Registration Method for the Detection of Tumors in Lung and Liver Using Multimodal Small Animal Imaging

Abstract

Small animal PET scanning with <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">18</sup> F-FDG has been increasingly used in the studies using murine tumor models. The aim of this study was to obtain multimodal tumor images with the use of small animal PET and clinical CT by using hardware guidance and a registration method. PET imaging studies were performed with a dedicated small animal PET scanner. Static PET images of mice with liver and lung tumors were scanned for 20 minute by the use of hardware guidance with 1% activity of the injected dose. The CT images obtained with the use of a clinical CT scanner can be used to improve the anatomical localization of uptake in PET images. <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">124</sup> I -FIAU-PET was obtained from mice containing an orthotopic hepatocellular carcinoma (HCC). Contrast enhanced CT images were obtained at three hours after injection of contrast agent. The PET and CT images were fused using hardware fiducial markers that were manually identified in both data sets. The PET and CT images were precisely registered by the use of a small animal contour point in both data sets to perform a point-based rigid registration. The registered images in the HCC model and a lung metastatic tumor model showed good agreement of tumor region on the both PET and CT images. The use of PET and contrast enhanced CT allowed a precise and improved detection of tumors in liver and lung models. Multimodal imaging with small animal PET and clinical CT images was useful in the detection of metastatic tumors and this multimodal imaging registration method can improve the quantitative accuracy and interpretation of tracer.