Abstract #2273
            Minimum sample size requirements for rCBV measures in patient glioblastoma trials
                      Melissa A Prah                     1                    , Steven M Stufflebeam                     2                    , 						Eric S Paulson                     1,3                    , Jayashree Kalpathy-Cramer                     2                    , 						Elizabeth R Gerstner                     4                    , Tracy T Batchelor                     4                    , 						Daniel P Barboriak                     5                    , Bruce Rosen                     2                    , 						and Kathleen M Schmainda                     1,6          
            
            1
           
           Radiology, Medical College of Wisconsin, 
						Milwaukee, WI, United States,
           
            2
           
           Radiology, 
						Massachusetts General Hospital, Charlestown, MA, United 
						States,
           
            3
           
           Radiation 
						Oncology, Medical College of Wisconsin, Milwaukee, WI, 
						United States,
           
            4
           
           Neurology, 
						Massachusetts General Hospital, Boston, MA, United 
						States,
           
            5
           
           Radiology, 
						Duke University Medical Center, Durham, NC, United 
						States,
           
            6
           
           Biophysics, 
						Medical College of Wisconsin, Milwaukee, WI, United 
						States
          
            
          Measures of relative cerebral blood volume (rCBV) have 
						shown to be immensely useful in assessing brain tumor 
						vascularity. This has led to increased interest in the 
						use of rCBV as a biomarker of clinical outcome or in 
						research. This work provides an estimate of the minimum 
						sample-size requirements to power a clinical imaging 
						trial involving glioblastoma patients for six of the 
						most commonly used rCBV estimation methods in order to 
						detect a parameter change of 10% or 20%. Using these 
						results, the efficiency of clinical trials may be 
						improved with methods requiring considerably fewer 
						participants to address a given hypothesis.
         
 
            
				
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