Self-reported exercise activity influences the relationship between coronary computed tomography angiographic finding and mortality.

AIM: Recent studies suggest that the application of exercise activity questionnaires, including the use of a single-item exercise question, can be additive to the prognostic efficacy of imaging findings. This study aims to evaluate the prognostic efficacy of exercise activity in patients undergoing coronary computed tomography angiography (CCTA). METHODS AND RESULTS: We assessed 9772 patients who underwent CCTA at a single center between 2007 and 2020. Patients were divided into 4 groups of physical activity as no exercise (n â€‹= â€‹1643, 17%), mild exercise (n â€‹= â€‹3156, 32%), moderate exercise (n â€‹= â€‹3542, 36%), and high exercise (n â€‹= â€‹1431,15%), based on a single-item self-reported questionnaire. Coronary stenosis was categorized as no (0%), non-obstructive (1-49%), borderline (50-69%), and obstructive (≥70%). During a median follow-up of 4.64 (IQR 1.53-7.89) years, 490 (7.6%) died. There was a stepwise inverse relationship between exercise activity and mortality (p â€‹< â€‹0.001). Compared with the high activity group, the no activity group had a 3-fold higher mortality risk (HR: 3.3, 95%CI (1.94-5.63), p â€‹< â€‹0.001) after adjustment for age, clinical risk factors, symptoms, and statin use. For any level of CCTA stenosis, mortality rates were inversely associated with the degree of patients' exercise activity. The risk of all-cause mortality was similar among the patients with obstructive stenosis with high exercise versus those with no coronary stenosis but no exercise activity (p â€‹= â€‹0.912). CONCLUSION: Physical activity as assessed by a single-item self-reported questionnaire is a strong stepwise inverse predictor of mortality risk among patients undergoing CCTA.

Association between an early revascularization strategy and major cardiac events based on left ventricular dyssynchrony in patients at intermediate risk of major cardiac events using the J-ACCESS risk model.

Objective This retrospective study aimed to investigate the association between therapeutic strategies and the development of major cardiac events (MCEs) in intermediate-risk patients by using the J-ACCESS risk model in combination with the stress phase bandwidth (SPBW), an index of left ventricular dyssynchrony. Methods Patients were followed-up for three years to confirm their prognosis. Based on the estimated propensity scores, the patients who underwent revascularization within the first 60 days after SPECT and those who did not were matched 1:1 (n = 367 per group). The composite endpoint was the occurrence of MCEs, consisting of cardiac death, non-fatal myocardial infarction, and severe heart failure. SPBW was calculated by a phase analysis using the Heart Risk View-F software program, and the MCE rate was compared between the two groups by applying the normal value of SPBW (38°). Patients The study included 2,053 patients with either known or suspected CAD who underwent electrocardiogram-gated single-photon emission computed tomography myocardial perfusion imaging and were at intermediate risk of MCE according to the J-ACCESS risk model. Results During follow-up, 54 of the 734 patients (7.4%) experienced MCEs. The overall incidence of MCE in intermediate-risk patients was not significantly different between the two groups. However, the incidence of MCE in patients with an abnormal SPBW was significantly lower in those who underwent early revascularization (4.8% vs. 11.9%, P = 0.0407). Conclusion The combination of the J-ACCESS risk model and the SPBW is thus considered to be an optimal treatment strategy for patients at intermediate risk of MCE, and early revascularization may lead to an improved prognosis in intermediate-risk patients with an abnormal SPBW.

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.

Automated Motion Correction for Myocardial Blood Flow Measurements and Diagnostic Performance of 82Rb PET Myocardial Perfusion Imaging.

