demonstrated high performance in risk stratification of thyroid nodules (TNs). However, further improvements are needed in view of the ongoing project of an international TIRADS. Even if thyroid-stimulating hormone (TSH) measurement is traditionally used to assess the thyroid function, several papers have reported that higher TSH levels are associated with the presence of differentiated thyroid carcinoma (DTC). The present study aimed to investigate the role of TSH levels as improvement factor of American College of Radiology (ACR-), European Thyroid Association (EU-), and Korean Society (K-)TIRADS. METHODS Patients undergoing thyroidectomy were reviewed and TNs were re-assessed according to TIRADSs. Different TSH subgroups were attained. Histology was the reference standard. DTC risk of relapse was assessed according to American Thyroid Association guidelines. RESULTS The study series included 97 patients with 39.2% cancer prevalence. ACR-, EU-, and K-TIRADS indicated fine-needle aspiration cytology (FNAC) in 78.9%, 81.6%, and 92.1% of cases, respectively. All high-risk DTC had FNAC indication according to the three TIRADSs. The cancer rate was significantly lower in patients with TSH<0.4 mIU/L (P=0.04). The receiver operating characteristic (ROC) curve analysis showed that the best TSH cut-off to detect DTC patient was >1.3 mIU/L with Area Under the Curve (AUC)=0.70. Combining TSH data with TIRADS, the sensitivity of ACR-, EU-, and K-TIRADS increased to 92.1% 89.5%, and 94.7%, respectively. Conversely, the rate of unnecessary FNAC raised. At multivariate analysis, gender, TSH, and TIRADS were independent predictors of cancer. CONCLUSIONS Even if TIRADSs are strongly reliable to stratify the risk of malignancy of TNs, measuring TSH can further improve our sensitivity in detecting DTC.
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Affiliation(s)
- Pierpaolo Trimboli
- Service of Endocrinology and Diabetology, EOC Ospedale Regionale di Lugano, Lugano, Switzerland -
- Faculty of Biomedical Sciences, Università della Svizzera Italiana (USI), Lugano, Switzerland -
| | - Marco Curti
- Service of Radiology and Interventional Radiology, Istituto di Imaging della Svizzera Italiana (IIMSI), Ente Ospedaliero Cantonale (EOC), Lugano, Switzerland
| | - Amos Colombo
- Unit of Clinical Trial, Ente Ospedaliero Cantonale (EOC), Bellinzona, Switzerland
- Unit of Team Innovation and Research, ICT Area, Ente Ospedaliero Cantonale (EOC), Bellinzona, Switzerland
| | - Lorenzo Scappaticcio
- Unit of Team Innovation and Research, ICT Area, Ente Ospedaliero Cantonale (EOC), Bellinzona, Switzerland
- Unit of Endocrinology and Metabolic Diseases, Luigi Vanvitelli University of Campania, Naples, Italy
| | - Andrea Leoncini
- Service of Radiology and Interventional Radiology, Istituto di Imaging della Svizzera Italiana (IIMSI), Ente Ospedaliero Cantonale (EOC), Lugano, Switzerland
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Li J, Li S, Zhou W, Duan Y, Zheng H. Enhancing malignancy prediction in thyroid nodules: A multimodal ultrasound radiomics approach in TI-RADS category 4 lesions. JOURNAL OF CLINICAL ULTRASOUND : JCU 2024; 52:511-521. [PMID: 38465504 DOI: 10.1002/jcu.23662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 01/03/2024] [Accepted: 02/12/2024] [Indexed: 03/12/2024]
Abstract
PURPOSE To explore the diagnostic value of intralesional and perilesional radiomics based on multimodal ultrasound (US) images in predicting the malignant ACR TIRADS 4 thyroid nodules (TNs). METHODS A total of 297 cases of TNs in patients who underwent preoperative thyroid grayscale US and shear wave elastography (STE) were enrolled (training cohort: n = 150, internal validation cohort: n = 77, external validation cohort: n = 70). Regions of interests (ROIs) were delineated on grayscale US images and STE images, and then an isotropic expansion of 1.0, 1.5, 2.0, 2.5, and 3.0 mm was applied. Predictive models were established using recursive feature elimination-support vector machines (RFE-SVM) based on radiomics features calculated by random forest. RESULTS The perilesional ROI1.5mm expansion achieved the highest area under curve (AUC) (AUC: 0.753 for grayscale US, 0.728 for STE; 95% confidence interval (CI): 0.664-0.743, 0.684-0.739, respectively). The joint model had the highest AUC values of 0.936 in the training dataset, 0.926 in internal dataset, and 0.893 in external dataset. The calibration curve showed good consistency and the decision curve indicated a greater clinical net benefit of the joint model. CONCLUSION Joint model containing perilesional radiomics (1.5 mm) had significant value in predicting the malignant ACR TIRADS 4 TNs.
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Affiliation(s)
- Jian Li
- Department of Ultrasound, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China
| | - Siyao Li
- Department of Ultrasound Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, China
- Department of Ultrasound, The Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, Shandong Province, China
| | - Wang Zhou
- Department of Ultrasound, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China
| | - Yayang Duan
- Department of Ultrasound, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China
| | - Hui Zheng
- Department of Ultrasound, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China
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Loor-Torres R, Duran M, Toro-Tobon D, Chavez MM, Ponce O, Jacome CS, Torres DS, Perneth SA, Montori V, Golembiewski E, Osorio MB, Fan JW, Ospina NS, Wu Y, Brito JP. A Systematic Review of Natural Language Processing Methods and Applications in Thyroidology. MAYO CLINIC PROCEEDINGS. DIGITAL HEALTH 2024; 2:270-279. [PMID: 38938930 PMCID: PMC11210322 DOI: 10.1016/j.mcpdig.2024.03.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/29/2024]
Abstract
This study aimed to review the application of natural language processing (NLP) in thyroid-related conditions and to summarize current challenges and potential future directions. We performed a systematic search of databases for studies describing NLP applications in thyroid conditions published in English between January 1, 2012 and November 4, 2022. In addition, we used a snowballing technique to identify studies missed in the initial search or published after our search timeline until April 1, 2023. For included studies, we extracted the NLP method (eg, rule-based, machine learning, deep learning, or hybrid), NLP application (eg, identification, classification, and automation), thyroid condition (eg, thyroid cancer, thyroid nodule, and functional or autoimmune disease), data source (eg, electronic health records, health forums, medical literature databases, or genomic databases), performance metrics, and stages of development. We identified 24 eligible NLP studies focusing on thyroid-related conditions. Deep learning-based methods were the most common (38%), followed by rule-based (21%), and traditional machine learning (21%) methods. Thyroid nodules (54%) and thyroid cancer (29%) were the primary conditions under investigation. Electronic health records were the dominant data source (17/24, 71%), with imaging reports being the most frequently used (15/17, 88%). There is increasing interest in NLP applications for thyroid-related studies, mostly addressing thyroid nodules and using deep learning-based methodologies with limited external validation. However, none of the reviewed NLP applications have reached clinical practice. Several limitations, including inconsistent clinical documentation and model portability, need to be addressed to promote the evaluation and implementation of NLP applications to support patient care in thyroidology.
