{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T13:57:15Z","timestamp":1781013435300,"version":"3.54.1"},"reference-count":20,"publisher":"Georg Thieme Verlag KG","issue":"03","license":[{"start":{"date-parts":[[2024,12,17]],"date-time":"2024-12-17T00:00:00Z","timestamp":1734393600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Indian J Radiol Imaging"],"published-print":{"date-parts":[[2025,7]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>\n               Background\u2003Preoperative magnetic resonance imaging (MRI) has an important role in the management and prognostication of parotid gland tumors. We aim to evaluate the role of multiparametric MRI in differentiating the major subgroup of parotid tumors.<\/jats:p><jats:p>\n               Materials and Methods\u2003Multiparametric MRI: T1-weighted imaging (T1WI), T2WI, diffusion-weighted imaging (DWI), pseudo-continuous arterial spin labeling (ASL) and dynamic contrast-enhanced (DCE) imaging were acquired in all patients. Apparent diffusion coefficient (ADC) values and tumor blood flow (TBF) were calculated from DWI and ASL, respectively. Ktrans, Kep, Ve, initial area under the gadolinium enhancement concentration curve (IAUGC), maximum slope, and contrast enhancement ratio (CER) were calculated from DCE-MRI perfusion. The above parameters were compared between three major subgroups of parotid gland tumors, such as non-Warthin benign tumors (NWBT), Warthin's tumors (WT), and malignant parotid tumors (MT).<\/jats:p><jats:p>\n               Results\u2003The mean ADC of MT (n\u2009=\u200913), WT (n\u2009=\u20095), and NWBT (n\u2009=\u200929) was 1.03\u2009\u00d7\u200910\u22123 mm2\/s, 0.97\u2009\u00d7\u200910\u22123 mm2\/s, and 1.89\u2009\u00d7\u200910\u22123 mm2\/s, respectively. The mean TBF (in mL\/100\u2009g\/min) was the highest MT (70.33), followed by WT (62.04) and NWBT (21.99). A cutoff of 40.51\u2009mL\/100\u2009g\/min showed a sensitivity of 96.6% and specificity of 77.8% for predicting NWBT. In DCE-MRI, 96.6% of the NWBT showed a type A time\u2013signal intensity curve. Although the majority of MT and WT had type C and B curves, respectively, there was overlapping. Among the quantitative DCE parameters, Ktrans and Kep were highly sensitive for differentiating NWBT, WT, and MT. Ktrans, Kep, IAUGC, and MS were maximum in WT, followed by MT and NWBT. Kep and Ktrans both had an accuracy of 84.7% for predicting pleomorphic adenoma.<\/jats:p><jats:p>\n               Conclusion\u2003Multiparametric MRI is useful for differentiating NWBT, WT, and MT. DCE-MRI helps in differentiating benign from malignant tumors. DWI and ASL are useful in differentiating NWBT from parotid malignancy.<\/jats:p>","DOI":"10.1055\/s-0044-1800861","type":"journal-article","created":{"date-parts":[[2024,12,18]],"date-time":"2024-12-18T00:22:16Z","timestamp":1734481336000},"page":"402-410","source":"Crossref","is-referenced-by-count":3,"title":["Multiparametric MRI in Diagnosis of Parotid Gland Tumor: An Observational Study in 3-T MRI"],"prefix":"10.1055","volume":"35","author":[{"given":"Sreecharan","family":"V.R","sequence":"additional","affiliation":[{"name":"Department of Radiodiagnosis, All India Institute of Medical Sciences, Bhubaneswar, Odisha, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Suprava","family":"Naik","sequence":"additional","affiliation":[{"name":"Department of Radiodiagnosis, All India Institute of Medical Sciences, Bhubaneswar, Odisha, 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