Our study results showed that multiple pharmacokinetic parameters derived from qDCE-MRI were different between stage III-IV and stage I-II OTSCCs. Stage I-II lesions had higher Ktrans, Kep and Vp values compared with stage III-IV lesions. Kep was an independent predictor for stage III-IV lesions.
qDCE-MRI with tracer pharmacokinetic modeling has emerged as a versatile technique for characterizing the microvasculature function of the tumor. It can obtain the microvasculature function of tissue perfusion, vessel permeability and extracellular leakage space via monitoring the delivery and distribution of intravascular contrast agent [5,6]. To date, qDCE-MRI has been widely used for tumor detection and characterization, therapy monitoring and predicting prognosis in various tumors such as protaste cancer, breast cancer, and gliomas . Nevertheless, the relative low reliability of this technique restricts its adoption in routine clinical practice [5,6]. There are many critical factors that influence the reliability of qDCE-MRI, including baseline T1 mapping, temporal resolution, and AIF in data acquisition [5,6]. Baseline T1 mapping, which is used to compensate for the nonlinear relationship between MRI signal intensity and contrast agent concentration, is essential for accurate kinetic fitting of acquired DCE-MRI data . In our study, we used five flip angles before injection of contrast agent to obtain the ideal baseline T1 mapping. Compared with other techniques of data acquisition for baseline T1 mapping (e.g., double flip angle technique, the inversion recovery technique, and the Look-Locker technique), the MFA method is now regarded as the technique of choice because it can provide more accurate, robust T1 mapping and kinetic parameter estimation with a short scan time but without sacrificing signal-to-noise ratio (SNR) [5,6]. In addition, the temporal resolution of DCE-MRI in our study was 3 sec, which was higher than what was found in most of the previous studies [9,13,14]. It has been suggested to use a temporal resolution from 1 to 5 sec, after which the errors of quantitative DCE-MRI parameters calculation grow rapidly with the decrease in temporal resolution . The chosen temporal resolution of 3 sec in our study is an appropriate balance between the temporal resolution, SNR and spatial resolution, which allowed us to obtain high-quality DCE-MRI images and, in the meantime, capture the hemodynamic processes of contrast agents. AIF, which estimates the time course of the contrast agent concentration in the feeding arteries, is another crucial prerequisite for quantitative analysis of DCE-MRI. At present, the individual or population AIF can be used in DCE-MRI . In our study, the AIF was extracted from individual patients rather than the population. Compared with the population AIF applied by previous studies [9,13,14], individual AIF could reflect the real AIF more closely, as it takes contrast agent injection rates and doses into account and presumes small intersubject variabilities . In addition to the above key points in data acquisition, a 3-D VOI was used in our study. To date, most of previous studies have used a two-dimensional ROI (2-D ROI) derive the pharmacokinetic parameters from DCE-MRI for tumor assessment in head and neck cancer, while few studies have used a 3-D VOI for tumor analysis [9,17]. Compared with 2-D ROI for tumor analysis, 3-D VOI can obtain the volumetric parameters and the heterogeneity data of the whole tumor, thus theoretically can more accurately describe the physiological characteristics of lesions .
