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AIMS: The incremental impact of atherosclerosis imaging-quantitative computed tomography (AI-QCT) on diagnostic certainty and downstream patient management is not yet known. The aim of this study was to compare the clinical utility of the routine implementation of AI-QCT versus conventional visual coronary CT angiography (CCTA) interpretation. METHODS AND RESULTS: In this multi-centre cross-over study in 5 expert CCTA sites, 750 consecutive adult patients referred for CCTA were prospectively recruited. Blinded to the AI-QCT analysis, site physicians established patient diagnoses and plans for downstream non-invasive testing, coronary intervention, and medication management based on the conventional site assessment. Next, physicians were asked to repeat their assessments based upon AI-QCT results. The included patients had an age of 63.8 ± 12.2 years; 433 (57.7%) were male. Compared with the conventional site CCTA evaluation, AI-QCT analysis improved physicians confidence two- to five-fold at every step of the care pathway and was associated with change in diagnosis or management in the majority of patients (428; 57.1%; P < 0.001), including for measures such as Coronary Artery Disease-Reporting and Data System (CAD-RADS) (295; 39.3%; P < 0.001) and plaque burden (197; 26.3%; P < 0.001). After AI-QCT including ischaemia assessment, the need for downstream non-invasive and invasive testing was reduced by 37.1% (P < 0.001), compared with the conventional site CCTA evaluation. Incremental to the site CCTA evaluation alone, AI-QCT resulted in statin initiation/increase an aspirin initiation in an additional 28.1% (P < 0.001) and 23.0% (P < 0.001) of patients, respectively. CONCLUSION: The use of AI-QCT improves diagnostic certainty and may result in reduced downstream need for non-invasive testing and increased rates of preventive medical therapy.

Background: Coronary tortuosity (CorT) is frequently observed in invasive angiography, though its aetiology and clinical significance remain ambiguous. Prior research has indicated possible links between CorT and factors such as hypertension, age, and calcium scores in the left anterior descending (LAD) artery. The aim of this study was to examine and optimize the usage of coronary computed tomography angiography (CCTA) with vessel tracking to explore these associations. Methods: Observational sub‐study of the single centre randomised controlled CATCH‐trial. From the original study 600 participants, who underwent CCTA, 250 were randomly selected. Clinical data and patient risk factors were sourced from medical records and structured interviews. Tortuosity of the LAD was quantified by calculating the ratio of the actual vessel‐length to the straight‐line distance. Results: The final study population comprised 194 patients (56 patients were excluded due to poor image quality or inability to perform adequate vessel tracking). After adjusting for confounding variables, tortuosity was significantly associated with hypertension (p < 0.001), female gender (p = 0.01), and increasing age (p = 0.045). No significant correlation was observed between CorT and calcium scores. Univariate analysis indicated that higher CorT levels were linked to lower metabolic equivalents of task (METs) in bicycle tests (p = 0.003); however, this relationship became nonsignificant (p = 0.97) upon adjustment for age, gender, and hypertension. Conclusions: Our findings suggest that increased CorT is most prevalent in patients with hypertension, advancing age, and female gender. Although higher tortuosity levels did not significantly impact METs during physical activity, further research is warranted to explore the underlying mechanisms of this relationship. [ABSTRACT FROM AUTHOR]

Coronary CT angiography (CCTA) offers an efficient and reliable tool for the non-invasive assessment of suspected coronary artery disease through the analysis of coronary artery plaque and stenosis. However, the detailed manual analysis of CCTA is a burdensome task requiring highly skilled experts. Recent advances in artificial intelligence (AI) have made significant progress toward a more comprehensive automated analysis of CCTA images, offering potential improvements in terms of speed, performance and scalability. This work offers an overview of the recent developments of AI in CCTA. We cover methodological advances for coronary artery tree and whole heart analysis, and provide an overview of AI techniques that have shown to be valuable for the analysis of cardiac anatomy and pathology in CCTA. Finally, we provide a general discussion regarding current challenges and limitations, and discuss prospects for future research. [ABSTRACT FROM AUTHOR]

Background: The occurrence of suspended cords of the left atrium (SCLA) is rare and has seldom been described. The purpose of this study was to summarize the cases of SCLA accidentally detected by coronary CT angiography (CCTA), describe their imaging features, conduct a preliminary analysis of their clinical significance, and review relevant literature. Methods: A total of 10,796 patients who underwent CCTA examinations from July 2020 to November 2021 were consecutively selected. The original and three-dimensional reconstruction images were reviewed to identify patients with SCLA. A control group was selected in a 1:2 ratio based on age, BMI, sex, and education level. The imaging characteristics and clinical data of the two groups were collected and compared. The case group was divided into two subgroups based on the starting and ending positions of the SCLA: Group 1 with the SCLA between the free wall and free wall, and Group 2 with the SCLA between the septum wall and free wall. The clinical features of these subgroups were compared. Furthermore, a review of literature on SCLA published in the past fifteen years that includes its clinical and imaging features was conducted. Results: In this study, a total of 35 patients were found to have SCLA, resulting in an incidence rate of approximately 0.32%. After excluding 1 patient for whom clinical features could not be obtained, the case group included a total of 18 males and 16 females, with a male-to-female ratio of 1:1 and a median age of 57.00 (52.00–64.00) years. It was found that 19 (55.88%) cases of SCLA were located near the right superior pulmonary vein ostia, while no SCLA was found near the left lower pulmonary vein orifice. A significant difference in the incidence of atrial arrhythmia between the two groups was observed (p = 0.009). Additionally, 3 patients (8.82%) in the SCLA group had a history of transient cerebral ischemic attack (TIA), which was significantly different from that in the control group (p = 0.035). The anteroposterior and transverse diameters of the left atrium were longer in the case group than in the control group (p < 0.05), but there was no significant change in left atrial volume. Subgroup analyses found no significant difference in the incidence of cerebral infarction, atrial arrhythmia, or other intracardiac structural malformations, although there was a significant difference in cord length (p = 0.013), with the length of SCLA in Group 1 and Group 2 being 2.64 ± 0.99 cm and 3.39 ± 0.68 cm, respectively. Notably, only 1 of these 34 patients was diagnosed based on echocardiography, whereas all cases were perfectly visualized using CCTA. Conclusion: SCLA is rare. CCTA can accurately detect and depict this abnormal structure as compared to echocardiography. SCLA may be linked to a higher incidence of atrial arrhythmias or transient ischemic attacks. It is important for radiologists and cardiovascular experts to recognize this structure, and further investigation is necessary to determine its clinical significance. [ABSTRACT FROM AUTHOR]

Background: Graft occlusions are commonly present in symptomatic patients after coronary artery bypass surgery (CABG). The aim of this study was to evaluate the diagnostic accuracy of coronary computed tomography angiography (CCTA) and stress single photon emission computed tomographic (SPECT) myocardial perfusion imaging (MPI) for detecting graft disease in symptomatic post-CABG patients. Methods: This was a prospective, single centre study of 100 symptomatic post-CABG patients with native coronary artery/graft occlusions on invasive angiography (CAG). Grafts were evaluated for degree of stenosis qualitatively on CCTA. Reversible perfusion defects were graded using summed difference score (SDS) on MPI. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of CCTA and MPI were evaluated against CAG. Results: CCTA identified 17/31 (55%), 30/43 (70%) and 18/19 (95%) patients with ≥50% stenosis of arterial, venous and both grafts respectively with specificity and PPV of 100%. Reversible perfusion defects were present in 81% of the patients with a mean SDS score of 5.4 ± 3.39 and sensitivity of 84%. Accuracy of CCTA and MPI for detection of graft occlusions were 99% and 84% respectively. 63/65 (97%) patients with ≥50% stenosis of grafts had ≥ 5 SDS score (moderate to severe grade ischemia) and 64% patients were revascularized. Conclusion: CCTA has a comparable diagnostic accuracy to CAG and can be used as an initial investigation in symptomatic post-CABG patients. Reversible perfusion defects on stress MPI help to risk stratify symptomatic post-CABG patients and guide further treatment. Hemodynamically significant occlusions may benefit from revascularization. [ABSTRACT FROM AUTHOR]

In recent years, a new technique called computed tomography-derived fractional flow reserve (CT-FFR) has been developed. CT-FFR overcomes many limitations in the current gold-standard fractional flow reserve (FFR) techniques while maintaining a better concordance with FFR. This technique integrates static coronary CT angiography data with hydrodynamic models, employing algorithms rather than guidewire interventions to compute the FFR. In addition to diagnosing coronary heart disease, CT-FFR has been applied in the preoperative risk assessment of major adverse cardiovascular events (MACEs) in organ transplantation and transcatheter aortic valve replacement (TAVR). Continuous advancements in CT-FFR techniques and algorithms are expanding their applicability to other methodologies. Subsequently, with robust clinical trial validation, CT-FFR can potentially supersede FFR as the primary “gatekeeper” for interventions. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the impact of acute intravenous beta-blocker administration on myocardial blood flow (MBF) during same-day hybrid coronary computed tomography angiography (CCTA) and 13N-ammonia positron emission tomography (PET) myocardial perfusion imaging (MPI). Previous research on the discontinuation of oral beta-blockers before MPI has shown mixed results, with no studies yet exploring the acute intravenous administration in the context of same-day hybrid imaging. This retrospective study included patients with suspected chronic coronary syndromes undergoing same-day hybrid CCTA/13N-ammonia PET MPI. Exclusion criteria comprised coronary artery stenosis ≥ 50% or regional perfusion abnormalities on PET, and baseline oral beta-blocker medication. Intravenous metoprolol (up to 30 mg) was administered as needed for heart rate control before CCTA. MBF measurements were obtained at rest (rMBF) and during stress (sMBF), and myocardial flow reserve (MFR) was calculated. After excluding 281 patients, 154 were eligible for propensity-score matching, resulting in 108 patients divided into two equal groups based on beta-blocker administration. The groups showed no significant differences in baseline characteristics. Among those who received beta-blockers, there was a significant decrease in sMBF (2.21 [IQR 1.72–2.78] versus 2.46 [2.08–2.99] ml∙min−1∙g−1, p = 0.027) and MFR (3.46 [2.70–4.05] versus 3.79 [3.22–4.46], p = 0.030), respectively, compared to those who did not receive beta-blockers. In contrast, rMBF remained unaffected (0.65 [0.54–0.78] versus 0.64 [0.55–0.76] ml∙min−1∙g−1, p = 0.931). Acute intravenous beta-blocker administration significantly impacts MBF, leading to a slight reduction in sMBF and MFR. In contrast, rMBF appears unaffected, suggesting that beta-blockers primarily affect the coronary capacity to respond to vasodilators. [ABSTRACT FROM AUTHOR]

Aims Cardiac cycle morphological changes can accelerate plaque growth proximal to myocardial bridging (MB) in the left anterior descending artery (LAD). To assess coronary computed tomography angiography (CCTA)-based vascular radiomics for predicting proximal plaque development in LAD MB. Methods and results Patients with repeated CCTA scans showing LAD MB without proximal plaque in index CCTA were included from Jinling Hospital as a development set. They were divided into training and internal testing in an 8:2 ratio. Patients from four other tertiary hospitals were set as external validation set. The endpoint was proximal plaque development of LAD MB in follow-up CCTA. Four vascular radiomics models were built: MB centreline (MB CL), proximal MB CL (pMB CL), MB cross-section (MB CS), and proximal MB CS (pMB CS), whose performances were evaluated using area under the receiver operating characteristic curve (AUC), integrated discrimination improvement (IDI), and net reclassification improvement (NRI). In total, 295 patients were included in the development (n = 192; median age, 54 ± 11 years; 137 men) and external validation sets (n = 103; median age, 57 ± 9 years; 57 men). The pMB CS vascular radiomics model exhibited higher AUCs in training, internal test, and external sets (AUC = 0.78, 0.75, 0.75) than the clinical and anatomical model (all P < 0.05). Integration of the pMB CS vascular radiomics model significantly raised the AUC of the clinical and anatomical model from 0.56 to 0.75 (P = 0.002), along with enhanced NRI [0.76 (0.37–1.14), P < 0.001] and IDI [0.17 (0.07–0.26), P < 0.001] in the external validation set. Conclusion The CCTA-based pMB CS vascular radiomics model can predict plaque development in LAD MB. [ABSTRACT FROM AUTHOR]

Objectives: To investigate the feasibility of a deep learning-constrained compressed sensing (DL-CS) method in non-contrast-enhanced modified DIXON (mDIXON) coronary magnetic resonance angiography (MRA) and compare its diagnostic accuracy using coronary CT angiography (CCTA) as a reference standard. Methods: Ninety-nine participants were prospectively recruited for this study. Thirty healthy subjects (age range: 20–65 years; 50% female) underwent three non-contrast mDIXON-based coronary MRA sequences including DL-CS, CS, and conventional sequences. The three groups were compared based on the scan time, subjective image quality score, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). The remaining 69 patients suspected of coronary artery disease (CAD) (age range: 39–83 years; 51% female) underwent the DL-CS coronary MRA and its diagnostic performance was compared with that of CCTA. Results: The scan time for the DL-CS and CS sequences was notably shorter than that of the conventional sequence (9.6 ± 3.1 min vs 10.0 ± 3.4 min vs 13.0 ± 4.9 min; p < 0.001). The DL-CS sequence obtained the highest image quality score, mean SNR, and CNR compared to CS and conventional methods (all p < 0.001). Compared to CCTA, the accuracy, sensitivity, and specificity of DL-CS mDIXON coronary MRA per patient were 84.1%, 92.0%, and 79.5%; those per vessel were 90.3%, 82.6%, and 92.5%; and those per segment were 98.0%, 85.1%, and 98.0%, respectively. Conclusion: The DL-CS mDIXON coronary MRA provided superior image quality and short scan time for visualizing coronary arteries in healthy individuals and demonstrated high diagnostic value compared to CCTA in CAD patients. Critical relevance statement: DL-CS resulted in improved image quality with an acceptable scan time, and demonstrated excellent diagnostic performance compared to CCTA, which could be an alternative to enhance the workflow of coronary MRA. Key Points: Current coronary MRA techniques are limited by scan time and the need for noise reduction. DL-CS reduced the scan time in coronary MR angiography. Deep learning achieved the highest image quality among the three methods. Deep learning-based coronary MR angiography demonstrated high performance compared to CT angiography. [ABSTRACT FROM AUTHOR]

Objective To explore the application value of 80 kV deep learning image reconstruction (DLIR) algorithm in coronary CT angiography (CCTA) . Methods Sixty patients who underwent CCTA were divided into two groups based on the scanning protocols: 100 kV group (Group A, n = 30) and 80 kV group (Group B, n = 30) . In Group A, 60% ASIR-V (A-AV60) and DLIR high-level reconstruction (A-DLIR) was adopted. In Group B, DLIR high-level reconstruction (B-DLIR) was employed. The CT volumetric dose index (CTDIvol) and the dose length product (DLP) were recorded in both groups, and the effective dose (ED) was calculated. Regions of interest (ROI) were placed in the aortic root (AR), left anterior descending coronary artery (LAD), left circumflex coronary artery (LCX), right coronary artery (RCA), and the same-layer pectoral fat area. The CT values and noise values of each ROI were recorded. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. Subjective evaluation was performed on the original axis, curved planar reconstruction (CPR), volume rendering (VR), and maximum intensity projection (MIP) reconstructions after the second-generation freeze technology (Snapshot Freeze 2, SSF-2), and the images in two groups were subject to subjective image quality evaluation. Results The ED in Group B was reduced by 45.14% compared to that in Group A. The CT values for AR, LAD, LCX, and RCA in the B-DLIR were higher than those in the A-AV60 and A-DLIR groups, and the differences were statistically significant (all P < 0.001) . The noise values for AR, LAD and LCX were similar, whereas statistical significance was observed in RCA between the A-DLIR and B-DLIR groups (P < 0.05) . The noise values in the A-DLIR and B-DLIR groups were smaller than that in the A-AV60 group, and the differences were statistically significant (both P < 0.001) . The SNR and CNR for AR, LAD, LCX and RCA were similar between the A-DLIR and B-DLIR groups, which were higher than those in the A-AV60 group (all P < 0.05) . The average subjective evaluation score of image quality in the B-DLIR group was higher than that in the A-AV60 group (P < 0.05), whereas lower than that in the A-DLIR group (P < 0.05) . There were no significant differences in clarity, artifact and small branch visibility between the A-DLIR and B-DLIR groups (all P > 0.05) . Conclusions During CCTA, the 80 kV DLIR algorithm contributes to yielding high-quality images, further improves the diagnostic efficiency and reduces the irradiation dose. [ABSTRACT FROM AUTHOR]

