We report the utility of DWI and DCE-MRI of the primary tumors and the metastatic nodes in predicting response to chemoradiation therapy in patients with HNSCC. In patients with HNSCC, clinical response is evaluated using the overall disease status, which includes local response from the primary tumor as well as from the metastatic neck node. Thus our approach of combining the analyses of both the primary tumor and the metastatic node is more clinically relevant than approaches described in previously published advanced MRI studies that focused primarily on analysis of the metastatic node [6
]. Because both primary tumors and nodal masses are potent risk factors for prediction of treatment failure and survival in patients with HNSCC [18
], evaluation of both lesions should be used to predict treatment outcome. Inclusion of ADC and DCE-MRI parameters (Ktrans
, and vp
) from primary tumors and nodal masses yielded an AUC of 0.85 and correct classification of 75% in differentiating responders from nonresponders. These results suggest that diffusion and perfusion parameters from two tumor sites may be synergistic interacting factors in the logistic regression analysis and that this interaction might be greater than what would be expected from individual sites or individual measurement parameters.
DWI studies of HNSCC have suggested that ADC can be used as a potential marker for prediction of treatment response and long-term survival [6
]. These results are consistent with the hypothesis that a high pretreatment ADC value may be indicative of micronecrosis and, consequently, of increased resistance to treatment and poor prognosis in these patients. Although our results are similar to those of earlier studies in the literature, we did not find a significant difference in ADC values between responders and nonresponders. Histologic observations have revealed that HNSCCs are very heterogeneous in nature, with marked variations in proliferation and cellular differentiation in different regions of the tumors [20
], and that this heterogeneity greatly influences the clinical course of the disease [21
]. We believe that a nonsignificant difference in ADC values between the two groups of patients in our study might be because of higher intratumor heterogeneity of the relatively smaller cohort of patients or differences in the clinical follow-up times (median, ≈ 24 months) in the current study in comparison with previously published studies that used much shorter response assessment times of 3–12 months from the end of chemoradiation therapy [6
DCE-MRI provides a perfusion parameterနKtrans
နthat reflects a combination of tumor blood flow and microvascular permeability. In the current study, patients with disease responsive to chemoradiation therapy had significantly higher pretreatment Ktrans
values from nodal masses than patients with a partial response or no response. This result is in agreement with previous studies that have reported HNSCC patients exhibiting elevated pretreatment tumor blood flow, increased blood volume, and higher Ktrans
values showed improved response to chemoradiation therapy and prolonged survival [7
]. We also observed higher Ktrans
values from primary tumors of responders in comparison with nonresponders; however, the difference was not significant. Our results and those of earlier published reports support the notion that tumors with relatively higher blood flow are associated with increased oxygenation levels resulting in better access to chemotherapeutic drugs and radiosensitivity [23
]. On the other hand, tumor hypoxia adversely influences treatment response and enhances chemoresistance by impeding delivery of therapeutic agents [24
]. In a recent DCE-MRI study [25
], an inverse correlation was observed between presurgical tumor perfusion parameters and hypoxia in patients with HNSCC; this finding suggests that high tumor blood flow and volume are associated with low levels of hypoxia.
In addition to Ktrans
, pharmacokinetic analysis of DCE-MRI data provides two other perfusion parameters: ve
. The ve
parameter reflects the extravascular extracellular space, which consists of interstitial fluid and connective tissue arranged in a supportive frame structure and is restricted by blood vessel walls and cell plasma membranes. In normal tissues, the extracellular space is balanced in size and shape to ensure adequate supply of nutrients and oxygen to the tissue. However, the composition of the extracellular space of neoplastic tissues is significantly different from that of most normal tissues. In general, the tumor extracellular space is characterized by a large interstitial space, higher collagen concentration, higher interstitial fluid pressure, and higher effective interstitial diffusion coefficient of macromolecules compared with normal tissues [26
]. Although the ve
parameters are physiologically important, previous studies of different cancers [27
] and the current study failed to show a significant difference in ve
values between responders and nonresponders. However, a recent study indicated the importance of ve
as prognostic biomarkers of clinical outcome in patients with osteosarcoma who underwent chemotherapy [29
]. Collectively these studies imply that ve
may not be considered to be reliable as independent parameters. However, given the inherently different physiologic information that ve
provide and the trend in the differences between responders and nonresponders, we believe these parameters may play a complementary role in the overall prediction of treatment response when used in conjunction with other parameters.
A multiparametric data analysis approach allows us to exploit the unique strengths of different imaging techniques. Previously, investigators have reported that the combination of DWI and DCE-MRI could improve diagnostic accuracy and decision making in the characterization of breast lesions [30
]. Thus, we believe that a combined analysis of DCE-MRI parameters (Ktrans
, and vp
) and ADC from both primary tumors and nodal masses may be a better approach to obtain greater discrimination accuracy for differentiating responders from nonresponders as has been observed in the current study.
