Literature DB >> 25258365

Diffusion-weighted imaging of the head and neck in healthy subjects: reproducibility of ADC values in different MRI systems and repeat sessions.

A S Kolff-Gart1, P J W Pouwels2, D P Noij1, R Ljumanovic1, V Vandecaveye3, F de Keyzer3, R de Bree4, P de Graaf1, D L Knol5, J A Castelijns6.   

Abstract

BACKGROUND AND
PURPOSE: DWI is typically performed with EPI sequences in single-center studies. The purpose of this study was to determine the reproducibility of ADC values in the head and neck region in healthy subjects. In addition, the reproducibility of ADC values in different tissues was assessed to identify the most suitable reference tissue.
MATERIALS AND METHODS: We prospectively studied 7 healthy subjects, with EPI and TSE sequences, on 5 MR imaging systems at 3 time points in 2 institutions. ADC maps of EPI (with 2 b-values and 6 b-values) and TSE sequences were compared. Mean ADC values for different tissues (submandibular gland, sternocleidomastoid muscle, spinal cord, subdigastric lymph node, and tonsil) were used to evaluate intra- and intersubject, intersystem, and intersequence variability by using a linear mixed model.
RESULTS: On 97% of images, a region of interest could be placed on the spinal cord, compared with 87% in the tonsil. ADC values derived from EPI-DWI with 2 b-values and calculated EPI-DWI with 2 b-values extracted from EPI-DWI with 6 b-values did not differ significantly. The standard error of ADC measurement was the smallest for the tonsil and spinal cord (standard error of measurement = 151.2 × 10(-6) mm/s(2) and 190.1 × 10(-6) mm/s(2), respectively). The intersystem difference for mean ADC values and the influence of the MR imaging system on ADC values among the subjects were statistically significant (P < .001). The mean difference among examinations was negligible (ie, <10 × 10(-6) mm/s(2)).
CONCLUSIONS: In this study, the spinal cord was the most appropriate reference tissue and EPI-DWI with 6 b-values was the most reproducible sequence. ADC values were more precise if subjects were measured on the same MR imaging system and with the same sequence. ADC values differed significantly between MR imaging systems and sequences.
© 2015 by American Journal of Neuroradiology.

Entities:  

Mesh:

Year:  2014        PMID: 25258365      PMCID: PMC7965670          DOI: 10.3174/ajnr.A4114

Source DB:  PubMed          Journal:  AJNR Am J Neuroradiol        ISSN: 0195-6108            Impact factor:   3.825


  20 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.  Statistical models for assessing agreement in method comparison studies with replicate measurements.

Authors:  Bendix Carstensen; Julie Simpson; Lyle C Gurrin
Journal:  Int J Biostat       Date:  2008       Impact factor: 0.968

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.  Diffusion-weighted MRI: a new functional clinical technique for tumour imaging.

Authors:  D-M Koh; A R Padhani
Journal:  Br J Radiol       Date:  2006-06-22       Impact factor: 3.039

5.  Detection of head and neck squamous cell carcinoma with diffusion weighted MRI after (chemo)radiotherapy: correlation between radiologic and histopathologic findings.

Authors:  Vincent Vandecaveye; Frederik De Keyzer; Sandra Nuyts; Karen Deraedt; Piet Dirix; Pascal Hamaekers; Vincent Vander Poorten; Pierre Delaere; Robert Hermans
Journal:  Int J Radiat Oncol Biol Phys       Date:  2006-12-04       Impact factor: 7.038

6.  Variability in absolute apparent diffusion coefficient values across different platforms may be substantial: a multivendor, multi-institutional comparison study.

Authors:  Makoto Sasaki; Kei Yamada; Yoshiyuki Watanabe; Mieko Matsui; Masahiro Ida; Shunrou Fujiwara; Eri Shibata
Journal:  Radiology       Date:  2008-11       Impact factor: 11.105

7.  Global cancer statistics.

Authors:  Ahmedin Jemal; Freddie Bray; Melissa M Center; Jacques Ferlay; Elizabeth Ward; David Forman
Journal:  CA Cancer J Clin       Date:  2011-02-04       Impact factor: 508.702

Review 8.  Apparent diffusion coefficient from magnetic resonance imaging as a biomarker in oncology drug development.

Authors:  Ralph Sinkus; Bernard E Van Beers; Valérie Vilgrain; Nandita DeSouza; John C Waterton
Journal:  Eur J Cancer       Date:  2012-01-05       Impact factor: 9.162

9.  Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations.

