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Yang Y, Huang H, Shao Y, Chen B. DAC-Net: A light-weight U-shaped network based efficient convolution and attention for thyroid nodule segmentation. Comput Biol Med 2024; 180:108972. [PMID: 39126790 DOI: 10.1016/j.compbiomed.2024.108972] [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: 03/08/2024] [Revised: 05/06/2024] [Accepted: 07/29/2024] [Indexed: 08/12/2024]
Abstract
Recently, there has been a focused effort to improve the efficiency of thyroid nodule segmentation algorithms. This endeavor has resulted in the development of increasingly complex modules, such as the Transformer, leading to models with a higher number of parameters and computing requirements. Sophisticated models have difficulties in being implemented in clinical medicine platforms because of limited resources. DAC-Net is a Lightweight U-shaped network created to achieve high performance in segmenting thyroid nodules. Our method consists of three main components: DWSE, which combines depthwise convolution and squeeze-excitation block to enhance feature extraction and connections between samples; ADA, which includes Split Atrous and Dual Attention to extract global and local feature information from various viewpoints; and CSSC, which involves channel- scale and spatial-scale connections. This module enables the fusing of multi-stage features at global and local levels, producing feature maps at different channel and geographical scales, delivering a streamlined integration of multi-scale information. Combining these three components in our U- shaped design allows us to achieve competitive performance while also decreasing the number of parameters and computing complexity. Several experiments were conducted on the DDTI and TN3K datasets. The experimental results demonstrate that our model outperforms state-of-the-art thyroid nodule segmentation architectures in terms of segmentation performance. Our model not only reduces the number of parameters and computing expenses by 73x and 56x, respectively, but also exceeds TransUNet in segmentation performance. The source code is accessible at https://github.com/Phil-y/DAC-Net.
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Affiliation(s)
- Yingwei Yang
- College of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou 325000, China
| | - Haiguang Huang
- College of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou 325000, China.
| | - Yingsheng Shao
- College of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou 325000, China
| | - Beilei Chen
- Department of Ultrasonic Imaging, Wenzhou Central Hospital, Wenzhou 325000, China
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2
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Fan Y, Zheng X, Xu T, Li P, Zhang Y, Ran Y, Wei T. A bibliometric analysis of follicular thyroid carcinoma: Current situation, hot spots, and global trends. Asian J Surg 2024:S1015-9584(24)01644-0. [PMID: 39117545 DOI: 10.1016/j.asjsur.2024.07.271] [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: 03/24/2024] [Revised: 06/26/2024] [Accepted: 07/22/2024] [Indexed: 08/10/2024] Open
Abstract
BACKGROUND Follicular thyroid carcinoma (FTC), the second most prevalent thyroid cancer after papillary thyroid cancer (PTC), tends to metastasize distantly, leading to poorer outcomes. Despite substantial research, a holistic bibliometric analysis of FTC literature is lacking. This study aims to fill this gap by employing bibliometric methods to track FTC research evolution. METHODS English FTC publications were systematically gathered from the Web of Science. Bibliometric analysis, using R, VOSviewer, CiteSpace, and Excel, synthesized data and explored global research trends and topics. RESULTS From 2000 to 2023, 9086 authors from 1953 institutions across 75 countries contributed to 1776 papers in 491 academic journals on FTC. The last two decades have witnessed a steady increase in publications related to FTC, with the United States leading in terms of publication volume. The United States dominated both in publications and citations, with the National Cancer Institute and Sheue-Yann Cheng as leading contributors. The journal 'Thyroid' featured the most publications, while the 'Journal of Clinical Endocrinology and Metabolism' ranked highest in citation frequency. Research focused on gene expression analysis and preoperative diagnostics, with recent trends shifting toward prognosis management and machine learning due to advances in medical technology and increased health awareness. CONCLUSION This comprehensive bibliometric analysis has mapped the landscape of FTC research, highlighting key contributors, institutions, and thematic trends. Current discourse predominantly revolves around genetic analysis, prognostic determinants, and preoperative diagnostics in FTC. This foundational work guides future FTC research, providing insights into its evolution.
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Affiliation(s)
- Yuanyuan Fan
- Division of Thyroid Surgery, Department of General Surgery, West China Hospital, Sichuan University, Chengdu, China
| | - Xun Zheng
- Division of Thyroid Surgery, Department of General Surgery, West China Hospital, Sichuan University, Chengdu, China
| | - Tianfeng Xu
- Division of Thyroid Surgery, Department of General Surgery, West China Hospital, Sichuan University, Chengdu, China
| | - Pengyu Li
- Division of Thyroid Surgery, Department of General Surgery, West China Hospital, Sichuan University, Chengdu, China
| | - Yujie Zhang
- Division of Thyroid Surgery, Department of General Surgery, West China Hospital, Sichuan University, Chengdu, China
| | - Yanhao Ran
- Division of Thyroid Surgery, Department of General Surgery, West China Hospital, Sichuan University, Chengdu, China
| | - Tao Wei
- Division of Thyroid Surgery, Department of General Surgery, West China Hospital, Sichuan University, Chengdu, 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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Bojunga J, Trimboli P. Thyroid ultrasound and its ancillary techniques. Rev Endocr Metab Disord 2024; 25:161-173. [PMID: 37946091 DOI: 10.1007/s11154-023-09841-1] [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] [Accepted: 09/29/2023] [Indexed: 11/12/2023]
Abstract
Ultrasound (US) of the thyroid has been used as a diagnostic tool since the late 1960s. US is the most important imaging tool for diagnosing thyroid disease. In the majority of cases a correct diagnosis can already be made in synopsis of the sonographic together with clinical findings and basal thyroid hormone parameters. However, the characterization of thyroid nodules by US remains challenging. The introduction of Thyroid Imaging Reporting and Data Systems (TIRADSs) has improved diagnostic accuracy of thyroid cancer significantly. Newer techniques such as elastography, superb microvascular imaging (SMI), contrast enhanced ultrasound (CEUS) and multiparametric ultrasound (MPUS) expand diagnostic options and tools further. In addition, the use of artificial intelligence (AI) is a promising tool to improve and simplify diagnostics of thyroid nodules and there is evidence that AI can exceed the performance of humans. Combining different US techniques with the introduction of new software, the use of AI, FNB as well as molecular markers might pave the way for a completely new area of diagnostic accuracy in thyroid disease. Finally, interventional ultrasound using US-guided thermal ablation (TA) procedures are increasingly proposed as therapy options for benign as well as malignant thyroid diseases.
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Affiliation(s)
- Joerg Bojunga
- Department of Medicine I, Goethe University Hospital, Theodor-Stern-Kai 7, Frankfurt am Main, 60590, Germany.
| | - Pierpaolo Trimboli
- Servizio di Endocrinologia e Diabetologia, Ospedale Regionale di Lugano, Ente Ospedaliero Cantonale (EOC), Lugano, Switzerland
- Facoltà di Scienze Biomediche, Università della Svizzera Italiana (USI), Lugano, Switzerland
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Decaussin-Petrucci M, Cochand Priollet B, Leteurtre E, Albarel F, Borson-Chazot F. [SFE-AFCE-SFMN 2022 consensus on the management of thyroid nodules: Interest and place of thyroid cytology]. Ann Pathol 2024; 44:20-29. [PMID: 38092572 DOI: 10.1016/j.annpat.2023.10.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 10/09/2023] [Indexed: 02/07/2024]
Abstract
The SFE-AFCE-SFMN 2022 consensus deals with the management of thyroid nodules, a symptom that is a frequent reason for consultation in endocrinology. Thyroid nodules are very common and mostly benign. Thyroid ultrasound and thyroid fine-needle aspiration biopsy (FNAB) are the reference tests for the analysis of these nodules. The aim of this article is to describe for the cytopathologist the key points of the SFE-AFCE-SFMN 2022 consensus involving thyroid cytology: the indications for thyroid FNAB, the technique and analysis, and the management (treatment, follow-up) following this cytological screening examination, a key element in the management of the thyroid nodule.
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Affiliation(s)
- Myriam Decaussin-Petrucci
- Pathology department, centre hospitalier Lyon Sud, hospices civils de Lyon, Pierre Bénite, EA 3738, Lyon 1 University, Lyon, France.
| | | | - Emannuelle Leteurtre
- University of Lille, CNRS, Inserm, CHU de Lille, UMR9020-U1277 - CANTHER-Cancer Heterogeneity Plasticity and Resistance to Therapies, 59000 Lille, France
| | - Frédérique Albarel
- Service d'endocrinologie, Assistance publique-Hôpitaux de Marseille (AP-HM), hôpital de la Conception, centre de référence des maladies rares de l'hypophyse HYPO, 13005 Marseille, France
| | - Françoise Borson-Chazot
- Fédération d'endocrinologie, hospices civils de Lyon, groupement hospitalier Est, Bron, université Lyon 1, Claude-Bernard, Lyon, France
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Becker C, Hardarson J, Hoelzer A, Geisler A, Schulz T, Reichl C, Burton NC, Schuler T, Kohl P, Zgierski-Johnston C. Evaluation of cervical lymph nodes using multispectral optoacoustic tomography: a proof-of-concept study. Eur Arch Otorhinolaryngol 2023; 280:4657-4664. [PMID: 37354339 PMCID: PMC10477228 DOI: 10.1007/s00405-023-08073-y] [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: 01/23/2023] [Accepted: 06/14/2023] [Indexed: 06/26/2023]
Abstract
OBJECTIVES Examination of lymph nodes is one of the most common indications for imaging in the head and neck region. The purpose of this study is to evaluate whether multispectral optoacoustic tomography can be used to observe chromophore differences between benign and malignant neck lymph nodes. MATERIALS AND METHODS Proof-of-concept ex vivo study of resected cervical lymph nodes from 11 patients. The examination of lymph nodes included imaging with hybrid ultrasound and multispectral tomography system followed by spectral unmixing to separate signals from the endogenous chromophores water, lipid, hemoglobin and oxygenated hemoglobin; calculation of semi-quantitative parameters (total hemoglobin and relative oxygenation of hemoglobin). Comparison of the results from the hybrid measurement with the histopathological results. RESULTS Most patients suffered from squamous cell carcinoma (n = 7), also metastasis from salivary gland adenocarcinoma and papillary thyroid carcinoma, were included. The comparison between benign cervical lymph nodes and metastases showed significant differences for the absorbers water, lipid, hemoglobin and oxygenated hemoglobin and total hemoglobin. CONCLUSIONS Our ex vivo study suggests that multispectral optoacoustic tomography can be used to detect differences between reactive lymph nodes and metastases. The measurement of endogenous chromophores can be used for this purpose. The examinations are non-invasively and thus potentially improve diagnostic prediction. However, potential influences from the ex vivo setting must be considered.
