The Role of Artificial Intelligence in Healthcare: Enhancing Coronary Computed Tomography Angiography for Coronary Artery Disease Management.

This review aims to explore the potential of artificial intelligence (AI) in coronary CT angiography (CCTA), a key tool for diagnosing coronary artery disease (CAD). Because CAD is still a major cause of death worldwide, effective and accurate diagnostic methods are required to identify and manage the condition. CCTA certainly is a noninvasive alternative for diagnosing CAD, but it requires a large amount of data as input. We intend to discuss the idea of incorporating AI into CCTA, which enhances its diagnostic accuracy and operational efficiency. Using such AI technologies as machine learning (ML) and deep learning (DL) tools, CCTA images are automated to perfection and the analysis is significantly refined. It enables the characterization of a plaque, assesses the severity of the stenosis, and makes more accurate risk stratifications than traditional methods, with pinpoint accuracy. Automating routine tasks through AI-driven CCTA will reduce the radiologists' workload considerably, which is a standard benefit of such technologies. More importantly, it would enable radiologists to allocate more time and expertise to complex cases, thereby improving overall patient care. However, the field of AI in CCTA is not without its challenges, which include data protection, algorithm transparency, as well as criteria for standardization encoding. Despite such obstacles, it appears that the integration of AI technology into CCTA in the future holds great promise for keeping CAD itself in check, thereby aiding the fight against this disease and begetting better clinical outcomes and more optimized modes of healthcare. Future research on AI algorithms for CCTA, making ethical use of AI, and thereby overcoming the technical and clinical barriers to widespread adoption of this new tool, will hopefully pave the way for profound AI-driven transformations in healthcare.

Cardiac computed tomography-derived coronary artery volume to myocardial mass in patients with severe coronary artery disease.

BACKGROUND: Coronary artery lumen volume (V) to myocardial mass (M) ratio (V/M) can show the mismatch between epicardial coronary arteries and the underlying myocardium. METHODS: The V, M and V/M were obtained from the coronary computed tomography angiography (CCTA) of patients in the FAST-TRACK CABG study, the first-in-human trial of coronary artery bypass grafting (CABG) guided solely by CCTA and fractional flow reserve derived from CCTA (FFRCT) in patients with complex coronary artery disease (CAD). The correlations between V/M ratios and baseline characteristics were determined and compared with those from the ADVANCE registry, an unselected cohort of historical controls with chronic CAD. RESULTS: The V/M ratio was obtained in 106 of the 114 pre-CABG CCTAs. Mean age was 65.6 years and 87% of them were male. The anatomical SYNTAX score from CCTA was significantly higher than the functional SYNTAX score derived using FFRCT [43.1 (15.2) vs 41.1 (16.5), p â€‹< â€‹0.001]. Mean V, M, and V/M were 2204 â€‹mm3, 137 â€‹g, and 16.5 â€‹mm3/g, respectively. There were weak negative correlations between V and anatomical and functional SYNTAX scores (Pearson's r â€‹= â€‹-0.26 and -0.34). V and V/M had a strong correlation (r â€‹= â€‹0.82). The V/M ratio in the current study was significantly lower than that in the ADVANCE registry (median 16.1 vs. 24.8 [1st quartile 20.1]). CONCLUSION: Systematically smaller V/M ratios were found in this population with severe CAD requiring CABG compared to an unselected cohort with chronic CAD. The V/M ratio could provide additional non-invasive assessment of CAD especially when combined with FFRCT.

Casting Light on The Hidden Prevalence: A Novel Perspective on Hypoplastic Coronary Artery Disease.

