Image testing based on biomedical drug loading in cardiovascular drug care simulation for coronary heart disease.

Coronary heart disease is a common cardiovascular disease, and its therapeutic effect is affected by the distribution and absorption of drugs in the body. Biomedical drug-carrying image testing technology can provide a quantitative assessment of drug distribution and absorption in the body. This study aims to explore the application of biomedical drug-carrying image testing technology in the simulation of cardiovascular drug care in coronary heart disease, so as to provide reference for the optimization of drug treatment plan and individualized treatment. The study collected clinical data and medication regiments of patients with coronary heart disease. Then, the imaging examination of patients was carried out by selecting appropriate drug loading markers using the biomedical drug loading image examination technology. Then quantitative analysis was used to process the image data to quantitatively evaluate the distribution and absorption of drugs in the cardiovascular system. The quantitative data of drug distribution and absorption in patients with coronary heart disease have been obtained successfully by means of biomedical imaging. These data reveal the dynamic changes of drugs in the cardiovascular system, and help doctors optimize drug therapy, improve treatment effectiveness, and achieve personalized treatment.

Associations of Abdominal Muscle Density and Area and Incident Cardiovascular Disease, Coronary Heart Disease, and Stroke: The Multi-Ethnic Study of Atherosclerosis.

BACKGROUND: Muscle density is inversely associated with all-cause mortality, but associations with cardiovascular disease (CVD) risk are not well understood. This study evaluated the association between muscle density and muscle area and incident total CVD, coronary heart disease (CHD), and stroke in diverse men and women. METHODS AND RESULTS: Adult participants (N=1869) in the Multi-Ethnic Study of Atherosclerosis Ancillary Body Composition Study underwent computer tomography scans of the L2-L4 region of the abdomen. Muscle was quantified by density (Hounsfield units) and area in cm2. Sex-stratified Cox proportional hazard models assessed associations between incident total CVD, incident CHD, and incident stroke across sex-specific percentiles of muscle area and density, which were entered simultaneously into the model. Mean age for men and women at baseline were 64.1 and 65.1 years, respectively, and median follow-up time was 10.3 years. For men, associations between muscle density and incident CVD were inverse but not significant in fully adjusted models (P trend=0.15). However, there was an inverse association between density and CHD (P trend=0.02; HR, 0.26 for 95th versus 10th percentile), and no association with stroke (P trend=0.78). Conversely, for men, there was a strong positive association between muscle area and incident CVD (HR, 4.19 for 95th versus 10th percentile; P trend<0.001). Associations were stronger for CHD (HR, 6.18 for 95th versus 10th percentile; P trend<0.001), and null for stroke (P trend=0.67). Associations for women were mostly null. CONCLUSIONS: For men, abdominal muscle density is associated with lower CHD risk, whereas greater muscle area is associated with markedly increased risk of CHD.

Rendimiento diagnóstico de un nuevo software de aprendizaje profundo para corrección de atenuación en la imagen de perfusión miocárdica utilizando una cámara CZT cardiodedicada. Experiencia en la práctica clínica / Diagnostic performance of a novel deep learning attenuation correction software for MPI using a cardio dedicated CZT camera: Experience in the clinical practice

Objetivo Evaluar el rendimiento diagnóstico de un nuevo software de aprendizaje profundo para corrección de atenuación (SAPCA) en imágenes de perfusión miocárdica (IPM) utilizando una cámara cardiodedicada de cadmio-cinc-telurio (CZT) con correlación con angiografía coronaria (AC) para el diagnóstico de enfermedad arterial coronaria (EAC) en una población de alto riesgo. Métodos Estudio retrospectivo de 300 pacientes (196 varones [65%], edad media de 68 años) desde septiembre de 2014 hasta octubre de 2019. Posteriormente realizaron una IPM, seguida de AC dentro de los 6 meses posteriores a la IPM. La probabilidad media pretest para EAC según los criterios de la Sociedad Europea de Cardiología fue del 37%. La IPM se realizó en una cámara CZT cardio dedicada (D-SPECT® Spectrum Dynamics) usando un protocolo de 2 días, de acuerdo con las guías de la Sociedad Europea de Medicina Nuclear (EANM). La IPM fue evaluada con y sin el SAPCA. Resultados La precisión diagnóstica global de la IPM sin el SAPCA para identificar pacientes con cualquier EAC obstructiva en la AC fue del 87%, sensibilidad del 94%, especificidad del 57%, valor predictivo positivo del 91% y valor predictivo negativo del 64%. Utilizando el SAPCA, la precisión diagnóstica global fue del 90%, la sensibilidad del 91%, la especificidad del 86%, el valor predictivo positivo del 97% y el valor predictivo negativo del 66%. Conclusión El uso del novel SAPCA mejora el rendimiento diagnóstico de la IPM usando la cámara CZT D-SPECT®, especialmente reduciendo el número de resultados falsos positivos al reducir los artefactos (AU)

