Literature DB >> 25584712

Gastric Carcinoma: Ex Vivo MR Imaging at 7.0 T-Correlation with Histopathologic Findings.

Ichiro Yamada1, Naoyuki Miyasaka, Keigo Hikishima, Keiji Kato, Kazuyuki Kojima, Tatsuyuki Kawano, Eisaku Ito, Daisuke Kobayashi, Yoshinobu Eishi, Hideyuki Okano.   

Abstract

PURPOSE: To determine the imaging detail and diagnostic information that can be obtained at 7.0-T magnetic resonance (MR) imaging with a voxel volume of 9.5-14.0 nL as a means of evaluating the depth of mural invasion by gastric carcinomas ex vivo.
MATERIALS AND METHODS: This study was approved by the institutional review board, and written informed consent was obtained from each patient. Twenty gastric specimens containing 20 carcinomas were studied with a 7.0-T MR imaging system equipped with a four-channel surface coil. MR images were obtained with a 50-60 × 25-30 mm field of view, a 512 × 256 matrix, and a 1.0-mm section thickness, resulting in a voxel volume of 0.0095-0.0140 mm(3) (9.5-14.0 nL). The signal intensity of the gastric wall layers, tumor tissue, and fibrosis was described as low, intermediate, or high by comparing it with the signal intensity of the muscularis propria. Depth of invasion initially was assessed by two reviewers independently and then by the two reviewers in consensus. MR images were compared with histopathologic findings.
RESULTS: The 7.0-T T2-weighted MR images clearly depicted the normal gastric wall in all 20 specimens (100%) as consisting of seven layers, which clearly corresponded to the tissue layers of the gastric wall. These MR images enabled clear differentiation between tumor tissue and fibrosis. Reviewers disagreed on the depth of invasion at the initial reading in three (15%) of 20 specimens (between mucosa and submucosa in two specimens and between muscularis propria and subserosa and serosa in one specimen); however, in all 20 gastric carcinomas, the depth of invasion could be accurately determined on T2-weighted images after consensus interpretation.
CONCLUSION: Ex vivo 7.0-T MR imaging enables clear delineation of the gastric wall layers and clear differentiation of tumor tissue from fibrosis and allows one to assess the depth of mural invasion by gastric carcinomas. RSNA, 2015

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Year:  2015        PMID: 25584712     DOI: 10.1148/radiol.14141878

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  9 in total

1.  Getting published in Radiology: A Deputy Editor's perspective.

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Review 2.  Imaging strategies in the management of gastric cancer: current role and future potential of MRI.

Authors:  Alicia S Borggreve; Lucas Goense; Hylke J F Brenkman; Stella Mook; Gert J Meijer; Frank J Wessels; Marcel Verheij; Edwin P M Jansen; Richard van Hillegersberg; Peter S N van Rossum; Jelle P Ruurda
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Authors:  Stefan C A Steens; Elise M Bekers; Willem L J Weijs; Geert J S Litjens; Andor Veltien; Arie Maat; Guido B van den Broek; Jeroen A W M van der Laak; Jürgen J Fütterer; Christina A Hulsbergen van der Kaa; Matthias A W Merkx; Robert P Takes
Journal:  Int J Comput Assist Radiol Surg       Date:  2017-01-27       Impact factor: 2.924

6.  Correlation of ultra-high field MRI with histopathology for evaluation of rectal cancer heterogeneity.

Authors:  Trang T Pham; Timothy Stait-Gardner; Cheok Soon Lee; Michael Barton; Petra L Graham; Gary Liney; Karen Wong; William S Price
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Authors:  Jan Heidkamp; Petra L M Zusterzeel; Adriana C H van Engen-van Grunsven; Christiaan G Overduin; Andor Veltien; Arie Maat; Maroeska M Rovers; Jurgen J Fütterer
Journal:  NMR Biomed       Date:  2018-11-15       Impact factor: 4.044

8.  Improving MR sequence of 18F-FDG PET/MR for diagnosing and staging gastric Cancer: a comparison study to 18F-FDG PET/CT.

Authors:  Dong Zheng; Yi Liu; Jiajin Liu; Ke Li; Mu Lin; Holger Schmidt; Baixuan Xu; Jiahe Tian
Journal:  Cancer Imaging       Date:  2020-06-16       Impact factor: 3.909

9.  Differentiating T1a-T1b from T2 in gastric cancer lesions with three different measurement approaches based on contrast-enhanced T1W imaging at 3.0 T.

Authors:  Yuan Yuan; Shengnan Ren; Tiegong Wang; Fu Shen; Qiang Hao; Jianping Lu
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  9 in total

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