Coronary Computed Tomography Imaging Research Articles

Computed tomography angiography assessment of Adamkiewicz artery with sublingual nitroglycerin administration.

Identification of the Adamkiewicz artery before aortic surgery is important for preventing postoperative complications due to spinal cord ischemia. The Adamkiewicz artery is difficult to identify due to its small diameter. Nitroglycerin has a vasodilatory effect and is used clinically to improve visualization of blood vessels on coronary computed tomography (CT) angiography. We investigated whether the vasodilatory effect of nitroglycerin could improve the ability to visualize the Adamkiewicz artery. We extracted 33 cases wherein contrast-enhanced CT images were taken before and after aortic aneurysm surgery. Nitroglycerin was administered for coronary artery evaluation on the preoperative CT. However, no nitroglycerin was administered before the postoperative CT. Aortic contrast-to-noise ratio, CT value, image noise, and diameter of the Adamkiewicz artery and anterior spinal artery were measured. The depiction of the Adamkiewicz artery was graded into four grades and evaluated. These measurements were performed by two independent reviewers. In nitroglycerin-administered cases, the contrast-to-noise ratio and CT values were significantly higher (P < 0.001, P < 0.001, respectively); the Adamkiewicz artery and anterior spinal artery diameters were dilated (P = 0.005, P = 0.001, respectively). The Adamkiewicz artery score also improved significantly (P < 0.001). No significant difference was found in image noise. Nitroglycerin contributed to improving the Adamkiewicz artery's visualization.

Agreement of ejection fraction measured by coronary computed tomography (CT) and cardiac ultrasound in evaluating patients with chronic heart failure: an observational comparative study.

Cardiac ultrasound is one of the most important examinations in cardiovascular medicine, but the technical requirements for the operator are relatively high, which to some extent affects the scope of its use. This study was dedicated to investigating the agreement of ejection fraction between coronary computed tomography (CT) and cardiac ultrasound and diagnostic performance in evaluating the clinical diagnosis of patients with chronic heart failure. We conducted a single-center-based retrospective study including 343 consecutive patients enrolled between January 2019 to April 2020, all of whom presented with suspected symptoms of heart failure within one month. All enrolled cases performed cardiac ultrasound and coronary CT scans. The CT images were analyzed using accurate left ventricle (AccuLV) artificial intelligence (AI) software to calculate the ejection fraction-computed tomography (EF-CT) and it was compared with the ejection fraction (EF) obtained based on ultrasound. Cardiac insufficiency was determined if the EF measured by ultrasound was below 50%. Diagnostic performance analysis, correlation analysis and Bland-Altman plot were used to compare agreement between EF-CT and CT. Of the 319 successfully performed patients, 220 (69%) were identified as cardiac insufficiency. Quantitative consistency analysis showed a good correlation between EF-CT and EF values in all cases (R square =0.704, r=0.837). Bland-Altman analysis showed mean bias of 6.6%, mean percentage error of 27.5% and 95% limit of agreement of -17% to 30% between EF and EF-CT. The results of the qualitative diagnostic study showed that the sensitivity and specificity of EF measured by coronary CT reached a high level of 91% [95% confidence interval (CI): 86-94%], and the positive diagnostic value was up to 96% (95% CI: 92-98%). The EF-CT and EF have excellent agreement, and AccuLV-based AI left ventricular function analysis software perhaps can be used as a clinical diagnostic reference.

Development of Pericardial Fat Count Images Using a Combination of Three Different Deep-Learning Models: Image Translation Model From Chest Radiograph Image to Projection Image of Three-Dimensional Computed Tomography

