title: Qualitative and Quantitative Evaluation of Blob-Based Time-of-Flight PET Image Reconstruction in Hybrid Brain PET/MR Imaging.
abstract: OBJECTIVE
  Many neurological diseases affect small structures in the brain and, as such, reliable visual evaluation and accurate quantification are required. Recent technological developments made the clinical use of hybrid positron emission tomography/magnetic resonance (PET/MR) systems possible, providing both functional and anatomical information in a single imaging session. Nevertheless, there is a trade-off between spatial resolution and image quality (contrast and noise), which is dictated mainly by the chosen acquisition and reconstruction protocols. Image reconstruction algorithms using spherical symmetric basis functions (blobs) for image representation have a number of additional parameters that impact both the qualitative and quantitative image characteristics. Hence, a detailed investigation of the blob-based reconstruction characteristics using different parameters is needed to achieve optimal reconstruction results.
  
  
  METHODS
  This work evaluated the impact of a range of blob parameters on image quality and quantitative accuracy of brain PET images acquired on the Ingenuity Time-of-Flight (TOF) PET/MR system. Two different phantoms were used to simulate brain imaging applications. Image contrast and noise characteristics were assessed using an image quality phantom. Quantitative performance in a clinical setting was investigated using the Hoffman 3D brain phantom at various count levels. Furthermore, the visual quality of four clinical studies was scored blindly by two experienced physicians to qualitatively evaluate the influence of different reconstruction protocols, hereby providing indications on parameters producing the best image quality.
  
  
  RESULTS
  Quantitative evaluation using the image quality phantom showed that larger basis function radii result in lower contrast recovery (∼2%) and lower variance levels (∼15%). The brain phantom and clinical studies confirmed these observations since lower contrast was seen between anatomical structures. High and low count statistics gave comparable values. The qualitative evaluation of the clinical studies, based on the assessment performed by the physicians, showed a preference towards lower image variance levels with a slightly lower contrast, favoring higher radii and four iterations.
  
  
  CONCLUSIONS
  This study systematically evaluated a number of basis function parameters and their quantitative and qualitative effect within PET image reconstruction in the context of brain imaging. A range of blob parameters can minimize error and provided optimal image quality, where the anatomical structures could be recognized but the exact delineation of these structures is simplified in scans with lower image variance levels and thus, higher radii should be preferred. With the optimization of blob parameters, the reconstructed images were found to be qualitatively improved (optimum parameters {d = 2.0375, alpha = 10.4101, radius = 3.9451}) as assessed by the physicians compared to the current clinical protocol. However, this qualitative improvement is task specific, depending on the desired image characteristics to be extracted. Finally, this work could be used as a guide for application-specific optimal parameter selection.
authors: Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, 1211, Geneva 4, Switzerland.|Technical Medicine, University of Twente, 7522 NB, Enschede, The Netherlands.
authors: Eva L
authors: EL
authors: Leemans
authors: Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, 1211, Geneva 4, Switzerland.
authors: Fotis
authors: F
authors: Kotasidis
authors: Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, 1211, Geneva 4, Switzerland.
authors: Michael
authors: M
authors: Wissmeyer
authors: Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, 1211, Geneva 4, Switzerland.
authors: Valentina
authors: V
authors: Garibotto
authors: Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, 1211, Geneva 4, Switzerland. habib.zaidi@hcuge.ch.|Geneva Neuroscience Center, Geneva University, 1205, Geneva, Switzerland. habib.zaidi@hcuge.ch.|Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, 9700 RB, Groningen, Netherlands. habib.zaidi@hcuge.ch.
authors: Habib
authors: H
authors: Zaidi
mesh_terms: D000465:Algorithms; D001921:Brain / Q000000981:diagnostic imaging*; D003704:Dementia / Q000000981:diagnostic imaging; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D019047:Phantoms, Imaging; D049268:Positron-Emission Tomography / Q000379:methods*
keywords: Blobs; Contrast; Image reconstruction; Noise; PET/MRI; Visual quality
references: Med Phys. 2011 Oct;38(10):5667-89
references: 21992383
references: J Nucl Med. 2014 May 12;55(Supplement 2):2S-10S
references: 24819419
references: J Nucl Med. 2002 Oct;43(10):1398-409
references: 12368380
references: J Nucl Med. 2010 Aug;51(8):1198-205
references: 20660388
references: Int J Biomed Imaging. 2012;2012:452910
references: 22548047
references: Phys Med Biol. 2011 May 21;56(10):3091-106
references: 21508443
references: J Nucl Med. 2012 Dec;53(12):1916-25
references: 23143086
references: Radiology. 2007 Oct;245(1):21-42
references: 17885179
references: Clin Nucl Med. 2013 Jan;38(1):e13-8
references: 23242058
references: Eur J Nucl Med Mol Imaging. 2011 Jan;38(1):138-52
references: 20922522
references: J Nucl Med. 1991 Dec;32(12):2342-50
references: 1744726
references: Eur J Nucl Med Mol Imaging. 2012 Jan;39(1):188-97
references: 22089660
references: Med Phys. 2014 Jun;41(6):062501
references: 24877835
references: IEEE Trans Med Imaging. 1996;15(1):68-78
references: 18215890
references: Phys Med Biol. 1992 Mar;37(3):705-16
references: 1565698