urpose To evaluate the diagnostic performance of a novel deep learning attenuation correction software (SAPCA) for myocardial perfusion imaging (MPI) using a cadmium-zinc-telluride (CZT) cardio dedicated camera with invasive coronary angiography (ICA) correlation for the diagnosis of coronary artery disease (CAD) in a high-risk population. Methods Retrospective study of 300 patients (196 males [65%], mean age 68 years) from September 2014 to October 2019 undergoing MPI, followed by ICA and evaluated by means of quantitative angiography software, within six months after the MPI. The mean pre-test probability score for coronary disease according to the European Society of Cardiology criteria was 37% for the whole cohort. The MPI was performed in a dedicated CZT cardio camera (D-SPECT® Spectrum Dynamics) with a two-day protocol, according to the European Association of Nuclear Medicine guidelines. MPI was retrospectively evaluated with and without the SAPCA. Results The overall diagnostic accuracy of MPI without SAPCA to identify patients with any obstructive CAD at ICA was 87%, Sensitivity 94%, Specificity 57%, positive predictive value 91% and negative predictive value 64%. Using SAPCA the overall diagnostic accuracy was 90%, sensitivity 91%, specificity 86%, positive predictive value 97% and negative predictive value 66%. Conclusion Use of the novel SAPCA enhances performance of the MPI using the CZT D-SPECT® camera and achieves improved results, especially avoiding artefacts and reducing the number of false positive results (AU)

Rendimiento diagnóstico de diferentes protocolos de estrés cardiaco usados en imagen de perfusión miocárdica para el diagnóstico de enfermedad coronaria usando una cámara de cadmio-zinc-telurio con correlación con angiografía coronaria / Diagnostic performance of different cardiac stress protocols for myocardial perfusion imaging for the diagnosis of coronary artery disease using a cadmium-zinc-telluride camera with invasive coronary angiography correlation

Objetivo Evaluar el rendimiento diagnóstico de tres protocolos diferentes de estrés cardiaco utilizados en imagen de perfusión miocárdica (IPM), usando una cámara de cadmio-zinc-telurio (CZT) en correlación con angiografía coronaria (AC) para el diagnóstico de enfermedad arterial coronaria (EAC) en una población de alto riesgo. Métodos Estudio retrospectivo realizado en 263 pacientes (96 mujeres y 167 varones, edad media 68 años), de los cuales 119 realizaron una prueba de estrés con bicicleta (PEB), 113 una prueba de estrés farmacológica (PEF) y 31 una combinación de ambas (PEC), entre septiembre de 2014 y diciembre de 2018. Posteriormente realizaron una IPM, seguida de AC dentro de los seis meses posteriores a la IPM. La probabilidad preprueba media para EAC según los criterios de la Sociedad Europea de Cardiología fue de 36%. La IPM se realizó en una cámara CZT cardio dedicada (D-SPECT Spectrum Dynamics) con un protocolo de dos días, de acuerdo con las guías de la Asociación Europea de Medicina Nuclear (EANM). Resultados No se observaron diferencias significativas entre los diferentes protocolos de estrés en términos de precisión diagnóstica (PEB 85%, PEF 88%, PEC 84%). La exactitud diagnóstica general de IPM para identificar pacientes con cualquier EAC obstructiva en AC fue de 86%, sensibilidad de 93%, especificidad de 54%, VPP de 90% y VPN de 63%. Conclusión La cámara CZT D-SPECT logra resultados generales satisfactorios en el diagnóstico de la EAC, sin encontrar diferencias significativas en el rendimiento diagnóstico cuando la prueba de esfuerzo se realizó como PEB, PEF o PEC. (AU)

Purpose To evaluate the diagnostic performance of three different cardiac stress protocols for myocardial perfusion imaging (MPI) using a cadmium-zinc-telluride (CZT) camera with invasive coronary angiography (ICA) correlation for the diagnosis of coronary artery disease in a high risk population. Methods Retrospective study of 263 patients (96 women and 167 males, mean age 68 years) from which 119 patients performed a bicycle stress test (BST), 113 pharmacological stress test (PST) and 31 a combination of the two (CST) between September 2014 and December 2018. The patients then underwent myocardial perfusion imaging (MPI), followed by ICA and evaluated by means of quantitative angiography software, within six months after the MPI. The mean pre-test probability score for coronary disease according to the European Society of Cardiology criteria was 36% for the whole population. The MPI was performed in a dedicated CZT cardio camera (D-SPECT Spectrum Dynamics) with a two-day protocol, according to the European Association of Nuclear Medicine guidelines. Results No significant difference was observed between the three stress protocols in terms of diagnostic accuracy (BST 85%, PST 88% and CST 84%). The overall diagnostic accuracy of MPI to identify patients with any obstructive CAD at ICA was 86%, Sensitivity 93%, Specificity 54%, PPV 90% and NPV 63%. Conclusion The CZT D-SPECT camera achieves overall satisfactory results in the diagnosis of CAD, observing no significant differences in the diagnostic performance when the stress test was performed as a BST, PST or CST (AU)