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Affiliation(s)
- Ricardo Loor-Torres
- Knowledge and Evaluation Research Unit (R.L.-T., M.D., M.M.C., C.S.., D.S.T., S.A.P., V.M., E.G., M.B.O., J.P.B.), Division of Endocrinology, Diabetes, Metabolism, and Nutrition (D.T.-T., J.P.B.), Department of Medicine, and Department of Artificial Intelligence and Informatics (N.S.O.), Mayo Clinic, Rochester, MN; University of Edinburgh, Edinburgh, Scotland, United Kingdom (D.S.T.); Montefiore Health Center, Albert Einstein College of Medicine, New York, NY (J.W.F.); Division of Endocrinology, Department of Medicine (N.S.O.), and Department of Health Outcomes and Biomedical Informatics (Y.W.), University of Florida, Gainesville, FL; and Respiratory, Cardiovascular, and Renal Pathobiology and Bioengineering, Universitat de Barcelona, Spain (D.S.T.)
| | - Mayra Duran
- Knowledge and Evaluation Research Unit (R.L.-T., M.D., M.M.C., C.S.., D.S.T., S.A.P., V.M., E.G., M.B.O., J.P.B.), Division of Endocrinology, Diabetes, Metabolism, and Nutrition (D.T.-T., J.P.B.), Department of Medicine, and Department of Artificial Intelligence and Informatics (N.S.O.), Mayo Clinic, Rochester, MN; University of Edinburgh, Edinburgh, Scotland, United Kingdom (D.S.T.); Montefiore Health Center, Albert Einstein College of Medicine, New York, NY (J.W.F.); Division of Endocrinology, Department of Medicine (N.S.O.), and Department of Health Outcomes and Biomedical Informatics (Y.W.), University of Florida, Gainesville, FL; and Respiratory, Cardiovascular, and Renal Pathobiology and Bioengineering, Universitat de Barcelona, Spain (D.S.T.)
| | - David Toro-Tobon
- Knowledge and Evaluation Research Unit (R.L.-T., M.D., M.M.C., C.S.., D.S.T., S.A.P., V.M., E.G., M.B.O., J.P.B.), Division of Endocrinology, Diabetes, Metabolism, and Nutrition (D.T.-T., J.P.B.), Department of Medicine, and Department of Artificial Intelligence and Informatics (N.S.O.), Mayo Clinic, Rochester, MN; University of Edinburgh, Edinburgh, Scotland, United Kingdom (D.S.T.); Montefiore Health Center, Albert Einstein College of Medicine, New York, NY (J.W.F.); Division of Endocrinology, Department of Medicine (N.S.O.), and Department of Health Outcomes and Biomedical Informatics (Y.W.), University of Florida, Gainesville, FL; and Respiratory, Cardiovascular, and Renal Pathobiology and Bioengineering, Universitat de Barcelona, Spain (D.S.T.)
| | - Maria Mateo Chavez
- Knowledge and Evaluation Research Unit (R.L.-T., M.D., M.M.C., C.S.., D.S.T., S.A.P., V.M., E.G., M.B.O., J.P.B.), Division of Endocrinology, Diabetes, Metabolism, and Nutrition (D.T.-T., J.P.B.), Department of Medicine, and Department of Artificial Intelligence and Informatics (N.S.O.), Mayo Clinic, Rochester, MN; University of Edinburgh, Edinburgh, Scotland, United Kingdom (D.S.T.); Montefiore Health Center, Albert Einstein College of Medicine, New York, NY (J.W.F.); Division of Endocrinology, Department of Medicine (N.S.O.), and Department of Health Outcomes and Biomedical Informatics (Y.W.), University of Florida, Gainesville, FL; and Respiratory, Cardiovascular, and Renal Pathobiology and Bioengineering, Universitat de Barcelona, Spain (D.S.T.)
| | - Oscar Ponce
- Knowledge and Evaluation Research Unit (R.L.-T., M.D., M.M.C., C.S.., D.S.T., S.A.P., V.M., E.G., M.B.O., J.P.B.), Division of Endocrinology, Diabetes, Metabolism, and Nutrition (D.T.-T., J.P.B.), Department of Medicine, and Department of Artificial Intelligence and Informatics (N.S.O.), Mayo Clinic, Rochester, MN; University of Edinburgh, Edinburgh, Scotland, United Kingdom (D.S.T.); Montefiore Health Center, Albert Einstein College of Medicine, New York, NY (J.W.F.); Division of Endocrinology, Department of Medicine (N.S.O.), and Department of Health Outcomes and Biomedical Informatics (Y.W.), University of Florida, Gainesville, FL; and Respiratory, Cardiovascular, and Renal Pathobiology and Bioengineering, Universitat de Barcelona, Spain (D.S.T.)
| | - Cristian Soto Jacome
- Knowledge and Evaluation Research Unit (R.L.-T., M.D., M.M.C., C.S.., D.S.T., S.A.P., V.M., E.G., M.B.O., J.P.B.), Division of Endocrinology, Diabetes, Metabolism, and Nutrition (D.T.-T., J.P.B.), Department of Medicine, and Department of Artificial Intelligence and Informatics (N.S.O.), Mayo Clinic, Rochester, MN; University of Edinburgh, Edinburgh, Scotland, United Kingdom (D.S.T.); Montefiore Health Center, Albert Einstein College of Medicine, New York, NY (J.W.F.); Division of Endocrinology, Department of Medicine (N.S.O.), and Department of Health Outcomes and Biomedical Informatics (Y.W.), University of Florida, Gainesville, FL; and Respiratory, Cardiovascular, and Renal Pathobiology and Bioengineering, Universitat de Barcelona, Spain (D.S.T.)
| | - Danny Segura Torres
- Knowledge and Evaluation Research Unit (R.L.-T., M.D., M.M.C., C.S.., D.S.T., S.A.P., V.M., E.G., M.B.O., J.P.B.), Division of Endocrinology, Diabetes, Metabolism, and Nutrition (D.T.-T., J.P.B.), Department of Medicine, and Department of Artificial Intelligence and Informatics (N.S.O.), Mayo Clinic, Rochester, MN; University of Edinburgh, Edinburgh, Scotland, United Kingdom (D.S.T.); Montefiore Health Center, Albert Einstein College of Medicine, New York, NY (J.W.F.); Division of Endocrinology, Department of Medicine (N.S.O.), and Department of Health Outcomes and Biomedical Informatics (Y.W.), University of Florida, Gainesville, FL; and Respiratory, Cardiovascular, and Renal Pathobiology and Bioengineering, Universitat de Barcelona, Spain (D.S.T.)
| | - Sandra Algarin Perneth
- Knowledge and Evaluation Research Unit (R.L.-T., M.D., M.M.C., C.S.., D.S.T., S.A.P., V.M., E.G., M.B.O., J.P.B.), Division of Endocrinology, Diabetes, Metabolism, and Nutrition (D.T.-T., J.P.B.), Department of Medicine, and Department of Artificial Intelligence and Informatics (N.S.O.), Mayo Clinic, Rochester, MN; University of Edinburgh, Edinburgh, Scotland, United Kingdom (D.S.T.); Montefiore Health Center, Albert Einstein College of Medicine, New York, NY (J.W.F.); Division of Endocrinology, Department of Medicine (N.S.O.), and Department of Health Outcomes and Biomedical Informatics (Y.W.), University of Florida, Gainesville, FL; and Respiratory, Cardiovascular, and Renal Pathobiology and Bioengineering, Universitat de Barcelona, Spain (D.S.T.)
