Literature DB >> 30484085

Magnetic resonance perfusion and diffusion characteristics of granulomatous diseases mimic those of malignant lesions: six case reports.

Misa Sumi1, Yukinori Takagi1, Miho Sasaki1, Sato Eida1, Ikuo Katayama1, Yuka Hotokezaka1, Takashi Nakamura2.   

Abstract

The perfusion and diffusion properties of a tumor are important clues in evaluating its growth potential and predicting its histological type, such as benign or malignant. Tumor perfusion can be estimated by assessing time-dependent changes in the intratumoral levels of the contrast agent during dynamic contrast-enhanced magnetic resonance (MR) imaging, whereas tumor diffusion can be estimated by assessing intratumoral water diffusivity on diffusion-weighted MR imaging. Granulomatous diseases with different etiologies occur in various head and neck regions, including the mandible, maxillary sinus, salivary glands, and lymph nodes. However, the perfusion and diffusion properties of granulomatous diseases in the head and neck regions are not well documented. In this study, we assessed the time-signal intensity curves and apparent diffusion coefficients of six granulomatous diseases of various histological types that appeared in the soft tissues of the head and neck. Our data show that the perfusion and diffusion characteristics of granulomatous diseases mimic those of malignant diseases, highlighting the need for careful interpretation of MR perfusion and diffusion findings to distinguish between granulomatous diseases and cancers of the head and neck region. Clinicians should pay particular attention to blood examination and biopsy results when interpreting imaging findings.

Entities:  

Keywords:  Diffusion; Granulomatous disease; Head and neck; Magnetic resonance imaging; Perfusion

Mesh:

Substances:

Year:  2017        PMID: 30484085     DOI: 10.1007/s11282-017-0271-2

Source DB:  PubMed          Journal:  Oral Radiol        ISSN: 0911-6028            Impact factor:   1.852


  16 in total

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Authors:  O Kenechi Nwawka; Rohini Nadgir; Akifumi Fujita; Osamu Sakai
Journal:  Radiographics       Date:  2014 Sep-Oct       Impact factor: 5.333

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Authors:  Stefan H Oehlers; Mark R Cronan; Ninecia R Scott; Monica I Thomas; Kazuhide S Okuda; Eric M Walton; Rebecca W Beerman; Philip S Crosier; David M Tobin
Journal:  Nature       Date:  2014-11-24       Impact factor: 49.962

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