CT attenuation correction improves quantitative risk prediction by cardiac SPECT in obese patients.

PURPOSE: This study aimed to compare the predictive value of CT attenuation-corrected stress total perfusion deficit (AC-sTPD) and non-corrected stress TPD (NC-sTPD) for major adverse cardiac events (MACE) in obese patients undergoing cadmium zinc telluride (CZT) SPECT myocardial perfusion imaging (MPI). METHODS: The study included 4,585 patients who underwent CZT SPECT/CT MPI for clinical indications (chest pain: 56%, shortness of breath: 13%, other: 32%) at Yale New Haven Hospital (age: 64 ± 12 years, 45% female, body mass index [BMI]: 30.0 ± 6.3 kg/m2, prior coronary artery disease: 18%). The association between AC-sTPD or NC-sTPD and MACE defined as the composite end point of mortality, nonfatal myocardial infarction or late coronary revascularization (> 90 days after SPECT) was evaluated with survival analysis. RESULTS: During a median follow-up of 25 months, 453 patients (10%) experienced MACE. In patients with BMI ≥ 35 kg/m2 (n = 931), those with AC-sTPD ≥ 3% had worse MACE-free survival than those with AC-sTPD < 3% (HR: 2.23, 95% CI: 1.40 - 3.55, p = 0.002) with no difference in MACE-free survival between patients with NC-sTPD ≥ 3% and NC-sTPD < 3% (HR:1.06, 95% CI:0.67 - 1.68, p = 0.78). AC-sTPD had higher AUC than NC-sTPD for the detection of 2-year MACE in patients with BMI ≥ 35 kg/m2 (0.631 versus 0.541, p = 0.01). In the overall cohort AC-sTPD had a higher ROC area under the curve (AUC, 0.641) than NC-sTPD (0.608; P = 0.01) for detection of 2-year MACE. In patients with BMI ≥ 35 kg/m2 AC sTPD provided significant incremental prognostic value beyond NC sTPD (net reclassification index: 0.14 [95% CI: 0.20 - 0.28]). CONCLUSIONS: AC sTPD outperformed NC sTPD in predicting MACE in patients undergoing SPECT MPI with BMI ≥ 35 kg/m2. These findings highlight the superior prognostic value of AC-sTPD in this patient population and underscore the importance of CT attenuation correction.

Downward myocardial creep during stress PET imaging is inversely associated with mortality.

PURPOSE: The myocardial creep is a phenomenon in which the heart moves from its original position during stress-dynamic PET myocardial perfusion imaging (MPI) that can confound myocardial blood flow measurements. Therefore, myocardial motion correction is important to obtain reliable myocardial flow quantification. However, the clinical importance of the magnitude of myocardial creep has not been explored. We aimed to explore the prognostic value of myocardial creep quantified by an automated motion correction algorithm beyond traditional PET-MPI imaging variables. METHODS: Consecutive patients undergoing regadenoson rest-stress [82Rb]Cl PET-MPI were included. A newly developed 3D motion correction algorithm quantified myocardial creep, the maximum motion at stress during the first pass (60 s), in each direction. All-cause mortality (ACM) served as the primary endpoint. RESULTS: A total of 4,276 patients (median age 71 years; 60% male) were analyzed, and 1,007 ACM events were documented during a 5-year median follow-up. Processing time for automatic motion correction was < 12 s per patient. Myocardial creep in the superior to inferior (downward) direction was greater than the other directions (median, 4.2 mm vs. 1.3-1.7 mm). Annual mortality rates adjusted for age and sex were reduced with a larger downward creep, with a 4.2-fold ratio between the first (0 mm motion) and 10th decile (11 mm motion) (mortality, 7.9% vs. 1.9%/year). Downward creep was associated with lower ACM after full adjustment for clinical and imaging parameters (adjusted hazard ratio, 0.93; 95%CI, 0.91-0.95; p < 0.001). Adding downward creep to the standard PET-MPI imaging model significantly improved ACM prediction (area under the receiver operating characteristics curve, 0.790 vs. 0.775; p < 0.001), but other directions did not (p > 0.5). CONCLUSIONS: Downward myocardial creep during regadenoson stress carries additional information for the prediction of ACM beyond conventional flow and perfusion PET-MPI. This novel imaging biomarker is quantified automatically and rapidly from stress dynamic PET-MPI.