| | - Victor Montori
- Knowledge and Evaluation Research Unit (R.L.-T., M.D., M.M.C., C.S.., D.S.T., S.A.P., V.M., E.G., M.B.O., J.P.B.), Division of Endocrinology, Diabetes, Metabolism, and Nutrition (D.T.-T., J.P.B.), Department of Medicine, and Department of Artificial Intelligence and Informatics (N.S.O.), Mayo Clinic, Rochester, MN; University of Edinburgh, Edinburgh, Scotland, United Kingdom (D.S.T.); Montefiore Health Center, Albert Einstein College of Medicine, New York, NY (J.W.F.); Division of Endocrinology, Department of Medicine (N.S.O.), and Department of Health Outcomes and Biomedical Informatics (Y.W.), University of Florida, Gainesville, FL; and Respiratory, Cardiovascular, and Renal Pathobiology and Bioengineering, Universitat de Barcelona, Spain (D.S.T.)
| | - Elizabeth Golembiewski
- Knowledge and Evaluation Research Unit (R.L.-T., M.D., M.M.C., C.S.., D.S.T., S.A.P., V.M., E.G., M.B.O., J.P.B.), Division of Endocrinology, Diabetes, Metabolism, and Nutrition (D.T.-T., J.P.B.), Department of Medicine, and Department of Artificial Intelligence and Informatics (N.S.O.), Mayo Clinic, Rochester, MN; University of Edinburgh, Edinburgh, Scotland, United Kingdom (D.S.T.); Montefiore Health Center, Albert Einstein College of Medicine, New York, NY (J.W.F.); Division of Endocrinology, Department of Medicine (N.S.O.), and Department of Health Outcomes and Biomedical Informatics (Y.W.), University of Florida, Gainesville, FL; and Respiratory, Cardiovascular, and Renal Pathobiology and Bioengineering, Universitat de Barcelona, Spain (D.S.T.)
| | - Mariana Borras Osorio
- Knowledge and Evaluation Research Unit (R.L.-T., M.D., M.M.C., C.S.., D.S.T., S.A.P., V.M., E.G., M.B.O., J.P.B.), Division of Endocrinology, Diabetes, Metabolism, and Nutrition (D.T.-T., J.P.B.), Department of Medicine, and Department of Artificial Intelligence and Informatics (N.S.O.), Mayo Clinic, Rochester, MN; University of Edinburgh, Edinburgh, Scotland, United Kingdom (D.S.T.); Montefiore Health Center, Albert Einstein College of Medicine, New York, NY (J.W.F.); Division of Endocrinology, Department of Medicine (N.S.O.), and Department of Health Outcomes and Biomedical Informatics (Y.W.), University of Florida, Gainesville, FL; and Respiratory, Cardiovascular, and Renal Pathobiology and Bioengineering, Universitat de Barcelona, Spain (D.S.T.)
| | - Jungwei W Fan
- Knowledge and Evaluation Research Unit (R.L.-T., M.D., M.M.C., C.S.., D.S.T., S.A.P., V.M., E.G., M.B.O., J.P.B.), Division of Endocrinology, Diabetes, Metabolism, and Nutrition (D.T.-T., J.P.B.), Department of Medicine, and Department of Artificial Intelligence and Informatics (N.S.O.), Mayo Clinic, Rochester, MN; University of Edinburgh, Edinburgh, Scotland, United Kingdom (D.S.T.); Montefiore Health Center, Albert Einstein College of Medicine, New York, NY (J.W.F.); Division of Endocrinology, Department of Medicine (N.S.O.), and Department of Health Outcomes and Biomedical Informatics (Y.W.), University of Florida, Gainesville, FL; and Respiratory, Cardiovascular, and Renal Pathobiology and Bioengineering, Universitat de Barcelona, Spain (D.S.T.)
| | - Naykky Singh Ospina
- Knowledge and Evaluation Research Unit (R.L.-T., M.D., M.M.C., C.S.., D.S.T., S.A.P., V.M., E.G., M.B.O., J.P.B.), Division of Endocrinology, Diabetes, Metabolism, and Nutrition (D.T.-T., J.P.B.), Department of Medicine, and Department of Artificial Intelligence and Informatics (N.S.O.), Mayo Clinic, Rochester, MN; University of Edinburgh, Edinburgh, Scotland, United Kingdom (D.S.T.); Montefiore Health Center, Albert Einstein College of Medicine, New York, NY (J.W.F.); Division of Endocrinology, Department of Medicine (N.S.O.), and Department of Health Outcomes and Biomedical Informatics (Y.W.), University of Florida, Gainesville, FL; and Respiratory, Cardiovascular, and Renal Pathobiology and Bioengineering, Universitat de Barcelona, Spain (D.S.T.)
| | - Yonghui Wu
- Knowledge and Evaluation Research Unit (R.L.-T., M.D., M.M.C., C.S.., D.S.T., S.A.P., V.M., E.G., M.B.O., J.P.B.), Division of Endocrinology, Diabetes, Metabolism, and Nutrition (D.T.-T., J.P.B.), Department of Medicine, and Department of Artificial Intelligence and Informatics (N.S.O.), Mayo Clinic, Rochester, MN; University of Edinburgh, Edinburgh, Scotland, United Kingdom (D.S.T.); Montefiore Health Center, Albert Einstein College of Medicine, New York, NY (J.W.F.); Division of Endocrinology, Department of Medicine (N.S.O.), and Department of Health Outcomes and Biomedical Informatics (Y.W.), University of Florida, Gainesville, FL; and Respiratory, Cardiovascular, and Renal Pathobiology and Bioengineering, Universitat de Barcelona, Spain (D.S.T.)
| | - Juan P Brito
- Knowledge and Evaluation Research Unit (R.L.-T., M.D., M.M.C., C.S.., D.S.T., S.A.P., V.M., E.G., M.B.O., J.P.B.), Division of Endocrinology, Diabetes, Metabolism, and Nutrition (D.T.-T., J.P.B.), Department of Medicine, and Department of Artificial Intelligence and Informatics (N.S.O.), Mayo Clinic, Rochester, MN; University of Edinburgh, Edinburgh, Scotland, United Kingdom (D.S.T.); Montefiore Health Center, Albert Einstein College of Medicine, New York, NY (J.W.F.); Division of Endocrinology, Department of Medicine (N.S.O.), and Department of Health Outcomes and Biomedical Informatics (Y.W.), University of Florida, Gainesville, FL; and Respiratory, Cardiovascular, and Renal Pathobiology and Bioengineering, Universitat de Barcelona, Spain (D.S.T.)