Motion correction (MC) affects myocardial blood flow (MBF) measurements in 82Rb PET myocardial perfusion imaging (MPI); however, frame-by-frame manual MC of dynamic frames is time-consuming. This study aims to develop an automated MC algorithm for time-activity curves used in compartmental modeling and compare the predictive value of MBF with and without automated MC for significant coronary artery disease (CAD). Methods: In total, 565 patients who underwent PET-MPI were considered. Patients without angiographic findings were split into training (n = 112) and validation (n = 112) groups. The automated MC algorithm used simplex iterative optimization of a count-based cost function and was developed using the training group. MBF measurements with automated MC were compared with those with manual MC in the validation group. In a separate cohort, 341 patients who underwent PET-MPI and invasive coronary angiography were enrolled in the angiographic group. The predictive performance in patients with significant CAD (≥70% stenosis) was compared between MBF measurements with and without automated MC. Results: In the validation group (n = 112), MBF measurements with automated and manual MC showed strong correlations (r = 0.98 for stress MBF and r = 0.99 for rest MBF). The automatic MC took less time than the manual MC (<12 s vs. 10 min per case). In the angiographic group (n = 341), MBF measurements with automated MC decreased significantly compared with those without (stress MBF, 2.16 vs. 2.26 mL/g/min; rest MBF, 1.12 vs. 1.14 mL/g/min; MFR, 2.02 vs. 2.10; all P < 0.05). The area under the curve (AUC) for the detection of significant CAD by stress MBF with automated MC was higher than that without (AUC, 95% CI, 0.76 [0.71-0.80] vs. 0.73 [0.68-0.78]; P < 0.05). The addition of stress MBF with automated MC to the model with ischemic total perfusion deficit showed higher diagnostic performance for detection of significant CAD (AUC, 95% CI, 0.82 [0.77-0.86] vs. 0.78 [0.74-0.83]; P = 0.022), but the addition of stress MBF without MC to the model with ischemic total perfusion deficit did not reach significance (AUC, 95% CI, 0.81 [0.76-0.85] vs. 0.78 [0.74-0.83]; P = 0.067). Conclusion: Automated MC on 82Rb PET-MPI can be performed rapidly with excellent agreement with experienced operators. Stress MBF with automated MC showed significantly higher diagnostic performance than without MC.

Optimization of 201Tl Dosage in a Simultaneous Acquisition Rest 99mTc/Stress 201Tl Dual-Isotope Myocardial Perfusion Single-Photon Emission Computed Tomography with Semiconductor Gamma Camera.

Background: The use of 201Tl in myocardial perfusion single-photon emission computed tomography (SPECT) is predominantly not recommended because of the higher radiation exposure of 201Tl compared to 99mTc agent. However, the advent of new gamma cameras with semiconductor detectors has made it possible to reduce the 201Tl dose and lower radiation exposure. In our hospital, the dose of 201Tl is adjusted according to the patient's body mass index (BMI), with 50 MBq for BMI<25 and 74 MBq for BMI≥25. The dose of 201Tl during simultaneous acquisition dual-isotope myocardial perfusion SPECT (MPS; stress 201Tl and rest 99mTc agent) exceeds 9 mSv/examination when 74 MBq of 201Tl is administered. In order to further reduce the radiation dose, optimization of the 201Tl dose was investigated. Methods: Two hundred and eighty consecutive patients who underwent stress MPS using simultaneous acquisition dual-isotope protocol (SDI protocol) for the estimation of ischemic heart disease were included. Patients with prior myocardial infarction were excluded. Correlations between BMI and acquisition time were determined in patients receiving 50 MBq (n=154) or 74 MBq (n=126) of 201Tl. In addition, linear regression analysis was used to determine the slope and intercept to derive a linear functional equation, and the theoretically optimal 201Tl dose was evaluated. Results: The correlation coefficient between BMI and acquisition time in the 201Tl 50 MBq group was 0.532 (P< 0.00001) and in the 201Tl 74 MBq group was 0.478 (P<0.00001), both showing a positive correlation. Linear regression analysis yielded two equations: y=0.52x-0.32 (201Tl 50 MBq group) and y=0.41x-0.69 (201Tl 74 MBq group). Linear function equation results indicated that patients with BMI between 25 and 30 could be examined within approximately 15 minutes with 50 MBq of 201Tl. Conclusion: Considering examination efficiency, a single acquisition time of less than 15 minutes is ideal. Theoretically, patients with BMI less than 30 could be examined within approximately 15 minutes with 50 MBq of 201Tl.

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.

Cardiac Computed Tomography for Quantification of Myocardial Extracellular Volume Fraction: A Systematic Review and Meta-Analysis.

