Objective Predicting the treatment response in patients with nasopharyngeal carcinoma (NPC) is challenging. This study evaluated the utility of diffusion-weighted imaging (DWI) in predicting the treatment response in patients with NPC. Methods We prospectively enrolled 33 patients with newly diagnosed NPC who underwent magnetic resonance imaging with the propeller DWI and apparent diffusion coefficient (ADC) map before and at 5 weeks after chemoradiation. The following ADC values of the primary tumor were calculated: pre-treatment ADC (pre-ADC), pre-treatment ADC ratio (pre-ADC ratio), ADC change (▵ADC), ADC change ratio (▵ADC ratio), and percentage of ADC change (▵%ADC). The correlations between these parameters and treatment outcomes were explored, and the patients were classified as good responders (complete response) and poor responders (stable disease, partial response, or progressive disease) based on the Response Evaluation Criteria in Solid Tumors, version 1.1. Results The ▵ADC, ▵ADC ratio, and ▵%ADC were significantly lower in the poor-responder group ( n = 12) than in the good-responder group ( n = 21; p = 0.001, p = 0.002, and p = 0.004, respectively). There was no significant difference between groups in the pre-ADC and pre-ADC ratios ( p = 0.602 and p = 0.685, respectively). The optimal ▵ADC, ▵ADC ratio, and ▵%ADC cutoff values for predicting poor response were >0.65 mm2/sec, 0.28, and 60%, respectively (sensitivity: 83.3%, 75%, and 83.3%; specificity: 71.4%, 85.7%, and 71.4%, respectively). Conclusion The ▵ADC, ▵ADC ratio, and ▵%ADC obtained during the pre-treatment and mid-treatment periods could be potential biomarkers for predicting treatment response in patients with NPC.

Diffusion-weighted imaging (DWI) is an MRI technique which provides functional information of tissue by detecting microscopic motion of water molecules. The change of apparent diffusion coefficient (ADC) derived from DWI was used as an imaging biomarker for treatment response prediction in cancers [1]. However, it was based on whole-tumor analysis which did not reflect heterogeneity within the tumor. To overcome this limitation, a new method called parametric response map (PRM) analysis was proposed to evaluate response by quantifying voxel-wise changes in ADC [2]. Here we investigated the use of PRM analysis on ADC from DWI as an imaging biomarker for treatment response prediction in nasopharyngeal cancer (NPC) patients. We collected thirteen patient datasets including ten complete response (CR) patients and three partial response (PR) patients at King Chulalongkorn Memorial Hospital where one patient dataset consisted of DWI and ADC data acquired before (i.e. pre-treatment) and at five weeks after (i.e. mid-treatment) initiation of chemoradiation therapy. For each dataset, we compared pre-treatment ADC image with co-registered mid-treatment ADC image, and calculated the percentage of voxels with increased ADC values with respect to total voxels within the tumor ROI, defined as PRM+. To validate the feasibility of the PRM biomarker, we computed the mean and standard deviation (SD) of percentage change in tumor volume (%AVol ) and in ADC (%AADC) and PRM+ across CR and PR patients, where tumor response was from 6-month follow-up data using RECIST1.1 guideline. The results showed that %AVol as well as %AADC between both groups was not significantly different. In contrast, PRM+ was significantly different between both groups (p < 0.05, 82.7±7.8% in CR vs 66.7±6.5% in PR). Our results implied that the proposed PRM+ biomarker could be a potential biomarker for early treatment response prediction in NPC patients.