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Affiliation(s)
- Christoph Becker
- Department of Otorhinolaryngology-Head and Neck Surgery, University Medical Centre Freiburg, University of Freiburg, Killianstrasse 5, 79106, Freiburg, Germany.
| | - Johannes Hardarson
- Department of Otorhinolaryngology-Head and Neck Surgery, University Medical Centre Freiburg, University of Freiburg, Killianstrasse 5, 79106, Freiburg, Germany
| | - Andrea Hoelzer
- Department of Otorhinolaryngology-Head and Neck Surgery, University Medical Centre Freiburg, University of Freiburg, Killianstrasse 5, 79106, Freiburg, Germany
| | - Antje Geisler
- Department of Otorhinolaryngology-Head and Neck Surgery, University Medical Centre Freiburg, University of Freiburg, Killianstrasse 5, 79106, Freiburg, Germany
| | - Tobias Schulz
- Department of Otorhinolaryngology-Head and Neck Surgery, University Medical Centre Freiburg, University of Freiburg, Killianstrasse 5, 79106, Freiburg, Germany
| | | | | | - Tobias Schuler
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg-Bad Krozingen, Freiburg, Germany
- Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Peter Kohl
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg-Bad Krozingen, Freiburg, Germany
- Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Callum Zgierski-Johnston
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg-Bad Krozingen, Freiburg, Germany
- Faculty of Medicine, University of Freiburg, Freiburg, Germany
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Chen F, Han H, Wan P, Liao H, Liu C, Zhang D. Joint Segmentation and Differential Diagnosis of Thyroid Nodule in Contrast-Enhanced Ultrasound Images. IEEE Trans Biomed Eng 2023; 70:2722-2732. [PMID: 37027278 DOI: 10.1109/tbme.2023.3262842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/08/2023]
Abstract
OBJECTIVE Microvascular perfusion can be observed in real time with contrast-enhanced ultrasound (CEUS), which is a novel ultrasound technology for visualizing the dynamic patterns of parenchymal perfusion. Automatic lesion segmentation and differential diagnosis of malignant and benign based on CEUS are crucial but challenging tasks for computer-aided diagnosis of thyroid nodule. METHODS To tackle these two formidable challenges concurrently, we provide Trans-CEUS, a spatial-temporal transformer-based CEUS analysis model to finish the joint learning of these two challenging tasks. Specifically, the dynamic swin-transformer encoder and multi-level feature collaborative learning are combined into U-net for achieving accurate segmentation of lesions with ambiguous boundary from CEUS. In addition, variant transformer-based global spatial-temporal fusion is proposed to obtain long-distance enhancement perfusion of dynamic CEUS for promoting differential diagnosis. RESULTS Empirical results of clinical data showed that our Trans-CEUS model achieved not only a good lesion segmentation result with a high Dice similarity coefficient of 82.41%, but also superior diagnostic accuracy of 86.59%. Conclusion & significance: This research is novel since it is the first to incorporate the transformer into CEUS analysis, and it shows promising results on dynamic CEUS datasets for both segmentation and diagnosis tasks of the thyroid nodule.
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Okasha HH, Mansor M, Sheriba N, Abdelfattah Y, Abdelfatah D, Orabi HE, Elebrashy IN, Saif A, Meligi AAE, Elshazli M, Elhadidy KE, Abushady MM, Islam EE, Yosef TM, Salama ASED, Ouf TI, Said SM, Eid YM, Mohsen AA, Rizk MN, Yousief E, Elrawi H, Ahmed TM, Roshdy E, Sedrak HK, Din HGE, Aboulsoud S, El-Sawy SS, El-Feki MA, Alzamzamy A, Elenin SA, Tag-Adeen M, Abdelhameed H, Awad A. Value of TI-RADS and elastography strain ratio in predicting malignant thyroid nodules: experience from a single center in Egypt. THE EGYPTIAN JOURNAL OF INTERNAL MEDICINE 2023; 35:45. [DOI: https:/doi.org/10.1186/s43162-023-00227-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2023] [Accepted: 06/04/2023] [Indexed: 11/04/2023] Open
Abstract
Abstract
Introduction
Thyroid nodules are highly prevalent in the general population; therefore, it is crucial to discriminate benign from malignant nodules. A practical thyroid imaging reporting and data system (TI-RADS) for thyroid nodules and ultrasound elastography are valuable tools not only for characterization of nodules but also for the selection of tumors for fine-needle aspiration cytology (FNAC).
Objective
This study aimed to evaluate the diagnostic accuracy of US evaluation in the prediction of malignant thyroid nodules and evaluate the role of the elastography score, strain ratio (SR), and the TI-RADS scoring system as non-invasive tools in differentiation between malignant and benign thyroid nodules.
Material and methods
A total of 1269 patients were evaluated between February 2017 and April 2020 by a single expert thyroid ultrasound operator. The final diagnosis was achieved from cytological and/or histological evaluation and follow-up for at least 1 year.
Results
There were 1088 females and 181 males with a mean age of 44 ± 10 SD. The final diagnosis was 1197 benign nodules and 72 malignant nodules. Most malignant nodules were scored elastography score 4 (83.3%) and TI-RADS category 5 (86.11%). We found that nodules with antero-posterior to transverse (A-P/T) diameter > 1, have 21 times more risk to be malignant than those with A-P/T diameter < 1, patients with solitary thyroid nodules have 4.5 times to develop malignancy compared to those with multinodular goiter (MNG), nodules with absent halo have 4 times more risk of malignancy. Furthermore, microcalcifications in thyroid nodules increase the risk of malignancy 9 times compared to those without calcifications. SR was found to be an excellent discriminator to differentiate between benign and malignant nodules with P < 0.001. Also, we found that for every unit increase in SR, the risk of malignancy increased by 20%. We reported that the accuracy of ultrasonography in the detection of malignant thyroid nodules had a sensitivity of 89%, specificity of 98%, 70% PPV, and 99.3% NPV, with an overall accuracy of 97.2%.
Conclusion
The application of ultrasonographic non-invasive criteria for thyroid nodules in clinical practice might significantly reduce the number of unnecessary FNAC. Elastography, SR, and TI-RADS classification could be good predictors for malignant thyroid nodules.
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Fu C, Cui Y, Li J, Yu J, Wang Y, Si C, Cui K. Effect of the categorization method on the diagnostic performance of ultrasound risk stratification systems for thyroid nodules. Front Oncol 2023; 13:1073891. [PMID: 37182157 PMCID: PMC10167303 DOI: 10.3389/fonc.2023.1073891] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 04/13/2023] [Indexed: 05/16/2023] Open
Abstract
Objective To evaluate whether the categorization methods of risk stratification systems (RSSs) is a decisive factor that influenced the diagnostic performances and unnecessary FNA rates in order to choose optimal RSS for the management of thyroid nodules. Methods From July 2013 to January 2019, 2667 patients with 3944 thyroid nodules had undergone pathological diagnosis after thyroidectomy and/or US-guided FNA. US categories were assigned according to the six RSSs. The diagnostic performances and unnecessary FNA rates were calculated and compared according to the US-based final assessment categories and the unified size thresholds for biopsy proposed by ACR-TIRADS, respectively. Results A total of 1781 (45.2%) thyroid nodules were diagnosed as malignant after thyroidectomy or biopsy. Significantly lowest specificity and accuracy, along with the highest unnecessary FNA rates were seen in EU-TIRADS for both US categories (47.9%, 70.2%, and 39.4%, respectively, all P < 0.05) and indications for FNA (54.2%, 50.0%, and 55.4%, respectively, all P < 0.05). Diagnostic performances for US-based final assessment categories exhibited similar accuracy for AI-TIRADS, Kwak-TIRADS, C-TIRADS, and ATA guidelines (78.0%, 77.8%, 77.9%, and 76.3%, respectively, all P > 0.05), while the lowest unnecessary FNA rate was seen in C-TIRADS (30.9%) and without significant differences to that of AI-TIRADS, Kwak-TIRADS, and ATA guideline (31.5%, 31.7%, and 33.6%, respectively, all P > 0.05). Diagnostic performance for US-FNA indications showed similar accuracy for ACR-TIRADS, Kwak-TIRADS, C-TIRADS and ATA guidelines (58.0%, 59.7%, 58.7%, and 57.1%, respectively, all P > 0.05). The highest accuracy and lowest unnecessary FNA rate were seen in AI-TIRADS (61.9%, 38.6%) and without significant differences to that of Kwak-TIRADS(59.7%, 42.9%) and C-TIRADS 58.7%, 43.9%, all P > 0.05). Conclusion The different US categorization methods used by each RSS were not determinant influential factors in diagnostic performance and unnecessary FNA rate. For daily clinical practice, the score-based counting RSS was an optimal choice.
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Affiliation(s)
- Chao Fu
- Department of Ultrasound, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yiyang Cui
- Department of Ultrasound, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jing Li
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jing Yu
- Department of Ultrasound, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yan Wang
- Department of Ultrasound, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Caifeng Si
- Department of Ultrasound, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Kefei Cui
- Department of Ultrasound, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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Liu L, Jia C, Li G, Shi Q, Du L, Wu R. Nomogram incorporating preoperative clinical and ultrasound indicators to predict aggressiveness of solitary papillary thyroid carcinoma. Front Oncol 2023; 13:1009958. [PMID: 36798828 PMCID: PMC9927212 DOI: 10.3389/fonc.2023.1009958] [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: 08/02/2022] [Accepted: 01/16/2023] [Indexed: 02/04/2023] Open
Abstract
Objective To construct a nomogram based on preoperative clinical and ultrasound indicators to predict aggressiveness of solitary papillary thyroid carcinoma (PTC). Methods Preoperative clinical and ultrasound data from 709 patients diagnosed with solitary PTC between January 2017 and December 2020 were analyzed retrospectively. Univariate and multivariate logistic regression analyses were performed to identify the factors associated with PTC aggressiveness, and these factors were used to construct a predictive nomogram. The nomogram's performance was evaluated in the primary and validation cohorts. Results The 709 patients were separated into a primary cohort (n = 424) and a validation cohort (n = 285). Univariate analysis in the primary cohort showed 13 variables to be associated with aggressive PTC. In multivariate logistic regression analysis, the independent predictors of aggressive behavior were age (OR, 2.08; 95% CI, 1.30-3.35), tumor size (OR, 4.0; 95% CI, 2.17-7.37), capsule abutment (OR, 2.53; 95% CI, 1.50-4.26), and suspected cervical lymph nodes metastasis (OR, 2.50; 95% CI, 1.20-5.21). The nomogram incorporating these four predictors showed good discrimination and calibration in both the primary cohort (area under the curve, 0.77; 95% CI, 0.72-0.81; Hosmer-Lemeshow test, P = 0.967 and the validation cohort (area under the curve, 0.72; 95% CI, 0.66-0.78; Hosmer-Lemeshow test, P = 0.251). Conclusion The proposed nomogram shows good ability to predict PTC aggressiveness and could be useful during treatment decision making. Advances in knowledge Our nomogram-based on four indicators-provides comprehensive assessment of aggressive behavior of PTC and could be a useful tool in the clinic.
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Affiliation(s)
- Long Liu
- Department of Ultrasound, Shanghai General Hospital of Nanjing Medical University, Shanghai, China,Department of Ultrasound, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chao Jia
- Department of Ultrasound, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Gang Li
- Department of Ultrasound, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qiusheng Shi
- Department of Ultrasound, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lianfang Du
- Department of Ultrasound, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Rong Wu
- Department of Ultrasound, Shanghai General Hospital of Nanjing Medical University, Shanghai, China,Department of Ultrasound, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China,*Correspondence: Rong Wu,
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Sorrenti S, Lauro A, Pironi D, Calò PG, Ulisse S. Editorial: Differential diagnoses of thyroid neoplasms: Molecular and histological features and the impact on follow-up. Front Oncol 2023; 13:1125887. [PMID: 36798815 PMCID: PMC9927641 DOI: 10.3389/fonc.2023.1125887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Accepted: 01/19/2023] [Indexed: 02/04/2023] Open
Affiliation(s)
| | - Augusto Lauro
- Department of Surgery, “Sapienza” University of Rome, Rome, Italy
| | - Daniele Pironi
- Department of Surgery, “Sapienza” University of Rome, Rome, Italy
| | - Pietro Giorgio Calò
- Department of Surgical Sciences, University of Cagliari, Monserrato, Cagliari, Italy
| | - Salvatore Ulisse
- Department of Surgery, “Sapienza” University of Rome, Rome, Italy,*Correspondence: Salvatore Ulisse,
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Gao X, Ran X, Ding W. The progress of radiomics in thyroid nodules. Front Oncol 2023; 13:1109319. [PMID: 36959790 PMCID: PMC10029726 DOI: 10.3389/fonc.2023.1109319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Accepted: 02/03/2023] [Indexed: 03/09/2023] Open
Abstract
Due to the development of Artificial Intelligence (AI), Machine Learning (ML), and the improvement of medical imaging equipment, radiomics has become a popular research in recent years. Radiomics can obtain various quantitative features from medical images, highlighting the invisible image traits and significantly enhancing the ability of medical imaging identification and prediction. The literature indicates that radiomics has a high potential in identifying and predicting thyroid nodules. So in this article, we explain the development, definition, and workflow of radiomics. And then, we summarize the applications of various imaging techniques in identifying benign and malignant thyroid nodules, predicting invasiveness and metastasis of thyroid lymph nodes, forecasting the prognosis of thyroid malignancies, and some new advances in molecular level and deep learning. The shortcomings of this technique are also summarized, and future development prospects are provided.
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Affiliation(s)
| | - Xuan Ran
- *Correspondence: Wei Ding, ; Xuan Ran,
| | - Wei Ding
- *Correspondence: Wei Ding, ; Xuan Ran,
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13
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Lin X, Zhou X, Tong T, Nie X, Wang L, Zheng H, Li J, Xue E, Chen S, Zheng M, Chen C, Jiang H, Du M, Gao Q. A Super-resolution Guided Network for Improving Automated Thyroid Nodule Segmentation. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2022; 227:107186. [PMID: 36334526 DOI: 10.1016/j.cmpb.2022.107186] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 10/03/2022] [Accepted: 10/15/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND AND OBJECTIVE A thyroid nodule is an abnormal lump that grows in the thyroid gland, which is the early symptom of thyroid cancer. In order to diagnose and treat thyroid cancer at the earliest stage, it is desired to characterize the nodule accurately. Ultrasound thyroid nodules segmentation is a challenging task due to the speckle noise, intensity heterogeneity, low contrast and low resolution. In this paper, we propose a novel framework to improve the accuracy of thyroid nodules segmentation. METHODS Different from previous work, a super-resolution reconstruction network is firstly constructed to upscale the resolution of the input ultrasound image. After that, our proposed N-shape network is utilized to perform the segmentation task. The guidance of super-resolution reconstruction network can make the high-frequency information of the input thyroid ultrasound image richer and more comprehensive than the original image. Our N-shape network consists of several atrous spatial pyramid pooling blocks, a multi-scale input layer, a U-shape convolutional network with attention blocks and a proposed parallel atrous convolution(PAC) module. These modules are conducive to capture context information at multiple scales so that semantic features can be fully utilized for lesion segmentation. Especially, our proposed PAC module is beneficial to further improve the segmentation by extracting high-level semantic features from different receptive fields. We use the UTNI-2021 dataset for model training, validating and testing. RESULTS The experimental results show that our proposed method achieve a Dice value of 91.9%, a mIoU value of 87.0%, a Precision value of 88.0%, a Recall value 83.7% and a F1-score value of 84.3%, which outperforms most state-of-the-art methods. CONCLUSIONS Our method achieves the best performance on the UTNI-2021 dataset and provides a new way of ultrasound image segmentation. We believe that our method can provide doctors with reliable auxiliary diagnosis information in clinical practice.
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Affiliation(s)
- Xingtao Lin
- College of Physics and Information Engineering, Fuzhou University; Fujian Key Lab of Medical Instrumentation & Pharmaceutical Technology, Fuzhou University
| | - Xiaogen Zhou
- College of Physics and Information Engineering, Fuzhou University; Fujian Key Lab of Medical Instrumentation & Pharmaceutical Technology, Fuzhou University
| | - Tong Tong
- College of Physics and Information Engineering, Fuzhou University; Fujian Key Lab of Medical Instrumentation & Pharmaceutical Technology, Fuzhou University; Imperial Vision Technology.
| | - Xingqing Nie
- College of Physics and Information Engineering, Fuzhou University; Fujian Key Lab of Medical Instrumentation & Pharmaceutical Technology, Fuzhou University
| | - Luoyan Wang
- College of Physics and Information Engineering, Fuzhou University; Fujian Key Lab of Medical Instrumentation & Pharmaceutical Technology, Fuzhou University
| | - Haonan Zheng
- College of Physics and Information Engineering, Fuzhou University; Fujian Key Lab of Medical Instrumentation & Pharmaceutical Technology, Fuzhou University
| | - Jing Li
- College of Physics and Information Engineering, Fuzhou University; Fujian Key Lab of Medical Instrumentation & Pharmaceutical Technology, Fuzhou University
| | | | - Shun Chen
- Fujian Medical University Union Hospital.
| | | | - Cong Chen
- Fujian Medical University Union Hospital
| | - Haiyan Jiang
- Fujian Key Lab of Medical Instrumentation & Pharmaceutical Technology, Fuzhou University
| | - Min Du
- College of Physics and Information Engineering, Fuzhou University; Fujian Key Lab of Medical Instrumentation & Pharmaceutical Technology, Fuzhou University
| | - Qinquan Gao
- College of Physics and Information Engineering, Fuzhou University; Fujian Key Lab of Medical Instrumentation & Pharmaceutical Technology, Fuzhou University; Imperial Vision Technology
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14
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Nabahati M, Moazezi Z. Malignancy risk stratification of thyroid nodules smaller than 10 mm with ACR-TIRADS, K-TIRADS, and ATA-2015 guidelines: a prospective study. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2022. [DOI: 10.1186/s43055-022-00802-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
Small thyroid nodules (≤ 10 mm) are common findings in thyroid ultrasonography. The first purpose of this study was to compare the performance of three guidelines in the diagnosis of malignancy for small thyroid nodules. The second aim was to find the ultrasonographic characteristics potentially associated with the risk of malignancy. This prospective cross-sectional study was performed on the patients with a diagnosis of small thyroid nodules (≤ 10 mm), who were rereferred to the radiologists for sonography and FNA. Sonographic features were recorded and scored according to the American College of Radiology-Thyroid Imaging Reporting and Data System (ACR-TIRADS), American Thyroid Association (ATA-2015), and Korean-TIRADS (K-TIRADS). Finally, FNA was conducted and cytological findings were reported.
Results
In total, 287 thyroid nodules from 256 subjects (64 men and 192 women) were finally included in the study. The accuracy of ACR-TIRADS categories TR5 and TR4/5 was 88.9% and 72.1%, respectively. This rate for ATA-2015 classes high suspicion and intermediate suspicion/high suspicion was 88.9% and 82.6%, respectively. For K-TIRADS classes 5 and 4/5, the diagnostic accuracy was 89.6% and 82.9%, respectively. Significant direct associations were found between malignancy and punctate echogenic foci (odds ratio [OR] = 6.46), hypoechogenicity (OR = 6.39), ill-defined margin (OR = 4.38), and irregular margin (OR = 7.33).
Conclusion
The differences in the strength of the three guidelines in the prediction of the malignancy should be considered by clinicians and radiologists in the management of thyroid nodules smaller than 10 mm.
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15
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Decaussin-Petrucci M, Albarel F, Leteurtre E, Borson-Chazot F, Cochand Priollet B. SFE-AFCE-SFMN 2022 Consensus on the management of thyroid nodules : Recommendations in thyroid cytology: from technique to interpretation. ANNALES D'ENDOCRINOLOGIE 2022; 83:389-394. [PMID: 36283459 DOI: 10.1016/j.ando.2022.10.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
The SFE-AFCE-SFMN 2022 consensus deals with the management of thyroid nodules, a condition that is a frequent reason for consultation in endocrinology. In more than 90% of cases, patients are euthyroid, with benign non-progressive nodules that do not warrant specific treatment. The clinician's objective is to detect malignant thyroid nodules at risk of recurrence and death, toxic nodules responsible for hyperthyroidism or compressive nodules warranting treatment. The diagnosis and treatment of thyroid nodules requires close collaboration between endocrinologists, nuclear medicine physicians and surgeons, but also involves other specialists. Therefore, this consensus statement was established jointly by 3 societies: the French Society of Endocrinology (SFE), French Association of Endocrine Surgery (AFCE) and French Society of Nuclear Medicine (SFMN); the various working groups included experts from other specialties (pathologists, radiologists, pediatricians, biologists, etc.). This section deals with the technique and interpretation of thyroid fine-needle aspiration biopsy (FNAB), a reference test for the analysis of thyroid nodules.
