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Published on: December 15, 2014
Intravoxel water diffusion heterogeneity MR imaging of nasopharyngeal carcinoma using stretched exponential diffusion
Vincent Lai1, Victor Ho Fun Lee, Ka On Lam
1Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, Queen Mary Hospital, University of Hong Kong, Room 406, Block K, Pok Fu Lam, Hong Kong, vincentlai166@yahoo.com.hk.
Purpose:
To determine the utility of stretched exponential diffusion model in characterisation of the water diffusion heterogeneity in different tumour stages of nasopharyngeal carcinoma (NPC).
Materials And Methods:
Fifty patients with newly diagnosed NPC were prospectively recruited. Diffusion-weighted MR imaging was performed using five b values (0-2,500 s/mm(2)). Respective stretched exponential parameters (DDC, distributed diffusion coefficient; and alpha (α), water heterogeneity) were calculated. Patients were stratified into low and high tumour stage groups based on the American Joint Committee on Cancer (AJCC) staging for determination of the predictive powers of DDC and α using t test and ROC curve analyses.
Results:
The mean ± standard deviation values were DDC = 0.692 ± 0.199 (×10(-3) mm(2)/s) for low stage group vs 0.794 ± 0.253 (×10(-3) mm(2)/s) for high stage group; α = 0.792 ± 0.145 for low stage group vs 0.698 ± 0.155 for high stage group. α was significantly lower in the high stage group while DDC was negatively correlated. DDC and α were both reliable independent predictors (p < 0.001), with α being more powerful. Optimal cut-off values were (sensitivity, specificity, positive likelihood ratio, negative likelihood ratio) DDC = 0.692 × 10(-3) mm(2)/s (94.4 %, 64.3 %, 2.64, 0.09), α = 0.720 (72.2 %, 100 %, -, 0.28).
Conclusion:
The heterogeneity index α is robust and can potentially help in staging and grading prediction in NPC.
Key Points:
• Stretched exponential diffusion models can help in tissue characterisation in nasopharyngeal carcinoma • α and distributed diffusion coefficient (DDC) are negatively correlated • α is a robust heterogeneity index marker • α can potentially help in staging and grading prediction.
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