Is typical angina still prognostically important? The influence of "treatment bias" upon prognostic assessments.

BACKGROUND: Since typical angina has become less frequent, it is unclear if this symptom still has prognostic significance. METHODS: We evaluated 38,383 patients undergoing stress/rest SPECT myocardial perfusion imaging followed for a median of 10.9 years. After dividing patients by clinical symptoms, we evaluated the magnitude of myocardial ischemia and subsequent mortality among medically treated versus revascularized subgroups following testing. RESULTS: Patients with typical angina had more frequent and greater ischemia than other symptom groups, but not higher mortality. Among typical angina patients, those who underwent early revascularization had substantially greater ischemia than the medically treated subgroup, including a far higher proportion with severe ischemia (44.9% vs 4.3%, P < 0.001) and transient ischemic dilation of the LV (31.3% vs 4.7%, P < 0.001). Nevertheless, the revascularized typical angina subgroup had a lower adjusted mortality risk than the medically treated subgroup (HR = 0.72, 95% CI: 0.57-0.92, P = 0.009) CONCLUSIONS: Typical angina is associated with substantially more ischemia than other clinical symptoms. However, the high referral of patients with typical angina patients with ischemia to early revascularization resulted in this group having a lower rather than higher mortality risk versus other symptom groups. These findings illustrate the need to account for "treatment bias" among prognostic studies.

Comparative predictors of mortality among patients referred for stress single-photon emission computed tomography versus positron emission tomography myocardial perfusion imaging.

BACKGROUND: There is currently little information regarding the usage and comparative predictors of mortality among patients referred for single-photon emission computed tomography (SPECT) versus positron emission tomography (PET) myocardial perfusion imaging (MPI) within multimodality imaging laboratories. METHODS: We compared the clinical characteristics and mortality outcomes among 15,718 patients referred for SPECT-MPI and 6202 patients referred for PET-MPI between 2008 and 2017. RESULTS: Approximately two-thirds of MPI studies were performed using SPECT-MPI. The PET-MPI group was substantially older and included more patients with known coronary artery disease (CAD), hypertension, diabetes, and myocardial ischemia. The annualized mortality rate was also higher in the PET-MPI group, and this difference persisted after propensity matching 3615 SPECT-MPI and 3615 PET-MPI patients to have similar clinical profiles. Among the SPECT-MPI patients, the most potent predictor of mortality was exercise ability and performance, including consideration of patients' mode of stress testing and exercise duration. Among the PET-MPI patients, myocardial flow reserve (MFR) was the most potent predictor of mortality. CONCLUSIONS: In our real-world setting, PET-MPI was more commonly employed among older patients with more cardiac risk factors than SPECT-MPI patients. The most potent predictors of mortality in our SPECT and PET-MPI groups were variables exclusive to each test: exercise ability/capacity for SPECT-MPI patients and MFR for PET-MPI patients.

A scaffolded and annotated reference genome of giant kelp (Macrocystis pyrifera).

