1
|
Schultz J, Siekkinen R, Tadi MJ, Teräs M, Klén R, Lehtonen E, Saraste A, Teuho J. Effect of respiratory motion correction and CT-based attenuation correction on dual-gated cardiac PET image quality and quantification. J Nucl Cardiol 2022; 29:2423-2433. [PMID: 34476780 PMCID: PMC9553777 DOI: 10.1007/s12350-021-02769-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 07/10/2021] [Indexed: 11/21/2022]
Abstract
BACKGROUND Dual-gating reduces respiratory and cardiac motion effects but increases noise. With motion correction, motion is minimized and image quality preserved. We applied motion correction to create end-diastolic respiratory motion corrected images from dual-gated images. METHODS [18F]-fluorodeoxyglucose ([18F]-FDG) PET images of 13 subjects were reconstructed with 4 methods: non-gated, dual-gated, motion corrected, and motion corrected with 4D-CT (MoCo-4D). Image quality was evaluated using standardized uptake values, contrast ratio, signal-to-noise ratio, coefficient of variation, and contrast-to-noise ratio. Motion minimization was evaluated using myocardial wall thickness. RESULTS MoCo-4D showed improvement for contrast ratio (2.83 vs 2.76), signal-to-noise ratio (27.5 vs 20.3) and contrast-to-noise ratio (14.5 vs 11.1) compared to dual-gating. The uptake difference between MoCo-4D and non-gated images was non-significant (P > .05) for the myocardium (2.06 vs 2.15 g/mL), but significant (P < .05) for the blood pool (.80 vs .86 g/mL). Non-gated images had the lowest coefficient of variation (27.3%), with significant increase for all other methods (31.6-32.5%). MoCo-4D showed smallest myocardial wall thickness (16.6 mm) with significant decrease compared to non-gated images (20.9 mm). CONCLUSIONS End-diastolic respiratory motion correction and 4D-CT resulted in improved motion minimization and image quality over standard dual-gating.
Collapse
Affiliation(s)
- Jussi Schultz
- Turku PET Centre, Turku University Hospital, Kiinamyllynkatu 4-8, 20521, Turku, Finland
- Turku PET Centre, University of Turku, Turku, Finland
| | - Reetta Siekkinen
- Turku PET Centre, Turku University Hospital, Kiinamyllynkatu 4-8, 20521, Turku, Finland
- Turku PET Centre, University of Turku, Turku, Finland
- Department of Medical Physics, Turku University Hospital, Turku, Finland
- Department of Computing, University of Turku, Turku, Finland
| | - Mojtaba Jafari Tadi
- Department of Computing, University of Turku, Turku, Finland
- School of ICT, Turku University of Applied Sciences, Turku, Finland
| | - Mika Teräs
- Department of Medical Physics, Turku University Hospital, Turku, Finland
- Department of Biomedicine, University of Turku, Turku, Finland
| | - Riku Klén
- Turku PET Centre, University of Turku, Turku, Finland
| | - Eero Lehtonen
- Department of Computing, University of Turku, Turku, Finland
| | - Antti Saraste
- Turku PET Centre, Turku University Hospital, Kiinamyllynkatu 4-8, 20521, Turku, Finland
- Turku PET Centre, University of Turku, Turku, Finland
- Heart Centre, Turku University Hospital, Turku, Finland
| | - Jarmo Teuho
- Turku PET Centre, Turku University Hospital, Kiinamyllynkatu 4-8, 20521, Turku, Finland.
- Turku PET Centre, University of Turku, Turku, Finland.
| |
Collapse
|
2
|
Radiomics model of dual-time 2-[ 18F]FDG PET/CT imaging to distinguish between pancreatic ductal adenocarcinoma and autoimmune pancreatitis. Eur Radiol 2021; 31:6983-6991. [PMID: 33677645 DOI: 10.1007/s00330-021-07778-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Revised: 01/19/2021] [Accepted: 02/11/2021] [Indexed: 12/24/2022]
Abstract
OBJECTIVES Pancreatic ductal adenocarcinoma (PDAC) and autoimmune pancreatitis (AIP) are diseases with a highly analogous visual presentation that are difficult to distinguish by imaging. The purpose of this research was to create a radiomics-based prediction model using dual-time PET/CT imaging for the noninvasive classification of PDAC and AIP lesions. METHODS This retrospective study was performed on 112 patients (48 patients with AIP and 64 patients with PDAC). All cases were confirmed by imaging and clinical follow-up, and/or pathology. A total of 502 radiomics features were extracted from the dual-time PET/CT images to develop a radiomics decision model. An additional 12 maximum intensity projection (MIP) features were also calculated to further improve the radiomics model. The optimal radiomics feature set was selected by support vector machine recursive feature elimination (SVM-RFE), and the final classifier was built using a linear SVM. The performance of the proposed dual-time model was evaluated using nested cross-validation for accuracy, sensitivity, specificity, and area under the curve (AUC). RESULTS The final prediction model was developed from a combination of the SVM-RFE and linear SVM with the required quantitative features. The multimodal and multidimensional features performed well for classification (average AUC: 0.9668, accuracy: 89.91%, sensitivity: 85.31%, specificity: 96.04%). CONCLUSIONS The radiomics model based on 2-[18F]fluoro-2-deoxy-D-glucose (2-[18F]FDG) PET/CT dual-time images provided promising performance for discriminating between patients with benign AIP and malignant PDAC lesions, which shows its potential for use as a diagnostic tool for clinical decision-making. KEY POINTS • The clinical symptoms and imaging visual presentations of PDAC and AIP are highly similar, and accurate differentiation of PDAC and AIP lesions is difficult. • Radiomics features provided a potential noninvasive method for differentiation of AIP from PDAC. • The diagnostic performance of the proposed radiomics model indicates its potential to assist doctors in making treatment decisions.
