Imaging of Myocardial αvß3 Integrin Expression for Evaluation of Myocardial Injury After Acute Myocardial Infarction.

[68Ga]Ga-NODAGA-Arg-Gly-Asp (RGD) is a PET tracer targeting αvß3 integrin, which is upregulated during angiogenesis soon after acute myocardial infarction (AMI). We prospectively evaluated determinants of myocardial uptake of [68Ga]Ga-NODAGA-RGD and its associations with left ventricular (LV) function in patients after AMI. Methods: Myocardial blood flow and [68Ga]Ga-NODAGA-RGD uptake (60 min after injection) were evaluated by PET in 31 patients 7.7 ± 3.8 d after primary percutaneous coronary intervention for ST-elevation AMI. Transthoracic echocardiography of LV function was performed on the day of PET and at the 6-mo follow-up. Results: PET images showed increased uptake of [68Ga]Ga-NODAGA-RGD in the ischemic area at risk (AAR), predominantly in injured myocardial segments. The SUV in the segment with the highest uptake (SUVmax) in the ischemic AAR was higher than the SUVmean of the remote myocardium (0.73 ± 0.16 vs. 0.51 ± 0.11, P < 0.001). Multivariable predictors of [68Ga]Ga-NODAGA-RGD uptake in the AAR included high peak N-terminal pro-B-type natriuretic peptide (P < 0.001), low LV ejection fraction, low global longitudinal strain (P = 0.01), and low longitudinal strain in the AAR (P = 0.01). [68Ga]Ga-NODAGA-RGD uptake corrected for myocardial blood flow and perfusable tissue fraction in the AAR predicted improvement in global longitudinal strain at follow-up (P = 0.002), independent of peak troponin, N-terminal pro-B-type natriuretic peptide, and LV ejection fraction. Conclusion: [68Ga]Ga-NODAGA-RGD uptake shows increased αvß3 integrin expression in the ischemic AAR early after AMI that is associated with regional and global systolic dysfunction, as well as increased LV filling pressure. Increased [68Ga]Ga-NODAGA-RGD uptake predicts improvement of global LV function 6 mo after AMI.

A retrospective evaluation of Bayesian-penalized likelihood reconstruction for [15O]H2O myocardial perfusion imaging.

BACKGROUND: New Block-Sequential-Regularized-Expectation-Maximization (BSREM) image reconstruction technique has been introduced for clinical use mainly for oncologic use. Accurate and quantitative image reconstruction is essential in myocardial perfusion imaging with positron emission tomography (PET) as it utilizes absolute quantitation of myocardial blood flow (MBF). The aim of the study was to evaluate BSREM reconstruction for quantitation in patients with suspected coronary artery disease (CAD). METHODS AND RESULTS: We analyzed cardiac [15O]H2O PET studies of 177 patients evaluated for CAD. Differences between BSREM and Ordered-Subset-Expectation-Maximization with Time-Of-Flight (TOF) and Point-Spread-Function (PSF) modeling (OSEM-TOF-PSF) in terms of MBF, perfusable tissue fraction, and vascular volume fraction were measured. Classification of ischemia was assessed between the algorithms. OSEM-TOF-PSF and BSREM provided similar global stress MBF in patients with ischemia (1.84 ± 0.21 g⋅ml-1⋅min-1 vs 1.86 ± 0.21 g⋅ml-1⋅min-1) and no ischemia (3.26 ± 0.34 g⋅ml-1⋅min-1 vs 3.28 ± 0.34 g⋅ml-1⋅min-1). Global resting MBF was also similar (0.97 ± 0.12 g⋅ml-1⋅min-1 and 1.12 ± 0.06 g⋅ml-1⋅min-1). The largest mean relative difference in MBF values was 7%. Presence of myocardial ischemia was classified concordantly in 99% of patients using OSEM-TOF-PSF and BSREM reconstructions CONCLUSION: OSEM-TOF-PSF and BSREM image reconstructions produce similar MBF values and diagnosis of myocardial ischemia in patients undergoing [15O]H2O PET due to suspected obstructive coronary artery disease.

Effect of respiratory motion correction and CT-based attenuation correction on dual-gated cardiac PET image quality and quantification.

BACKGROUND: Dual-gating reduces respiratory and cardiac motion effects but increases noise. With motion correction, motion is minimized and image quality preserved. We applied motion correction to create end-diastolic respiratory motion corrected images from dual-gated images. METHODS: [18F]-fluorodeoxyglucose ([18F]-FDG) PET images of 13 subjects were reconstructed with 4 methods: non-gated, dual-gated, motion corrected, and motion corrected with 4D-CT (MoCo-4D). Image quality was evaluated using standardized uptake values, contrast ratio, signal-to-noise ratio, coefficient of variation, and contrast-to-noise ratio. Motion minimization was evaluated using myocardial wall thickness. RESULTS: MoCo-4D showed improvement for contrast ratio (2.83 vs 2.76), signal-to-noise ratio (27.5 vs 20.3) and contrast-to-noise ratio (14.5 vs 11.1) compared to dual-gating. The uptake difference between MoCo-4D and non-gated images was non-significant (P > .05) for the myocardium (2.06 vs 2.15 g/mL), but significant (P < .05) for the blood pool (.80 vs .86 g/mL). Non-gated images had the lowest coefficient of variation (27.3%), with significant increase for all other methods (31.6-32.5%). MoCo-4D showed smallest myocardial wall thickness (16.6 mm) with significant decrease compared to non-gated images (20.9 mm). CONCLUSIONS: End-diastolic respiratory motion correction and 4D-CT resulted in improved motion minimization and image quality over standard dual-gating.