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Affiliation(s)
- M Decaussin-Petrucci
- Pathology Department, Centre Hospitalier Lyon Sud, Hospices Civils de Lyon, Pierre Bénite, France, EA 3738, Lyon 1 University, Lyon, France.
| | - F Albarel
- Service d'Endocrinologie, Assistance Publique-Hôpitaux de Marseille (AP-HM), Hôpital de la Conception, Centre de Référence des Maladies Rares de l'Hypophyse HYPO, 13005 Marseille, France
| | - E Leteurtre
- University Lille, CNRS, Inserm, CHU Lille, UMR9020-U1277 - CANTHER-Cancer Heterogeneity Plasticity and Resistance to Therapies, 59000 Lille, France
| | - F Borson-Chazot
- Fédération d'Endocrinologie, Hospices Civils de Lyon, Groupement Hospitalier Est, Bron, France; Université Lyon 1, Claude Bernard, Lyon, France
| | - B Cochand Priollet
- Hôpital Cochin, Paris 75014, France; APHP Centre; université Paris-Cité, Paris, France
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16
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Combined Shear Wave Elastography and EU TIRADS in Differentiating Malignant and Benign Thyroid Nodules. Cancers (Basel) 2022; 14:cancers14225521. [PMID: 36428614 PMCID: PMC9688054 DOI: 10.3390/cancers14225521] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 11/04/2022] [Accepted: 11/07/2022] [Indexed: 11/12/2022] Open
Abstract
Although multimodal ultrasound approaches have been suggested to potentially improve the diagnosis of thyroid cancer; the diagnostic utility of the combination of SWE and malignancy-risk stratification systems remains vague due to the lack of standardized criteria. The purpose of the study was to assess the diagnostic value of the combination of grey scale ultrasound assessment using EU TIRADS and shear wave elastography. 121 patients (126 nodules−81 benign; 45 malignant) underwent grey scale ultrasound and SWE imaging of nodules between 0.5 cm and 5 cm prior to biopsy and/or surgery. Nodules were analyzed based on size stratifications: <1 cm (n = 43); 1−2 cm (n = 52) and >2 cm (n = 31) and equivocal cytology status (n = 52), and diagnostic performance assessments were conducted. The combination of EU TIRADS with SWE using the SD parameter; maintained a high sensitivity and significantly improved the specificity of sole EU TIRADS for nodules 1−2 cm (SEN: 72.2% vs. 88.9%, p > 0.05; SPEC: 76.5% vs. 55.9%, p < 0.01) and >2 cm (SEN: 71.4% vs. 85.7%, p > 0.05; SPEC: 95.8% vs. 62.5%, p < 0.01). For cytologically-equivocal nodules; the combination with the SWE minimum parameter resulted in a significant reduction in sensitivity with increased specificity (SEN: 60% vs. 80%; SPEC: 83.4% vs. 37.8%; all p < 0.05). SWE in combination with EU TIRADS is diagnostically efficient in discriminating nodules > 1 cm but is not ideal for discriminating cytologically-equivocal nodules.
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17
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Torregrossa L, Poma AM, Macerola E, Rago T, Vignali P, Romani R, Proietti A, Di Stefano I, Scuotri G, Ugolini C, Basolo A, Antonelli A, Materazzi G, Santini F, Basolo F. The Italian Consensus for the Classification and Reporting of Thyroid Cytology: Cytohistologic and molecular correlations on 37,371 nodules from a single institution. Cancer Cytopathol 2022; 130:899-912. [PMID: 35789118 PMCID: PMC9796474 DOI: 10.1002/cncy.22618] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 06/10/2022] [Accepted: 06/14/2022] [Indexed: 01/01/2023]
Abstract
BACKGROUND The Italian Consensus for the Classification and Reporting of Thyroid Cytology (ICCRTC) includes six diagnostic categories (TIR 1/1C, TIR 2, TIR 3A, TIR 3B, TIR 4, and TIR 5), each indicating a different risk of malignancy. The objective of this monocentric retrospective study was to evaluate the distribution of the ICCRTC classes at the authors' institution and assess their cytohistologic correlations. METHODS The authors retrospectively collected 37,371 consecutive cytologic reports of thyroid nodules and described the clinical-pathologic features of the different cytologic categories. The cytologic diagnoses also were compared with histologic outcomes in a subset of patients. RESULTS The cytologic classes were distributed as follows: nondiagnostic, 15.6%; benign, 66.5%; low-risk indeterminate, 10% (TIR 3A); high-risk indeterminate, 3.5% (TIR 3B); suspicious, 1.7%; and malignant, 2.6%. According to histology, the risk of malignancy was very high in the nondiagnostic category (29.8%), with young male patients more exposed to malignancy, and it was relatively high among benign (7.8%) and indeterminate nodules (32.5% in TIR 3A; 52.1% in TIR 3B), mainly because of the high prevalence of follicular architecture in malignant tumors. On histology, the malignancy rates were 92.4% and 99.3% for the suspicious and malignant categories, respectively; aggressive variants of papillary thyroid carcinoma were mostly diagnosed in these categories. CONCLUSIONS In this series, nondiagnostic nodules showed high prevalence and, surprisingly, high malignancy rates. Malignant tumors with follicular architecture represented a diagnostic pitfall in benign and indeterminate nodules. The suspicious and malignant categories had high specificity for malignancy. Importantly, the ICCRTC had high reliability for identifying preoperatively aggressive histotypes of thyroid carcinoma.
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Affiliation(s)
- Liborio Torregrossa
- Department of Surgical, Medical, Molecular Pathology and Clinical AreaUniversity of PisaPisaItaly
| | - Anello Marcello Poma
- Department of Surgical, Medical, Molecular Pathology and Clinical AreaUniversity of PisaPisaItaly
| | - Elisabetta Macerola
- Department of Surgical, Medical, Molecular Pathology and Clinical AreaUniversity of PisaPisaItaly
| | - Teresa Rago
- Department of Clinical and Experimental MedicineUniversity of PisaPisaItaly
| | - Paola Vignali
- Department of Surgical, Medical, Molecular Pathology and Clinical AreaUniversity of PisaPisaItaly
| | - Rossana Romani
- Section of PathologyUniversity Hospital of PisaPisaItaly
| | | | - Iosè Di Stefano
- Department of Surgical, Medical, Molecular Pathology and Clinical AreaUniversity of PisaPisaItaly
| | | | - Clara Ugolini
- Department of Surgical, Medical, Molecular Pathology and Clinical AreaUniversity of PisaPisaItaly
| | - Alessio Basolo
- Department of Clinical and Experimental MedicineUniversity of PisaPisaItaly
| | - Alessandro Antonelli
- Department of Surgical, Medical, Molecular Pathology and Clinical AreaUniversity of PisaPisaItaly
| | - Gabriele Materazzi
- Department of Surgical, Medical, Molecular Pathology and Clinical AreaUniversity of PisaPisaItaly
| | - Ferruccio Santini
- Department of Clinical and Experimental MedicineUniversity of PisaPisaItaly
| | - Fulvio Basolo
- Department of Surgical, Medical, Molecular Pathology and Clinical AreaUniversity of PisaPisaItaly
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18
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Brandenstein M, Wiesinger I, Künzel J, Hornung M, Stroszczynski C, Jung EM. Multiparametric Sonographic Imaging of Thyroid Lesions: Chances of B-Mode, Elastography and CEUS in Relation to Preoperative Histopathology. Cancers (Basel) 2022; 14:cancers14194745. [PMID: 36230668 PMCID: PMC9564296 DOI: 10.3390/cancers14194745] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 09/21/2022] [Accepted: 09/23/2022] [Indexed: 12/03/2022] Open
Abstract
Simple Summary As the incidence of thyroid lesions in Europe is rising, more and more people affected by thyroid pathologies seek treatment in a clinic. Every suspicious thyroid nodule needs to be confirmed as benign or malignant in order to be treated correctly. Unnecessary invasive diagnostics and thyroid surgery should be avoided. The aim of this retrospective study was to improve the distinction between benign and malignant nodules by using new high-performance multiparametric ultrasound examination techniques. By analyzing 122 thyroid nodules we created a score-based system combining B-mode, shear-wave elastography and contrast-enhanced ultrasound malignancy criteria. This system allows for a quite accurate detection of thyroid carcinomas with a sensitivity of 95% and specificity of 75.49%. Shear-wave elastography and contrast-enhanced ultrasound can detect unique malignancy features, which cannot be found in B-mode. Therefore, these criteria would present a relevant addition to the B-mode TI-RADS classification. Abstract Background: The aim was to improve preoperative diagnostics of solid non-cystic thyroid lesions by using new high-performance multiparametric ultrasound examination techniques. Methods: Multiparametric ultrasound consists of B-mode, shear-wave elastography and contrast enhanced ultrasound (CEUS) including Time-Intensity-Curve (TIC) analysis. A bolus of 1–2.4 mL Sulfur Hexafluorid microbubbles was injected for CEUS. Postoperative histopathology was the diagnostic gold standard. Results: 116 patients were included in this study. 102 benign thyroid nodules were diagnosed as well as 20 carcinomas. Suspicious B-mode findings like microcalcifications, a blurry edge and no homogeneous sonomorphological structure were detected in 60, 75 and 80% of all carcinomas but only in 13.7, 36.3 and 46.1% of all benign lesions. The average shear-wave elastography measurements of malignant lesions (4.6 m/s or 69.8 kPa centrally and 4.2 m/s or 60.1 kPa marginally) exceed the values of benign nodules. Suspicious CEUS findings like a not-homogeneous wash-in and a wash-out were detected almost twice as often in carcinomas. Conclusion: Multiparametric ultrasound offers new possibilities for the preoperative distinction between benign and malignant thyroid nodules. A score based system of B-mode, shear-wave and CEUS malignancy criteria shows promising results in the detection of thyroid carcinomas. It reaches a sensitivity of 95% and specificity of 75.49%.
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Affiliation(s)
- Moritz Brandenstein
- Institute of Diagnostic Radiology, Interdisciplinary Ultrasound Department, University Hospital, 93053 Regensburg, Germany
- Correspondence: ; Tel.: +49-17-647-793-303
| | - Isabel Wiesinger
- Institute of Diagnostic Radiology, Interdisciplinary Ultrasound Department, University Hospital, 93053 Regensburg, Germany
| | - Julian Künzel
- Department of Otorhinolaryngology, Head and Neck Surgery, University Hospital of Regensburg, 93053 Regensburg, Germany
| | - Matthias Hornung
- Department of Surgery, University Hospital, 93053 Regensburg, Germany
| | - Christian Stroszczynski
- Institute of Diagnostic Radiology, Interdisciplinary Ultrasound Department, University Hospital, 93053 Regensburg, Germany
| | - Ernst-Michael Jung
- Institute of Diagnostic Radiology, Interdisciplinary Ultrasound Department, University Hospital, 93053 Regensburg, Germany
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19
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Bellini MI, Lori E, Forte F, Lauro A, Tripodi D, Amabile MI, Cantisani V, Varanese M, Ferent IC, Baldini E, Ulisse S, D’Andrea V, Pironi D, Sorrenti S. Thyroid and renal cancers: A bidirectional association. Front Oncol 2022; 12:951976. [PMID: 36212468 PMCID: PMC9538481 DOI: 10.3389/fonc.2022.951976] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 08/22/2022] [Indexed: 12/01/2022] Open
Abstract
There is a deep interrelation between the thyroid gland and the kidney parenchyma, with dysfunction of the first leading to significant changes in renal metabolism and vice versa. Given the recognition of cancer as a systemic disease, the raise of thyroid tumors and the common association of several malignancies, such as breast cancer, prostate cancer, colorectal cancer, and other, with an increased risk of kidney disease, public health alert for these conditions is warranted. A systematic review of the current evidence on the bidirectional relationship between thyroid and renal cancers was conducted including 18 studies, highlighting patient’s characteristics, histology, time for secondary malignancy to develop from the first diagnosis, treatment, and follow-up. A total of 776 patients were identified; median age was 64 years (range: 7–76 years). Obesity and family history were identified as the most common risk factors, and genetic susceptibility was suggested with a potential strong association with Cowden syndrome. Controversy on chemo and radiotherapy effects was found, as not all patients were previously exposed to these treatments. Men were more likely to develop kidney cancer after a primary thyroid malignancy, with 423/776 (54%) experiencing renal disease secondarily. Median time after the first malignancy was 5.2 years (range: 0–20 years). With the advancement of current oncological therapy, the prognosis for thyroid cancer patients has improved, although there has been a corresponding rise in the incidence of multiple secondary malignancy within the same population, particularly concerning the kidney. Surgery can achieve disease-free survival, if surveillance follow-up allows for an early localized form, where radical treatment is recommended.
