Integrated PET-IVIM-DKI MRI for predicting lymphovascular invasion in NSCLC
Qianqian Chen, Nan Meng, Dujuan Li, Xue Liu, Yaping Wu, Yang Yang, Zhun Huang, Zhe Wang, Meiyun Wang, Fangfang Fu

TL;DR
This study shows that combining PET and MRI scans can help predict lymphovascular invasion in lung cancer, with a specific combination of parameters offering the best accuracy.
Contribution
The study introduces a combined PET-IVIM-DKI MRI model that outperforms individual methods in predicting lymphovascular invasion in NSCLC.
Findings
PET-derived MTV and MRI-derived D parameters are independent predictors of lymphovascular invasion.
The combined model of MTV and D achieves an AUC of 0.841, with high specificity and moderate sensitivity.
Metabolic and diffusion parameters show similar individual diagnostic efficacy for LVI prediction.
Abstract
To evaluate the potential value of 18F-FDG positron emission tomography (PET) and multiparametric MRI (intravoxel incoherent motion, IVIM, and diffusion kurtosis imaging, DKI) in the prediction of lymphovascular invasion (LVI) in non-small cell lung cancer (NSCLC). A total of 73 patients with NSCLC who underwent integrated 18F-FDG PET/MRI were included. IVIM, DKI, and PET parameters with or without LVI of NSCLC were measured and compared, and the area under the receiver operating characteristic curve (AUC) was used to evaluate the diagnostic efficacy of each parameter. Univariate and multivariate logistic regression models were used to study the optimal combination of PET/MRI parameters for predicting LVI. PET-derived parameters (SUVmax, MTV, TLG) and IVIM, DKI MRI-derived parameters (ADCstand, D, MK, MD) were significantly different between patients with and without LVI (p < 0.05).…
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Taxonomy
TopicsMRI in cancer diagnosis · Lung Cancer Diagnosis and Treatment · Radiomics and Machine Learning in Medical Imaging