Valor pronóstico a 10 años de la angiografía coronaria por TAC en pacientes asintomáticos con diabetes tipo 2 / Ten-year prognostic value of coronary CT angiography in asymptomatic patients with type 2 diabetes

Introducción y objetivos: La escala UKPDS (acrónimo inglés de «Estudio Prospectivo de Diabetes del Reino Unido») tiene un valor limitado para la predicción de eventos de enfermedad arterial coronaria (EAC). El estudio pretende investigar el valor añadido de la angiografía coronaria por tomografía computarizada (ACTC) sobre la escala de riesgo UKPDS para la predicción a 10 años de eventos cardiacos adversos en pacientes asintomáticos con diabetes tipo 2. Métodos: Se evaluó a 589 pacientes diabéticos asintomáticos sin historia de EAC a quienes se les realizó una ACTC. El objetivo principal estaba compuesto por muerte cardiaca, infarto de miocardio no mortal, angina inestable que requiere hospitalización y revascularización. Se estimó la habilidad de discriminación y reclasificación para modelos de predicción que incluían combinaciones de la categoría UKPDS, gravedad de estenosis y puntuación de calcio arterial coronario por ACTC. Resultados: La incidencia del objetivo primario fue del 12,4%. A lo largo de 10 años de seguimiento, los pacientes sin placa ateroesclerótica por ACTC tendieron a tener un bajo ratio de eventos coronarios en tanto que aquellos con EAC obstructiva tuvieron una mayor ratio de eventos, independientemente de la categoría de riesgo de la escala UKPDS. EL modelo que solo incluyó la categoría UKPDS tuvo un índice C de Harrell de 0,658; añadiendo el grado de estenosis coronaria al modelo se incrementó significativamente el índice C en 0,066 (p=0,004), en tanto que la adición del CSC incrementó el índice C en solo 0,039 (p=0,056). Globalmente, la información de la ACTC añadida a la categoría de riesgo UKPDS mejoró el ratio de reclasificación para la predicción del objetivo primario. Conclusiones: En pacientes asintomáticos con diabetes tipo 2, la información de la ACTC para EAC...(AU)

Introduction and objectives: The United Kingdom Prospective Diabetes Study (UKPDS) risk score has limited value for predicting coronary artery disease (CAD) events. We investigated the additive value of coronary computed tomography angiography (CCTA) on top of the UKPDS risk score in predicting 10-year adverse cardiac events in asymptomatic patients with type 2 diabetes. Methods: We evaluated 589 asymptomatic diabetic patients without a history of CAD who underwent CCTA. The primary outcome was a composite of cardiac death, nonfatal myocardial infarction, unstable angina requiring hospitalization, and revascularization. We estimated the discrimination and reclassification ability for the prediction models, which included combinations of the UKPDS category, severity of stenosis, and coronary artery calcium score by CCTA. Results: The incidence of the primary outcome was 12.4%. During 10 years of follow-up, patients without plaque by CCTA tended to have a low CAD event rate, while those with obstructive CAD tended to have a high event rate, irrespective of the baseline UKPDS risk category. The model that included only the UKPDS category had a Harrell's c-index of 0.658; adding the degree of stenosis to the model significantly increased the c-index by 0.066 (P=.004), while adding coronary artery calcium score increased the c-index by only 0.039 (P=.056). Overall, CCTA information in addition to the UKPDS risk category improved the reclassification rate for predicting the primary outcome. Conclusions: In asymptomatic patients with type 2 diabetes, CCTA information for CAD provided significant incremental discriminatory power beyond the UKPDS risk score category for predicting 10-year adverse coronary events.(AU)

Changes and Significance of 2D-STI and Right Ventricular Function Parameters in Evaluating Cardiac Function in Patients with Coronary Heart Disease and Atrial Fibrillation.

Objective: To investigate the changes and clinical significance of two-dimensional speckle tracking imaging (2D-STI) and echocardiography in patients with coronary heart disease (CHD) and atrial fibrillation (AF). Methods: In this study, 102 patients with CHD accompanied by AF were selected as the case group, and 100 patients with CHD but without AF were selected as the control group. All patients received conventional echocardiography and 2D-STI, and the right heart function parameters and right heart strain parameters were compared. The relationship between the above indicators and the occurrence of adverse endpoint events in patients from the case group was analyzed by a logistic regression model. Results: The values of right ventricular ejection fraction (RVEF), right ventricular systolic volume (RVSV), and tricuspid valve systolic displacement (TAPSE) in the case group were lower than those in the control group, and the differences were statistically significant (P < .05). The values of right ventricular end-diastolic volume (RVEDV) and right ventricular end-systolic volume (RVESV) in the case group were higher than those in the control group, and the differences were statistically significant (P < .05). The values of right ventricular longitudinal strain in the basal segment (RVLSbas), right ventricular longitudinal strain in the middle segment (RVLSmid), right ventricular longitudinal strain in the apical segment (RVLSapi), and right ventricular longitudinal strain in the free wall (RVLSfw) in the case group were higher than those in the control group, and the differences were statistically significant (P < .05). The number of coronary lesions ≥2 branches, cardiac function class ≥III, coronary stenosis ≥70%, reduced RVEF, increased RVLSbas, RVLSmid, RVLSapi, and RVLSfw were found to be independent risk factors for adverse endpoint events in patients with CHD and AF (P < 0.05). Conclusion: In patients with CHD accompanied by AF, the right ventricular systolic function and myocardial longitudinal strain capacity decreases, and the decreased right ventricular function was closely related to the occurrence of adverse endpoint events.

