Abstract

) Core A will provide all administrative support to the grant. The core also provides all statistical support to the research projects and cores. Specific areas of administrative responsibility include long and short term planning, review of scientific progress, coordination of component cores and projects, purchasing and personnel management, budget and accounts management, and the preparation and submission of progress reports. Clerical support and management of efficient office operations will be the responsibility of this core. Statistical support provided by this core includes statistical design, control, and analysis of the clinical dose escalation studies in Project 4, and statistical design and analysis of the many different experiments and studies in the other projects.

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Program Projects (P01)
Project #
2P01CA059827-06A1
Application #
6347363
Study Section
Project Start
2000-09-01
Project End
2001-07-31
Budget Start
Budget End
Support Year
6
Fiscal Year
2000
Total Cost
Indirect Cost

  Institution

Name
University of Michigan Ann Arbor
Department
Type
DUNS #
791277940
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109

  Publications

Feng, Mary; Suresh, Krithika; Schipper, Matthew J et al. (2018) Individualized Adaptive Stereotactic Body Radiotherapy for Liver Tumors in Patients at High Risk for Liver Damage: A Phase 2 Clinical Trial. JAMA Oncol 4:40-47
Owen, Daniel Rocky; Boonstra, Phillip S; Viglianti, Benjamin L et al. (2018) Modeling Patient-Specific Dose-Function Response for Enhanced Characterization of Personalized Functional Damage. Int J Radiat Oncol Biol Phys 102:1265-1275
Deist, Timo M; Dankers, Frank J W M; Valdes, Gilmer et al. (2018) Machine learning algorithms for outcome prediction in (chemo)radiotherapy: An empirical comparison of classifiers. Med Phys 45:3449-3459
Johansson, Adam; Balter, James; Cao, Yue (2018) Rigid-body motion correction of the liver in image reconstruction for golden-angle stack-of-stars DCE MRI. Magn Reson Med 79:1345-1353
Johansson, Adam; Balter, James M; Cao, Yue (2018) Abdominal DCE-MRI reconstruction with deformable motion correction for liver perfusion quantification. Med Phys 45:4529-4540
Tseng, Huan-Hsin; Luo, Yi; Ten Haken, Randall K et al. (2018) The Role of Machine Learning in Knowledge-Based Response-Adapted Radiotherapy. Front Oncol 8:266
Jochems, Arthur; El-Naqa, Issam; Kessler, Marc et al. (2018) A prediction model for early death in non-small cell lung cancer patients following curative-intent chemoradiotherapy. Acta Oncol 57:226-230
Rosen, Benjamin S; Hawkins, Peter G; Polan, Daniel F et al. (2018) Early Changes in Serial CBCT-Measured Parotid Gland Biomarkers Predict Chronic Xerostomia After Head and Neck Radiation Therapy. Int J Radiat Oncol Biol Phys 102:1319-1329
Luo, Yi; McShan, Daniel L; Matuszak, Martha M et al. (2018) A multiobjective Bayesian networks approach for joint prediction of tumor local control and radiation pneumonitis in nonsmall-cell lung cancer (NSCLC) for response-adapted radiotherapy. Med Phys :
Simeth, Josiah; Johansson, Adam; Owen, Dawn et al. (2018) Quantification of liver function by linearization of a two-compartment model of gadoxetic acid uptake using dynamic contrast-enhanced magnetic resonance imaging. NMR Biomed 31:e3913

Showing the most recent 10 out of 289 publications