Literature DB >> 11176288

Tumor angiogenesis and dynamic CT in lung adenocarcinoma: radiologic-pathologic correlation.

U Tateishi1, H Nishihara, S Watanabe, T Morikawa, K Abe, K Miyasaka.   

Abstract

PURPOSE: The purpose of this work was to evaluate the correlation of tumor angiogenesis and dynamic CT in lung adenocarcinoma.
METHOD: Thirty-five consecutive patients with lung adenocarcinoma underwent dynamic chest CT. Maximum attenuation of dynamic CT was compared with microvessel densities (MVDs) and vascular endothelial growth factor (VEGF) expression by immunohistochemistry.
RESULTS: The mean peak attenuation (A(PA)) of lung adenocarcinoma correlated with MVD (r = 0.689, p < 0.0001). VEGF positiveness of lung adenocarcinoma was 63%. There was a significant difference in A(PA) between VEGF-positive and -negative lung adenocarcinomas (39.9 +/- 3.9 and 24.3 +/- 2.3; p < 0.05). The mean MVDs of VEGF-positive adenocarcinomas were significantly higher than those of negative ones (82.5 +/- 5.9 and 49.2 +/- 7.1; p < 0.05). The mean A(PA) of VEGF-positive lung adenocarcinomas correlated positively with MVD (r = 0.707, p < 0.0001).
CONCLUSION: The A(PA) value of dynamic CT reflects MVD in lung adenocarcinoma. The A(PA) value of dynamic CT might be an index for VEGF-related tumor angiogenesis.

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Year:  2001        PMID: 11176288     DOI: 10.1097/00004728-200101000-00004

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


  22 in total

1.  Xenon-inhalation computed tomography for noninvasive quantitative measurement of tissue blood flow in pancreatic tumor.

Authors:  Masaru Kubota; Takamichi Murakami; Hiroaki Nagano; Hidetoshi Eguchi; Shigeru Marubashi; Shogo Kobayashi; Hiroshi Wada; Masahiro Tanemura; Keizo Dono; Shoji Nakamori; Masato Sakon; Morito Monden; Masaki Mori; Yuichiro Doki
Journal:  Dig Dis Sci       Date:  2011-09-28       Impact factor: 3.199

2.  Predicting adenocarcinoma recurrence using computational texture models of nodule components in lung CT.

Authors:  Adrien Depeursinge; Masahiro Yanagawa; Ann N Leung; Daniel L Rubin
Journal:  Med Phys       Date:  2015-04       Impact factor: 4.071

3.  Quantitative contrast-enhanced computed tomography: is there a need for system calibration?

Authors:  Kenneth A Miles; Helen Young; Sandra L Chica; Peter D Esser
Journal:  Eur Radiol       Date:  2006-09-29       Impact factor: 5.315

4.  Validation of the use of calibration factors between the iodine concentration and the computed tomography number measured outside the objects for estimation of iodine concentration inside the objects: phantom experiment.

Authors:  Kentaro Takanami; Shuichi Higano; Kei Takase; Tomohiro Kaneta; Takayuki Yamada; Hiroki Ishiya; Issei Mori; Shoki Takahashi
Journal:  Radiat Med       Date:  2008-05-29

5.  Fractal analysis of contrast-enhanced CT images to predict survival of patients with hepatocellular carcinoma treated with sunitinib.

Authors:  Koichi Hayano; Hiroyuki Yoshida; Andrew X Zhu; Dushyant V Sahani
Journal:  Dig Dis Sci       Date:  2014-02-22       Impact factor: 3.199

6.  Dynamic contrast-enhanced CT in patients treated with sorafenib and erlotinib for non-small cell lung cancer: a new method of monitoring treatment?

Authors:  Joline S W Lind; Martijn R Meijerink; Anne-Marie C Dingemans; Cornelis van Kuijk; Michel C Ollers; Dirk de Ruysscher; Pieter E Postmus; Egbert F Smit
Journal:  Eur Radiol       Date:  2010-07-13       Impact factor: 5.315

7.  Blood flow-metabolic relationships are dependent on tumour size in non-small cell lung cancer: a study using quantitative contrast-enhanced computer tomography and positron emission tomography.

Authors:  K A Miles; M R Griffiths; C J Keith
Journal:  Eur J Nucl Med Mol Imaging       Date:  2005-09-23       Impact factor: 9.236

8.  Correlation of CT enhancement, tumor angiogenesis and pathologic grading of pancreatic carcinoma.

Authors:  Zhong-Qiu Wang; Jie-Shou Li; Guang-Ming Lu; Xin-Hua Zhang; Zi-Qian Chen; Kui Meng
Journal:  World J Gastroenterol       Date:  2003-09       Impact factor: 5.742

9.  The Use of CT Perfusion to Determine Microvessel Density in Lung Cancer: Comparison with FDG-PET and Pathology.

Authors:  Ning Xing; Zu-Long Cai; Shao-Hong Zhao; Li Yang; Bai-Xuan Xu; Fu-Lin Wang
Journal:  Chin J Cancer Res       Date:  2011-06       Impact factor: 5.087

Review 10.  Clinical biomarkers of angiogenesis inhibition.

Authors:  Aaron P Brown; Deborah E Citrin; Kevin A Camphausen
Journal:  Cancer Metastasis Rev       Date:  2008-09       Impact factor: 9.264

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