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Wang M, Yang S, Yang L, Lin N. Comparative Analysis of AI-SONICTM Thyroid System and Six Thyroid Risk Stratification Guidelines in Papillary Thyroid Cancer: A Retrospective Cohort Study. Ther Clin Risk Manag 2024; 20:515-528. [PMID: 39193477 PMCID: PMC11348989 DOI: 10.2147/tcrm.s458576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Accepted: 07/15/2024] [Indexed: 08/29/2024] Open
Abstract
Aim The study aimed to compare the diagnostic performance of AI-SONICTM Thyroid System (AI-SONICTM) with six thyroid nodule ultrasound risk stratification systems, as well as the interobserver agreement among different-year ultrasound examiners using the same diagnostic approach. Methods This retrospective study included patients who underwent thyroid ultrasound examination and surgery between 2010 and 2022. Three ultrasound examiners with 2, 5, and 10 years of experience, respectively, used AI-SONICTM and six guidelines to risk-stratify the nodules. The diagnostic performance and interobserver agreement were assessed. Results A total of 370 thyroid nodules were included, including 195 papillary thyroid carcinomas (PTC) and 175 benign nodules. For physicians of varying seniority from low to high, AI-SONICTM had a moderate sensitivities of 82.56%, 83.08%, 84.62%, respectively, while AACE/ACE/AME had the highest diagnostic sensitivities (96.41%, 95.38%, 96.41%, respectively); And relatively higher specificities were 85.14%, 85.71%, 85.71% for KSThR, while moderate specificities with values of 84.0%, 85.14%, and 85.71%, respectively were found for AI-SONICTM; The accuracy was highest for ATA (excluding non-classifiable nodules), with values of 87.26%, 87.93%, and 88.82%, respectively, while the accuracy for AI-SONICTM were 83.24%, 84.05%, and 85.14%, respectively. The Kendall's tau coefficient indicated strong or moderate interobserver agreement among all examiners using different diagnostic methods (Kendall's tau coefficient >0.6, P<0.001). AI-SONICTM showed the highest interobserver agreement (Kendall's tau coefficient=0.995, P<0.001). A binary probit regression analysis showed that nodules with cystic components had a significantly higher regression coefficient value of 0.983 (P=0.002), indicating that AI-SONICTM may have higher accuracy for nodules with cystic components. Conclusion AI-SONICTM and the six thyroid nodule ultrasound risk stratification systems showed high diagnostic performance for papillary thyroid carcinoma. All examiners showed strong or moderate interobserver agreement when using different diagnostic methods. AI-SONICTM may have higher accuracy for nodules with cystic components.
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Affiliation(s)
- Mingyan Wang
- Ultrasound Department of Shengli Clinical Medical College of Fujian Medical University, Fuzhou City, Fujian Province, 350001, People’s Republic of China
- Ultrasound Department of Fujian Provincial Hospital, Fuzhou City, Fujian Province, 350001, People’s Republic of China
- Ultrasound Department of Fuzhou University Affiliated Provincial Hospital, Fuzhou City, Fujian Province, 350001, People’s Republic of China
| | - Siyuan Yang
- Ultrasound Department of Shengli Clinical Medical College of Fujian Medical University, Fuzhou City, Fujian Province, 350001, People’s Republic of China
- Ultrasound Department of Fujian Provincial Hospital, Fuzhou City, Fujian Province, 350001, People’s Republic of China
- Ultrasound Department of Fuzhou University Affiliated Provincial Hospital, Fuzhou City, Fujian Province, 350001, People’s Republic of China
| | - Linxin Yang
- Ultrasound Department of Shengli Clinical Medical College of Fujian Medical University, Fuzhou City, Fujian Province, 350001, People’s Republic of China
- Ultrasound Department of Fujian Provincial Hospital, Fuzhou City, Fujian Province, 350001, People’s Republic of China
- Ultrasound Department of Fuzhou University Affiliated Provincial Hospital, Fuzhou City, Fujian Province, 350001, People’s Republic of China
| | - Ning Lin
- Ultrasound Department of Shengli Clinical Medical College of Fujian Medical University, Fuzhou City, Fujian Province, 350001, People’s Republic of China
- Ultrasound Department of Fujian Provincial Hospital, Fuzhou City, Fujian Province, 350001, People’s Republic of China
- Ultrasound Department of Fuzhou University Affiliated Provincial Hospital, Fuzhou City, Fujian Province, 350001, People’s Republic of China