Macrocystis pyrifera (giant kelp), is a brown macroalga of great ecological importance as a primary producer and structure-forming foundational species that provides habitat for hundreds of species. It has many commercial uses (e.g. source of alginate, fertilizer, cosmetics, feedstock). One of the limitations to exploiting giant kelp's economic potential and assisting in giant kelp conservation efforts is a lack of genomic tools like a high quality, contiguous reference genome with accurate gene annotations. Reference genomes attempt to capture the complete genomic sequence of an individual or species, and importantly provide a universal structure for comparison across a multitude of genetic experiments, both within and between species. We assembled the giant kelp genome of a haploid female gametophyte de novo using PacBio reads, then ordered contigs into chromosome level scaffolds using Hi-C. We found the giant kelp genome to be 537 MB, with a total of 35 scaffolds and 188 contigs. The assembly N50 is 13,669,674 with GC content of 50.37%. We assessed the genome completeness using BUSCO, and found giant kelp contained 94% of the BUSCO genes from the stramenopile clade. Annotation of the giant kelp genome revealed 25,919 genes. Additionally, we present genetic variation data based on 48 diploid giant kelp sporophytes from three different Southern California populations that confirms the population structure found in other studies of these populations. This work resulted in a high-quality giant kelp genome that greatly increases the genetic knowledge of this ecologically and economically vital species.

IL-6 evoked biochemical changes in prostate cancer cells.

The pro-inflammatory cytokine IL-6 has been associated with the progression of PCa to a castration-resistant phenotype. In this work, we characterized the biochemical changes evoked by IL-6 in three different models of PCa cells, including LNCaP, C4-2, and PC3. The effect of IL-6 on PCa cells was compared with the effect obtained by co-stimulation with the cAMP-inducing agent forskolin (FSK). Stimulation of LNCaP cells with IL-6 or IL-6 + FSK evoked increased expression of the neuroendocrine marker tubulin IIIß and Cav3.2 T-type Ca2+ channel subunit. PC3 cells, representing a more advanced state of PCa, had high levels of tubulin IIIß expression without any further changes observed by treatment with IL-6 or IL-6 + FSK. Elevated expression of the glucocorticoid receptor was observed in PC3, but not in LNCaP or C4-2 cells. Glucocorticoid receptor expression was not regulated by IL-6 stimulation of LNCaP or C4-2 cells. IL-6 acting alone or together with FSK evoked a significant reduction in the expression of the transcription factor REST and retinoblastoma tumor suppressor protein Rb1. In LNCaP cells, IL-6 acting alone or together with FSK had no effect on the expression of several biological markers of advanced PCa, including Aurora kinase A, valosin-containing protein, calcium-sensing receptor, calreticulin, S100A protein, and Protein S. In PC3 cells, co-treatment with IL-6 + FSK evoked increased expression of REST and S100A proteins, as well as a reduction in Protein S levels. These findings reveal a complex pattern of biochemical changes in PCa cells under the influence of IL-6.

Incremental prognostic value of stress phase entropy over standard PET myocardial perfusion imaging variables.

PURPOSE: Phase analysis can assess left ventricular dyssynchrony. The independent prognostic value of phase variables over positron emission tomography myocardial perfusion imaging (PET-MPI) variables including myocardial flow reserve (MFR) has not been studied. The aim of this study was to explore the prognostic value of phase variables for predicting mortality over standard PET-MPI variables. METHODS: Consecutive patients who underwent pharmacological stress-rest 82Rb PET study were enrolled. All PET-MPI variables including phase variables (phase entropy, phase bandwidth, and phase standard deviation) were automatically obtained by QPET software (Cedars-Sinai, Los Angeles, CA). Cox proportional hazard analyses were used to assess associations with all-cause mortality (ACM). RESULTS: In a total of 3963 patients (median age 71 years; 57% male), 923 patients (23%) died during a median follow-up of 5 years. Annualized mortality rates increased with stress phase entropy, with a 4.6-fold difference between the lowest and highest decile groups of entropy (2.6 vs. 12.0%/year). Abnormal stress phase entropy (optimal cutoff value, 43.8%) stratified ACM risk in patients with normal and impaired MFR (both p < 0.001). Among three phase variables, only stress phase entropy was significantly associated with ACM after the adjustment of standard clinical and PET-MPI variables including MFR and stress-rest change of phase variables, whether modeled as binary variables (adjusted hazard ratio, 1.44 for abnormal entropy [> 43.8%]; 95%CI, 1.18-1.75; p < 0.001) or continuous variables (adjusted hazard ratio, 1.05 per 5% increase; 95%CI, 1.01-1.10; p = 0.030). The addition of stress phase entropy to the standard PET-MPI variables significantly improved the discriminatory power for ACM prediction (p < 0.001), but the other phase variables did not (p > 0.1). CONCLUSION: Stress phase entropy is independently and incrementally associated with ACM beyond standard PET-MPI variables including MFR. Phase entropy can be obtained automatically and included in clinical reporting of PET-MPI studies to improve patient risk prediction.

