Literature DB >> 27711986

Esophageal carcinoma: Ex vivo evaluation by high-spatial-resolution T2 -mapping MRI compared with histopathological findings at 3.0T.

Yi Wei1,2, Sen Wu3, Feifei Gao1,2, Tingyi Sun4, Dandan Zheng5, Peigang Ning1,2, Cuihua Zhao1,2, Ziyuan Li1,2, Xiaodong Li1,2, Linlin Li1,2, Shaocheng Zhu1,2.   

Abstract

PURPOSE: To prospectively determine the feasibility of T2 -mapping magnetic resonance imaging (MRI) to quantitatively describe the signal characteristics of the normal esophageal wall and assess the depth of esophageal wall invasion by carcinoma at 3.0T.
MATERIALS AND METHODS: Thirty-two patient specimens, each having foci of carcinoma, were studied using 3.0T MR. Freehand regions of interest were placed to measure the T2 value of the normal esophageal layers and were compared with the regions of carcinoma. Three independent readers reviewed the MR images to evaluate the depth of carcinoma invasion; when the three radiologists could not fully agree with each other, the final stage was determined by consensus. The Games-Howell test was used to compare the difference between the normal esophageal layers and carcinoma. Spearman correlation coefficient analysis was used to compare the stage at MRI with that at histopathological analysis. The interobserver agreement was compared with Cohen's kappa. The sensitivity, specificity, and accuracy for detecting carcinoma invasion were calculated.
RESULTS: The T2 values between the carcinoma and normal esophageal layers were different (all P < 0.01), except for the inner circular muscle (P = 0.511). The T2 value of each layer of the normal esophageal wall was also different from that of the adjacent layer (all P < 0.01). In 29 of 32 lesions, the depth of the esophageal wall invasion determined by MR was consistent with the histopathological stage (r = 0.969, P < 0.001). The sensitivity, specificity, and accuracy were 80%, 96.3%, and 93.8%, respectively, for invasion into the mucosa; 77.8%, 95.7%, and 90.6%, respectively, for invasion into submucosa; 100%, 95.8%, and 96.9%, respectively, for invasion into muscularis propria; and 100%, 100%, and 100%, respectively, for invasion into the adventitia.
CONCLUSION: T2 -mapping MR images obtained using a 3.0T MR scanner can be used to depict the precise histopathological layers of the esophageal wall clearly and provide excellent diagnostic accuracy for assessing esophageal carcinoma invasion. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;45:1609-1616.
© 2016 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  T2-mapping; esophageal carcinoma; ex vivo; histopathological slices; magnetic resonance image

Mesh:

Year:  2016        PMID: 27711986     DOI: 10.1002/jmri.25509

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


  4 in total

1.  MR fingerprinting with simultaneous T1, T2, and fat signal fraction estimation with integrated B0 correction reduces bias in water T1 and T2 estimates.

Authors:  Jason Ostenson; Bruce M Damon; E Brian Welch
Journal:  Magn Reson Imaging       Date:  2019-03-23       Impact factor: 2.546

Review 2.  The Role of Magnetic Resonance Imaging in the Management of Esophageal Cancer.

Authors:  Anna Pellat; Anthony Dohan; Philippe Soyer; Julie Veziant; Romain Coriat; Maximilien Barret
Journal:  Cancers (Basel)       Date:  2022-02-23       Impact factor: 6.639

3.  Response Prediction to Concurrent Chemoradiotherapy in Esophageal Squamous Cell Carcinoma Using Delta-Radiomics Based on Sequential Whole-Tumor ADC Map.

Authors:  Dianzheng An; Qiang Cao; Na Su; Wanhu Li; Zhe Li; Yanxiao Liu; Yuxing Zhang; Baosheng Li
Journal:  Front Oncol       Date:  2022-03-15       Impact factor: 6.244

4.  DCE-MRI-Derived Volume Transfer Constant (Ktrans) and DWI Apparent Diffusion Coefficient as Predictive Markers of Short- and Long-Term Efficacy of Chemoradiotherapy in Patients With Esophageal Cancer.

Authors:  Zhi-Min Ye; Shu-Jun Dai; Feng-Qin Yan; Lei Wang; Jun Fang; Zhen-Fu Fu; Yue-Zhen Wang
Journal:  Technol Cancer Res Treat       Date:  2018-01-01
  4 in total

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