Pharmacological stress myocardial perfusion imaging after an inadequate exercise stress test

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.

Role of cardiac imaging in acute chest pain

Chest pain is the second most common complaint in the emergency department. The need to diagnose the cause of chest pain in a timely manner and appropriately direct care is crucial. This article discusses the role of imaging in acute chest pain, after first differentiating chest pain into cardiac and non-cardiac causes with upfront clinical and biochemical assessment. The role of non-invasive imaging including point-of-care ultrasound, echocardiography, myocardial perfusion imaging, cardiac MRI, coronary computed tomography angiography and novel cardiac CT applications are discussed. Updates in the literature regarding the role of coronary plaque imaging in acute chest pain are reviewed, as are ongoing challenges and future directions. This includes a discussion on the yield of diagnostic testing in low-risk acute chest pain cohorts vs intermediate-high risk cohorts. The incremental value of further testing in the former is low, which is reflected in contemporary guidelines that discourage the use of costly diagnostic tests in these cohorts. In the latter cohort, emerging evidence has shown specifically the role coronary computed tomography angiography could play in reducing the need for invasive coronary angiography in selective patients where the true probability of acute coronary syndrome is thought to be low. Real-world considerations such as accessibility and affordability are also discussed in the paper because while guidelines offer clinicians the flexibility of evidence-based choice, physician decision must necessarily be made in consideration of real-world constraints.

"Global" cardiac atherosclerotic burden assessed by artificial intelligence-based versus manual segmentation in 18F-sodium fluoride PET/CT scans: Head-to-head comparison

BACKGROUND

Artificial intelligence (AI) is known to provide effective means to accelerate and facilitate clinical and research processes. So in this study it was aimed to compare a AI-based method for cardiac segmentation in positron emission tomography/computed tomography (PET/CT) scans with manual segmentation to assess global cardiac atherosclerosis burden.

METHODS

A trained convolutional neural network (CNN) was used for cardiac segmentation in 18F-sodium fluoride PET/CT scans of 29 healthy volunteers and 20 angina pectoris patients and compared with manual segmentation. Parameters for segmented volume (Vol) and mean, maximal, and total standardized uptake values (SUVmean, SUVmax, SUVtotal) were analyzed by Bland-Altman Limits of Agreement. Repeatability with AI-based assessment of the same scans is 100%. Repeatability (same conditions, same operator) and reproducibility (same conditions, two different operators) of manual segmentation was examined by re-segmentation in 25 randomly selected scans.

RESULTS

Mean (± SD) values with manual vs. CNN-based segmentation were Vol 617.65 ± 154.99 mL vs 625.26 ± 153.55 mL (P = .21), SUVmean 0.69 ± 0.15 vs 0.69 ± 0.15 (P = .26), SUVmax 2.68 ± 0.86 vs 2.77 ± 1.05 (P = .34), and SUVtotal 425.51 ± 138.93 vs 427.91 ± 132.68 (P = .62). Limits of agreement were - 89.42 to 74.2, - 0.02 to 0.02, - 1.52 to 1.32, and - 68.02 to 63.21, respectively. Manual segmentation lasted typically 30 minutes vs about one minute with the CNN-based approach. The maximal deviation at manual re-segmentation was for the four parameters 0% to 0.5% with the same and 0% to 1% with different operators.

CONCLUSION

The CNN-based method was faster and provided values for Vol, SUVmean, SUVmax, and SUVtotal comparable to the manually obtained ones. This AI-based segmentation approach appears to offer a more reproducible and much faster substitute for slow and cumbersome manual segmentation of the heart.

Transient Opening of the Blood-Brain Barrier by Vasoactive Peptides to Increase CNS Drug Delivery: Reality Versus Wishful Thinking?

BACKGROUND

The blood-brain barrier inhibits the central nervous system penetration of 98% of small molecule drugs and virtually all biologic agents, which has limited progress in treating neurologic disease. Vasoactive peptides have been shown in animal studies to transiently disrupt the blood-brain barrier and regadenoson is currently being studied in humans to determine if it can improve drug delivery to the brain. However, many other vasoactive peptides could potentially be used for this purpose.

METHODS

We performed a review of the literature evaluating the physiologic effects of vasoactive peptides on the vasculature of the brain and systemic organs. To assess the likelihood that a vasoactive peptide might transiently disrupt the blood-brain barrier, we devised a four-tier classification system to organize the available evidence.

RESULTS

We identified 32 vasoactive peptides with potential blood-brain barrier permeabilityaltering properties. To date, none of these are shown to open the blood-brain barrier in humans. Twelve vasoactive peptides increased blood-brain barrier permeability in rodents. The remaining 20 had favorable physiologic effects on blood vessels but lacked specific information on permeability changes to the blood-brain barrier.

CONCLUSION

Vasoactive peptides remain an understudied class of drugs with the potential to increase drug delivery and improve treatment in patients with brain tumors and other neurologic diseases. Dozens of vasoactive peptides have yet to be formally evaluated for this important clinical effect. This narrative review summarizes the available data on vasoactive peptides, highlighting agents that deserve further in vitro and in vivo investigations.

Patient-Specific Inverse Modeling of In Vivo Cardiovascular Mechanics with Medical Image-Derived Kinematics as Input Data: Concepts, Methods, and Applications

Inverse modeling approaches in cardiovascular medicine are a collection of methodologies that can provide non-invasive patient-specific estimations of tissue properties, mechanical loads, and other mechanics-based risk factors using medical imaging as inputs. Its incorporation into clinical practice has the potential to improve diagnosis and treatment planning with low associated risks and costs. These methods have become available for medical applications mainly due to the continuing development of image-based kinematic techniques, the maturity of the associated theories describing cardiovascular function, and recent progress in computer science, modeling, and simulation engineering. Inverse method applications are multidisciplinary, requiring tailored solutions to the available clinical data, pathology of interest, and available computational resources. Herein, we review biomechanical modeling and simulation principles, methods of solving inverse problems, and techniques for image-based kinematic analysis. In the final section, the major advances in inverse modeling of human cardiovascular mechanics since its early development in the early 2000s are reviewed with emphasis on method-specific descriptions, results, and conclusions. We draw selected studies on healthy and diseased hearts, aortas, and pulmonary arteries achieved through the incorporation of tissue mechanics, hemodynamics, and fluid-structure interaction methods paired with patient-specific data acquired with medical imaging in inverse modeling approaches.