Impact of motion and partial volume effects correction on PET myocardial perfusion imaging using simultaneous PET-MR

Petibon, Yoann; Guehl, Nicolas J.; Reese, Timothy G.; Ebrahimi, Behzad; Normandin, Marc D.; Shoup, Timothy M.; Alpert, Nathaniel M.; Fakhri, Georges El; Ouyang, Jinsong

doi:10.1088/1361-6560/aa5087

Cited by 33 publications

(26 citation statements)

References 49 publications

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“…More advanced methods, that use the synergistic information derived from the simultaneous PET and MR data acquisition, have been proposed to estimate [198] and to correct for motion in both PET and MR images [189]. Other attempts focused on the implementation of joint MoCo and PVC approaches to further improve the PET quantification of small lesions in regions that are susceptible to motion [199,200].…”

Section: Motion Compensationmentioning

confidence: 99%

Hybrid Imaging: Instrumentation and Data Processing

et al. 2018

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State-of-the-art patient management frequently requires the use of non-invasive imaging methods to assess the anatomy, function or molecular-biological conditions of patients or study subjects. Such imaging methods can be singular, providing either anatomical or molecular information, or they can be combined, thus, providing "anato-metabolic" information. Hybrid imaging denotes image acquisitions on systems that physically combine complementary imaging modalities for an improved diagnostic accuracy and confidence as well as for increased patient comfort. The physical combination of formerly independent imaging modalities was driven by leading innovators in the field of clinical research and benefited from technological advances that permitted the operation of PET and MR in close physical proximity, for example. This review covers milestones of the development of various hybrid imaging systems for use in clinical practice and small-animal research. Special attention is given to technological advances that helped the adoption of hybrid imaging, as well as to introducing methodological concepts that benefit from the availability of complementary anatomical and biological information, such as new types of image reconstruction and data correction schemes. The ultimate goal of hybrid imaging is to provide useful, complementary and quantitative information during patient work-up. Hybrid imaging also opens the door to multi-parametric assessment of diseases, which will help us better understand the causes of various diseases that currently contribute to a large fraction of healthcare costs.

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Section: Motion Compensationmentioning

confidence: 99%

Hybrid Imaging: Instrumentation and Data Processing

et al. 2018

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“…Although MPI studies have been performed on PET-MR systems using relatively low injected activities (i.e. 400 MBq 15-oxygen [ 17 ], 214 MBq [ 13 N]NH 3 [ 18 ], 396 ± 26 MBq [ 13 N]NH 3 [ 19 ] and 259–296 MBq 18F-flurpiridaz [ 20 ]), there are as yet no detailed studies of the performance characteristics of these systems at count rates expected during MPI with traditional perfusion radiotracers. Use of these tracers introduces added considerations in PET-MRI imaging, as the field of view is typically larger and ring diameter typically smaller than traditional PET-CT systems.…”

Section: Introductionmentioning

confidence: 99%

The effect of high count rates on cardiac perfusion quantification in a simultaneous PET-MR system using a cardiac perfusion phantom