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Grani G, Sponziello M, Filetti S, Durante C. Thyroid nodules: diagnosis and management. Nat Rev Endocrinol 2024:10.1038/s41574-024-01025-4. [PMID: 39152228 DOI: 10.1038/s41574-024-01025-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/22/2024] [Indexed: 08/19/2024]
Abstract
Thyroid nodules, with a prevalence of almost 25% in the general population, are a common occurrence. Their prevalence varies considerably depending on demographics such as age and sex as well as the presence of risk factors. This article provides a comprehensive overview of the prevalence, risk stratification and current management strategies for thyroid nodules, with a particular focus on changes in diagnostic and therapeutic protocols that have occurred over the past 10 years. Several sonography-based stratification systems (such as Thyroid Imaging Reporting and Data Systems (TIRADS)) might help to predict the malignancy risk of nodules, potentially eliminating the need for biopsy in many instances. However, large or suspicious nodules necessitate cytological evaluation following fine-needle aspiration biopsy for accurate classification. In the case of cytology yielding indeterminate results, additional tools, such as molecular testing, can assist in guiding the management plan. Surgery is no longer the only treatment for symptomatic or malignant nodules: active surveillance or local ablative treatments might be beneficial for appropriately selected patients. To enhance clinician-patient interactions and discussions about diagnostic options, shared decision-making tools have been developed. A personalized, risk-based protocol promotes high-quality care while minimizing costs and unnecessary testing.
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Affiliation(s)
- Giorgio Grani
- Department of Translational and Precision Medicine, Sapienza University of Rome, Rome, Italy
| | - Marialuisa Sponziello
- Department of Translational and Precision Medicine, Sapienza University of Rome, Rome, Italy
| | - Sebastiano Filetti
- Department of Translational and Precision Medicine, Sapienza University of Rome, Rome, Italy
| | - Cosimo Durante
- Department of Translational and Precision Medicine, Sapienza University of Rome, Rome, Italy.
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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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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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5
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Qian Y, Li Z, Fan C, Huang Y. Comparison of ultrasound-guided microwave ablation, laser ablation, and radiofrequency ablation for the treatment of elderly patients with benign thyroid nodules: A meta-analysis. Exp Gerontol 2024; 191:112425. [PMID: 38604254 DOI: 10.1016/j.exger.2024.112425] [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: 02/02/2024] [Revised: 03/27/2024] [Accepted: 04/08/2024] [Indexed: 04/13/2024]
Abstract
BACKGROUND A new minimally invasive technique, ultrasound-guided thermal ablation has become one of the treatment methods for benign thyroid nodules. This study aims to evaluate the efficacy and safety of laser ablation (LA), radiofrequency ablation (RFA), and microwave ablation (MWA) in the treatment of elderly patients with benign thyroid nodules. METHODS PubMed, Web of Science, and Cochrane Library were searched for qualified randomized controlled studies (RCTs) issued from establishing databases to March 2022. After screening and evaluating the article quality, the data on nodular volume reduction rate (VRR) and the incidence of complications after thermal ablation were extracted and analyzed by RevMan 5.3 and Stata l4.0. RESULTS The meta-analysis included seven articles with 3055 participants. We found that LA, RFA, and MWA could markedly reduce the volume of benign thyroid nodules. LA was superior to RFA and MWA in reducing the volume of benign thyroid nodules in 6 months of follow-up (all P < 0.05). LA, RFA, and MWA can be safely implemented in patients with benign thyroid nodules. The incidence of significant complications after the RFA group was enhanced compared with that in the MWA (P < 0.05), and the incidence of secondary complications after RFA was slightly higher than that of LA (P < 0.05). CONCLUSION LA, RFA, and MWA can markedly reduce the volume of benign thyroid nodules in elderly patients and can safely treat benign thyroid nodules.
