Clinical Impact of Cardiac-Gated PET Imaging

Value of PET ECG gating in a cross-validation study of cardiac function assessment by PET/MR imaging

BACKGROUND

This work investigated the impact of different cardiac gating methods on the assessment of cardiac function by FDG-PET in a cross-validation PET/MR study.

METHODS AND RESULTS

MR- and PET-based left ventricular end-diastolic, end-systolic volumes, and ejection fraction (EDV, ESV, and EF) were delineated in 30 patients with a PET/MR examination. Cardiac PET imaging was performed using three ECG gating methods: fixed number of gates per beat (STD), STD with a beat acceptance window (STD-BR), and fixed gate duration (FW). High MR-PET correlations were found in all the values. ESVs correlated better than EDVs and EFs: Pearson's r coefficient [0.92, 0.92, 0.92] in ESV vs [0.75, 0.81, 0.80] in EDV and [0.79, 0.91, 0.87] in EF, for each method [STD, STD-BR, FW]. Biases with respect to MRI for all the evaluated PET methods were less than 13% in EDV, 5% in ESV, and 14% in EF, but with wide limits of agreements, in the range (59-68)% in EDV, (65-70)% in ESV, and (49-71)% in EF. STD showed the strongest disagreement, while there were no marked differences between STD-BR and FW.

CONCLUSION

Based on these findings, PET- and MR-based cardiac function parameters were highly correlated but in substantial disagreement with variabilities introduced by the selected PET ECG gating method. The most significant differences were associated with the ECG gating method susceptible to highly irregular beats, while similar performance was observed in the methods using uniform adjustment of gates width per beat with the beat acceptance window, and fixed gate width along all the beats. Thus, strict quality controls of R peak detection are needed to minimize its impact on the function assessment.

Clinical comparison of the positron emission tracking (PeTrack) algorithm with the real-time position management system for respiratory gating in cardiac positron emission tomography

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.

Gating Approaches in Cardiac PET Imaging

Cardiac PET provides high sensitivity and high negative predictive value in the diagnosis of coronary artery disease and cardiomyopathies. Cardiac, respiratory as well as bulk patient motion have detrimental effects on thoracic PET imaging, in particular on cardiovascular PET imaging where the motion can affect the PET images quantitatively as well as qualitatively. Gating can ameliorate the unfavorable impact of motion additionally enabling evaluation of left ventricular systolic function. In this article, the authors review the recent advances in gating approaches and highlight the advances in data-driven approaches, which hold promise in motion detection without the need for complex hardware setup.

Lesion quantification and detection in myocardial (18)F-FDG PET using edge-preserving priors and anatomical information from CT and MRI: a simulation study

Background

The limited spatial resolution of the clinical PET scanners results in image blurring and does not allow for accurate quantification of very thin or small structures (known as partial volume effect). In cardiac imaging, clinically relevant questions, e.g. to accurately define the extent or the residual metabolic activity of scarred myocardial tissue, could benefit from partial volume correction (PVC) techniques.

The use of high-resolution anatomical information for improved reconstruction of the PET datasets has been successfully applied in other anatomical regions. However, several concerns linked to the use of any kind of anatomical information for PVC on cardiac datasets arise. The moving nature of the heart, coupled with the possibly non-simultaneous acquisition of the anatomical and the activity datasets, is likely to introduce discrepancies between the PET and the anatomical image, that in turn might mislead lesion quantification and detection. Non-anatomical (edge-preserving) priors could represent a viable alternative for PVC in this case.

In this work, we investigate and compare the regularizing effect of different anatomical and non-anatomical priors applied during maximum-a-posteriori (MAP) reconstruction of cardiac PET datasets. The focus of this paper is on accurate quantification and lesion detection in myocardial ¹⁸F-FDG PET.

Methods

Simulated datasets, obtained with the XCAT software, are reconstructed with different algorithms and are quantitatively analysed.

Results

The results of this simulation study show a superiority of the anatomical prior when an ideal, perfectly matching anatomy is used. The anatomical information must clearly differentiate between normal and scarred myocardial tissue for the PVC to be successful. In case of mismatched or missing anatomical information, the quality of the anatomy-based MAP reconstructions decreases, affecting both overall image quality and lesion quantification. The edge-preserving priors produce reconstructions with good noise properties and recovery of activity, with the advantage of not relying on an external, additional scan for anatomy.

Conclusions

The performance of edge-preserving priors is acceptable but inferior to those of a well-applied anatomical prior that differentiates between lesion and normal tissue, in the detection and quantification of a lesion in the reconstructed images. When considering bull’s eye plots, all of the tested MAP algorithms produced comparable results.

Dynamic whole-body PET parametric imaging: I. Concept, acquisition protocol optimization and clinical application

Static whole-body PET/CT, employing the standardized uptake value (SUV), is considered the standard clinical approach to diagnosis and treatment response monitoring for a wide range of oncologic malignancies. Alternative PET protocols involving dynamic acquisition of temporal images have been implemented in the research setting, allowing quantification of tracer dynamics, an important capability for tumor characterization and treatment response monitoring. Nonetheless, dynamic protocols have been confined to single-bed-coverage limiting the axial field-of-view to ~15-20 cm, and have not been translated to the routine clinical context of whole-body PET imaging for the inspection of disseminated disease. Here, we pursue a transition to dynamic whole-body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed dynamic PET acquisition protocols and parametric imaging methods. We investigate solutions to address the challenges of: (i) long acquisitions, (ii) small number of dynamic frames per bed, and (iii) non-invasive quantification of kinetics in the plasma. In the present study, a novel dynamic (4D) whole-body PET acquisition protocol of ~45 min total length is presented, composed of (i) an initial 6 min dynamic PET scan (24 frames) over the heart, followed by (ii) a sequence of multi-pass multi-bed PET scans (six passes × seven bed positions, each scanned for 45 s). Standard Patlak linear graphical analysis modeling was employed, coupled with image-derived plasma input function measurements. Ordinary least squares Patlak estimation was used as the baseline regression method to quantify the physiological parameters of tracer uptake rate Ki and total blood distribution volume V on an individual voxel basis. Extensive Monte Carlo simulation studies, using a wide set of published kinetic FDG parameters and GATE and XCAT platforms, were conducted to optimize the acquisition protocol from a range of ten different clinically acceptable sampling schedules examined. The framework was also applied to six FDG PET patient studies, demonstrating clinical feasibility. Both simulated and clinical results indicated enhanced contrast-to-noise ratios (CNRs) for Ki images in tumor regions with notable background FDG concentration, such as the liver, where SUV performed relatively poorly. Overall, the proposed framework enables enhanced quantification of physiological parameters across the whole body. In addition, the total acquisition length can be reduced from 45 to ~35 min and still achieve improved or equivalent CNR compared to SUV, provided the true Ki contrast is sufficiently high. In the follow-up companion paper, a set of advanced linear regression schemes is presented to particularly address the presence of noise, and attempt to achieve a better trade-off between the mean-squared error and the CNR metrics, resulting in enhanced task-based imaging.