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MRI-based radiomics analysis to predict preoperative lymph node metastasis in papillary thyroid carcinoma
Wenjuan Hu1, Hao Wang1, Ran Wei1
1Department of Radiology, Minhang Hospital, Fudan University, Minhang District, Shanghai, China.
Gland Surgery
|November 23, 2020
Summary
This study developed a magnetic resonance imaging (MRI) radiomics model to predict lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC). The combined MRI radiomics model showed high accuracy in identifying patients with LNM, aiding personalized treatment strategies.
Area of Science:
- Radiology
- Oncology
- Medical Imaging
Background:
- Papillary thyroid carcinoma (PTC) is a common endocrine malignancy.
- Lymph node metastasis (LNM) is a critical prognostic factor in PTC.
- Accurate preoperative prediction of LNM is essential for treatment planning.
Purpose of the Study:
- To develop and validate a magnetic resonance imaging (MRI) radiomics model for predicting preoperative lymph node metastasis (LNM) in patients with papillary thyroid carcinoma (PTC).
- To evaluate the clinical utility of the developed radiomics model.
Main Methods:
- Retrospective review of 129 PTC patients' data.
- Extraction of 395 radiomics features from T2WI, DWI, and T1C+ MRI sequences.
- Feature selection using mRMR and LASSO, followed by model construction and validation with ROC analysis and DCA.
Main Results:
- A combined MRI radiomics model outperformed individual sequence models in predicting LNM.
- The combined model achieved AUC values of 0.835 (training) and 0.830 (validation).
- Radiomics nomogram and DCA confirmed the clinical utility of the combined model.
Conclusions:
- An MRI radiomics model utilizing anatomical and functional imaging can serve as a non-invasive biomarker for identifying PTC patients at high risk of LNM.
- This approach facilitates the development of individualized treatment strategies for PTC.