Coronary Artery Calcium Score and Polygenic Risk Score for the Prediction of Coronary Heart Disease Events.

Importance: Coronary artery calcium score and polygenic risk score have each separately been proposed as novel markers to identify risk of coronary heart disease (CHD), but no prior studies have directly compared these markers in the same cohorts. Objective: To evaluate change in CHD risk prediction when a coronary artery calcium score, a polygenic risk score, or both are added to a traditional risk factor-based model. Design, Setting, and Participants: Two observational population-based studies involving individuals aged 45 years through 79 years of European ancestry and free of clinical CHD at baseline: the Multi-Ethnic Study of Atherosclerosis (MESA) study involved 1991 participants at 6 US centers and the Rotterdam Study (RS) involved 1217 in Rotterdam, the Netherlands. Exposure: Traditional risk factors were used to calculate CHD risk (eg, pooled cohort equations [PCEs]), computed tomography for the coronary artery calcium score, and genotyped samples for a validated polygenic risk score. Main Outcomes and Measures: Model discrimination, calibration, and net reclassification improvement (at the recommended risk threshold of 7.5%) for prediction of incident CHD events were assessed. Results: The median age was 61 years in MESA and 67 years in RS. Both log (coronary artery calcium+1) and polygenic risk score were significantly associated with 10-year risk of incident CHD (hazards ratio per SD, 2.60; 95% CI, 2.08-3.26 and 1.43; 95% CI, 1.20-1.71, respectively), in MESA. The C statistic for the coronary artery calcium score was 0.76 (95% CI, 0.71-0.79) and for the polygenic risk score, 0.69 (95% CI, 0.63-0.71). The change in the C statistic when each was added to the PCEs was 0.09 (95% CI, 0.06-0.13) for the coronary artery calcium score, 0.02 (95% CI, 0.00-0.04) for the polygenic risk score, and 0.10 (95% CI, 0.07-0.14) for both. Overall categorical net reclassification improvement was significant when the coronary artery calcium score (0.19; 95% CI, 0.06-0.28) but was not significant when the polygenic risk score (0.04; 95% CI, -0.05 to 0.10) was added to the PCEs. Calibration of the PCEs and models with coronary artery calcium and/or polygenic risk scores was adequate (all χ2<20). Subgroup analysis stratified by the median age demonstrated similar findings. Similar findings were observed for 10-year risk in RS and in longer-term follow-up in MESA (median, 16.0 years). Conclusions and Relevance: In 2 cohorts of middle-aged to older adults from the US and the Netherlands, the coronary artery calcium score had better discrimination than the polygenic risk score for risk prediction of CHD. In addition, the coronary artery calcium score but not the polygenic risk score significantly improved risk discrimination and risk reclassification for CHD when added to traditional risk factors.

On the nonlinear relationship between wall shear stress topology and multi-directionality in coronary atherosclerosis.

BACKGROUND AND OBJECTIVE: In this paper we investigate twelve multi-directional/topological wall shear stress (WSS) derived metrics and their relationships with the formation of coronary plaques in both computational fluid dynamics (CFD) and dynamic fluid-structure interaction (FSI) frameworks. While low WSS is one of the most established biomechanical markers associated with coronary atherosclerosis progression, alone it is limited. Multi-directional and topological WSS derived metrics have been shown to be important in atherosclerosis related mechanotransduction and near-wall transport processes. However, the relationships between these twelve WSS metrics and the influence of both FSI simulations and coronary dynamics is understudied. METHODS: We first investigate the relationships between these twelve WSS derived metrics, stenosis percentage and lesion length through a parametric, transient CFD study. Secondly, we extend the parametric study to FSI, both with and without the addition of coronary dynamics, and assess their correlations. Finally, we present the case of a patient who underwent invasive coronary angiography and optical coherence tomography imaging at two time points 18 months apart. Associations between each of the twelve WSS derived metrics in CFD, static FSI and dynamic FSI simulations were assessed against areas of positive/negative vessel remodelling, and changes in plaque morphology. RESULTS: 22-32% stenosis was the threshold beyond which adverse multi-directional/topological WSS results. Each metric produced a different relationship with changing stenoses and lesion length. Transient haemodynamics was impacted by coronary dynamics, with the topological shear variation index suppressed by up to 94%. These changes appear more critical at smaller stenosis levels, suggesting coronary dynamics could play a role in the earlier stages of atherosclerosis development. In the patient case, both dynamics and FSI vs CFD changes altered associations with measured changes in plaque morphology. An appendix of the linear fits between the various FSI- and CFD-based simulations is provided to assist in scaling CFD-based results to resemble the compliant walled characteristics of FSI more accurately. CONCLUSIONS: These results highlight the potential for coronary dynamics to alter multi-directional/topological WSS metrics which could impact associations with changes in coronary atherosclerosis over time. These results warrant further investigation in a wider range of morphological settings and longitudinal cohort studies in the future.

