Arrhythmic Mitral Valve Prolapse Phenotype: An Unsupervised Machine Learning Analysis Using a Multicenter Cardiac MRI Registry.

Purpose To use unsupervised machine learning to identify phenotypic clusters with increased risk of arrhythmic mitral valve prolapse (MVP). Materials and Methods This retrospective study included patients with MVP without hemodynamically significant mitral regurgitation or left ventricular (LV) dysfunction undergoing late gadolinium enhancement (LGE) cardiac MRI between October 2007 and June 2020 in 15 European tertiary centers. The study end point was a composite of sustained ventricular tachycardia, (aborted) sudden cardiac death, or unexplained syncope. Unsupervised data-driven hierarchical k-mean algorithm was utilized to identify phenotypic clusters. The association between clusters and the study end point was assessed by Cox proportional hazards model. Results A total of 474 patients (mean age, 47 years ± 16 [SD]; 244 female, 230 male) with two phenotypic clusters were identified. Patients in cluster 2 (199 of 474, 42%) had more severe mitral valve degeneration (ie, bileaflet MVP and leaflet displacement), left and right heart chamber remodeling, and myocardial fibrosis as assessed with LGE cardiac MRI than those in cluster 1. Demographic and clinical features (ie, symptoms, arrhythmias at Holter monitoring) had negligible contribution in differentiating the two clusters. Compared with cluster 1, the risk of developing the study end point over a median follow-up of 39 months was significantly higher in cluster 2 patients (hazard ratio: 3.79 [95% CI: 1.19, 12.12], P = .02) after adjustment for LGE extent. Conclusion Among patients with MVP without significant mitral regurgitation or LV dysfunction, unsupervised machine learning enabled the identification of two phenotypic clusters with distinct arrhythmic outcomes based primarily on cardiac MRI features. These results encourage the use of in-depth imaging-based phenotyping for implementing arrhythmic risk prediction in MVP. Keywords: MR Imaging, Cardiac, Cardiac MRI, Mitral Valve Prolapse, Cluster Analysis, Ventricular Arrhythmia, Sudden Cardiac Death, Unsupervised Machine Learning Supplemental material is available for this article. © RSNA, 2024.

The Role of Multimodality Imaging (CT & MR) as a Guide to the Management of Chronic Coronary Syndromes.

Chronic coronary syndrome (CCS) is one of the leading cardiovascular causes of morbidity, mortality, and use of medical resources. After the introduction by international guidelines of the same level of recommendation to non-invasive imaging techniques in CCS evaluation, a large debate arose about the dilemma of choosing anatomical (with coronary computed tomography angiography (CCTA)) or functional imaging (with stress echocardiography (SE), cardiovascular magnetic resonance (CMR), or nuclear imaging techniques) as a first diagnostic evaluation. The determinant role of the atherosclerotic burden in defining cardiovascular risk and prognosis more than myocardial inducible ischemia has progressively increased the use of a first anatomical evaluation with CCTA in a wide range of pre-test probability in CCS patients. Functional testing holds importance, both because the role of revascularization in symptomatic patients with proven ischemia is well defined and because functional imaging, particularly with stress cardiac magnetic resonance (s-CMR), gives further prognostic information regarding LV function, detection of myocardial viability, and tissue characterization. Emerging techniques such as stress computed tomography perfusion (s-CTP) and fractional flow reserve derived from CT (FFRCT), combining anatomical and functional evaluation, appear capable of addressing the need for a single non-invasive examination, especially in patients with high risk or previous revascularization. Furthermore, CCTA in peri-procedural planning is promising to acquire greater importance in the non-invasive planning and guiding of complex coronary revascularization procedures, both by defining the correct strategy of interventional procedure and by improving patient selection. This review explores the different roles of non-invasive imaging techniques in managing CCS patients, also providing insights into preoperative planning for percutaneous or surgical myocardial revascularization.

Pre-procedural imaging with cardiac computed tomography for endo-epicardial ventricular tachycardia ablation.

