Prediction of the development of distant metastases from nasopharyngeal carcinoma using Diffusion-Weighted Imaging
Qi Yong Ai1, Ann D. King1, Benjamin King Hong Law1, Lok Yiu Sheila Wong1, Kunwar S. Bhatia1, David Ka Wai Yeung2, and Brigette B.Y. Ma2

1Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, Hong Kong, 2Department of Clinical Oncology, The Chinese University of Hong Kong, Shatin, Hong Kong

Synopsis

This study evaluated pre-treatment diffusion weighted imaging of primary nasopharyngeal carcinoma for the prediction of patients at risk of distant metastases, based on long-term follow-up for at least 5 years. Analysis was performed of ADC parameters using histogram analysis (ADCmean, ADCskewness and ADCkurtosis), together with stage and volume of the primary tumour and nodes. Multivariate analysis showed pre-treatment ADCskewness, T stage and nodal volume were significant ( p =0.026, 0.022 and 0.005, respectively), distant metastases being more likely in patients with tumours with ADC values skewed toward the higher ADC range, and higher T stage and nodal volume.

Background and Purpose

The incidence of distant metastases (DM) from nasopharyngeal carcinoma (NPC) ranges from 5% at diagnosis up to 41% during follow-up[1] and DM have become the main cause of mortality in these patients. Therefore, accurate prediction of patients at risk of DM potentially may lead to better management of this disease in the future. Using diffusion weighted imaging(DWI), high apparent diffusion coefficients (ADC) have been associated with poor outcomes in patients with squamous cell carcinoma of the head and neck[2]. At present there is little data showing the predictive value of NPC with long term outcome[3], especially in regard to the prediction of distant metastases. This study aimed at using pre-treatment DWI to predict patients at risk of DM based on long-term clinical follow-up at a minimum of 5 years.

Materials and methods

Patients with biopsy-proven NPC without evidence of distant metastases at diagnosis, in whom clinical follow-up was available for a minimum of 5 years were included in the study. Diffusion-weighted imaging was performed pre-treatment on the primary tumour on a 1.5T MRI (ACS-NT, Philips Medical Systems) using six b-values (b=0, 100, 200, 300, 400 and 500s/mm2). Conventional anatomy sequences were performed also.

Each slice of the primary tumour was outlined on the ADC maps to obtain data from the entire tumour volume. ADC parameters were acquired from ADC histograms including ADCmean, ADCskewness and ADCkurtosis. In addition data regarding stage (T and N stage) and volume (primary and nodal) were analysed.

The ADC parameters, tumour volumes and stage were compared between patients with distant metastases failure (DMF) and patients with distant metastases control (DMC) using the student t-test and Chi-square test to compare the two group as well as logistic regression. Parameters with p-value of less than 0.05 were considered to indicate a statistically significant difference.

Results

162 patients with primary tumours (male: 123, female: 39; follow-up time: 6.1-119.6 months) were analyzed, DMF occurred in 26/162 (16%) and DMC occurred in 136/162 (84%). Compared to patients with DMC, patients with DMF had significantly lower primary tumour ADCskewness (ADCs skewed towards the higher values), higher T and N stage, and higher primary and nodal volume (table 1). Multivariate analysis showed that pre-treatment ADCskewness, T stage and nodal volume remained significant (p-values of 0.026, 0.022 and 0.005, respectively).

Discussion

High stromal content and micronecrosis increase tumour ADC, and high stromal content and tumour hypoxia are two of the factors that are associated with an increased risk of distant metastases[4–6]. Therefore it could be postulated that a high primary tumour ADC could be a predictor for distant metastases. In this study the ADCmean showed no significant difference between those patients with DMC and those with DMF, however ADCskewness, which is a more sophisticated method of analysis that takes into account tumour heterogeneity, showed that tumours with a distribution of ADC values skewed towards the high ADCs were more likely to have distant metastases. On multivariate analysis primary tumours with the ADC values skewed towards the higher range remained significant together with high T stage and high nodal volume.

Conclusion

The pre-treatment DWI of primary tumour has the potential to allow prediction of patients at risk of distant metastases. Distant metastases were more likely in those patients with primary tumours with ADC values skewed toward the higher range.

Acknowledgements

No acknowledgement found.

References

[1] Marks JE, Phillips JL, Menck HR. The National Cancer Data Base report on the relationship of race and national origin to the histology of nasopharyngeal carcinoma. Cancer 1998;83:582–8.

[2] Hermans R, Vandecaveye V. Diffusion-weighted MRI in head and neck cancer. Cancer Imaging 2007;7:126–7. doi:10.1102/1470-7330.2007.0018.

[3] Zhang Y, Liu X, Zhang Y, Li W-F, Chen L, Mao Y-P, et al. Prognostic value of the primary lesion apparent diffusion coefficient (ADC) in nasopharyngeal carcinoma: a retrospective study of 541 cases. Sci Rep 2015;5:12242. doi:10.1038/srep12242.

[4] Juliette P. Driessen, Caldas-Magalhaes J, Janssen LM, et al. Diffusion-weighted MR imaging in Laryngeal and Hypopharyngeal Carcinoma: Association between Apparent Diffusion Coefficient and Histologic Findings. Radiology 2014;272:456–63. doi:10.1148/radiol.14131173.

[5] Hatakenaka M, Nakamura K, Yabuuchi H, et al. Pretreatment apparent diffusion coefficient of the primary lesion correlates with local failure in head-and-neck cancer treated with chemoradiotherapy or radiotherapy. Int J Radiat Oncol Biol Phys 2011;81:339–45. doi:10.1016/j.ijrobp.2010.05.051.

[6] Lu X, Kang Y. Hypoxia and hypoxia-inducible factors: Master regulators of metastasis. Clin Cancer Res 2010;16:5928–35. doi:10.1158/1078-0432.CCR-10-1360.

Figures

Table1: Predictive factors for DM on univariate analysis



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
3452