DCE-MRI has been determined as a useful tool for diagnosis and differential diagnosis of benign and malignant tumors in head and neck, characterizing metastatic cervical lymph nodes, evaluating tumor cell proliferation and microvessel attenuation, predicting treatment response, evaluating treatment outcome and prognosis in head and neck cancers [19-21]. Previously, DCE-MRI has been found to be useful for differential diagnosis between benign and malignant tongue lesions , as well as between squamous cell carcinoma and undifferentiated carcinoma in head and neck . Results indicated that the mean slope of the time-intensity curve (TIC) derived from DCE-MRI in malignant tongue tumors was steeper than that in benign lesions . And the semi-quantitative parameter AUC at initial 90 s was the most accurate parameter to distinguish squamous cell carcinoma from undifferentiated carcinoma . A recent study has shown that the value of Ktrans, Ve and initial AUC obtained from qDCE-MRI in metastatic cervical lymph nodes from SCC were higher than that in benign lymph nodes . Nevertheless, there have been a limited number of studies that have utilized quantitative DCE-MRI for predicting the staging of SCC in the head and neck, and discrepancies exist in the previous reports. For example, Chikui et al. found that the clinical T stage of oral squamous cell carcinoma is negatively correlated with Ktrans and the N stage showed a negative correlation with Ktrans and Vp . In contrast, Leifels et al. reported that the Kep was higher in HNSCC cancers with N2-3 stages; however, no diﬀerences were observed in DCE-MRI parameters between T1-2 and T3-4 tumors . In our study, Ktrans, Kep and Vp were found to be lower in pathologic stage III-IV lesions than in stage I-II lesions; these results are similar to that of Chikui et al  but different from that of Leifels et al . This discrepancy might be related to the different protocol of DCE-MRI scanning as well as different method of pharmacokinetic analysis. In our study, the MFA method for T1 measurement, individual AIF, higher temporal resolution and 3-D VOI were applied. These data acquisition and DCE-MRI data analysis methods made our results more reliable than the previous studies, which used the dual flip angle method, population AIF, and temporal resolution of 3.5 ms  and 6 ms . Additionally, the pathologic TNM stage was used in our study, which is different from the study by Chikui et al , which applied the clinical TNM stage. It is reasonable that our results are more favorable for reference in clinical practice.
In this study, the advanced stage OTSCCs had lower Ktrans, Kep and Vp values than early stage ones. It has been shown that DCE-MRI parameters, such as Ktrans and Kep, are negatively correlated with tumor hypoxia . In addition, the more invasive oral squamous cell carcinoma had more highly hypoxic areas but less vessel density because of the gradual destruction of microvessels during tumor growth [25-27]. Ktrans is positively coupled to blood flow, microvessel permeability and surface area, while Kep represents microvessel permeability [7,28]. Numerous studies have demonstrated that Ktrans was negatively correlated with the fraction of hypoxic cells in tumors [29,30], and there is a strong positive correlation between Kep and microvessel density in HNSCCs . Therefore, the highly hypoxic areas but with low microvessel density might be an explanation why advanced stages of OTSCC had lower Ktrans and Kep values in our study.
In our study, multivariate logistic analysis showed that Kep was an independent predictor for advanced stage OTSCC. Kep had the highest predictive capability, with a sensitivity of 64.3%, a specificity of 82.6%, a PPV of 81.8%, a NPV of 65.5%, and an accuracy of 72.5%. Kep was more valuable for predicting the staging of OTSCC compared with other DCE-MRI parameters such as Ktrans and Vp. Kep, which represents the rate constant between the plasma and extracellular space, and is regarded as a marker that directly reflects microvessel permeability . Previous studies have shown that the Kep positively correlated with the mean blood vessel count and mean vessel area fraction parameter . The advanced stage OTSCCs commonly had less vessel density because of the highly hypoxic areas , resulting in its lower Kep within tumors. Taken together, our results indicated that Kep can be used as a valuable predictive biomarker for tumor staging of OTSCC.
There was no significant difference in Ve between the stage III-IV lesions and the stage I-II lesions in our study. Ve, which represents the volume of the extravascular extracellular leakage space, was mainly influenced by cellular density and tumor interstitium . Pathologically, the cellular density and tumor interstitium of OTSCCs were variable among different stages and grades of tumor. Cell proliferation in advanced OTSCCs may be more intensive than that of early stage OTSCCs, which would cause high cellular density and contractible tumor interstitium resulting in low Ve. Nonetheless, the rapidly growing late stage OTSCCs may have large regions suffering from chronic or acute hypoxia in the central area, which may lead to a focal or extensive apoptotic response and then decrease the cellular density [32, 33]. Therefore, Ve can be influenced by the varying cellular density between advanced and early stages of OTSCC; thus, it is less robust for predicting the stages of OTSCC compared with other qDCE-MRI parameters.
Our study had several limitations. First, the number of patients included was relatively small; a larger cohort is needed to confirm our results in a future investigation. Second, the enrolled patients did not receive follow-up. As a result, the correlation between qDCE-MRI parameters and survival outcomes remains unknown. Future follow-up investigation is needed to determine whether this method could be used to predict survival outcomes in patients with OTSCC.