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Affiliation(s)
- Maria Irene Bellini
- Department of Surgical Sciences, Sapienza University of Rome, Rome, Italy
- *Correspondence: Maria Irene Bellini,
| | - Eleonora Lori
- Department of Surgical Sciences, Sapienza University of Rome, Rome, Italy
| | - Flavio Forte
- Department of Urology, M. G. Vannini Hospital, Rome, Italy
| | - Augusto Lauro
- Department of Surgical Sciences, Sapienza University of Rome, Rome, Italy
| | - Domenico Tripodi
- Department of Surgical Sciences, Sapienza University of Rome, Rome, Italy
| | - Maria Ida Amabile
- Department of Surgical Sciences, Sapienza University of Rome, Rome, Italy
| | - Vito Cantisani
- Department of Radiological, Anatomopathological and Oncological Sciences, Sapienza University of Rome, Rome, Italy
| | - Marzia Varanese
- Department of Surgical Sciences, Sapienza University of Rome, Rome, Italy
| | | | - Enke Baldini
- Department of Surgical Sciences, Sapienza University of Rome, Rome, Italy
| | - Salvatore Ulisse
- Department of Surgical Sciences, Sapienza University of Rome, Rome, Italy
| | - Vito D’Andrea
- Department of Surgical Sciences, Sapienza University of Rome, Rome, Italy
| | - Daniele Pironi
- Department of Surgical Sciences, Sapienza University of Rome, Rome, Italy
| | - Salvatore Sorrenti
- Department of Surgical Sciences, Sapienza University of Rome, Rome, Italy
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20
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Ulisse S, Baldini E, Pironi D, Gagliardi F, Tripodi D, Lauro A, Carbotta S, Tarroni D, D’Armiento M, Morrone A, Forte F, Frattaroli F, Persechino S, Odorisio T, D’Andrea V, Lori E, Sorrenti S. Is Melanoma Progression Affected by Thyroid Diseases? Int J Mol Sci 2022; 23:ijms231710036. [PMID: 36077430 PMCID: PMC9456309 DOI: 10.3390/ijms231710036] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 08/25/2022] [Accepted: 08/31/2022] [Indexed: 11/16/2022] Open
Abstract
Clinical and epidemiological evidence indicate a relationship between thyroid diseases and melanoma. In particular, the hypothyroidism condition appears to promote melanoma spread, which suggests a protective role of thyroid hormones against disease progression. In addition, experimental data suggest that, in addition to thyroid hormones, other hormonal players of the hypothalamic–pituitary–thyroid (HPT) axis, namely the thyrotropin releasing hormone and the thyrotropin, are likely to affect melanoma cells behavior. This information warrants further clinical and experimental studies in order to build a precise pattern of action of the HPT hormones on melanoma cells. An improved knowledge of the involved molecular mechanism(s) could lead to a better and possibly personalized clinical management of these patients.
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Affiliation(s)
- Salvatore Ulisse
- Department of Surgical Sciences, “Sapienza” University of Rome, 00161 Rome, Italy
- Correspondence:
| | - Enke Baldini
- Department of Surgical Sciences, “Sapienza” University of Rome, 00161 Rome, Italy
| | - Daniele Pironi
- Department of Surgical Sciences, “Sapienza” University of Rome, 00161 Rome, Italy
| | - Federica Gagliardi
- Department of Surgical Sciences, “Sapienza” University of Rome, 00161 Rome, Italy
| | - Domenico Tripodi
- Department of Surgical Sciences, “Sapienza” University of Rome, 00161 Rome, Italy
| | - Augusto Lauro
- Department of Surgical Sciences, “Sapienza” University of Rome, 00161 Rome, Italy
| | - Sabino Carbotta
- Department of Surgical Sciences, “Sapienza” University of Rome, 00161 Rome, Italy
| | - Danilo Tarroni
- Department of Surgical Sciences, “Sapienza” University of Rome, 00161 Rome, Italy
| | - Matteo D’Armiento
- Scientific Direction, IRCCS San Gallicano Dermatological Institute, 00144 Rome, Italy
| | - Aldo Morrone
- Scientific Direction, IRCCS San Gallicano Dermatological Institute, 00144 Rome, Italy
| | - Flavio Forte
- Urology Department, M.G. Vannini Hospital, 00177 Rome, Italy
| | - Flaminia Frattaroli
- Department of Surgical Sciences, “Sapienza” University of Rome, 00161 Rome, Italy
| | - Severino Persechino
- Department of Neurosciences, Mental Health and Sensory Organs, “Sapienza” University of Rome, 00161 Rome, Italy
| | - Teresa Odorisio
- Laboratory of Molecular and Cell Biology, Istituto Dermopatico dell’Immacolata, IDI-IRCCS, 00167 Rome, Italy
| | - Vito D’Andrea
- Department of Surgical Sciences, “Sapienza” University of Rome, 00161 Rome, Italy
| | - Eleonora Lori
- Department of Surgical Sciences, “Sapienza” University of Rome, 00161 Rome, Italy
| | - Salvatore Sorrenti
- Department of Surgical Sciences, “Sapienza” University of Rome, 00161 Rome, Italy
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21
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Sorrenti S, Dolcetti V, Radzina M, Bellini MI, Frezza F, Munir K, Grani G, Durante C, D’Andrea V, David E, Calò PG, Lori E, Cantisani V. Artificial Intelligence for Thyroid Nodule Characterization: Where Are We Standing? Cancers (Basel) 2022; 14:cancers14143357. [PMID: 35884418 PMCID: PMC9315681 DOI: 10.3390/cancers14143357] [Citation(s) in RCA: 40] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 06/24/2022] [Accepted: 07/08/2022] [Indexed: 12/12/2022] Open
Abstract
Simple Summary In the present review, an up-to-date summary of the state of the art of artificial intelligence (AI) implementation for thyroid nodule characterization and cancer is provided. The opinion on the real effectiveness of AI systems remains controversial. Taking into consideration the largest and most scientifically valid studies, it is possible to state that AI provides results that are comparable or inferior to expert ultrasound specialists and radiologists. Promising data approve AI as a support tool and simultaneously highlight the need for a radiologist supervisory framework for AI provided results. Therefore, current solutions might be more suitable for educational purposes. Abstract Machine learning (ML) is an interdisciplinary sector in the subset of artificial intelligence (AI) that creates systems to set up logical connections using algorithms, and thus offers predictions for complex data analysis. In the present review, an up-to-date summary of the current state of the art regarding ML and AI implementation for thyroid nodule ultrasound characterization and cancer is provided, highlighting controversies over AI application as well as possible benefits of ML, such as, for example, training purposes. There is evidence that AI increases diagnostic accuracy and significantly limits inter-observer variability by using standardized mathematical algorithms. It could also be of aid in practice settings with limited sub-specialty expertise, offering a second opinion by means of radiomics and computer-assisted diagnosis. The introduction of AI represents a revolutionary event in thyroid nodule evaluation, but key issues for further implementation include integration with radiologist expertise, impact on workflow and efficiency, and performance monitoring.
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Affiliation(s)
- Salvatore Sorrenti
- Department of Surgical Sciences, “Sapienza” University of Rome, 00161 Rome, Italy; (S.S.); (V.D.); (E.L.)
| | - Vincenzo Dolcetti
- Department of Radiological, Anatomo-Pathological Sciences, “Sapienza” University of Rome, 00161 Rome, Italy; (V.D.); (V.C.)
| | - Maija Radzina
- Radiology Research Laboratory, Riga Stradins University, LV-1007 Riga, Latvia;
- Medical Faculty, University of Latvia, Diagnostic Radiology Institute, Paula Stradina Clinical University Hospital, LV-1007 Riga, Latvia
| | - Maria Irene Bellini
- Department of Surgical Sciences, “Sapienza” University of Rome, 00161 Rome, Italy; (S.S.); (V.D.); (E.L.)
- Correspondence:
| | - Fabrizio Frezza
- Department of Information Engineering, Electronics and Telecommunications, “Sapienza” University of Rome, 00184 Rome, Italy; (F.F.); (K.M.)
- Consorzio Nazionale Interuniversitario per le Telecomunicazioni (CNIT), Viale G.P. Usberti 181/A Sede Scientifica di Ingegneria-Palazzina 3, 43124 Parma, Italy
| | - Khushboo Munir
- Department of Information Engineering, Electronics and Telecommunications, “Sapienza” University of Rome, 00184 Rome, Italy; (F.F.); (K.M.)
| | - Giorgio Grani
- Department of Translational and Precision Medicine, “Sapienza” University of Rome, 00161 Rome, Italy; (G.G.); (C.D.); (E.D.)
| | - Cosimo Durante
- Department of Translational and Precision Medicine, “Sapienza” University of Rome, 00161 Rome, Italy; (G.G.); (C.D.); (E.D.)
| | - Vito D’Andrea
- Department of Surgical Sciences, “Sapienza” University of Rome, 00161 Rome, Italy; (S.S.); (V.D.); (E.L.)
| | - Emanuele David
- Department of Translational and Precision Medicine, “Sapienza” University of Rome, 00161 Rome, Italy; (G.G.); (C.D.); (E.D.)
| | - Pietro Giorgio Calò
- Department of Surgical Sciences, “Policlinico Universitario Duilio Casula”, University of Cagliari, 09042 Monserrato, Italy;
| | - Eleonora Lori
- Department of Surgical Sciences, “Sapienza” University of Rome, 00161 Rome, Italy; (S.S.); (V.D.); (E.L.)
| | - Vito Cantisani
- Department of Radiological, Anatomo-Pathological Sciences, “Sapienza” University of Rome, 00161 Rome, Italy; (V.D.); (V.C.)
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22
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Xi NM, Wang L, Yang C. Improving the diagnosis of thyroid cancer by machine learning and clinical data. Sci Rep 2022; 12:11143. [PMID: 35778428 PMCID: PMC9249901 DOI: 10.1038/s41598-022-15342-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2022] [Accepted: 06/22/2022] [Indexed: 12/13/2022] Open
Abstract
Thyroid cancer is a common endocrine carcinoma that occurs in the thyroid gland. Much effort has been invested in improving its diagnosis, and thyroidectomy remains the primary treatment method. A successful operation without unnecessary side injuries relies on an accurate preoperative diagnosis. Current human assessment of thyroid nodule malignancy is prone to errors and may not guarantee an accurate preoperative diagnosis. This study proposed a machine learning framework to predict thyroid nodule malignancy based on our collected novel clinical dataset. The ten-fold cross-validation, bootstrap analysis, and permutation predictor importance were applied to estimate and interpret the model performance under uncertainty. The comparison between model prediction and expert assessment shows the advantage of our framework over human judgment in predicting thyroid nodule malignancy. Our method is accurate, interpretable, and thus useable as additional evidence in the preoperative diagnosis of thyroid cancer.
