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 Singh^4,5

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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