Pericardial fat (PF)-the thoracic visceral fat surrounding the heart-promotes the development of coronary artery disease by inducing inflammation of the coronary arteries. To evaluate PF, we generated pericardial fat count images (PFCIs) from chest radiographs (CXRs) using a dedicated deep-learning model. We reviewed data of 269 consecutive patients who underwent coronary computed tomography (CT). We excluded patients with metal implants, pleural effusion, history of thoracic surgery, or malignancy. Thus, the data of 191 patients were used. We generated PFCIs from the projection of three-dimensional CT images, wherein fat accumulation was represented by a high pixel value. Three different deep-learning models, including CycleGAN were combined in the proposed method to generate PFCIs from CXRs. A single CycleGAN-based model was used to generate PFCIs from CXRs for comparison with the proposed method. To evaluate the image quality of the generated PFCIs, structural similarity index measure (SSIM), mean squared error (MSE), and mean absolute error (MAE) of (i) the PFCI generated using the proposed method and (ii) the PFCI generated using the single model were compared. The mean SSIM, MSE, and MAE were 8.56×10-1, 1.28×10-2, and 3.57×10-2, respectively, for the proposed model, and 7.62×10-1, 1.98×10-2, and 5.04×10-2, respectively, for the single CycleGAN-based model. PFCIs generated from CXRs with the proposed model showed better performance than those generated with the single model. The evaluation of PF without CT may be possible using the proposed method.

P153 A DEEP–LEARNING APPROACH FOR SCAR DETECTION IN EARLY CONTRAST–ENHANCED CARDIAC COMPUTED TOMOGRAPHY IMAGES

Abstract Diagnosis of myocardial fibrosis has a relevant prognostic and therapeutic role. Scar–tissue analysis is commonly performed with late gadolinium contrast–enhanced (CE) cardiac magnetic resonance (CMR). However, CMR might be contraindicated or unavailable. Coronary computed tomography (CCT), which is the technique of choice for many routine assessments, is emerging as an alternative to CMR. The objective of this study is to evaluate whether artificial intelligence (AI) could allow identification of myocardial fibrosis from routine early CE–CCT images. Fifty consecutive patients with left ventricular dysfunction (LVD), who underwent both CE–CMR and (early and late) CE–CCT were retrospectively selected. According to the late enhancement CMR patterns, patients were classified as with ischemic (n=15, 30%) or non–ischemic (n=25, 70%) LVD. Scar regions were manually traced on late CE–CCT using CE–CMR as ground–truth. On early CE–CCT images, the myocardial sectors were extracted according to AHA 16–segment model and labeled as with scar or not based on the late CE–CCT manual tracing. A deep–learning model was developed to classify each sector (Picture 1). Of the initial 44187 sectors computed out of the 8285 slices available from the early CE–CCT images, 4594 sectors (10%) presented scar. The CNN approach on the early CE–CCT images yielded a classification accuracy for all sectors of 71% (95% confidence interval (CI): 63%–79%) obtained through 5–fold cross validation. The mean sensitivity, positive predictive value (PPV) and negative predictive value (NPV) for the testing fold resulted in 73% (95% CI: 66%–79%), 56% (95% CI: 48%–65%) and 85% (95% CI: 82%– 88%), respectively. The mean AUC across the five folds was 76% (95% CI: 72%–81%). In a per–segment analysis of the 16–segment AHA model the bull’s eye segmental comparison of CE–CMR and respective early CE–CCT findings an 91% agreement was achieved (Picture 2). Artificial intelligence can detect both ischemic and non–ischemic myocardial fibrosis from routine noninvasive coronary scans, without additional contrast–agent administration or radiational dose, thus assisting diagnosis and management of patients with LV dysfunction and coronary artery disease.

Identification of Optical Coherence Tomography-Defined Coronary Plaque Erosion by Preprocedural Computed Tomography Angiography.

Background A previous coronary computed tomography (CT) angiographic study failed to discriminate optical coherence tomography-defined intact fibrous cap culprit lesions (IFC group) from those with ruptured fibrous caps (RFC group) in patients with coronary artery disease. This study aimed to evaluate the diagnostic efficacy of preprocedural coronary CT imaging in identifying subsequently performed optical coherence tomography-defined plaque rupture or erosion at culprit lesions in patients with non-ST-segment-elevation acute myocardial infarction. Methods and Results This study used data from 2 recently published studies that tested the hypothesis that coronary CT angiography (CCTA) before percutaneous coronary intervention may provide diagnostic information on the high-risk atherosclerotic burden in patients with non-ST-segment-elevation acute myocardial infarction. In the analysis of 186 patients, optical coherence tomography identified 106 RFC plaques and 80 IFC plaques as the culprit lesions. On CT, the prevalence of low-attenuation plaque, positive remodeling, napkin-ring sign, and spotty calcification were all significantly lower in the IFC group. The culprit vessel pericoronary adipose tissue inflammation and coronary artery calcium scores were significantly lower in the IFC group than in the RFC group. The absence of low-attenuation plaque, napkin-ring sign, zero coronary artery calcium, and low pericoronary adipose tissue inflammation were independent predictors of IFC. When stratified into 5 subgroups according to the number of these 4 CT factors, the prevalence of IFC was 8.3%, 20.8%, 44.6%, 75.6%, and 100% (P<0.001), respectively. Conclusions Preprocedural comprehensive coronary CT imaging, including coronary artery calcium and pericoronary adipose tissue inflammation assessment, can accurately and noninvasively identify optical coherence tomography-defined IFC or RFC culprit lesions.