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Affiliation(s)
- Ying Qian
- Department of Ultrasound, The People's Hospital of Danyang, Danyang Hospital of Nantong University, Danyang 212300, Jiangsu, China
| | - Zheng Li
- Department of Ultrasound, The People's Hospital of Danyang, Danyang Hospital of Nantong University, Danyang 212300, Jiangsu, China
| | - Chunyun Fan
- Department of Ultrasound, The People's Hospital of Danyang, Danyang Hospital of Nantong University, Danyang 212300, Jiangsu, China
| | - Yong Huang
- Department of Endocrinology, The People's Hospital of Danyang, Danyang Hospital of Nantong University, Danyang 212300, Jiangsu, China.
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Kreissl MC, Ovčariček PP, Campenni A, Vrachimis A, Tuncel M, Giovanella L. The European Association of Nuclear Medicine (EANM)'s Response to the 2023 European Thyroid Association (ETA) clinical practice guidelines for thyroid nodule management and nuclear medicine: a deliberate oversight? Eur J Nucl Med Mol Imaging 2024; 51:1678-1681. [PMID: 38226985 PMCID: PMC11043102 DOI: 10.1007/s00259-023-06571-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2024]
Affiliation(s)
- Michael C Kreissl
- Division of Nuclear Medicine, Department of Radiology and Nuclear Medicine, University Hospital Magdeburg, Otto-Von-Guericke University, 39120, Magdeburg, Germany.
| | - Petra Petranović Ovčariček
- Department of Oncology and Nuclear Medicine, University Hospital Center Sestre Milosrdnice, 10000, Zagreb, Croatia
- School of Medicine, University of Zagreb, 10000, Zagreb, Croatia
| | - Alfredo Campenni
- Department of Biomedical and Dental Sciences and Morpho-Functional Imaging, Unit of Nuclear Medicine, University of Messina, 98100, Messina, Italy
| | - Alexis Vrachimis
- Department of Nuclear Medicine, German Oncology Center, University Hospital of the European University, 4108, Limassol, Cyprus
| | - Murat Tuncel
- Department of Nuclear Medicine, Hacettepe University, 06230, Ankara, Turkey
| | - Luca Giovanella
- Clinic for Nuclear Medicine, Imaging Institute of Southern Switzerland, Ente Ospedaliero Cantonale, 6500, Bellinzona, Switzerland
- Clinic for Nuclear Medicine, University Hospital of Zürich, 8004, Zürich, Switzerland
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7
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Rao KN, Randolph GW, Lopez F, Zafereo M, Coca-Pelaz A, Piazza C, Dange P, Rodrigo JP, Stenman G, de Keizer B, Nixon I, Sinha S, Leboulleux S, Mäkitie AA, Agaimy A, Thompson L, Ferlito A. Assessment of the risk of malignancy in Bethesda III thyroid nodules: a comprehensive review. Endocrine 2024:10.1007/s12020-024-03737-z. [PMID: 38416380 DOI: 10.1007/s12020-024-03737-z] [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: 01/07/2024] [Accepted: 02/08/2024] [Indexed: 02/29/2024]
Abstract
The increasing prevalence of thyroid cancer emphasizes the need for a thorough assessment of risk of malignancy in Bethesda III nodules. Various methods ranging commercial platforms of molecular genetic testing (including Afirma® GEC, Afirma® GSC, ThyroSeq® V3, RosettaGX®, ThyGeNEXT®/ThyraMIR®, ThyroidPRINT®) to radionuclide scans and ultrasonography have been investigated to provide a more nuanced comprehension of risk estimation. The integration of molecular studies and imaging techniques into clinical practice may provide clinicians with improved and personalized risk assessment. This integrated approach we feel may enable clinicians to carefully tailor interventions, thereby minimizing the likelihood of unnecessary thyroid surgeries and overall crafting the optimal treatment. By aligning with the evolving landscape of personalized healthcare, this comprehensive strategy ensures a patient-centric approach to thyroid nodule and thyroid cancer management.