BACKGROUND: Extracellular volume (ECV) is a quantitative measure of extracellular compartment expansion, and an increase in ECV is a marker of myocardial fibrosis. Although cardiac magnetic resonance (CMR) is considered the standard imaging tool for ECV quantification, cardiac computed tomography (CT) has also been used for ECV assessment. OBJECTIVES: The aim of this meta-analysis was to evaluate the correlation and agreement in the quantification of myocardial ECV by CT and CMR. METHODS: PubMed and Web of Science were searched for relevant publications reporting on the use of CT for ECV quantification compared with CMR as the reference standard. The authors employed a meta-analysis using the restricted maximum-likelihood estimator with a random-effects method to estimate summary correlation and mean difference. A subgroup analysis was performed to compare the correlation and mean differences between single-energy CT (SECT) and dual-energy CT (DECT) techniques for the ECV quantification. RESULTS: Of 435 papers, 13 studies comprising 383 patients were identified. The mean age range was 57.3 to 82 years, and 65% of patients were male. Overall, there was an excellent correlation between CT-derived ECV and CMR-derived ECV (mean: 0.90 [95% CI: 0.86-0.95]). The pooled mean difference between CT and CMR was 0.96% (95% CI: 0.14%-1.78%). Seven studies reported correlation values using SECT, and 4 studies reported those using DECT. The pooled correlation from studies utilizing DECT for ECV quantification was significantly higher compared with those with SECT (mean: 0.94 [95% CI: 0.91-0.98] vs 0.87 [95% CI: 0.80-0.94], respectively; P = 0.01). There was no significant difference in pooled mean differences between SECT vs DECT (P = 0.85). CONCLUSIONS: CT-derived ECV showed an excellent correlation and mean difference of <1% with CMR-derived ECV. However, the overall quality of the included studies was low, and larger, prospective studies are needed to examine the accuracy and diagnostic and prognostic utility of CT-derived ECV.

Usefulness of phase analysis on ECG gated single photon emission computed tomography myocardial perfusion imaging.

Electrocardiogram (ECG)-gated single photon emission computed tomography myocardial perfusion imaging (GSPECT-MPI) is widely used for assessing coronary artery disease. Phase analysis on GSPECT-MPI can assess left ventricular mechanical dyssynchrony quantitatively on standard GSPECT-MPI alongside myocardial perfusion and function assessment. It has been shown that phase variables by GSPECT-MPI correlate well with tissue Doppler imaging by echocardiography. Main phase variables quantified by GSPECT-MPI are entropy, bandwidth, and phase standard deviation. Although those variables are automatically obtained from several software packages including Quantitative Gated SPECT and Emory Cardiac Toolbox, the methods for their measurement vary in each package. Several studies have shown that phase analysis has predictive value for response to cardiac resynchronization therapy and prognostic value for future adverse cardiac events beyond standard GSPECT-MPI variables. In this review, we summarize the basics of phase analysis on GSPECT-MPI and usefulness of phase analysis in clinical practice.

Relationship between impaired myocardial blood flow by positron emission tomography and low-attenuation plaque burden and pericoronary adipose tissue attenuation from coronary computed tomography: From the prospective PACIFIC trial.

BACKGROUND: Positron emission tomography (PET) is the clinical gold standard for quantifying myocardial blood flow (MBF). Pericoronary adipose tissue (PCAT) attenuation may detect vascular inflammation indirectly. We examined the relationship between MBF by PET and plaque burden and PCAT on coronary CT angiography (CCTA). METHODS: This post hoc analysis of the PACIFIC trial included 208 patients with suspected coronary artery disease (CAD) who underwent [15O]H2O PET and CCTA. Low-attenuation plaque (LAP, < 30HU), non-calcified plaque (NCP), and PCAT attenuation were measured by CCTA. RESULTS: In 582 vessels, 211 (36.3%) had impaired per-vessel hyperemic MBF (≤ 2.30 mL/min/g). In multivariable analysis, LAP burden was independently and consistently associated with impaired hyperemic MBF (P = 0.016); over NCP burden (P = 0.997). Addition of LAP burden improved predictive performance for impaired hyperemic MBF from a model with CAD severity and calcified plaque burden (P < 0.001). There was no correlation between PCAT attenuation and hyperemic MBF (r = - 0.11), and PCAT attenuation was not associated with impaired hyperemic MBF in univariable or multivariable analysis of all vessels (P > 0.1). CONCLUSION: In patients with stable CAD, LAP burden was independently associated with impaired hyperemic MBF and a stronger predictor of impaired hyperemic MBF than NCP burden. There was no association between PCAT attenuation and hyperemic MBF.

Sex differences in computed tomography angiography-derived coronary plaque burden in relation to invasive fractional flow reserve.