The Value of Iterative Reconstruction of Algorithm-Based Coronary Artery Computed Tomography Imaging in the Diagnosis of Old Myocardial Infarction.

The objective of this study was to compare the diagnostic value of computed tomography (CT) based on iterative reconstruction algorithm in old myocardial infarction (OMI), thereby providing theoretical guidance and practical basis for clinical treatment. In this study, in order to provide theoretical guidance and practical basis for the diagnosis and treatment of clinical OMI, 10 patients with OMI were selected and divided into two groups, with 5 patients in each group. In addition, an algebraic iterative reconstruction algorithm is constructed, which starts from the initial estimation value, compares, and corrects the estimation results and the measured results continuously until the error between the two results is less than the predetermined value. The experimental group was optimized by algebraic iterative reconstruction algorithm, and the control group was reconstructed by the hospital original method. The image quality parameters under different iteration times were analyzed and compared to obtain the optimal iteration times. The value of iterative reconstruction algorithm in clinical diagnosis was investigated by analyzing the time of drawing and the accuracy of diagnosis after drawing. Through the analysis and comparison of the image quality parameters of the patients from the experimental group, it was found that the image quality firstly increased with the increase in the number of iterations but decreased with the increase of the number of iterations after a certain number of iterations. The results showed that the optimal number of iterations was 13 times. The drawing time of the experimental group and the control group was 54.27 minutes and 117.87 minutes in turn, so the difference between the two groups was significant (P < 0.05). Besides, there was a statistically marked difference in the accuracy rate of the experimental group (93.33%) and the control group (73.33%) (P < 0.05). In conclusion, the time required for coronary artery CT imaging using algebraic iterative reconstruction algorithm was greatly reduced and the diagnostic accuracy was hugely improved. Therefore, the coronary artery CT imaging based on iterative reconstruction algorithm could make more effective use of medical resources and improve the diagnostic accuracy in the diagnosis of OMI.

Association of coronary artery calcium score groups with qualitative and quantitatively assessed adverse plaque

Abstract Introduction Coronary artery calcification is a marker of cardiovascular risk, but its association with qualitatively and quantitatively assessed plaque subtypes on coronary computed tomography (CT) angiography (CCTA) is unknown. Methods In this post-hoc analysis, CT images and clinical outcomes were assessed in SCOT-HEART trial participants. Agatston coronary artery calcium score (CACS) was measured on non-contrast CT and was stratified as zero (0 Agatston units, AU), minimal (1 to 9AU), low (10 to 99AU), moderate (100 to 399AU), high (400 to 999AU) and very high (≥1000AU). Adverse plaques were investigated with qualitative (visual categorisation of positive remodelling, low-attenuation plaque, spotty calcification, napkin ring sign) and quantitative (calcified, non-calcified, low-attenuation and total plaque burden) methods. Results Images of 1769 patients were assessed (mean age 58±9 years, 56% male, median Agatston score 21 [interquartile range 0 to 230] AU). Of these 36% had a zero, 9% minimal, 20% low, 17% moderate, 10% high and 8% very high CACS. Amongst patients with a zero CACS, 14% had nonobstructive disease, 2% had obstructive disease, 2% had visually assessed adverse plaques and 13% had quantitative low-attenuation plaque (LAP) burden &amp;gt;4% (Figure 1). Non-calcified and low-attenuation plaque burden increased between patients with zero, minimal and low CACS (p&amp;lt;0.001), but there was no difference between those with medium, high and very high CACS. Over a median follow-up of 4.8 [4.1 to 5.7] years, fatal or non-fatal myocardial infarction occurred in 41 patients, 10% of whom had zero CACS. CACS ≥1000AU (Hazard ratio (HR) 4.55 [1.20 to 17.3], p=0.026) and low-attenuation plaque burden (HR 1.74 [1.19 to 2.54], p=0.004) were the only predictors of myocardial infarction, independent of obstructive disease and cardiovascular risk score. Figure 2 shows example CCTA images in a patient with zero CACS, non-calcified plaque (red), low attenuation plaque (orange) burden &amp;gt;4% and obstructive disease in the left anterior descending coronary artery. Conclusions In patients with stable chest pain, a zero CACS is associated with a good prognosis, but 1 in 6 have coronary artery disease, including the presence of adverse plaques. Funding Acknowledgement Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): British Heart Foundation, National Institute of Health/National Heart, Lung, and Blood Institute