Authors:  Anwar R Padhani; Guoying Liu; Dow Mu Koh; Thomas L Chenevert; Harriet C Thoeny; Taro Takahara; Andrew Dzik-Jurasz; Brian D Ross; Marc Van Cauteren; David Collins; Dima A Hammoud; Gordon J S Rustin; Bachir Taouli; Peter L Choyke
Journal:  Neoplasia       Date:  2009-02       Impact factor: 5.715

10.  Diagnostic evaluation of squamous cell carcinoma metastatic to cervical lymph nodes from an unknown head and neck primary site.

Authors:  Marco Cianchetti; Anthony A Mancuso; Robert J Amdur; John W Werning; Jessica Kirwan; Christopher G Morris; William M Mendenhall
Journal:  Laryngoscope       Date:  2009-12       Impact factor: 3.325

View more
  17 in total

1.  Differentiation of lymphomatous, metastatic, and non-malignant lymphadenopathy in the neck with quantitative diffusion-weighted imaging: systematic review and meta-analysis.

Authors:  Seyedmehdi Payabvash; Alexandria Brackett; Reza Forghani; Ajay Malhotra
Journal:  Neuroradiology       Date:  2019-06-07       Impact factor: 2.804

2.  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

3.  Influence of blade width and magnetic field strength on the ADC on PROPELLER DWI in head and neck.

Authors:  Tetsuo Sumikawa; Hidetake Yabuuchi; Chiharu Sumikawa; Yoshiteru Nakashima; Gouji Miura
Journal:  Neuroradiol J       Date:  2019-08-13

4.  Combining standardized uptake value of FDG-PET and apparent diffusion coefficient of DW-MRI improves risk stratification in head and neck squamous cell carcinoma.

Authors:  Lorenzo Preda; Giorgio Conte; Luke Bonello; Caterina Giannitto; Laura L Travaini; Sara Raimondi; Paul E Summers; Ansarin Mohssen; Daniela Alterio; Maria Cossu Rocca; Chiara Grana; Francesca Ruju; Massimo Bellomi
Journal:  Eur Radiol       Date:  2016-03-10       Impact factor: 5.315

5.  Role of diffusion-weighted imaging for detecting bone marrow infiltration in skull in children with acute lymphoblastic leukemia.

Authors:  Weiguo Cao; Changhong Liang; Yungan Gen; Chen Wang; Cailei Zhao; Longwei Sun
Journal:  Diagn Interv Radiol       Date:  2016 Nov-Dec       Impact factor: 2.630

6.  Accuracy of turbo spin-echo diffusion-weighted imaging signal intensity measurements for the diagnosis of cholesteatoma.

Authors:  Burçe Özgen; Elif Bulut; Anıl Dolgun; Munir Demir Bajin; Levent Sennaroğlu
Journal:  Diagn Interv Radiol       Date:  2017 Jul-Aug       Impact factor: 2.630

7.  Diffusion-Weighted Imaging to Assess HPV-Positive versus HPV-Negative Oropharyngeal Squamous Cell Carcinoma: The Importance of b-Values.

Authors:  V Lenoir; B M A Delattre; Y M'RaD; C De Vito; T de Perrot; M Becker
Journal:  AJNR Am J Neuroradiol       Date:  2022-05-26       Impact factor: 4.966

Review 8.  Diffusion-weighted magnetic resonance imaging in cancer: Reported apparent diffusion coefficients, in-vitro and in-vivo reproducibility.

Authors:  Maysam M Jafar; Arman Parsai; Marc E Miquel
Journal:  World J Radiol       Date:  2016-01-28

9.  Apparent diffusion coefficient normalization of normal liver: Will it improve the reproducibility of diffusion-weighted imaging at different MR scanners as a new biomarker?

Authors:  Jie Zhu; Jie Zhang; Jia-Yin Gao; Jin-Ning Li; Da-Wei Yang; Min Chen; Cheng Zhou; Zheng-Han Yang
Journal:  Medicine (Baltimore)       Date:  2017-01       Impact factor: 1.889

Review 10.  Functional MRI for the prediction of treatment response in head and neck squamous cell carcinoma: potential and limitations.

Authors:  Ann D King; Harriet C Thoeny
Journal:  Cancer Imaging       Date:  2016-08-19       Impact factor: 3.909

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.