Mitigating bias in deep learning for diagnosis of coronary artery disease from myocardial perfusion SPECT images.

PURPOSE: Artificial intelligence (AI) has high diagnostic accuracy for coronary artery disease (CAD) from myocardial perfusion imaging (MPI). However, when trained using high-risk populations (such as patients with correlating invasive testing), the disease probability can be overestimated due to selection bias. We evaluated different strategies for training AI models to improve the calibration (accurate estimate of disease probability), using external testing. METHODS: Deep learning was trained using 828 patients from 3 sites, with MPI and invasive angiography within 6 months. Perfusion was assessed using upright (U-TPD) and supine total perfusion deficit (S-TPD). AI training without data augmentation (model 1) was compared to training with augmentation (increased sampling) of patients without obstructive CAD (model 2), and patients without CAD and TPD < 2% (model 3). All models were tested in an external population of patients with invasive angiography within 6 months (n = 332) or low likelihood of CAD (n = 179). RESULTS: Model 3 achieved the best calibration (Brier score 0.104 vs 0.121, p < 0.01). Improvement in calibration was particularly evident in women (Brier score 0.084 vs 0.124, p < 0.01). In external testing (n = 511), the area under the receiver operating characteristic curve (AUC) was higher for model 3 (0.930), compared to U-TPD (AUC 0.897) and S-TPD (AUC 0.900, p < 0.01 for both). CONCLUSION: Training AI models with augmentation of low-risk patients can improve calibration of AI models developed to identify patients with CAD, allowing more accurate assignment of disease probability. This is particularly important in lower-risk populations and in women, where overestimation of disease probability could significantly influence down-stream patient management.

Unsupervised learning to characterize patients with known coronary artery disease undergoing myocardial perfusion imaging.

PURPOSE: Patients with known coronary artery disease (CAD) comprise a heterogenous population with varied clinical and imaging characteristics. Unsupervised machine learning can identify new risk phenotypes in an unbiased fashion. We use cluster analysis to risk-stratify patients with known CAD undergoing single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI). METHODS: From 37,298 patients in the REFINE SPECT registry, we identified 9221 patients with known coronary artery disease. Unsupervised machine learning was performed using clinical (23), acquisition (17), and image analysis (24) parameters from 4774 patients (internal cohort) and validated with 4447 patients (external cohort). Risk stratification for all-cause mortality was compared to stress total perfusion deficit (< 5%, 5-10%, ≥10%). RESULTS: Three clusters were identified, with patients in Cluster 3 having a higher body mass index, more diabetes mellitus and hypertension, and less likely to be male, have dyslipidemia, or undergo exercise stress imaging (p < 0.001 for all). In the external cohort, during median follow-up of 2.6 [0.14, 3.3] years, all-cause mortality occurred in 312 patients (7%). Cluster analysis provided better risk stratification for all-cause mortality (Cluster 3: hazard ratio (HR) 5.9, 95% confidence interval (CI) 4.0, 8.6, p < 0.001; Cluster 2: HR 3.3, 95% CI 2.5, 4.5, p < 0.001; Cluster 1, reference) compared to stress total perfusion deficit (≥10%: HR 1.9, 95% CI 1.5, 2.5 p < 0.001; < 5%: reference). CONCLUSIONS: Our unsupervised cluster analysis in patients with known CAD undergoing SPECT MPI identified three distinct phenotypic clusters and predicted all-cause mortality better than ischemia alone.