18F-Sodium fluoride positron emission tomography, aortic disease activity and ischaemic stroke risk

Abstract Background Arterial 18F-sodium fluoride (18F-NaF) activity on positron emission tomography (PET) is a marker of active microcalcification and atherosclerosis. Coronary 18F-NaF activity (CMA) predicts coronary artery disease progression and subsequent myocardial infarction. Objective To investigate whether aortic 18F-NaF activity (AMA) predicts thoracic aortic atherosclerotic disease progression and subsequent ischaemic stroke or myocardial infarction in patients with established cardiovascular disease. Methods In a post-hoc observational cohort study, we evaluated AMA and CMA in patients with stable coronary artery disease (n=239) or aortic stenosis (n=158) who had underwent thoracic 18F-NaF PET and computed tomography (CT). We assessed the associations between AMA or CMA and progression of calcified atherosclerotic plaque in both thoracic aortic and coronary territories on follow up CT, as well as subsequent ischaemic stroke or myocardial infarction. Results In 141 and 231 patients with repeat aortic and coronary CT imaging respectively at 12.7±2.7 months, AMA correlated with log progression of thoracic aortic calcium scores (r=0.21, p=0.011), volume (r=0.29, p&amp;lt;0.01) and mass (r=0.29, P&amp;lt;0.01) as well as log coronary calcium score progression (r=0.21, p=0.03). CMA correlated with log coronary (r=0.42, p&amp;lt;0.01), but not log aortic (p&amp;gt;0.80) calcium score progression. In 397 patients, 16 had an ischaemic stroke and 25 had a myocardial infarction after 4.7±1.6 years. After adjusting for clinical risk factors, CMA and calcium scoring, AMA was associated with stroke (hazard ratio, 1.71 [95% confidence interval 1.00–2.90], p=0.048]). AMA was superior to clinical risk and calcium scores in identifying patients with stroke (c-statistic 0.76 versus 0.58 versus 0.63 respectively, p&amp;lt;0.05). Survival analysis demonstrated that AMA was associated with ischaemic stroke (p&amp;lt;0.001) but not myocardial infarction (p=0.45), whereas CMA was associated with myocardial infarction (p&amp;lt;0.001) but not stroke (p=0.39). Conclusions In patients with established cardiovascular disease, AMA is associated with progression of aortic atherosclerosis and future ischaemic stroke. Arterial 18F-NaF identifies localised areas of atherosclerotic disease activity that relate to regional atherothrombotic events. Funding Acknowledgement Type of funding sources: Other. Main funding source(s): British Heart Foundation AMA, disease progression and outcomesVariables associated with stroke

Impact of epicardial adipose tissue accumulation on left ventricular mass and hypertrophy in non-obstructive coronary artery disease