Risk score for coronary heart disease (CHD-RISK) and hemodynamically significant aortic valve stenosis.

BACKGROUND AND AIM: Multiple studies have investigated the association between coronary heart disease (CHD) risk factors and aortic valve stenosis (AS). However, limited studies have explored the relationship between CHD risk scores and AS. Whether incident risk scores for coronary heart disease (CHD-RISK) may be applied to predict AS remains unclear. We aim to investigate the association between AS and CHD-RISK. METHODS AND RESULTS: We included 4791 participants (age 54.6 ± 5.0 yrs, 58.7% women, 81% were of European origin), and CHD-RISK was estimated in 1990-1992. The participants were then followed-up until December 31, 2013. The primary outcome was hemodynamic significant AS identified by Doppler echocardiography in 2011-2013. We used multivariate-logistic regression models to assess the associations between CHD-RISK and AS. During follow-up, 963 (20.1%) cases of AS were identified. Per-standard deviation (6%) increase in CHD-RISK was associated with OR 95% Cl [1.194, 95% CI 1.068 to 1.335, p = 0.002] risk of AS in the fully adjusted models. Results were similar when stratified by quintiles of CHD-RISK, using the lowest quintiles <0.94% of CHD-RISK as the reference, 0.94%-2.26%, 2.26%-4.83%, 4.83%-9.21%, and >9.21% were; 1.33 (95% CI, 0.99-1.78, p = 0.055), 1.64 (95% CI, 1.17-2.29, p = 0.004), 2.23 (95% CI, 1.49-3.32, p = <0.001), 2.66 (95% CI, 1.65-4.31, p = <0.001) respectively. CONCLUSIONS: CHD-RISK was associated with AS. CHD-RISK and AS were high in females, age ≥55 yrs, current smokers, and BMI ≥ 30 kg/m2. This investigation suggests CHD-RISK may be applied to forecast AS risk similar to CHD. Future studies are required to detect, manage, and establish better treatment strategies in these high-risk subgroups.

Clinical Predictors of Coronary Artery Ectasia.

Coronary artery ectasia (CAE) is defined as abnormal dilation of a coronary artery ≥1.5 times the normal segment. We aimed to determine the prevalence and clinical predictors of CAE. This was a prospective analysis performed on 6465 patients undergoing coronary angiography. Patients were divided based on the presence or absence of CAE and compared for angiographic characteristics and clinical risk factors. The prevalence of CAE was 7%, CAE associated with coronary artery stenosis was 5.4%, and isolated CAE was 1.6%. The mean age of presentation in CAE patients was 60 years, with male predominance (83.8%) and stable angina was the most common presentation. The left anterior descending artery (LAD) (51.7%) was the most commonly involved vessel, with diffuse ectasia more commonly seen in right coronary artery and discrete ectasia in LAD. Type 4 CAE was the most common type (92.4%). Hypertension, diabetes, smoking, dyslipidemia, and obesity were found in 62.4%, 35.3%, 45.3%, 54.9%, and 23.3%, respectively in CAE patients, with significant association with smoking (Odds Ratio = 3.06). The prevalence of CAE was 7% and was frequently associated with atherosclerotic coronary disease. Smoking was a significant predisposing factor for CAE.

Decreased Regional Spontaneous Brain Activity and Cognitive Dysfunction in Patients with Coronary Heart Disease: a Resting-state Functional MRI Study.

OBJECTIVES: Chronic coronary heart disease (CHD) is correlated with an increased risk of cognitive impairment (CI), but the mechanisms underlying these changes remain unclear. The aim of the present study was to explore the potential changes in regional spontaneous brain activities and their association with CI, to explore the pathophysiological mechanisms underlying CI in patients with CHD. MATERIALS AND METHODS: A total of 71 CHD patients and 73 matched healthy controls (HCs) were included in this study. Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) were used to assess the participants' cognitive functions. Regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuation(fALFF) values were calculated to determine regional spontaneous brain activity. Coronary artery calcium (CAC) score provides a measure of the total coronary plaque burden. Mediation analyses were performed to test whether CHD's effects on cognitive decline are mediated by decreased regional spontaneous brain activity. RESULTS: Patients with CHD had significantly lower MMSE and MoCA scores than the HCs. Compared with the HCs, the patients with CHD demonstrated significantly decreased ReHo and fALFF values in the bilateral medial superior frontal gyrus (SFGmed), left superior temporal gyrus (TPOsup) and left middle temporal gyrus (TPOmid). Impaired cognitive performance was positively correlated with decreased activities in the SFGmed. Mediation analyses revealed that the decreased regional spontaneous brain activity in the SFGmed played a critical role in the relationship between the increase in CAC score and the MoCA and MMSE scores. CONCLUSION: The abnormalities of spontaneous brain activity in SFGmed may provide insights into the neurological pathophysiology underlying CHD associated with cognitive dysfunction.