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Affiliation(s)
- Nan Miles Xi
- Department of Mathematics and Statistics, Loyola University Chicago, Chicago, IL, 60660, USA
| | - Lin Wang
- Department of Statistics, Purdue University, West Lafayette, IN, 47907, USA
| | - Chuanjia Yang
- Department of General Surgery, Shengjing Hospital of China Medical University, Shenyang, 110004, Liaoning, China.
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23
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Zhu T, Chen J, Zhou Z, Ma X, Huang Y. Differentiation of Thyroid Nodules (C-TIRADS 4) by Combining Contrast-Enhanced Ultrasound Diagnosis Model With Chinese Thyroid Imaging Reporting and Data System. Front Oncol 2022; 12:840819. [PMID: 35847847 PMCID: PMC9280912 DOI: 10.3389/fonc.2022.840819] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 05/18/2022] [Indexed: 11/13/2022] Open
Abstract
Objectives To establish a contrast-enhanced ultrasound (CEUS) diagnostic schedule by CEUS analysis of thyroid nodules of C-TIRADS 4. To establish a CEUS-TIRADS diagnostic model to differentiate thyroid nodules (C-TIRADS 4) by combining CEUS with Chinese thyroid imaging reporting and data system (C-TIRADS). Methods A total of 228 thyroid nodules (C-TIRADS 4) were estimated by CEUS. The arrival time, enhancement degree, enhancement homogeneity, enhancement pattern, enhancement ring, and wash-out time were analyzed in CEUS for all of the nodules. Multivariate factors logistic analysis was performed and a CEUS diagnostic schedule was established. If the nodule had a regular hyper-enhancement ring or got a score of less than 2 in CEUS analysis, CEUS-TIRADS subtracted 1 category. If the nodule got a score of 2 in the CEUS schedule, the CEUS-TIRADS category remained the same as before. If the nodule got a score of more than 2 in the CEUS schedule, CEUS-TIRADS added 1 category. When it reflected an absent enhancement in CEUS, the nodule was judged as CEUS-TIRADS 3. All of the C-TIRADS 4 nodules were re-graded by CEUS-TIRADS. We then compare the diagnosis performance of C-TIRADS, CEUS, and CEUS-TIRADS by sensitivity, specificity, and accuracy. Results Among the 228 C-TIRADS 4 nodules, 69 were determined as C-TIRADS 4a, 114 were C-TIRADS 4b, and 45 were C-TIRADS 4c. The sensitivity, specificity, and accuracy of C-TIRADS were 93.1%, 55.3%, and 74.6% respectively. The area under the curve was 0.753. Later arrival time, hypo-enhancement, heterogeneous enhancement, centripetal enhancement, and rapid washout were risk factors of malignancy in multivariate analysis. The sensitivity, specificity, and accuracy of CEUS were 78.7%, 87.5%, and 83.3% respectively. The area under the curve was 0.803. By CEUS-TIRADS diagnostic model combining CEUS with C-TIRADS, a total of 127 cases were determined as malignancy (111 were malignant and 16 were benign) and 101 were diagnosed as benign ones (5 were malignant and 96 were benign). The sensitivity, specificity, and accuracy of CEUS-TIRADS were 95.7%, 85.7%, and 92.1% respectively. The area under the curve was 0.916. The diagnostic performance of CEUS-TIRADS was significantly better than CEUS and C-TIRADS. The difference was statistically significant (P<0.05). Conclusions The diagnostic schedule of CEUS could get better diagnostic performance than US in the differentiation of thyroid nodules. The CEUS-TIRADS combining CEUS analysis with C-TIRADS could make up for the deficient sensibility of C-TIRADS, showing a better diagnostic performance than US and CEUS.
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Affiliation(s)
- Tiantong Zhu
- Department of ultrasound, Shengjing Hospital of China Medical University, Shenyang, China
| | - Jiahui Chen
- Department of ultrasound, Shengjing Hospital of China Medical University, Shenyang, China
| | - Zimo Zhou
- Department of Orthopedics, Shengjing Hospital of China Medical University, Shenyang, China
| | - Xiaofen Ma
- Department of ultrasound, Shengjing Hospital of China Medical University, Shenyang, China
| | - Ying Huang
- Department of ultrasound, Shengjing Hospital of China Medical University, Shenyang, China
- *Correspondence: Ying Huang,
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24
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Canu GL, Medas F, Cappellacci F, Giordano ABF, Gurrado A, Gambardella C, Docimo G, Feroci F, Conzo G, Testini M, Calò PG. Risk of Complications in Patients Undergoing Completion Thyroidectomy after Hemithyroidectomy for Thyroid Nodule with Indeterminate Cytology: An Italian Multicentre Retrospective Study. Cancers (Basel) 2022; 14:cancers14102472. [PMID: 35626075 PMCID: PMC9139447 DOI: 10.3390/cancers14102472] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Revised: 05/09/2022] [Accepted: 05/14/2022] [Indexed: 12/19/2022] Open
Abstract
Simple Summary The increasing use of high-quality imaging techniques together with improved access to healthcare has led to an increase in the detection of thyroid nodules. Fine-needle aspiration cytology (FNAC) is currently considered the most accurate examination for the assessment of thyroid nodular disease. However, in about 25% of cases, FNAC leads to the diagnosis of an indeterminate thyroid nodule, which represents a problem because malignancy, although relatively low (up to 30%), cannot be excluded with certainty. According to the 2015 American Thyroid Association guidelines, patients with thyroid nodular disease with an indeterminate cytology can undergo, based on established factors, a total thyroidectomy or a hemithyroidectomy. However, if an intermediate or high-risk differentiated thyroid carcinoma is detected after the hemithyroidectomy, through histological examination, the above-mentioned guidelines recommend performing a completion thyroidectomy. The main aim of this study was to assess the rate of complications in patients undergoing a completion thyroidectomy after a hemithyroidectomy for a thyroid nodule with an indeterminate cytology. Abstract There is still controversy as to whether patients undergoing a completion thyroidectomy after a hemithyroidectomy for a thyroid nodule with an indeterminate cytology have a comparable, increased or decreased risk of complications compared to those submitted to primary thyroid surgery. The main aim of this study was to investigate this topic. Patients undergoing a thyroidectomy for thyroid nodular disease with an indeterminate cytology in four high-volume thyroid surgery centres in Italy, between January 2017 and December 2020, were retrospectively analysed. Based on the surgical procedure performed, four groups were identified: the TT Group (total thyroidectomy), HT Group (hemithyroidectomy), CT Group (completion thyroidectomy) and HT + CT Group (hemithyroidectomy with subsequent completion thyroidectomy). A total of 751 patients were included. As for the initial surgery, 506 (67.38%) patients underwent a total thyroidectomy and 245 (32.62%) a hemithyroidectomy. Among all patients submitted to a hemithyroidectomy, 66 (26.94%) were subsequently submitted to a completion thyroidectomy. No statistically significant difference was found in terms of complications comparing both the TT Group with the HT + CT Group and the HT Group with the CT Group. The risk of complications in patients undergoing a completion thyroidectomy after a hemithyroidectomy for a thyroid nodule with an indeterminate cytology was comparable to that of patients submitted to primary thyroid surgery (both a total thyroidectomy and hemithyroidectomy).
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Affiliation(s)
- Gian Luigi Canu
- Department of Surgical Sciences, University of Cagliari, 09042 Monserrato, CA, Italy; (F.M.); (F.C.); (P.G.C.)
- Correspondence:
| | - Fabio Medas
- Department of Surgical Sciences, University of Cagliari, 09042 Monserrato, CA, Italy; (F.M.); (F.C.); (P.G.C.)
| | - Federico Cappellacci
- Department of Surgical Sciences, University of Cagliari, 09042 Monserrato, CA, Italy; (F.M.); (F.C.); (P.G.C.)
| | | | - Angela Gurrado
- Department of Biomedical Sciences and Human Oncology, University of Bari “Aldo Moro”, 70124 Bari, BA, Italy; (A.G.); (M.T.)
| | - Claudio Gambardella
- Department of Medical and Advanced Surgical Sciences, University of Campania “Luigi Vanvitelli”, 80131 Naples, NA, Italy; (C.G.); (G.D.)
| | - Giovanni Docimo
- Department of Medical and Advanced Surgical Sciences, University of Campania “Luigi Vanvitelli”, 80131 Naples, NA, Italy; (C.G.); (G.D.)
| | - Francesco Feroci
- Department of General and Oncologic Surgery, Santo Stefano Hospital, 59100 Prato, PO, Italy; (A.B.F.G.); (F.F.)
| | - Giovanni Conzo
- Department of Traslational Medical Sciences, University of Campania “Luigi Vanvitelli”, 80131 Naples, NA, Italy;
| | - Mario Testini
- Department of Biomedical Sciences and Human Oncology, University of Bari “Aldo Moro”, 70124 Bari, BA, Italy; (A.G.); (M.T.)
| | - Pietro Giorgio Calò
- Department of Surgical Sciences, University of Cagliari, 09042 Monserrato, CA, Italy; (F.M.); (F.C.); (P.G.C.)
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25
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Cantisani V, De Silvestri A, Scotti V, Fresilli D, Tarsitano MG, Polti G, Guiban O, Polito E, Pacini P, Durante C, Grani G, Isidori AM, Giannetta E, Sorrenti S, Trimboli P, Catalano C, Cirocchi R, Lauro A, D'Andrea V. US-Elastography With Different Techniques for Thyroid Nodule Characterization: Systematic Review and Meta-analysis. Front Oncol 2022; 12:845549. [PMID: 35371974 PMCID: PMC8966910 DOI: 10.3389/fonc.2022.845549] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 02/16/2022] [Indexed: 12/25/2022] Open
Abstract
Background Thyroid nodules are frequent in adult population and thyroid cancer incidence has increased dramatically over the past three decades. The aim of this systematic review and meta-analysis was to evaluate the US-Elastosonography (USE) diagnostic performance in assessing the thyroid nodules malignancy risk. Methods PubMed and Embase databases were searched from January 2011 to July 2021. We extracted data from selected studies and calculated the overall diagnostic accuracy of qualitative USE, semi-quantitative USE and quantitative USE. Summary receiver operating characteristic (ROC) curve was elaborated to show the results. All statistical tests were performed using Metadisc and Medcal software package. Results Finally 72 studies with 13,505 patients and 14,015 thyroid nodules (33% malignant) undergoing elastography were included. The pooled sensitivity, specificity and AUC were 84%, 81%, and 0.89 respectively for qualitative USE; 83%, 80%, and 0.93 for semi-quantitative USE and 78%, 81% and 0.87, for quantitative USE. The qualitative and semiquantitative USE present very similar diagnostic accuracy values and both better than the quantitative USE. Conclusions USE is a useful imaging tool for thyroid nodule characterization. In accordance with recent guidelines and meta-analyses, the USE could be used daily in thyroid nodule malignancy risk stratification. Systematic Review Registration PROSPERO: CRD42021279257.