BACKGROUND: Studies evaluating the systematic use of cardiac computer tomography (CCT) for the pre-procedural assessment of myocardial fibrosis are limited and their implementation in the electrophysiology workflow has not been extensively described. OBJECTIVE: To explore the degree of concordance between cardiac fibrosis evaluated by CCT compared to electroanatomical mapping (EAM) in patients undergoing endo-epicardial ventricular tachycardia (VT) ablation. METHODS: From November-2017 to December-2021, patients undergoing endo-epicardial VT catheter ablation (CA) with CCT as the only source of pre-procedural scar assessment were prospectively enrolled. After image integration, myocardial fibrosis detected with CCT was compared with low voltage areas identified by endo-epicardial EAM. Post-procedural VT recurrences of this approach were evaluated after at least one-year follow-up. RESULTS: 35 patients (mean age 60.7±13.2 years, 94.2% males) were enrolled. The most common underlying arrhythmic substrate was dilated cardiomyopathy (48.6%). CCT was employed for contraindications to cardiac magnetic resonance, as unstable VTs (31.4%) or non-conditional ICDs (28.8%), but also for patients' and operators' preferences (14.3%-25.7%). Myocardial fibrosis was correctly identified by CCT and EAM, with strong agreement between these two techniques, both overall (Cohen's Kappa for agreement=0.933) and in per-segment analysis (K ranging from 0.796 to 1.0). Ischemic patients showed the best correlation (K=1.000) while myocarditis showed the worst (K=0.750). After a median follow-up of 14 [12-24] months, 1-year freedom from recurrences was achieved in 74.3% patients; overall freedom from recurrences was 60.0%. CONCLUSIONS: A CCT-based pre-procedural assessment pre-VT ablation is feasible, showing high diagnostic concordance with EAM in detecting myocardial fibrosis.

Quantitative coronary computed tomography assessment for differentiating between total occlusions and severe stenoses.

BACKGROUNDS: The impact of quantitative assessment to differentiate total occlusions (TOs) from severe stenoses on coronary computed tomography angiography (CCTA) remains unknown. OBJECTIVE: This study investigated whether quantitative characteristics assessed on CCTA could help differentiate a TO from a severe stenosis on invasive coronary angiography (ICA). METHODS: This study is a sub-analysis of the FASTTRACK CABG (NCT04142021) in which both CCTA and ICA were routinely performed. Quantitative analysis was performed with semi-automated CCTA plaque-analysis software. Blinded analysts compared TOs on CCTA, defined as a complete lack of contrast opacification within the coronary occlusion, with corresponding ICA. RESULTS: Eighty-four TOs were seen on CCTA in 59 of the 114 patients enrolled in the trial. The concordance in diagnosing a TO between ICA and CCTA was 56.0% (n â€‹= â€‹47). Compared to severe stenoses, TOs had a significantly longer lesion length (25.1 â€‹± â€‹23.0 â€‹mm vs 9.4 â€‹± â€‹11.2 â€‹mm, P â€‹< â€‹0.001). The best cut-off value to differentiate a TO from severe stenosis was a lesion length of 5.5 â€‹mm (area under the curve 0.77, 95% CI: 0.66-0.87), with a 91.1% sensitivity and 61.1% specificity. Dense calcium percentage atheroma volume (PAV) was significantly higher in TOs compared to severe stenoses (18.7 â€‹± â€‹19.6% vs. 6.6 â€‹± â€‹13.0%, P â€‹< â€‹0.001), whilst the opposite was seen for fibro-fatty PAV (31.3 â€‹± â€‹14.2% vs. 19.5 â€‹± â€‹10.5%, P â€‹< â€‹0.001). On a multivariable logistic regression analysis, lesion length (>5.5 â€‹mm) was the only parameter associated with differentiating a TO from a severe stenosis. CONCLUSION: In quantitative CCTA analysis, a lesion length >5.5 â€‹mm was the only independent predictor differentiating a TO from a severe stenosis. NCT REGISTRATION NUMBER: NCT04142021.

Monitoring of environmental persistent organic pollutants in hair samples of cats and dogs.