BACKGROUND: Distinct sex-related differences exist in coronary artery plaque burden and distribution. We aimed to explore sex differences in quantitative plaque burden by coronary CT angiography (CCTA) in relation to ischemia by invasive fractional flow reserve (FFR). METHODS: This post-hoc analysis of the PACIFIC trial included 581 vessels in 203 patients (mean age 58.1 â€‹± â€‹8.7 years, 63.5% male) who underwent CCTA and per-vessel invasive FFR. Quantitative assessment of total, calcified, non-calcified, and low-density non-calcified plaque burden were performed using semiautomated software. Significant ischemia was defined as invasive FFR ≤0.8. RESULTS: The per-vessel frequency of ischemia was higher in men than women (33.5% vs. 7.5%, p â€‹< â€‹0.001). Women had a smaller burden of all plaque subtypes (all p â€‹< â€‹0.01). There was no sex difference on total, calcified, or non-calcified plaque burdens in vessels with ischemia; only low-density non-calcified plaque burden was significantly lower in women (beta: -0.183, p â€‹= â€‹0.035). The burdens of all plaque subtypes were independently associated with ischemia in both men and women (For total plaque burden (5% increase): Men, OR: 1.15, 95%CI: 1.06-1.24, p â€‹= â€‹0.001; Women, OR: 1.96, 95%CI: 1.11-3.46, p â€‹= â€‹0.02). No significant interaction existed between sex and total plaque burden for predicting ischemia (interaction p â€‹= â€‹0.108). The addition of quantitative plaque burdens to stenosis severity and adverse plaque characteristics improved the discrimination of ischemia in both men and women. CONCLUSIONS: In symptomatic patients with suspected CAD, women have a lower CCTA-derived burden of all plaque subtypes compared to men. Quantitative plaque burden provides independent and incremental predictive value for ischemia, irrespective of sex.

Effect of Atorvastatin on Microcirculation Evaluated by Vascular Occlusion Test with Peripheral Near-Infrared Spectroscopy.

The vascular occlusion test (VOT) with peripheral near-infrared spectroscopy (NIRS) is a non-invasive method to evaluate peripheral microcirculation. Statin therapy is widely used for patients with dyslipidaemia and contributes to reducing low-density lipoprotein cholesterol (LDL-C) levels and adverse cardiovascular events. However, it is not yet clear whether statin treatment improves peripheral microcirculation assessed by VOT with NIRS. In the present study, using VOT with NIRS, we evaluated the effect of statin therapy on peripheral microcirculation in patients with dyslipidaemia before and after statin therapy. METHODS: A total of six consecutive patients with dyslipidaemia who had not received statin therapy (6 males, mean age 71.8 ± 7.4 years) were enrolled. All patients were administered atorvastatin and their peripheral microcirculation assessed using VOT with NIRS (NIRO-200NX, Hamamatsu Photonics K.K., Japan) before and after statin therapy. The NIRS probe was attached to the right thenar eminence and brachial artery blood flow was blocked for 3 min at 50 mmHg above the resting systolic blood pressure. Maximum and minimum values of NIRS parameters after the VOT were used to determine concentration changes for total haemoglobin (ΔcHb), oxyhaemoglobin (ΔO2Hb), deoxyhaemoglobin (ΔHHb), and tissue oxygenation index (ΔTOI). RESULTS: During the follow-up period (mean 30.3 ± 6.5 days), LDL-C level decreased from 129.7 ± 26.3 to 67.5 ± 20.2 mg/dL (p-value = 0.031), ΔTOI increased from 24.0 ± 5.3 to 33.7 ± 6.3% (p-value = 0.023), and ΔO2Hb increased from 16.4 ± 5.3 to 20.0 ± 6.6 µmol/L (p-value = 0.007). ΔcHb and ΔHHb did not change significantly. CONCLUSION: ΔO2Hb and ΔTOI were significantly increased during the follow-up period. These findings suggest that ΔO2Hb and ΔTOI could assess the improvement of peripheral microcirculation by statin therapy. Compared to ΔTOI, ΔO2Hb seems to be a more useful parameter to evaluate peripheral microcirculation.

Machine Learning From Quantitative Coronary Computed Tomography Angiography Predicts Fractional Flow Reserve-Defined Ischemia and Impaired Myocardial Blood Flow.

