Thyroid ultrasound images, classified into 5 classes that correspond to the European EU-TIRADS scale, this consists of:

EU-TIRADS 1: no nodule
EU-TIRADS 2: benign
EU-TIRADS 3: low risk (oval, smooth margin, iso / hyperechoic, no high risk features)
EU-TIRADS 4: intermediate risk (oval, smooth margin, mildly hypoechoic, no high risk features)
EU-TIRADS 5: any high risk features (non-oval, irregular margin, microcalcifications, marked hypoechogenicity)

Ultrasound images of the thyroid that were taken from the ultrasound scanners of the FOSCAL/FOSUNAB clinic, as a final master's project for the Polytechnic University of Valencia, in collaboration with doctors Federico Lubinus and Boris Marconi, who together with Yhary Arias have worked on the classification of said ultrasounds that are saved in .DICOM format and then transformed to PNG to make the process lighter. The strategy that was carried out for the collection of images and later their labeling was: for each examination that was carried out on patients with or without a possible diagnosis, only the images without personal or sensitive information were kept, all this on a hard drive. , then a pre-processing of the images was done, their format was changed and finally they were mounted on a web page with a single view to facilitate the classification of the doctors who were in charge of this arduous task. Ultrasounds were classified into 5 classes that correspond to the European EU-TIRADS scale, this consists of:

EU-TIRADS 1: no nodule
EU-TIRADS 2: benign
EU-TIRADS 3: low risk (oval, smooth margin, iso / hyperechoic, no high risk features)
EU-TIRADS 4: intermediate risk (oval, smooth margin, mildly hypoechoic, no high risk features)
EU-TIRADS 5: any high risk features (non-oval, irregular margin, microcalcifications, marked hypoechogenicity)

Risk of malignancy
EU-TIRADS 1: n/a
EU-TIRADS 2: 0%
EU-TIRADS 3: low risk (2-4%)
EU-TIRADS 4: intermediate risk (6-17%)
EU-TIRADS 5: high risk (26-87%)

References
1. Gilles Russ, Steen J. Bonnema, Murat Faik Erdogan, Cosimo Durante, Rose Ngu, Laurence Leenhardt. European Thyroid Association Guidelines for Ultrasound Malignancy Risk Stratification of Thyroid Nodules in Adults: The EU-TIRADS. (2019) European ThyroidJournal. 6 (5): 225. doi:10.1159/000478927 - Pubmed
2. Gilles Russ, Bénédicte Royer, Claude Bigorgne, Agnès Rouxel, Marie Bienvenu-Perrard, Laurence Leenhardt. Prospective evaluation of thyroid imaging reporting and data system on 4550 nodules with and without elastography. (2013) European Journal of Endocrinology. 168 (5): 649. doi:10.1530/EJE-12-0936 - Pubmed
3. Jung Hyun Yoon, Kyunghwa Han, Eun-Kyung Kim, Hee Jung Moon, Jin Young Kwak. Diagnosis and Management of Small Thyroid Nodules: A Comparative Study with Six Guidelines for Thyroid Nodules. (2016) Radiology. 283 (2): 560-569. doi:10.1148/radiol.2016160641 - Pubmed
4. Ting Xu, Ya Wu, Run-Xin Wu, Yu-Zhi Zhang, Jing-Yu Gu, Xin-Hua Ye, Wei Tang, Shu-Hang Xu, Chao Liu, Xiao-Hong Wu. Validation and comparison of three newly-released Thyroid Imaging Reporting and Data Systems for cancer risk determination. (2019). Endocrine. 64 (2): 299. doi:10.1007/s12020-018-1817-8 - Pubmed
5. Ting Xu, Ya Wu, Run-Xin Wu, Yu-Zhi Zhang, Jing-Yu Gu, Xin-Hua Ye, Wei Tang, Shu-Hang Xu, Chao Liu, Xiao-Hong Wu. Validation and comparison of three newly-released Thyroid Imaging Reporting and Data Systems for cancer risk determination. (2019). Endocrine. 64 (2): 299. doi:10.1007/s12020-018-1817-8 - Pubmed
6. Grani, Giorgio, Lamartina, Livia, Ascoli, Valeria, Bosco, Daniela, Biffoni, Marco, Giacomelli, Laura, Maranghi, Marianna, Falcone, Rosa, Ramundo, Valeria, Cantisani, Vito, Filetti, Sebastiano, Durante, Cosimo. Reducing the Number of Unnecessary Thyroid Biopsies While Improving Diagnostic Accuracy: Toward the “Right” TIRADS. (2019) The Journal of Clinical Endocrinology & Metabolism. 104 (1): 95. doi:10.1210/jc.2018-01674 - Pubmed
7. Giorgio Grani, Livia Lamartina, Vito Cantisani, Marianna Maranghi, Piernatale Lucia, Cosimo Durante. Interobserver agreement of various thyroid imaging reporting and data systems. (2018) Endocrine Connections. 7 (1): 1. doi:10.1530/EC-17-0336 - Pubmed

Taken from: https://radiopaedia.org/articles/european-thyroid-association-tirads

*Citation Information*

@yharyarias{tirads_tiroides:2022,
  author = {Yhary Arias, Federico Lubinus, Boris Marconi},
  title = {Common Voice: Thyroid Ultrasound Imaging Dataset},
  thesistitle = {Sistema para la clasificación y reconocimiento de imágenes de ultrasonido en
tiroides, basado en técnicas de aprendizaje profundo para el apoyo en el proceso
de diagnóstico según la escala EU-TIRADS},
  year = 2022
}

