title: Extension of the intravoxel incoherent motion model to non-gaussian diffusion in head and neck cancer.
abstract: OBJECTIVE
  To extend the intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) model to restricted diffusion and to simultaneously quantify the perfusion and restricted diffusion parameters in neck nodal metastases.
  
  
  METHODS
  The non-gaussian (NG)-IVIM model was developed and tested on diffusion-weighted MRI data collected on a 1.5-Tesla MRI scanner from eight patients with head and neck cancer. Voxel-wise parameter quantification was performed by using a noise-rectified least-square fitting method. The NG-IVIM, IVIM, Kurtosis, and ADC (apparent diffusion coefficient) models were used for comparison. For each voxel, within the metastatic node, the optimal model was determined using the Bayesian Information Criterion. The voxel percentage preferred by each model was calculated and the optimal model map was generated. Monte Carlo simulations were performed to evaluate the accuracy and precision dependency of the new model.
  
  
  RESULTS
  For the eight neck nodes, the range of voxel percentage preferred by the NG-IVIM model was 2.3-79.3%. The optimal modal maps showed heterogeneities within the tumors. The Monte Carlo simulations demonstrated that the accuracy and precision of the NG-IVIM model improved by increasing signal-to-noise ratio and b value.
  
  
  CONCLUSIONS
  The NG-IVIM model characterizes perfusion and restricted diffusion simultaneously in neck nodal metastases.
authors: Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York 10065, USA.
authors: Yonggang
authors: Y
authors: Lu
authors: Jacobus F A
authors: JF
authors: Jansen
authors: Yousef
authors: Y
authors: Mazaheri
authors: Hilda E
authors: HE
authors: Stambuk
authors: Jason A
authors: JA
authors: Koutcher
authors: Amita
authors: A
authors: Shukla-Dave
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D005260:Female; D006258:Head and Neck Neoplasms / Q000473:pathology* / Q000556:secondary*; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016018:Least-Squares Analysis; D008198:Lymph Nodes / Q000473:pathology*; D008207:Lymphatic Metastasis; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D015233:Models, Statistical; D009038:Motion; D016011:Normal Distribution; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity