PURPOSE: 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. MATERIALS AND 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. CONCLUSION: The NG-IVIM model characterizes perfusion and restricted diffusion simultaneously in neck nodal metastases.
PURPOSE: 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. MATERIALS AND 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. CONCLUSION: The NG-IVIM model characterizes perfusion and restricted diffusion simultaneously in neck nodal metastases.
Authors: J Dudink; D J Larkman; O Kapellou; J P Boardman; J M Allsop; F M Cowan; J V Hajnal; A D Edwards; M A Rutherford; S J Counsell Journal: AJNR Am J Neuroradiol Date: 2008-08-07 Impact factor: 3.825
Authors: Vincent Lai; Victor Ho Fun Lee; Ka On Lam; Henry Chun Kin Sze; Queenie Chan; Pek Lan Khong Journal: Eur Radiol Date: 2014-12-23 Impact factor: 5.315
Authors: Gene Young Cho; Linda Moy; Sungheon G Kim; Steven H Baete; Melanie Moccaldi; James S Babb; Daniel K Sodickson; Eric E Sigmund Journal: Eur Radiol Date: 2015-11-28 Impact factor: 5.315
Authors: Louisa Bokacheva; Jennifer B Kaplan; Dilip D Giri; Sujata Patil; Merlin Gnanasigamani; C Gregory Nyman; Joseph O Deasy; Elizabeth A Morris; Sunitha B Thakur Journal: J Magn Reson Imaging Date: 2013-11-22 Impact factor: 4.813