A lesion-level risk prediction for acute coronary syndrome (ACS) needs better characterization. This study sought to investigate the additive value of artificial intelligence–enabled quantitative coronary plaque and hemodynamic analysis (AI-QCPHA). Among ACS patients who underwent coronary computed tomography angiography (CTA) from 1 month to 3 years before the ACS event, culprit and nonculprit lesions on coronary CTA were adjudicated based on invasive coronary angiography. The primary endpoint was the predictability of the risk models for ACS culprit lesions. The reference model included the Coronary Artery Disease Reporting and Data System, a standardized classification for stenosis severity, and high-risk plaque, defined as lesions with ≥2 adverse plaque characteristics. The new prediction model was the reference model plus AI-QCPHA features, selected by hierarchical clustering and information gain in the derivation cohort. The model performance was assessed in the validation cohort. Among 351 patients (age: 65.9 ± 11.7 years) with 2,088 nonculprit and 363 culprit lesions, the median interval from coronary CTA to ACS event was 375 days (Q1-Q3: 95-645 days), and 223 patients (63.5%) presented with myocardial infarction. In the derivation cohort (n = 243), the best AI-QCPHA features were fractional flow reserve across the lesion, plaque burden, total plaque volume, low-attenuation plaque volume, and averaged percent total myocardial blood flow. The addition of AI-QCPHA features showed higher predictability than the reference model in the validation cohort (n = 108) (AUC: 0.84 vs 0.78; P < 0.001). The additive value of AI-QCPHA features was consistent across different timepoints from coronary CTA. AI-enabled plaque and hemodynamic quantification enhanced the predictability for ACS culprit lesions over the conventional coronary CTA analysis. (Exploring the Mechanism of Plaque Rupture in Acute Coronary Syndrome Using Coronary Computed Tomography Angiography and Computational Fluid Dynamics II [EMERALD-II]; NCT03591328) [Display omitted] [ABSTRACT FROM AUTHOR]

Abstract Background The occurrence of suspended cords of the left atrium (SCLA) is rare and has seldom been described. The purpose of this study was to summarize the cases of SCLA accidentally detected by coronary CT angiography (CCTA), describe their imaging features, conduct a preliminary analysis of their clinical significance, and review relevant literature. Methods A total of 10,796 patients who underwent CCTA examinations from July 2020 to November 2021 were consecutively selected. The original and three-dimensional reconstruction images were reviewed to identify patients with SCLA. A control group was selected in a 1:2 ratio based on age, BMI, sex, and education level. The imaging characteristics and clinical data of the two groups were collected and compared. The case group was divided into two subgroups based on the starting and ending positions of the SCLA: Group 1 with the SCLA between the free wall and free wall, and Group 2 with the SCLA between the septum wall and free wall. The clinical features of these subgroups were compared. Furthermore, a review of literature on SCLA published in the past fifteen years that includes its clinical and imaging features was conducted. Results In this study, a total of 35 patients were found to have SCLA, resulting in an incidence rate of approximately 0.32%. After excluding 1 patient for whom clinical features could not be obtained, the case group included a total of 18 males and 16 females, with a male-to-female ratio of 1:1 and a median age of 57.00 (52.00–64.00) years. It was found that 19 (55.88%) cases of SCLA were located near the right superior pulmonary vein ostia, while no SCLA was found near the left lower pulmonary vein orifice. A significant difference in the incidence of atrial arrhythmia between the two groups was observed (p = 0.009). Additionally, 3 patients (8.82%) in the SCLA group had a history of transient cerebral ischemic attack (TIA), which was significantly different from that in the control group (p = 0.035). The anteroposterior and transverse diameters of the left atrium were longer in the case group than in the control group (p

Objective To explore the application value of 80 kV deep learning image reconstruction （DLIR） algorithm in coronary CT angiography （CCTA）. Methods Sixty patients who underwent CCTA were divided into two groups based on the scanning protocols： 100 kV group （Group A， n = 30） and 80 kV group （Group B， n = 30）. In Group A， 60% ASIR-V （A-AV60） and DLIR high-level reconstruction （A-DLIR） was adopted. In Group B， DLIR high-level reconstruction （B-DLIR） was employed. The CT volumetric dose index （CTDIvol） and the dose length product （DLP） were recorded in both groups， and the effective dose （ED） was calculated. Regions of interest （ROI） were placed in the aortic root （AR）， left anterior descending coronary artery （LAD）， left circumflex coronary artery （LCX）， right coronary artery （RCA）， and the same-layer pectoral fat area. The CT values and noise values of each ROI were recorded. Signal-to-noise ratio （SNR） and contrast-to-noise ratio （CNR） were calculated. Subjective evaluation was performed on the original axis， curved planar reconstruction （CPR）， volume rendering （VR）， and maximum intensity projection （MIP） reconstructions after the second-generation freeze technology （Snapshot Freeze 2， SSF-2）， and the images in two groups were subject to subjective image quality evaluation. Results The ED in Group B was reduced by 45.14% compared to that in Group A. The CT values for AR， LAD， LCX， and RCA in the B-DLIR were higher than those in the A-AV60 and A-DLIR groups， and the differences were statistically significant （all P < 0.001）. The noise values for AR， LAD and LCX were similar， whereas statistical significance was observed in RCA between the A-DLIR and B-DLIR groups （P < 0.05）. The noise values in the A-DLIR and B-DLIR groups were smaller than that in the A-AV60 group， and the differences were statistically significant （both P < 0.001）. The SNR and CNR for AR， LAD， LCX and RCA were similar between the A-DLIR and B-DLIR groups， which were higher than those in the A-AV60 group （all P < 0.05）. The average subjective evaluation score of image quality in the B-DLIR group was higher than that in the A-AV60 group （P < 0.05）， whereas lower than that in the A-DLIR group （P < 0.05）. There were no significant differences in clarity， artifact and small branch visibility between the A-DLIR and B-DLIR groups （all P > 0.05）. Conclusions During CCTA， the 80 kV DLIR algorithm contributes to yielding high-quality images， further improves the diagnostic efficiency and reduces the irradiation dose.

Abstract Objectives To investigate the feasibility of a deep learning-constrained compressed sensing (DL-CS) method in non-contrast-enhanced modified DIXON (mDIXON) coronary magnetic resonance angiography (MRA) and compare its diagnostic accuracy using coronary CT angiography (CCTA) as a reference standard. Methods Ninety-nine participants were prospectively recruited for this study. Thirty healthy subjects (age range: 20–65 years; 50% female) underwent three non-contrast mDIXON-based coronary MRA sequences including DL-CS, CS, and conventional sequences. The three groups were compared based on the scan time, subjective image quality score, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). The remaining 69 patients suspected of coronary artery disease (CAD) (age range: 39–83 years; 51% female) underwent the DL-CS coronary MRA and its diagnostic performance was compared with that of CCTA. Results The scan time for the DL-CS and CS sequences was notably shorter than that of the conventional sequence (9.6 ± 3.1 min vs 10.0 ± 3.4 min vs 13.0 ± 4.9 min; p

Objectives: This study aimed to assess the impact of super-resolution deep learning reconstruction (SR-DLR) on coronary CT angiography (CCTA) image quality and blooming artifacts from coronary artery stents in comparison to conventional methods, including hybrid iterative reconstruction (HIR) and deep learning-based reconstruction (DLR). Methods: A retrospective analysis included 66 CCTA patients from July to November 2022. Major coronary arteries were evaluated for image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). Stent sharpness was quantified using 10%-90% edge rise slope (ERS) and 10%-90% edge rise distance (ERD). Qualitative analysis employed a 5-point scoring system to assess overall image quality, image noise, vessel wall, and stent structure. Results: SR-DLR demonstrated significantly lower image noise compared to HIR and DLR. SNR and CNR were notably higher in SR-DLR. Stent ERS was significantly improved in SR-DLR, with mean ERD values of 0.70 ± 0.20 mm for SR-DLR, 1.13 ± 0.28 mm for HIR, and 0.85 ± 0.26 mm for DLR. Qualitatively, SR-DLR scored higher in all categories. Conclusions: SR-DLR produces images with lower image noise, leading to improved overall image quality, compared with HIR and DLR. SR-DLR is a valuable image reconstruction algorithm for enhancing the spatial resolution and sharpness of coronary artery stents without being constrained by hardware limitations. Advances in knowledge: The overall image quality was significantly higher in SR-DLR, resulting in sharper coronary artery stents compared to HIR and DLR. [ABSTRACT FROM AUTHOR]