et al. 2017

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BackgroundPET-MRI is under investigation as a new strategy for quantitative myocardial perfusion imaging. Consideration is required as to the maximum scanner count rate in order to limit dead-time losses resulting from administered activity in the scanner field of view during the first pass of the radiotracer.ResultsWe performed a decaying-source experiment to investigate the high count-rate performance of a PET-MR system (Siemens mMR) over the expected range of activities during a clinical study. We also performed imaging of a cardiac perfusion phantom, which provides an experimental simulation of clinical transit of a simultaneous radiotracer (phantom injected activities range 252 to 997 MBq) and gadolinium-based contrast agent (GBCA). Time-activity and time-intensity curves of the aorta and myocardium compartments from PET and MR images were determined, and quantification of perfusion was then performed using a standard cardiac kinetic model. The decaying-source experiment showed a maximum noise equivalent count rate (NECRmax) of 286 kcps at a singles rate of 47.1 Mcps. NECR was maintained within 5% (NECR95%) of the NECRmax with a singles rate of 34.1 Mcps, corresponding to 310 MBq in the phantom. Count-rate performance was degraded above the singles rate of 64.9 Mcps due to the number of detection events impacting the quantitative accuracy of reconstructed images. A 10% bias in image activity concentration was observed between singles rates of 78.2 and 82.9 Mcps. Perfusion phantom experiments showed that image-based activity concentration and quantified values of perfusion were affected by count losses when the total singles rate was greater than 64.9 Mcps. This occurred during the peak arterial input function (AIF) phase of imaging for injected activities to the phantom of 600 MBq and greater.ConclusionsCare should be taken to avoid high count-rate losses in simultaneous PET-MRI studies. Based on our results in phantoms, bias in reconstructed images should be avoided by adhering to a singles rate lower than 64.9 Mcps on the mMR system. Quantification of perfusion values using singles rates higher than 64.9 Mcps on this system may be compromised and should be avoided.

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“…There are three types of motion, which include cardiac, respiratory, and body motion, associated with a cardiac PET scan. We and others have previously studied extensively how to correct for cardiac and respiratory motion alone or together assuming no body motion . One future work is to correct for all types of motion together for cardiac PET.…”

Section: Discussionmentioning

confidence: 99%

“…Two different types of motion can affect cardiac PET imaging: physiologic motion (i.e., pseudo‐periodic motion due to cardiac and respiratory functions) and body motion (i.e., unpredictable changes in the patient’s body position). Cardiac and respiratory motion correction has recently attracted great attention in PET imaging . Methods designed to correct physiologic motion may become inaccurate if data are corrupted by body motion.…”

Section: Introductionmentioning

confidence: 99%

Body motion detection and correction in cardiac PET: Phantom and human studies

et al. 2019

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Purpose: Patient body motion during a cardiac positron emission tomography (PET) scan can severely degrade image quality. We propose and evaluate a novel method to detect, estimate, and correct body motion in cardiac PET. Methods: Our method consists of three key components: motion detection, motion estimation, and motion-compensated image reconstruction. For motion detection, we first divide PET list-mode data into 1-s bins and compute the center of mass (COM) of the coincidences' distribution in each bin. We then compute the covariance matrix within a 25-s sliding window over the COM signals inside the window. The sum of the eigenvalues of the covariance matrix is used to separate the list-mode data into "static" (i.e., body motion free) and "moving" (i.e. contaminated by body motion) frames. Each moving frame is further divided into a number of evenly spaced sub-frames (referred to as "sub-moving" frames), in which motion is assumed to be negligible. For motion estimation, we first reconstruct the data in each static and sub-moving frame using a rapid back-projection technique. We then select the longest static frame as the reference frame and estimate elastic motion transformations to the reference frame from all other static and sub-moving frames using nonrigid registration. For motion-compensated image reconstruction, we reconstruct all the list-mode data into a single image volume in the reference frame by incorporating the estimated motion transformations in the PET system matrix. We evaluated the performance of our approach in both phantom and human studies. Results: Visually, the motion-corrected (MC) PET images obtained using the proposed method have better quality and fewer motion artifacts than the images reconstructed without motion correction (NMC). Quantitative analysis indicates that MC yields higher myocardium to blood pool concentration ratios. MC also yields sharper myocardium than NMC. Conclusions: The proposed body motion correction method improves image quality of cardiac PET.

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Impact of motion and partial volume effects correction on PET myocardial perfusion imaging using simultaneous PET-MR

Cited by 33 publications

References 49 publications

Hybrid Imaging: Instrumentation and Data Processing

Hybrid Imaging: Instrumentation and Data Processing

The effect of high count rates on cardiac perfusion quantification in a simultaneous PET-MR system using a cardiac perfusion phantom

Body motion detection and correction in cardiac PET: Phantom and human studies

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