Risk Stratification of Thyroid Nodule: From Ultrasound Features to TIRADS

Since the 1990s, ultrasound (US) has played a major role in the assessment of thyroid nodules and their risk of malignancy. Over the last decade, the most eminent international societies have published US-based systems for the risk stratification of thyroid lesions, namely, Thyroid Imaging Reporting...

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Veröffentlicht: MDPI - Multidisciplinary Digital Publishing Institute 2022
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collection Directory of Open Access Books
description Since the 1990s, ultrasound (US) has played a major role in the assessment of thyroid nodules and their risk of malignancy. Over the last decade, the most eminent international societies have published US-based systems for the risk stratification of thyroid lesions, namely, Thyroid Imaging Reporting And Data Systems (TIRADSs). The introduction of TIRADSs into clinical practice has significantly increased the diagnostic power of US to a level approaching that of fine-needle aspiration cytology (FNAC). At present, we are probably approaching a new era in which US could be the primary tool to diagnose thyroid cancer. However, before using US in this new dominant role, we need further proof. This Special Issue, which includes reviews and original articles, aims to pave the way for the future in the field of thyroid US. Highly experienced thyroidologists focused on US are asked to contribute to achieve this goal.
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publisher MDPI - Multidisciplinary Digital Publishing Institute
publisherStr MDPI - Multidisciplinary Digital Publishing Institute
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spelling doab-20.500.12854ir-809562024-03-31T13:10:33Z Risk Stratification of Thyroid Nodule: From Ultrasound Features to TIRADS Trimboli, Pierpaolo n/a thyroid ultrasonography follicular neoplasm follicular lesion of unknown significance follicular thyroid cancer papillary thyroid carcinoma neoplasm metastasis biopsy fine-needle thyroglobulin US-guided minimally invasive techniques radiofrequency ablation RFA benign thyroid nodules thyroid cancer DTC recurrences PTMC long term follow-up regrowth classification system ultrasound classification system TIRAD nodule risk stratification TI-RADS fine-needle aspiration cancer ultrasound scintigraphy non-autonomously functioning thyroid imaging reporting and data systems (TIRADS) risk of malignancy (ROM) thyroid nodules paediatrics radiotherapy risk assessment DTC thyroid neoplasm medical imaging artificial intelligence machine learning deep learning radiomics prediction diagnosis Thyroid Imaging Reporting and Data Systems (TIRADS) pediatric thyroid nodules neck ultrasound contrast-enhanced ultrasound (CEUS) papillary thyroid cancer TIRADS thyroid nodule fine-needle aspiration biopsy elastosonography thema EDItEUR::M Medicine and Nursing thema EDItEUR::M Medicine and Nursing::MJ Clinical and internal medicine Since the 1990s, ultrasound (US) has played a major role in the assessment of thyroid nodules and their risk of malignancy. Over the last decade, the most eminent international societies have published US-based systems for the risk stratification of thyroid lesions, namely, Thyroid Imaging Reporting And Data Systems (TIRADSs). The introduction of TIRADSs into clinical practice has significantly increased the diagnostic power of US to a level approaching that of fine-needle aspiration cytology (FNAC). At present, we are probably approaching a new era in which US could be the primary tool to diagnose thyroid cancer. However, before using US in this new dominant role, we need further proof. This Special Issue, which includes reviews and original articles, aims to pave the way for the future in the field of thyroid US. Highly experienced thyroidologists focused on US are asked to contribute to achieve this goal. 2022-05-06T11:18:05Z 2022-05-06T11:18:05Z 2022 book ONIX_20220506_9783036537603_21 9783036537603 9783036537597 https://directory.doabooks.org/handle/20.500.12854/80956 eng image/jpeg Attribution 4.0 International https://mdpi.com/books/pdfview/book/5294 https://mdpi.com/books/pdfview/book/5294 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-3759-7 10.3390/books978-3-0365-3759-7 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036537603 9783036537597 212 Basel open access