Background and Objectives: Coronary artery anomalies (CAAs) represent a group of rare cardiac abnormalities with an incidence of up to 1.2%. The aim of this retrospective study was to conduct a comprehensive epidemiological assessment of the prevalence of hypoplastic coronary arteries using coronary computed tomography angiography (CCTA) in patients with diagnosed CAAs and individuals presenting with cardiovascular manifestations in the north-eastern region of Romania. This study was motivated by the limited investigation of the CAAs conducted in this area. Methods: We analyzed data collected from 12,758 coronary computed tomography angiography (CCTA) records available at the "Prof. Dr. George I.M. Georgescu" Cardiovascular Diseases Institute, spanning the years 2012 to 2022. Results: Among 350 individuals with CAAs (2.7% of the total cohort), 71 patients (20.3% of the anomaly presenting group and 0.5% of the entire CCTA cohort) exhibited at least one hypoplastic coronary artery. The mean age of individuals diagnosed with hypoplastic coronary artery disease (HCAD) was 61 years, while the age distribution among them ranged from 22 to 84 years. Nearly equal cases of right and left dominance (33 and 31, respectively) were observed, with only 7 cases of co-dominance. Conclusions: HCAD may be considered underexplored in current published research, despite its potentially significant implications ranging to an increased risk of sudden cardiac arrest. The specific prevalence of HCAD among CAAs might be higher than previously reported, possibly reflecting better diagnostic accuracy of CCTA over classic coronary imaging. The absence of standard diagnostic and therapeutic protocols for HCAD underscores the necessity of a personalized approach for such cases.

Quantitative analysis of the relationship between the myocardial bridge and the FAI of pericoronal fat on computed tomography.

We performed this cohort study to investigate whether the myocardial bridge (MB) affects the fat attenuation index (FAI) and to determine the optimal cardiac phase to measure the volume and the FAI of pericoronary adipose tissue (PCAT). The data of 300 patients who were diagnosed with MB of the left anterior descending (LAD) coronary artery were retrospectively analyzed. All of patients were divided into the MB group and the MB with atherosclerosis group. In addition, 104 patients with negative CCTA results were enrolled as the control group. There was no significant difference between FAI values measured in systole and diastole (P > 0.05). There was no significant difference in FAI among the MB group, the MB with atherosclerosis group, and the control group (P > 0.05). In MB with atherosclerosis group, LAD stenosis degree (< 50%) (OR = 0.186, 95% CI 0.036-0.960; P = 0.045) and MB located in the distal part of LAD opening (OR = 0.880, 95% CI 0.789-0.980; P = 0.020) were protective factors of FAI value. A distance (from the LAD opening to the proximal point of the MB) of 29.85 mm had the highest predictive value for abnormal FAI [area under the curve (AUC), 0.798], with a sensitivity of 81.1% and a specificity of 74.6%.

Effect of deep learning image reconstruction with high-definition standard scan mode on image quality of coronary stents and arteries.

Background: The high-definition standard (HD-standard) scan mode has been proven to display stents better than the standard (STND) scan mode but with more image noise. Deep learning image reconstruction (DLIR) is capable of reducing image noise. This study examined the impact of HD-standard scan mode with DLIR algorithms on stent and coronary artery image quality in coronary computed tomography angiography (CCTA) via a comparison with conventional STND scan mode and adaptive statistical iterative reconstruction-Veo (ASIR-V) algorithms. Methods: The data of 121 patients who underwent HD-standard mode scans (group A: N=47, with coronary stent) or STND mode scans (group B: N=74, without coronary stent) were retrospectively collected. All images were reconstructed with ASIR-V at a level of 50% (ASIR-V50%) and a level of 80% (ASIR-V80%) and with DLIR at medium (DLIR-M) and high (DLIR-H) levels. The noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), artifact index (AI), and in-stent diameter were measured as objective evaluation parameters. Subjective assessment involved a 5-point scale for overall image quality, image noise, stent appearance, stent artifacts, vascular sharpness, and diagnostic confidence. Diagnostic confidence was evaluated based on the presence or absence of significant stenosis (≥50% lumen reduction). Both subjective and objective evaluations were conducted by two radiologists independently, with kappa and intraclass correlation statistics being used to test the interobserver agreement. Results: There were 76 evaluable stents in group A, and the DLIR-H algorithm significantly outperformed other algorithms, demonstrating the lowest noise (41.6±7.1/41.3±7.2) and AI (32.4±8.9/31.2±10.1), the highest SNR (14.6±3.5/15.0±3.5) and CNR (13.6±3.8/13.9±3.8), and the largest in-stent diameter (2.18±0.61/2.19±0.61) in representing true stent diameter (all P values <0.01), as well as the highest score in each subjective evaluation parameter. In group B, a total of 296 coronary arteries were evaluated, and the DLIR-H algorithm provided the best objective image quality, with statistically superior noise, SNR, and CNR compared with the other algorithms (all P values <0.05). Moreover, the HD-standard mode scan with DLIR provided better image quality and a lower radiation dose than did the STND mode scan with ASIR-V (P<0.01). Conclusions: HD-standard scan mode with DLIR-H improves image quality of both stents and coronary arteries on CCTA under a lower radiation dose.

