Literature DB >> 25442795

The application of dynamic contrast-enhanced MRI and diffusion-weighted MRI in patients with maxillofacial tumors.

Erina Kitamoto1, Toru Chikui2, Shintaro Kawano3, Masahiro Ohga4, Kouji Kobayashi4, Yoshio Matsuo5, Takashi Yoshiura5, Makoto Obara6, Hiroshi Honda5, Kazunori Yoshiura2.   

Abstract

RATIONALE AND
OBJECTIVES: To elucidate the characteristics of four types of tumors, including squamous cell carcinoma (SCC), malignant lymphoma (ML), malignant salivary gland tumors (MSGTs), and pleomorphic adenoma (Pleo), in the maxillofacial region using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted MRI (DW-MRI)data.
MATERIALS AND METHODS: A total of 59 tumors were included in this research. DCE-MRI and DW-MRI were performed. We applied the Tofts and Kermode model (TK model) for the DCE-MRI data and obtained three dependent parameters: the influx forward volume transfer constant into the extravascular extracellular space from the plasma (K(trans)), the fractional volume of extravascular extracellular space per unit volume of tissue (ve), and the fractional volume of plasma (vp).
RESULTS: Among the K(trans) values, there were no significant differences between the three types of malignant tumors; however, there was a significant difference between the SCC and Pleo (P = .0099). The ve values of the Pleo were highest, with significant differences compared to the other categories (SCC, P = .0012; ML, P = .0017; and MSGT, P = .041). The ML had the lowest ve values, and there were significant differences between ML and the other two types of malignant tumors (SCC, P = .0278 and MSGT, P = .0062). In 14 (24%) cases, apparent diffusion coefficient (ADC) could not be measured because of poor image quality. The ADC values of the ML were lowest, whereas those of Pleo were highest, similar to that observed for ve.
CONCLUSIONS: The Pleo tumors had lower K(trans) values and higher ve values, which are useful for differentiating them from the malignant tumors. Moreover, the ve was also useful for establishing a diagnosis of ML.
Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  ADC; DCE-MRI; TIC; TK model; head and neck tumor; pharmacokinetic analyses

Mesh:

Substances:

Year:  2014        PMID: 25442795     DOI: 10.1016/j.acra.2014.08.016

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  11 in total

1.  Differential diagnosis of nasopharyngeal carcinoma and nasopharyngeal lymphoma based on DCE-MRI and RESOLVE-DWI.

Authors:  Chengru Song; Peng Cheng; Jingliang Cheng; Yong Zhang; Mengtian Sun; Shanshan Xie; Xiaonan Zhang
Journal:  Eur Radiol       Date:  2019-08-01       Impact factor: 5.315

2.  The diagnostic value of combining conventional, diffusion-weighted imaging and dynamic contrast-enhanced MRI for salivary gland tumors.

Authors:  Ning Zheng; Rui Li; Wenjuan Liu; Shuo Shao; Shan Jiang
Journal:  Br J Radiol       Date:  2018-06-27       Impact factor: 3.039

3.  Differential diagnostic value of diffusion-weighted and dynamic contrast-enhanced MR imaging in non-cystic lesions in floor of the mouth.

Authors:  Ying Yuan; Mengda Jiang; Lizhong Wu; Xiaofeng Tao
Journal:  Dentomaxillofac Radiol       Date:  2018-11-30       Impact factor: 2.419

4.  Diffusion-weighted MRI for differentiation between sialadenitis and pleomorphic adenoma.

Authors:  Guilherme T C Terra; Jefferson X D Oliveira; Adalsa Hernandez; Silvia V Lourenço; Emiko S Arita; Arthur R G Cortes
Journal:  Dentomaxillofac Radiol       Date:  2016-11-15       Impact factor: 2.419

5.  Quantitative dynamic contrast-enhanced and diffusion-weighted MRI for differentiation between nasopharyngeal carcinoma and lymphoma at the primary site.

Authors:  Xiao-ping Yu; Jing Hou; Fei-ping Li; Wang Xiang; Qiang Lu; Yin Hu; Hui Wang
Journal:  Dentomaxillofac Radiol       Date:  2016-02-05       Impact factor: 2.419

6.  Quantitative dynamic contrast-enhanced MRI and readout segmentation of long variable echo-trains diffusion-weighted imaging in differentiating parotid gland tumors.

Authors:  Nan Huang; Zebin Xiao; Yu Chen; Dejun She; Wei Guo; Xiefeng Yang; Qi Chen; Dairong Cao; Tanhui Chen
Journal:  Neuroradiology       Date:  2021-07-09       Impact factor: 2.804

Review 7.  Actual applications of magnetic resonance imaging in dentomaxillofacial region.

Authors:  Migi Johnson; L S Sreela; Philips Mathew; Twinkle S Prasad
Journal:  Oral Radiol       Date:  2021-02-26       Impact factor: 1.852

8.  The application of a gamma distribution model to diffusion-weighted images of the orofacial region.

Authors:  Toru Chikui; Kenji Tokumori; Wannakamon Panyarak; Osamu Togao; Yasuo Yamashita; Shintaro Kawano; Takeshi Kamitani; Kazunori Yoshiura
Journal:  Dentomaxillofac Radiol       Date:  2020-08-14       Impact factor: 2.419

9.  Intravoxel Incoherent Motion Diffusion Weighted Magnetic Resonance Imaging for Differentiation Between Nasopharyngeal Carcinoma and Lymphoma at the Primary Site.

Authors:  Xiao-Ping Yu; Jing Hou; Fei-Ping Li; Hui Wang; Ping-Sheng Hu; Feng Bi; Wei Wang
Journal:  J Comput Assist Tomogr       Date:  2016 May-Jun       Impact factor: 1.826

10.  Head and neck paragangliomas: diffusion weighted and dynamic contrast enhanced magnetic resonance imaging characteristics.

Authors:  Ying Yuan; Huimin Shi; Xiaofeng Tao
Journal:  BMC Med Imaging       Date:  2016-02-01       Impact factor: 1.930

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