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Ren T, Lavender I, Coombs P, Nandurkar D. Sonographic risk stratification of FDG-avid thyroid nodules using the Thyroid Imaging Reporting and Data System. J Med Imaging Radiat Oncol 2024. [PMID: 38803292 DOI: 10.1111/1754-9485.13712] [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: 09/30/2023] [Accepted: 05/15/2024] [Indexed: 05/29/2024]
Abstract
INTRODUCTION The increasing usage of positron emission tomography/computed tomography (PET/CT) for detection and monitoring of malignancy has led to an increase in incidental detection of thyroid nodules. Nodules that demonstrate increased avidity for 2-[18F]-fluoro-2-deoxy-d-glucose (FDG) have been shown to carry a high incidence of malignancy and warrant further investigation. At present, there has been limited research on the risk stratification of FDG-avid thyroid incidentalomas. Thus, this study aims to evaluate the efficacy of the ACR TIRADS classification in the risk stratification of such nodules. METHODS Data were collected retrospectively for FDG-avid thyroid incidentalomas over a 10-year period. Nodules were characterised using the TIRADS classification and, subsequently, underwent fine-needle aspirate cytology. Cytological findings were classified using the Bethesda reporting system. Non-diagnostic samples (Bethesda class I) were excluded. The remaining samples were divided into two groups: benign (Bethesda class II) or suspicious for malignancy/malignant (Bethesda class III or above). RESULTS Thirty-six percent of low-risk nodules and 45% of high-risk nodules were malignant, respectively (P = 0.516). The sensitivity and specificity of TIRADS for detection of malignant nodules were 56% and 54%, respectively. There were no malignant TIRADS 1 or 2 nodules. The absence of any suspicious sonographic features had a 1.0 negative predictive value. CONCLUSIONS FDG-avid nodules classified as TIRADS 1 or 2 or have no suspicious ultrasound features have a 0% incidence of malignancy and thus may not require further assessment with fine-needle aspirate cytology (FNA) when detected incidentally. FDG-avid nodules that are TIRADS 3 or above should undergo FNA regardless of size due to the high risk of malignancy and poor sensitivity of the TIRADS classification system.
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Affiliation(s)
- Tianchi Ren
- Department of Diagnostic Imaging, Monash Health, Melbourne, Victoria, Australia
| | - Ilona Lavender
- Department of Diagnostic Imaging, Monash Health, Melbourne, Victoria, Australia
| | - Peter Coombs
- Department of Diagnostic Imaging, Monash Health, Melbourne, Victoria, Australia
| | - Dee Nandurkar
- Department of Diagnostic Imaging, Monash Health, Melbourne, Victoria, Australia
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Latia M, Borlea A, Mihuta MS, Neagoe OC, Stoian D. Impact of ultrasound elastography in evaluating Bethesda category IV thyroid nodules with histopathological correlation. Front Endocrinol (Lausanne) 2024; 15:1393982. [PMID: 38863927 PMCID: PMC11165070 DOI: 10.3389/fendo.2024.1393982] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Accepted: 05/10/2024] [Indexed: 06/13/2024] Open
Abstract
Introduction Fine needle aspiration (FNA) is the gold standard method recommended in the diagnosis of thyroid nodules. Bethesda IV cytology results are identified in 7-9% of nodules investigated through FNA, with reported malignancy rate in a wide range of 10-40%. The recommended treatment is either surgical or risk additional molecular testing before surgery. However, a large number of nodules belonging to this category (60-80%) are observed to be benign after surgical excision, which can put the patient at risk of unnecessary surgical morbidity. This study aimed to assess the diagnostic performance of conventional ultrasound, the ACR TI-RADS score and elastography in cases of Bethesda IV cytology on FNA. Methods We evaluated ninety-seven consecutive cases with Bethesda category IV results on FNA by using conventional B-mode ultrasound, qualitative strain or shear-wave elastography (Hitachi Preirus Machine, Hitachi Inc., Japan and Aixplorer Mach 30 Supersonic Imagine, Aix-en-Provence, France) and all nodules were classified according to the ACR TI-RADS system. Conventional ultrasound was used to categorize the nodules as potentially malignant based on the following features: hypoechogenicity, inhomogeneity, a taller than wide shape, irregular margins, presence of microcalcifications, an interrupted thyroid capsule and suspicious cervical lymph nodes. Elastography classified nodules with increased stiffness as suspicious for malignancy. Results We considered pathology results as the gold standard diagnosis, finding that 32 out of 97 nodules were carcinomas (33%) and 65 out of 97 were benign nodules (67%). The benign group included twenty cases of non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP). Finally, we compared ultrasound data with pathology results, which showed that nineteen out of the 32 malignant nodules presented with increased stiffness on elastography (p=0.0002). On conventional ultrasound, we found that microcalcifications (p=0.007), hypoechogenicity and irregular margins (p=0.006) are features which can distinguish between benign and malignant nodules with statistical significance. Discussion Integrating elastography as a parameter of the ACR TI-RADS score in the evaluation of Bethesda category IV nodules showed a sensitivity of 90.62% in detecting thyroid cancer cases (p=0.006). We can conclude that elastographic stiffness as an addition to high risk features observed on conventional ultrasound improves the detection of malignant nodules in cases with Bethesda IV cytology.
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Affiliation(s)
- Monica Latia
- Department of Doctoral Studies, Victor Babes University of Medicine and Pharmacy, Timisoara, Romania
- Dr. D Medical Center, Center for Advanced Ultrasound Evaluation, Timisoara, Romania
| | - Andreea Borlea
- Dr. D Medical Center, Center for Advanced Ultrasound Evaluation, Timisoara, Romania
- Center of Molecular Research in Nephrology and Vascular Disease, Faculty of Medicine, Victor Babes University of Medicine and Pharmacy, Timisoara, Romania
- 2 Department of Internal Medicine, Victor Babes University of Medicine and Pharmacy, Timisoara, Romania
| | - Monica Simina Mihuta
- Dr. D Medical Center, Center for Advanced Ultrasound Evaluation, Timisoara, Romania
- Center of Molecular Research in Nephrology and Vascular Disease, Faculty of Medicine, Victor Babes University of Medicine and Pharmacy, Timisoara, Romania
| | - Octavian Constantin Neagoe
- Dr. D Medical Center, Center for Advanced Ultrasound Evaluation, Timisoara, Romania
- 1 Department of Surgery, Victor Babes University of Medicine and Pharmacy, Timisoara, Romania
- Second Clinic of General Surgery and Surgical Oncology, Emergency Clinical Municipal Hospital, Timisoara, Romania
| | - Dana Stoian
- Dr. D Medical Center, Center for Advanced Ultrasound Evaluation, Timisoara, Romania
- Center of Molecular Research in Nephrology and Vascular Disease, Faculty of Medicine, Victor Babes University of Medicine and Pharmacy, Timisoara, Romania
- 2 Department of Internal Medicine, Victor Babes University of Medicine and Pharmacy, Timisoara, Romania
- Endocrinology Unit, Pius Brinzeu Emergency Clinical Hospital, Timisoara, Romania
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90
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Liu T, Yang F, Qiao J, Mao M. Deciphering the progression of fine-needle aspiration: A bibliometric analysis of thyroid nodule research. Medicine (Baltimore) 2024; 103:e38059. [PMID: 38758913 PMCID: PMC11098219 DOI: 10.1097/md.0000000000038059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Accepted: 04/08/2024] [Indexed: 05/19/2024] Open
Abstract
This study aims to dissect the evolution and pivotal shifts in Fine-Needle Aspiration (FNA) research for thyroid nodules over the past 2 decades, focusing on delineating key technological advancements and their impact on clinical practice. A comprehensive bibliometric analysis was conducted on 5418 publications from the Web of Science Core Collection database (2000-2023). Publications were rigorously selected based on their contributions to the advancement of FNA techniques and their influence on thyroid nodule management practices. Our analysis uncovered significant breakthroughs, most notably the incorporation of ultrasound and molecular diagnostics in FNA, which have markedly elevated diagnostic accuracy. A pivotal shift was identified towards minimally invasive post-FNA treatments, such as Radiofrequency Ablation, attributable to these diagnostic advancements. Additionally, the emergence of AI-assisted cytology represents a frontier in precision diagnostics, promising enhanced disease identification. The geographical analysis pinpointed the United States, Italy, and China as key contributors, with the United States leading in both publication volume and citation impact. This bibliometric analysis sheds light on the transformative progression in FNA practices for thyroid nodules, characterized by innovative diagnostic technologies and a trend towards patient-centric treatment approaches. The findings underscore the need for further research into AI integration and global practice standardization. Future explorations should focus on the practical application of these advancements in diverse healthcare settings and their implications for global thyroid nodule management.