The sudden death of a young or high-level athlete or adolescent during recreational sports is one of the events with the greatest impact on public opinion in modern society. Sudden cardiac death (SCD) is the principal medical cause of death in athletes and can be the first and last clinical presentation of underlying disease. To prevent such episodes, pre-participation screening has been introduced in many countries to guarantee cardiovascular safety during sports and has become a common target among medical sports/governing organizations. Different cardiac conditions may cause SCD, with incidence depending on definition, evaluation methods, and studied populations, and a prevalence and etiology changing according to the age of athletes, with CAD most frequent in master athletes, while coronary anomalies and non-ischemic causes prevalent in young. To detect silent underlying causes early would be of considerable clinical value. This review summarizes the pre-participation screening in athletes, the specialist agonistic suitability visit performed in Italy, the anatomical characteristics of malignant coronary anomalies, and finally, the role of coronary CT angiography in such arena. In particular, the anatomical conditions suggesting potential disqualification from sport, the post-treatment follow-up to reintegrate young athletes, the diagnostic workflow to rule-out CAD in master athletes, and their clinical management are analyzed. [ABSTRACT FROM AUTHOR]

To investigate the diagnostic value of fractional flow reserve (FFR) of coronary CT angiography (CCTA) in coronary heart disease (CHD) in high altitude environment of plateau. 54 patients who underwent CCTA examination and guidewire measurement of FFR in Qinghai Provincial Cardiovascular and Cerebrovascular Disease Specialized Hospital from January 2022 to May 2023 were selected as the research objects. The data were collected by Flash dual-source spiral CT, CCTA-based FFR (CT-FFR) was simulated calculation by fluid mechanics principle based on CCTA images. FFR as the gold standard, positive predictive value, negative predictive value, sensitivity, accuracy and specificity of CT-FFR in the diagnosis of coronary heart disease and coronary artery lesions were analyzed, the diagnostic efficacy of CT-FFR in coronary heart disease and coronary artery lesions were analyzed by receiver operating characteristic (ROC) curve. The consistency between CT-FFR and FFR were analyzed by Bland-Altman plot. The positive predictive value of CT-FFR in the diagnosis of coronary heart disease was 73.08%, negative predictive value was 89.29%, sensitivity was 86.36%, accuracy was 81.48%, sensitivity was 78.13%. The area under the curve (AUC) of CT-FFR in the diagnosis of coronary heart disease was 0.854, and 95%CI was 0.747~0.962. The positive predictive value of CT-FFR in the diagnosis of coronary artery lesions was 71.05%, negative predictive value was 91.84%, sensitivity was 87.10%, accuracy was 82.76%, sensitivity was 80.36%. The AUC of CT-FFR in the diagnosis of coronary artery lesions was 0.921, and 95%CI was 0.865~0.978. Whether the diagnosis of coronary heart disease or diagnosis of coronary artery lesions, CT-FFR and FFR had good consistency. CT-FFR has high accuracy and sensitivity in the diagnosis of coronary heart disease in high altitude environment, and the detection efficiency is ideal, which has good consistency with FFR. [ABSTRACT FROM AUTHOR]

Aims The incremental impact of atherosclerosis imaging-quantitative computed tomography (AI-QCT) on diagnostic certainty and downstream patient management is not yet known. The aim of this study was to compare the clinical utility of the routine implementation of AI-QCT versus conventional visual coronary CT angiography (CCTA) interpretation. Methods and results In this multi-centre cross-over study in 5 expert CCTA sites, 750 consecutive adult patients referred for CCTA were prospectively recruited. Blinded to the AI-QCT analysis, site physicians established patient diagnoses and plans for downstream non-invasive testing, coronary intervention, and medication management based on the conventional site assessment. Next, physicians were asked to repeat their assessments based upon AI-QCT results. The included patients had an age of 63.8 ± 12.2 years; 433 (57.7%) were male. Compared with the conventional site CCTA evaluation, AI-QCT analysis improved physician's confidence two- to five-fold at every step of the care pathway and was associated with change in diagnosis or management in the majority of patients (428; 57.1%; P < 0.001), including for measures such as Coronary Artery Disease-Reporting and Data System (CAD-RADS) (295; 39.3%; P < 0.001) and plaque burden (197; 26.3%; P < 0.001). After AI-QCT including ischaemia assessment, the need for downstream non-invasive and invasive testing was reduced by 37.1% (P < 0.001), compared with the conventional site CCTA evaluation. Incremental to the site CCTA evaluation alone, AI-QCT resulted in statin initiation/increase an aspirin initiation in an additional 28.1% (P < 0.001) and 23.0% (P < 0.001) of patients, respectively. Conclusion The use of AI-QCT improves diagnostic certainty and may result in reduced downstream need for non-invasive testing and increased rates of preventive medical therapy. [ABSTRACT FROM AUTHOR]

Multidetector computed tomography is considered a reliable, non-invasive modality for diagnosing myocardial bridging. The prevalence of myocardial bridges varies greatly based on the technique used to identify the anomaly. We aimed to evaluate the frequency and morphological features of myocardial bridging in patients who underwent ECG-gated 640 slice Multidetector computed tomography coronary angiography at Shahid Gangalal National Heart Centre.

Transthoracic echocardiography is the main imaging modality to diagnose left ventricular thrombus (LVT), but its efficacy in certain cases is suboptimal. We report a patient in whom an LVT, initially unidentified by transthoracic echocardiography, was successfully diagnosed with iodine maps derived from dual-source photon-counting detector CT (DS-PCD-CT). The 64-year-old male was admitted to our institution following myocardial infarction. Although TTE failed to detect this small LVT, iodine maps derived from CT angiography (which was conducted to evaluate the coronary artery stenosis) revealed its presence. Iodine maps derived from DS-PCD-CT collecting data with high temporal resolution are beneficial to diagnose LVTs.

BACKGROUND: Ischemia with nonobstructive coronary arteries (INOCA) is common clinically, particularly among women, but its prevalence among patients with at least moderate ischemia and the relationship between ischemia severity and non-obstructive atherosclerosis severity are unknown. OBJECTIVES: The authors investigated predictors of INOCA in enrolled, nonrandomized participants in ISCHEMIA (International Study of Comparative Health Effectiveness with Medical and Invasive Approaches), sex differences, and the relationship between ischemia and atherosclerosis in patients with INOCA. METHODS: Core laboratories independently reviewed screening noninvasive stress test results (nuclear imaging, echocardiography, magnetic resonance imaging or nonimaging exercise tolerance testing), and coronary computed tomography angiography (CCTA), blinded to results of the screening test. INOCA was defined as all stenoses

The long-term prognostic implications of CT angiography-derived fractional flow reserve (FFR CT) remains unclear. We aimed to explore the long-term outcomes of FFR CT in the first-in-human study of it. A total of 156 vessels from 102 patients with stable coronary artery disease, who underwent coronary CT angiography (CCTA) and invasive FFR measurement, were followed. The primary endpoint was target vessel failure (TVF), including cardiovascular death, target vessel myocardial infarction, and target vessel revascularization. Outcome analysis with FFR CT was performed on a per-vessel basis using a marginal Cox proportional hazard model. During median 9.9 years of follow-up, TVF occurred in 20 (12.8%) vessels. FFR CT ​≤0.80 discriminated TVF (hazard ratio [HR] 2.61, 95% confidence interval [CI] 1.06, 6.45). Among 94 vessels with deferral of percutaneous coronary intervention (PCI), TVF risk was inversely correlated with FFR CT ​(HR 0.62 per 0.1 increase, 95% CI 0.44, 0.86), with the cumulative incidence of TVF being 2.6%, 15.2%, and 28.6% for vessels with FFR CT ​>0.90, 0.81–0.90, and ≤0.80, respectively (p-for-trend 0.005). Predictive value for clinical outcomes of FFR CT was similar to that of invasive FFR (c-index 0.79 vs 0.71, P ​= ​0.28). The estimated TVF risk was higher in the deferral of PCI group than the PCI group for vessels with FFR CT ≤0.81. FFR CT showed improved long-term risk stratification and displayed a risk continuum similar to invasive FFR. NCT01189331. Table of Contents Summary. [ABSTRACT FROM AUTHOR]

