Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Jian Z"'
Publikováno v:
International Journal of Radiation Oncology*Biology*Physics. 84:478-484
Purpose Accelerated tumor repopulation has significant implications in low–dose rate (LDR) brachytherapy. Repopulation onset time remains undetermined for cervical cancer. The purpose of this study was to determine the onset time of accelerated rep
Autor:
Joseph F. Montebello, Simon S. Lo, John C. Grecula, William T.C. Yuh, Nina A. Mayr, K Li, Jian Z. Wang, D. Zhang
Publikováno v:
Cancer. 116:5093-5101
Background To investigate outcome prediction by measuring tumor absolute volume and regression ratio using serial magnetic resonance imaging (MRI) during radiation therapy (RT) of cervical cancer and to develop algorithms identifying patients at risk
Autor:
Nina A. Mayr, William T.C. Yuh, L Lu, John C. Grecula, Joseph F. Montebello, Simon S. Lo, D. Zhang, Jeffrey M. Fowler, Jian Z. Wang
Publikováno v:
International Journal of Radiation Oncology*Biology*Physics. 76:719-727
To assess individual volumetric tumor regression pattern in cervical cancer during therapy using serial four-dimensional MRI and to define the regression parameters' prognostic value validated with local control and survival correlation.One hundred a
Autor:
Joseph F. Montebello, Jian Z. Wang, David Jajoura, D. Zhang, William T.C. Yuh, Simon S. Lo, D. Scott McMeekin, Kyle Porter, Nina A. Mayr, John M. Buatti
Publikováno v:
Cancer. 116:903-912
BACKGROUND: The authors prospectively evaluated magnetic resonance imaging (MRI) parameters quantifying heterogeneous perfusion pattern and residual tumor volume early during treatment in cervical cancer, and compared their predictive power for prima
Predicting Outcomes in Cervical Cancer: A Kinetic Model of Tumor Regression during Radiation Therapy
Autor:
Nilendu Gupta, K Li, Jian Z. Wang, Joseph F. Montebello, Zhibin Huang, L Lu, William T.C. Yuh, John C. Grecula, Simon S. Lo, Nina A. Mayr, H Zhang
Publikováno v:
Cancer Research. 70:463-470
Applications of mathematical modeling can improve outcome predictions of cancer therapy. Here we present a kinetic model incorporating effects of radiosensitivity, tumor repopulation, and dead-cell resolving on the analysis of tumor volume regression
Publikováno v:
The British journal of radiology. 88(1048)
Current cancer therapy strategy is mostly population based, however, there are large differences in tumour response among patients. It is therefore important for treating physicians to know individual tumour response. In recent years, many studies pr
Autor:
Kruti Patel, M Kang, Warren D. D'Souza, P Klahr, William F. Regine, Barton F. Lane, Ming Xue, Jian Z. Wang, Shifeng Chen, Wenju Lu, Wookjin Choi
Publikováno v:
Medical Physics. 43:3897-3898
Purpose: To develop an individually optimized contrast-enhanced (CE) 4D-CT for radiotherapy simulation in pancreatic ductal adenocarcinomas (PDA). Methods: Ten PDA patients were enrolled. Each underwent 3 CT scans: a 4D-CT immediately following a CE
Autor:
Steffen Sammet, Jian Z. Wang, Christina L. Sammet, Guang Jia, William T.C. Yuh, Nina A. Mayr, Jun Zhang, Zhibin Huang, Michael V. Knopp, John C. Grecula, Joline M. Fan, Simon S. Lo
Publikováno v:
International journal of radiation oncology, biology, physics. 83(3)
Treatment response in cancer has been monitored by measuring anatomic tumor volume (ATV) at various times without considering the inherent functional tumor heterogeneity known to critically influence ultimate treatment outcome: primary tumor control
Autor:
John C. Grecula, Simon S. Lo, L Lu, Joseph F. Montebello, Dee H. Wu, Zhibin Huang, Jeffery M. Fowler, Michael V. Knopp, H Zhang, David Jaroura, D. Zhang, Jian Z. Wang, K Li, William T.C. Yuh, Nina A. Mayr
Publikováno v:
International journal of radiation oncology, biology, physics. 77(2)
Purpose: To study the temporal changes of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) perfusion patterns during the radiation therapy (RT) course and their influence on local control and survival in cervical cancer. Methods and Mat
Autor:
Metin N. Gurcan, Joel H. Saltz, William T.C. Yuh, Nina A. Mayr, D. Zhang, Jeffrey W. Prescott, Jian Z. Wang
Publikováno v:
Journal of digital imaging. 23(3)
In this paper, we present a method of quantifying the heterogeneity of cervical cancer tumors for use in radiation treatment outcome prediction. Features based on the distribution of masked wavelet decomposition coefficients in the tumor region of in