Collapse
|
3
|
Manwell S, Klein R, Xu T, deKemp RA. Clinical comparison of the positron emission tracking (PeTrack) algorithm with the real-time position management system for respiratory gating in cardiac positron emission tomography. Med Phys 2020; 47:1713-1726. [PMID: 31990986 DOI: 10.1002/mp.14052] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Revised: 01/09/2020] [Accepted: 01/20/2020] [Indexed: 11/11/2022] Open
Abstract
PURPOSE A data-driven motion tracking system was developed for respiratory gating in positron emission tomography (PET)/computed tomography (CT) studies. The positron emission tracking system (PeTrack) estimates the position of a low-activity fiducial marker placed on the patient during imaging. The aim of this study was to compare the performance of PeTrack against that of the real-time position management (RPM) system as applied to respiratory gating in cardiac PET/CT studies. METHODS The list-mode data of 35 patients that were referred for 82 Rb myocardial perfusion studies were retrospectively processed with PeTrack to generate respiratory motion signals and triggers. Fifty acquisitions from the initial cohort, conducted under physiologic rest and stress, were considered for analysis. Respiratory-gated reconstructions were performed using reconstruction software provided by the vendor. The respiratory signals and triggers of the gating systems were compared using quantitative measurements of the respiratory signal correlation, median, and interquartiles range (IQR) of observed respiratory rates and the relative frequencies of respiratory cycle outliers. Quantitative measurements of left-ventricular wall thicknesses and motion due to respiration were also compared. Real-time position management signals were also retrospectively processed using the trigger detection method of PeTrack for a third comparator ("RPMretro") that allowed direct comparison of the motion tracking quality independently of differences in the trigger detection methods. The comparison of PeTrack to the original RPM data represent a practical comparison of the two systems, whereas that of PeTrack and RPMretro represents an equal comparison of the two. Nongated images were also reconstructed to provide reference left-ventricular wall thicknesses. LV wall thickness and motion measurements were repeated for a subset of cases with motion ≥7 mm as image artifacts were expected to be more severe in these cases. RESULTS A significant correlation (P < 0.05) was observed between the RPM and PeTrack respiratory signals in 45/50 acquisitions; the mean correlation coefficient was 0.43. Similar results were found between PeTrack and RPMretro. No significant difference was observed between the RPM and PeTrack with respect to median respiratory rates and the percentage of respiratory cycles outliers. Respiratory rate variability (IQR) was significantly higher with PeTrack vs RPM (P = 0.002) and RPMretro (P = 0.04). Both PeTrack and RPM had a significant increase in the percentage of respiratory rate outliers compared to RPMretro (P < 0.001 and P = 0.001, respectively). All methods indicated significant differences in LV thickness compared to nongated images (P < 0.02). LV thickness was significantly larger for PeTrack compared to RPMretro in the highest motion subset (P = 0.009). Images gated with RPMretro showed significant increases in motion compared to both PeTrack (P < 0.001) and prospective RPM (P = 0.002). In the subset of highest motion cases, the difference between RPM and RPMretro was no longer present. CONCLUSIONS The data-driven PeTrack algorithm performed similarly to the well-established RPM system for respiratory gating of 82 Rb cardiac perfusion PET/CT studies. Real-time position management performance improved after retrospective processing and led to enhanced performance compared to both PeTrack and prospective RPM. With further development PeTrack has the potential to reduce the need for ancillary hardware systems to monitor respiratory motion.