Objective: To assess the accuracy of a virtual stenting tool based on coronary CT angiography (CCTA) and fractional flow reserve (FFR) derived from CCTA (FFRCT Planner) across different levels of image quality. Materials and methods: Prospective, multicenter, single-arm study of patients with chronic coronary syndromes and lesions with FFR ≤ 0.80. All patients underwent CCTA performed with recent-generation scanners. CCTA image quality was adjudicated using the four-point Likert scale at a per-vessel level by an independent committee blinded to the FFRCT Planner. Patient- and technical-related factors that could affect the FFRCT Planner accuracy were evaluated. The FFRCT Planner was applied mirroring percutaneous coronary intervention (PCI) to determine the agreement with invasively measured post-PCI FFR. Results: Overall, 120 patients (123 vessels) were included. Invasive post-PCI FFR was 0.88 ± 0.06 and Planner FFRCT was 0.86 ± 0.06 (mean difference 0.02 FFR units, the lower limit of agreement (LLA) − 0.12, upper limit of agreement (ULA) 0.15). CCTA image quality was assessed as excellent (Likert score 4) in 48.3%, good (Likert score 3) in 45%, and sufficient (Likert score 2) in 6.7% of patients. The FFRCT Planner was accurate across different levels of image quality with a mean difference between FFRCT Planner and invasive post-PCI FFR of 0.02 ± 0.07 in Likert score 4, 0.02 ± 0.07 in Likert score 3 and 0.03 ± 0.08 in Likert score 2, p = 0.695. Nitrate dose ≥ 0.8mg was the only independent factor associated with the accuracy of the FFRCT Planner (95%CI − 0.06 to − 0.001, p = 0.040). Conclusion: The FFRCT Planner was accurate in predicting post-PCI FFR independent of CCTA image quality. Clinical relevance statement: Being accurate in predicting post-PCI FFR across a wide spectrum of CT image quality, the FFRCT Planner could potentially enhance and guide the invasive treatment. Adequate vasodilation during CT acquisition is relevant to improve the accuracy of the FFRCT Planner. Key Points: • The fractional flow reserve derived from coronary CT angiography (FFRCT) Planner is a novel tool able to accurately predict fractional flow reserve after percutaneous coronary intervention. • The accuracy of the FFRCT Planner was confirmed across a wide spectrum of CT image quality. Nitrates dose at CT acquisition was the only independent predictor of its accuracy. • The FFRCT Planner could potentially enhance and guide the invasive treatment. [ABSTRACT FROM AUTHOR]

Objective Coronary artery fistula is the termination of the coronary artery branch in the cardiac chamber or pulmonary vein. In this study, we aimed to evaluate the type, origin, termination, and accompanying anomalies, if any, of coronary artery fistulas in patients who underwent coronary CTA in our clinic. Material and Method Coronary CTA examinations were performed on a 128-slice CT scanner. Images were evaluated using MPR, MIP and 3D VR reconstructions on the workstation. CTA image interpretation was performed independently by two radiologists with 15 and 2 years of experience in coronary CTA. In case of disagreement, a third radiologist was consulted. Results Coronary artery fistulas were found in 8 female and 6 male patients aged between 10 and 71 years, with a mean age of 39.07 years. Of the 15 fistula, 6 were coronacameral fistula, 7 were coronopulmonary fistula, 1 was between the left circumflex artery and the conal branch of the right coronary artery, and 1 was between the pulmonary trunk and the descending aorta. One patient was treated with coil placement in the interventional radiology department, while three cases were treated surgically. The other cases were followed up by the relevant clinics. Conclusion Coronary CT angiography provides three-dimensional images of the origin, course and termination of the fistula and is an important tool in guiding the patient's treatment plan. [ABSTRACT FROM AUTHOR]

Objective: Coronary artery anatomical variations and anomalies are an important topic due to their potential clinical manifestations. This study aims to investigate the prevalence of coronary artery anatomical variations and anomalies in symptomatic patients with coronary computed tomography angiography (CCTA). Methods: This is a retrospective study that included all symptomatic patients who had CCTA in a tertiary care hospital in Saudi Arabia during a period of seven years. Results: The total number of included patients was 507 (60% males) with a mean age of 57.4 years. Approximately 41% had luminal stenoses, averaging 49.7%. The total number of patients with coronary anatomical variations (CAV) and coronary artery anomalies (CAA) was 217 (43%). CAV prevalence was 26%, which included 14% non-right coronary dominance, 5% short left main coronary artery (LMCA), and 7% division variations (trifurcation and quadrifurcarion) of the LMCA. The prevalence of CAA was 29%, which included 5% origin anomalies, 22% myocardial bridge, and 2% course anomalies. Conclusions: A high prevalence of coronary artery anatomic variations and anomalies in symptomatic patients is reported in this study. Systematic reviews, meta-analyses, reporting guidelines, and unified definitions and classifications of coronary variations and anomalies are lacking in the literature, presenting potential opportunities for future research and publications. [ABSTRACT FROM AUTHOR]

Background: The risk of coronary artery disease (CAD) and CAD events is increased in those with diabetes mellitus (DM). When compared to individuals without diabetes, type 2 diabetics have a two- to four-fold higher risk of cardiovascular events. Aim: To use optical coherence tomography angiography to evaluate DM duration as a predictor of coronary atherosclerosis in patients presenting by chest pain with low to intermediate pre-test probability (PTP). Methods: This was a cohort observational study that used coronary CT angiography to assess the relationship between DM duration and coronary atherosclerosis in individuals presenting with low to intermediate PTP and chest pain. Depending on the length of DM, patients were divided into three equal groups: Group A with DM duration is less than five years, Group B with DM duration is five to ten years, and Group C with DM duration is more than ten years. Results: There were significant variations in the coronary computed tomography angiography (CCTA) results for coronary artery disease (CAD) and coronary artery calcium scores across the groups under study. Group C had a significantly higher prevalence of stenosis (≥50%) than groups A and B. While the vessels affected showed insignificant differences among the groups, the coronary artery calcium score was higher in group C compared to both A and B, with group B also exhibiting a significantly higher score than group A. Atheroma burden obstructive and segment involve scores were significantly elevated in group C compared to both A and B, with insignificant variation between groups A and B. The segment stenosis score was higher in groups B and C compared to group A, while being insignificant between B and C. There were differences between the groups in the parts of the left anterior descending, left circumflex, and right coronary arteries, with different patterns of importance in the proximal, mid, and distal parts. Group C experienced a significant higher incidence of major adverse cardiac and cerebrovascular events (MACCE) early in life compared to groups A and B. The best cutoff of burden thrombus score for prediction of stenosis and time for detection of obstructive coronary atheroma burden was >0, >7 years with 100%, 61.76% sensitivity, 100%, 66.67% specificity, 100%,79.7% PPV and 100%, 45.1%NPV respectively. Conclusion: Long-term diabetes was strongly correlated with a higher severity of coronary atheroma load. Individuals who had had diabetes for longer than ten years showed a dramatically greater frequency of severe adverse cardiovascular events, an increased atheroma burden, and significantly raised rates of coronary artery disease (CAD). [ABSTRACT FROM AUTHOR]