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Affiliation(s)
- Karthik Nagaraja Rao
- Department of Head and Neck Oncology, Sri Shankara Cancer Hospital and Research Center, Bangalore, 560004, India.
| | - Gregory W Randolph
- Division of Thyroid and Parathyroid Endocrine Surgery, Department of Otolaryngology-Head and Neck Surgery, Massachusetts Eye and Ear Infirmary, Harvard Medical School, Boston, MA, USA
| | - Fernando Lopez
- Department of Otolaryngology, Hospital Universitario Central de Asturias, University of Oviedo, ISPA, IUOPA, CIBERONC, 33011, Oviedo, Spain
| | - Mark Zafereo
- Department of Head and Neck Surgery, The University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
| | - Andrés Coca-Pelaz
- Department of Otolaryngology, Hospital Universitario Central de Asturias, University of Oviedo, ISPA, IUOPA, CIBERONC, 33011, Oviedo, Spain
| | - Cesare Piazza
- Unit of Otorhinolaryngology-Head and Neck Surgery, ASST Spedali Civili of Brescia, Brescia, Italy
| | - Prajwal Dange
- Department of Head and Neck Oncology, Sri Shankara Cancer Hospital and Research Center, Bangalore, 560004, India
| | - Juan Pablo Rodrigo
- Department of Otolaryngology, Hospital Universitario Central de Asturias, University of Oviedo, ISPA, IUOPA, CIBERONC, 33011, Oviedo, Spain
| | - Göran Stenman
- Sahlgrenska Center for Cancer Research Department of Pathology, University of Gothenburg, Gothenburg, Sweden
| | - Bart de Keizer
- Department of Nuclear Medicine and Radiology, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
| | - Iain Nixon
- Department of Surgery and Otolaryngology, Head and Neck Surgery, Edinburgh University, Edinburgh, EH3 9YL, UK
| | - Shriyash Sinha
- Department of Head and Neck Oncology, Sri Shankara Cancer Hospital and Research Center, Bangalore, 560004, India
| | - Sophie Leboulleux
- Department of Endocrinology, Diabetology, Nutrition and Therapeutic Education, Geneva University Hospitals, Rue Gabrielle Perret Gentil, Geneva University, Geneva, Switzerland
| | - Antti A Mäkitie
- Department of Otorhinolaryngology-Head and Neck Surgery, Faculty of Medicine, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
- Research Program in Systems Oncology, University of Helsinki, Helsinki, Finland
| | - Abbas Agaimy
- Institute of Pathology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91054, Erlangen, Germany
- Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), 91054, Erlangen, Germany
| | - Lester Thompson
- Head and Neck Pathology Consultations, Woodland Hills, CA, 91364, USA
| | - Alfio Ferlito
- Coordinator of the International Head and Neck Scientific Group, Padua, Italy
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Boucai L, Zafereo M, Cabanillas ME. Thyroid Cancer: A Review. JAMA 2024; 331:425-435. [PMID: 38319329 DOI: 10.1001/jama.2023.26348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2024]
Abstract
Importance Approximately 43 720 new cases of thyroid carcinoma are expected to be diagnosed in 2023 in the US. Five-year relative survival is approximately 98.5%. This review summarizes current evidence regarding pathophysiology, diagnosis, and management of early-stage and advanced thyroid cancer. Observations Papillary thyroid cancer accounts for approximately 84% of all thyroid cancers. Papillary, follicular (≈4%), and oncocytic (≈2%) forms arise from thyroid follicular cells and are termed well-differentiated thyroid cancer. Aggressive forms of follicular cell-derived thyroid cancer are poorly differentiated thyroid cancer (≈5%) and anaplastic thyroid cancer (≈1%). Medullary thyroid cancer (≈4%) arises from parafollicular C cells. Most cases of well-differentiated thyroid cancer are asymptomatic and detected during physical examination or incidentally found on diagnostic imaging studies. For microcarcinomas (≤1 cm), observation without surgical resection can be considered. For tumors larger than 1 cm with or without lymph node metastases, surgery with or without radioactive iodine is curative in most cases. Surgical resection is the preferred approach for patients with recurrent locoregional disease. For metastatic disease, surgical resection or stereotactic body irradiation is favored over systemic therapy (eg, lenvatinib, dabrafenib). Antiangiogenic multikinase inhibitors (eg, sorafenib, lenvatinib, cabozantinib) are approved for thyroid cancer that does not respond to radioactive iodine, with response rates 12% to 65%. Targeted therapies such as dabrafenib and selpercatinib are directed to genetic mutations (BRAF, RET, NTRK, MEK) that give rise to thyroid cancer and are used in patients with advanced thyroid carcinoma. Conclusions Approximately 44 000 new cases of thyroid cancer are diagnosed each year in the US, with a 5-year relative survival of 98.5%. Surgery is curative in most cases of well-differentiated thyroid cancer. Radioactive iodine treatment after surgery improves overall survival in patients at high risk of recurrence. Antiangiogenic multikinase inhibitors and targeted therapies to genetic mutations that give rise to thyroid cancer are increasingly used in the treatment of metastatic disease.