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Affiliation(s)
- Tengfei Liu
- Department of Head and Neck Thyroid Surgery, Xingtai People’s Hospital of Hebei Medical University, Xingtai, P.R. China
| | - Fei Yang
- Department of Otorhinolaryngology – Head and Neck Surgery, The Fourth Hospital of Hebei Medical University, Shijiazhuang, P.R. China
| | - Junli Qiao
- Department of Head and Neck Thyroid Surgery, Xingtai People’s Hospital of Hebei Medical University, Xingtai, P.R. China
| | - Mengxuan Mao
- Department of Head and Neck Thyroid Surgery, Xingtai People’s Hospital of Hebei Medical University, Xingtai, P.R. China
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91
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Kinet S, van Weezelenburg MAS, Pijnenburg A, Stoot JHMB, van Bastelaar J. Feasibility and complications after transoral endoscopic thyroidectomy via vestibular approach (TOETVA) - a single-center first experience case series. Langenbecks Arch Surg 2024; 409:158. [PMID: 38748236 DOI: 10.1007/s00423-024-03347-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 05/06/2024] [Indexed: 05/18/2024]
Abstract
BACKGROUND This paper reports on the first experience after implementation of a transoral endoscopic thyroidectomy via vestibular approach (TOETVA) as an alternative to (partial) thyroidectomy or isthmusectomy in a single center. Feasibility, implementation and specific complications are addressed. METHODS All patients who underwent a TOETVA procedure in our center between November 2019 and March 2023 were included. The surgical technique was performed as described by Anuwong et al. All procedures were performed by two dedicated head- and neck surgeons. RESULTS A total of 20 patients were included. All patients underwent TOETVA surgery as planned and no conversions were needed. Observed complications were post-operative wound infections (POWI) (2/20; 10%), clinically significant seroma (1/20, 5%) and unilateral hemiparesis of the larynx (3/20; 15%). Permanent mental nerve damage was seen in 3/20 patients (15%), and 4 other patients (20%) experienced transient neuropraxia. CONCLUSIONS TOETVA is a feasible alternative to (partial) thyroidectomy or isthmusectomy in selected patients. Special care should be taken when placing the trocars in the oral vestibulum to prevent mental nerve damage. Experience and training are essential for implementing the TOETVA procedure. TRIAL REGISTRATION This study was registered to ClinicalTrials.gov. TRIAL REGISTRATION NUMBER NCT05396703.
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Affiliation(s)
- Sam Kinet
- Faculty of Medicine, KU Leuven, Herestraat 49, Leuven, 3000, Belgium.
| | | | - A Pijnenburg
- Department of Surgery, Zuyderland Medical Centre, Dr. H. van der Hoffplein 1, Sittard-Geleen, 6162 BG, The Netherlands
| | - J H M B Stoot
- Department of Surgery, Zuyderland Medical Centre, Dr. H. van der Hoffplein 1, Sittard-Geleen, 6162 BG, The Netherlands
| | - J van Bastelaar
- Department of Surgery, Zuyderland Medical Centre, Dr. H. van der Hoffplein 1, Sittard-Geleen, 6162 BG, The Netherlands
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92
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Chakrabarty N, Mahajan A, Basu S, D’Cruz AK. Comprehensive Review of the Imaging Recommendations for Diagnosis, Staging, and Management of Thyroid Carcinoma. J Clin Med 2024; 13:2904. [PMID: 38792444 PMCID: PMC11122658 DOI: 10.3390/jcm13102904] [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: 04/18/2024] [Revised: 05/01/2024] [Accepted: 05/08/2024] [Indexed: 05/26/2024] Open
Abstract
Thyroid cancer is the most common head and neck cancer (HNC) in the world. In this article, we comprehensively cover baseline, posttreatment, and follow-up imaging recommendations for thyroid carcinomas along with the eighth edition of the tumor, node, metastasis (TNM) staging system proposed by the American Joint Committee on Cancer (AJCC) and the Union for International Cancer Control (UICC). We include characterization and risk stratification of thyroid nodules on ultrasound (US) proposed by various international bodies. Management guidelines (depending upon the type of thyroid carcinoma) based on the international consensus recommendations (mainly by the American Thyroid Association) are also extensively covered in this article, including the role of a radioiodine scan. The management of recurrent disease is also briefly elucidated in this article. In addition, we cover the risk factors and etiopathogenesis of thyroid carcinoma along with the non-imaging diagnostic workup essential for thyroid carcinoma management, including the significance of genetic mutations. US is the diagnostic imaging modality of choice, with US-guided fine needle aspiration (FNA) being the procedure of choice for tissue diagnosis. The roles of computed tomography (CT), magnetic resonance imaging (MRI), and fluorodeoxyglucose positron emission tomography/CT (FDG-PET/CT) in thyroid carcinoma staging are also specified. Through this article, we aim to provide a comprehensive reference guide for the radiologists and the clinicians in the pursuit of optimal care for patients with thyroid carcinoma.
