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Published on: December 15, 2014
Utility of diffusion-weighted magnetic resonance imaging in predicting the treatment response of nasopharyngeal
Thidaporn Tangyoosuk1, Chawalit Lertbutsayanukul2, Nutchawan Jittapiromsak1
1Department of Radiology, Faculty of Medicine, Division of Diagnostic Radiology, 26683Chulalongkorn University, King Chulalongkorn Memorial Hospital, Bangkok, Thailand.
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.
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