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Affiliation(s)
- Laura Boucai
- Department of Medicine, Division of Endocrinology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Mark Zafereo
- Department of Head and Neck Surgery, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Maria E Cabanillas
- Department of Endocrine Neoplasia and Hormonal Disorders, University of Texas MD Anderson Cancer Center, Houston, Texas
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Reuter KL. US Follow-up of Papillary Microcarcinoma of the Thyroid Gland. Radiology 2023; 309:e231913. [PMID: 37906008 DOI: 10.1148/radiol.231913] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Affiliation(s)
- Karen L Reuter
- From the Department of Radiology, Lahey Hospital and Medical Center, 41 Mall Rd, Burlington, MA 01805-0105
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10
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Xing Z, Qiu Y, Zhu J, Su A, Wu W. Diagnostic performance of ultrasound risk stratification systems on thyroid nodules cytologically classified as indeterminate: a systematic review and meta-analysis. Ultrasonography 2023; 42:518-531. [PMID: 37697824 PMCID: PMC10555695 DOI: 10.14366/usg.23055] [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: 03/27/2023] [Revised: 06/15/2023] [Accepted: 06/18/2023] [Indexed: 09/13/2023] Open
Abstract
PURPOSE Ultrasound (US) risk stratification systems (RSSs) are increasingly being utilized for the optimal management of thyroid nodules, including those with indeterminate cytology. The goal of this study was to evaluate the category-based diagnostic performance of US RSSs in identifying malignancy in indeterminate nodules. METHODS This systematic review and meta-analysis was registered on PROSPERO (CRD42021266195). PubMed, EMBASE, and Web of Science were searched through December 1, 2022. Original articles reporting data on the performance of US RSSs for indeterminate nodules were included. The numbers of nodules classified as true negative, true positive, false negative, and false positive were extracted. RESULTS Thirty-three studies evaluating 7,225 indeterminate thyroid nodules were included. The diagnostic accuracy was quantitatively synthesized using a Bayesian bivariate model based on the integrated nested Laplace approximation in R. For the intermediate- to high-risk category, the sensitivity levels of the American College of Radiology, the American Thyroid Association, the European Thyroid Association, the Korean Thyroid Association/Korean Society of Thyroid Radiology, and Kwak et al. were found to be 0.80, 0.72, 0.76, 0.96, and 0.97, respectively. The corresponding specificity measurements were 0.36, 0.50, 0.49, 0.28, and 0.17. Furthermore, for the high-risk category, the sensitivity values were 0.40, 0.46, 0.55, 0.47, and 0.10, while the specificity levels were 0.91, 0.90, 0.71, 0.91, and 0.99, respectively. CONCLUSION The overall diagnostic performance of the US RSSs was moderate in the differentiation of indeterminate nodules.
