Research Papers:

High-resolution dynamic imaging and quantitative analysis of lung cancer xenografts in nude mice using clinical PET/CT

Ying Yi Wang, Kai Wang, Zuo Yu Xu, Yan Song, Chu Nan Wang, Chong Qing Zhang, Xi Lin Sun and Bao Zhong Shen _

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Oncotarget. 2017; 8:52802-52812. https://doi.org/10.18632/oncotarget.17263

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Ying Yi Wang1,2, Kai Wang1,2, Zuo Yu Xu1,2, Yan Song1,2, Chu Nan Wang1,2, Chong Qing Zhang1,2, Xi Lin Sun1,2,3 and Bao Zhong Shen1,2

1TOF-PET/CT/MR center, the Fourth Hospital of Harbin Medical University, Heilongjiang, China

2Molecular Imaging Research Center, Harbin Medical University, Heilongjiang, China

3Molecular Imaging Program at Stanford (MIPS), Department of Radiology, Stanford University School of Medicine, Stanford, California, USA

Correspondence to:

Bao Zhong Shen, email: shenbzh@vip.sina.com

Xi Lin Sun, email: sunxilin@aliyun.com

Keywords: PET/ CT, dynamic scan, molecular imaging, lung cancer

Received: November 09, 2016     Accepted: March 13, 2017     Published: April 20, 2017


Considering the general application of dedicated small-animal positron emission tomography/computed tomography is limited, an acceptable alternative in many situations might be clinical PET/CT. To estimate the feasibility of using clinical PET/CT with [F-18]-fluoro-2-deoxy-D-glucose for high-resolution dynamic imaging and quantitative analysis of cancer xenografts in nude mice. Dynamic clinical PET/CT scans were performed on xenografts for 60 min after injection with [F-18]-fluoro-2-deoxy-D-glucose. Scans were reconstructed with or without SharpIR method in two phases. And mice were sacrificed to extracting major organs and tumors, using ex vivo γ-counting as a reference. Strikingly, we observed that the image quality and the correlation between the all quantitive data from clinical PET/CT and the ex vivo counting was better with the SharpIR reconstructions than without. Our data demonstrate that clinical PET/CT scanner with SharpIR reconstruction is a valuable tool for imaging small animals in preclinical cancer research, offering dynamic imaging parameters, good image quality and accurate data quatification.

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