To identify anatomical and morphological plaque features predictors of PCI and create a multiparametric score to increase the predictive yield. Moreover, we assessed the incremental predictive value of FFR CT (Fractional Flow Reserve derived from CCTA) trans -lesion gradient (ΔFFR CT) when integrated into the score. Observational cohort study including patients undergoing CCTA for suspected coronary artery disease, with FFR CT available, referred to invasive coronary angiogram and assessment of fractional flow reserve. Plaque analysis was performed using validated semi-automated software. Logistic regression was performed to identify anatomical and morphological plaque features predictive of PCI. Optimal thresholds were defined by area under the receiver-operating characteristics curve (AUC) analysis. A scoring system was developed in a derivation cohort (70 ​% of the study population) and tested in a validation cohort (30 ​% of patients). The overall study population included 340 patients (455 vessels), among which 238 patients (320 vessels) were included in the derivation cohort. At multivariate logistic regression analysis, absence of left main disease, diameter stenosis (DS), non-calcified plaque (NCP) volume, and percent atheroma volume (PAV) were independent predictors of PCI. Optimal thresholds were: DS ​≥ ​50 ​%, volume of NCP>113 ​mm3 and PAV>17 ​%. A weighted score (CT-PCI Score) ranging from 0 to 11 was obtained. The AUC of the score was 0.80 (95%CI 0.74–0.86). The integration of ΔFFR CT in the CT-PCI score led to a mild albeit not significant increase in the AUC (0.82, 95%CI 0.77–0.87, p ​= ​0.328). Plaque anatomy and morphology derived from CCTA could aid in identifying patients amenable to PCI. Derivation of the "CT-PCI score". At the top, each variable included in the score with the relative score assigned is described. At the bottom, the ROC curve of the score to predict PCI is reported. [Display omitted] Coronary CT Angiography (CCTA) has become an established tool in the diagnostic work-up of patients with a low-to-intermediate likelihood of coronary artery disease (CAD), allowing the evaluation of anatomical, morphological, and functional plaque features. CCTA could aid decision-making for treatment strategy. We derived a CCTA score (CT-PCI score) based on plaque anatomy and morphology able to predict PCI referral in a cohort of patients undergoing CCTA for suspected CAD, with FFR CT available, referred to invasive coronary angiography and physiological assessment. The AUC of the score was 0.80 (95%CI 0.74–0.86), sensitivity ​= ​68.0 ​%, specificity ​= ​84.0 ​%, accuracy ​= ​80.0 ​%. The integration of ΔFFR CT in the CT-PCI score led to a mild albeit not significant increase in the accuracy. [ABSTRACT FROM AUTHOR]

ObjectiveThis study aims to investigate the image quality of a high-resolution, low-dose coronary CT angiography (CCTA) with deep learning image reconstruction (DLIR) and second-generation motion correction algorithms, namely, SnapShot Freeze 2 (SSF2) algorithm, and its diagnostic accuracy for in-stent restenosis (ISR) in patients after percutaneous coronary intervention (PCI), in comparison with standard-dose CCTA with high-definition mode reconstructed by adaptive statistical iterative reconstruction Veo algorithm (ASIR-V) and the first-generation motion correction algorithm, namely, SnapShot Freeze 1 (SSF1).MethodsPatients after PCI and suspected of having ISR scheduled for high-resolution CCTA (randomly for 100 kVp low-dose CCTA or 120 kVp standard-dose) and invasive coronary angiography (ICA) were prospectively enrolled in this study. After the basic information pairing, a total of 105 patients were divided into the LD group (60 patients underwent 100 kVp low-dose CCTA reconstructed with DLIR and SSF2) and the SD group (45 patients underwent 120 kVp standard-dose CCTA reconstructed with ASIR-V and SSF1). Radiation and contrast medium doses, objective image quality including CT value, image noise (standard deviation), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) for the aorta, left main artery (LMA), left ascending artery (LAD), left circumflex artery (LCX), and right coronary artery (RCA) of the two groups were compared. A five-point scoring system was used for the overall image quality and stent appearance evaluation. Binary ISR was defined as an in-stent neointimal proliferation with diameter stenosis ≥50% to assess the diagnostic performance between the LD group and SD group with ICA as the standard reference.ResultsThe LD group achieved better objective and subjective image quality than that of the SD group even with 39.1% radiation dose reduction and 28.0% contrast media reduction. The LD group improved the diagnostic accuracy for coronary ISR to 94.2% from the 83.8% of the SD group on the stent level and decreased the ratio of false-positive cases by 19.2%.ConclusionCompared with standard-dose CCTA with ASIR-V and SSF1, the high-resolution, low-dose CCTA with DLIR and SSF2 reconstruction algorithms further improves the image quality and diagnostic performance for coronary ISR at 39.1% radiation dose reduction and 28.0% contrast dose reduction.

Background and aimsPeople living with HIV (HIV+) are surviving longer due to effective antiretroviral therapy. Cardiovascular disease is a leading cause of non-AIDS related clinical events. We determined HIV-related factors associated with coronary artery stenosis progression.MethodsWe performed serial coronary CT angiography among HIV+ and HIV-uninfected (HIV-) men in the Multicenter AIDS Cohort Study. The median inter-scan interval was 4.5 years. Stenosis was graded as 0, 1-29, 30-49, 50-69 or ≥70%. Progression was defined as an increase ≥2 categories. Suppressed HIV infection was consistent viral loads 1 viral load >500 copies/ml demonstrated greatest stenosis progression (RR 3.01; 95% CI, 1.53-4.92, p = 0.001 compared with HIV- men). Suppressed HIV+ men with suboptimal antiretroviral adherence had greater stenosis progression (RR 1.91; 95% CI 1.12-3.24, p = 0.02) than HIV + suppressed men with optimal adherence.ConclusionsCoronary artery stenosis progression was associated with suboptimal HIV RNA suppression and antiretroviral therapy adherence. Effective ongoing HIV virologic suppression and antiretroviral therapy adherence may mitigate risk for coronary disease events among people living with HIV.

Objectives Fat radiomic profile (FRP) was a promising imaging biomarker for identifying increased cardiac risk. We hypothesize FRP can be extended to fat regions around pulmonary veins (PV), left atrium (LA), and left atrial appendage (LAA) to investigate their usefulness in identifying atrial fibrillation (AF) and the risk of AF recurrence. Methods We analysed 300 individuals and grouped patients according to the occurrence and types of AF. We used receiver operating characteristic and survival curves analyses to evaluate the value of imaging biomarkers, including fat attenuation index (FAI) and FRP, in distinguishing AF from sinus rhythm and predicting post-ablation recurrence. Results FRPs from AF-relevant fat regions showed significant performance in distinguishing AF and non-AF with higher AUC values than FAI (peri-PV: FRP = 0.961 vs FAI = 0.579, peri-LA: FRP = 0.923 vs FAI = 0.575, peri-LAA: FRP = 0.900 vs FAI = 0.665). FRPs from peri-PV, peri-LA, and peri-LAA were able to differentiate persistent and paroxysmal AF with AUC values of 0.804, 0.819, and 0.694. FRP from these regions improved AF recurrence prediction with an AUC of 0.929, 0.732, and 0.794. Patients with FRP cut-off values of ≥0.16, 0.38, and 0.26 had a 7.22-, 5.15-, and 4.25-fold higher risk of post-procedure recurrence, respectively. Conclusions FRP demonstrated potential in identifying AF, distinguishing AF types, and predicting AF recurrence risk after ablation. FRP from peri-PV fat depot exhibited a strong correlation with AF. Therefore, evaluating epicardial fat using FRP was a promising approach to enhance AF clinical management. Advances in knowledge The role of epicardial adipose tissue (EAT) in AF had been confirmed, we focussed on the relationship between EAT around pulmonary arteries and LAA in AF which was still unknown. Meanwhile, we used the FRP to excavate more information of EAT in AF. [ABSTRACT FROM AUTHOR]

Cardiac function and structure significantly impact nonischemic heart failure (HF) patient outcomes. This study investigated 236 patients (107 nonischemic heart failure, 129 healthy) to assess the relationship between coronary computed tomography angiography (CCTA)-derived parameters and clinical outcomes. Among the nonischemic heart failure patients, 37.3% experienced readmissions. In this group, specific CCTA measurements were identified as significant predictors of readmission: epicardial adipose tissue (CTEAT) at 54.49 cm3 (HR: 1.05; 95% CI: 1.03–1.07; P < 0.001), cardiac muscle mass to lumen volume (CTV/M) at 20% (HR: 0.59; 95% CI: 0.48–0.72; P < 0.001), peri-coronary adipose (CTPCAT) at -64.68 HU (HR: 1.1; 95% CI: 1.03–1.16; P = 0.002) for the right coronary artery, -81.07 HU (HR: 1.3; 95% CI: 1.1–1.53; P = 0.002) for the left anterior descending artery, and -73.42 HU (HR: 1.33; 95% CI: 1.18–1.51; P < 0.001) for the circumflex branch of the left coronary artery. In patients with nonischemic heart failure, increased CTEAT, CTPCAT, and CTV/M independently predicted rehospitalization. [ABSTRACT FROM AUTHOR]

