| Title |
Correcting for respiratory motion in liver PET/MRI: preliminary evaluation of the utility of bellows and navigated hepatobiliary phase imaging
|
|---|---|
| Published in |
EJNMMI Physics, September 2015
|
| DOI | 10.1186/s40658-015-0125-0 |
| Pubmed ID | |
| Authors |
Thomas A. Hope, Emily F. Verdin, Emily K. Bergsland, Michael A. Ohliger, Carlos U. Corvera, Eric K. Nakakura |
| Abstract |
The purpose of this study was to evaluate the utility of bellows-based respiratory compensation and navigated hepatobiliary phase imaging to correct for respiratory motion in the setting of dedicated liver PET/MRI. Institutional review board approval and informed consent were obtained. Six patients with metastatic neuroendocrine tumor were imaged using Ga-68 DOTA-TOC PET/MRI. Whole body imaging and a dedicated 15-min liver PET acquisition was performed, in addition to navigated and breath-held hepatobiliary phase (HBP) MRI. Liver PET data was reconstructed three ways: the entire data set (liver PET), gated using respiratory bellows (RC-liver PET), and a non-gated data set reconstructed using the same amount of data used in the RC-liver PET (shortened liver PET). Liver lesions were evaluated using SUVmax, SUVpeak, SUVmean, and Volisocontour. Additionally, the displacement of each lesion between the RC-liver PET images and the navigated and breath-held HBP images was calculated. Respiratory compensation resulted in a 43 % increase in SUVs compared to ungated data (liver vs RC-liver PET SUVmax 26.0 vs 37.3, p < 0.001) and a 25 % increase compared to a non-gated reconstruction using the same amount of data (RC-liver vs shortened liver PET SUVmax 26.0 vs 32.6, p < 0.001). Lesion displacement was minimized using navigated HBP MRI (1.3 ± 1.0 mm) compared to breath-held HBP MRI (23.3 ± 1.0 mm). Respiratory bellows can provide accurate respiratory compensation when imaging liver lesions using PET/MRI, and results in increased SUVs due to a combination of increased image noise and reduced respiratory blurring. Additionally, navigated HBP MRI accurately aligns with respiratory compensated PET data. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 31 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 26% |
| Other | 5 | 16% |
| Student > Ph. D. Student | 5 | 16% |
| Student > Master | 4 | 13% |
| Lecturer | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 7 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Physics and Astronomy | 7 | 23% |
| Medicine and Dentistry | 6 | 19% |
| Engineering | 4 | 13% |
| Agricultural and Biological Sciences | 2 | 6% |
| Neuroscience | 2 | 6% |
| Other | 2 | 6% |
| Unknown | 8 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 October 2015.
All research outputs
#15,349,419
of 22,831,537 outputs
Outputs from EJNMMI Physics
#76
of 181 outputs
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#159,676
of 272,846 outputs
Outputs of similar age from EJNMMI Physics
#2
of 4 outputs
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