Kersemans, V.* ; Kannan, P.* ; Beech, J.S.* ; Bates, R.* ; Irving, B.* ; Gilchrist, S.* ; Allen, P.D.* ; Thompson, J.* ; Kinchesh, P.* ; Casteleyn, C.* ; Schnabel, J.A.* ; Partridge, M.* ; Muschel, R.J.* ; Smart, S.C.*
    
    
        
Improving in vivo high-resolution CT imaging of the tumour vasculature in xenograft mouse models through reduction of motion and bone-streak artefacts.
    
    
        
    
    
        
        PLoS ONE 10:e0128537 (2015)
    
    
    
      
      
	
	    Introduction: Preclinical in vivo CT is commonly used to visualise vessels at a macroscopic scale. However, it is prone to many artefacts which can degrade the quality of CT images significantly. Although some artefacts can be partially corrected for during image processing, they are best avoided during acquisition. Here, a novel imaging cradle and tumour holder was designed to maximise CT resolution. This approach was used to improve preclinical in vivo imaging of the tumour vasculature. Procedures: A custom built cradle containing a tumour holder was developed and fix-mounted to the CT system gantry to avoid artefacts arising from scanner vibrations and out-of-field sample positioning. The tumour holder separated the tumour from bones along the axis of rotation of the CT scanner to avoid bone-streaking. It also kept the tumour stationary and insensitive to respiratory motion. System performance was evaluated in terms of tumour immobilisation and reduction of motion and bone artefacts. Pre- and post-contrast CT followed by sequential DCE-MRI of the tumour vasculature in xenograft transplanted mice was performed to confirm vessel patency and demonstrate the multimodal capacity of the new cradle. Vessel characteristics such as diameter, and branching were quantified. Results: Image artefacts originating from bones and out-of-field sample positioning were avoided whilst those resulting from motions were reduced significantly, thereby maximising the resolution that can be achieved with CT imaging in vivo. Tumour vessels ≥ 77 μm could be resolved and blood flow to the tumour remained functional. The diameter of each tumour vessel was determined and plotted as histograms and vessel branching maps were created. Multimodal imaging using this cradle assembly was preserved and demonstrated. Conclusions: The presented imaging workflow minimised image artefacts arising from scanner induced vibrations, respiratory motion and radiopaque structures and enabled in vivo CT imaging and quantitative analysis of the tumour vasculature at higher resolution than was possible before. Moreover, it can be applied in a multimodal setting, therefore combining anatomical and dynamic information.
	
	
	    
	
       
      
	
	    
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        Publication type
        Article: Journal article
    
 
    
        Document type
        Scientific Article
    
 
    
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        Language
        english
    
 
    
        Publication Year
        2015
    
 
    
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        HGF-reported in Year
        2015
    
 
    
    
        ISSN (print) / ISBN
        1932-6203
    
 
    
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	    Volume: 10,  
	    Issue: 6,  
	    Pages: ,  
	    Article Number: e0128537 
	    Supplement: ,  
	
    
 
    
        
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            Publisher
            Public Library of Science (PLoS)
        
 
        
            Publishing Place
            Lawrence, Kan.
        
 
	
        
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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
        2022-09-05