Assessment of a digital and an analog PET/CT system for accurate myocardial perfusion imaging with a flow phantom.

In Myocardial Perfusion Imaging (MPI) with Positron Emission Tomography/Computed Tomography (PET/CT) systems, accurate quantification is essential. We assessed flow quantification accuracy over various injected activities using a flow phantom. METHODS: The study was performed on the digital 4-ring Discovery MI (DMI-20) and analog Discovery 690 (D690) PET/CT systems, using 325-1257 MBq of [15O]H2O. PET performance and flow quantification accuracy were assessed in terms of count-rates, dead-time factors (DTF), scatter fractions (SF), time-activity curves (TACs), areas-under-the-curves (AUCs) and flow values. RESULTS: On DMI-20, prompts of 12.8 Mcps, DTF of 2.06 and SF of 46.1% were measured with 1257 MBq of activity. On the D690, prompts of 6.85 Mcps, DTF of 1.57 and SF of 32.5% were measured with 1230 MBq of activity. AUC values were linear over all activities. Mean wash-in flow error was - 9% for both systems whereas wash-out flow error was - 5% and - 6% for DMI-20 and D690. With the highest activity, wash-out flow error was - 12% and - 7% for the DMI-20 and D690. CONCLUSION: DMI-20 and D690 preserved accurate flow quantification over all injected activities, with maximum error of - 12%. In the future, flow quantification accuracy over the activities and count-rates evaluated in this study should be assessed.

A Respiratory Motion Estimation Method Based on Inertial Measurement Units for Gated Positron Emission Tomography.

We present a novel method for estimating respiratory motion using inertial measurement units (IMUs) based on microelectromechanical systems (MEMS) technology. As an application of the method we consider the amplitude gating of positron emission tomography (PET) imaging, and compare the method against a clinically used respiration motion estimation technique. The presented method can be used to detect respiratory cycles and estimate their lengths with state-of-the-art accuracy when compared to other IMU-based methods, and is the first based on commercial MEMS devices, which can estimate quantitatively both the magnitude and the phase of respiratory motion from the abdomen and chest regions. For the considered test group consisting of eight subjects with acute myocardial infarction, our method achieved the absolute breathing rate error per minute of 0.44 ± 0.23 1/min, and the absolute amplitude error of 0.24 ± 0.09 cm, when compared to the clinically used respiratory motion estimation technique. The presented method could be used to simplify the logistics related to respiratory motion estimation in PET imaging studies, and also to enable multi-position motion measurements for advanced organ motion estimation.

A Computational Framework for Data Fusion in MEMS-Based Cardiac and Respiratory Gating.

Dual cardiac and respiratory gating is a well-known technique for motion compensation in nuclear medicine imaging. In this study, we present a new data fusion framework for dual cardiac and respiratory gating based on multidimensional microelectromechanical (MEMS) motion sensors. Our approach aims at robust estimation of the chest vibrations, that is, high-frequency precordial vibrations and low-frequency respiratory movements for prospective gating in positron emission tomography (PET), computed tomography (CT), and radiotherapy. Our sensing modality in the context of this paper is a single dual sensor unit, including accelerometer and gyroscope sensors to measure chest movements in three different orientations. Since accelerometer- and gyroscope-derived respiration signals represent the inclination of the chest, they are similar in morphology and have the same units. Therefore, we use principal component analysis (PCA) to combine them into a single signal. In contrast to this, the accelerometer- and gyroscope-derived cardiac signals correspond to the translational and rotational motions of the chest, and have different waveform characteristics and units. To combine these signals, we use independent component analysis (ICA) in order to obtain the underlying cardiac motion. From this cardiac motion signal, we obtain the systolic and diastolic phases of cardiac cycles by using an adaptive multi-scale peak detector and a short-time autocorrelation function. Three groups of subjects, including healthy controls (n = 7), healthy volunteers (n = 12), and patients with a history of coronary artery disease (n = 19) were studied to establish a quantitative framework for assessing the performance of the presented work in prospective imaging applications. The results of this investigation showed a fairly strong positive correlation (average r = 0.73 to 0.87) between the MEMS-derived (including corresponding PCA fusion) respiration curves and the reference optical camera and respiration belt sensors. Additionally, the mean time offset of MEMS-driven triggers from camera-driven triggers was 0.23 to 0.3 ± 0.15 to 0.17 s. For each cardiac cycle, the feature of the MEMS signals indicating a systolic time interval was identified, and its relation to the total cardiac cycle length was also reported. The findings of this study suggest that the combination of chest angular velocity and accelerations using ICA and PCA can help to develop a robust dual cardiac and respiratory gating solution using only MEMS sensors. Therefore, the methods presented in this paper should help improve predictions of the cardiac and respiratory quiescent phases, particularly with the clinical patients. This study lays the groundwork for future research into clinical PET/CT imaging based on dual inertial sensors.