@article{RN152,
   author = {Lu, Y. and Jansen, J. F. and Mazaheri, Y. and Stambuk, H. E. and Koutcher, J. A. and Shukla-Dave, A.},
   title = {Extension of the intravoxel incoherent motion model to non-gaussian diffusion in head and neck cancer},
   journal = {J Magn Reson Imaging},
   volume = {36},
   number = {5},
   pages = {1088-96},
   note = {Lu, Yonggang
Jansen, Jacobus F A
Mazaheri, Yousef
Stambuk, Hilda E
Koutcher, Jason A
Shukla-Dave, Amita
eng
R01 CA115895/CA/NCI NIH HHS/
1 R01 CA115895/CA/NCI NIH HHS/
Research Support, N.I.H., Extramural
2012/07/25 06:00
J Magn Reson Imaging. 2012 Nov;36(5):1088-96. doi: 10.1002/jmri.23770. Epub 2012 Jul 23.},
   abstract = {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.},
   keywords = {*Algorithms
Computer Simulation
Data Interpretation, Statistical
Female
Head and Neck Neoplasms/*pathology/*secondary
Humans
Imaging, Three-Dimensional/*methods
Least-Squares Analysis
Lymph Nodes/*pathology
Lymphatic Metastasis
Male
Middle Aged
*Models, Biological
Models, Statistical
Motion
Normal Distribution
Pattern Recognition, Automated/*methods
Reproducibility of Results
Sensitivity and Specificity},
   ISSN = {1522-2586 (Electronic)
1053-1807 (Linking)},
   DOI = {10.1002/jmri.23770},
   url = {http://www.ncbi.nlm.nih.gov/pubmed/22826198
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3482143/pdf/nihms-391133.pdf},
   year = {2012},
   type = {Journal Article}
}

{"_id":"tGLaCztJYPvShKWDN","bibbaseid":"lu-jansen-mazaheri-stambuk-koutcher-shukladave-extensionoftheintravoxelincoherentmotionmodeltonongaussiandiffusioninheadandneckcancer-2012","downloads":0,"creationDate":"2017-09-02T18:10:13.529Z","title":"Extension of the intravoxel incoherent motion model to non-gaussian diffusion in head and neck cancer","author_short":["Lu, Y.","Jansen, J. F.","Mazaheri, Y.","Stambuk, H. E.","Koutcher, J. A.","Shukla-Dave, A."],"year":2012,"bibtype":"article","biburl":"https://raw.githubusercontent.com/jansenjfa1/bibbase.github.io/master/jansenjfa.bib","bibdata":{"bibtype":"article","type":"Journal Article","author":[{"propositions":[],"lastnames":["Lu"],"firstnames":["Y."],"suffixes":[]},{"propositions":[],"lastnames":["Jansen"],"firstnames":["J.","F."],"suffixes":[]},{"propositions":[],"lastnames":["Mazaheri"],"firstnames":["Y."],"suffixes":[]},{"propositions":[],"lastnames":["Stambuk"],"firstnames":["H.","E."],"suffixes":[]},{"propositions":[],"lastnames":["Koutcher"],"firstnames":["J.","A."],"suffixes":[]},{"propositions":[],"lastnames":["Shukla-Dave"],"firstnames":["A."],"suffixes":[]}],"title":"Extension of the intravoxel incoherent motion model to non-gaussian diffusion in head and neck cancer","journal":"J Magn Reson Imaging","volume":"36","number":"5","pages":"1088-96","note":"Lu, Yonggang Jansen, Jacobus F A Mazaheri, Yousef Stambuk, Hilda E Koutcher, Jason A Shukla-Dave, Amita eng R01 CA115895/CA/NCI NIH HHS/ 1 R01 CA115895/CA/NCI NIH HHS/ Research Support, N.I.H., Extramural 2012/07/25 06:00 J Magn Reson Imaging. 2012 Nov;36(5):1088-96. doi: 10.1002/jmri.23770. Epub 2012 Jul 23.","abstract":"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.","keywords":"*Algorithms Computer Simulation Data Interpretation, Statistical Female Head and Neck Neoplasms/*pathology/*secondary Humans Imaging, Three-Dimensional/*methods Least-Squares Analysis Lymph Nodes/*pathology Lymphatic Metastasis Male Middle Aged *Models, Biological Models, Statistical Motion Normal Distribution Pattern Recognition, Automated/*methods Reproducibility of Results Sensitivity and Specificity","issn":"1522-2586 (Electronic) 1053-1807 (Linking)","doi":"10.1002/jmri.23770","url":"http://www.ncbi.nlm.nih.gov/pubmed/22826198 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3482143/pdf/nihms-391133.pdf","year":"2012","bibtex":"@article{RN152,\n author = {Lu, Y. and Jansen, J. F. and Mazaheri, Y. and Stambuk, H. E. and Koutcher, J. A. and Shukla-Dave, A.},\n title = {Extension of the intravoxel incoherent motion model to non-gaussian diffusion in head and neck cancer},\n journal = {J Magn Reson Imaging},\n volume = {36},\n number = {5},\n pages = {1088-96},\n note = {Lu, Yonggang\nJansen, Jacobus F A\nMazaheri, Yousef\nStambuk, Hilda E\nKoutcher, Jason A\nShukla-Dave, Amita\neng\nR01 CA115895/CA/NCI NIH HHS/\n1 R01 CA115895/CA/NCI NIH HHS/\nResearch Support, N.I.H., Extramural\n2012/07/25 06:00\nJ Magn Reson Imaging. 2012 Nov;36(5):1088-96. doi: 10.1002/jmri.23770. Epub 2012 Jul 23.},\n abstract = {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.},\n keywords = {*Algorithms\nComputer Simulation\nData Interpretation, Statistical\nFemale\nHead and Neck Neoplasms/*pathology/*secondary\nHumans\nImaging, Three-Dimensional/*methods\nLeast-Squares Analysis\nLymph Nodes/*pathology\nLymphatic Metastasis\nMale\nMiddle Aged\n*Models, Biological\nModels, Statistical\nMotion\nNormal Distribution\nPattern Recognition, Automated/*methods\nReproducibility of Results\nSensitivity and Specificity},\n ISSN = {1522-2586 (Electronic)\n1053-1807 (Linking)},\n DOI = {10.1002/jmri.23770},\n url = {http://www.ncbi.nlm.nih.gov/pubmed/22826198\nhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3482143/pdf/nihms-391133.pdf},\n year = {2012},\n type = {Journal Article}\n}\n\n","author_short":["Lu, Y.","Jansen, J. F.","Mazaheri, Y.","Stambuk, H. E.","Koutcher, J. 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