Blood pool and tissue phase patient motion effects on 82rubidium PET myocardial blood flow quantification

Lee, Benjamin C.; Moody, Jonathan B.; Poitrasson-Rivière, Alexis; Melvin, Amanda C.; Weinberg, Richard L.; Corbett, James R.; Ficaro, Edward P.; Murthy, Venkatesh L.

doi:10.1007/s12350-018-1256-1

Journal of Nuclear Cardiology

2019

DOI: 10.1007/s12350-018-1256-1

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Blood pool and tissue phase patient motion effects on 82rubidium PET myocardial blood flow quantification

Benjamin C. Lee

Jonathan B. Moody

Alexis Poitrasson-Rivière

et al.

Abstract: Patient motion was most prevalent in the blood phase and MBF and MFR errors increased most substantially with motion in the inferior direction. Motion correction focused on these motions is needed to reduce MBF and MFR errors.

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Cited by 38 publications

(54 citation statements)

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“…Substantial respiratory movement of the heart ([ 1 cm) occurs in more than 30% of SPECT MPI studies 13 and motion is known to be a potential source major errors in MBF. 14,15 Changes in breathing patterns during imaging can lead to shifts in the mean cardiac position and introduce errors in the position of the regions used to measure time-activity curves. Breathing, such as cardiac contraction, also reduces spatial resolution leading to an increase in the partial volume and spill-over effects.…”

mentioning

confidence: 99%

Dynamic phantoms: Making the right tool for the job

Wells

Klein

2021

Journal of Nuclear Cardiology

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Myocardial blood flow (MBF) measurement has been shown to add incremental value in the diagnosis and prognosis of patients with coronary artery disease. New cardiac cameras make dynamic imaging possible with SPECT and there has been substantial interest in SPECT MBF. As with any new clinical test, a need exists to validate its results, characterize its limitations, and benchmark its performance with evolving methodology. As a test moves into clinical implementation there is a further need to ensure the quality, both of the camera performance in the acquisition of the data and of the processing of that data. Meeting these needs can be readily achieved if there exists a well-controlled reference truth that realistically emulates the inputs to the test.For conventional gamma cameras, there already exist standards for assuring camera performance with respect to static imaging, 1 but many of these tests are not applicable to the new cardiac SPECT camera designs. In addition, as we move into dynamic imaging, there are even less standards available to test and assure accurate performance. From work with PET, we know that camera technical factors such as deadtime corrections 2 and type of reconstruction 3 can influence the values measured for MBF. Therefore, we need to develop new standards for characterizing camera performance, to understand how camera performance influences MBF measurement and to ensure accurate camera performance over its useful life. The ideal test will efficiently test the performance of the complete system, not just select components, by simulating its input and validating the final result.When asking questions about the capability of the design of a system, computer simulations can be extremely valuable. Complex anthropomorphic computer phantoms (such as the XCAT phantom) 4 are available to simulate time-varying activity distributions in the patient, complete with respiratory motion, cardiac contraction and myocardial defects. Coupling these with an accurate model of the camera itself, Monte Carlo simulation (e.g. with GATE 5 or Simind) 6 can provide very realistic datasets for which the truth is well known. Computer simulations also have the advantage that with them we can alter reality-we can turn-off patient breathing, remove scatter or attenuation, increase the tracer extraction fraction-and examine each aspect of the problem and the effect it might have on the final measurement of MBF. However, despite the benefits of computer modeling and the wealth of information it might provide on the ideal performance of a system, it can only simulate what the operator designs into it and there is often an element of doubt that the simulation is accurately modeling all aspects of the problem, especially if complete knowledge of the system (i.e. camera hardware and software) is not known. In addition, and perhaps more importantly, computer simulations can tell us how well the camera design works but cannot tell us how well the camera in our department works.To assess your camera's performance, you need to...