External validation of the CRAX2MACE model.

BACKGROUND: Single-photon emission computed tomography (SPECT) myocardial perfusion is frequently used to predict risk of major adverse cardiovascular events (MACE). We performed an external validation of the CRAX2MACE score, developed to estimate 2-year risk of MACE in patients with suspected coronary artery disease (CAD). METHODS: Patients who underwent clinically indicated SPECT with available follow-up for MACE were included (N = 2,985). The prediction performance for MACE (revascularization, myocardial infarction, or death) within 2 years for CRAX2MACE was compared with stress and ischemic total perfusion deficit (TPD) using area under the receiver operating characteristic curve (AUC). Calibration was assessed with calibration plots, Brier score, and the Hosmer-Lemeshow test. RESULTS: MACE occurred within 2 years in 243 (8.1%) patients. The AUC for CRAX2MACE (0.710, 95% CI 0.677-0.743) was significantly higher compared to stress TPD (AUC 0.669, 95% CI 0.632-0.706, P = .010) and ischemic TPD (AUC 0.664, 95% CI 0.627-0.700, P < .001). The model had acceptable goodness-of-fit (P = .103) and was well-calibrated with Brier score of 0.071. CONCLUSION: CRAX2MACE had higher predictive performance for 2-year MACE than quantitative perfusion in an external population. The current model is simple to use and could be implemented to assist physicians when estimating patient risk.

Diagnostic accuracy of bone scintigraphy imaging for transthyretin cardiac amyloidosis: systematic review and meta-analysis.

BACKGROUND: Bone scintigraphy imaging is frequently used to investigate patients with suspected transthyretin cardiac amyloidosis (ATTR-CM). However, the reported accuracy for interpretation approaches has changed over time. We performed a systematic review and meta-analysis to determine the diagnostic accuracy of visual planar grading, heart-to-contralateral (HCL) ratio, and quantitative analysis of SPECT imaging and evaluate reasons for shifts in reported accuracy. METHODS: We performed a systematic review to identify studies of the diagnostic accuracy of bone scintigraphy for ATTR-CM from 1990 until February 2023 using PUBMED and EMBASE. Studies were reviewed separately by two authors for inclusion and for risk of bias assessment. Summary receiver operating characteristic curves and operating points were determined with hierarchical modeling. RESULTS: Out of a total of 428 identified studies, 119 were reviewed in detail and 23 were included in the final analysis. The studies included a total of 3954 patients, with ATTR-CM diagnosed in 1337 (39.6%) patients and prevalence ranging from 21 to 73%. Visual planar grading and quantitative analysis had higher diagnostic accuracy (.99) than HCL ratio (.96). Quantitative analysis of SPECT imaging had the highest specificity (97%) followed by planar visual grade (96%) and HCL ratio (93%). ATTR-CM prevalence accounted for some of the observed between study heterogeneity. CONCLUSIONS: Bone scintigraphy imaging is highly accurate for identifying patients with ATTR-CM, with between study heterogeneity in part explained by differences in disease prevalence. We identified small differences in specificity, which may have important clinical implications when applied to low-risk screening populations.

Development and validation of ischemia risk scores.

BACKGROUND: The likelihood of ischemia on myocardial perfusion imaging is central to physician decisions regarding test selection, but dedicated risk scores are lacking. We derived and validated two novel ischemia risk scores to support physician decision making. METHODS: Risk scores were derived using 15,186 patients and validated with 2,995 patients from a different center. Logistic regression was used to assess associations with ischemia to derive point-based and calculated ischemia scores. Predictive performance for ischemia was assessed using area under the receiver operating characteristic curve (AUC) and compared with the CAD consortium basic and clinical models. RESULTS: During derivation, the calculated ischemia risk score (0.801) had higher AUC compared to the point-based score (0.786, p < 0.001). During validation, the calculated ischemia score (0.716, 95% CI 0.684- 0.748) had higher AUC compared to the point-based ischemia score (0.699, 95% CI 0.666- 0.732, p = 0.016) and the clinical CAD model (AUC 0.667, 95% CI 0.633- 0.701, p = 0.002). Calibration for both ischemia scores was good in both populations (Brier score  < 0.100). CONCLUSIONS: We developed two novel risk scores for predicting probability of ischemia on MPI which demonstrated high accuracy during model derivation and in external testing. These scores could support physician decisions regarding diagnostic testing strategies.