Abstract Introduction Increased left ventricular mass index (LVMi) and left ventricular hypertrophy (LVH) by echocardiography are common in obesity and important cardiovascular risk predictors associated with myocardial ischemia in non-obstructive coronary artery disease (CAD). Accumulation of epicardial adipose tissue (EAT) suggest a possible direct impact on LVMi and LVH. Purpose To explore the association between EAT volume, LVMi and LVH in patients with chest pain and non-obstructive CAD. Methods We included 129 patients with chest pain and non-obstructive CAD (&amp;lt;50% stenosis) by coronary computed tomography (CT) angiography. EAT volume was quantified using a semiautomatic analysis software on non-contrast cardiac CT images. Patients were grouped according to EAT volume, where high EAT volume was adjudicated when EAT volume was in the highest tertile (≥125 ml). Left ventricular mass was assessed by echocardiography, calculated by the Devereux formula and indexed for height in the allometric power of 2.7 (LVMi). LVH was defined as LVMi &amp;gt;46.7 g/m2.7 in women and &amp;gt;49.2 g/m2.7 in men. Coronary artery plaque burden was assessed as calcium score and segment involvement score on coronary CT angiography. Results High EAT volume was more common in men with higher BMI, waist circumference, serum triglycerides and higher prevalence of hypertension and obesity (all p&amp;lt;0.05). Age, coronary calcium score and coronary artery segment involvement score did not differ between groups. Patients with high EAT volume had higher LVMi compared to those with low EAT volume (42.5 g/m2.7 vs. 36.1 g/m2.7, p=0.003), while there was no difference in EAT volume among patients with or without LVH. In univariable logistic regression analysis, high EAT volume was associated with higher LVMi (OR 1.05 [95% CI 1.01–1.10] per g/m2.7, p=0.015). After adjusting for hypertension and obesity in a multivariable model, higher LVMi remained significantly associated with high EAT volume (Model 1, Table 1), but the association was attenuated after adjusting for sex (Model 2, Table 1). Conclusion High EAT volume was associated with increased LVMi in patients with non-obstructive CAD, independent of hypertension and obesity, while there was no association with LVH. This suggest that direct infiltration of adipose tissue in the myocardium may contribute to the development of increased LVMi. Funding Acknowledgement Type of funding sources: Public Institution(s). Main funding source(s): Western Norwegian Regional Health Authorities Table 1

Deep Recursive Bayesian Tracking for Fully Automatic Centerline Extraction of Coronary Arteries in CT Images.

Extraction of coronary arteries in coronary computed tomography (CT) angiography is a prerequisite for the quantification of coronary lesions. In this study, we propose a tracking method combining a deep convolutional neural network (DNN) and particle filtering method to identify the trajectories from the coronary ostium to each distal end from 3D CT images. The particle filter, as a non-linear approximator, is an appropriate tracking framework for such thin and elongated structures; however, the robust ‘vesselness’ measurement is essential for extracting coronary centerlines. Importantly, we employed the DNN to robustly measure the vesselness using patch images, and we integrated softmax values to the likelihood function in our particle filtering framework. Tangent patches represent cross-sections of coronary arteries of circular shapes. Thus, 2D tangent patches are assumed to include enough features of coronary arteries, and the use of 2D patches significantly reduces computational complexity. Because coronary vasculature has multiple bifurcations, we also modeled a method to detect branching sites by clustering the particle locations. The proposed method is compared with three commercial workstations and two conventional methods from the academic literature.

Relationship between epicardial adipose tissue volume and coronary artery spasm

BackgroundEpicardial adipose tissue (EAT) is considered to play a critical role in vascular endothelial function. Coronary artery spasm has been postulated to be a causal factor in vascular endothelial abnormalities and atherosclerosis. This study aimed to investigate the relationship between coronary artery spasm and EAT volume, total abdominal adipose tissue (AAT) area, and abdominal visceral adipose tissue (AVAT) area. MethodAmong patients undergoing coronary computed tomography (CT) to evaluate coronary artery disease, we identified 110 patients who did not have significant coronary artery stenosis and underwent a coronary spasm provocation test with cardiac catheterization. They were divided into two groups according to the results of the spasm provocation test: spasm-positive and spasm-negative. EAT volume, total AAT area, and AVAT area were evaluated using CT images. ResultsSeventy-seven patients were included in the spasm-positive group and 33 patients in the spasm-negative group. There were no significant differences in baseline clinical characteristics between the two groups, except for the prevalence of current smoking (48% vs. 27%, p = 0.04). EAT volume was significantly higher in the spasm-positive group (108 ± 38 mL vs. 87 ± 34 mL, p = 0.007), while no significant difference was seen in total AAT area (280 ± 113 cm2 vs. 254 ± 128 cm2, p = 0.32) or AVAT area (112 ± 54 cm2 vs. 98 ± 55 cm2, p = 0.27). Multivariate logistic analysis indicated that EAT volume (per 10 cm3) (odds ratio, 1.198; 95% confidence interval, 1.035–1.388; p = 0.016) was a significant predictor of coronary artery spasm. ConclusionOur results suggest that EAT has a strong association with coronary artery spasm, while AAT may not.

