Literature DB >> 34319774

A comparison among gamma distribution, intravoxel incoherent motion, and mono-exponential models with turbo spin-echo diffusion-weighted MR imaging in the differential diagnosis of orofacial lesions.

Wannakamon Panyarak1,2, Toru Chikui3, Kenji Tokumori4, Yasuo Yamashita5, Takeshi Kamitani6, Osamu Togao6, Shintaro Kawano7, Kazunori Yoshiura3.   

Abstract

OBJECTIVES: To compare the gamma distribution (GD), intravoxel incoherent motion (IVIM), and monoexponential (ME) models in terms of their goodness-of-fit, correlations among the parameters, and the effectiveness in the differential diagnosis of various orofacial lesions.
METHODS: A total of 85 patients underwent turbo spin-echo diffusion-weighted imaging with six b-values. The goodness-of-fit of three models was assessed using Akaike Information Criterion. We analysed the correlations and compared the effectiveness in the differential diagnosis among the parameters of GD model (κ, shape parameter; θ, scale parameter; fractions of diffusion: ƒ1, cellular component; ƒ2, extracellular diffusion; ƒ3, perfusion component), IVIM model (D, true diffusion coefficient; D*, pseudodiffusion coefficient; f, perfusion fraction), and ME model (apparent diffusion coefficient, ADC).
RESULTS: The GD and IVIM models showed a better goodness-of-fit than the ME model (p < 0.05). ƒ1 had strong negative correlations with D and ADC (ρ = -0.901 and -0.937, respectively), while ƒ3 had a moderate positive correlation with f (ρ = 0.661). Malignant entity presented significantly higher ƒ1 and lower D and ADC than benign entity (p < 0.0001). Malignant lymphoma had significantly higher ƒ1 in comparison to squamous cell carcinoma (p = 0.0007) and granulation (p = 0.0075). The trend in ƒ1 was opposite to the trend in D. Malignant lymphoma had significant lower ƒ3 than squamous cell carcinoma (p = 0.005) or granulation (p = 0.0075).
CONCLUSIONS: The strong correlations were found between the GD- and IVIM-derived parameters. Furthermore, the GD model's parameters were useful for characterising the pathological structure in orofacial lesions.

Entities:  

Keywords:  Differential diagnosis; Diffusion weighted imaging; Magnetic resonance imaging; Orofacial lesions; Statistical models

Mesh:

Year:  2021        PMID: 34319774      PMCID: PMC8693325          DOI: 10.1259/dmfr.20200609

Source DB:  PubMed          Journal:  Dentomaxillofac Radiol        ISSN: 0250-832X            Impact factor:   2.419


  30 in total

1.  Statistical model for diffusion attenuated MR signal.

Authors:  Dmitriy A Yablonskiy; G Larry Bretthorst; Joseph J H Ackerman
Journal:  Magn Reson Med       Date:  2003-10       Impact factor: 4.668

2.  Time-dependent diffusion MRI to distinguish malignant from benign head and neck tumors.

Authors:  Mami Iima; Akira Yamamoto; Masako Kataoka; Yosuke Yamada; Koichi Omori; Thorsten Feiweier; Kaori Togashi
Journal:  J Magn Reson Imaging       Date:  2018-12-21       Impact factor: 4.813

Review 3.  Imaging findings of head and neck inflammatory pseudotumor.

Authors:  Sung Bin Park; Jeong Hyun Lee; Young Cheol Weon
Journal:  AJR Am J Roentgenol       Date:  2009-10       Impact factor: 3.959

4.  Comparison of intravoxel incoherent motion diffusion-weighted imaging between turbo spin-echo and echo-planar imaging of the head and neck.

Authors:  Ryoji Mikayama; Hidetake Yabuuchi; Shinjiro Sonoda; Koji Kobayashi; Kazuya Nagatomo; Mitsuhiro Kimura; Satoshi Kawanami; Takeshi Kamitani; Seiji Kumazawa; Hiroshi Honda
Journal:  Eur Radiol       Date:  2017-08-04       Impact factor: 5.315

5.  MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders.

Authors:  D Le Bihan; E Breton; D Lallemand; P Grenier; E Cabanis; M Laval-Jeantet
Journal:  Radiology       Date:  1986-11       Impact factor: 11.105

6.  Advanced diffusion models in head and neck squamous cell carcinoma patients: Goodness of fit, relationships among diffusion parameters and comparison with dynamic contrast-enhanced perfusion.

Authors:  Noriyuki Fujima; Tomohiro Sakashita; Akihiro Homma; Yukie Shimizu; Atsushi Yoshida; Taisuke Harada; Khin Khin Tha; Kohsuke Kudo; Hiroki Shirato
Journal:  Magn Reson Imaging       Date:  2016-10-27       Impact factor: 2.546

Review 7.  Clinical Intravoxel Incoherent Motion and Diffusion MR Imaging: Past, Present, and Future.

Authors:  Mami Iima; Denis Le Bihan
Journal:  Radiology       Date:  2016-01       Impact factor: 11.105

Review 8.  State of the art MRI in head and neck cancer.

Authors:  Y L Dai; A D King
Journal:  Clin Radiol       Date:  2017-06-24       Impact factor: 2.350

9.  Measurement reproducibility of perfusion fraction and pseudodiffusion coefficient derived by intravoxel incoherent motion diffusion-weighted MR imaging in normal liver and metastases.

Authors:  A Andreou; D M Koh; D J Collins; M Blackledge; T Wallace; M O Leach; M R Orton
Journal:  Eur Radiol       Date:  2012-10-06       Impact factor: 5.315

10.  Non-Gaussian analysis of diffusion weighted imaging in head and neck at 3T: a pilot study in patients with nasopharyngeal carcinoma.

Authors:  Jing Yuan; David Ka Wai Yeung; Greta S P Mok; Kunwar S Bhatia; Yi-Xiang J Wang; Anil T Ahuja; Ann D King
Journal:  PLoS One       Date:  2014-01-23       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.