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Dynamic phantoms: Making the right tool for the job

Wells

Klein

2021

Journal of Nuclear Cardiology

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“…The authors established a body motioncorrection framework for dynamic 82 Rb cardiac PET. With extension from their previous studies, 13,14 the current study addressed the needs of automated motion correction for the entire dynamic cardiac study, including both the late phase and the early blood pool phase with rapidly changing tracer kinetics. In this study, 225 patients underwent dynamic rest/stress 82 Rb PET imaging using a Siemens Biograph mCT PET/CT scanner, where pharmacological stress was performed with regadenoson.…”

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confidence: 99%

“…The investigators, without the ground truth, assumed good correlation in MBF/MFR with manual motion-correction results to be a measure of success. The strength of this premise relies on their previous studies, 13 based on the same 225 patients cohort, that manual motion correction was considered as the gold standard when it was performed by a clinician for every dynamic frame. In Ref.…”

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confidence: 99%

“…In Ref. 13, Lee et al found that translational body motion was most prevalent in the blood phase, resulting in the strongest impact on the right coronary artery region. Although only translational rigid motion was considered, the current work established an automated correction framework for cardiac dynamic PET especially including the blood pool phase, making it the only correction algorithm that applies to the entire dynamic sequence to the best of our knowledge.…”

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confidence: 99%

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Patient motion correction for dynamic cardiac PET: Current status and challenges

Liu

2020

Journal of Nuclear Cardiology

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For dynamic cardiac PET of quantifying myocardial blood flow (MBF), patient motion is a major factor that affects the ROI definition and absolute quantification accuracy. In a recent study, an 82 rubidium ( 82 Rb)-dynamic-tailored motion-correction framework has been proposed to address the voluntary body motion for all the dynamic frames, including both early and late phases. 1 This approach brings us one step closer to the practical and full motion correction for dynamic cardiac PET studies. In this editorial, we discussed the current status and limitations of motion-correction methods for dynamic cardiac PET, including the recent publication at JNC, and also pointed out the remaining challenges for future developments.PET myocardial perfusion imaging has been shown to improve the detection accuracy of coronary artery disease as compared to other non-invasive imaging modalities. 2 Many investigators, in the past two decades, have established methods for absolute quantification of MBF and myocardial flow reserve (MFR) 3 using dynamic PET, which is superior in diagnostic and prognostic value as compared to the conventional relative myocardial perfusion imaging. 4 A prerequisite of accurate quantification in dynamic PET requires appropriate corrections 5 to the original dynamic frame data. In additional to corrections for physical factors such as attenuation, scatter, randoms, and normalization, physiological factors such as patient motion also require correction. Patient motion in cardiac imaging typically includes respiratory motion, cardiac motion, and voluntary body motion. Such motions can cause inaccurate tracer distribution estimation, as well as artifacts introduced by the mismatch between PET and CT-based attenuation map. 6 Comparing to more periodic respiratory motion and cardiac motion, the timing for voluntary body motion is typically unpredictable, thus its impact on the MBF and MFR quantifications can be complicated. 7 Methods for respiratory motion 8 and cardiac motion management 9 have been proposed in the past. The body motion correction has also been studied for several PET applications, especially for brain studies. 10

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“…In this issue, Lee et al 12 join the growing number of publications focussed particularly on patient motion and its impact on the accuracy of MBF quantification. While motion correction of dynamic PET data is certainly not a novel concept, even in cardiac PET, 13 what Lee et al uniquely demonstrate is that the magnitude of motion varies significantly within the distinct physiological phases of tracer kinetics, i.e., the immediate vascular bloodpool phase and the later tissue uptake phase.…”

mentioning

confidence: 99%

A tale of two phases: Can the worst of scans become the best of scans with motion correction?

Armstrong

Memmott

2019

Journal of Nuclear Cardiology

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Blood pool and tissue phase patient motion effects on 82rubidium PET myocardial blood flow quantification

Abstract: Patient motion was most prevalent in the blood phase and MBF and MFR errors increased most substantially with motion in the inferior direction. Motion correction focused on these motions is needed to reduce MBF and MFR errors.

Cited by 38 publications

References 20 publications

Dynamic phantoms: Making the right tool for the job

Dynamic phantoms: Making the right tool for the job

Patient motion correction for dynamic cardiac PET: Current status and challenges

A tale of two phases: Can the worst of scans become the best of scans with motion correction?

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