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European Radiology

, Volume 25, Issue 6, pp 1708–1713 | Cite as

Intravoxel water diffusion heterogeneity MR imaging of nasopharyngeal carcinoma using stretched exponential diffusion model

  • Vincent LaiEmail author
  • Victor Ho Fun Lee
  • Ka On Lam
  • Henry Chun Kin Sze
  • Queenie Chan
  • Pek Lan Khong
Head and Neck

Abstract

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/mm2). 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 mm2/s) for low stage group vs 0.794 ± 0.253 (×10−3 mm2/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 mm2/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

Keywords

Nasopharyngeal carcinoma Diffusion weighted imaging Magnetic resonance imaging Stretched exponential Staging 

Abbreviations

α

Alpha (intravoxel water diffusion heterogeneity)

AJCC

American Joint Committee on Cancer

AUC

Area under curve

DDC

Distributed diffusion coefficient

DW

Diffusion-weighted

F-FDG

18-fluoro-2-deoxyglucose

IVIM

Intravoxel incoherent motion

MR

Magnetic resonance

NPC

Nasopharyngeal carcinoma

PET/CT

Positron emission tomography with computed tomography

ROC

Receiver operating characteristic

ROI

Region-of-interest

SD

Standard deviation

SNR

Signal-to-noise ratio

SPIR

Spectral presaturation inversion recovery

STIR

Short TI inversion recovery

TFE

Turbo-field-echo

TR/TE

Repetition time/echo time

TSE

Turbo spin echo

Notes

Acknowledgments

The scientific guarantor of this publication is Prof. Khong Pek Lan. The authors of this manuscript declare relationships with the following companies: Dr. Q Chan is currently employed by Philips Medial Systems. This study has received funding by University Grants Council (UGC) seed funding from The University of Hong Kong, project no. 201112159010.

No complex statistical methods were necessary for this paper. Institutional review board approval was obtained. Written informed consent was obtained from all subjects (patients) in this study. Approval from the institutional animal care committee was not required because this study did not involve animals. Study subjects or cohorts have not been previously reported.

Methodology: prospective, diagnostic or prognostic study, performed at one institution.

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Copyright information

© European Society of Radiology 2014

Authors and Affiliations

  • Vincent Lai
    • 1
    Email author
  • Victor Ho Fun Lee
    • 2
  • Ka On Lam
    • 2
  • Henry Chun Kin Sze
    • 2
  • Queenie Chan
    • 3
  • Pek Lan Khong
    • 1
  1. 1.Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, Queen Mary HospitalUniversity of Hong KongPok Fu LamHong Kong
  2. 2.Department of Clinical Oncology, Li Ka Shing Faculty of Medicine, Queen Mary HospitalUniversity of Hong KongPok Fu LamHong Kong
  3. 3.Philips Healthcare, Hong KongShatinHong Kong

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