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Affiliation(s)
- Nivedita Chakrabarty
- Department of Radiodiagnosis, Advanced Centre for Treatment, Research and Education in Cancer (ACTREC), Tata Memorial Centre, Homi Bhabha National Institute (HBNI), Parel, Mumbai 400012, Maharashtra, India;
| | - Abhishek Mahajan
- Department of Imaging, The Clatterbridge Cancer Centre NHS Foundation Trust, 65 Pembroke Place, Liverpool L7 8YA, UK
- Faculty of Health and Life Sciences, University of Liverpool, Liverpool L69 3BX, UK
| | - Sandip Basu
- Radiation Medicine Centre, Bhabha Atomic Research Centre, Tata Memorial Hospital Annexe, Homi Bhabha National Institute (HBNI), Parel, Mumbai 400012, Maharashtra, India;
| | - Anil K. D’Cruz
- Apollo Hospitals, Navi Mumbai 400614, Maharashtra, India;
- Foundation of Head Neck Oncology, Mumbai 400012, Maharashtra, India
- Union International Cancer Control (UICC), 1202 Geneva, Switzerland
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93
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Cao SL, Shi WY, Niu YR, Zhao ZL, Wei Y, Wu J, Peng LL, Li Y, Yu MA. Influence of maximum diameter on fine-needle aspiration biopsy outcomes in ACR TI-RADS 5 thyroid nodules. Front Endocrinol (Lausanne) 2024; 15:1374888. [PMID: 38808118 PMCID: PMC11130351 DOI: 10.3389/fendo.2024.1374888] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Accepted: 04/22/2024] [Indexed: 05/30/2024] Open
Abstract
Introduction Fine needle aspiration (FNA) biopsy is a widely accepted method for diagnosing thyroid nodules. However, the influence of maximum diameter (MD) of ACR TIRADS 5 (TR5) thyroid nodules on the FNA outcomes remains debated. This study examined the influence of MD on the FNA outcomes and investigated the optimal MD threshold for FNA in TR5 nodules. Methods We conducted a retrospective analysis of 280 TR5 thyroid nodules from 226 patients who underwent FNA from January to June 2022 in our department. Probably malignant (PM) group was defined as Bethesda V in cytopathology with confirmed BRAF V600E mutation or Bethesda VI, the other cytopathology outcomes were defined as probably benign (PB) group. We examined factors influencing malignant cytopathology outcomes and determined the optimal MD threshold for FNA in TR5 nodules using logistic regression and restricted cubic spline (RCS) analysis. Results Among these nodules, 58.2% (163/280) had PM outcomes. The PM group had a significantly larger MD than the PB group [6.5mm (range 5.0-8.4) vs. 5.3mm (range 4.0-7.0), p < 0.001]. In multivariate logistic regression fully adjusted for confounders, MD was significantly associated with PM outcomes [odds ratio 1.16, 95%CI 1.05-1.31; p = 0.042]. The highest quartile of MD had a greater likelihood of PM outcomes compared to the lowest quartile [odds ratio 4.71, 95% CI 1.97-11.69, p = 0.001]. The RCS analysis identified 6.2 mm as the optimal MD threshold for FNA in TR5 nodules. Conclusion MD significantly affects the probability of malignant outcomes in FNA of TR5 thyroid nodules. A MD threshold of ≥6.2mm is suggested for FNA in these nodules.
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Affiliation(s)
- Shi-Liang Cao
- Department of Interventional Medicine, China-Japan Friendship Hospital, Beijing, China
| | - Wan-Ying Shi
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Yi-Ru Niu
- Pathology Department, China-Japan Friendship Hospital, Beijing, China
| | - Zhen-Long Zhao
- Department of Interventional Medicine, China-Japan Friendship Hospital, Beijing, China
| | - Ying Wei
- Department of Interventional Medicine, China-Japan Friendship Hospital, Beijing, China
| | - Jie Wu
- Department of Interventional Medicine, China-Japan Friendship Hospital, Beijing, China
| | - Li-Li Peng
- Department of Interventional Medicine, China-Japan Friendship Hospital, Beijing, China
| | - Yan Li
- Department of Interventional Medicine, China-Japan Friendship Hospital, Beijing, China
| | - Ming-An Yu
- Department of Interventional Medicine, China-Japan Friendship Hospital, Beijing, China
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94
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Su K, Liu J, Ren X, Huo Y, Du G, Zhao W, Wang X, Liang B, Li D, Liu PX. A fully autonomous robotic ultrasound system for thyroid scanning. Nat Commun 2024; 15:4004. [PMID: 38734697 DOI: 10.1038/s41467-024-48421-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2023] [Accepted: 04/23/2024] [Indexed: 05/13/2024] Open
Abstract
The current thyroid ultrasound relies heavily on the experience and skills of the sonographer and the expertise of the radiologist, and the process is physically and cognitively exhausting. In this paper, we report a fully autonomous robotic ultrasound system, which is able to scan thyroid regions without human assistance and identify malignant nod- ules. In this system, human skeleton point recognition, reinforcement learning, and force feedback are used to deal with the difficulties in locating thyroid targets. The orientation of the ultrasound probe is adjusted dynamically via Bayesian optimization. Experimental results on human participants demonstrated that this system can perform high-quality ultrasound scans, close to manual scans obtained by clinicians. Additionally, it has the potential to detect thyroid nodules and provide data on nodule characteristics for American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) calculation.
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Affiliation(s)
- Kang Su
- School of Computer Science and Engineering, South China University of Technology, Guangzhou, 510006, China
| | - Jingwei Liu
- School of Computer Science and Engineering, South China University of Technology, Guangzhou, 510006, China
| | - Xiaoqi Ren
- School of Future Technology, South China University of Technology, Guangzhou, 511442, China
- Peng Cheng Laboratory, Shenzhen, 518000, China
| | - Yingxiang Huo
- School of Future Technology, South China University of Technology, Guangzhou, 511442, China
- Peng Cheng Laboratory, Shenzhen, 518000, China
| | - Guanglong Du
- School of Computer Science and Engineering, South China University of Technology, Guangzhou, 510006, China.
| | - Wei Zhao
- Division of Vascular and Interventional Radiology, Nanfang Hospital Southern Medical University, Guangzhou, 510515, China
| | - Xueqian Wang
- Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China.
| | - Bin Liang
- Department of Automation, Tsinghua University, 100854, Beijing, China.
| | - Di Li
- School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, 510641, China
| | - Peter Xiaoping Liu
- Department of Systems and Computer Engineering, Carleton University, Ottawa, ON, K1S 5B6, Canada.
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Bozer A, Çetin Tunçez H, Kul TD, Argon A. Ultrasonographic Characteristics of Thyroid Nodules with Nondiagnostic and Atypia of Undetermined Significance in Fine-Needle Aspiration Cytology. J Belg Soc Radiol 2024; 108:52. [PMID: 38737380 PMCID: PMC11086593 DOI: 10.5334/jbsr.3577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Accepted: 04/25/2024] [Indexed: 05/14/2024] Open
Abstract
Objectives This study aimed to investigate ultrasound (US) features of thyroid nodules categorized as nondiagnostic (ND) and atypia of undetermined significance (AUS) according to the Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) and their potential implications for clinical management. Materials and Methods A retrospective study was conducted on patients who underwent thyroid nodules FNAC between 2019 and 2023. Nodules falling into the ND and AUS categories were analyzed for US features, nodule size, composition, echogenicity, shape, margin, echogenic foci, the distribution of the American College of Radiology's Thyroid Imaging Reporting and Data System (ACR TI-RADS) categories, and other parameters. The study included a total of 1,199 patients and 1,252 nodules (ND: 1110; AUS: 142). Results No significant differences in age, gender, nodule features, echogenicity, shape, margin, echogenic foci, TI-RADS scores, localization, number of nodules, or thyroid parenchymal disease presence were found between the ND and AUS categories (p > 0.05). Also, no statistically significant difference in nodule size (<10 mm vs. ≥10 mm) existed between the ND and AUS categories (p = 0.475). Both showed predominantly solid composition and hyperechoic/isoechoic echogenicity. High proportions of TI-RADS 4 nodules were observed in both groups, with 727 (65.5%) in ND and 95 (66.9%) in AUS. Conclusion This study found no statistically significant differences in US characteristics between the ND and AUS categories, indicating potential similarities in their radiological appearances. Also, no significant difference in nodule size (<10 mm and ≥10 mm) was observed between these categories. Clinical management should consider further investigations, including repeat FNAC, due to the diagnostic challenges and malignancy risk in both categories.
