Retrospective data-driven respiratory gating for PET/CT

2009 ◽  
Vol 54 (7) ◽  
pp. 1935-1950 ◽  
Author(s):  
Paul J Schleyer ◽  
Michael J O'Doherty ◽  
Sally F Barrington ◽  
Paul K Marsden
2020 ◽  
Vol 61 (11) ◽  
pp. 1678-1683 ◽  
Author(s):  
Matthew D. Walker ◽  
Andrew J. Morgan ◽  
Kevin M. Bradley ◽  
Daniel R. McGowan

2021 ◽  
Vol 77 (11) ◽  
pp. 1356-1365
Author(s):  
Kenta Miwa ◽  
Noriaki Miyaji ◽  
Kosuke Yamashita ◽  
Tensho Yamao ◽  
Yuto Kamitaka

2021 ◽  
pp. 20201350
Author(s):  
Michael Messerli ◽  
Virginia Liberini ◽  
Hannes Grünig ◽  
Alexander Maurer ◽  
Stephan Skawran ◽  
...  

Objectives: To evaluate the impact of fully automatic motion correction by data-driven respiratory gating (DDG) on positron emission tomography (PET) image quality, lesion detection and patient management. Materials and Methods: A total of 149 patients undergoing PET/CT for cancer (re-)staging were retrospectively included. Patients underwent a PET/CT on a digital detector scanner and for every patient a PET data set where DDG was enabled (PETDDG) and as well as where DDG was not enabled (PETnonDDG) was reconstructed. All PET data sets were evaluated by two readers which rated the general image quality, motion effects and organ contours. Further, both readers reviewed all scans on a case-by-case basis and evaluated the impact of PETDDG on additional apparent lesion, change of report, and change of management. Results: In 85% (n = 126) of the patients, at least one bed position was acquired using DDG, resulting in mean scan time increase of 4:37 min per patient in the whole study cohort (n = 149). General image quality was not rated differently for PETnonDDG and PETDDG images (p = 1.000) while motion effects (i.e. indicating general blurring) was rated significantly lower in PETDDG images and organ contours, including liver and spleen, were rated significantly sharper using PETDDG as compared to PETnonDDG (all p < 0.001). In 27% of patients, PETDDG resulted in a change of the report and in a total of 12 cases (8%), PETDDG resulted in a change of further clinical management. Conclusion: Deviceless DDG provided reliable fully automatic motion correction in clinical routine and increased lesion detectability and changed management in a considerable number of patients. Advances in knowledge: DDG enables PET/CT with respiratory gating to be used routinely in clinical practice without external gating equipment needed.


2021 ◽  
Vol 35 (3) ◽  
pp. 328-337
Author(s):  
Seo Young Kang ◽  
Byung Seok Moon ◽  
Hye Ok Kim ◽  
Hai-Jeon Yoon ◽  
Bom Sahn Kim

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jonathan Sigfridsson ◽  
Elin Lindström ◽  
Victor Iyer ◽  
Maria Holstensson ◽  
Irina Velikyan ◽  
...  

Abstract Aim The aim of this prospective study was to evaluate a data-driven gating software’s performance, in terms of identifying the respiratory signal, comparing [68Ga]Ga-DOTATOC and [18F]FDG examinations. In addition, for the [68Ga]Ga-DOTATOC examinations, tracer uptake quantitation and liver lesion detectability were assessed. Methods Twenty-four patients with confirmed or suspected neuroendocrine tumours underwent whole-body [68Ga]Ga-DOTATOC PET/CT examinations. Prospective DDG was applied on all bed positions and respiratory motion correction was triggered automatically when the detected respiratory signal exceeded a certain threshold (R value ≥ 15), at which point the scan time for that bed position was doubled. These bed positions were reconstructed with quiescent period gating (QPG), retaining 50% of the total coincidences. A respiratory signal evaluation regarding the software’s efficacy in detecting respiratory motion for [68Ga]Ga-DOTATOC was conducted and compared to [18F]FDG data. Measurements of SUVmax, SUVmean, and tumour volume were performed on [68Ga]Ga-DOTATOC PET and compared between gated and non-gated images. Results The threshold of R ≥ 15 was exceeded and gating triggered on mean 2.1 bed positions per examination for [68Ga]Ga-DOTATOC as compared to 1.4 for [18F]FDG. In total, 34 tumours were evaluated in a quantitative analysis. An increase of 25.3% and 28.1%, respectively, for SUVmax (P < 0.0001) and SUVmean (P < 0.0001), and decrease of 21.1% in tumour volume (P < 0.0001) was found when DDG was applied. Conclusions High respiratory signal was exclusively detected in bed positions where respiratory motion was expected, indicating reliable performance of the DDG software on [68Ga]Ga-DOTATOC PET/CT. DDG yielded significantly higher SUVmax and SUVmean values and smaller tumour volumes, as compared to non-gated images.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Virginia Liberini ◽  
Fotis Kotasidis ◽  
Valerie Treyer ◽  
Michael Messerli ◽  
Erika Orita ◽  
...  

