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Prediction of Delivered Dose Based On a Joint Histogram of CT and FDG PET Images

M Park

M Park1*, Y Choi2 , A Cho2 , S Hwang2 , J Cha2 , N Lee2 , M Yun2 , (1) Brigham and Women's Hospital and Harvard Medical School, Boston, MA, (2) Yonsei University College of Medicine, Seoul, Korea


SU-D-201-2 (Sunday, July 12, 2015) 2:05 PM - 3:00 PM Room: 201

Purpose:To investigate whether pre-treatment images can be used in predicting microsphere distribution in tumors. When intra-arterial radioembolization using Y90 microspheres was performed, the microspheres were often delivered non-uniformly within the tumor, which could lead to an inefficient therapy. Therefore, it is important to estimate the distribution of microspheres.

Methods:Early arterial phase CT and FDG PET images were acquired for patients with primary liver cancer prior to radioembolization (RE) using Y90 microspheres. Tumor volume was delineated on CT images and fused with FDG PET images. From each voxel (3.9 x3.9x3.3 mm3) in the tumor, the Hounsfield unit (HU) from the CT and SUV values from the FDG PET were harvested. We binned both HU and SUV into 11 bins and then calculated a normalized joint-histogram in an 11x11 array.
Patients also underwent a post-treatment Y90 PET imaging. Radiation dose for the tumor was estimated using convolution of the Y90 distribution with a dose-point kernel. We also calculated a fraction of the tumor volume that received a radiation dose great than 100Gy.

Results:Averaged over 40 patients, 55% of tumor volume received a dose greater than 100Gy (range : 1.1 – 100%). The width of the joint histogram was narrower for patients with a high dose. For patients with a low dose, the width was wider and a larger fraction of tumor volume had low HU.

Conclusion:We have shown the pattern of joint histogram of the HU and SUV depends on delivered dose. The patterns can predict the efficacy of uniform intra-arterial delivery of Y90 microspheres.

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