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Affiliation(s)
- Zhichao Xing
- Center of Thyroid and Parathyroid Surgery, West China Hospital, Sichuan University, Chengdu, China
- Laboratory of Thyroid and Parathyroid Disease, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, China
| | - Yuxuan Qiu
- Ultrasound Department, West China Hospital, Sichuan University, Chengdu, China
| | - Jingqiang Zhu
- Center of Thyroid and Parathyroid Surgery, West China Hospital, Sichuan University, Chengdu, China
| | - Anping Su
- Center of Thyroid and Parathyroid Surgery, West China Hospital, Sichuan University, Chengdu, China
| | - Wenshuang Wu
- Center of Thyroid and Parathyroid Surgery, West China Hospital, Sichuan University, Chengdu, China
- Laboratory of Thyroid and Parathyroid Disease, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, China
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Torshizian A, Hashemi F, Khoshhal N, Ghodsi A, Rastegar H, Mousavi Z, Dadgar Moghadam M, Mohebbi M. Diagnostic Performance of ACR TI-RADS and ATA Guidelines in the Prediction of Thyroid Malignancy: A Prospective Single Tertiary Center Study and Literature Review. Diagnostics (Basel) 2023; 13:2972. [PMID: 37761339 PMCID: PMC10527732 DOI: 10.3390/diagnostics13182972] [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: 06/29/2023] [Revised: 09/04/2023] [Accepted: 09/14/2023] [Indexed: 09/29/2023] Open
Abstract
AIM This study sought to compare two common risk stratification systems in terms of their diagnostic performance for the evaluation of thyroid malignancy. METHODS The American College of Radiology (ACR) Thyroid Imaging, Reporting and Data System (TI-RADS) and the American Thyroid Association (ATA) guidelines were compared among 571 thyroid nodules with definitive fine needle aspiration (FNA) cytology or postoperative histopathology. Ultrasound characteristics such as composition, echogenicity, shape, margin, size, and vascularity were assessed for each thyroid nodule. Diagnostic performance measures were determined and compared through receiver operating characteristic (ROC) curves, and decision curve analysis (DCA). RESULTS Of 571 nodules, 65 (11.4%) were malignant. The AUC, sensitivity, specificity, positive predictive value, and negative predictive value were 0.691, 49.2%, 84.9%, 29.6%, and 92.8% for ATA guideline, and 0.776, 72.3%, 79.2%, 30.9%, and 95.7%, for ACR TI-RADS, respectively. ACR TI-RADS was more sensitive (p = 0.003), while the ATA guideline was more specific (p < 0.001). DCA demonstrated that the ACR TI-RADS provided a greater net benefit than the ATA guideline. In addition, the net reduction in unnecessary biopsies is higher for ACR TI-RADS than ATA guidelines. The total number of indicated biopsies and unnecessary FNA rates were lower in ACR TI-RADS compared to ATA guideline (293 vs. 527 and 80.2 vs. 87.8). ACR TI-RADS presented no biopsy indication in seven malignant nodules (all categorized as TR2), whereas ATA guideline missed one. Hypoechogenicity was the most significant predictor of malignancy (OR = 8.34, 95% CI: 3.75-19.45), followed by a taller-than-wide shape (OR = 6.73, 95% CI: 3.07-14.77). CONCLUSIONS Our findings suggest that each system has particular advantages in the evaluation of thyroid nodules. ACR TI-RADS reduces unnecessary FNA rates, however, malignant nodules categorized as TR2 might be missed using this system. Further evaluation of this group of nodules using Doppler and other ultrasound modalities is recommended.
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Affiliation(s)
- Ashkan Torshizian
- Student Research Committee, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad 13944-91388, Iran
| | - Fatemeh Hashemi
- Student Research Committee, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad 13944-91388, Iran
| | - Nastaran Khoshhal
- Student Research Committee, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad 13944-91388, Iran
| | - Alireza Ghodsi
- Student Research Committee, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad 13944-91388, Iran
| | - Houra Rastegar
- Student Research Committee, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad 13944-91388, Iran
| | - Zohreh Mousavi
- Metabolic Syndrome Research Center, Mashhad University of Medical Sciences, Mashhad 13944-91388, Iran
| | - Maliheh Dadgar Moghadam
- Clinical Research Development Unit, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad 13944-91388, Iran
| | - Masoud Mohebbi
- Metabolic Syndrome Research Center, Mashhad University of Medical Sciences, Mashhad 13944-91388, Iran
- Faculty of Medicine, Mashhad University of Medical Sciences, Azadi Sq., Mashhad 13944-91388, Iran
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Nagendra L, Pappachan JM, Fernandez CJ. Artificial intelligence in the diagnosis of thyroid cancer: Recent advances and future directions. Artif Intell Cancer 2023; 4:1-10. [DOI: 10.35713/aic.v4.i1.1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Revised: 07/24/2023] [Accepted: 08/07/2023] [Indexed: 09/07/2023] Open
Abstract
The diagnosis and management of thyroid cancer is fraught with challenges despite the advent of innovative diagnostic, surgical, and chemotherapeutic modalities. Challenges like inaccuracy in prognostication, uncertainty in cytopathological diagnosis, trouble in differentiating follicular neoplasms, intra-observer and inter-observer variability on ultrasound imaging preclude personalised treatment in thyroid cancer. Artificial intelligence (AI) is bringing a paradigm shift to the healthcare, powered by quick advancement of the analytic techniques. Several recent studies have shown remarkable progress in thyroid cancer diagnostics based on AI-assisted algorithms. Application of AI techniques in thyroid ultrasonography and cytopathology have shown remarkable impro-vement in sensitivity and specificity over the traditional diagnostic modalities. AI has also been explored in the development of treatment algorithms for indeterminate nodules and for prognostication in the patients with thyroid cancer. The benefits of high repeatability and straightforward implementation of AI in the management of thyroid cancer suggest that it holds promise for clinical application. Limited clinical experience and lack of prospective validation studies remain the biggest drawbacks. Developing verified and trustworthy algorithms after extensive testing and validation using prospective, multi-centre trials is crucial for the future use of AI in the pipeline of precision medicine in the management of thyroid cancer.