DCE-MRI–derived parametric maps of primary tumors are vulnerable to severe image distortion caused by motion- and susceptibility-induced artifacts that may result in inaccurate pixel-by-pixel maps unless offline postprocessing motion-correction algorithms are applied to the imaging data. Although DCE-MRI parameters from primary tumors have been reported as being helpful for predicting and monitoring treatment response in patients with HNSCC [4
], the quality of the data and potential errors in fitting the parametric maps could not be ascertained from those studies because the authors did not report these values. In the current study, we used the goodness of fit as a criterion for DCE-MRI data quality. Acceptable χ2
values were observed from 84% of primary tumors and from 100% of nodal masses. The relatively high quality of the data in our study was possible because we used a robust modified radial imaging scheme along with a KWIC filtering reconstruction scheme [31
]. This method is inherently less sensitive to motion-induced artifacts and also provides high-spatial-resolution, high-temporal-resolution DCE-MRI data. In addition, we used a self-navigated autocorrection method to correct for in-plane rotational motion artifacts caused by voluntary and involuntary motion. This method results in substantial motion correction with a relative error of less than 5% [17
]. However despite these efforts, data from five patients were discarded because of severe motion artifacts that led to poor fitting of the DCE-MRI data. A dropout rate of about 17% occurred from primary tumors primarily because of motion from swallowing and coughing. We believe that more stringent acquisition and postprocessing tools would be needed in the future to reduce the dropout rate further.
The evaluation of treatment efficacy and incidences of adverse effects after chemoradiation therapy are dependent on the time to follow-up and thus are different for patients who undergo short-term follow-up than for those who are followed up for longer periods [32
]. However, earlier studies have evaluated the prognostic value of DCE-MRI [5
] and DWI [6
] in predicting treatment response with relatively shorter follow-up periods in HNSCC. In the current study, we used a long-term follow-up period (median = 23.72 months) to assess the prognostic significance of DWI and DCE-MRI in predicting therapeutic response to chemoradiation therapy, and we believe that these results have greater clinical significance in the management of HNSCC patients.
In the current study, data from patients scanned on 1.5- and 3-T MR systems were combined. In addition, investigators have reported that ADC values from submandibular glands were not significantly different when healthy volunteers underwent DWI within 1 hour on MR systems of both field strengths [6
], suggesting that ADC values are independent of field strength. A strong correlation for ADC values between 1.5 and 3 T has also been observed from the parotid glands of healthy volunteers [33
]. For DCE-MRI data, differences in magnetic field were accounted for by using the published relaxivity values at the two field strengths and by using individually measured T1 relaxation times while computing the DCE-MRI parameters. Because DCE-MRI data were acquired using a modified radial imaging sequence with a temporal resolution of 2.5 seconds in the current study, this sequence allowed us to acquire data from only eight central slices with a slice thickness of 5 mm covering the primary tumor and largest metastatic cervical lymph node with a nodal mass as the epicenter from each patient. However, a recent development of a 3D golden angle radial scheme allows more coverage of tissues of interest while acquiring the DCE-MRI data with high temporal resolution [34
]. We believe that this newer scheme will allow us to acquire DCE-MRI data with greater tissue coverage encompassing both primary tumors and nodal masses in all the patients. This scheme will also help in excluding only the motion-corrupted image slices from a particular set of images, thus permitting us to make use of the remaining good-quality image slices for data analysis.
The results of our study should be treated with caution because these findings are from a relatively smaller number of patients (n
= 24). Further studies of a larger cohort may be necessary to confirm our findings. Another limitation of the current study was that the chemotherapy doses and regimens were different among patients because assessment of treatment strategy was based on curative intent. These differences in treatment regimens may have played a confounding role in differentiating responders from nonresponders. To account for these differences, we performed an analysis of a subgroup of patients who underwent only chemoradiation therapy. The discriminatory accuracy for this subgroup of patients was similar to that of the entire patient group. These findings suggest that the differences in treatment regimens did not have an influence in distinguishing between responders and nonresponders in our cohort of patients. Using DCE-MRI and PET, some studies [10
] have shown a relationship between the vascular and metabolic characteristics of HNSCC and have suggested that a combined approach of PET and MRI may provide a better assessment of tumor microenvironment. Although some of our patients also underwent FDG PET before the commencement of chemoradiation therapy, different patient orientations during the two imaging examinations (PET and MRI) precluded us from performing a comparative analysis in predicting treatment response. To address the issue of image coregistration, the use of combined MRI/PET systems would be the best alternative in future studies [35
]. Despite these shortcomings, our study shows that patients exhibiting complete response to chemoradiation therapy can be separated from nonresponders.
In conclusion, our preliminary data suggest that high-spatial-resolution, high-temporal-resolution ADC maps and DCE-MRI parametric maps may be obtained of both primary tumors and nodal masses. A multiparametric approach to analyze pretreatment DWI and DCE-MRI of primary tumors and nodal masses is promising in accurately predicting local treatment response to chemoradiation therapy in HNSCC. However, further studies of a larger patient population are required to confirm these findings.