title: Texture-based and diffusion-weighted discrimination of parotid gland lesions on MR images at 3.0 Tesla.
abstract: The purpose of this study was to evaluate whether texture-based analysis of standard MRI sequences and diffusion-weighted imaging can help in the discrimination of parotid gland masses. The MR images of 38 patients with a biopsy- or surgery-proven 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-based analysis was performed with the texture analysis software MaZda (version 4.7), with ROI measurements covering the entire tumor in three slices. COC (co-occurrence matrix), RUN (run-length matrix), GRA (gradient), ARM (auto-regressive 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 k nearest neighbor classification (k-NN). Using histology as a standard of reference, benign tumors, including subtypes, and malignant tumors were compared with regard to ADC and texture-based values, with a one-way analysis of variance with post-hoc t-tests. 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-enhanced T1-weighted 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. Texture analysis proved to differentiate benign from malignant lesions, as well as pleomorphic adenomas from Warthin tumors, based on standard T(1w) sequences (without and with contrast). Of all benign parotid masses, Warthin tumors had significantly lower ADC values than the other entities.
authors.affiliation: Medical University of Vienna, Department of Radiology, Subdivision of Neuroradiology and Musculoskeletal Radiology, Vienna, Austria.
authors.forename: Julia
authors.initials: J
authors.lastname: Fruehwald-Pallamar
authors.forename: Christian
authors.initials: C
authors.lastname: Czerny
authors.forename: Laura
authors.initials: L
authors.lastname: Holzer-Fruehwald
authors.forename: Stefan F
authors.initials: SF
authors.lastname: Nemec
authors.forename: Christina
authors.initials: C
authors.lastname: Mueller-Mang
authors.forename: Michael
authors.initials: M
authors.lastname: Weber
authors.forename: Marius E
authors.initials: ME
authors.lastname: Mayerhoefer
mesh_terms: D000235:Adenolymphoma / Q000175:diagnosis / Q000473:pathology; D008949:Adenoma, Pleomorphic / Q000175:diagnosis / Q000473:pathology; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D004058:Diffusion; D038524:Diffusion Magnetic Resonance Imaging; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008297:Male; D008875:Middle Aged; D010306:Parotid Gland / Q000473:pathology*; D055815:Young Adult
keywords: 3T MRI; diffusion-weighted MRI; parotid gland tumors; parotid tumor; texture-based analysis