Elsevier

Academic Radiology

Volume 22, Issue 2, February 2015, Pages 210-216
Academic Radiology

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

https://doi.org/10.1016/j.acra.2014.08.016Get rights and content

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 (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.

Section snippets

Study Population

We investigated patients with untreated primary head and neck tumors who were referred to the Department of Oral Surgery and underwent DCE-MRI at our institute between April 2009 and October 2013. The institutional review board approved this study, and the requirement for informed consent was waived. Of the patients, one was omitted from this study because of poor images; therefore, 55 patients were enrolled in this study.

The characteristics of the patients (n = 55; 26 male and 29 female;

TK Model Analysis

Table 2 shows the mean Ktrans, ve, vp, Kep, and AUGC values for benign neoplasms (Pleo) and malignant tumors. Both Table 3 and Figure 1 present the results of the Steel-Dwass test performed to evaluate the parameters with significant differences between the four categories. Figure 2, Figure 3, Figure 4, Figure 5 show representative images of the four categories.

Pleo had lower Ktrans values compared to the malignant tumor (P = .0089) (Table 2). There was a significant difference between SCC and

Discussion

The malignant tumors had higher Ktrans values than the Pleo tumors (Table 2, Fig 1a). The Ktrans is determined according to both the permeability surface area product and tissue perfusion (blood flow) 24, 25. A lower Ktrans of the Pleo suggests a lower degree of permeability or a small blood flow. Moreover, the higher ve was also characteristic of Pleo.

Making the differential diagnosis between SCC (or MSGT) and ML was quite difficult based on the subjective TIC pattern classification. For

Conclusions

The Ktrans value of the Pleo was significantly smaller than that of SCC; however, it showed considerable overlap with those of the other two malignant tumors. Pleo has a characteristic large ve value, whereas ML has characteristically small ve values. Therefore, pharmacokinetic analyses are regarded to be an acceptable tool for making the differential diagnosis of lesions in the maxillofacial region.

Acknowledgments

This work was supported by an MEXT (Ministry of Education, Culture, Sports, Science and Technology) Grant-in-Aid for Scientific Research (C) 2 4 5 9 2 8 3 4.

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