BACKGROUND: A pathophysiological interplay exists between plaque morphology and coronary physiology. Machine learning (ML) is increasingly being applied to coronary computed tomography angiography (CCTA) for cardiovascular risk stratification. We sought to assess the performance of a ML score integrating CCTA-based quantitative plaque features for predicting vessel-specific ischemia by invasive fractional flow reserve (FFR) and impaired myocardial blood flow (MBF) by positron emission tomography (PET). METHODS: This post-hoc analysis of the PACIFIC trial (Prospective Comparison of Cardiac Positron Emission Tomography/Computed Tomography [CT]' Single Photon Emission Computed Tomography/CT Perfusion Imaging and CT Coronary Angiography with Invasive Coronary Angiography) included 208 patients with suspected coronary artery disease who prospectively underwent CCTA' [15O]H2O PET, and invasive FFR. Plaque quantification from CCTA was performed using semiautomated software. An ML algorithm trained on the prospective NXT trial (484 vessels) was used to develop a ML score for the prediction of ischemia (FFR≤0.80), which was then evaluated in 581 vessels from the PACIFIC trial. Thereafter, the ML score was applied for predicting impaired hyperemic MBF (≤2.30 mL/min per g) from corresponding PET scans. The performance of the ML score was compared with CCTA reads and noninvasive FFR derived from CCTA (FFRCT). RESULTS: One hundred thirty-nine (23.9%) vessels had FFR-defined ischemia, and 195 (33.6%) vessels had impaired hyperemic MBF. For the prediction of FFR-defined ischemia, the ML score yielded an area under the receiver-operating characteristic curve of 0.92, which was significantly higher than that of visual stenosis grade (0.84; P<0.001) and comparable with that of FFRCT (0.93; P=0.34). Quantitative percent diameter stenosis and low-density noncalcified plaque volume had the greatest ML feature importance for predicting FFR-defined ischemia. When applied for impaired MBF prediction, the ML score exhibited an area under the receiver-operating characteristic curve of 0.80; significantly higher than visual stenosis grade (area under the receiver-operating characteristic curve 0.74; P=0.02) and comparable with FFRCT (area under the receiver-operating characteristic curve 0.77; P=0.16). CONCLUSIONS: An externally validated ML score integrating CCTA-based quantitative plaque features accurately predicts FFR-defined ischemia and impaired MBF by PET, performing superiorly to standard CCTA stenosis evaluation and comparably to FFRCT.

Long-term Survival Benefit From Revascularization Compared With Medical Therapy in Patients With or Without Diabetes Undergoing Myocardial Perfusion Single Photon Emission Computed Tomography.

OBJECTIVE: To explore the long-term association of survival benefit from early revascularization with the magnitude of ischemia in patients with diabetes compared with those without diabetes using a large observational cohort of patients undergoing single photon emission computed tomography myocardial perfusion imaging (SPECT-MPI). RESEARCH DESIGN AND METHODS: Of 41,982 patients who underwent stress and rest SPECT-MPI from 1998 to 2017, 8,328 (19.8%) had diabetes. A propensity score was used to match 8,046 patients with diabetes to 8,046 patients without diabetes. Early revascularization was defined as occurring within 90 days after SPECT-MPI. The percentage of myocardial ischemia was assessed from the magnitude of reversible myocardial perfusion defect on SPECT-MPI. RESULTS: Over a median 10.3-year follow-up, the annualized mortality rate was higher for the patients with diabetes compared with those without diabetes (4.7 vs. 3.6%; P < 0.001). There were significant interactions between early revascularization and percent myocardial ischemia in patients with and without diabetes (all interaction P values <0.05). After adjusting for confounding variables, survival benefit from early revascularization was observed in patients with diabetes above a threshold of >8.6% ischemia and in patients without diabetes above a threshold of >12.1%. Patients with diabetes receiving insulin had a higher mortality rate (6.2 vs. 4.1%; P < 0.001), but there was no interaction between revascularization and insulin use (interaction P value = 0.405). CONCLUSIONS: Patients with diabetes, especially those on insulin treatment, had higher mortality rate compared with patients without diabetes. Early revascularization was associated with a mortality benefit at a lower ischemic threshold in patients with diabetes compared with those without diabetes.

Low alanine aminotransferase levels are independently associated with mortality risk in patients with atrial fibrillation.