Bucaramanga, Santander, 2022
region:us
{}
TAGS
#region-us 

Thyroid ultrasound images, classified into 5 classes that correspond to the European EU-TIRADS scale, this consists of:

EU-TIRADS 1: no nodule
EU-TIRADS 2: benign
EU-TIRADS 3: low risk (oval, smooth margin, iso / hyperechoic, no high risk features)
EU-TIRADS 4: intermediate risk (oval, smooth margin, mildly hypoechoic, no high risk features)
EU-TIRADS 5: any high risk features (non-oval, irregular margin, microcalcifications, marked hypoechogenicity)

Ultrasound images of the thyroid that were taken from the ultrasound scanners of the FOSCAL/FOSUNAB clinic, as a final master's project for the Polytechnic University of Valencia, in collaboration with doctors Federico Lubinus and Boris Marconi, who together with Yhary Arias have worked on the classification of said ultrasounds that are saved in .DICOM format and then transformed to PNG to make the process lighter. The strategy that was carried out for the collection of images and later their labeling was: for each examination that was carried out on patients with or without a possible diagnosis, only the images without personal or sensitive information were kept, all this on a hard drive. , then a pre-processing of the images was done, their format was changed and finally they were mounted on a web page with a single view to facilitate the classification of the doctors who were in charge of this arduous task. Ultrasounds were classified into 5 classes that correspond to the European EU-TIRADS scale, this consists of:

EU-TIRADS 1: no nodule
EU-TIRADS 2: benign
EU-TIRADS 3: low risk (oval, smooth margin, iso / hyperechoic, no high risk features)
EU-TIRADS 4: intermediate risk (oval, smooth margin, mildly hypoechoic, no high risk features)
EU-TIRADS 5: any high risk features (non-oval, irregular margin, microcalcifications, marked hypoechogenicity)

Risk of malignancy
EU-TIRADS 1: n/a
EU-TIRADS 2: 0%
EU-TIRADS 3: low risk (2-4%)
EU-TIRADS 4: intermediate risk (6-17%)
EU-TIRADS 5: high risk (26-87%)

References
1. Gilles Russ, Steen J. Bonnema, Murat Faik Erdogan, Cosimo Durante, Rose Ngu, Laurence Leenhardt. European Thyroid Association Guidelines for Ultrasound Malignancy Risk Stratification of Thyroid Nodules in Adults: The EU-TIRADS. (2019) European ThyroidJournal. 6 (5): 225. doi:10.1159/000478927 - Pubmed
2. Gilles Russ, Bénédicte Royer, Claude Bigorgne, Agnès Rouxel, Marie Bienvenu-Perrard, Laurence Leenhardt. Prospective evaluation of thyroid imaging reporting and data system on 4550 nodules with and without elastography. (2013) European Journal of Endocrinology. 168 (5): 649. doi:10.1530/EJE-12-0936 - Pubmed
3. Jung Hyun Yoon, Kyunghwa Han, Eun-Kyung Kim, Hee Jung Moon, Jin Young Kwak. Diagnosis and Management of Small Thyroid Nodules: A Comparative Study with Six Guidelines for Thyroid Nodules. (2016) Radiology. 283 (2): 560-569. doi:10.1148/radiol.2016160641 - Pubmed
4. Ting Xu, Ya Wu, Run-Xin Wu, Yu-Zhi Zhang, Jing-Yu Gu, Xin-Hua Ye, Wei Tang, Shu-Hang Xu, Chao Liu, Xiao-Hong Wu. Validation and comparison of three newly-released Thyroid Imaging Reporting and Data Systems for cancer risk determination. (2019). Endocrine. 64 (2): 299. doi:10.1007/s12020-018-1817-8 - Pubmed
5. Ting Xu, Ya Wu, Run-Xin Wu, Yu-Zhi Zhang, Jing-Yu Gu, Xin-Hua Ye, Wei Tang, Shu-Hang Xu, Chao Liu, Xiao-Hong Wu. Validation and comparison of three newly-released Thyroid Imaging Reporting and Data Systems for cancer risk determination. (2019). Endocrine. 64 (2): 299. doi:10.1007/s12020-018-1817-8 - Pubmed
6. Grani, Giorgio, Lamartina, Livia, Ascoli, Valeria, Bosco, Daniela, Biffoni, Marco, Giacomelli, Laura, Maranghi, Marianna, Falcone, Rosa, Ramundo, Valeria, Cantisani, Vito, Filetti, Sebastiano, Durante, Cosimo. Reducing the Number of Unnecessary Thyroid Biopsies While Improving Diagnostic Accuracy: Toward the “Right” TIRADS. (2019) The Journal of Clinical Endocrinology & Metabolism. 104 (1): 95. doi:10.1210/jc.2018-01674 - Pubmed
7. Giorgio Grani, Livia Lamartina, Vito Cantisani, Marianna Maranghi, Piernatale Lucia, Cosimo Durante. Interobserver agreement of various thyroid imaging reporting and data systems. (2018) Endocrine Connections. 7 (1): 1. doi:10.1530/EC-17-0336 - Pubmed

Taken from: URL

*Citation Information*

@yharyarias{tirads_tiroides:2022,
  author = {Yhary Arias, Federico Lubinus, Boris Marconi},
  title = {Common Voice: Thyroid Ultrasound Imaging Dataset},
  thesistitle = {Sistema para la clasificación y reconocimiento de imágenes de ultrasonido en
tiroides, basado en técnicas de aprendizaje profundo para el apoyo en el proceso
de diagnóstico según la escala EU-TIRADS},
  year = 2022
}

Bucaramanga, Santander, 2022
TAGS
#region-us 

passage: TAGS
#region-us 
