Purpose

Nasopharyngeal carcinoma (NPC) has been linked to Epstein-Barr virus (EBV)¹. The current standard of care for locally-advanced NPC is definitive chemoradiation therapy (chemo-RT)². Due to deep anatomic tumor location and proximity to critical tissue structures, treatment is still associated with toxicities¹. Therefore, identification of quantitative imaging (QI) metrics that predict the optimal chemo-RT dosage prior to treatment would greatly benefit NPC patients. The pre-treatment (TX) apparent diffusion coefficient (ADC) skewness value is a predictor of locoregional failure (LRF) in NPC³. DCE-MRI-derived QI metrics correlate with clinical stage of NPC⁴. The fast exchange regime (FXR) model volume transfer constant K^trans has exhibited promise at pre-TX for predicting chemo-RT in HN cancer⁵. A previous study reported that the combination of K^trans and ADC metrics were superior to either separately in detecting early-stage NPC accurately⁶. The aim of the present study was to identify whether the QI metrics from pre-TX NG IVIM DW- and FXR DCE-MRI can predict patients with LRF in NPC.

Materials and Methods

Patient: Our institutional review board approved this retrospective study, and written informed consent was obtained from all eligible NPC patients prior to the pre-TX MRI study. Between June 2014 and September 2016, a total of 29 NPC patients (median age: 43 years, range: 21-67 years; 20 M/9 F) were enrolled, all were treated with chemoradiation therapy (standard dose 70Gy). The clinical response was based on standard-of-care imaging and clinical follow-up after treatment completion up to 33 months. Treating physicians categorized the patients into two groups, with (n=6) and without (n=23) locoregional failure (LRF).
DWI and DCE data acquisition: MRI protocol consisted of multi-planar T₁/T₂ weighted imaging followed by multiple b-value DWI on a 3.0T scanner (Ingenia, Philips Healthcare, Netherlands) using a neurovascular phased-array coil as detailed in Paudyal et al.⁷. T₁w DCE-MRI were acquired using a fast 3D Spoiled Gradient Recalled sequence as detailed elsewhere⁸.
DW- and DCE-MRI data analysis: ADC was calculated from mono-exponential, and (b) true diffusion (D), pseudo diffusion (D^*), diffusion kurtosis (K) coefficients, and perfusion fraction (f) from NG-IVIM model^9,10 were estimated by fitting all multiple b- value data. The longitudinal relaxation rate, R₁ (R₁=1/T₁), with time derived from the FXR model yields the following QI metrics: K^trans, extravascular extracellular volume fraction [EES], v_e, and the mean lifetime of intracellular water molecules τ_i, a marker of cellular metabolic activity¹¹. Regions of interest (ROIs) were delineated on the primary tumor by radiation oncologists on the multiple b- value DW image (b = 0 s/mm²) and late phase of T₁w DCE images using ImageJ software¹². All image processing was performed using in-house software MRI-QAMPER (MRI Quantitative Analysis of Multi-Parametric Evaluation Routines)^8,13.
Statistical analysis: Wilcoxon rank-sum test was performed to assess the differences in QI values between the groups. Cumulative incidence analysis (CIA) was performed on the two groups, dichotomized with Youden’s index¹⁴. Competing-risks regression, based on Fine and Gray’s (FG) proportional sub hazards model, was used to estimate subdistribution hazard ratios (SHRs) and their adjusted 95% confidence intervals (CIs) were calculated. A p-value <0.05 was considered statistically significant. Statistical analysis was performed using R¹⁵.

Results

The mean pre-TX tumor volume was not significantly different between patients with and without LRF of NPC (P>0.05). Representative pre-TX ADC, D, f, and K maps display the tumor cellularity, vascularity, and microstructure integrity, respectively, in patients with (n=6) and without LRF (n=22) (Figure 1). The mean f showed borderline-significant difference between the groups (P=0.08). The mean ve value was significantly higher in patients without LRF than those with LRF (P=0.03). Ktrans and ti values were leaning towards a significant difference between two groups (P=0.14 for Ktrans and P=0.11 for ti). Representative pre-TX maps of K^trans, ve, and τ_i are displayed in Figure 2 for two groups. The regions with alternating high and low values of K^trans and τ_i can be seen. D and K^trans histograms tend to show sharper peaks in patients who experienced LRF compared to those without LRF. K and τi histograms showed the longer tail towards higher values with LRF than those without LRF (Figure 3). QI metrics from DW- and DCE-MRI analyses are given in Table 1. The results from the CIA and FG proportional sub-hazards model are listed in Table 2. Gary’s test showed a significant difference between dichotomized ADC, D, and f values (P<0.05). K showed a significant difference (P=0.034), whereas τi showed a borderline significant trend (0.07) with the FG proportional sub-hazards model analysis. Figure 4 displays the predicted CIA analysis curves for the two groups.

Discussion and Conclusion

QI metrics values indicate different tumor cell density, microstructure integrity, permeability, and cell metabolic activity between patients with and without LRF in NPC. Representative parametric maps and voxel distribution (%) histogram plots of QI metrics revealed tumor heterogeneity between the two groups. CIA analysis demonstrated that the pre-TX ADC, D, and τi could be the a priori predictors of LRF in NPC patients.
After appropriate validation in a larger NPC population, these findings may be useful for adaptive radiotherapy.

Acknowledgements

NIH U01 CA211205 and NIH/NCI Cancer Center Support Grant P30 CA008748

References

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