Abstract #0265

Impact of attenuation correction on image-derived input function and cerebral blood flow quantification with simultaneous [15O]-water PET/MRI

Trine Hjoernevik¹, Mohammad Mehdi Khalighi², Sandeep Kaushik³, Yosuke Ishii^2,4, Greg Zaharchuk², and Audrey Peiwen Fan²

¹Oslo University Hospital, Oslo, Norway, ²Radiology, Stanford Unversity, Stanford, CA, United States, ³GE Global Research, Bangalore, India, ⁴Neurosurgery, Tokyo Medical and Dental University, Tokyo, Japan

This study evaluated the impact of attenuation correction (AC) on image-derived input functions (IDIF) and kinetic modeling of cerebral blood flow (CBF) parameters for simultaneous [¹⁵O]-water PET/MRI in the brain. Atlas-based AC led to 4.3% underestimation of the IDIF peak and 8-18% overestimation of absolute CBF in different brain perfusion states. On the other hand, zero echo time (ZTE)-based AC provided reproducible quantification of absolute CBF, comparable to the deep learning AC reference that was trained on real CT images. Attenuation correction is an important consideration for IDIF calculation and parametric mapping with PET/MRI; and ZTE-based and deep learning-based AC provide suitable quantitative accuracy for [¹⁵O]-water studies.

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