Decline in typical angina among patients referred for cardiac stress testing.

OBJECTIVE: To evaluate temporal trends in the prevalence of typical angina and its clinical correlates among patients referred for stress/rest SPECT myocardial perfusion imaging (MPI). PATIENTS AND METHODS: We evaluated the prevalence of chest pain symptoms and their relationship to inducible myocardial ischemia among 61,717 patients undergoing stress/rest SPECT-MPI between January 2, 1991 and December 31, 2017. We also assessed the relationship between chest pain symptom and angiographic findings among 6,579 patients undergoing coronary CT angiography between 2011 and 2017. RESULTS: The prevalence of typical angina among SPECT-MPI patients declined from 16.2% between 1991 and 1997 to 3.1% between 2011 and 2017, while the prevalence of dyspnea without any chest pain increased from 5.9 to 14.5% over the same period. The frequency of inducible myocardial ischemia declined over time within all symptom groups, but its frequency among current patients (2011-2017) with typical angina was approximately three-fold higher versus other symptom groups (28.4% versus 8.6%, p < 0.001). Overall, patients with typical angina had a higher prevalence of obstructive CAD on CCTA than those with other clinical symptoms, but 33.3% of typical angina patients had no coronary stenoses, 31.1% had 1-49% stenoses, and 35.4% had ≥ 50% stenoses. CONCLUSIONS: The prevalence of typical angina has declined to a very low level among contemporary patients referred for noninvasive cardiac tests. The angiographic findings among current typical angina patients are now quite heterogeneous, with one-third of such patients having normal coronary angiograms. However, typical angina remains associated with a substantially higher frequency of inducible myocardial ischemia compared to patients with other cardiac symptoms.

Increasing frequency of dyspnea among patients referred for cardiac stress testing.

OBJECTIVE: To assess the frequency, change in prevalence, and prognostic significance of dyspnea among contemporary patients referred for cardiac stress testing. PATIENTS AND METHODS: We evaluated the prevalence of dyspnea and its relationship to all-cause mortality among 33,564 patients undergoing stress/rest SPECT-MPI between January 1, 2002 and December 31, 2017. Dyspnea was assessed as a single-item question. Patients were divided into three temporal groups. RESULTS: The overall prevalence of dyspnea in our cohort was 30.2%. However, there was a stepwise increase in the temporal prevalence of dyspnea, which was present in 25.6% of patients studied between 2002 and 2006, 30.5% of patients studied between 2007 and 2011, and 38.7% of patients studied between 2012 and 2017. There was a temporal increase in the prevalence of dyspnea in each age, symptom, and risk factor subgroup. The adjusted hazard ratio for mortality was higher among patients with dyspnea vs those without dyspnea both among all patients, and within each chest pain subgroup. CONCLUSIONS: Dyspnea has become increasingly prevalent among patients referred for cardiac stress testing and is now present among nearly two-fifths of contemporary cohorts referred for stress-rest SPECT-MPI. Prospective study is needed to standardize the assessment of dyspnea and evaluate the reasons for its increasing prevalence.

Hot spot imaging in cardiovascular diseases: an information statement from SNMMI, ASNC, and EANM.

