Literature DB >> 18830115

Computed tomographic findings and prognosis in thymic epithelial tumor patients.

Satomi Yakushiji1, Ukihide Tateishi, Shunji Nagai, Yoshihiro Matsuno, Kazuo Nakagawa, Hisao Asamura, Masahiko Kusumoto.   

Abstract

OBJECTIVE: To determine which computed tomographic findings are associated with high-risk thymic epithelial tumors and a poor prognosis.
METHODS: Computed tomographic findings of thymic epithelial neoplasms were retrospectively evaluated in 75 patients diagnosed with thymic tumor between January 1997 and October 2003. We analyzed the correlation of the computed tomographic findings, histological subtype according to the World Health Organization classification, and the prognosis.
RESULTS: There were 34 with type A approximately B1 tumor and 41 with type B2 approximately C tumor. On multiple regression analysis, vascular obliteration and a blunt sternum-anterior mediastinum angle were more frequent with thymic carcinoma than with thymoma. On multivariate analysis, pleural effusion and mediastinal fat infiltration on initial computed tomography had a significant impact on survival.
CONCLUSIONS: Vascular obliteration and a blunt sternum-anterior mediastinum angle were predictive of thymic carcinoma. Pleural effusion and mediastinal fat infiltration were predictive of a poor prognosis.

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Year:  2008        PMID: 18830115     DOI: 10.1097/RCT.0b013e31815896df

Source DB:  PubMed          Journal:  J Comput Assist Tomogr        ISSN: 0363-8715            Impact factor:   1.826


  10 in total

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Authors:  Daniel B Green; Sarah Eliades; Alan C Legasto; Gulce Askin; Jeffrey L Port; James F Gruden
Journal:  Eur Radiol       Date:  2019-02-26       Impact factor: 5.315

2.  Only when all contribute their firewood can they build up a big fire.

Authors:  Marcelo F Benveniste; Edith M Marom
Journal:  J Thorac Dis       Date:  2016-07       Impact factor: 2.895

3.  Risk stratification of thymic epithelial tumors by using a nomogram combined with radiomic features and TNM staging.

Authors:  Qijun Shen; Yanna Shan; Wen Xu; Guangzhu Hu; Wenhui Chen; Zhan Feng; Peipei Pang; Zhongxiang Ding; Wenli Cai
Journal:  Eur Radiol       Date:  2020-08-05       Impact factor: 5.315

4.  Volume-based quantification using dual-energy computed tomography in the differentiation of thymic epithelial tumours: an initial experience.

Authors:  Suyon Chang; Jin Hur; Dong Jin Im; Young Joo Suh; Yoo Jin Hong; Hye-Jeong Lee; Young Jin Kim; Kyunghwa Han; Dae Joon Kim; Chang Young Lee; Ha Young Shin; Byoung Wook Choi
Journal:  Eur Radiol       Date:  2016-08-23       Impact factor: 5.315

5.  CT imaging-based machine learning model: a potential modality for predicting low-risk and high-risk groups of thymoma: "Impact of surgical modality choice".

Authors:  Ayten Kayi Cangir; Kaan Orhan; Yusuf Kahya; Hilal Özakıncı; Betül Bahar Kazak; Buse Mine Konuk Balcı; Duru Karasoy; Çağlar Uzun
Journal:  World J Surg Oncol       Date:  2021-05-11       Impact factor: 2.754

6.  Efficacy of computed tomography features in predicting stage III thymic tumors.

Authors:  Yan Shen; Jianding Ye; Wentao Fang; Yu Zhang; Xiaodan Ye; Yonghong Ma; Libo Chen; Minghua Li
Journal:  Oncol Lett       Date:  2016-11-23       Impact factor: 2.967

Review 7.  Prognostic impact of pleural effusion in patients with malignancy: A systematic review and meta-analysis.

Authors:  Yuan Yang; Juan Du; Yi-Shan Wang; Han-YuJie Kang; Kan Zhai; Huan-Zhong Shi
Journal:  Clin Transl Sci       Date:  2022-03-21       Impact factor: 4.438

8.  Volumetric analysis of the thymic epithelial tumors: correlation of tumor volume with the WHO classification and Masaoka staging.

Authors:  Yukihisa Sato; Masahiro Yanagawa; Akinori Hata; Yukihiro Enchi; Noriko Kikuchi; Osamu Honda; Katsuyuki Nakanishi; Noriyuki Tomiyama
Journal:  J Thorac Dis       Date:  2018-10       Impact factor: 2.895

9.  Iodine Quantification Using Dual-Energy Computed Tomography for Differentiating Thymic Tumors.

Authors:  Wei-Qiang Yan; Yong-Kang Xin; Yong Jing; Gang-Feng Li; Shu-Mei Wang; Wei-Cheng Rong; Gang Xiao; Xue-Bin Lei; Bo Li; Yu-Chuan Hu; Guang-Bin Cui
Journal:  J Comput Assist Tomogr       Date:  2018 Nov/Dec       Impact factor: 1.826

10.  Long non-coding RNA-based signatures to improve prognostic prediction of breast cancer.

Authors:  Yi Zhang; Yuzhi Wang; Gang Tian; Tianhua Jiang
Journal:  Medicine (Baltimore)       Date:  2020-10-02       Impact factor: 1.817

  10 in total

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