The value of coordinated analysis of multimodal atherosclerotic plaque imaging in the assessment of cardiovascular and cerebrovascular events.

Background: Although atherosclerosis (AS) can affect multiple vascular beds, previous studies have focused on the analysis of single-site AS plaques. Objective: The aim of this study is to explore the differences or similarities in the characteristics of atherosclerotic plaque found in the internal carotid artery, cerebral artery, and coronary artery between patients with atherosclerotic cardiovascular disease (ASCVD) and those without events. Methods: Patients aged ≥ 18 years who underwent both high-resolution vessel wall imaging (HR-VWI) and coronary computed tomography angiography (CCTA) were retrospectively collected and categorized into the ASCVD group and the non-event group. The plaques were then categorized into culprit plaques, non-culprit plaques, and non-event plaques. Plaque morphological data such as stenosis, stenosis grades, plaque length (PL), plaque volume (PV), minimal lumen area (MLA), enhancement grade, and plaque composition data such as calcified plaque volume (CPV), fibrotic plaque volume (FPV), fibro-lipid plaque volume (FLPV), lipid plaque volume (LPV), calcified plaque volume ratio (CPR), fibrotic plaque volume ratio (FPR), fibro-lipid plaque ratio (FLPR), lipid plaque volume ratio (LPR), intraplaque hemorrhage volume (IPHV), and intraplaque hemorrhage volume ratio (IPHR)were recorded and analyzed. Results: A total of 44 patients (mean age 66 years, SD 9 years, 28 men) were included. In cervicocephalic plaques, the ASCVD group had more severe stenosis grades (p = 0.030) and demonstrated significant differences in LPV, LPR, and CPV (p = 0.044, 0.030, 0.020) compared with the non-event group. In coronary plaques, the ASCVD group had plaques with greater stenosis (p < 0.001), more severe stenosis grades (p < 0.001), larger volumes (p = 0.001), longer length (p = 0.008), larger FLPV (p = 0.012), larger FPV (p = 0.002), and higher FPR (p = 0.043) compared with the non-event group. There were significant differences observed in stenosis (HR-VWI, CCTA: p < 0.001, p < 0.001), stenosis grades (HR-VWI, CCTA: p < 0.001, p < 0.001), plaque length (HR-VWI, CCTA: p = 0.028, p < 0.001), and plaque volume (HR-VWI, CCTA: p = 0.013, p = 0.018) between the non-event plaque, non-culprit plaque, and culprit plaque. In the image analysis of HR-VWI, there were differences observed between IPHR (p < 0.001), LPR (p = 0.001), FPV (p = 0.011), and CPV (p = 0.015) among the three groups of plaques. FLPV and FPV were significantly different among the three different plaque types from the coronary artery (p = 0.043, p = 0.022). Conclusion: There is a consistent pattern of change in plaque characteristics between the cervicocephalic and coronary arteries in the same patient.

What's New in Preoperative Cardiac Testing.

More than 300 million surgeries are performed annually worldwide. Patients are progressively aging and often have multiple comorbidities that put them at increased cardiovascular risk in the perioperative period. The United States published latest guidelines regarding preoperative cardiac evaluation and risk stratification for patients undergoing non-cardiac surgery in 2014. There are multiple risk stratification tools available that can help guide management. Furthermore, newer laboratory tests, such as preoperative NT-proBNP and high-sensitivity troponin assays, may aid in preventing and diagnosing perioperative myocardial injury.

Pericoronary adipose tissue attenuation in patients with acute aortic dissection based on coronary computed tomography angiography.