Extremely low alanine aminotransferase (ALT) may reflect aging, frailty, sarcopenia, and malnutrition in several cardiovascular diseases, but the association between low ALT and patient characteristics, cardiovascular and all-cause mortality is not well investigated in the population with atrial fibrillation. We conducted a post hoc analysis of a prospective, observational multicenter study. Patients with nonvalvular AF in the SAKURA AF Registry (n = 3156) were classified into 3 tertiles according to baseline ALT: first (ALT ≤ 15 U/L, n = 1098), second (15 < ALT < 23 U/L, n = 1055), and third (ALT ≥ 23 U/L, n = 1003). The first tertile had an older age; lower body mass index (BMI); higher prevalence of heart failure; and lower hemoglobin, total cholesterol, and triglycerides (all P < 0.05). During median 39.2 months follow-up, the first tertile had significantly higher incidences of cardiovascular and all-cause mortality (log-rank P < 0.001). Lower ALT was significantly associated with the incidence of cardiovascular and all-cause mortality, even after adjusting for clinically relevant factors (P < 0.05). Low ALT may reflect aging, sarcopenia, and malnutrition and be independently associated with a high risk of all-cause mortality in patients with AF.

Explainable Deep Learning Improves Physician Interpretation of Myocardial Perfusion Imaging.

Artificial intelligence may improve accuracy of myocardial perfusion imaging (MPI) but will likely be implemented as an aid to physician interpretation rather than an autonomous tool. Deep learning (DL) has high standalone diagnostic accuracy for obstructive coronary artery disease (CAD), but its influence on physician interpretation is unknown. We assessed whether access to explainable DL predictions improves physician interpretation of MPI. Methods: We selected a representative cohort of patients who underwent MPI with reference invasive coronary angiography. Obstructive CAD, defined as stenosis ≥50% in the left main artery or ≥70% in other coronary segments, was present in half of the patients. We used an explainable DL model (CAD-DL), which was previously developed in a separate population from different sites. Three physicians interpreted studies first with clinical history, stress, and quantitative perfusion, then with all the data plus the DL results. Diagnostic accuracy was assessed using area under the receiver-operating-characteristic curve (AUC). Results: In total, 240 patients with a median age of 65 y (interquartile range 58-73) were included. The diagnostic accuracy of physician interpretation with CAD-DL (AUC 0.779) was significantly higher than that of physician interpretation without CAD-DL (AUC 0.747, P = 0.003) and stress total perfusion deficit (AUC 0.718, P < 0.001). With matched specificity, CAD-DL had higher sensitivity when operating autonomously compared with readers without DL results (P < 0.001), but not compared with readers interpreting with DL results (P = 0.122). All readers had numerically higher accuracy with CAD-DL, with AUC improvement 0.02-0.05, and interpretation with DL resulted in overall net reclassification improvement of 17.2% (95% CI 9.2%-24.4%, P < 0.001). Conclusion: Explainable DL predictions lead to meaningful improvements in physician interpretation; however, the improvement varied across the readers, reflecting the acceptance of this new technology. This technique could be implemented as an aid to physician diagnosis, improving the diagnostic accuracy of MPI.

Clinical Utility of a Slow 201Tl Washout Rate in the Detection of Multi-Vessel Coronary Artery Disease Using a Simultaneous Acquisition Rest 99 mTc/Stress 201Tl Protocol and a Semiconducting Gamma Camera.

BACKGROUND: The diagnostic accuracy of stress myocardial perfusion single-photon emission computed tomography (SPECT) to detect coronary artery disease (CAD) is reduced by the balanced reduction of myocardial perfusion in patients with multi-vessel or left main trunk CAD (multi-vessel group). This study investigated the diagnostic performance of a simultaneous acquisition rest 99 mTc/stress 201Tl dual-isotope protocol for myocardial perfusion SPECT (MPS) in a multi-vessel group by examining the assessment of a slow 201Tl washout rate (WR) finding in comparison to the accuracy of perfusion assessments.Methods and Results: This study enrolled 91 patients who had undergone angiography within 3 months after MPS. The diagnostic performances of perfusion assessments and a slow 201Tl WR parameter were compared using the area under the curve (AUC) in a multi-vessel group of patients with mild ischemia (2≤summed difference score [SDS]≤7). The AUC of a slow WR parameter was significantly larger compared with that for perfusion assessments, in patients with mild ischemia, (AUC, 0.736 vs. 0.504-0.558, P value: <0.01-0.05). CONCLUSIONS: Among patients with mild ischemia, a slow 201Tl WR parameter improved the detection of CAD in a multi-vessel group.

