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Abstract #4799

A Method to Improve Automated Subject Specific Arterial Input Function for DCE-MRI and to Evaluate its Effect on Glioma Grading at 3T

Dinil Sasi S1, Sameer Manickam2, Rakshit Dadarwal1, Rakesh K Gupta3, and Anup Singh4,5
1Center for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India, 2KTH Royal Institute of Technology, Stockholm, Sweden, 3Fortis Memorial Research Institute, Gurugram, India, 4Indian Institute of Technology Delhi, Hauz Khas, India, 5All India Institute of Medical Science, New Delhi, India

Arterial-input-function(AIF) or vascular-input-function is a prerequisite for quantitative analysis of dynamic-contrast-enhanced(DCE)-MRI data. For DCE-MRI data of human brain used in the current study, previously reported automatic AIF estimation approach resulted in large variations from theoretically expected shape. In this study, DCE-MRI data of 25 treatment-naïve glioma patients were included. Proposed optimization enabled the removal of wrongly selected voxels having distorted concentration curve and hence provided an improved AIF. A substantial change in the shape of AIF was observed on optimization. Corrected AIF also resulted in significant improvement in quantitative perfusion parameters and glioma gradin

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