spellingShingle n/a
thyroid
ultrasonography
follicular neoplasm
follicular lesion of unknown significance
follicular thyroid cancer
papillary thyroid carcinoma
neoplasm metastasis
biopsy
fine-needle
thyroglobulin
US-guided minimally invasive techniques
radiofrequency ablation
RFA
benign thyroid nodules
thyroid cancer
DTC recurrences
PTMC
long term
follow-up
regrowth
classification system
ultrasound classification system
TIRAD
nodule
risk stratification
TI-RADS
fine-needle aspiration
cancer
ultrasound
scintigraphy
non-autonomously functioning
thyroid imaging reporting and data systems (TIRADS)
risk of malignancy (ROM)
thyroid nodules
paediatrics
radiotherapy
risk assessment
DTC
thyroid neoplasm
medical imaging
artificial intelligence
machine learning
deep learning
radiomics
prediction
diagnosis
Thyroid Imaging Reporting and Data Systems (TIRADS)
pediatric thyroid nodules
neck ultrasound
contrast-enhanced ultrasound (CEUS)
papillary thyroid cancer
TIRADS
thyroid nodule
fine-needle aspiration biopsy
elastosonography
thema EDItEUR::M Medicine and Nursing
thema EDItEUR::M Medicine and Nursing::MJ Clinical and internal medicine
Risk Stratification of Thyroid Nodule: From Ultrasound Features to TIRADS
title Risk Stratification of Thyroid Nodule: From Ultrasound Features to TIRADS
title_full Risk Stratification of Thyroid Nodule: From Ultrasound Features to TIRADS
title_fullStr Risk Stratification of Thyroid Nodule: From Ultrasound Features to TIRADS
title_full_unstemmed Risk Stratification of Thyroid Nodule: From Ultrasound Features to TIRADS
title_short Risk Stratification of Thyroid Nodule: From Ultrasound Features to TIRADS
title_sort risk stratification of thyroid nodule from ultrasound features to tirads
topic n/a
thyroid
ultrasonography
follicular neoplasm
follicular lesion of unknown significance
follicular thyroid cancer
papillary thyroid carcinoma
neoplasm metastasis
biopsy
fine-needle
thyroglobulin
US-guided minimally invasive techniques
radiofrequency ablation
RFA
benign thyroid nodules
thyroid cancer
DTC recurrences
PTMC
long term
follow-up
regrowth
classification system
ultrasound classification system
TIRAD
nodule
risk stratification
TI-RADS
fine-needle aspiration
cancer
ultrasound
scintigraphy
non-autonomously functioning
thyroid imaging reporting and data systems (TIRADS)
risk of malignancy (ROM)
thyroid nodules
paediatrics
radiotherapy
risk assessment
DTC
thyroid neoplasm
medical imaging
artificial intelligence
machine learning
deep learning
radiomics
prediction
diagnosis
Thyroid Imaging Reporting and Data Systems (TIRADS)
pediatric thyroid nodules
neck ultrasound
contrast-enhanced ultrasound (CEUS)
papillary thyroid cancer
TIRADS
thyroid nodule
fine-needle aspiration biopsy
elastosonography
thema EDItEUR::M Medicine and Nursing
thema EDItEUR::M Medicine and Nursing::MJ Clinical and internal medicine
topic_facet n/a
thyroid
ultrasonography
follicular neoplasm
follicular lesion of unknown significance
follicular thyroid cancer
papillary thyroid carcinoma
neoplasm metastasis
biopsy
fine-needle
thyroglobulin
US-guided minimally invasive techniques
radiofrequency ablation
RFA
benign thyroid nodules
thyroid cancer
DTC recurrences
PTMC
long term
follow-up
regrowth
classification system
ultrasound classification system
TIRAD
nodule
risk stratification
TI-RADS
fine-needle aspiration
cancer
ultrasound
scintigraphy
non-autonomously functioning
thyroid imaging reporting and data systems (TIRADS)
risk of malignancy (ROM)
thyroid nodules
paediatrics
radiotherapy
risk assessment
DTC
thyroid neoplasm
medical imaging
artificial intelligence
machine learning
deep learning
radiomics
prediction
diagnosis
Thyroid Imaging Reporting and Data Systems (TIRADS)
pediatric thyroid nodules
neck ultrasound
contrast-enhanced ultrasound (CEUS)
papillary thyroid cancer
TIRADS
thyroid nodule
fine-needle aspiration biopsy
elastosonography
thema EDItEUR::M Medicine and Nursing
thema EDItEUR::M Medicine and Nursing::MJ Clinical and internal medicine
url ONIX_20220506_9783036537603_21