Background: Periaortic fat is associated with coronary disease. Thus, it was hypothesized that the inflammation associated with acute aortic dissection (AAD) spreads to pericoronary adipose tissue (PCAT) via thoracic periaortic fat. Pericoronary adipose tissue attenuation (PCATa) serves as a marker for inflammation of perivascular adipose tissue (PVAT). This study sought to examine PCATa in individuals diagnosed with AAD. Methods: Consecutive patients with chest pain from May 2020 to September 2022 were prospectively enrolled in this study and underwent coronary computed tomography angiography (CCTA) and/or aorta computed tomography angiography (CTA). Based on the results of the CTA, the patients were divided into the following two groups: (I) the AAD group; and (II) the non-AAD group. PCATa of the right coronary angiography (RCA), left anterior descending (LAD), and left circumflex (LCx) was quantified for each patient using semi-automated software. The PCATa values were compared between the AAD and non-AAD patients according to the atherosclerosis of the coronary arteries. Similarly, the PCATa values of the AAD patients were compared between the preoperative and postoperative steady states. Results: A total of 136 patients (42 female, 94 male; mean age: 63.3±11.9 years) were divided into the two groups according to the presence of aortic dissection on CTA. The RCAPCATa, LADPCATa, and LCxPCATa values were significantly higher in the AAD subjects than the non-AAD subjects, regardless of the presence or absence of atherosclerosis in the coronary arteries [-85.1±9.3 vs. -92.9±10.0 Hounsfield unit (HU); -83.2±7.4 vs. -89.9±9.1 HU; -77.5±8.4 vs. -85.6±7.9 HU, all P<0.001). The preoperative RCAPCATa, LADPCATa, and LCxPCATa values were higher in the AAD patients than the postoperative steady-state patients (-82.9±8.7 vs. -97.6±8.8 HU; -79.8±7.6 vs. -92.8±6.8 HU; -74.6±7.1 vs. -87.7±6.9 HU, all P<0.001). According to the multivariable logistic regression analysis, high RCAPCATa and LADPCATa values were associated with AAD regardless of the degree of stenosis [odds ratio (OR) =0.014; 95% confidence interval (CI): 0.001-0.177; P=0.001 and OR =0.010; 95% CI: 0.001-0.189; P=0.002]. Conclusions: PCATa on computed tomography was increased in patients with AAD regardless of the presence or absence of coronary artery disease (CAD). This suggests that vascular inflammation is present in AAD independent of CAD. Further research should be conducted to investigate the potential of this imaging biomarker to predict AAD and monitor patients' responses to therapies for AAD.

Relationships between the coronary fat attenuation index for patients with heart-related disease measured automatically on coronary computed tomography angiography and coronary adverse events and degree of coronary stenosis.

Background: Pericoronary artery coronary tissue (PACT) is a type of epicardial fat that can reflect the state of the coronary artery (inflammation, etc.). However, it cannot be reasonably and efficiently utilized in routine computed tomography (CT) examination. The aim of this study was to use artificial intelligence (AI) software to analyze coronary computed tomography angiography (CCTA) and measure the coronary perivascular fat attenuation index (FAI) of patients. The relationship between FAI and the occurrence of coronary adverse events and the degree of coronary stenosis were further analyzed. Methods: This study involved patients who experienced CCTA in West China Hospital, Sichuan University, from January 2012 to December 2012. These patients were followed up to 2020 and classified according to the occurrence of coronary adverse events and the degree of stenosis of the lumen. For all patients, AI software was used to analyze the CCTA images of patients, and the FAI of 3 coronary arteries, the left anterior descending artery (LAD), the left circumflex artery (LCX), and the right coronary artery (RCA), was measured. Moreover, the relationship between FAI and patients with different degrees of coronary stenosis and adverse coronary events was determined. Results: Comparisons between any 2 groups showed that the differences in the FAI among the 4 groups for the LAD were significant (all P values <0.05). There were no significant differences between the group with less-than-moderate stenosis (Mb) without adverse events and the group with moderate-or-above stenosis (M) with no adverse events for the LCX (P>0.05). For the remaining groups, FAI values exhibited statistically significant differences (P<0.05). According to the degree of lumen stenosis, the patients were divided into groups according to LAD, LCX, and RCA and the sum of the 3 vessels. There were significant differences in coronary FAI among the groups with different degrees of lumen stenosis for the sum of the 3 vessels, the LAD, and the LCX (P<0.05). Conclusions: FAI can reflect the state of the coronary artery, which is related to inflammation of the coronary lumen. Moreover, there is a relationship between FAI and the degree of stenosis in the coronary lumen: the narrower the coronary lumen is, the higher the FAI around the lumen.