Background: Coronary CT angiography (CCTA) may detect coronary artery disease (CAD) in transcatheter aortic valve implantation (TAVI) patients and may obviate invasive coronary angiography (ICA) in selected patients. We assessed the diagnostic accuracy of CCTA for detecting CAD in TAVI patients based on published data. Methods: Meta-analysis and meta-regression were performed based on a comprehensive electronic search, including relevant studies assessing the diagnostic accuracy of CCTA in the setting of TAVI patients compared to ICA. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), were calculated on a patient and per segment level. Results: Overall, 27 studies (total of 7458 patients) were included. On the patient level, the CCTA's pooled sensitivity and NPV were 95% (95% CI: 93–97%) and 97% (95% CI: 95–98%), respectively, while the specificity and PPV were at 73% (95% CI: 62–82%) and 64% (95% CI: 57–71%), respectively. On the segmental coronary vessel level, the sensitivity and NPV were 90% (95% CI: 79–96%) and 98% (95% CI: 97–99%). Conclusions: This meta-analysis highlights CCTA's potential as a first-line diagnostic tool although its limited PPV and specificity may pose challenges when interpreting heavily calcified arteries. This study underscores the need for further research and protocol standardization in this area. [ABSTRACT FROM AUTHOR]

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Coronary artery disease is a leading cause of death worldwide. Major adverse cardiac events are associated not only with coronary luminal stenosis but also with atherosclerotic plaque components. Coronary computed tomography angiography (CCTA) enables noninvasive evaluation of atherosclerotic plaque along the entire coronary tree. However, precise and efficient assessment of plaque features on CCTA is still a challenge for physicians in daily practice. Artificial intelligence (AI) refers to algorithms that can simulate intelligent human behavior to improve clinical work efficiency. Recently, cardiovascular imaging has seen remarkable advancements with the use of AI. AI-assisted CCTA has the potential to facilitate the clinical workflow, offer objective and repeatable quantitative results, accelerate the interpretation of reports, and guide subsequent treatment. Several AI algorithms have been developed to provide a comprehensive assessment of atherosclerotic plaques. This review serves to highlight the cutting-edge applications of AI-assisted CCTA in atherosclerosis plaque characterization, including detecting obstructive plaques, assessing plaque volumes and vulnerability, monitoring plaque progression, and providing risk assessment. Finally, this paper discusses the current problems and future directions for implementing AI in real-world clinical settings. [ABSTRACT FROM AUTHOR]

As the number of coronary computed tomography angiography (CTA) examinations is expected to increase, technologies to optimize the imaging workflow are of great interest. The aim of this study was to investigate the potential of artificial intelligence (AI) to improve clinical workflow and diagnostic accuracy in high-volume cardiac imaging centers. A total of 120 patients (79 men; 62.4 (55.0–72.7) years; 26.7 (24.9–30.3) kg/m2) undergoing coronary CTA were randomly assigned to a standard or an AI-based (human AI) coronary analysis group. Severity of coronary artery disease was graded according to CAD-RADS. Initial reports were reviewed and changes were classified. Both groups were similar with regard to age, sex, body mass index, heart rate, Agatston score, and CAD-RADS. The time for coronary CTA assessment (142.5 (106.5–215.0) s vs. 195.0 (146.0–265.5) s; p < 0.002) and the total reporting time (274.0 (208.0–377.0) s vs. 350 (264.0–445.5) s; p < 0.02) were lower in the human AI than in the standard group. The number of cases with no, minor, or CAD-RADS relevant changes did not differ significantly between groups (52, 7, 1 vs. 50, 8, 2; p = 0.80). AI-based analysis significantly improves clinical workflow, even in a specialized high-volume setting, by reducing CTA analysis and overall reporting time without compromising diagnostic accuracy. [ABSTRACT FROM AUTHOR]

Purpose of Review: The study aims to describe methods for detecting subclinical coronary artery disease (CAD) and their potential implications in asymptomatic patients with diabetes. Recent Findings: Imaging tools can assess non-invasively the presence and severity of CAD, based on myocardial ischemia, coronary artery calcium score, and coronary computed tomography coronary angiography. Subclinical CAD is common in the general population ageing 50 to 64 years with any coronary atherosclerosis present in 42.1% and obstructive CAD in 5.2%. In patients with diabetes, an even higher prevalence has been noted. The presence of myocardial ischemia, obstructive CAD, and the extent of coronary atherosclerosis provide powerful risk stratification regarding the risk of cardiovascular events. However, randomized trials evaluating systematic screening in the general population or patients with diabetes have demonstrated only moderate impact on management and no significant impact on patient outcomes. Summary: Despite providing improved risk stratification, systematic screening of CAD is not recommended in patients with diabetes. [ABSTRACT FROM AUTHOR]

Background Coronary artery disease (CAD) is a leading cause of death among the 38.4 million people with HIV globally. The extent to which cardiovascular polygenic risk scores (PRSs) derived in non‐HIV populations generalize to people with HIV is not well understood. Methods and Results PRSs for CAD (GPSMult) and lipid traits were calculated in a global cohort of people with HIV treated with antiretroviral therapy with low‐to‐moderate atherosclerotic cardiovascular disease risk enrolled in REPRIEVE (Randomized Trial to Prevent Vascular Events in HIV). The PRSs were associated with baseline lipid traits in 4495 genotyped participants, and with subclinical CAD in a subset of 662 who underwent coronary computed tomography angiography. Among participants who underwent coronary computed tomography angiography (mean age, 50.9 [SD, 5.8] years; 16.1% women; 41.8% African, 57.3% European, 1.1% Asian), GPSMult was associated with plaque presence with odds ratio (OR) per SD in GPSMult of 1.42 (95% CI, 1.20–1.68; P=3.8×10−5), stenosis >50% (OR, 2.39 [95% CI, 1.48–3.85]; P=3.4×10−4), and noncalcified/vulnerable plaque (OR, 1.45 [95% CI, 1.23–1.72]; P=9.6×10−6). Effects were consistent in subgroups of age, sex, 10‐year atherosclerotic cardiovascular disease risk, ancestry, and CD4 count. Adding GPSMult to established risk factors increased the C‐statistic for predicting plaque presence from 0.718 to 0.734 (P=0.02). Furthermore, a PRS for low‐density lipoprotein cholesterol was associated with plaque presence with OR of 1.21 (95% CI, 1.01–1.44; P=0.04), and partially calcified plaque with OR of 1.21 (95% CI, 1.01–1.45; P=0.04) per SD. Conclusions Among people with HIV treated with antiretroviral therapy without documented atherosclerotic cardiovascular disease and at low‐to‐moderate calculated risk in REPRIEVE, an externally developed CAD PRS was predictive of subclinical atherosclerosis. PRS for low‐density lipoprotein cholesterol was also associated with subclinical atherosclerosis, supporting a role for low‐density lipoprotein cholesterol in HIV‐associated CAD. Registration URL: https://www.reprievetrial.org; Unique identifier: NCT02344290.

Coronary artery anomalies are congenital variations of the origin(s), course(s), and terminations(s) of the 3 main epicardial coronary arteries that make up less than 1% of cases. Clinically, coronary artery anomalies can be asymptomatic or present with dyspnea, chest pain, and even sudden cardiac death. In this report, we discuss the case of a patient who was found to have a rare presentation of an anomalous right coronary artery originating from the anterior ascending aorta 20.9 mm above the sino-tubular junction that was discovered on coronary CT angiography.

The review article highlights the main stages of the formation of computed tomography (CT) as a key method used in modern cardiology. The progress of CT scanners is directly related to the increase in the number of detectors, and thus, with an increase in the number of simultaneously collected projections. Modern developments and future technologies in the field of further development of the technique, including CT angiography and other new methods for assessing coronary blood flow, are discussed. The use of artificial intelligence technologies may make it possible to improve and accelerate the interpretation of the resulting images in the future, especially if it is economically justified.

