Publications by authors named "Terrence Ruddy"
The Registry of Fast Myocardial Perfusion Imaging with Next-Generation SPECT (REFINE SPECT) has been expanded to include more patients and CT attenuation correction imaging. We present the design and initial results from the updated registry. The updated REFINE SPECT is a multicenter, international registry with clinical data and image files.
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- Researchers developed a new AI method to analyze routine CTAC scans from cardiac imaging to create volumetric measurements of various tissues, including fat and muscle, in the chest area.
- The study examined data from nearly 10,000 patients, finding that higher volumes of certain types of body fat (VAT, EAT, IMAT) were linked to an increased risk of all-cause mortality, whereas higher bone and skeletal muscle volumes were associated with lower mortality risk.
- This suggests that CTAC scans hold significant potential for identifying body composition markers that may help predict patient mortality risk beyond their current use.
Background: Although positron emission tomography (PET) imaging is well established for its diagnostic role in cardiac sarcoidosis, less is known about the prognostic value of PET and its use in risk stratification for major adverse cardiac events (MACE).
Objectives: The goal of this study was to perform a systematic review and meta-analysis looking at the prognostic value of PET imaging in patients with cardiac sarcoidosis.
Methods: Study investigators systematically searched EMBASE (Excerpta Medica dataBASE), MEDLINE, PubMed, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, CINAHL (Cumulative Index to Nursing and Allied Health Literature), ClinicalTrials.
Article Synopsis
- Low-dose computed tomography (CT) scans, used in hybrid myocardial perfusion imaging, provide valuable anatomical and pathological insights beyond just attenuation correction, which may be enhanced through AI-driven frameworks.
- This study analyzed data from over 10,000 patients, segmenting various structures and utilizing deep learning to assess coronary artery health, leading to improved all-cause mortality predictions.
- The comprehensive model integrating data from CT attenuation correction, myocardial perfusion imaging, and clinical factors outperformed other AI models in predicting mortality risk, particularly among patients with normal perfusion.
Background: Coronary microvascular dysfunction (CMD) has been implicated in the pathogenesis of Takotsubo syndrome (TTS). Positron emission tomography (PET) plays a key role in the assessment of CMD through myocardial flow reserve (MFR). However, there is limited information on the temporal progression of MFR and its relationship to coronary artery disease (CAD) in TTS patients.
View Article and Find Full Text PDFDevelopment and evolution of nuclear cardiology and cardiac PET in Canada.
J Med Imaging Radiat Sci
June 2024
Gated radionuclide angiography and myocardial perfusion imaging were developed in the United States and Europe in the 1970's and soon adopted in Canadian centers. Much of the early development of nuclear cardiology in Canada was in Toronto, Ontario and was quickly followed by new programs across the country. Clinical research in Canada contributed to the further development of nuclear cardiology and cardiac PET.
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- Chest CT scans are widely used in the U.S., with 15 million performed yearly, primarily for diagnosing various conditions, including cardiac risks.
- A new automated AI system can quickly and accurately assess coronary calcium and various heart chamber volumes from these scans, processing data in about 18 seconds and only missing 0.1% of cases.
- The AI-generated measurements of coronary calcium and heart volumes are effective in predicting overall and cardiovascular mortality, offering a better risk assessment method than traditional evaluations by radiologists.
Introduction: The addition of absolute myocardial blood flow (MBF) data improves the diagnostic and prognostic accuracy of relative perfusion imaging with nuclear medicine. Cardiac-specific gamma cameras allow measurement of MBF with SPECT.
Methods: This paper reviews the evidence supporting the use of SPECT to measure myocardial blood flow (MBF).
Article Synopsis
- The study investigates how the size of the heart affects the accuracy of SPECT myocardial perfusion imaging (MPI) in identifying obstructive coronary artery disease (CAD).
- Among 2066 patients, it was found that those with a low left ventricular volume had lower diagnostic performance compared to those with larger volumes, particularly affecting older and male patients.