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Affiliation(s)
- Lakshmi Nagendra
- Department of Endocrinology, JSS Medical College & JSS Academy of Higher Education and Research Center, Mysore 570015, India
| | - Joseph M Pappachan
- Department of Endocrinology & Metabolism, Lancashire Teaching Hospitals NHS Trust, Preston PR2 9HT, United Kingdom
- Faculty of Science, Manchester Metropolitan University, Manchester M15 6BH, M15 6BH, United Kingdom
- Faculty of Biology, Medicine and Health, The University of Manchester, Manchester M13 9PL, United Kingdom
| | - Cornelius James Fernandez
- Department of Endocrinology & Metabolism, Pilgrim Hospital, United Lincolnshire Hospitals NHS Trust, PE21 9QS PE21 9QS, United Kingdom
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Yang L, Li C, Chen Z, He S, Wang Z, Liu J. Diagnostic efficiency among Eu-/C-/ACR-TIRADS and S-Detect for thyroid nodules: a systematic review and network meta-analysis. Front Endocrinol (Lausanne) 2023; 14:1227339. [PMID: 37720531 PMCID: PMC10501732 DOI: 10.3389/fendo.2023.1227339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 08/16/2023] [Indexed: 09/19/2023] Open
Abstract
Background The performance in evaluating thyroid nodules on ultrasound varies across different risk stratification systems, leading to inconsistency and uncertainty regarding diagnostic sensitivity, specificity, and accuracy. Objective Comparing diagnostic performance of detecting thyroid cancer among distinct ultrasound risk stratification systems proposed in the last five years. Evidence acquisition Systematic search was conducted on PubMed, EMBASE, and Web of Science databases to find relevant research up to December 8, 2022, whose study contents contained elucidation of diagnostic performance of any one of the above ultrasound risk stratification systems (European Thyroid Imaging Reporting and Data System[Eu-TIRADS]; American College of Radiology TIRADS [ACR TIRADS]; Chinese version of TIRADS [C-TIRADS]; Computer-aided diagnosis system based on deep learning [S-Detect]). Based on golden diagnostic standard in histopathology and cytology, single meta-analysis was performed to obtain the optimal cut-off value for each system, and then network meta-analysis was conducted on the best risk stratification category in each system. Evidence synthesis This network meta-analysis included 88 studies with a total of 59,304 nodules. The most accurate risk category thresholds were TR5 for Eu-TIRADS, TR5 for ACR TIRADS, TR4b and above for C-TIRADS, and possible malignancy for S-Detect. At the best thresholds, sensitivity of these systems ranged from 68% to 82% and specificity ranged from 71% to 81%. It identified the highest sensitivity for C-TIRADS TR4b and the highest specificity for ACR TIRADS TR5. However, sensitivity for ACR TIRADS TR5 was the lowest. The diagnostic odds ratio (DOR) and area under curve (AUC) were ranked first in C-TIRADS. Conclusion Among four ultrasound risk stratification options, this systemic review preliminarily proved that C-TIRADS possessed favorable diagnostic performance for thyroid nodules. Systematic review registration https://www.crd.york.ac.uk/prospero, CRD42022382818.
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Affiliation(s)
- Longtao Yang
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Cong Li
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Zhe Chen
- Department of Thoracic Surgery, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Shaqi He
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Zhiyuan Wang
- Department of Ultrasound, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, Hunan, China
| | - Jun Liu
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
- Clinical Research Center for Medical Imaging in Hunan Province, Changsha, China
- Department of Radiology Quality Control Center in Hunan Province, Changsha, China
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