{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T01:52:10Z","timestamp":1782957130393,"version":"3.54.5"},"reference-count":33,"publisher":"Wiley","issue":"11","license":[{"start":{"date-parts":[[2013,5,23]],"date-time":"2013-05-23T00:00:00Z","timestamp":1369267200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["NMR in Biomedicine"],"published-print":{"date-parts":[[2013,11]]},"abstract":"<jats:p>The purpose of this study was to evaluate whether texture\u2010based analysis of standard MRI sequences and diffusion\u2010weighted imaging can help in the discrimination of parotid gland masses.<\/jats:p><jats:p>The MR images of 38 patients with a biopsy\u2010 or surgery\u2010proven parotid gland mass were retrospectively analyzed. All patients were examined on the same 3.0 Tesla MR unit, with one standard protocol. The ADC (apparent diffusion coefficient) values of the tumors were measured with three regions of interest (ROIs) covering the entire tumor. Texture\u2010based analysis was performed with the texture analysis software MaZda (version 4.7), with ROI measurements covering the entire tumor in three slices. COC (co\u2010occurrence matrix), RUN (run\u2010length matrix), GRA (gradient), ARM (auto\u2010regressive model), and WAV (wavelet transform) features were calculated for all ROIs. Three subsets of 10 texture features each were used for a linear discriminant analysis (LDA) in combination with <jats:italic>k<\/jats:italic> nearest neighbor classification (k\u2010NN).<\/jats:p><jats:p>Using histology as a standard of reference, benign tumors, including subtypes, and malignant tumors were compared with regard to ADC and texture\u2010based values, with a one\u2010way analysis of variance with post\u2010hoc <jats:italic>t<\/jats:italic>\u2010tests.<\/jats:p><jats:p>Significant differences were found in the mean ADC values between Warthin tumors and pleomorphic adenomas, as well as between Warthin tumors and benign lesions. Contrast\u2010enhanced T1\u2010weighted images contained the most relevant textural information for the discrimination between benign and malignant parotid masses, and also for the discrimination between pleomorphic adenomas and Warthin tumors. STIR images contained the least relevant texture features, particularly for the discrimination between pleomorphic adenomas and Warthin tumors.<\/jats:p><jats:p>Texture analysis proved to differentiate benign from malignant lesions, as well as pleomorphic adenomas from Warthin tumors, based on standard <jats:italic>T<\/jats:italic><jats:sub>1w<\/jats:sub> sequences (without and with contrast). Of all benign parotid masses, Warthin tumors had significantly lower ADC values than the other entities. Copyright \u00a9 2013 John Wiley &amp; Sons, Ltd.<\/jats:p>","DOI":"10.1002\/nbm.2962","type":"journal-article","created":{"date-parts":[[2013,5,23]],"date-time":"2013-05-23T09:35:44Z","timestamp":1369301744000},"page":"1372-1379","source":"Crossref","is-referenced-by-count":92,"title":["Texture\u2010based and diffusion\u2010weighted discrimination of parotid gland lesions on MR images at 3.0 Tesla"],"prefix":"10.1002","volume":"26","author":[{"given":"Julia","family":"Fruehwald\u2010Pallamar","sequence":"first","affiliation":[{"name":"Medical University of Vienna Department of Radiology, Subdivision of Neuroradiology and Musculoskeletal Radiology  Vienna Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christian","family":"Czerny","sequence":"additional","affiliation":[{"name":"Medical University of Vienna Department of Radiology, Subdivision of Neuroradiology and Musculoskeletal Radiology  Vienna Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Laura","family":"Holzer\u2010Fruehwald","sequence":"additional","affiliation":[{"name":"Medical University of Vienna Department of Radiology  Vienna Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefan F.","family":"Nemec","sequence":"additional","affiliation":[{"name":"Medical University of Vienna Department of Radiology, Subdivision of Neuroradiology and Musculoskeletal Radiology  Vienna Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christina","family":"Mueller\u2010Mang","sequence":"additional","affiliation":[{"name":"Medical University of Vienna Department of Radiology  Vienna Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"Weber","sequence":"additional","affiliation":[{"name":"Medical University of Vienna Department of Radiology  Vienna Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marius E.","family":"Mayerhoefer","sequence":"additional","affiliation":[{"name":"Medical University of Vienna Department of Radiology  Vienna Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2013,5,23]]},"reference":[{"key":"e_1_2_7_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12105-011-0281-z"},{"key":"e_1_2_7_3_1","doi-asserted-by":"publisher","DOI":"10.3174\/ajnr.A2520"},{"key":"e_1_2_7_4_1","first-page":"2005","volume-title":"Head and Neck Imaging","author":"Som P","year":"2003"},{"key":"e_1_2_7_5_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiology.173.3.2813793"},{"key":"e_1_2_7_6_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiology.185.3.1438746"},{"key":"e_1_2_7_7_1","unstructured":"HajekM DezortovaM MaterkaA.R L. 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