- The results indicate that smaller heart sizes lead to a significant decrease in the effectiveness of SPECT MPI, highlighting the need for tailored diagnostic approaches based on cardiac size, age, and sex.
Article Synopsis
- Epicardial adipose tissue (EAT) volume and attenuation can indicate cardiovascular risk, but measuring them manually is time-consuming; the study explored using deep learning to automate this process using CT scans.
- Researchers trained a deep learning model on data from 500 patients to accurately identify EAT, achieving results in under 2 seconds compared to 15 minutes for manual analysis.
- After analyzing 8781 patients, results showed that higher EAT measurements were linked to an increased risk of death or myocardial infarction over a median follow-up of 2.7 years, indicating that automated EAT assessments could enhance cardiovascular risk prediction.
Background: The hypertension specialist often receives referrals of patients with young-onset, severe, difficult-to-control hypertension, patients with hypertensive emergencies, and patients with secondary causes of hypertension. Specialist hypertension care compliments primary care for these complex patients and contributes to an overall hypertension control strategy. The objective of this study was to characterize hypertension centres and the practice patterns of Canadian hypertension specialists.
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- Myocardial perfusion imaging (MPI) is widely used to diagnose coronary artery disease, but many patients have normal results; this study explores whether machine learning can identify unique patient profiles among those with normal scans and assess their risk of death or myocardial infarction.
- The research involved a large cohort of over 21,000 patients from an international MPI registry, employing unsupervised clustering to discover four distinct patient phenotypes, revealing differing characteristics and stress testing requirements among them.
- Findings indicated that one specific cluster of patients (Cluster 4), despite having normal scans, faced a significantly higher risk of serious cardiovascular events, suggesting that identifying these phenotypes could enhance risk assessment and patient management.
Background: Single-center studies have shown that single photon emission computed tomography myocardial blood flow (MBF) measurement is accurate compared with MBF measured with microspheres in a porcine model, positron emission tomography, and angiography. Clinical implementation requires consistency across multiple sites. The study goal is to determine the intersite processing repeatability of single photon emission computed tomography MBF and the additional camera time required.
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- A new explainable deep learning model has been developed to predict specific cardiovascular risks (like death, acute coronary syndrome, and need for revascularization) based on myocardial perfusion imaging (MPI) combined with clinical data.
- The model was tested with a large group of patients and showed better performance in predicting short-term risks in the first six months post-scan, outperforming traditional methods.
- It provides individualized risk assessments and visual explanations for patients, potentially helping to focus on modifiable risk factors and improve shared decision-making in healthcare.
Article Synopsis
- The study aimed to use unsupervised machine learning to classify patients with known coronary artery disease (CAD) based on their risk profiles during SPECT myocardial perfusion imaging.
- Out of 37,298 patients in the REFINE SPECT registry, 9,221 with CAD were analyzed, identifying three distinct clusters that varied in clinical characteristics, particularly concerning body mass index, diabetes, and hypertension.
- The cluster analysis provided superior risk stratification for all-cause mortality compared to traditional methods based on stress total perfusion deficit, indicating its potential for enhancing patient management in CAD.
The clinical presentation of coronary artery disease (CAD) has changed during the last 20 years with less ischemia on stress testing and more nonobstructive CAD on coronary angiography. Single-photon emission computed tomography (SPECT) myocardial perfusion imaging should include the measurement of myocardial flow reserve and assessment of coronary calcium for the diagnosis of nonobstructive CAD and coronary microvascular disease. SPECT/CT systems provide reliable attenuation correction for better specificity and low-dose CT for coronary calcium evaluation.
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- Angina and dyspnea in patients with normal coronary arteries present a diagnostic challenge, with many possibly suffering from coronary microvascular dysfunction (CMD) rather than traditional coronary artery disease.
- Positron emission tomography (PET) is used to measure myocardial blood flow (MBF) and reserve (MFR), which helps noninvasively detect CMD, leading to better understanding of patients' symptoms.
- A consensus document is in development to standardize the diagnosis and reporting for CMD to improve treatment decisions and patient outcomes, involving experts from around the world.