Coronary computed tomography angiography analysis using artificial intelligence for stenosis quantification and stent segmentation: a multicenter study.

Background: Accurate interpretation of coronary computed tomography angiography (CCTA) is a labor-intensive and expertise-driven endeavor, as inexperienced readers may inadvertently overestimate stenosis severity. Recent artificial intelligence (AI) advances in medical imaging present compelling prospects for auxiliary diagnostic tools in CCTA. This study aimed to externally validate an AI-assisted analysis system capable of rapidly evaluating stenosis severity, exploring its potential integration into routine clinical workflows. Methods: This multicenter study consisted of an internal and external cohort of patients who underwent CCTA scans between April 2017 and February 2023. CCTA scans were evaluated using Coronary Artery Disease Reporting and Data System (CAD-RADS) scores to determine stenosis severity, while ground-truth stents were manually annotated by expert readers. The InferRead CT Heart (version 1.6; Infervision Medical Technology Co., Ltd., Beijing, China), which incorporates AI-assisted coronary artery stenosis quantification and automatic stent segmentation, was employed for CCTA scan analysis. AI-based stenosis assessment performance was determined using sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), while the AI-based stent segmentation overlap was assessed using the Dice similarity coefficient (DSC). Results: For ≥50% stenosis diagnoses, the AI system attained per-patient sensitivity, specificity, PPV, and NPV surpassing 90.0% for the internal dataset; for the external dataset, the per-patient values were 88.0% [95% confidence interval (CI): 81.0-94.4%], 94.5% (95% CI: 90.7-97.6%), 90.0% (95% CI: 83.3-95.6%), and 93.4% (95% CI: 89.2-96.8%), respectively. For ≥70% stenosis diagnoses, the per-patient values on the internal dataset were 94.2% (95% CI: 89.2-98.1%), 95.8% (95% CI: 94.1-97.4%), 80.8% (95% CI: 73.5-87.7%), and 98.9% (95% CI: 97.9-99.6%), respectively; for the external dataset, the per-patient values were 91.9% (95% CI: 82.6-100.0%), 97.3% (95% CI: 94.9-99.1%), 85.0% (95% CI: 72.5-94.6%), and 98.6% (95% CI: 96.8-100.0%), respectively. Regarding CAD-RADS categorization, the Cohen kappa was 0.75 and 0.81 for the internal per-patient and per-vessel basis, respectively, and 0.72 and 0.76 for the external per-patient and per-vessel basis, respectively. The DSC for stent segmentation was 0.96±0.06. Conclusions: The AI-assisted analysis system for CCTA interpretation exhibited exceptional proficiency in stenosis quantification and stent segmentation, indicating that AI holds considerable potential in advancing CCTA postprocessing techniques.

Prognostic utility of semi-quantitative coronary computed tomography angiography scores in the SCOT-HEART trial.

BACKGROUND: Information from cardiac computed tomography angiography can be summarized using visual semi-quantitative scores. However, the optimal method and their prognostic utility is unknown. METHODS: Five semi-quantitative scores were calculated in the SCOT-HEART trial, including segment involvement score (SIS), segment stenosis score (SSS), CT Leaman (CT-LeSc), multivessel aggregate stenosis score (MVAS), and CAD-RADS 2.0 including plaque modifier (P). Prediction of fatal or non-fatal myocardial infarction and major adverse cardiovascular events (MACE) was compared to the 10-year cardiovascular risk score. RESULTS: Imaging was performed in 1,769 individuals (age 58 â€‹± â€‹10 years, 56% male) with 41 (2.3%) experiencing myocardial infarction and 74 (4%) MACE over 4.9 â€‹± â€‹1.1 years. P based on calcium score and SIS had good agreement (weighted Cohen's kappa 0.79, 95% confidence interval [CI] 0.79, 0.79). SIS, SSS, CT-LeSec, and MVAS performed similarly for the prediction of myocardial infarction (area under the curve [AUC] 0.74, 0.75, 0.75, 0.74, all p â€‹> â€‹0.1) and MACE (AUC 0.73, 0.74, 0.74, 0.73, all p â€‹> â€‹0.1), and were superior to the cardiovascular risk score (AUC 0.62 and 0.65, both p â€‹< â€‹0.001). High semi-quantitative scores were associated with increased risk of myocardial infarction and MACE, with the greatest adjusted risk associated with CT-LeSc≥8 (Hazard ratio [HR] 5.6, 95% confidence interval [CI] 2.7, 11.6, p â€‹< â€‹0.001 and HR 5.2, 95% CI 3.1, 8.7, p â€‹< â€‹0.001) and SSS≥10 (HR 4.7, 95% CI 2.4, 8.9, p â€‹< â€‹0.001 and HR 5.3, 95% CI 3.3, 8.5, p â€‹< â€‹0.001). CONCLUSIONS: Semi-quantitative scores performed similarly for the prediction of myocardial infarction and MACE, with all superior to the cardiovascular risk score.

