Review of cardiovascular imaging in the Journal of Nuclear Cardiology in 2017. Part 2 of 2: Myocardial perfusion imaging

Automatic reorientation to generate short-axis myocardial PET images

BACKGROUND

Accurately redirecting reconstructed Positron emission tomography (PET) images into short-axis (SA) images shows great significance for subsequent clinical diagnosis. We developed a system for automatic redirection and quantitative analysis of myocardial PET images.

METHODS

A total of 128 patients were enrolled for 18 F-FDG PET/CT myocardial metabolic images (MMIs), including 3 image classifications: without defects, with defects, and excess uptake. The automatic reorientation system includes five modules: regional division, myocardial segmentation, ellipsoid fitting, image rotation and quantitative analysis. First, the left ventricular geometry-based canny edge detection (LVG-CED) was developed and compared with the other 5 common region segmentation algorithms, the optimized partitioning was determined based on partition success rate. Then, 9 myocardial segmentation methods and 4 ellipsoid fitting methods were combined to derive 36 cross combinations for diagnostic performance in terms of Pearson correlation coefficient (PCC), Kendall correlation coefficient (KCC), Spearman correlation coefficient (SCC), and determination coefficient. Finally, the deflection angles were computed by ellipsoid fitting and the SA images were derived by affine transformation. Furthermore, the polar maps were used for quantitative analysis of SA images, and the redirection effects of 3 different image classifications were analyzed using correlation coefficients.

RESULTS

On the dataset, LVG-CED outperformed other methods in the regional division module with a 100% success rate. In 36 cross combinations, PSO-FCM and LLS-SVD performed the best in terms of correlation coefficient. The linear results indicate that our algorithm (LVG-CED, PSO-FCM, and LLS-SVD) has good consistency with the reference manual method. In quantitative analysis, the similarities between our method and the reference manual method were higher than 96% at 17 segments. Moreover, our method demonstrated excellent performance in all 3 image classifications.

CONCLUSION

Our algorithm system could realize accurate automatic reorientation and quantitative analysis of PET MMIs, which is also effective for images suffering from interference.

Automatic reorientation by deep learning to generate short-axis SPECT myocardial perfusion images

BACKGROUND

Single photon emission computed tomography (SPECT) myocardial perfusion images (MPI) can be displayed both in traditional short-axis (SA) cardiac planes and polar maps for interpretation and quantification. It is essential to reorient the reconstructed transaxial SPECT MPI into standard SA slices. This study is aimed to develop a deep-learning-based approach for automatic reorientation of MPI.

METHODS

A total of 254 patients were enrolled, including 226 stress SPECT MPIs and 247 rest SPECT MPIs. Fivefold cross-validation with 180 stress and 201 rest MPIs was used for training and internal validation; the remaining images were used for testing. The rigid transformation parameters (translation and rotation) from manual reorientation were annotated by an experienced nuclear cardiologist and used as the reference standard. A convolutional neural network (CNN) was designed to predict the transformation parameters. Then, the derived transform was applied to the grid generator and sampler in spatial transformer network (STN) to generate the reoriented image. A loss function containing mean absolute errors for translation and mean square errors for rotation was employed. A three-stage optimization strategy was adopted for model optimization: (1) optimize the translation parameters while fixing the rotation parameters; (2) optimize rotation parameters while fixing the translation parameters; (3) optimize both translation and rotation parameters together.

RESULTS

In the test set, the Spearman determination coefficients of the translation distances and rotation angles between the model prediction and the reference standard were 0.993 in X axis, 0.992 in Y axis, 0.994 in Z axis, 0.987 along X axis, 0.990 along Y axis and 0.996 along Z axis, respectively. For the 46 stress MPIs in the test set, the Spearman determination coefficients were 0.858 in percentage of profusion defect (PPD) and 0.858 in summed stress score (SSS); for the 46 rest MPIs in the test set, the Spearman determination coefficients were 0.9 in PPD and 0.9 in summed rest score (SRS).

CONCLUSIONS

Our deep learning-based LV reorientation method is able to accurately generate the SA images. Technical validations and subsequent evaluations of measured clinical parameters show that it has great promise for clinical use.

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.

