A preliminary evaluation of a high temporal resolution data-driven motion correction algorithm for rubidium-82 on a SiPM PET-CT system

Review of cardiovascular imaging in the Journal of Nuclear Cardiology 2022: positron emission tomography, computed tomography, and magnetic resonance

In 2022, the Journal of Nuclear Cardiology® published many excellent original research articles and editorials focusing on imaging in patients with cardiovascular disease. In this review of 2022, we summarize a selection of articles to provide a concise recap of major advancements in the field. In the first part of this 2-part series, we addressed publications pertaining to single-photon emission computed tomography. In this second part, we focus on positron emission tomography, cardiac computed tomography, and cardiac magnetic resonance. We specifically review advances in imaging of non-ischemic cardiomyopathy, cardio-oncology, infectious disease cardiac manifestations, atrial fibrillation, detection and prognostication of atherosclerosis, and technical improvements in the field. We hope that this review will be useful to readers as a reminder to articles they have seen during the year as well as ones they have missed.

Advances in Digital PET Technology and Its Potential Impact on Myocardial Perfusion and Blood Flow Quantification

PURPOSE OF REVIEW

In this review, we explore the development of digital PET scanners and describe the mechanism by which they work. We dive into some technical details on what differentiates a digital PET from a conventional PET scanner and how such differences lead to better imaging characteristics. Additionally, we summarize the available evidence on the improvements in the images acquired by digital PET as well as the remaining pitfalls. Finally, we report the comparative studies available on how digital PET compares to conventional PET, particularly in the quantification of coronary blood flow.

RECENT FINDINGS

The advent of digital PET offers high sensitivity and time-of-flight (TOF), which allow lower activity and scan times, with much less risk of detector saturation. This allows faster patient throughput, scanning more patients per generator, and acquiring more consistent image quality across patients. The higher sensitivity captures more of the potential artifacts, particularly motion-related ones, which presents a current challenge that still needs to be tackled. The digital silicon photomultiplier (SiPM) positron emission tomography (PET) machine has been an important development in the technological advancements of non-invasive nuclear cardiovascular imaging. It has enhanced the utility for PET myocardial perfusion imaging (MPI) and myocardial blood flow (MBF) quantification.

Change in positron emission tomography perfusion imaging quality with a data-driven motion correction algorithm

INTRODUCTION

Cardiac motion frequently reduces the interpretability of PET images. This study utilized a prototype data-driven motion correction (DDMC) algorithm to generate corrected images and compare DDMC images with non-corrected images (NMC) to evaluate image quality and change of perfusion defect size and severity.

METHODS

Rest and stress images with NMC and DDMC from 40 consecutive patients with motion were rated by 2 blinded investigators on a 4-point visual ordinal scale (0: minimal motion; 1: mild motion; 2: moderate motion; 3: severe motion/uninterpretable). Motion was also quantified using Dwell Fraction, which is the fraction of time the motion vector shows the heart to be within 6 mm of the corrected position and was derived from listmode data of NMC images.

RESULTS

Minimal motion was seen in 15% of patients, while 40%, 30%, and 15% of patients had mild moderate and severe motion, respectively. All corrected images showed an improvement in quality and were interpretable after processing. This was confirmed by a significant correlation (Spearman's correlation coefficient 0.626, P < .001) between machine measurement of motion quantification and physician interpretation.

CONCLUSION

The novel DDMC algorithm improved quality of cardiac PET images with motion. Correlation between machine measurement of motion quantification and physician interpretation was significant.

The prevalence of image degradation due to motion in rest-stress rubidium-82 imaging on a SiPM PET-CT system

BACKGROUND

Motion of the heart is known to affect image quality in cardiac PET. The prevalence of motion blurring in routine cardiac PET is not fully appreciated due to challenges identifying subtle motion artefacts. This study utilizes a recent prototype Data-Driven Motion Correction (DDMC) algorithm to generate corrected images that are compared with non-corrected images to identify visual differences in relative rubidium-82 perfusion images due to motion.