Deep learning-enabled coronary CT angiography for plaque and stenosis quantification and cardiac risk prediction: an international multicentre study.

BACKGROUND: Atherosclerotic plaque quantification from coronary CT angiography (CCTA) enables accurate assessment of coronary artery disease burden and prognosis. We sought to develop and validate a deep learning system for CCTA-derived measures of plaque volume and stenosis severity. METHODS: This international, multicentre study included nine cohorts of patients undergoing CCTA at 11 sites, who were assigned into training and test sets. Data were retrospectively collected on patients with a wide range of clinical presentations of coronary artery disease who underwent CCTA between Nov 18, 2010, and Jan 25, 2019. A novel deep learning convolutional neural network was trained to segment coronary plaque in 921 patients (5045 lesions). The deep learning network was then applied to an independent test set, which included an external validation cohort of 175 patients (1081 lesions) and 50 patients (84 lesions) assessed by intravascular ultrasound within 1 month of CCTA. We evaluated the prognostic value of deep learning-based plaque measurements for fatal or non-fatal myocardial infarction (our primary outcome) in 1611 patients from the prospective SCOT-HEART trial, assessed as dichotomous variables using multivariable Cox regression analysis, with adjustment for the ASSIGN clinical risk score. FINDINGS: In the overall test set, there was excellent or good agreement, respectively, between deep learning and expert reader measurements of total plaque volume (intraclass correlation coefficient [ICC] 0·964) and percent diameter stenosis (ICC 0·879; both p<0·0001). When compared with intravascular ultrasound, there was excellent agreement for deep learning total plaque volume (ICC 0·949) and minimal luminal area (ICC 0·904). The mean per-patient deep learning plaque analysis time was 5·65 s (SD 1·87) versus 25·66 min (6·79) taken by experts. Over a median follow-up of 4·7 years (IQR 4·0-5·7), myocardial infarction occurred in 41 (2·5%) of 1611 patients from the SCOT-HEART trial. A deep learning-based total plaque volume of 238·5 mm3 or higher was associated with an increased risk of myocardial infarction (hazard ratio [HR] 5·36, 95% CI 1·70-16·86; p=0·0042) after adjustment for the presence of deep learning-based obstructive stenosis (HR 2·49, 1·07-5·50; p=0·0089) and the ASSIGN clinical risk score (HR 1·01, 0·99-1·04; p=0·35). INTERPRETATION: Our novel, externally validated deep learning system provides rapid measurements of plaque volume and stenosis severity from CCTA that agree closely with expert readers and intravascular ultrasound, and could have prognostic value for future myocardial infarction. FUNDING: National Heart, Lung, and Blood Institute and the Miriam & Sheldon G Adelson Medical Research Foundation.

Association of Plaque Location and Vessel Geometry Determined by Coronary Computed Tomographic Angiography With Future Acute Coronary Syndrome-Causing Culprit Lesions.