Is there an association between coronary artery inflammation and coronary atherosclerotic burden?

Background: As for the coronary artery inflammation and coronary atherosclerotic burden, which are used to assess the risk of adverse cardiac events in patients, it is unclear whether there is any certain correlation between them. Therefore, the purpose of this study was to explore the potential relationship between coronary artery inflammation and coronary atherosclerotic burden. Methods: A total of 346 eligible patients underwent assessment of computed tomography (CT) attenuation values of pericoronary adipose tissue (PCAT) in the right coronary artery and Agatston coronary artery calcium (CAC) based on coronary CT angiography. These measurements were utilized to evaluate coronary inflammation and atherosclerotic burden, respectively. Patients with a CAC score of 0 were categorized into groups based on the presence or absence of coronary artery disease (CAD). CAC scores of 10, 100, and 400 were chosen as cutoff values to compare differences in PCAT attenuation values across different CAC scores. Results: When comparing all CAD patients to non-CAD patients, a significantly higher PCAT attenuation was observed in CAD patients (-87.54±9.39 vs. -93.45±7.42 HU, P=0.000). The PCAT attenuation in CAD patients with a CAC score of 0 was significantly higher than that in patients with a CAC score greater than 0 and in non-CAD patients with a CAC score of 0 (-82.63±8.70 vs. -90.38±8.59 vs. -93.45±7.42 HU, P=0.000). The PCAT attenuation values did not exhibit significant differences among different CAC scores (all P>0.05); however, it was highest in CAD patients with a CAC score of 0 (P<0.05). Body mass index, hyperlipidemia, hypertension, and PCAT attenuation were identified as independent risk factors in both CAD patients with a CAC score of 0 and patients with a CAC score greater than 0 (all P<0.05). Conclusions: The results of this study suggest that a direct relationship between coronary inflammation and coronary atherosclerotic burden is not evident. Nonetheless, it is noteworthy that coronary inflammation was most pronounced in CAD patients with a CAC score of 0, while CAC score did not demonstrate an association with inflammation.

Dual left anterior descending coronary artery and anomalous origin of left circumflex artery: a novel coronary anomaly revealed by CCTA.

In the rare coronary anomaly of Dual LAD, two segments of the vessel reside within the anterior interventricular sulcus. In our case, the short LAD originated from the Left Coronary Sinus (LCS), while the long LAD emerged from the Right Coronary Sinus (RCS). The LCx arose from the RCS, and the RCA displayed typical features. This anomaly was deemed incidental, prompting routine follow-up. It underscores the significance of integrating CCTA for a thorough assessment, offering crucial insights for patient management.

Association of Soluble Markers of Inflammation With Peri-coronary Artery Inflammation in People With and Without HIV Infection and Without Cardiovascular Disease.

Background: Inflammation is linked to elevated cardiovascular disease (CVD) risk in people with HIV (PWH) on antiretroviral therapy (ART). Fat attenuation index (FAI) is a measure of peri-coronary inflammation that independently predicts CVD risk in HIV-uninfected persons. Whether FAI is associated with soluble inflammatory markers is unknown. Methods: Plasma levels of inflammatory markers were measured in 58 PWH and 16 controls without current symptoms or prior known CVD who underwent coronary computed tomography angiography and had FAI measurements. A cross-sectional analysis was performed, and associations of markers with FAI values of the right coronary artery (RCA) and left anterior descending artery (LAD) were assessed using multivariable regression models adjusted for the potential confounders age, sex, race, low-density lipoprotein cholesterol, body mass index, and use of lipid-lowering medication. Results: Several inflammatory markers had significant associations with RCA or LAD FAI in adjusted models, including sCD14, sCD163, TNFR-I, and TNFR-II, CCL5, CX3CL1, IP-10. Conclusions: The associations between indices of systemic and peri-coronary inflammation are novel and suggest that these systemic markers and FAI together are promising noninvasive biomarkers that can be applied to assess asymptomatic CVD in people with and without HIV; they also may be useful tools to evaluate effects of anti-inflammatory interventions.