[A deep-learning model for the assessment of coronary heart disease and related risk factors via the evaluation of retinal fundus photographs].

Objective: To develop and validate a deep learning model based on fundus photos for the identification of coronary heart disease (CHD) and associated risk factors. Methods: Subjects aged>18 years with complete clinical examination data from 149 hospitals and medical examination centers in China were included in this retrospective study. Two radiologists, who were not aware of the study design, independently evaluated the coronary angiography images of each subject to make CHD diagnosis. A deep learning model using convolutional neural networks (CNN) was used to label the fundus images according to the presence or absence of CHD, and the model was proportionally divided into training and test sets for model training. The prediction performance of the model was evaluated in the test set using monocular and binocular fundus images respectively. Prediction efficacy of the algorithm for cardiovascular risk factors (e.g., age, systolic blood pressure, gender) and coronary events were evaluated by regression analysis using the area under the receiver operating characteristic curve (AUC) and R2 correlation coefficient. Results: The study retrospectively collected 51 765 fundus images from 25 222 subjects, including 10 255 patients with CHD, and there were 14 419 male subjects in this cohort. Of these, 46 603 fundus images from 22 701 subjects were included in the training set and 5 162 fundus images from 2 521 subjects were included in the test set. In the test set, the deep learning model could accurately predict patients' age with an R2 value of 0.931 (95%CI 0.929-0.933) for monocular photos and 0.938 (95%CI 0.936-0.940) for binocular photos. The AUC values for sex identification from single eye and binocular retinal fundus images were 0.983 (95%CI 0.982-0.984) and 0.988 (95%CI 0.987-0.989), respectively. The AUC value of the model was 0.876 (95%CI 0.874-0.877) with either monocular fundus photographs and AUC value was 0.885 (95%CI 0.884-0.888) with binocular fundus photographs to predict CHD, the sensitivity of the model was 0.894 and specificity was 0.755 with accuracy of 0.714 using binocular fundus photographs for the prediction of CHD. Conclusion: The deep learning model based on fundus photographs performs well in identifying coronary heart disease and assessing related risk factors such as age and sex.

Intracoronary Ultrasound Imaging Combined with Traditional Chinese Medicine Nursing Applied in the Treatment of Coronary Heart Disease Patients with Phlegm and Blood Stasis Syndrome.

This study was to explore the effect of traditional Chinese medicine (TCM) nursing intervention based on intracoronary ultrasound imaging on patients with coronary heart disease (CHD) and phlegm and blood stasis syndrome (PBSS). 100 hospitalized patients with CHD with Qi deficiency and blood stasis syndrome (QDBSS) were rolled into the experimental (Exp) group (routine nursing intervention) and control (Ctrl) group (TCM nursing intervention, syndrome differentiation nursing), with 50 patients in each group. They underwent the intracoronary ultrasound imaging scanning. The results showed that after intervention, the plaque load (45.08 ± 6.02%), plaque eccentricity index (0.47 ± 0.08%), vascular remodeling index (0.53 ± 0.11%), and vascular external elastic membrane area (8.67 ± 3.06 mm2) of the Exp group were notably inferior to those of the Ctrl group (60.22 ± 5.82%, 0.59 ± 0.08%, 0.71 ± 0.09%, and 10.56 ± 2.31 mm2). The total effective rate in the Exp group (88%) was greatly superior to that of the Ctrl group (68%). In terms of TCM symptom scores, the TCM symptom scores of chest pain, chest tightness, and shortness of breath in the Exp group after intervention (1.07 ± 0.21 points, 0.75 ± 0.27 points, and 0.58 ± 0.12 points) were notably inferior to those in the Ctrl group (1.62 ± 0.28 points, 1.03 ± 0.21 points, and 0.79 ± 0.14 points). In the Exp group, after intervention, the degree of physical activity limitation (67.05 ± 5.08 points), the stable state of angina pectoris (65.28 ± 3.76 points), the frequency of angina pectoris attack (85.92 ± 2.97 points), the degree of treatment satisfaction (75.39 ± 5.94 points), the cognition score of disease (63.56 ± 5.84 points), the levels of triglyceride (1.27 ± 0.41 mmol/L), and total cholesterol (2.24 ± 0.41 mmol/L) were remarkably inferior to the Ctrl group (52.97 ± 4.31 points, 50.77 ± 4.69 points, 71.36 ± 3.77 points, 64.08 ± 5.64 points, 51.77 ± 6.33 points, 2.09 ± 0.57 mmol/L, and 3.06 ± 0.84 mmol/L) (P < 0.05). It suggested that intracoronary ultrasound imaging can clearly display the coronary plaques of patients and accurately evaluate the clinical efficacy of patients with CHD. The TCM nursing program can greatly improve the angina symptoms and quality of life of patients with CHD and PBSS, reduce blood lipid levels, and effectively improve the clinical efficacy of patients.