METHODS

300 stress and 300 rest static images were reconstructed with DDMC and without correction (NMC). The 600 DDMC/NMC image pairs were assigned Visual Difference Score (VDS). The number of non-diagnostic images were noted. A "Dwell Fraction" (DF) was derived from the data to quantify motion and predict image degradation.

RESULTS

Motion degradation (VDS = 1 or 2) was evident in 58% of stress images and 33% of rest images. Seven NMC images were non-diagnostic-these originated from six studies giving a 2% rate of non-diagnostic studies due to motion. The DF metric was able to effectively predict image degradation. The DDMC heart identification and tracking was successful in all images.

CONCLUSION

Motion degradation is present in almost half of all relative perfusion images. The DDMC algorithm is a robust tool for predicting, assessing and correcting image degradation.

Motion in nuclear cardiology imaging: types, artifacts, detection and correction techniques

In this paper, the authors review the field of motion detection and correction in nuclear cardiology with single photon emission computed tomography (SPECT) and positron emission tomography (PET) imaging systems. We start with a brief overview of nuclear cardiology applications and description of SPECT and PET imaging systems, then explaining the different types of motion and their related artefacts. Moreover, we classify and describe various techniques for motion detection and correction, discussing their potential advantages including reference to metrics and tasks, particularly towards improvements in image quality and diagnostic performance. In addition, we emphasize limitations encountered in different motion detection and correction methods that may challenge routine clinical applications and diagnostic performance.

Advances in PET-CT technology: An update

This article reviews the current evolution and future directions in PET-CT technology focusing on three areas: time of flight, image reconstruction, and data-driven gating. Image reconstruction is considered with advances in point spread function modelling, Bayesian penalised likelihood reconstruction, and artificial intelligence approaches. Data-driven gating is examined with reference to respiratory motion, cardiac motion, and head motion. For each of these technological advancements, theory will be briefly discussed, benefits of their use in routine practice will be detailed and potential future developments will be discussed. Representative clinical cases will be presented, demonstrating the huge opportunities given to the PET community by hardware and software advances in PET technology when it comes to lesion detection, disease characterization, accurate quantitation and quicker scans. Through this review, hospitals are encouraged to embrace, evaluate and appropriately implement the wide range of new PET technologies that are available now or in the near future, for the improvement of patient care.

Dynamic cardiac PET motion correction using 3D normalized gradient fields in patients and phantom simulations

This work expands on the implementation of three-dimensional (3D) normalized gradient fields to correct for whole-body motion and cardiac creep in [N-13]-ammonia patient studies and evaluates its accuracy using a dynamic phantom simulation model.

METHODS

A full rigid-body algorithm was developed using 3D normalized gradient fields including a multi-resolution step and sampling off the voxel grid to reduce interpolation artifacts. Optimization was performed using a weighted similarity metric that accounts for opposing gradients between images of blood pool and perfused tissue without the need for segmentation. Forty-three retrospective dynamic [N-13]-ammonia PET/CT rest/adenosine-stress patient studies were motion corrected and the mean motion parameters plotted at each frame time point. Motion correction accuracy was assessed using a comprehensive dynamic XCAT simulation incorporating published physiologic parameters of the heart's trajectory following adenosine infusion as well as corrupted attenuation correction commonly observed in clinical studies. Accuracy of the algorithm was assessed objectively by comparing the errors between isosurfaces and centers of mass of the motion corrected XCAT simulations.

RESULTS

In the patient studies, the overall mean cranial-to-caudal translation was 7 mm at stress over the duration of the adenosine infusion. Noninvasive clinical measures of relative flow reserve and myocardial flow reserve were highly correlated with their invasive analogues. Motion correction accuracy assessed with the XCAT simulations showed an error of <1 mm in late perfusion frames that broadened gradually to <3 mm in earlier frames containing blood pool.

CONCLUSION

This work demonstrates that patients undergoing [N-13]-ammonia dynamic PET/CT exhibit a large cranial-to-caudal translation related to cardiac creep primarily at stress and to a lesser extent at rest, which can be accurately corrected by optimizing their 3D normalized gradient fields. Our approach provides a solution to the challenging condition where the image intensity and its gradients are opposed without the need for segmentation and remains robust in the presence of PET-CT mismatch.