Literature DB >> 10966715

Dynamic contrast-enhanced MR imaging of uterine cervical cancer: pharmacokinetic analysis with histopathologic correlation and its importance in predicting the outcome of radiation therapy.

Y Yamashita1, T Baba, Y Baba, R Nishimura, S Ikeda, M Takahashi, H Ohtake, H Okamura.   

Abstract

PURPOSE: To investigate the histopathologic bases of different enhancement patterns on dynamic contrast material-enhanced magnetic resonance (MR) images of cervical cancer and to assess their importance in predicting the outcome of patients after radiation therapy.
MATERIALS AND METHODS: Dynamic enhanced MR imaging and pharmacokinetic analyses were performed in 26 patients with cervical cancer who subsequently underwent hysterectomy and in 36 patients with cervical cancer who received radiation therapy. Histopathologic findings and clinical outcomes were correlated with results of dynamic MR imaging and pharmacokinetic analysis.
RESULTS: On dynamic MR images of the surgical patients, areas with intense homogeneous enhancement showed increased permeability (k = 27.4 x 10(-3)) compared with areas with poor enhancement (k = 19.0 x 10(-3)). Well-enhanced areas were predominantly composed of cancer cell fascicles, whereas poorly enhanced areas were composed of fibrous tissue with scattered cancer cells. Radiation therapy was more effective in tumors with higher tissue permeability (k = 31.3 x 10(-3)) on dynamic MR images than in those with lower tissue permeability (k = 18.3 x 10(-3)).
CONCLUSION: Areas of increased contrast enhancement are mainly composed of abundant cancer cell fascicles, whereas poorly perfused areas are composed of fibrous tissue with scattered cancer cells. Radiation therapy is more effective in well-enhanced tumors, resulting in improved local control.

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Year:  2000        PMID: 10966715     DOI: 10.1148/radiology.216.3.r00se07803

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


  22 in total

1.  Multi-parametric MRI in cervical cancer: early prediction of response to concurrent chemoradiotherapy in combination with clinical prognostic factors.

Authors:  Wei Yang; Jin Wei Qiang; Hai Ping Tian; Bing Chen; Ai Jun Wang; Jian Guo Zhao
Journal:  Eur Radiol       Date:  2017-08-04       Impact factor: 5.315

2.  Prediction of response to chemoradiation therapy in squamous cell carcinomas of the head and neck using dynamic contrast-enhanced MR imaging.

Authors:  S Kim; L A Loevner; H Quon; A Kilger; E Sherman; G Weinstein; A Chalian; H Poptani
Journal:  AJNR Am J Neuroradiol       Date:  2009-10-01       Impact factor: 3.825

Review 3.  The promise of dynamic contrast-enhanced imaging in radiation therapy.

Authors:  Yue Cao
Journal:  Semin Radiat Oncol       Date:  2011-04       Impact factor: 5.934

4.  Perfusion and diffusion characteristics of cervical cancer based on intraxovel incoherent motion MR imaging-a pilot study.

Authors:  Elaine Yuen Phin Lee; Xue Yu; Mandy Man Yee Chu; Hextan Yuen Sheung Ngan; Steven Wai Kwan Siu; Inda Sung Soong; Queenie Chan; Pek-Lan Khong
Journal:  Eur Radiol       Date:  2014-04-19       Impact factor: 5.315

Review 5.  Imaging hypoxia in gliomas.

Authors:  I Mendichovszky; A Jackson
Journal:  Br J Radiol       Date:  2011-12       Impact factor: 3.039

6.  Characterizing tumor heterogeneity with functional imaging and quantifying high-risk tumor volume for early prediction of treatment outcome: cervical cancer as a model.

Authors:  Nina A Mayr; Zhibin Huang; Jian Z Wang; Simon S Lo; Joline M Fan; John C Grecula; Steffen Sammet; Christina L Sammet; Guang Jia; Jun Zhang; Michael V Knopp; William T C Yuh
Journal:  Int J Radiat Oncol Biol Phys       Date:  2011-12-28       Impact factor: 7.038

7.  The value of perfusion CT in predicting the short-term response to synchronous radiochemotherapy for cervical squamous cancer.

Authors:  Xiang Sheng Li; Hong Xia Fan; Hong Xian Zhu; Yun Long Song; Chun Wu Zhou
Journal:  Eur Radiol       Date:  2011-09-30       Impact factor: 5.315

8.  Predicting control of primary tumor and survival by DCE MRI during early therapy in cervical cancer.

Authors:  William T C Yuh; Nina A Mayr; David Jarjoura; Dee Wu; John C Grecula; Simon S Lo; Susan M Edwards; Vincent A Magnotta; Steffen Sammet; Hualin Zhang; Joseph F Montebello; Jeffrey Fowler; Michael V Knopp; Jian Z Wang
Journal:  Invest Radiol       Date:  2009-06       Impact factor: 6.016

Review 9.  Magnetic resonance imaging of the tumor microenvironment in radiotherapy: perfusion, hypoxia, and metabolism.

Authors:  Masayuki Matsuo; Shingo Matsumoto; James B Mitchell; Murali C Krishna; Kevin Camphausen
Journal:  Semin Radiat Oncol       Date:  2014-07       Impact factor: 5.934

10.  Validation of optimal DCE-MRI perfusion threshold to classify at-risk tumor imaging voxels in heterogeneous cervical cancer for outcome prediction.

Authors:  Zhibin Huang; Kevin A Yuh; Simon S Lo; John C Grecula; Steffen Sammet; Christina L Sammet; Guang Jia; Michael V Knopp; Qiang Wu; Norman J Beauchamp; William T C Yuh; Roy Wang; Nina A Mayr
Journal:  Magn Reson Imaging       Date:  2014-08-29       Impact factor: 2.546

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