Composite carotid intima-media thickness as a risk predictor of coronary heart disease in a selected population in Sri Lanka.

BACKGROUND: Segment-specific variations of carotid intima-media thickness (CIMT) have not been assessed in South Asian populations. The purpose of this study was to determine if segment-specific CIMTs or a composite-CIMT score is a better risk predictor of coronary heart disease in South Asian populations. METHODS: A comparative prospective study was conducted from November 2019 to October 2020 in a hospital in Colombo, Sri Lanka. Based on pre-defined inclusion and exclusion criteria, cases (having a diagnosis of Coronary Heart Disease (CHD), n = 338) and controls (non-CHD group, n = 356) were recruited. Ultrasound examination of the common carotid (CCA), the carotid bulb (CB) and the internal carotid segments (ICA) of the carotid vessels was conducted by a radiologist, and CIMTs were measured. A composite-CIMT score defined as the average value of all six segments of the left and right sides was derived. RESULTS: 694 participants were enrolled (male n = 399, 57.5%). The mean (±SD) age of the study sample was 60.2 (±9.86) years. There were variations in segment-specific values between the left and right vessels. The mean composite-CIMT value of the CHD group was significantly higher than that of the non-CHD group. A composite-CIMT score of 0.758 had a sensitivity of 98.4% and a specificity of 64.6% in distinguishing CHD from non-CHD groups (Area under the curve (AUC): 0.926). CONCLUSIONS: Carotid artery segment-specific CIMT variations were present in this population. The composite CIMT score is better than segment-specific CIMTs in predicting CHD and may be used to predict CHD in this population.

Aberrant Spontaneous Brain Activity in Coronary Heart Disease Using Fractional Amplitude of Low-Frequency Fluctuations: A Preliminary Resting-State Functional MRI Study.

Objective: This study is aimed at exploring the spontaneous brain activity changes by measuring the fractional amplitude of low-frequency fluctuations (fALFF) and their relationship with clinical characteristics in patients with coronary heart disease (CHD). Methods: Coronary heart disease patients (n = 25) and age, gender, and education level-matched control subjects (controls, n = 35) were included. The grey matter volume (GMV) and fALFF values were calculated to assess the difference in brain structure and function between the two groups, respectively. Correlation analyses between the fALFF values and clinical characteristics were further assessed in CHD patients. In addition, receiver operating characteristic (ROC) curves were conducted to access the diagnostic ability of the fALFF method. Results: There was no significant difference in GMV between the CHD and control groups. Compared with the control group, patients with CHD showed significantly decreased fALFF in the left precentral/postcentral gyrus and increased fALFF in the right inferior cerebellum. Patients with a history of myocardial infarction (MI) showed significantly decreased fALFF values of the right inferior cerebellum than patients without MI. There was no significant correlation between the fALFF values in specific brain regions and disease duration. Furthermore, the ROC curves of abnormal brain regions showed the perfect accuracy of the fALFF value in distinguishing between CHD patients and controls. Conclusion: CHD demonstrated aberrant neural activity in specific brain regions mainly related to sensorimotor networks and pain processing, which may contribute to understanding the underlying neurological mechanism of CHD.

Association between triglyceride glucose index and carotid artery plaque in different glucose metabolic states in patients with coronary heart disease: a RCSCD-TCM study in China.

BACKGROUND: The triglyceride glucose (TyG) index serves as a surrogate indicator of insulin resistance. However, there is limited evidence on the association between the TyG index and carotid artery plaque (CAP) in patients with coronary heart disease (CHD). METHODS: The 10,535 CHD patients were divided according to TyG index quartiles (Q1: TyG index < 8.52; Q2: 8.52 ≤ TyG index < 8.93; Q3: 8.93 ≤ TyG index ≤ 9.40; Q4: TyG index > 9.40). The presence or absence of CAP was determined by carotid ultrasonography. Logistic regression was used to analyze the relationship between the TyG index and CAP in CHD patients. The relationship between the TyG index and CAP in according to sex, age groups, and glucose metabolism states were also assessed. RESULTS: The baseline analysis showed that there were significant differences in related parameters among CHD patients divided into four groups according to the quartile of the TyG index. In the multi-adjusted modles, compared to Q1 of the TyG index, the odds ratios (OR) for Q4 of the TyG index for CAP were 1.37 (95% confidence interval [CI] 1.28-1.47) in CHD patients. The association between the TyG index and CAP in female (OR: 1.35; 95% CI 1.29-1.43) was higher than that in male (OR: 1.20; 95% CI 1.13-1.27). The OR value of middle-aged (≤ 60 years old) patients (OR: 1.34; 95% CI 1.26-1.42) was higher than that in elderly (> 60 years old) patients (OR: 1.16; 95% CI 1.11-1.22). In different glucose metabolism states, the TyG index of CHD patients was significantly related to the risk of CAP, with the highest OR value observed for diabetes (OR: 1.36; 95% CI 1.26-1.46). CONCLUSIONS: The TyG index and CAP showed a significant association in CHD patients. This association between TyG index and CAP in CHD patients is higher in female than in male, and the association in middle-aged and elderly patients is higher than that in elderly patients. In the condition of DM, the association between TyG index and carotid artery plaque in CHD patients is higher.

