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Erschienen in: International Journal of Clinical Oncology 3/2017

20.02.2017 | Original Article

Multivariate evaluation of Thyroid Imaging Reporting and Data System (TI-RADS) in diagnosis malignant thyroid nodule: application to PCA and PLS-DA analysis

verfasst von: Tan Zhang, Fangxuan Li, Jiali Mu, Juntian Liu, Sheng Zhang

Erschienen in: International Journal of Clinical Oncology | Ausgabe 3/2017

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Abstract

Objective

To explore the significance of ultrasonic features in differential diagnosis of thyroid nodules via combining the thyroid imaging reporting and data system (TI-RADS) and multivariate statistical analysis.

Methods

Patients who received surgical treatment and was diagnosed with single thyroid nodule by postoperative pathology and preoperative ultrasound were enrolled in this study. Multivariate analysis was applied to assess the significant ultrasonic features which correlated with identifying benign or malignance and grading the TI-RADS classification of thyroid nodule.

Results

There were significant differences in the nodule size, aspect ratio, internal, echogenicity, boundary, presence or absence of calcifications, calcification type and CDFI between benign and malignant thyroid nodules. Multivariate analysis showed clear-cut distinction both between benign and malignance and among different TI-RADS categories of malignancy nodules. The shape and calcification of the nodule were important factors for distinguish the benign and malignance. Height of the nodule, aspect and calcification was important factors for grading TI-RADS categories of malignancy thyroid nodules.

Conclusions

Ill-defined boundary, irregular shape and presence of calcification related with highly malignant risk for thyroid nodule. The larger height and aspect and presence of calcification related with higher TI-RADS classification of malignancy thyroid nodule.
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Metadaten
Titel
Multivariate evaluation of Thyroid Imaging Reporting and Data System (TI-RADS) in diagnosis malignant thyroid nodule: application to PCA and PLS-DA analysis
verfasst von
Tan Zhang
Fangxuan Li
Jiali Mu
Juntian Liu
Sheng Zhang
Publikationsdatum
20.02.2017
Verlag
Springer Japan
Erschienen in
International Journal of Clinical Oncology / Ausgabe 3/2017
Print ISSN: 1341-9625
Elektronische ISSN: 1437-7772
DOI
https://doi.org/10.1007/s10147-017-1098-x

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