This information statement from the Society of Nuclear Medicine and Molecular Imaging, American Society of Nuclear Cardiology, and European Association of Nuclear Medicine describes the performance, interpretation, and reporting of hot spot imaging in nuclear cardiology. The field of nuclear cardiology has historically focused on cold spot imaging for the interpretation of myocardial ischemia and infarction. Hot spot imaging has been an important part of nuclear medicine, particularly for oncology or infection indications, and the use of hot spot imaging in nuclear cardiology continues to expand. This document focuses on image acquisition and processing, methods of quantification, indications, protocols, and reporting of hot spot imaging. Indications discussed include myocardial viability, myocardial inflammation, device or valve infection, large vessel vasculitis, valve calcification and vulnerable plaques, and cardiac amyloidosis. This document contextualizes the foundations of image quantification and highlights reporting in each indication for the cardiac nuclear imager.

Aging of Copper Nanoparticles in the Marine Environment Regulates Toxicity for a Coastal Phytoplankton Species.

Environmental conditions in aquatic ecosystems transform toxic chemicals over time, influencing their bioavailability and toxicity. Using an environmentally relevant methodology, we tested how exposure to seawater for 1-15 weeks influenced the accumulation and toxicity of copper nanoparticles (nano-Cu) in a marine phytoplankton species. Nano-Cu rapidly agglomerated in seawater and then decreased in size due to Cu dissolution. Dissolution rates declined during weeks 1-4 and remained low until 15 weeks, when the large agglomerates that had formed began to rapidly dissolve again. Marine phytoplankton species were exposed for 5-day periods to nano-Cu aged from 1 to 15 weeks at concentrations from 0.01 to 20 ppm. Toxicity to phytoplankton, measured as change in population growth rate, decreased significantly with particle aging from 0 to 4 weeks but increased substantially in the 15-week treatment due apparently to elevated Cu dissolution of reagglomerated particles. Results indicate that the transformation, fate, and toxicity of nano-Cu in marine ecosystems are influenced by a highly dynamic physicochemical aging process.

Prevalence, incidence and clinical outcomes of epicardial coronary artery disease among transthyretin amyloidosis cardiomyopathy patients.

BACKGROUND: Transthyretin amyloidosis cardiomyopathy (ATTR-CM) patients are often older and may be at risk for obstructive epicardial coronary artery disease (oeCAD). While ATTR-CM may cause small vessel coronary disease, the prevalence and clinical significance of oeCAD is not well described. METHODS AND RESULTS: The prevalence and incidence of oeCAD and its association with all-cause mortality and hospitalization among 133 ATTR-CM patients with ≥ 1-year follow-up was evaluated. The mean age was 78 ± 9 years, 119 (89%) were male, 116 (87%) had wild-type and 17 (13%) had hereditary subtypes. Seventy-two (54%) patients underwent oeCAD investigations, with 30 (42%) receiving a positive diagnosis. Among patients with a positive oeCAD diagnosis, 23 (77%) were diagnosed prior to ATTR-CM diagnosis, 6 (20%) at the time of ATTR-CM diagnosis, and 1 (3%) after ATTR-CM diagnosis. Baseline characteristics between patients with and without oeCAD were similar. Among patients with oeCAD, only 2 (7%) required additional investigations, intervention or hospitalization after ATTR-CM diagnosis. After a median follow-up of 27 months there were 37 (28%) deaths in the study population, including 5 patients with oeCAD (17%). Fifty-six (42%) patients in the study population required hospitalization, including 10 patients with oeCAD (33%). There was no significant difference in the rates of death or hospitalization among ATTR-CM patients with and without oeCAD, and oeCAD was not significantly associated with either outcome by univariable regression analysis. CONCLUSIONS: While oeCAD is prevalent in ATTR-CM patients, this diagnosis is frequently known at time of ATTR-CM diagnosis and characteristics are similar to patients without oeCAD.

Influence of offshore oil and gas structures on seascape ecological connectivity.

