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Abstract
PET/CT has become a preferred imaging modality over PET-only scanners in clinical practice. However, along with the significant improvement in diagnostic accuracy and patient throughput, pitfalls on PET/CT are reported as well. This review provides a general overview on the potential influence of the limitations with respect to PET/CT instrumentation and artifacts associated with the modality integration on the image appearance and quantitative accuracy of PET. Approaches proposed in literature to address the limitations or minimize the artifacts are discussed as well as their current challenges for clinical applications. Although the CT component can play an important role in assisting clinical diagnosis, we concentrate on the imaging scenarios where CT is used to provide auxiliary information for attenuation compensation and scatter correction in PET.
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Affiliation(s)
- Yu-Jung Tsai
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT
| | - Chi Liu
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT; Department of Biomedical Engineering, Yale University, New Haven, CT.
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Mannheim JG, Cheng JCK, Vafai N, Shahinfard E, English C, McKenzie J, Zhang J, Barlow L, Sossi V. Cross-validation study between the HRRT and the PET component of the SIGNA PET/MRI system with focus on neuroimaging. EJNMMI Phys 2021; 8:20. [PMID: 33635449 PMCID: PMC7910400 DOI: 10.1186/s40658-020-00349-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Accepted: 12/16/2020] [Indexed: 01/20/2023] Open
Abstract
Background The Siemens high-resolution research tomograph (HRRT - a dedicated brain PET scanner) is to this day one of the highest resolution PET scanners; thus, it can serve as useful benchmark when evaluating performance of newer scanners. Here, we report results from a cross-validation study between the HRRT and the whole-body GE SIGNA PET/MR focusing on brain imaging. Phantom data were acquired to determine recovery coefficients (RCs), % background variability (%BG), and image voxel noise (%). Cross-validation studies were performed with six healthy volunteers using [11C]DTBZ, [11C]raclopride, and [18F]FDG. Line profiles, regional time-activity curves, regional non-displaceable binding potentials (BPND) for [11C]DTBZ and [11C]raclopride scans, and radioactivity ratios for [18F]FDG scans were calculated and compared between the HRRT and the SIGNA PET/MR. Results Phantom data showed that the PET/MR images reconstructed with an ordered subset expectation maximization (OSEM) algorithm with time-of-flight (TOF) and TOF + point spread function (PSF) + filter revealed similar RCs for the hot spheres compared to those obtained on the HRRT reconstructed with an ordinary Poisson-OSEM algorithm with PSF and PSF + filter. The PET/MR TOF + PSF reconstruction revealed the highest RCs for all hot spheres. Image voxel noise of the PET/MR system was significantly lower. Line profiles revealed excellent spatial agreement between the two systems. BPND values revealed variability of less than 10% for the [11C]DTBZ scans and 19% for [11C]raclopride (based on one subject only). Mean [18F]FDG ratios to pons showed less than 12% differences. Conclusions These results demonstrated comparable performances of the two systems in terms of RCs with lower voxel-level noise (%) present in the PET/MR system. Comparison of in vivo human data confirmed the comparability of the two systems. The whole-body GE SIGNA PET/MR system is well suited for high-resolution brain imaging as no significant performance degradation was found compared to that of the reference standard HRRT.
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Affiliation(s)
- Julia G Mannheim
- Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada. .,Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard-Karls University Tuebingen, Tuebingen, Germany. .,Cluster of Excellence iFIT (EXC 2180) "Image Guided and Functionally Instructed Tumor Therapies", University of Tuebingen, Tuebingen, Germany.
| | - Ju-Chieh Kevin Cheng
- Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,Pacific Parkinson's Research Centre, University of British Columbia, Vancouver, British Columbia, Canada
| | - Nasim Vafai
- Pacific Parkinson's Research Centre, University of British Columbia, Vancouver, British Columbia, Canada
| | - Elham Shahinfard
- Pacific Parkinson's Research Centre, University of British Columbia, Vancouver, British Columbia, Canada
| | - Carolyn English
- Pacific Parkinson's Research Centre, University of British Columbia, Vancouver, British Columbia, Canada
| | - Jessamyn McKenzie
- Djavad Mowafaghian Centre for Brain Health, Pacific Parkinson's Research Centre, University of British Columbia & Vancouver Coastal Health, Vancouver, British Columbia, Canada
| | - Jing Zhang
- Global MR Applications & Workflow, GE Healthcare Canada, Vancouver, British Columbia, Canada
| | - Laura Barlow
- UBC MRI Research Centre, University of British Columbia, Vancouver, British Columbia, Canada
| | - Vesna Sossi
- Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada
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