The Association Between Marital Status, Coronary Computed Tomography Imaging Biomarkers, and Mortality in a Lung Cancer Screening Population.

The purpose of this study was to elucidate the impact of being unmarried on coronary computed tomography (CT) imaging biomarkers and mortality in a lung cancer screening population. In this retrospective case-control study, 5707 subjects (3777 married; mean age: 61.9±5.1 y and 1930 unmarried; mean age: 61.9±5.3 y) underwent low-dose CT as part of the National Lung Screening Trial (NLST). The median follow-up time was 6.5 (Q1-Q3: 5.6 to 6.9) years. Being unmarried was defined as never married, widowed, separated, or divorced. Being married was defined as married or living as married. Our primary endpoint was cardiovascular disease (CVD)-related death; our secondary endpoint was all-cause mortality. Coronary CT imaging biomarkers (calcium score, density, and volume) on low-dose chest CT scan were calculated using dedicated automatic software. Weighted Cox proportional-hazards regression was performed to examine the association between marital status and death. Kaplan-Meier curves were generated to visualize subject survival. Being unmarried was significantly associated with an increased risk for CVD-related death (hazard ratio [HR]: 1.58; 95% confidence interval [CI]: 1.31-1.91) and all-cause mortality (HR: 1.39; 95% CI: 1.26-1.53), which remained significant even after adjusting for traditional cardiovascular risk factors (HR CVD death: 1.75; 1.44-2.12 and HR all-cause mortality: 1.58; 95% CI: 1.43-1.74) and coronary calcium score (HR CVD death: 1.58; 95% CI: 1.31-1.91 and HR all-cause mortality: 1.40; 95% CI: 1.27-1.54). Being unmarried is associated with an increased CVD-related death and all-cause mortality mainly due to cardiovascular etiology. On the basis of this, marital status might be taken into consideration when assessing individuals' health status.

Impact of abdominal fat distribution, visceral fat, and subcutaneous fat on coronary plaque scores assessed by 320-row computed tomography coronary angiography

Background and aimsObesity is a risk factor for coronary artery disease (CAD), but the association between fat distribution, i.e., visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT), and coronary artery plaque morphology remains unclear. This study explored the association between abdominal fat distribution and coronary artery plaques. MethodsWe retrospectively evaluated 4327 consecutive patients without CAD history, undergoing coronary computed tomography (CT) angiography. Plaques were assessed using segment stenosis score (SSS) and segment involvement score (SIS). We evaluated abdominal VAT and SAT areas using CT images. Patients were categorized into four groups: low VAT (<median)/low SAT (<median); low VAT/high SAT (≥median); high VAT (≥median)/low SAT; and high VAT/high SAT. ResultsMean age was 65 years (men, 66.4%). VAT area correlated with SSS (β-coefficient = 0.11, p < 0.001) and SIS (β-coefficient = 0.006, p < 0.001), whereas SAT area was inversely correlated with SSS (β-coefficient = −0.007,p < 0.001) and SIS (β-coefficient = −0.004, p < 0.001). The low VAT/high SAT group had the lowest risk of higher SSS (≥5) and SIS (≥5) (odds ratio [OR] using low VAT/low SAT group as the reference category, 0.76, 95% confidence interval [CI], 0.61–0.95, p < 0.05; OR, 0.68, 95% CI, 0.53–0.88, p < 0.01, respectively) in multivariate analysis adjusted for age, sex, and traditional CAD risk factors. In the obese population (body mass index ≥25, n = 1694), the low VAT/high SAT group had the lowest risk of higher coronary plaque scores. ConclusionsHigher SAT and lower VAT were inversely correlated with the extent and severity of coronary artery plaques. Fat distribution may be useful for evaluating risk and prognosis of CAD.