Review of cardiovascular imaging in the Journal of Nuclear Cardiology 2022: single photon emission computed tomography

In this review, we will summarize a selection of articles on single-photon emission computed tomography published in the Journal of Nuclear Cardiology in 2022. The aim of this review is to concisely recap major advancements in the field to provide the reader a glimpse of the research published in the journal over the last year. This review will place emphasis on myocardial perfusion imaging using single-photon emission computed tomography summarizing advances in the field including in prognosis, non-perfusion variables, attenuation compensation, machine learning and camera design. It will also review nuclear imaging advances in amyloidosis, left ventricular mechanical dyssynchrony, cardiac innervation, and lung perfusion. We encourage interested readers to go back to the original articles, and editorials, for a comprehensive read as necessary but hope that this yearly review will be helpful in reminding readers of articles they have seen and attracting their attentions to ones they have missed.

Direct Attenuation Correction Using Deep Learning for Cardiac SPECT: A Feasibility Study

Dedicated cardiac SPECT scanners with cadmium-zinc-telluride cameras have shown capabilities for shortened scan times or reduced radiation doses, as well as improved image quality. Since most dedicated scanners do not have integrated CT, image quantification with attenuation correction (AC) is challenging and artifacts are routinely encountered in daily clinical practice. In this work, we demonstrated a direct AC technique using deep learning (DL) for myocardial perfusion imaging (MPI). Methods: In an institutional review board-approved retrospective study, 100 cardiac SPECT/CT datasets with 99mTc-tetrofosmin, obtained using a scanner specifically with a small field of view, were collected at the Yale New Haven Hospital. A convolutional neural network was used for generating DL-based attenuation-corrected SPECT (SPECTDL) directly from noncorrected SPECT (SPECTNC) without undergoing an additional image reconstruction step. The accuracy of SPECTDL was evaluated by voxelwise and segmentwise analyses against the reference, CT-based AC (SPECTCTAC), using the 17-segment myocardial model of the American Heart Association. Polar maps of representative (best, median, and worst) cases were visually compared to illustrate potential benefits and pitfalls of the DL approach. Results: The voxelwise correlations with SPECTCTAC were 92.2% ± 3.7% (slope, 0.87; R2 = 0.81) and 97.7% ± 1.8% (slope, 0.94; R2 = 0.91) for SPECTNC and SPECTDL, respectively. The segmental errors of SPECTNC scattered from -35% to 21% (P < 0.001), whereas the errors of SPECTDL stayed mostly within ±10% (P < 0.001). The average segmental errors (mean ± SD) were -6.11% ± 8.06% and 0.49% ± 4.35% for SPECTNC and SPECTDL, respectively. The average absolute segmental errors were 7.96% ± 6.23% and 3.31% ± 2.87% for SPECTNC and SPECTDL, respectively. Review of polar maps revealed successful reduction of attenuation artifacts; however, the performance of SPECTDL was not consistent for all subjects, likely because of different amounts of attenuation and different uptake patterns. Conclusion: We demonstrated the feasibility of direct AC using DL for SPECT MPI. Overall, our DL approach reduced attenuation artifacts substantially compared with SPECTNC, justifying further studies to establish safety and consistency for clinical applications in stand-alone SPECT systems suffering from attenuation artifacts.

Review of cardiovascular imaging in the Journal of Nuclear Cardiology 2020: positron emission tomography, computed tomography, and magnetic resonance

Although the year 2020 was different from other years in many respects, the Journal of Nuclear Cardiology published excellent articles pertaining to imaging in patients with cardiovascular disease due to the dedication of the investigators in our field all over the world. In this review, we will summarize a selection of these articles to provide a concise review of the main advancements that have recently occurred in the field and provide the reader with an opportunity to review a wide selection of articles. We will focus on publications dealing with positron emission tomography, computed tomography, and magnetic resonance and hope that you will find this review helpful.

