NDLI: Preoperative prediction of extrathyroidal extension: radiomics signature based on multimodal ultrasound to papillary thyroid carcinoma

Content Provider	Springer Nature : BioMed Central
Author	Wan, Fang He, Wen Zhang, Wei Zhang, Yukang Zhang, Hongxia Guang, Yang
Abstract	Background There is a recognized need for additional approaches to improve the accuracy of extrathyroidal extension (ETE) diagnosis in papillary thyroid carcinoma (PTC) before surgery. Up to now, multimodal ultrasound has been widely applied in disease diagnosis. We investigated the value of radiomic features extracted from multimodal ultrasound in the preoperative prediction of ETE. Methods We retrospectively pathologically confirmed PTC lesions in 235 patients from January 2019 to April 2022 in our hospital, including 45 ETE lesions and 205 non-ETE lesions. MaZda software was employed to obtain radiomics parameters in multimodal sonography. The most valuable radiomics features were selected by the Fisher coefficient, mutual information, probability of classification error and average correlation coefficient methods (F + MI + PA) in combination with the least absolute shrinkage and selection operator (LASSO) method. Finally, the multimodal model was developed by incorporating the clinical records and radiomics features through fivefold cross-validation with a linear support vector machine algorithm. The predictive performance was evaluated by sensitivity, specificity, accuracy, F1 scores and the area under the receiver operating characteristic curve (AUC) in the training and test sets. Results A total of 5972 radiomics features were extracted from multimodal sonography, and the 13 most valuable radiomics features were selected from the training set using the F + MI + PA method combined with LASSO regression. The multimodal prediction model yielded AUCs of 0.911 (95% CI 0.866–0.957) and 0.716 (95% CI 0.522–0.910) in the cross-validation and test sets, respectively. The multimodal model and radiomics model showed good discrimination between ETE and non-ETE lesions. Conclusion Radiomics features based on multimodal ultrasonography could play a promising role in detecting ETE before surgery.
Related Links	https://bmcmedimaging.biomedcentral.com/counter/pdf/10.1186/s12880-023-01049-8.pdf
Ending Page	12
Page Count	12
Starting Page	1
File Format	HTM / HTML
ISSN	14712342
DOI	10.1186/s12880-023-01049-8
Journal	BMC Medical Imaging
Issue Number	1
Volume Number	23
Language	English
Publisher	BioMed Central
Publisher Date	2023-07-20
Access Restriction	Open
Subject Keyword	Imaging Radiology Multimodal ultrasound Extrathyroidal extension Radiomics signature
Content Type	Text
Resource Type	Article
Subject	Radiology, Nuclear Medicine and Imaging
Journal Impact Factor	2.9/2023
5-Year Journal Impact Factor	2.8/2023

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