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Affiliation(s)
- Vito Cantisani
- Department of Radiological Sciences, Oncology and Pathology, Policlinico Umberto I, Sapienza University of Rome, Rome, Italy
| | - Annalisa De Silvestri
- Servizio di Epidemiologia Clinica e Biometria Direzione Scientifica-Fondazione Istituti di Ricovero e Cura a Carattere Scientifico (IRCCS) Policlinico san Matteo, Pavia, Italy
| | - Valeria Scotti
- Servizio di Epidemiologia Clinica e Biometria Direzione Scientifica-Fondazione Istituti di Ricovero e Cura a Carattere Scientifico (IRCCS) Policlinico san Matteo, Pavia, Italy
| | - Daniele Fresilli
- Department of Radiological Sciences, Oncology and Pathology, Policlinico Umberto I, Sapienza University of Rome, Rome, Italy
| | - Maria Grazia Tarsitano
- Department of Clinical and Surgical Science, "Magna Graecia" University, Catanzaro, Italy
| | - Giorgia Polti
- Department of Radiological Sciences, Oncology and Pathology, Policlinico Umberto I, Sapienza University of Rome, Rome, Italy
| | - Olga Guiban
- Department of Radiological Sciences, Oncology and Pathology, Policlinico Umberto I, Sapienza University of Rome, Rome, Italy
| | - Eleonora Polito
- Department of Radiological Sciences, Oncology and Pathology, Policlinico Umberto I, Sapienza University of Rome, Rome, Italy
| | - Patrizia Pacini
- Department of Radiological Sciences, Oncology and Pathology, Policlinico Umberto I, Sapienza University of Rome, Rome, Italy
| | - Cosimo Durante
- Department of Translational and Precision Medicine, "Sapienza" University of Rome, Rome, Italy
| | - Giorgio Grani
- Department of Translational and Precision Medicine, "Sapienza" University of Rome, Rome, Italy
| | - Andrea M Isidori
- Department of Experimental Medicine, Sapienza University of Rome, Rome, Italy
| | - Elisa Giannetta
- Department of Experimental Medicine, Sapienza University of Rome, Rome, Italy
| | - Salvatore Sorrenti
- Department of Surgical Sciences, Hospital "Policlinico Umberto I", "Sapienza" University of Rome, Rome, Italy
| | - Pierpaolo Trimboli
- Clinic for Endocrinology and Diabetology, Lugano Regional Hospital, Ente Ospedaliero Cantonale, Lugano, Switzerland
| | - Carlo Catalano
- Department of Radiological Sciences, Oncology and Pathology, Policlinico Umberto I, Sapienza University of Rome, Rome, Italy
| | - Roberto Cirocchi
- Department of Surgery and Biomedical Sciences, University of Perugia, Perugia, Italy
| | - Augusto Lauro
- Department of Surgical Sciences, Hospital "Policlinico Umberto I", "Sapienza" University of Rome, Rome, Italy
| | - Vito D'Andrea
- Department of Surgical Sciences, Hospital "Policlinico Umberto I", "Sapienza" University of Rome, Rome, Italy
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26
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Walker E, Karthik S, Chengot P, Vaidyanathan S. It's not all about the thyroid! Extrinsic and unusual pathology affecting the thyroid gland: A pictorial review. Clin Imaging 2022; 85:29-42. [DOI: 10.1016/j.clinimag.2022.02.017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 02/09/2022] [Accepted: 02/14/2022] [Indexed: 12/11/2022]
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27
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Triggiani V, Lisco G, Renzulli G, Frasoldati A, Guglielmi R, Garber J, Papini E. The TNAPP web-based algorithm improves thyroid nodule management in clinical practice: A retrospective validation study. Front Endocrinol (Lausanne) 2022; 13:1080159. [PMID: 36778596 PMCID: PMC9911894 DOI: 10.3389/fendo.2022.1080159] [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: 10/25/2022] [Accepted: 12/23/2022] [Indexed: 01/28/2023] Open
Abstract
BACKGROUND The detection of thyroid nodules has been increasing over time, resulting in an extensive use of fine-needle aspiration (FNA) and cytology. Tailored methods are required to improve the management of thyroid nodules, including algorithms and web-based tools. STUDY AIMS To assess the performance of the Thyroid Nodule App (TNAPP), a web-based, readily modifiable, interactive algorithmic tool, in improving the management of thyroid nodules. METHODS One hundred twelve consecutive patients with 188 thyroid nodules who underwent FNA from January to December 2016 and thyroid surgery were retrospectively evaluated. Neck ultrasound images were collected from a thyroid nodule registry and re-examined to extract data to run TNAPP. Each nodule was evaluated for ultrasonographic risk and suitability for FNA. The sensitivity, specificity, positive and negative predictive values, and overall accuracy of TNAPP were calculated and compared to the diagnostic performance of the other two algorithms by the American Association of Clinical Endocrinology/American College of Endocrinology/Associazione Medici Endocrinologi (AACE/ACE/AME), which it was derived from the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS). RESULTS TNAPP performed better in terms of sensitivity (>80%) and negative predictive value (68%) with an overall accuracy of 50.5%, which was similar to that found with the AACE/ACE/AME algorithm. TNAPP displayed a slightly better performance than AACE/ACE/AME and ACR TI-RADS algorithms in selectively discriminating unnecessary FNA for nodules with benign cytology (TIR 2 - Bethesda class II: TNAPP 32% vs. AACE/ACE/AME 31% vs. ACR TI-RADS 29%). The TNAPP reduced the number of missed diagnoses of thyroid nodules with suspicious and highly suspicious cytology (TIR 4 + TIR 5 - Bethesda classes V + VI: TNAPP 18% vs. AACE/ACE/AME 26% vs. ACR TI-RADS 20.5%). A total of 14 nodules that would not have been aspirated were malignant, 13 of which were microcarcinomas (92.8%). DISCUSSION The TNAPP algorithm is a reliable, easy-to-learn tool that can be readily employed to improve the selection of thyroid nodules requiring cytological characterization. The rate of malignant nodules missed because of inaccurate characterization at baseline by TNAPP was lower compared to the other two algorithms and, in almost all the cases, the tumors were microcarcinomas. TNAPP's use of size >20 mm as an independent determinant for considering or recommending FNA reduced its specificity. CONCLUSION TNAPP performs well compared to AACE/ACE/AME and ACR-TIRADS algorithms. Additional retrospective and, ultimately, prospective studies are needed to confirm and guide the development of future iterations that incorporate different risk stratification systems and targets for diagnosing malignancy while reducing unnecessary FNA procedures.
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Affiliation(s)
- Vincenzo Triggiani
- Interdisciplinary Department of Medicine, Section of Internal Medicine, Geriatrics, Endocrinology and Rare Diseases, School of Medicine, University of Bari “Aldo Moro”, Bari, Italy
- *Correspondence: Vincenzo Triggiani,
| | - Giuseppe Lisco
- Interdisciplinary Department of Medicine, Section of Internal Medicine, Geriatrics, Endocrinology and Rare Diseases, School of Medicine, University of Bari “Aldo Moro”, Bari, Italy
| | - Giuseppina Renzulli
- Department of Emergency and Organ Transplantation, Section of Pathological Anatomy, University of Bari “Aldo Moro”, Bari, Italy
| | - Andrea Frasoldati
- Endocrinology and Metabolism Department, Arcispedale Santa Maria Nuova Istituto di Ricovero e Cura a Carattere Scientifico-Azienda Sanitaria Locale, Reggio Emilia, Italy
| | - Rinaldo Guglielmi
- Endocrinology and Metabolism Department, Regina Apostolorum Hospital, Rome, Italy
| | - Jeffrey Garber
- Endocrine Division, Harvard Vanguard Medical Associates Harvard Medical School, Boston, MA, United States
| | - Enrico Papini
- Endocrinology and Metabolism Department, Regina Apostolorum Hospital, Rome, Italy
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28
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Zhang Y, Mei F, He X, Ma J, Wang S. Reconceptualize tall-cell variant papillary thyroid microcarcinoma: From a "sonographic histology" perspective. Front Endocrinol (Lausanne) 2022; 13:1001477. [PMID: 36425468 PMCID: PMC9681115 DOI: 10.3389/fendo.2022.1001477] [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: 09/29/2022] [Accepted: 10/19/2022] [Indexed: 11/10/2022] Open
Abstract
OBJECTIVE This study aimed to examine the relationship between sonographic features and histological manifestations in the tall-cell variant of papillary thyroid microcarcinoma (TCV-PTMC), thus proposing the concept of "sonographic histology" and examine its value in the clinical management of the aggressive tall-cell variant. METHODS This study retrospectively included 104 participants who were admitted to Peking University Third Hospital from 2015 to 2022 and were histopathologically confirmed as having TCV-PTMC or classical PTMC. We mainly compared the general characteristics, sonographic characteristics, and pathological specimens between the two cohorts. RESULTS Hypoechoic nodules with a localized central isoechoic lesion and hypoechoic halo around nodules were most often observed in TCV-PTMC, which correlated with circumferentially distributed tumor epithelium and densely distributed tumor stroma histopathologically. Additionally, TCV-PTMC showed nodules with a more regular margin and less microcalcification than classical PTMC, which led to an underestimation of the risk of TCV-PTMC. CONCLUSION The good association between the ultrasound echo pattern and tissue cell arrangement was defined as sonographic histology in this study and can be applied in the preoperative identification of TCV-PTMC. This concept may provide novel insight for the identification of special subtypes of thyroid tumors and may modify pitfalls of the Thyroid Imaging Reporting and Data System in aggressive variants of microcarcinoma.
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Affiliation(s)
- Yongyue Zhang
- Department of Ultrasound, Peking University Third Hospital, Beijing, China
| | - Fang Mei
- Department of Pathology, Peking University Third Hospital, Beijing, China
| | - Xiaoxi He
- Department of Ultrasound, Peking University Third Hospital, Beijing, China
| | - Jing Ma
- Department of Ultrasound, Peking University Third Hospital, Beijing, China
| | - Shumin Wang
- Department of Ultrasound, Peking University Third Hospital, Beijing, China
- *Correspondence: Shumin Wang,
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29
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Zhang H, Tan X, Qian L. Contrast-Enhanced Ultrasound: An Effective Method for Noninvasive Diagnosis of Mummified Thyroid Nodules. Int J Endocrinol 2022; 2022:4289708. [PMID: 35529081 PMCID: PMC9068332 DOI: 10.1155/2022/4289708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 03/18/2022] [Indexed: 11/17/2022] Open
Abstract
Mummified thyroid nodules are a special type of thyroid nodule, which is benign, but is often diagnosed as malignant by ultrasound. This study investigated the usefulness of contrast-enhanced ultrasound (CEUS) in the diagnosis of mummified nodules. 66 patients with mummified nodules were divided into two groups: a no-enhancement group and a low-enhancement group. 32 patients with papillary thyroid carcinoma (PTC) were recruited in control group. In the no-enhancement group, CEUS showed that there was no contrast agent entering the nodules, with or without a little dot enhancement or regular ring enhancement around the nodules. The low-enhancement group showed low enhancement inside nodules, which was similar to that in the PTC group. In semiquantitative time-intensity curve analyses, intensity maximum of the central area of nodules in the low-enhancement group was lower than that in the PTC group (P < 0.05) and time to peak of the central area of nodules in the low-enhancement group was lower than that in the PTC group (P < 0.05). The results demonstrate that CEUS could be used to effectively diagnose mummified nodules, obviating the need for patients to undergo invasive examination such as biopsy or even surgery.
