Literature DB >> 33096226

Free-breathing radial volumetric interpolated breath-hold examination sequence and dynamic contrast-enhanced MRI combined with diffusion-weighted imaging for assessment of solitary pulmonary nodules.

Hui Feng1, Gaofeng Shi2, Hui Liu1, Qian Xu1, Ning Zhang1, Jie Kuang1.   

Abstract

OBJECTIVE: To test the performance of free-breathing Dynamic Contrast-Enhanced MRI (DCE-MRI) using a radial volumetric interpolated breath-hold examination (VIBE) sequence combined with diffusion-weighted imaging (DWI) for quantitative solitary pulmonary nodule (SPN) assessment.
METHODS: A total of 67 SPN cases receiving routine MRI routine scans, DWI, and dynamic-enhanced MRI in our hospital from May 2017 to November 2018 were collected. These cases were divided into a malignant group and a benign group according to the characteristics of the SPNs. The quantitative DCE-MRI parameters (Ktrans, Kep, Ve) and apparent diffusion coefficient (ADC) values of the nodules were measured.
RESULTS: The Ktrans and Kep values in the malignant group were higher than those in the benign group, while the ADC values in the malignant group were lower than those in the benign group. Furthermore, the Ktrans value of adenocarcinoma was higher than that of squamous cell carcinoma and small cell carcinoma (P < 0.05). The Ve value was significantly different between non-small cell carcinoma and small cell carcinoma (P < 0.05). With an ADC value of 0.98 × 10-3 mm2/s as the threshold, the specificity and sensitivity to diagnose benign and malignant nodules was 90.6% and 80%, respectively.
CONCLUSION: High-temporal-resolution DCE-MRI using the r-VIBE technique in combination with DWI could contribute to pulmonary nodule analysis and possibly serve as a potential alternative to distinguish malignant from benign nodules as well as differentiate different types of malignancies.
Copyright © 2020. Published by Elsevier Inc.

Entities:  

Keywords:  Diagnosis; Diffusion-weighted imaging; Dynamic contrast enhanced; Magnetic resonance imaging; Solitary pulmonary nodules

Year:  2020        PMID: 33096226     DOI: 10.1016/j.mri.2020.10.009

Source DB:  PubMed          Journal:  Magn Reson Imaging        ISSN: 0730-725X            Impact factor:   2.546


  1 in total

1.  MRI Image Segmentation Model with Support Vector Machine Algorithm in Diagnosis of Solitary Pulmonary Nodule.

Authors:  Bo Feng; Meihua Zhang; Hanlin Zhu; Lingang Wang; Yanli Zheng
Journal:  Contrast Media Mol Imaging       Date:  2021-07-20       Impact factor: 3.161

  1 in total

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