Purpose of reviewTo provide an update and to outline the status of coronary computer tomography angiography (CCTA) in evaluation of coronary plaques and discuss the relevance of serial CCTA in guiding cardiovascular risk stratification and anti- atherosclerotic medical therapy.Recent findingsCoronary CTA is now the imaging modality of choice in monitoring changes in coronary plaque. It has been used in innumerable clinical trials which have demonstrated the benefits of several therapeutic agents and has excellent correlation with previously used invasive imaging modalities. It is safe, fast, less cumbersome, and a cost-effective testing method compared to other invasive imaging modalities for coronary plaque analysis.SummaryThe emergence of a noninvasive imaging modality such as CCTA, now permits quantification not only of plaque burden but also allows for further distinction of plaque components and identification of vulnerable plaques. Application of these findings continues to extend the prospect of coronary CTA in evaluation and management of atherosclerotic coronary artery disease (CAD) in clinical practice. In the future artificial intelligence and machine learning will play a significant role in plaque analysis allowing for high accuracy and reproducibility which will lead to a substantial increase in the utilization of coronary CTA.

IntroductionAccurate identification of the myocardial texture features of fat around the coronary artery on coronary computed tomography angiography (CCTA) images are crucial to improve clinical diagnostic efficiency of myocardial ischemia (MI). However, current coronary CT examination is difficult to recognize and segment the MI characteristics accurately during earlier period of inflammation.Materials and methodsWe proposed a random forest model to automatically segment myocardium and extract peripheral fat features. This hybrid machine learning (HML) model is integrated by CCTA images and clinical data. A total of 1,316 radiomics features were extracted from CCTA images. To further obtain the features that contribute the most to the diagnostic model, dimensionality reduction was applied to filter features to three: LNS, GFE, and WLGM. Moreover, statistical hypothesis tests were applied to improve the ability of discriminating and screening clinical features between the ischemic and non-ischemic groups.ResultsBy comparing the accuracy, recall, specificity and AUC of the three models, it can be found that HML had the best performance, with the value of 0.848, 0.762, 0.704 and 0.729.ConclusionIn sum, this study demonstrates that ML-based radiomics model showed good predictive value in MI, and offer an enhanced tool for predicting prognosis with greater accuracy.

Objective: Coronary artery disease (CAD) usually coexists with subclinical cerebrovascular diseases given the systematic nature of atherosclerosis. In this study, our objective was to predict the progression of white matter hyperintensity (WMH) and find its risk factors in CAD patients using the coronary artery calcium (CAC) score. We also investigated the relationship between the CAC score and the WMH volume in different brain regions. Methods: We evaluated 137 CAD patients with WMH who underwent coronary computed tomography angiography (CCTA) and two magnetic resonance imaging (MRI) scans from March 2018 to February 2023. Patients were categorized into progressive (n = 66) and nonprogressive groups (n = 71) by the change in WMH volume from the first to the second MRI. We collected demographic, clinical, and imaging data for analysis. Independent risk factors for WMH progression were identified using logistic regression. Three models predicting WMH progression were developed and assessed. Finally, patients were divided into groups based on their total CAC score (0 to <100, 100 to 400, and > 400) to compare their WMH changes in nine brain regions. Results: Alcohol abuse, maximum pericoronary fat attenuation index (pFAI), CT-fractional flow reserve (CT-FFR), and CAC risk grade independently predicted WMH progression (p < 0.05). The logistic regression model with all four variables performed best (training: AUC = 0.878, 95% CI: 0.790, 0.938; validation: AUC = 0.845, 95% CI: 0.734, 0.953). An increased CAC risk grade came with significantly higher WMH volume in the total brain, corpus callosum, and frontal, parietal and occipital lobes (p < 0.05). Conclusion: This study demonstrated the application of the CCTA-derived CAC score to predict WMH progression in elderly people (=60 years) with CAD. [ABSTRACT FROM AUTHOR]

Objective To evaluate the effect of one-beat acquisition with wide detector CT on the image quality and diagnostic efficiency of coronary CT angiography(CCTA)in patients with atrial fibrillation. MethodsA total of 52 consecutive patients with atrial fibrillation, including 31 males,(67.32±11.45)years old, who underwent CCTA from July 2022 to February 2023, were analyzed retrospectively. All patients underwent one-beat acquisition CCTA. The subjective and objective image quality of the coronary arteries was evaluated, and using invasive coronary catheter angiography as the gold standard, the diagnostic efficacy of stenosis degrees above moderate and severe degrees was calculated, respectively. Results Subjective evaluation results: 92.31%(384/416)of the vascular segments were rated as excellent or good, and the diagnosable rate reached 98.08%(408/416, subjective score ≥3 points). Objective evaluation results: The CT value of the right coronary artery, anterior descending branch, and circumflex branch was(433.41±95.17)HU,(422.69±92.81)HU and(420.27±95.43)HU, respectively; the contrast-to-noise ratio was 38.46±7.54, 32.46±13.78 and 37.74±8.89, respectively. The total diagnostic accuracy, sensitivity, and specificity was 94.71%, 87.9% and 96.62%, respectively, for moderate stenosis and 96.15%, 83.64% and 98.06% for severe stenosis. Conclusion One-beat acquisition with wide detector CT can obtain high-quality coronary artery images and high diagnostic accuracy for patients with atrial fibrillation without radiation dose increase to patients. It has good clinical application value for patients with atrial fibrillation. [ABSTRACT FROM AUTHOR]

While coronary artery calcium (CAC) can now be evaluated by multiple imaging modalities, there is presently scant study regarding how CAC scores may vary among populations of varying clinical risk. We evaluated the distribution of CAC scores among three patient groups: 18,941 referred for CAC scanning, 5101 referred for diagnostic coronary CT angiography (CCTA), and 3307 referred for diagnostic positron emission tomography (PET) myocardial perfusion imaging (MPI). We assessed the relationship between CAC score and myocardial ischemia, obstructive coronary artery disease (CAD), and all-cause mortality across imaging modalities. Within each age group, the frequency of CAC abnormalities were relatively similar across testing modalities, despite an annualized mortality rate which varied from 0.5%/year among CAC patients to 3.8%/year among PET-MPI patients (p < 0.001). Among CCTA and PET-MPI patients, a zero CAC score was common, occurring in ~70% of patients <50 years, ~40% of patients 50–59 years, and ~ 25% of patients 60–69 years. Among CCTA patients, zero CAC was associated with a normal coronary angiogram with high frequency, ranging from 92.2% among patients <50 years to 87.9% among patients ≥70 years. Among PET-MPI patients, zero CAC was associated with a very low frequency of inducible ischemia across all age groups, ranging from 1.5% among patients <50 years to 0.9% among patients ≥70 years. In our study, relatively similar CAC scores were noted among patients varying markedly in mortality risk. Clinically, zero CAC scores predicted both a low likelihood of obstructive CAD and inducible myocardial ischemia in all age groups and were observed with high frequency across diagnostic testing modalities. [ABSTRACT FROM AUTHOR]

Non-obstructing small coronary plaques may not be well recognized by expert readers during coronary computed tomography angiography (CCTA) evaluation. Recent developments in atherosclerosis imaging quantitative computed tomography (AI-QCT) enabled by machine learning allow for whole-heart coronary phenotyping of atherosclerosis, but its diagnostic role for detection of small plaques on CCTA is unknown. We performed AI-QCT in patients who underwent serial CCTA in the multinational PARADIGM study. AI-QCT results were verified by a level III experienced reader, who was blinded to baseline and follow-up status of CCTA. This retrospective analysis aimed to characterize small plaques on baseline CCTA and evaluate their serial changes on follow-up imaging. Small plaques were defined as a total plaque volume <50 ​mm3. A total of 99 patients with 502 small plaques were included. The median total plaque volume was 6.8 ​mm3 (IQR 3.5–13.9 ​mm3), most of which was non-calcified (median 6.2 ​mm3; 2.9–12.3 ​mm3). The median age at the time of baseline CCTA was 61 years old and 63% were male. The mean interscan period was 3.8 ​± ​1.6 years. On follow-up CCTA, 437 (87%) plaques were present at the same location as small plaques on baseline CCTA; 72% were larger and 15% decreased in volume. The median total plaque volume and non-calcified plaque volume increased to 18.9 ​mm3 (IQR 8.3–45.2 ​mm3) and 13.8 ​mm3 (IQR 5.7–33.4 ​mm3), respectively, among plaques that persisted on follow-up CCTA. Small plaques no longer visualized on follow-up CCTA were significantly more likely to be of lower volume, shorter in length, non-calcified, and more distal in the coronary artery, as compared with plaques that persisted at follow-up. In this retrospective analysis from the PARADIGM study, small plaques (<50 ​mm3) identified by AI-QCT persisted at the same location and were often larger on follow-up CCTA. [ABSTRACT FROM AUTHOR]