Collapse
Affiliation(s)
- Spencer Manwell
- Department of Physics, Carleton University, Ottawa, Ontario, K1S 5B6, Canada.,National Cardiac PET Centre, University of Ottawa Heart Institute, Ottawa, Ontario, K1Y 4W7, Canada
| | - Ran Klein
- Department of Nuclear Medicine, The Ottawa Hospital, Ottawa, Ontario, K1H 8L6, Canada.,Division of Nuclear Medicine, University of Ottawa, Ottawa, Ontario, K1N 6N5, Canada
| | - Tong Xu
- Department of Physics, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
| | - Robert A deKemp
- National Cardiac PET Centre, University of Ottawa Heart Institute, Ottawa, Ontario, K1Y 4W7, Canada
| |
Collapse
|
4
|
Büther F, Jones J, Seifert R, Stegger L, Schleyer P, Schäfers M. Clinical Evaluation of a Data-Driven Respiratory Gating Algorithm for Whole-Body PET with Continuous Bed Motion. J Nucl Med 2020; 61:1520-1527. [PMID: 32060218 DOI: 10.2967/jnumed.119.235770] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2019] [Accepted: 01/30/2020] [Indexed: 12/13/2022] Open
Abstract
Respiratory gating is the standard to prevent respiration effects from degrading image quality in PET. Data-driven gating (DDG) using signals derived from PET raw data is a promising alternative to gating approaches requiring additional hardware (e.g., pressure-sensitive belt gating [BG]). However, continuous-bed-motion (CBM) scans require dedicated DDG approaches for axially extended PET, compared with DDG for conventional step-and-shoot scans. In this study, a CBM-capable DDG algorithm was investigated in a clinical cohort and compared with BG using optimally gated (OG) and fully motion-corrected (elastic motion correction [EMOCO]) reconstructions. Methods: Fifty-six patients with suspected malignancies in the thorax or abdomen underwent whole-body 18F-FDG CBM PET/CT using DDG and BG. Correlation analyses were performed on both gating signals. Besides static reconstructions, OG and EMOCO reconstructions were used for BG and DDG. The metabolic volume, SUVmax, and SUVmean of lesions were compared among the reconstructions. Additionally, the quality of lesion delineation in the different PET reconstructions was independently evaluated by 3 experts. Results: The global correlation coefficient between BG and DDG signals was 0.48 ± 0.11, peaking at 0.89 ± 0.07 when scanning the kidney and liver region. In total, 196 lesions were analyzed. SUV measurements were significantly higher in BG-OG, DDG-OG, BG-EMOCO, and DDG-EMOCO than in static images (P < 0.001; median SUVmax: static, 14.3 ± 13.4; BG-EMOCO, 19.8 ± 15.7; DDG-EMOCO, 20.5 ± 15.6; BG-OG, 19.6 ± 17.1; and DDG-OG, 18.9 ± 16.6). No significant differences between BG-OG and DDG-OG or between BG-EMOCO and DDG-EMOCO were found. Visual lesion delineation was significantly better in BG-EMOCO and DDG-EMOCO than in static reconstructions (P < 0.001); no significant difference was found when comparing BG and DDG for either EMOCO or OG reconstruction. Conclusion: DDG-based motion compensation of CBM PET acquisitions outperforms static reconstructions, delivering qualities comparable to BG approaches. The new algorithm may be a valuable alternative for CBM PET systems.
Collapse
Affiliation(s)
- Florian Büther
- Department of Nuclear Medicine, University Hospital Münster, Münster, Germany
| | | | - Robert Seifert
- Department of Nuclear Medicine, University Hospital Münster, Münster, Germany
| | - Lars Stegger
- Department of Nuclear Medicine, University Hospital Münster, Münster, Germany
| | | | - Michael Schäfers
- Department of Nuclear Medicine, University Hospital Münster, Münster, Germany.,European Institute for Molecular Imaging, University of Münster, Münster, Germany
| |
Collapse
|
5
|
AlJaroudi WA, Hage FG. Review of cardiovascular imaging in the Journal of Nuclear Cardiology 2018. Part 1 of 2: Positron emission tomography, computed tomography, and magnetic resonance. J Nucl Cardiol 2019; 26:524-535. [PMID: 30603892 DOI: 10.1007/s12350-018-01558-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2018] [Accepted: 11/28/2018] [Indexed: 12/26/2022]
Abstract
In this review, we summarize key articles that have been published in the Journal of Nuclear Cardiology in 2018 pertaining to nuclear cardiology with advanced multi-modality and hybrid imaging including positron emission tomography, cardiac-computed tomography, and magnetic resonance. In an upcoming review, we will summarize key articles that relate to the progress made in the field of single-photon emission computed tomography. We hope that these sister reviews will be useful to the reader to navigate the literature in our field.
Collapse
Affiliation(s)
- Wael A AlJaroudi
- Division of Cardiovascular Medicine, Clemenceau Medical Center, Beirut, Lebanon
| | - Fadi G Hage
- Division of Cardiovascular Disease, Department of Medicine, University of Alabama at Birmingham, 306 Lyons-Harrison Research Building, 701 19th Street South, Birmingham, AL, 35294-0007, USA.
- Section of Cardiology, Birmingham Veterans Affairs Medical Center, Birmingham, AL, USA.
| |
Collapse
|