P1788A novel software for on-site estimation of fractional flow reserve using coronary computed tomography images

P1788A novel software for on-site estimation of fractional flow reserve using coronary computed tomography images

Surgical unroofing of hemodynamically significant myocardial bridges in a pediatric population

BackgroundAlthough myocardial bridges (MBs) are traditionally regarded as incidental findings, it has been reported that adult patients with symptomatic MBs refractory to medical therapy benefit from unroofing. However, there is limited literature in the pediatric population. The aim of our study was to evaluate the indications and outcomes for unroofing in pediatric patients. MethodsWe retrospectively reviewed all pediatric patients with MB in our institution who underwent surgical relief. Clinical characteristics, relevant diagnostic data, intraoperative findings, and postoperative outcomes were evaluated. ResultsBetween 2012 and 2016, 14 pediatric patients underwent surgical unroofing of left anterior descending artery MBs. Thirteen patients had anginal symptoms refractory to medical therapy, and 1 patient was asymptomatic until experiencing aborted sudden cardiac arrest during exercise. Thirteen patients underwent exercise stress echocardiography, all of which showed mid-septal dys-synergy. Coronary computed tomography imaging confirmed the presence of MBs in all patients. Intravascular ultrasound imaging confirmed the length of MBs: 28.2 ± 16.3 mm, halo thickness: 0.59 ± 0.24 mm, and compression of left anterior descending artery at resting heart rate: 33.0 ± 11.6%. Invasive hemodynamic assessment with dobutamine confirmed the physiologic significance of the MBs with diastolic fractional flow reserve: 0.59 ± 0.13. Unroofing was performed with the patient under cardiopulmonary bypass (CPB) in the initial 9 cases and without CPB in the subsequent 5 cases. All patients were discharged without complications. The 13 symptomatic patients reported resolution of symptoms on follow-up, and improvement in symptoms and quality of life was documented using the Seattle Angina Questionnaire version 7. ConclusionsUnroofing of MBs can be safely performed in pediatric patients, with or without use of CPB. In symptomatic patients, unroofing can provide relief of symptoms refractory to medical therapy.

An Efficient Coronary Disease Diagnosis System Using Dual-Phase Multi-Objective Optimization and Embedded Feature Selection

Developments in healthcare technologies have significantly enhanced spatial resolution and improved contrast resolution, permitting analysis of additional subtle structures than formerly attainable. An approach for Automatic recognition and quantification of calcifications from arteries in computed tomography (CT) scans is developed which is a key necessity in planning the treatment of individuals with suspected coronary artery disease. First, a Dual-Phase Multi-_objective Optimization approach using an Active Contour Model-based region-growing technique is developed. Second, an embedded feature selection method is developed with an expert classifier to detect calcified objects in the segmented artery with great accuracy. Finally, the Agatston scoring method is utilized to quantify the level of coronary artery calcium plaque. Coronary CT images from the AS+CT scanner with a slice thickness of 3 mm were obtained from clinical practice. Experimental results demonstrate that our proposed method improves the accuracy of lesion detection for better treatment planning.

Estimation of the flow resistances exerted in coronary arteries using a vessel length-based method.

Flow resistances exerted in the coronary arteries are the key parameters for the image-based computer simulation of coronary hemodynamics. The resistances depend on the anatomical characteristics of the coronary system. A simple and reliable estimation of the resistances is a compulsory procedure to compute the fractional flow reserve (FFR) of stenosed coronary arteries, an important clinical index of coronary artery disease. The cardiac muscle volume reconstructed from computed tomography (CT) images has been used to assess the resistance of the feeding coronary artery (muscle volume-based method). In this study, we estimate the flow resistances exerted in coronary arteries by using a novel method. Based on a physiological observation that longer coronary arteries have more daughter branches feeding a larger mass of cardiac muscle, the method measures the vessel lengths from coronary angiogram or CT images (vessel length-based method) and predicts the coronary flow resistances. The underlying equations are derived from the physiological relation among flow rate, resistance, and vessel length. To validate the present estimation method, we calculate the coronary flow division over coronary major arteries for 50 patients using the vessel length-based method as well as the muscle volume-based one. These results are compared with the direct measurements in a clinical study. Further proving the usefulness of the present method, we compute the coronary FFR from the images of optical coherence tomography.