Offshore platforms, subsea pipelines, wells and related fixed structures supporting the oil and gas (O&G) industry are prevalent in oceans across the globe, with many approaching the end of their operational life and requiring decommissioning. Although structures can possess high ecological diversity and productivity, information on how they interact with broader ecological processes remains unclear. Here, we review the current state of knowledge on the role of O&G infrastructure in maintaining, altering or enhancing ecological connectivity with natural marine habitats. There is a paucity of studies on the subject with only 33 papers specifically targeting connectivity and O&G structures, although other studies provide important related information. Evidence for O&G structures facilitating vertical and horizontal seascape connectivity exists for larvae and mobile adult invertebrates, fish and megafauna; including threatened and commercially important species. The degree to which these structures represent a beneficial or detrimental net impact remains unclear, is complex and ultimately needs more research to determine the extent to which natural connectivity networks are conserved, enhanced or disrupted. We discuss the potential impacts of different decommissioning approaches on seascape connectivity and identify, through expert elicitation, critical knowledge gaps that, if addressed, may further inform decision making for the life cycle of O&G infrastructure, with relevance for other industries (e.g. renewables). The most highly ranked critical knowledge gap was a need to understand how O&G structures modify and influence the movement patterns of mobile species and dispersal stages of sessile marine species. Understanding how different decommissioning options affect species survival and movement was also highly ranked, as was understanding the extent to which O&G structures contribute to extending species distributions by providing rest stops, foraging habitat, and stepping stones. These questions could be addressed with further dedicated studies of animal movement in relation to structures using telemetry, molecular techniques and movement models. Our review and these priority questions provide a roadmap for advancing research needed to support evidence-based decision making for decommissioning O&G infrastructure.

Amyloidosis and COVID-19: experience from an amyloid program in Canada.

Severe acute respiratory syndrome coronavirus (SARS-CoV2) and associated COVID-19 infection continue to impact patients globally. Patients with underlying health conditions are at heightened risk of adverse outcomes from COVID-19; however, research involving patients with rare health conditions remains scarce. The amyloidoses are a rare grouping of protein deposition diseases. Light-chain and transthyretin amyloidosis are the most common disease forms, often present with systemic involvement of vital organs including the heart, nerves, kidneys, and GI tracts of affected individuals. The Amyloidosis Program of Calgary examined 152 ATTR patients and 103 AL patients analyzing rates of vaccination, COVID-19 testing, infection outcomes, influence referrals, and excess deaths. Results showed 15 total PCR-confirmed COVID-19 infections in the tested population of amyloid patients, with a higher frequency of infections among patient with AL compared to the ATTR cohort (26.2% vs 5.1%). Four patients (26.6%) required hospital admission for COVID-19 infection, 2 ATTR, and 2 AL patients. Of the confirmed cases, 1 (0.07%) unvaccinated ATTR patient died of a COVID-19 infection. An excess of deaths was found in both the ATTR and AL cohorts when comparing pre-pandemic years 2018 and 2019 to the pandemic years of 2020 and 2021. The finding suggests that amyloidosis patients are likely at a high risk for severe COVID-19 infection and mortality, especially those of advanced age, those on an active treatment with chemotherapy, and those with concomitant B-cell or plasma cell disorder. The impact of virtual healthcare visits and pandemic measures on the excess of deaths observed requires further research.

Artificial intelligence for disease diagnosis and risk prediction in nuclear cardiology.

Artificial intelligence (AI) techniques have emerged as a highly efficient approach to accurately and rapidly interpret diagnostic imaging and may play a vital role in nuclear cardiology. In nuclear cardiology, there are many clinical, stress, and imaging variables potentially available, which need to be optimally integrated to predict the presence of obstructive coronary artery disease (CAD) or predict the risk of cardiovascular events. In spite of clinical awareness of a large number of potential variables, it is difficult for physicians to integrate multiple features consistently and objectively. Machine learning (ML) is particularly well suited to integrating this vast array of information to provide patient-specific predictions. Deep learning (DL), a branch of ML characterized by a multi-layered convolutional model architecture, can extract information directly from images and identify latent image features associated with a specific prediction. This review will discuss the latest AI applications to disease diagnosis and risk prediction in nuclear cardiology with a focus on potential clinical applications.