The Application of Dynamic Contrast-Enhanced MRI and Diffusion-Weighted MRI in Patients with Maxillofacial Tumors

Erina Kitamoto, Toru Chikui, Shintaro Kawano, Masahiro Ohga, Kouji Kobayashi, Yoshio Matsuo, Takashi Yoshiura, Makoto Obara, Hiroshi Honda, Kazunori Yoshiura

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26 Citations (Scopus)


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[U+FF09]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 (Ktrans), the fractional volume of extravascular extracellular space per unit volume of tissue (ve), and the fractional volume of plasma (vp). Results: Among the Ktrans 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 Ktrans 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.

Original languageEnglish
Pages (from-to)210-216
Number of pages7
JournalAcademic Radiology
Issue number2
Publication statusPublished - Feb 1 2015

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging


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