Performance Simulation of an Ultra-High Resolution Brain PET Scanner Using 1.2-mm Pixel Detectors.

Performance Simulation of an Ultra-High Resolution Brain PET Scanner Using 1.2-mm Pixel Detectors.

Gaudin, Émilie;Toussaint, Maxime;Thibaudeau, Christian;Paillé, Maxime;Fontaine, Réjean;Lecomte, Roger;
ieee transactions on radiation and plasma medical sciences 2019 Vol. 3 pp. 334-342
194
gaudin2019performanceieee

Abstract

The concept of a new ultra-high resolution positron emission tomography (PET) brain scanner featuring truly pixelated detectors based on the LabPET II technology is presented. The aim of this study is to predict the performance of the scanner using GATE simulations. The NEMA procedures for human and small animal PET scanners were used, whenever appropriate, to simulate spatial resolution, scatter fraction, count rate performance and the sensitivity of the proposed system compared to state-of-the-art PET scanners that would currently be the preferred choices for brain imaging, namely the HRRT dedicated brain PET scanner and the Biograph Vision wholebody clinical PET scanner. The imaging performance was also assessed using the NEMA-NU4 image quality phantom, a mini hot spot phantom and a 3-D voxelized brain phantom. A reconstructed nearly isotropic spatial resolution of 1.3 mm FWHM is obtained at 10 mm from the center of the field of view. With an energy window of 250-650 keV, the system absolute sensitivity is estimated at 3.4% and its maximum NECR reaches 16.4 kcps at 12 kBq/cc. The simulation results provide evidence of the promising capabilities of the proposed scanner for ultra-high resolution brain imaging.

Citation

ID: 20271
Ref Key: gaudin2019performanceieee
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
20271
Unique Identifier:
10.1109/TRPMS.2018.2877511
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet