Reducing the influence of the partial volume effect on SPECT activity quantitation with 3D modelling of spatial resolution in iterative reconstruction
Open accessAbstract
Quantitative parameters such as the maximum and total counts in a volume are influenced by the partial volume effect. The magnitude of this effect varies with the non-stationary and anisotropic spatial resolution in SPECT slices. The objective of this investigation was to determine whether iterative reconstruction which includes modelling of the three-dimensional (3D) spatial resolution of SPECT imaging can reduce the impact of the partial volume effect on the quantitation of activity compared with filtered backprojection (FBP) techniques which include low-pass, and linear restoration filtering using the frequency distance relationship (FDR). The iterative reconstruction algorithms investigated were maximum-likelihood expectation-maximization (MLEM), MLEM with ordered subset acceleration (ML-OS), and MLEM with acceleration by the rescaled-block-iterative technique (ML-RBI). The SIMIND Monte Carlo code was used to simulate small hot spherical objects in an elliptical cylinder with and without uniform background activity as imaged by a low-energy ultra-high-resolution (LEUHR) collimator. Centre count ratios (CCRs) and total count ratios (TCRs) were determined as the observed counts over true counts. CCRs were unstable while TCRs had a bias of approximately 10% for all iterative techniques. The variance in the TCRs for ML-OS and ML-RBI was clearly elevated over that of MLEM, with ML-RBI having the smaller elevation. TCRs obtained with FDR-Wiener filtering had a larger bias (approximately 30%) than any of the iterative reconstruction methods but near stationarity is also reached. Butterworth filtered results varied by 9.7% from the centre to the edge. The addition of background has an influence on the convergence rate and noise properties of iterative techniques.
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The Fragile X syndrome population has susceptibility to ASD, ADHD, anxiety disorders, and neurological disorders such as epilepsy.
“This population also has susceptibility to certain other neuropsychiatric disabilities including ASD, ADHD, anxiety disorders, and neurological disorders such as epilepsy (Hessl et al., 2001; Pretorius et al., 1998).”
From Oxytocin and vasopressin systems in genetic syndromes and neurodevelopmental disorders (2014) · cites this paper as Pretorius et al., 1998
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Oxytocin and vasopressin systems in genetic syndromes and neurodevelopmental disorders
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- Authors
- Pretorius, P. H., King, M. A., Pan, T.-S., Vries, D. J. D., Glick, S. J., & Byrne, C. L.
- Affiliations
- University of Massachusetts Chan Medical School (US)
- University of Massachusetts Lowell (US)
- ORCID
- Venue
- Physics in Medicine and Biology
- Publisher
- IOP Publishing
- Published
- 1998-02-01
- Volume
- 43
- Issue
- 2
- Pages
- 407-420
- ISSN
- 0031-9155 (ISSN-L)
- 1361-6560
- OpenAlex
- W2108626141
- Cited by
- 72
- References
- 37
- Citations by year
- 2026: 1 · 2025: 3 · 2023: 2 · 2022: 1 · 2021: 1 · 2020: 1 · 2019: 1 · 2016: 3 · 2015: 3 · 2014: 2 · 2012: 5
- FWCI
- 2.27
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Physics in Medicine and Biology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (2r01ca042165-12)
- National Heart, Lung, and Blood Institute (R01HL050349, HL-50349)
- National Cancer Institute (CA-42165)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Medical Imaging Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Cardiac Imaging and Diagnostics
- Physical Sciences › Engineering › Biomedical Engineering › Advanced X-ray and CT Imaging
- Keywords
- partial volume effect, iterative reconstruction, maximum likelihood expectation maximization, filtered backprojection, Wiener filter, background activity
- MeSH terms
- Humans, Image Processing, Computer-Assisted, Models, Theoretical, Tomography, Emission-Computed, Single-Photon, Likelihood Functions, Phantoms, Imaging
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