Cardio-Oncology: Understanding the Intersections Between Cardiac Metabolism and Cancer Biology

An important priority in the cardiovascular care of oncology patients is to reduce morbidity and mortality, and improve the quality of life in cancer survivors through cross-disciplinary efforts. The rate of survival in cancer patients has improved dramatically over the past decades. Nonetheless, survivors may be more likely to die from cardiovascular disease in the long term, secondary, not only to the potential toxicity of cancer therapeutics, but also to the biology of cancer. In this context, efforts from basic and translational studies are crucial to understanding the molecular mechanisms causal to cardiovascular disease in cancer patients and survivors, and identifying new therapeutic targets that may prevent and treat both diseases. This review aims to highlight our current understanding of the metabolic interaction between cancer and the heart, including potential therapeutic targets. An overview of imaging techniques that can support both research studies and clinical management is also provided. Finally, this review highlights opportunities and challenges that are necessary to advance our understanding of metabolism in the context of cardio-oncology.

Assessment of ejection fraction and heart perfusion using myocardial perfusion single-photon emission computed tomography in Finland and Estonia: a multicenter phantom study

OBJECTIVES

Myocardial SPECT/CT imaging is frequently performed to assess myocardial perfusion and dynamic parameters of heart function, such as ejection fraction (EF). However, potential pitfalls exist in the imaging chain that can unfavorably affect diagnosis and treatment. We performed a national cardiac quality control study to investigate how much SPECT/CT protocols vary between different nuclear medicine units in Finland, and how this may affect the heart perfusion and EF values.

METHODS

Altogether, 21 nuclear medicine units participated with 27 traditional SPECT/CT systems and two cardiac-centered IQ-SPECT systems. The reproducibility of EF and the uniformity of perfusion were studied using a commercial dynamic heart phantom. SPECT/CT acquisitions were performed and processed at each participating unit using their own clinical protocol and with a standardized protocol. The effects of acquisition protocols and analysis routines on EF estimates and uniformity of perfusion were studied.

RESULTS

Considerable variation in EF estimates and in the uniformity of perfusion were observed between the units. Uniformity of perfusion was improved in some units after applying the higher count-statistic standard acquisition protocol. EF estimates varied more due to differences in analysis routines than as a result of different acquisition protocols. The results obtained with the two IQ-SPECT systems differed substantially from the traditional multipurpose cameras.

CONCLUSION

On average, the EF and heart perfusion were accurately estimated by SPECT/CT, but high errors could be produced if the acquisition and analysis routines were poorly optimized. Eight of the 21 participants altered their imaging protocol after this quality control tour.

Review of cardiovascular imaging in the Journal of Nuclear Cardiology 2019: Single-photon emission computed tomography

In 2019, the Journal of Nuclear Cardiology published excellent articles pertaining to imaging in patients with cardiovascular disease. In this review, we will summarize a selection of these articles to provide a concise review of the main advancements that have recently occurred in the field and provide the reader with an opportunity to review a wide selection of articles. In the first article of this 2-part series, we focused on publications dealing with positron emission tomography, computed tomography, and magnetic resonance. This review will place emphasis on myocardial perfusion imaging using single-photon emission computed tomography summarizing advances in the field including in diagnosis and prognosis, non-perfusion variables, safety of testing, imaging in patients with heart failure and renal disease.

Review of cardiovascular imaging in the Journal of Nuclear Cardiology 2019: Positron emission tomography, computed tomography and magnetic resonance

In 2019, the Journal of Nuclear Cardiology published excellent articles pertaining to imaging in patients with cardiovascular disease. In this review we will summarize a selection of these articles to provide a concise review of the main advancements that have recently occurred in the field and provide the reader with an opportunity to review a wide selection of articles. In this first article of this 2-part series we will focus on publications dealing with positron emission tomography, computed tomography and magnetic resonance. We will specifically discuss imaging as it relates to coronary artery disease, atherosclerosis and inflammation, coronary artery calcification, cardiomyopathies, cardiac implantable electronic devices, prosthetic valves, and left ventricular assist devices. The second part of this review will place emphasis on myocardial perfusion imaging using single-photon emission computed tomography.

Review of cardiovascular imaging in the Journal of Nuclear Cardiology 2018. Part 1 of 2: Positron emission tomography, computed tomography, and magnetic resonance

In this review, we summarize key articles that have been published in the Journal of Nuclear Cardiology in 2018 pertaining to nuclear cardiology with advanced multi-modality and hybrid imaging including positron emission tomography, cardiac-computed tomography, and magnetic resonance. In an upcoming review, we will summarize key articles that relate to the progress made in the field of single-photon emission computed tomography. We hope that these sister reviews will be useful to the reader to navigate the literature in our field.