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Affiliation(s)
- Ahmet Bozer
- Department of Radiology, İzmir City Hospital, İzmir, Turkey
| | | | - Tuğçe Doğa Kul
- Department of Radiology, İzmir City Hospital, İzmir, Turkey
| | - Asuman Argon
- Department of Pathology, İzmir City Hospital, İzmir, Turkey
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Qu C, Li HJ, Gao Q, Zhang JC, Li WM. Alteration Trend and Overlap Analysis of Positive Features in Different-Sized Benign and Malignant Thyroid Nodules: Based on Chinese Thyroid Imaging Reporting and Data System. Int J Gen Med 2024; 17:1887-1895. [PMID: 38736670 PMCID: PMC11086651 DOI: 10.2147/ijgm.s461076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Accepted: 04/22/2024] [Indexed: 05/14/2024] Open
Abstract
Purpose This study aimed to investigate the alteration trends and overlaps of positive features in benign and malignant thyroid nodules of different sizes based on the Chinese Thyroid Imaging Reporting and Data System (C-TIRADS). Patients and Methods 1337 patients with 1558 thyroid nodules were retrospectively recruited from November 2021 to December 2023. These nodules were divided into three groups according to maximum diameter: A (≤10 mm), B (10-20 mm), and C (≥20 mm). C-TIRADS positive features were compared between benign and malignant thyroid nodules of different sizes. In addition, the trends of positive features with changes in nodule size among malignant thyroid nodules were analyzed. Results The incidence of positive features in malignant thyroid nodules was higher than that in benign. As benign nodules grow, the incidence of all positive features showed a linear decreasing trend (Z values were 72.103, 101.081, 17.344, 33.909, and 129.304, P values < 0.001). With the size of malignant thyroid nodules increased, vertical orientation, solid, marked hypoechogenicity, and ill-defined/irregular margins/extrathyroidal extension showed a linear decreasing trend (Z = 148.854, 135.378, 8.590, and 69.239, respectively; P values < 0.05), while suspicious microcalcifications showed a linear increasing trend (Z = 34.699, P<0.001). In terms of overlapping characteristics, group A had a significantly higher overlapping rate than the other two groups, and the overlapping rate of solid indicators remained the highest among all three groups (P < 0.05). Conclusion Differences in positive features were observed between thyroid nodules of different sizes. Except for suspicious microcalcifications, the incidence of other four positive features decreased with increasing nodule size. In addition, a negative correlation was observed between the overlap rate and nodule size. These results may provide a basis for sonographers to upgrade or downgrade thyroid nodules based on their own experience.
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Affiliation(s)
- Chen Qu
- Department of Ultrasonography, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, People’s Republic of China
| | - Hong-jian Li
- Department of Ultrasonography, Huai’an Cancer Hospital, Huai’an, Jiangsu, People’s Republic of China
| | - Qi Gao
- Department of Ultrasonography, Zhongda Hospital Southeast University, Nanjing, Jiangsu, People’s Republic of China
| | - Jun-chao Zhang
- Department of Ultrasonography, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, People’s Republic of China
| | - Wei-min Li
- Department of Ultrasonography, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, People’s Republic of China
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97
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Ryu YJ, Kim JW, Park SC, Hur YH, Kim HJ, Kim TH. Differential diagnosis of thyroid nodules using heterogeneity quantification software on ultrasound images: correlation with the Bethesda system and surgical pathology. Sci Rep 2024; 14:10288. [PMID: 38704392 PMCID: PMC11069538 DOI: 10.1038/s41598-024-60881-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Accepted: 04/29/2024] [Indexed: 05/06/2024] Open
Abstract
Ultrasonography (US)-guided fine-needle aspiration cytology (FNAC) is the primary modality for evaluating thyroid nodules. However, in cases of atypia of undetermined significance (AUS) or follicular lesion of undetermined significance (FLUS), supplemental tests are necessary for a definitive diagnosis. Accordingly, we aimed to develop a non-invasive quantification software using the heterogeneity scores of thyroid nodules. This cross-sectional study retrospectively enrolled 188 patients who were categorized into four groups according to their diagnostic classification in the Bethesda system and surgical pathology [II-benign (B) (n = 24); III-B (n = 52); III-malignant (M) (n = 54); V/VI-M (n = 58)]. Heterogeneity scores were derived using an image pixel-based heterogeneity index, utilized as a coefficient of variation (CV) value, and analyzed across all US images. Differences in heterogeneity scores were compared using one-way analysis of variance with Tukey's test. Diagnostic accuracy was determined by calculating the area under the receiver operating characteristic (AUROC) curve. The results of this study indicated significant differences in mean heterogeneity scores between benign and malignant thyroid nodules, except in the comparison between III-M and V/VI-M nodules. Among malignant nodules, the Bethesda classification was not observed to be associated with mean heterogeneity scores. Moreover, there was a positive correlation between heterogeneity scores and the combined diagnostic category, which was based on the Bethesda system and surgical cytology grades (R = 0.639, p < 0.001). AUROC for heterogeneity scores showed the highest diagnostic performance (0.818; cut-off: 30.22% CV value) for differentiating the benign group (normal/II-B/III-B) from the malignant group (III-M/V&VI-M), with a diagnostic accuracy of 72.5% (161/122). Quantitative heterogeneity measurement of US images is a valuable non-invasive diagnostic tool for predicting the likelihood of malignancy in thyroid nodules, including AUS or FLUS.
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Affiliation(s)
- Young Jae Ryu
- Department of Surgery, Chonnam National University Medical School, Chonnam National University Hwasun Hospital, 322 Seoyang-ro, Hwasun-eup, Hwasun-gun, Jeonnam, 58128, Republic of Korea
| | - Jin Woong Kim
- Department of Radiology, Chosun University College of Medicine, Chosun University Hospital, Gwangju, 61452, Republic of Korea
| | - Sang Chun Park
- Department of Surgery, Chonnam National University Medical School, Chonnam National University Hwasun Hospital, 322 Seoyang-ro, Hwasun-eup, Hwasun-gun, Jeonnam, 58128, Republic of Korea
| | - Young Hoe Hur
- Department of Surgery, Chonnam National University Medical School, Chonnam National University Hwasun Hospital, 322 Seoyang-ro, Hwasun-eup, Hwasun-gun, Jeonnam, 58128, Republic of Korea
| | - Hyung Joong Kim
- Medical Science Research Institute, Kyung Hee University Hospital, 23 Kyungheedae-ro, Dongdaemun-gu, Seoul, 02447, Republic of Korea
| | - Tae-Hoon Kim
- Medical Science Research Institute, Kyung Hee University Hospital, 23 Kyungheedae-ro, Dongdaemun-gu, Seoul, 02447, Republic of Korea.
