A 3D-printed anatomical pancreas and kidney phantom for optimizing SPECT/CT reconstruction settings in beta cell imaging using (111)In-exendin

利用(111)In-艾塞那肽优化β细胞成像中SPECT/CT重建设置的3D打印解剖胰腺和肾脏模型

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Abstract

BACKGROUND: Quantitative single photon emission computed tomography (SPECT) is challenging, especially for pancreatic beta cell imaging with (111)In-exendin due to high uptake in the kidneys versus much lower uptake in the nearby pancreas. Therefore, we designed a three-dimensionally (3D) printed phantom representing the pancreas and kidneys to mimic the human situation in beta cell imaging. The phantom was used to assess the effect of different reconstruction settings on the quantification of the pancreas uptake for two different, commercially available software packages. METHODS: 3D-printed, hollow pancreas and kidney compartments were inserted into the National Electrical Manufacturers Association (NEMA) NU2 image quality phantom casing. These organs and the background compartment were filled with activities simulating relatively high and low pancreatic (111)In-exendin uptake for, respectively, healthy humans and type 1 diabetes patients. Images were reconstructed using Siemens Flash 3D and Hermes Hybrid Recon, with varying numbers of iterations and subsets and corrections. Images were visually assessed on homogeneity and artefacts, and quantitatively by the pancreas-to-kidney activity concentration ratio. RESULTS: Phantom images were similar to clinical images and showed comparable artefacts. All corrections were required to clearly visualize the pancreas. Increased numbers of subsets and iterations improved the quantitative performance but decreased homogeneity both in the pancreas and the background. Based on the phantom analyses, the Hybrid Recon reconstruction with 6 iterations and 16 subsets was found to be most suitable for clinical use. CONCLUSIONS: This work strongly contributed to quantification of pancreatic (111)In-exendin uptake. It showed how clinical images of (111)In-exendin can be interpreted and enabled selection of the most appropriate protocol for clinical use.

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