Comparison of diagnostic accuracy and utility of artificial intelligence–optimized ACR TI-RADS and original ACR TI-RADS: a multi-center validation study based on 2061 thyroid nodules

Liu, Ying; Li, Xiaoxian; Yan, Cuiju; Liu, Longzhong; Liu, Ying; Zeng, Hongyan; Huang, Weijun; Li, Qian; Tao, Nansheng; Zhou, Jianhua

doi:10.1007/s00330-022-08827-y

Cited by 13 publications

(14 citation statements)

References 38 publications

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“…There was no difference in diagnostic performances for the Kwak-TIRADS in comparison to the C-TIRADS. Whereas the AI-TIRADS had, although small, higher specificity, accuracy, AUC, and lower unnecessary FNA rate compared with the ACR-TIRADS, which was very similar to the results reported by Liu et al (29). Furthermore, there is some previous studies supporting this conclusion.…”

Section: Discussionsupporting

confidence: 89%

Effect of the categorization method on the diagnostic performance of ultrasound risk stratification systems for thyroid nodules

Cui

et al. 2023

Front. Oncol.

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ObjectiveTo 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.MethodsFrom 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.ResultsA 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).ConclusionThe 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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Section: Discussionsupporting

confidence: 89%

Effect of the categorization method on the diagnostic performance of ultrasound risk stratification systems for thyroid nodules

Cui

et al. 2023

Front. Oncol.

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“…Finally, what to think of the whole RADS approach in the world of artificial intelligence (AI)? Currently, AI is being evaluated for autonomous classification of imaging features required for pre-existing RADSs with encouraging initial results [5]. Given the rate of development in AI, it is possible the same could be done for a future optimized RADS for bone lesions despite the fact that various different imaging signs in different modalities would have to be integrated.…”

Section: Future Directionsmentioning

confidence: 99%

Imaging report and data system (RADS) for bone tumors: where do we stand and future directions

et al. 2022

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“…Multimodal ultrasound imaging has been the focus of ultrasound diagnosis of thyroid nodules in recent years, including the combined application of two or more methods in conventional ultrasound, ACR TI-RADS, shear wave elastography (SWE), super micro vascular imaging (SMI), contrast enhanced ultrasound (CEU), "firefly" imaging and artificial intelligence (AI), and so forth. [7][8][9][10] Imaging of thyroid TI-RADS 4 nodules by multimodal ultrasound can concentrate the advantages of various methods. It is expected to adjust the classification of nodules, improve the diagnostic accuracy of benign and malignant TI-RADS 4 nodules, and reduce the puncture rate and manual operation rate of thyroid TI-RADS 4 nodules to a certain extent.…”

mentioning

confidence: 99%

“…Although surgical resection and pathological examination are the gold standard for differentiating benign and malignant thyroid nodules, noninvasive diagnostic methods are more easily accepted by patients and can avoid unnecessary biopsy and surgery. Multimodal ultrasound imaging has been the focus of ultrasound diagnosis of thyroid nodules in recent years, including the combined application of two or more methods in conventional ultrasound, ACR TI‐RADS, shear wave elastography (SWE), super micro vascular imaging (SMI), contrast enhanced ultrasound (CEU), “firefly” imaging and artificial intelligence (AI), and so forth 7–10 . Imaging of thyroid TI‐RADS 4 nodules by multimodal ultrasound can concentrate the advantages of various methods.…”

mentioning

confidence: 99%

Multimodal ultrasound imaging: A method to improve the accuracy of diagnosing thyroid TI‐RADS 4 nodules

Han

Huang

Wang

et al. 2022

J of Clinical Ultrasound

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Thyroid nodule is a common and frequently occurring disease in the neck in recent years, and ultrasound has become the preferred imaging diagnosis method for thyroid nodule due to its advantages of noninvasive, nonradiation, real‐time, and repeatable. The thyroid imaging, reporting and data system (TI‐RADS) classification standard scores suspicious nodules that are difficult to determine benign and malignant as grade 4, and further pathological puncture is recommended clinically, which may lead to a large number of unnecessary biopsies and operations. Including conventional ultrasound, ACR TI‐RADS, shear wave elastography, super microvascular imaging, contrast enhanced ultrasound, “firefly,” artificial intelligence, and multimodal ultrasound imaging used in combination. In order to identify the most clinically significant malignant tumors when reducing invasive operations. This article reviews the application and research progress of multimodal ultrasound imaging in the diagnosis of TI‐RADS 4 thyroid nodules.

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Comparison of diagnostic accuracy and utility of artificial intelligence–optimized ACR TI-RADS and original ACR TI-RADS: a multi-center validation study based on 2061 thyroid nodules

Cited by 13 publications

References 38 publications

Effect of the categorization method on the diagnostic performance of ultrasound risk stratification systems for thyroid nodules

Effect of the categorization method on the diagnostic performance of ultrasound risk stratification systems for thyroid nodules

Imaging report and data system (RADS) for bone tumors: where do we stand and future directions

Multimodal ultrasound imaging: A method to improve the accuracy of diagnosing thyroid TI‐RADS 4 nodules

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