Literature DB >> 32706975

The application of a gamma distribution model to diffusion-weighted images of the orofacial region.

Toru Chikui1, Kenji Tokumori2, Wannakamon Panyarak3, Osamu Togao4, Yasuo Yamashita5, Shintaro Kawano6, Takeshi Kamitani4, Kazunori Yoshiura1.   

Abstract

OBJECTIVES: This study evaluated the correlation among the diffusion-derived parameters obtained by monoexponential (ME), intravoxel incoherent motion (IVIM) and γ distribution (GD) models and compared these parameters among representative orofacial tumours.
METHODS: Ninety-two patients who underwent 1.5 T MRI including diffusion-weighted imaging were included. The shape parameter (κ), scale parameter (θ), ratio of the intracellular diffusion (ƒ1), extracellular diffusion (ƒ2) and perfusion (ƒ3) were obtained by the GD model; the true diffusion coefficient (D) and perfusion fraction (f) were obtained by the IVIM model; and the apparent diffusion coefficient (ADC) was obtained by the ME model.
RESULTS: ƒ1 had a strongly negative correlation with the ADC (ρ = -0.993) and D (ρ = -0.926). A strong positive correlation between f and ƒ3 (ρ = 0.709) was found. Malignant lymphoma (ML) had the highest ƒ1, followed by squamous cell carcinoma (SCC), malignant salivary gland tumours, pleomorphic adenoma (Pleo) and angioma. Both the IVIM and GD models suggested the highest perfusion in angioma and the lowest perfusion in ML. The GD model demonstrated a high extracellular component in Pleo and revealed that the T4a+T4b SCC group had a lower ƒ2 than the T2+T3 SCC group, and poor to moderately differentiated SCC had a higher ƒ1 than highly differentiated SCC.
CONCLUSIONS: Given the correlation among the diffusion-derived parameters, the GD model might be a good alternative to the IVIM model. Furthermore, the GD model's parameters were useful for characterizing the pathological structure.

Entities:  

Keywords:  Diffusion Mri; Neoplasms; Statistical Model

Mesh:

Year:  2020        PMID: 32706975      PMCID: PMC7860948          DOI: 10.1259/dmfr.20200252

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


  29 in total

Review 1.  Diffusion-weighted MR imaging in the head and neck.

Authors:  Harriet C Thoeny; Frederik De Keyzer; Ann D King
Journal:  Radiology       Date:  2012-04       Impact factor: 11.105

2.  Pretreatment apparent diffusion coefficient of the primary lesion correlates with local failure in head-and-neck cancer treated with chemoradiotherapy or radiotherapy.

Authors:  Masamitsu Hatakenaka; Katsumasa Nakamura; Hidetake Yabuuchi; Yoshiyuki Shioyama; Yoshio Matsuo; Kayoko Ohnishi; Shunya Sunami; Takeshi Kamitani; Taro Setoguchi; Takashi Yoshiura; Torahiko Nakashima; Kei Nishikawa; Hiroshi Honda
Journal:  Int J Radiat Oncol Biol Phys       Date:  2010-09-09       Impact factor: 7.038

3.  Predictive value of diffusion-weighted magnetic resonance imaging during chemoradiotherapy for head and neck squamous cell carcinoma.

Authors:  Vincent Vandecaveye; Piet Dirix; Frederik De Keyzer; Katya Op de Beeck; Vincent Vander Poorten; I Roebben; Sandra Nuyts; Robert Hermans
Journal:  Eur Radiol       Date:  2010-02-24       Impact factor: 5.315

4.  Intravoxel incoherent motion diffusion-weighted imaging of resectable oesophageal squamous cell carcinoma: association with tumour stage.

Authors:  Yu-Cheng Huang; Tian-Wu Chen; Xiao-Ming Zhang; Nan-Lin Zeng; Rui Li; Yu-Lian Tang; Fan Chen; Yan-Li Chen
Journal:  Br J Radiol       Date:  2018-02-05       Impact factor: 3.039

5.  Quantitative non-Gaussian diffusion and intravoxel incoherent motion magnetic resonance imaging: differentiation of malignant and benign breast lesions.

Authors:  Mami Iima; Kojiro Yano; Masako Kataoka; Masaki Umehana; Katsutoshi Murata; Shotaro Kanao; Kaori Togashi; Denis Le Bihan
Journal:  Invest Radiol       Date:  2015-04       Impact factor: 6.016

6.  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

7.  Salivary gland tumors: use of intravoxel incoherent motion MR imaging for assessment of diffusion and perfusion for the differentiation of benign from malignant tumors.

Authors:  Misa Sumi; Marc Van Cauteren; Tadateru Sumi; Makoto Obara; Yoko Ichikawa; Takashi Nakamura
Journal:  Radiology       Date:  2012-03-23       Impact factor: 11.105

8.  Nasopharyngeal adenoid cystic carcinoma: magnetic resonance imaging features in ten cases.

Authors:  Xue-Wen Liu; Chuan-Miao Xie; Hui Li; Rong Zhang; Zhi-Jun Geng; Yun-Xian Mo; Jing Zhao; Mu-Yan Cai; Yan-Chun Lv; Pei-Hong Wu
Journal:  Chin J Cancer       Date:  2011-12-23

9.  Clinical efficacy of simplified intravoxel incoherent motion imaging using three b-values for differentiating high- and low-grade gliomas.

Authors:  Takuya Hino; Osamu Togao; Akio Hiwatashi; Koji Yamashita; Kazufumi Kikuchi; Daichi Momosaka; Hiroshi Honda
Journal:  PLoS One       Date:  2018-12-27       Impact factor: 3.240

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
  1 in total

1.  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.

Authors:  Wannakamon Panyarak; Toru Chikui; Kenji Tokumori; Yasuo Yamashita; Takeshi Kamitani; Osamu Togao; Shintaro Kawano; Kazunori Yoshiura
Journal:  Dentomaxillofac Radiol       Date:  2021-07-28       Impact factor: 2.419

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.