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Sengul D, Sengul I, Kesicioglu T, Cinar E. Re: "American Thyroid Association and Thyroid Imaging Reporting and Data System developed by the American College of Radiology: which one is better at predicting malignancy risk?" in thyroidology. REVISTA DA ASSOCIACAO MEDICA BRASILEIRA (1992) 2024; 70:e20231584. [PMID: 38716955 PMCID: PMC11068400 DOI: 10.1590/1806-9282.20231584] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Accepted: 11/19/2023] [Indexed: 05/12/2024]
Affiliation(s)
- Demet Sengul
- Giresun University, Faculty of Medicine, Department of Pathology – Giresun, Turkey
| | - Ilker Sengul
- Giresun University, Faculty of Medicine, Division of Endocrine Surgery – Giresun, Turkey
- Giresun University Faculty of Medicine, Department of General Surgery – Giresun, Turkey
| | - Tugrul Kesicioglu
- Giresun University Faculty of Medicine, Department of General Surgery – Giresun, Turkey
| | - Esma Cinar
- Giresun University, Faculty of Medicine, Department of Pathology – Giresun, Turkey
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99
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Polat Z, Elmalı M, Tanrivermis Sayit A, Kalkan C, Danacı M, Kefeli M. Comparative evaluation of shear wave elastography elasticity values in thyroid nodules with cytology results and TI-RADS scoring in differentiation of benign-malignant nodules. Eur Arch Otorhinolaryngol 2024; 281:2609-2617. [PMID: 38461420 PMCID: PMC11023991 DOI: 10.1007/s00405-024-08516-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Accepted: 01/29/2024] [Indexed: 03/12/2024]
Abstract
PURPOSE The aim of this prospective study was to investigate the diagnostic performance of shear wave elastography (SWE) in differentiating benign and malignant thyroid nodules and their correlation with the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS). METHODS This prospective study included 370 thyroid nodules in 308 patients aged 18-70 years. All the patients underwent B-mode ultrasound (US), Doppler examination, and SWE and were given an ACR TI-RADS risk score before fine needle aspiration biopsy (FNAB) and/or surgery. The correlation between SWE parameters and ACR TI-RADS categories was investigated statistically and compared with histopathologic results. Additionally, the diagnostic performance of SWE was evaluated to distinguish malignant and benign thyroid nodules. RESULTS One hundred and thirty-five of the 370 thyroid nodules were malignant, and 235 nodules were benign. The mean shear wave velocity (SWV) value of the malignant nodules (3.70 ± 0.98 m/s) was statistically higher than that of the benign nodules (2.70 ± 0.37 m/s). The best cutoff value of the mean SWV for differentiating benign and malignant nodules was found to be 2.94 m/s (sensitivity 90.4%, specificity 89.9%, positive predictive value 81.3%, negative predictive value 94.1%, p < 0.001). The average score of the nodules according to the ACR TI-RADS was 3.57 ± 1.83 in benign nodules and 7.38 ± 2.69 in malignant nodules (p ≤ 0.001). CONCLUSION This study showed that combining SWE and TI-RADS improves the specificity of TI-RADS alone in differentiating benign and malignant nodules.
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Affiliation(s)
- Zafer Polat
- Faculty of Medicine, Department of Radiology, Ondokuzmayis University, 55139, Atakum, Samsun, Turkey
| | - Muzaffer Elmalı
- Faculty of Medicine, Department of Radiology, Ondokuzmayis University, 55139, Atakum, Samsun, Turkey
| | - Asli Tanrivermis Sayit
- Faculty of Medicine, Department of Radiology, Ondokuzmayis University, 55139, Atakum, Samsun, Turkey.
| | - Cihan Kalkan
- Faculty of Medicine, Department of Radiology, Ondokuzmayis University, 55139, Atakum, Samsun, Turkey
| | - Murat Danacı
- Faculty of Medicine, Department of Radiology, Ondokuzmayis University, 55139, Atakum, Samsun, Turkey
| | - Mehmet Kefeli
- Faculty of Medicine, Department of Pathology, Ondokuzmayis University, Samsun, Turkey
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Li L, Deng H, Chen W, Wu L, Li Y, Wang J, Ye X. Comparison of the diagnostic effectiveness of ultrasound imaging coupled with three mathematical models for discriminating thyroid nodules. Acta Radiol 2024; 65:441-448. [PMID: 38232946 DOI: 10.1177/02841851231221912] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
BACKGROUND The overlapping nature of thyroid lesions visualized on ultrasound (US) images could result in misdiagnosis and missed diagnoses in clinical practice. PURPOSE To compare the diagnostic effectiveness of US coupled with three mathematical models, namely logistic regression (Logistics), partial least-squares discriminant analysis (PLS-DA), and support vector machine (SVM), in discriminating between malignant and benign thyroid nodules. MATERIAL AND METHODS A total of 588 thyroid nodules (287 benign and 301 malignant) were collected, among which 80% were utilized for constructing the mathematical models and the remaining 20% were used for internal validation. In addition, an external validation cohort comprising 160 nodules (80 benign and 80 malignant) was employed to validate the accuracy of these mathematical models. RESULTS Our study demonstrated that all three models exhibited effective predictive capabilities for distinguishing between benign and malignant nodules, whose diagnostic effectiveness surpassed that of the TI-RADS classification, particularly in terms of true negative diagnoses. SVM achieved a higher diagnostic rate for malignant thyroid nodules (93.8%) compared to Logistics (91.5%) and PLS-DA (91.6%). PLS-DA exhibited higher diagnostic rates for benign thyroid nodules (91.9%) compared to Logistics (86.7%) and SVM (88.7%). Both the area under the receiver operating characteristic curve (AUC) values of PLS-DA (0.917) and SVM (0.913) were higher than that of Logistics (0.891). CONCLUSION Our findings indicate that SVM had significantly higher rates of true positive diagnoses and PLS-DA exhibited significantly higher rates of true negative diagnoses. All three models outperformed the TI-RADS classification in discriminating between malignant and benign thyroid nodules.
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Affiliation(s)
- Lu Li
- Department of Ultrasound, The First Affiliated Hospital, Nanjing Medical University, Nanjing, PR China
| | - Hongyan Deng
- Department of Ultrasound, The First Affiliated Hospital, Nanjing Medical University, Nanjing, PR China
| | - Wenqin Chen
- Department of Ultrasound, The First Affiliated Hospital, Nanjing Medical University, Nanjing, PR China
| | - Liuxi Wu
- Department of Ultrasound, The First Affiliated Hospital, Nanjing Medical University, Nanjing, PR China
| | - Yong Li
- Institute of Food Safety and Nutrition, Jiangsu Academy of Agricultural Sciences, Nanjing, PR China
| | - Jie Wang
- Department of Radiology, The First Affiliated Hospital, Nanjing Medical University, Nanjing, PR China
| | - Xinhua Ye
- Department of Ultrasound, The First Affiliated Hospital, Nanjing Medical University, Nanjing, PR China
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