@article{RN181,
   author = {Jansen, J. F. and Lu, Y. and Gupta, G. and Lee, N. Y. and Stambuk, H. E. and Mazaheri, Y. and Deasy, J. O. and Shukla-Dave, A.},
   title = {Texture analysis on parametric maps derived from dynamic contrast-enhanced magnetic resonance imaging in head and neck cancer},
   journal = {World J Radiol},
   volume = {8},
   number = {1},
   pages = {90-7},
   note = {Jansen, Jacobus Fa
Lu, Yonggang
Gupta, Gaorav
Lee, Nancy Y
Stambuk, Hilda E
Mazaheri, Yousef
Deasy, Joseph O
Shukla-Dave, Amita
eng
R01 CA115895/CA/NCI NIH HHS/
2016/02/03 06:00
World J Radiol. 2016 Jan 28;8(1):90-7. doi: 10.4329/wjr.v8.i1.90.},
   abstract = {AIM: To investigate the merits of texture analysis on parametric maps derived from pharmacokinetic modeling with dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) as imaging biomarkers for the prediction of treatment response in patients with head and neck squamous cell carcinoma (HNSCC). METHODS: In this retrospective study, 19 HNSCC patients underwent pre- and intra-treatment DCE-MRI scans at a 1.5T MRI scanner. All patients had chemo-radiation treatment. Pharmacokinetic modeling was performed on the acquired DCE-MRI images, generating maps of volume transfer rate (K(trans)) and volume fraction of the extravascular extracellular space (ve). Image texture analysis was then employed on maps of K(trans) and ve, generating two texture measures: Energy (E) and homogeneity. RESULTS: No significant changes were found for the mean and standard deviation for K(trans) and ve between pre- and intra-treatment (P > 0.09). Texture analysis revealed that the imaging biomarker E of ve was significantly higher in intra-treatment scans, relative to pretreatment scans (P < 0.04). CONCLUSION: Chemo-radiation treatment in HNSCC significantly reduces the heterogeneity of tumors.},
   keywords = {Dynamic contrast-enhanced magnetic resonance imaging
Head and neck squamous cell carcinomas
Image texture analysis
Tumor heterogeneity},
   ISSN = {1949-8470 (Print)
1949-8470 (Linking)},
   DOI = {10.4329/wjr.v8.i1.90},
   url = {http://www.ncbi.nlm.nih.gov/pubmed/26834947
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4731352/pdf/WJR-8-90.pdf},
   year = {2016},
   type = {Journal Article}
}

{"_id":"BJCj4h6BuTGKqzFhe","bibbaseid":"jansen-lu-gupta-lee-stambuk-mazaheri-deasy-shukladave-textureanalysisonparametricmapsderivedfromdynamiccontrastenhancedmagneticresonanceimaginginheadandneckcancer-2016","downloads":0,"creationDate":"2017-09-02T16:45:18.614Z","title":"Texture analysis on parametric maps derived from dynamic contrast-enhanced magnetic resonance imaging in head and neck cancer","author_short":["Jansen, J. F.","Lu, Y.","Gupta, G.","Lee, N. Y.","Stambuk, H. E.","Mazaheri, Y.","Deasy, J. O.","Shukla-Dave, A."],"year":2016,"bibtype":"article","biburl":"https://raw.githubusercontent.com/jansenjfa1/bibbase.github.io/master/jansenjfa.bib","bibdata":{"bibtype":"article","type":"Journal Article","author":[{"propositions":[],"lastnames":["Jansen"],"firstnames":["J.","F."],"suffixes":[]},{"propositions":[],"lastnames":["Lu"],"firstnames":["Y."],"suffixes":[]},{"propositions":[],"lastnames":["Gupta"],"firstnames":["G."],"suffixes":[]},{"propositions":[],"lastnames":["Lee"],"firstnames":["N.","Y."],"suffixes":[]},{"propositions":[],"lastnames":["Stambuk"],"firstnames":["H.","E."],"suffixes":[]},{"propositions":[],"lastnames":["Mazaheri"],"firstnames":["Y."],"suffixes":[]},{"propositions":[],"lastnames":["Deasy"],"firstnames":["J.","O."],"suffixes":[]},{"propositions":[],"lastnames":["Shukla-Dave"],"firstnames":["A."],"suffixes":[]}],"title":"Texture analysis on parametric maps derived from dynamic contrast-enhanced magnetic resonance imaging in head and neck cancer","journal":"World J Radiol","volume":"8","number":"1","pages":"90-7","note":"Jansen, Jacobus Fa Lu, Yonggang Gupta, Gaorav Lee, Nancy Y Stambuk, Hilda E Mazaheri, Yousef Deasy, Joseph O Shukla-Dave, Amita eng R01 CA115895/CA/NCI NIH HHS/ 2016/02/03 06:00 World J Radiol. 