IMPORTANCE: Distinct plaque locations and vessel geometric features predispose to altered coronary flow hemodynamics. The association between these lesion-level characteristics assessed by coronary computed tomographic angiography (CCTA) and risk of future acute coronary syndrome (ACS) is unknown. OBJECTIVE: To examine whether CCTA-derived adverse geometric characteristics (AGCs) of coronary lesions describing location and vessel geometry add to plaque morphology and burden for identifying culprit lesion precursors associated with future ACS. DESIGN, SETTING, AND PARTICIPANTS: This substudy of ICONIC (Incident Coronary Syndromes Identified by Computed Tomography), a multicenter nested case-control cohort study, included patients with ACS and a culprit lesion precursor identified on baseline CCTA (n = 116) and propensity score-matched non-ACS controls (n = 116). Data were collected from July 20, 2012, to April 30, 2017, and analyzed from October 1, 2020, to October 31, 2021. EXPOSURES: Coronary lesions were evaluated for the following 3 AGCs: (1) distance from the coronary ostium to lesion; (2) location at vessel bifurcations; and (3) vessel tortuosity, defined as the presence of 1 bend of greater than 90° or 3 curves of 45° to 90° using a 3-point angle within the lesion. MAIN OUTCOMES AND MEASURES: Association between lesion-level AGCs and risk of future ACS-causing culprit lesions. RESULTS: Of 548 lesions, 116 culprit lesion precursors were identified in 116 patients (80 [69.0%] men; mean [SD], age 62.7 [11.5] years). Compared with nonculprit lesions, culprit lesion precursors had a shorter distance from the ostium (median, 35.1 [IQR, 23.6-48.4] mm vs 44.5 [IQR, 28.2-70.8] mm), more frequently localized to bifurcations (85 [73.3%] vs 168 [38.9%]), and had more tortuous vessel segments (5 [4.3%] vs 6 [1.4%]; all P < .05). In multivariable Cox regression analysis, an increasing number of AGCs was associated with a greater risk of future culprit lesions (hazard ratio [HR] for 1 AGC, 2.90 [95% CI, 1.38-6.08]; P = .005; HR for ≥2 AGCs, 6.84 [95% CI, 3.33-14.04]; P < .001). Adverse geometric characteristics provided incremental discriminatory value for culprit lesion precursors when added to a model containing stenosis severity, adverse morphological plaque characteristics, and quantitative plaque characteristics (area under the curve, 0.766 [95% CI, 0.718-0.814] vs 0.733 [95% CI, 0.685-0.782]). In per-patient comparison, patients with ACS had a higher frequency of lesions with adverse plaque characteristics, AGCs, or both compared with control patients (≥2 adverse plaque characteristics, 70 [60.3%] vs 50 [43.1%]; ≥2 AGCs, 92 [79.3%] vs 60 [51.7%]; ≥2 of both, 37 [31.9%] vs 20 [17.2%]; all P < .05). CONCLUSIONS AND RELEVANCE: These findings support the concept that CCTA-derived AGCs capturing lesion location and vessel geometry are associated with risk of future ACS-causing culprit lesions. Adverse geometric characteristics may provide additive prognostic information beyond plaque assessment in CCTA.

Implication of thoracic aortic calcification over coronary calcium score regarding the 2018 ACC/AHA Multisociety cholesterol guideline: results from the CAC Consortium.

OBJECTIVE: TAC is associated with an increased atherosclerotic cardiovascular disease (ASCVD) risk, but it is unclear how to interpret thoracic aortic calcification (TAC) findings in conjunction with ASCVD risk and coronary artery calcium (CAC) score according to 2018 ACC/AHA Multisociety cholesterol guidelines. We evaluate the incremental value of thoracic aortic calcification TAC over CAC for predicting and reclassifying ASCVD mortality risk. METHOD: The study included 30,630 asymptomatic individuals (mean age: 55 ± 8 years, male: 64%) from the CAC Consortium. TAC was categorized as TAC 0, 1-300, and >300. Patients were categorized as low (<5%), borderline (5-7.5%), intermediate (7.5-20%), or high (≥20%) 10-year ASCVD risk according to the Pooled Cohorts Equation. In the intermediate risk group, the utility of TAC beyond CAC for statin eligibility was assessed according to the guideline. CAC was categorized as CAC=0 (no statin), CAC 1-100 (favors statin), or CAC>100 (initiate stain). RESULTS: During the median 11.2 years (IQR 9.2-12.4) follow-up, 345 (1.1%) CVD deaths occurred. TAC>300 was associated with increased CVD mortality after adjusting for ASCVD risk and CAC (HR:4.72, 95% CI: 3.39-6.57, p<0.001). In borderline and intermediate risk groups, TAC improved discrimination when added to a model included ASCVD risk and CAC (C-statistic: 0.77 vs. 0.68 in borderline group; 0.67 vs. 0.63 in intermediate group, both p < 0.05). The addition of TAC over CAC improved risk reclassification in borderline, intermediate and high-risk groups (categorical net reclassification index: 0.40, 0.29, and 0.49, respectively, all p < 0.001). Of intermediate risk participants for whom consideration of CAC was recommended based on the guideline, TAC >300 was associated with an increased CVD mortality risk across each statin eligibility group (all p < 0.001, compared to TAC 0). CONCLUSION: TAC was independently associated with CVD death. Among individuals with borderline or intermediate ASCVD risk, a TAC threshold of 300 may provide added prognostic and reclassification value beyond the current guideline-based approach.