AbstractTo evaluate whether quantitative PET parameters of motion-corrected 68Ga-DOTATATE PET/CT can differentiate between intrapancreatic accessory spleens (IPAS) and pancreatic neuroendocrine tumor (pNET). A total of 498 consecutive patients with neuroendocrine tumors (NET) who underwent 68Ga-DOTATATE PET/CT between March 2017 and July 2019 were retrospectively analyzed. Subjects with accessory spleens (n = 43, thereof 7 IPAS) and pNET (n = 9) were included, resulting in a total of 45 scans. PET images were reconstructed using ordered-subsets expectation maximization (OSEM) and a fully convergent iterative image reconstruction algorithm with β-values of 1000 (BSREM1000). A data-driven gating (DDG) technique (MOTIONFREE, GE Healthcare) was applied to extract respiratory triggers and use them for PET motion correction within both reconstructions. PET parameters among different samples were compared using non-parametric tests. Receiver operating characteristics (ROC) analyzed the ability of PET parameters to differentiate IPAS and pNETs. SUVmax was able to distinguish pNET from accessory spleens and IPAs in BSREM1000 reconstructions (p < 0.05). This result was more reliable using DDG-based motion correction (p < 0.003) and was achieved in both OSEM and BSREM1000 reconstructions. For differentiating accessory spleens and pNETs with specificity 100%, the ROC analysis yielded an AUC of 0.742 (sensitivity 56%)/0.765 (sensitivity 56%)/0.846 (sensitivity 62%)/0.840 (sensitivity 63%) for SUVmax 36.7/41.9/36.9/41.7 in OSEM/BSREM1000/OSEM + DDG/BSREM1000 + DDG, respectively. BSREM1000 + DDG can accurately differentiate pNET from accessory spleen. Both BSREM1000 and DDG lead to a significant SUV increase compared to OSEM and non-motion-corrected data.


Author(s):  
Bruno Madore ◽  
Gabriela Belsley ◽  
Cheng-Chieh Cheng ◽  
Frank Preiswerk ◽  
Marie Foley Kijewski ◽  
...  

Abstract Breathing motion can displace internal organs by up to several cm; as such, it is a primary factor limiting image quality in medical imaging. Motion can also complicate matters when trying to fuse images from different modalities, acquired at different locations and/or on different days. Currently available devices for monitoring breathing motion often do so indirectly, by detecting changes in the outline of the torso rather than the internal motion itself, and these devices are often fixed to floors, ceilings or walls, and thus cannot accompany patients from one location to another. We have developed small ultrasound-based sensors, referred to as ‘organ configuration motion’ (OCM) sensors, that attach to the skin and provide rich motion-sensitive information. In the present work we tested the ability of OCM sensors to enable respiratory gating during in vivo PET imaging. A motion phantom involving an FDG solution was assembled, and two cancer patients scheduled for a clinical PET/CT exam were recruited for this study. OCM signals were used to help reconstruct phantom and in vivo data into time series of motion-resolved images. As expected, the motion-resolved images captured the underlying motion. In Patient #1, a single large lesion proved to be mostly stationary through the breathing cycle. However, in Patient #2, several small lesions were mobile during breathing, and our proposed new approach captured their breathing-related displacements. In summary, a relatively inexpensive hardware solution was developed here for respiration monitoring. Because the proposed sensors attach to the skin, as opposed to walls or ceilings, they can accompany patients from one procedure to the next, potentially allowing data gathered in different places and at different times to be combined and compared in ways that account for breathing motion.


2009 ◽  
Vol 23 (2) ◽  
pp. 191-196 ◽  
Author(s):  
Andrea Lupi ◽  
Marta Zaroccolo ◽  
Matteo Salgarello ◽  
Veronica Malfatti ◽  
Pierluigi Zanco

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