Italian Chapter of the International Society of Cardiovascular Ultrasound expert consensus document on coronary computed tomography angiography: overview and new insights.

Coronary computed tomography angiography is a noninvasive heart imaging test currently undergoing rapid development and advancement. The high resolution of the three-dimensional pictures of the moving heart and great vessels is performed during a coronary computed tomography to identify coronary artery disease and classify patient risk for atherosclerotic cardiovascular disease. The technique provides useful information about the coronary tree and atherosclerotic plaques beyond simple luminal narrowing and plaque type defined by calcium content. This application will improve image-guided prevention, medical therapy, and coronary interventions. The ability to interpret coronary computed tomography images is of utmost importance as we develop personalized medical care to enable therapeutic interventions stratified on the bases of plaque characteristics. This overview provides available data and expert's recommendations in the utilization of coronary computed tomography findings. We focus on the use of coronary computed tomography to detect coronary artery disease and stratify patients at risk, illustrating the implications of this test on patient management. We describe its diagnostic power in identifying patients at higher risk to develop acute coronary syndrome and its prognostic significance. Finally, we highlight the features of the vulnerable plaques imaged by coronary computed tomography angiography.

Prognostic Value of Coronary Computed Tomography Imaging in Patients at High Risk Without Symptoms of Coronary Artery Disease

At present, traditional risk factors are used to guide cardiovascular management of asymptomatic subjects. Intensified surveillance may be warranted in those identified as high risk of developing cardiovascular disease (CVD). This study aims to determine the prognostic value of coronary computed tomography (CT) angiography (CCTA) next to the coronary artery calcium score (CACS) in patients at high CVD risk without symptoms suspect for coronary artery disease (CAD). A total of 665 patients at high risk (mean age 56 ± 9years, 417 men), having at least one important CVD risk factor (diabetes mellitus, familial hypercholesterolemia, peripheral artery disease, or severe hypertension) or a calculated European systematic coronary risk evaluation of >10% were included from outpatient clinics at 2 academic centers. Follow-up was performed for the occurrence of adverse events including all-cause mortality, nonfatal myocardial infarction, unstable angina, or coronary revascularization. During a median follow-up of 3.0 (interquartile range 1.3 to 4.1) years, adverse events occurred in 40 subjects (6.0%). By multivariate analysis, adjusted for age, gender, and CACS, obstructive CAD on CCTA (≥50% luminal stenosis) was a significant predictor of adverse events (hazard ratio 5.9 [CI 1.3 to 26.1]). Addition of CCTA to age, gender, plus CACS, increased the C statistic from 0.81 to 0.84 and resulted in a total net reclassification index of 0.19 (p <0.01). In conclusion, CCTA has incremental prognostic value and risk reclassification benefit beyond CACS in patients without CAD symptoms but with high risk of developing CVD.

Imaging in Minimally Invasive Mitral Valve Repair.

Minimally invasive mitral valve (MV) repair and replacement techniques have evolved as increasingly used alternatives to open heart surgery especially in patients unsuitable for surgery or at high perioperative risk. The vast majority of these techniques are still under development, and only a limited number of devices are approved for clinical use; however, they do show promising results in terms of minimizing complications and improving clinical outcome. The complex anatomy of the MV and the annulus complicates not only the development of devices for minimally invasive MV repair or replacement but also complicates preprocedural planning, which is mandatory for minimization of postprocedural complications. Although echocardiography still plays a crucial clinical role, cross-sectional imaging modalities such as coronary computed tomography (CCT) and cardiac magnetic resonance imaging (CMR) are increasingly gaining importance for preprocedural planning. Specifically, CCT seems to be more practicable for preinterventional planning and device sizing, whereas CMR has been shown useful in detecting increased risk for adverse clinical outcomes through delayed gadolinium enhancement and the monitoring of cardiac morphology and function in the framework of follow-up examinations. This article describes recent techniques currently available or under development for minimally invasive repair or replacement of the MV and reviews the current state of CCT and CMR imaging for preinterventional and postinterventional diagnostic workup.