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Affiliation(s)
- Hong Zhang
- Department of Ultrasound, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Xiaoqu Tan
- Department of Ultrasound, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Linxue Qian
- Department of Ultrasound, Beijing Friendship Hospital, Capital Medical University, Beijing, China
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30
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Deep Learning Based Fast Screening Approach on Ultrasound Images for Thyroid Nodules Diagnosis. Diagnostics (Basel) 2021; 11:diagnostics11122209. [PMID: 34943444 PMCID: PMC8700062 DOI: 10.3390/diagnostics11122209] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 11/21/2021] [Accepted: 11/25/2021] [Indexed: 11/23/2022] Open
Abstract
Thyroid nodules are widespread in the United States and the rest of the world, with a prevalence ranging from 19 to 68%. The problem with nodules is whether they are malignant or benign. Ultrasonography is currently recommended as the initial modality for evaluating thyroid nodules. However, obtaining a good diagnosis from ultrasound imaging depends entirely on the radiologists levels of experience and other circumstances. There is a tremendous demand for automated and more reliable methods to screen ultrasound images more efficiently. This research proposes an efficient and quick detection deep learning approach for thyroid nodules. An open and publicly available dataset, Thyroid Digital Image Database (TDID), is used to determine the robustness of the suggested method. Each image is formatted into a pyramid tile-based data structure, which the proposed VGG-16 model evaluates to provide segmentation results for nodular detection. The proposed method adopts a top-down approach to hierarchically integrate high- and low-level features to distinguish nodules of varied sizes by employing fuse features effectively. The results demonstrated that the proposed method outperformed the U-Net model, achieving an accuracy of 99%, and was two times faster than the competitive model.
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31
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Bellini MI, Biffoni M, Patrone R, Borcea MC, Costanzo ML, Garritano T, Melcarne R, Menditto R, Metere A, Scorziello C, Summa M, Ventrone L, D’Andrea V, Giacomelli L. Poorly Differentiated Thyroid Carcinoma: Single Centre Experience and Review of the Literature. J Clin Med 2021; 10:jcm10225258. [PMID: 34830540 PMCID: PMC8623499 DOI: 10.3390/jcm10225258] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Revised: 11/05/2021] [Accepted: 11/11/2021] [Indexed: 11/21/2022] Open
Abstract
There is controversy in the literature regarding a distinct subset of thyroid carcinoma whose histologically classification falls between well-differentiated and anaplastic carcinomas, previously identified as ‘poorly differentiated thyroid carcinoma’ (PDTC), or ‘insular carcinoma’, in view of the peculiar morphological characteristics of the cell groupings. The correct diagnosis and treatment of this entity have important prognostic and therapeutic significance. In this review, we describe the epidemiology, diagnosis, and management of PDTC and report our single centre experience to add to the limited evidence existing in the literature.
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Affiliation(s)
- Maria Irene Bellini
- Azienda Ospedaliera San Camillo Forlanini, 00152 Rome, Italy
- Department of Surgical Sciences, Sapienza University of Rome, 00161 Rome, Italy; (M.B.); (M.C.B.); (M.L.C.); (T.G.); (R.M.); (R.M.); (C.S.); (M.S.); (L.V.); (V.D.); (L.G.)
- Correspondence:
| | - Marco Biffoni
- Department of Surgical Sciences, Sapienza University of Rome, 00161 Rome, Italy; (M.B.); (M.C.B.); (M.L.C.); (T.G.); (R.M.); (R.M.); (C.S.); (M.S.); (L.V.); (V.D.); (L.G.)
| | - Renato Patrone
- ICTUS, University of Naples Federico II, Via Pansini 5, 80131 Naples, Italy;
| | - Maria Carola Borcea
- Department of Surgical Sciences, Sapienza University of Rome, 00161 Rome, Italy; (M.B.); (M.C.B.); (M.L.C.); (T.G.); (R.M.); (R.M.); (C.S.); (M.S.); (L.V.); (V.D.); (L.G.)
| | - Maria Ludovica Costanzo
- Department of Surgical Sciences, Sapienza University of Rome, 00161 Rome, Italy; (M.B.); (M.C.B.); (M.L.C.); (T.G.); (R.M.); (R.M.); (C.S.); (M.S.); (L.V.); (V.D.); (L.G.)
| | - Tiziana Garritano
- Department of Surgical Sciences, Sapienza University of Rome, 00161 Rome, Italy; (M.B.); (M.C.B.); (M.L.C.); (T.G.); (R.M.); (R.M.); (C.S.); (M.S.); (L.V.); (V.D.); (L.G.)
| | - Rossella Melcarne
- Department of Surgical Sciences, Sapienza University of Rome, 00161 Rome, Italy; (M.B.); (M.C.B.); (M.L.C.); (T.G.); (R.M.); (R.M.); (C.S.); (M.S.); (L.V.); (V.D.); (L.G.)
| | - Rosa Menditto
- Department of Surgical Sciences, Sapienza University of Rome, 00161 Rome, Italy; (M.B.); (M.C.B.); (M.L.C.); (T.G.); (R.M.); (R.M.); (C.S.); (M.S.); (L.V.); (V.D.); (L.G.)
| | - Alessio Metere
- General Surgery Department, Ospedale dei Castelli (O.D.C.), Via Nettunense Km 11,5, 00040 Rome, Italy;
| | - Chiara Scorziello
- Department of Surgical Sciences, Sapienza University of Rome, 00161 Rome, Italy; (M.B.); (M.C.B.); (M.L.C.); (T.G.); (R.M.); (R.M.); (C.S.); (M.S.); (L.V.); (V.D.); (L.G.)
| | - Marco Summa
- Department of Surgical Sciences, Sapienza University of Rome, 00161 Rome, Italy; (M.B.); (M.C.B.); (M.L.C.); (T.G.); (R.M.); (R.M.); (C.S.); (M.S.); (L.V.); (V.D.); (L.G.)
| | - Luca Ventrone
- Department of Surgical Sciences, Sapienza University of Rome, 00161 Rome, Italy; (M.B.); (M.C.B.); (M.L.C.); (T.G.); (R.M.); (R.M.); (C.S.); (M.S.); (L.V.); (V.D.); (L.G.)
| | - Vito D’Andrea
- Department of Surgical Sciences, Sapienza University of Rome, 00161 Rome, Italy; (M.B.); (M.C.B.); (M.L.C.); (T.G.); (R.M.); (R.M.); (C.S.); (M.S.); (L.V.); (V.D.); (L.G.)
| | - Laura Giacomelli
- Department of Surgical Sciences, Sapienza University of Rome, 00161 Rome, Italy; (M.B.); (M.C.B.); (M.L.C.); (T.G.); (R.M.); (R.M.); (C.S.); (M.S.); (L.V.); (V.D.); (L.G.)
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Papillary Thyroid Cancer Prognosis: An Evolving Field. Cancers (Basel) 2021; 13:cancers13215567. [PMID: 34771729 PMCID: PMC8582937 DOI: 10.3390/cancers13215567] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Revised: 11/04/2021] [Accepted: 11/04/2021] [Indexed: 12/13/2022] Open
Abstract
Simple Summary Over the last couple of decades, the prognostic stratification systems of differentiated thyroid cancer (DTC) patients have been revised several times in an attempt to achieve a tailored clinical management reflecting the single patients’ needs. Such revisions are likely to continue in the near future, since the prognostic value of a number of promising clinicopathological features and new molecular biomarkers are being evaluated. Here, we will review the current staging systems of thyroid cancer patients and discuss the most relevant clinicopathological parameters and new molecular markers that are potentially capable of refining the prognosis. Abstract Over the last few years, a great advance has been made in the comprehension of the molecular pathogenesis underlying thyroid cancer progression, particularly for the papillary thyroid cancer (PTC), which represents the most common thyroid malignancy. Putative cancer driver mutations have been identified in more than 98% of PTC, and a new PTC classification into molecular subtypes has been proposed in order to resolve clinical uncertainties still present in the clinical management of patients. Additionally, the prognostic stratification systems have been profoundly modified over the last decade, with a view to refine patients’ staging and being able to choose a clinical approach tailored on single patient’s needs. Here, we will briefly discuss the recent changes in the clinical management of thyroid nodules, and review the current staging systems of thyroid cancer patients by analyzing promising clinicopathological features (i.e., gender, thyroid auto-immunity, multifocality, PTC histological variants, and vascular invasion) as well as new molecular markers (i.e., BRAF/TERT promoter mutations, miRNAs, and components of the plasminogen activating system) potentially capable of ameliorating the prognosis of PTC patients.
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Ratajczak M, Gaweł D, Godlewska M. Novel Inhibitor-Based Therapies for Thyroid Cancer-An Update. Int J Mol Sci 2021; 22:11829. [PMID: 34769260 PMCID: PMC8584403 DOI: 10.3390/ijms222111829] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 10/27/2021] [Accepted: 10/28/2021] [Indexed: 12/16/2022] Open
Abstract
Thyroid cancers (TCs) are the most common tumors of the endocrine system and a constant rise in the number of TC cases has been observed for the past few decades. TCs are one of the most frequent tumors in younger adults, especially in women, therefore early diagnosis and effective therapy are especially important. Ultrasonography examination followed by fine needle biopsy have become the gold standard for diagnosis of TCs, as these strategies allow for early-stage detection and aid accurate qualification for further procedures, including surgical treatment. Despite all the advancements in detection and treatment of TCs, constant mortality levels are still observed. Therefore, a novel generation line of targeted treatment strategies is being developed, including personalized therapies with kinase inhibitors. Recent molecular studies on TCs demonstrate that kinase inhibitor-based therapies might be considered as the most promising. In the past decade, new kinase inhibitors with different mechanisms of action have been reported and approved for clinical trials. This review presents an up-to-date picture of new approaches and challenges of inhibitor-based therapies in treatment of TCs, focusing on the latest findings reported over the past two years.
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Affiliation(s)
- Maciej Ratajczak
- Centre of Postgraduate Medical Education, Department of Endocrinology, Marymoncka 99/103, 01-813 Warsaw, Poland;
| | - Damian Gaweł
- Centre of Postgraduate Medical Education, Department of Immunohematology, Marymoncka 99/103, 01-813 Warsaw, Poland
- Centre of Postgraduate Medical Education, Department of Biochemistry and Molecular Biology, Marymoncka 99/103, 01-813 Warsaw, Poland
| | - Marlena Godlewska
- Centre of Postgraduate Medical Education, Department of Biochemistry and Molecular Biology, Marymoncka 99/103, 01-813 Warsaw, Poland
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