Enescu, M.* ; Bhushan, M.* ; Hill, E.J.* ; Franklin, J.* ; Anderson, E.M.* ; Sharma, R.A.* ; Schnabel, J.A.*
    
    
        
pCT derived arterial input function for improved pharmacokinetic analysis of longitudinal dceMRI for colorectal cancer.
    
    
        
    
    
        
        In:. SPIE, 2013. (Proc. SPIE ; 8669)
    
    
 	
    
	
	  DOI
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			Open Access Green as soon as Postprint is submitted to ZB.
		
     
    
      
      
	
	    Dynamic contrast-enhanced MRI is a dynamic imaging technique that is now widely used for cancer imaging. Changes in tumour microvasculature are typically quantified by pharmacokinetic modelling of the contrast uptake curves. Reliable pharmacokinetic parameter estimation depends on the measurement of the arterial in- put function, which can be obtained from arterial blood sampling, or extracted from the image data directly. However, arterial blood sampling poses additional risks to the patient, and extracting the input function from MR intensities is not reliable. In this work, we propose to compute a perfusion CT based arterial input function, which is then employed for dynamic contrast enhanced MRI pharmacokinetic parameter estimation. Here, pa- rameter estimation is performed simultaneously with intra-sequence motion correction by using nonlinear image registration. Ktrans maps obtained with this approach were compared with those obtained using a population averaged arterial input function, i.e. Orton. The dataset comprised 5 rectal cancer patients, who had been imaged with both perfusion CT and dynamic contrast enhanced MRI, before and after the administration of a radiosensitising drug. Ktrans distributions pre and post therapy were computed using both the perfusion CT and the Orton arterial input function. Perfusion CT derived arterial input functions can be used for pharmacokinetic modelling of dynamic contrast enhanced MRI data, when perfusion CT images of the same patients are available. Compared to the Orton model, perfusion CT functions have the potential to give a more accurate separation between responders and non-responders.
	
	
	    
	
       
      
	
	    
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        Publication type
        Article: Conference contribution
    
 
    
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        Keywords
        Arterial Input Function ; Dcemri ; Motion Correction ; Perfusion Ct Arterial Input Function ; Pharmacokinetic Modelling ; Rectal Cancer ; Registration
    
 
    
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        Language
        english
    
 
    
        Publication Year
        2013
    
 
    
        Prepublished in Year
        
    
 
    
        HGF-reported in Year
        2013
    
 
    
    
        ISSN (print) / ISBN
        0277-786X
    
 
    
        e-ISSN
        1996-756X
    
 
    
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	    Volume: 8669 
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            SPIE
        
 
        
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        Reviewing status
        Peer reviewed
    
 
    
        Institute(s)
        Institute for Machine Learning in Biomed Imaging (IML)
    
 
    
        POF-Topic(s)
        30205 - Bioengineering and Digital Health
    
 
    
        Research field(s)
        Enabling and Novel Technologies
    
 
    
        PSP Element(s)
        G-507100-001
    
 
    
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        Erfassungsdatum
        2022-09-06