2016 Jan 28;8(1):90-7. doi: 10.4329/wjr.v8.i1.90.","abstract":"AIM: To investigate the merits of texture analysis on parametric maps derived from pharmacokinetic modeling with dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) as imaging biomarkers for the prediction of treatment response in patients with head and neck squamous cell carcinoma (HNSCC). METHODS: In this retrospective study, 19 HNSCC patients underwent pre- and intra-treatment DCE-MRI scans at a 1.5T MRI scanner. All patients had chemo-radiation treatment. Pharmacokinetic modeling was performed on the acquired DCE-MRI images, generating maps of volume transfer rate (K(trans)) and volume fraction of the extravascular extracellular space (ve). Image texture analysis was then employed on maps of K(trans) and ve, generating two texture measures: Energy (E) and homogeneity. RESULTS: No significant changes were found for the mean and standard deviation for K(trans) and ve between pre- and intra-treatment (P > 0.09). Texture analysis revealed that the imaging biomarker E of ve was significantly higher in intra-treatment scans, relative to pretreatment scans (P < 0.04). CONCLUSION: Chemo-radiation treatment in HNSCC significantly reduces the heterogeneity of tumors.","keywords":"Dynamic contrast-enhanced magnetic resonance imaging Head and neck squamous cell carcinomas Image texture analysis Tumor heterogeneity","issn":"1949-8470 (Print) 1949-8470 (Linking)","doi":"10.4329/wjr.v8.i1.90","url":"http://www.ncbi.nlm.nih.gov/pubmed/26834947 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4731352/pdf/WJR-8-90.pdf","year":"2016","bibtex":"@article{RN181,\n author = {Jansen, J. F. and Lu, Y. and Gupta, G. and Lee, N. Y. and Stambuk, H. E. and Mazaheri, Y. and Deasy, J. O. and Shukla-Dave, A.},\n title = {Texture analysis on parametric maps derived from dynamic contrast-enhanced magnetic resonance imaging in head and neck cancer},\n journal = {World J Radiol},\n volume = {8},\n number = {1},\n pages = {90-7},\n note = {Jansen, Jacobus Fa\nLu, Yonggang\nGupta, Gaorav\nLee, Nancy Y\nStambuk, Hilda E\nMazaheri, Yousef\nDeasy, Joseph O\nShukla-Dave, Amita\neng\nR01 CA115895/CA/NCI NIH HHS/\n2016/02/03 06:00\nWorld J Radiol. 2016 Jan 28;8(1):90-7. doi: 10.4329/wjr.v8.i1.90.},\n abstract = {AIM: To investigate the merits of texture analysis on parametric maps derived from pharmacokinetic modeling with dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) as imaging biomarkers for the prediction of treatment response in patients with head and neck squamous cell carcinoma (HNSCC). METHODS: In this retrospective study, 19 HNSCC patients underwent pre- and intra-treatment DCE-MRI scans at a 1.5T MRI scanner. All patients had chemo-radiation treatment. Pharmacokinetic modeling was performed on the acquired DCE-MRI images, generating maps of volume transfer rate (K(trans)) and volume fraction of the extravascular extracellular space (ve). Image texture analysis was then employed on maps of K(trans) and ve, generating two texture measures: Energy (E) and homogeneity. RESULTS: No significant changes were found for the mean and standard deviation for K(trans) and ve between pre- and intra-treatment (P > 0.09). Texture analysis revealed that the imaging biomarker E of ve was significantly higher in intra-treatment scans, relative to pretreatment scans (P < 0.04). CONCLUSION: Chemo-radiation treatment in HNSCC significantly reduces the heterogeneity of tumors.},\n keywords = {Dynamic contrast-enhanced magnetic resonance imaging\nHead and neck squamous cell carcinomas\nImage texture analysis\nTumor heterogeneity},\n ISSN = {1949-8470 (Print)\n1949-8470 (Linking)},\n DOI = {10.4329/wjr.v8.i1.90},\n url = {http://www.ncbi.nlm.nih.gov/pubmed/26834947\nhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4731352/pdf/WJR-8-90.pdf},\n year = {2016},\n type = {Journal Article}\n}\n\n","author_short":["Jansen, J. F.","Lu, Y.","Gupta, G.","Lee, N. Y.","Stambuk, H. E.","Mazaheri, Y.","Deasy, J. 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