ArticleBioengineering (Basel, Switzerland)2023
Amide Proton Transfer-Weighted Imaging Combined with ZOOMit Diffusion Kurtosis Imaging in Predicting Lymph Node Metastasis of Cervical Cancer.
Article in Bioengineering (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The trial behind it
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Who cites it
4 citing papers in PubMed, 7 citations in OpenAlex.
- Restricted spectrum imaging and diffusion kurtosis imaging for assessing lymph node metastasis in cervical cancer: a histogram analysis-based study.BMC cancer · 2025Article
- The value of restriction spectrum imaging in predicting lymph node metastases in rectal cancer: a comparative study with diffusion-weighted imaging and diffusion kurtosis imaging.Insights into imaging · 2024Article
- Article
- Using amide proton transfer-weighted magnetic resonance imaging (MRI) in peritumor tissue to predict parametrial infiltration of cervical cancer: a case-control study.Quantitative imaging in medicine and surgery · 2024Article
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 2 countries.
Funding
Abstract
backgroundThe aim of this study is to investigate the feasibility of amide proton transfer-weighted (APTw) imaging combined with ZOOMit diffusion kurtosis imaging (DKI) in predicting lymph node metastasis (LNM) in cervical cancer (CC). MATERIALS AND
methodsSixty-one participants with pathologically confirmed CC were included in this retrospective study. The APTw MRI and ZOOMit diffusion-weighted imaging (DWI) were acquired. The mean values of APTw and DKI parameters including mean kurtosis (MK) and mean diffusivity (MD) of the primary tumors were calculated. The parameters were compared between the LNM and non-LNM groups using the Student's t-test or Mann-Whitney U test. Binary logistic regression analysis was performed to determine the association between the LNM status and the risk factors. The diagnostic performance of these quantitative parameters and their combinations for predicting the LNM was assessed with receiver operating characteristic (ROC) curve analysis.
resultsPatients were divided into the LNM group (n = 17) and the non-LNM group (n = 44). The LNM group presented significantly higher APTw (3.7 ± 1.1% vs. 2.4 ± 1.0%,
conclusionAPTw and ZOOMit DKI parameters may serve as potential noninvasive biomarkers in predicting LNM of CC.
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