Double rule-out technique for evaluation of acute chest pain using 128-row multidetector CT.

AIM: To evaluate the feasibility and image quality of the double rule-out (DRO) technique using 128-row multidetector computed tomography (CT) for simultaneous evaluation of the aorta and coronary arteries in patients with acute non-specific chest pain. MATERIALS AND METHODS: Sixty-eight patients underwent electrocardiography (ECG)-gated coronary CT followed by non-ECG-gated abdominal CT. The contrast-to-noise ratio and signal-to-noise ratio between the vessels and adjacent perivascular fat tissue were calculated for both the aorta and coronary arteries. Dose-length products were recorded. Two blinded readers graded the image quality of the aorta and coronary arteries on a two-point and a four-point scale, respectively. In addition, the severity of coronary stenosis was independently analysed for each coronary vessel. RESULTS: The average attenuation was more than 350 HU for the aorta and >330 HU for the coronary arteries. The average (±standard deviation) volume of contrast media was 69.5 ± 12.5 ml. Interobserver agreement on the image quality of aortic and coronary data sets was perfect and substantial, respectively. There was almost perfect interobserver agreement for the all observations of the severity of coronary stenosis. CONCLUSION: The DRO technique with a standard volume (approximately 70 ml) of contrast media is useful for acute chest pain evaluation in patients suspected of having acute aortic syndrome or acute coronary syndrome. It is also accurate and safe while maintaining the average CT attenuation of the aorta and coronary arteries >330 HU.

Vessel segmentation for X-ray coronary angiography using ensemble methods with deep learning and filter-based features.

BACKGROUND: Automated segmentation of coronary arteries is a crucial step for computer-aided coronary artery disease (CAD) diagnosis and treatment planning. Correct delineation of the coronary artery is challenging in X-ray coronary angiography (XCA) due to the low signal-to-noise ratio and confounding background structures. METHODS: A novel ensemble framework for coronary artery segmentation in XCA images is proposed, which utilizes deep learning and filter-based features to construct models using the gradient boosting decision tree (GBDT) and deep forest classifiers. The proposed method was trained and tested on 130 XCA images. For each pixel of interest in the XCA images, a 37-dimensional feature vector was constructed based on (1) the statistics of multi-scale filtering responses in the morphological, spatial, and frequency domains; and (2) the feature maps obtained from trained deep neural networks. The performance of these models was compared with those of common deep neural networks on metrics including precision, sensitivity, specificity, F1 score, AUROC (the area under the receiver operating characteristic curve), and IoU (intersection over union). RESULTS: With hybrid under-sampling methods, the best performing GBDT model achieved a mean F1 score of 0.874, AUROC of 0.947, sensitivity of 0.902, and specificity of 0.992; while the best performing deep forest model obtained a mean F1 score of 0.867, AUROC of 0.95, sensitivity of 0.867, and specificity of 0.993. Compared with the evaluated deep neural networks, both models had better or comparable performance for all evaluated metrics with lower standard deviations over the test images. CONCLUSIONS: The proposed feature-based ensemble method outperformed common deep convolutional neural networks in most performance metrics while yielding more consistent results. Such a method can be used to facilitate the assessment of stenosis and improve the quality of care in patients with CAD.

Prediction of coronary heart disease based on combined reinforcement multitask progressive time-series networks.

Coronary heart disease is the first killer of human health. At present, the most widely used approach of coronary heart disease diagnosis is coronary angiography, a surgery that could potentially cause some physical damage to the patients, together with some complications and adverse reactions. Furthermore, coronary angiography is expensive thus cannot be widely used in under development country. On the other hand, the heart color Doppler echocardiography report, blood biochemical indicators and personal information, such as gender, age and diabetes, can reflect the degree of heart damage in patients to some extent. This paper proposes a combined reinforcement multitask progressive time-series networks (CRMPTN) model to predict the grade of coronary heart disease through heart color Doppler echocardiography report, blood biochemical indicators and ten basic body information items about the patients. In this model, the first step is to perform deep reinforcement learning (DRL) pre-training through asynchronous advantage actor-critic (A3C). Training data is adopted to optimize the recurrent neural network (RNN) that parameterizes the stochastic policy. In the second step, soft parameter sharing module, hard parameter sharing module and progressive time-series networks are used to predict the status of coronary heart disease. The experimental results show that after DRL pre-training, the multiple tasks in the model interact with each other and learn together to achieve satisfactory results and outperform other state-of-the-art methods.