The Role of Coronary CT Angiography in the Evaluation of Dual Left Anterior Descending Artery Prevalence and Subtypes: A Retrospective Multicenter Study.

BACKGROUND: The aim of this multicenter study was to evaluate the prevalence and features of dual left anterior descending artery (LAD) subtypes using coronary CT angiography (CCTA). METHODS: A retrospective multicenter analysis of 2083 CCTA from December 2020 to November 2022 was conducted to search for the presence and morphological features of dual LAD. The two classifications used were the updated classification of Spindola-Franco and the Jariwala classification. Statistical tests were conducted to evaluate the prevalence of dual LADs among sexes and its association with angina in patients without significant coronary stenoses and/or associated cardiac anomalies. RESULTS: Dual LAD was observed in 124 (5.96%) patients analyzed. According to the Spindola-Franco revisited classification, type I dual LAD was the most common (71/124, 57.26%). According to the Jariwala classification, all cases were group I. In the general population, there was a higher prevalence of dual LAD among females (7.3% females vs. 5.1% males; p value: 0.04). No statistically significant difference was found in the prevalence of angina in the dual LAD population compared to the no dual LAD population (2.1% vs. 1.5%; p value: 0.10). CONCLUSIONS: The acknowledgment and reporting of LAD duplication is helpful for an optimal management of coronary patients with this condition. Dual LAD was more frequent in the female population, mainly not related with angina. Myocardial bridge was more frequent in the dual LAD population than in the no dual LAD population.

Identification of ischemia-causing lesions using coronary plaque quantification and changes in fractional flow reserve derived from computed tomography across the lesion.

Background: This study sought to evaluate the association between coronary plaque characteristics, changes in the fractional flow reserve (FFR) derived from computed tomography across the lesion (ΔFFRCT), and lesion-specific ischemia using the FFR in patients with suspected or known coronary artery disease. Methods: The study assessed coronary computed tomography (CT) angiography stenosis, plaque characteristics, ΔFFRCT, and FFR in 164 vessels of 144 patients. Obstructive stenosis was defined as stenosis ≥50%. An area under the receiver -operating characteristics curve (AUC) analysis was conducted to define the optimal thresholds for ΔFFRCT and the plaque variables. Ischemia was defined as a FFR of ≤0.80. Results: The optimal cut-off value of ΔFFRCT was 0.14. Low-attenuation plaque (LAP) ≥76.23 mm3 and a percentage aggregate plaque volume (%APV) ≥28.91% can be used to predict ischemia independent of other plaque characteristics. The addition of LAP ≥76.23 mm3 and %APV ≥28.91% improved the discrimination (AUC, 0.742 vs. 0.649, P=0.001) and reclassification abilities [category-free net reclassification index (NRI), 0.339, P=0.027; relative integrated discrimination improvement (IDI) index, 0.093, P<0.001] of the assessments compared to the stenosis evaluation alone, and the addition of information about ΔFFRCT ≥0.14 further increased the discrimination (AUC, 0.828 vs. 0.742, P=0.004) and reclassification abilities (NRI, 1.029, P<0.001; relative IDI, 0.140, P<0.001) of the assessments. Conclusions: The addition of the plaque assessment and ΔFFRCT to the stenosis assessments improved the identification of ischemia compared to the stenosis assessment alone.

Identification of patients with acute coronary syndrome and representation of their degree of inflammation: application of pericoronary adipose tissue within different radial distances of the proximal coronary arteries.

