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Cervical cancer (CC) is one of the most common gynecological malignancies worldwide, and its incidence is gradually increasing. Acurate identification of lymph node metastases (LNM) is crucial for predicting prognosis and choosing the best available treatment. Amide proton transfer weighted (APTw) imaging can detect the chemical exchange rate of between water and endogenous mobile proteins, peptides or polypeptides1. Diffusion kurtosis imaging (DKI) can reflect the limited diffusion movement of water molecules in tissue and the complexity of tissue microstructure 2. This study is aimed to investigate the quantitative prediction of LNM in CC by APTw combined with DKI.
Wang et al. (Wed,) studied this question.
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