Background: Pericoronary adipose tissue (PCAT) around the proximal right coronary artery (RCA) is considered a marker of coronary inflammation. We aimed to explore the segments of PCAT that represent coronary inflammation in patients with acute coronary syndrome (ACS) and to identify patients with ACS and stable coronary artery disease (CAD) prior to intervention. Methods: We retrospectively enrolled consecutive patients with ACS and stable CAD who underwent invasive coronary angiography (ICA) after coronary computed tomography angiography (CCTA) from November 2020 to October 2021 at the Fourth Affiliated Hospital of Harbin Medical University. The fat attenuation index (FAI) was obtained using PCAT quantitative measurement software, and the coronary Gensini score was also calculated to indicate the severity of CAD. The differences and correlations between FAI within different radial distances of proximal coronary arteries were evaluated, and the recognition ability of FAI for patients with ACS and stable CAD was evaluated by establishing receiver operator characteristic (ROC) curves. Results: A total of 267 patients were included in the cross-sectional study, including 173 patients with ACS. With the increase of radial distance from the outer wall of proximal coronary vessels, the FAI decreased (P<0.001). The FAI around the proximal left anterior descending artery (LAD) within the reference diameter from the outer wall of the vessel (LADref) had the highest correlation with the FAI around culprit lesions [r=0.587; 95% confidence interval (CI): 0.489-0.671; P<0.001]. The model based on clinical features, Gensini score, and LADref had the highest recognition performance for patients with ACS and stable CAD [area under the curve (AUC): 0.663; 95% CI: 0.540-0.785]. Conclusions: LADref is most correlated with FAI around culprit lesions in patients with ACS and has higher value in the preintervention differentiation of patients with ACS and stable CAD compared to the use of clinical features alone.

Assessment of Image Quality of Coronary CT Angiography Using Deep Learning-Based CT Reconstruction: Phantom and Patient Studies.

BACKGROUND: In coronary computed tomography angiography (CCTA), the main issue of image quality is noise in obese patients, blooming artifacts due to calcium and stents, high-risk coronary plaques, and radiation exposure to patients. OBJECTIVE: To compare the CCTA image quality of deep learning-based reconstruction (DLR) with that of filtered back projection (FBP) and iterative reconstruction (IR). METHODS: This was a phantom study of 90 patients who underwent CCTA. CCTA images were acquired using FBP, IR, and DLR. In the phantom study, the aortic root and the left main coronary artery in the chest phantom were simulated using a needleless syringe. The patients were classified into three groups according to their body mass index. Noise, the signal-to-noise ratio (SNR), and the contrast-to-noise ratio (CNR) were measured for image quantification. A subjective analysis was also performed for FBP, IR, and DLR. RESULTS: According to the phantom study, DLR reduced noise by 59.8% compared to FBP and increased SNR and CNR by 121.4% and 123.6%, respectively. In a patient study, DLR reduced noise compared to FBP and IR. Furthermore, DLR increased the SNR and CNR more than FBP and IR. In terms of subjective scores, DLR was higher than FBP and IR. CONCLUSION: In both phantom and patient studies, DLR effectively reduced image noise and improved SNR and CNR. Therefore, the DLR may be useful for CCTA examinations.

Radiomics applications in cardiac imaging: a comprehensive review.

Radiomics is a new emerging field that includes extraction of metrics and quantification of so-called radiomic features from medical images. The growing importance of radiomics applied to oncology in improving diagnosis, cancer staging and grading, and improved personalized treatment, has been well established; yet, this new analysis technique has still few applications in cardiovascular imaging. Several studies have shown promising results describing how radiomics principles could improve the diagnostic accuracy of coronary computed tomography angiography (CCTA) and magnetic resonance imaging (MRI) in diagnosis, risk stratification, and follow-up of patients with coronary heart disease (CAD), ischemic heart disease (IHD), hypertrophic cardiomyopathy (HCM), hypertensive heart disease (HHD), and many other cardiovascular diseases. Such quantitative approach could be useful to overcome the main limitations of CCTA and MRI in the evaluation of cardiovascular diseases, such as readers' subjectiveness and lack of repeatability. Moreover, this new discipline could potentially overcome some technical problems, namely the need of contrast administration or invasive examinations. Despite such advantages, radiomics is still not applied in clinical routine, due to lack of standardized parameters acquisition, inconsistent radiomic methods, lack of external validation, and different knowledge and experience among the readers. The purpose of this manuscript is to provide a recent update on the status of radiomics clinical applications in cardiovascular imaging.