This study investigated 32 persistent organic pollutants, including 9 organochlorine pesticides, 15 polychlorinated biphenyls, 6 polycyclic aromatic hydrocarbons, and 2 organophosphate pesticides in the hair samples of domestic cats and dogs living in an urban area in Samsun, Turkiye. Hair samples were collected from 35 cats and 38 dogs, grouped by sex and age (<3 or >3 years old). Samples were extracted using a liquid-liquid extraction method and analyzed by Gas Chromatography-Mass Spectrometry (GC-MS). The results revealed the presence of organochlorine pesticides (n = 58, 468.65 ± 92.30 ng/g), polycyclic aromatic hydrocarbons (n = 57, 15.65 ± 3.91 ng/g), polychlorinated biphenyls (n = 55, 54.11 ± 9.47 ng/g), and organophosphate pesticides (n = 25, 568.43 ± 113.17 ng/g) in the samples. PCBs 81, 118, 128, 208, and 2,4-DDE were not detected in any samples. Only one sample did not contain any of the searched compounds. Fluorene was the most frequently detected pollutant (n = 53, 72.6 %), followed by ß-hexachlorocyclohexane (n = 34, 46.6 %). The highest maximum concentration was observed for hexachlorobenzene (2748.03 ng/g), followed by aldrin (2313.45 ng/g) and fenitrothion (2081.13 ng/g). Pollutant concentrations did not differ between cats and dogs, sexes, and ages (p > 0.05). This study highlights the significant threat that urban areas pose to pets, and therefore, POPs should be monitored periodically in hair and other samples. To the best of our knowledge, this is the first report to investigate POP levels in hair samples from cats and dogs in Turkiye.

The Role of Magnetic Resonance Imaging in Cardiomyopathies in the Light of New Guidelines: A Focus on Tissue Mapping.

Cardiomyopathies (CMPs) are a group of myocardial disorders that are characterized by structural and functional abnormalities of the heart muscle. These abnormalities occur in the absence of coronary artery disease (CAD), hypertension, valvular disease, and congenital heart disease. CMPs are an increasingly important topic in the field of cardiovascular diseases due to the complexity of their diagnosis and management. In 2023, the ESC guidelines on cardiomyopathies were first published, marking significant progress in the field. The growth of techniques such as cardiac magnetic resonance imaging (CMR) and genetics has been fueled by the development of multimodal imaging approaches. For the diagnosis of CMPs, a multimodal imaging approach, including CMR, is recommended. CMR has become the standard for non-invasive analysis of cardiac morphology and myocardial function. This document provides an overview of the role of CMR in CMPs, with a focus on tissue mapping. CMR enables the characterization of myocardial tissues and the assessment of cardiac functions. CMR sequences and techniques, such as late gadolinium enhancement (LGE) and parametric mapping, provide detailed information on tissue composition, fibrosis, edema, and myocardial perfusion. These techniques offer valuable insights for early diagnosis, prognostic evaluation, and therapeutic guidance of CMPs. The use of quantitative CMR markers enables personalized treatment plans, improving overall patient outcomes. This review aims to serve as a guide for the use of these new tools in clinical practice.

Clinical and cardiac CT characteristics of congenital coronary abnormalities occasionally detected in a middle-aged population: A long-term follow-up study.

INTRODUCTION: Congenital coronary artery anomalies (CCAA) represent one of the most challenging conditions as their clinical presentation may range from sudden cardiac death to a complete subclinical form. The aim of the present study was to evaluate the diagnostic and prognostic role of cardiac CT (CCT) evaluation in patients with CCAA, focusing on anomalies of origin. MATERIAL AND METHODS: The present is a retrospective analysis of a prospective clinical registry including a consecutive cohort of patients who underwent clinically indicated CCT from January 2007 to October 2015 for suspected but unknown coronary artery disease (CAD) and were diagnosed for having a congenital coronary abnormality compared to a control group matched for age, sex and segment stenosis score (SSS). Dedicated analysis of all CCT was performed for the present study and only coronary anomalies of origin were considered and included in the study. Two different composite end-points were identified for the present analysis: major cardiovascular events (MACE) and all-cause of death. RESULTS: Among the 81 patients with CCAAs enrolled the most frequent anomaly was left main artery absence, which was identified in 41 individuals (50.6%). Forty-five subjects (55.5%) have an anomalous origin of the coronary artery from a different sinus of Valsalva and 45 subjects had also an anomalous course with the retro-aortic being the most common (32%). Eleven participants (13.6%) displayed also an intramural segment, while 10 (10.3%) had a slit-like ostial morphology. At multivariate analysis CT identification of ARCA, anomalous inter-arterial course and abnormal ostial morphology were significantly associated with MACE even when adjusted for age and SSS, without any differences in all-cause mortality between the two groups (6.2% vs 2.4% p â€‹= â€‹0.2478). CONCLUSION: The result of the present study is that CCT can be successfully used to define the anatomy and features of CAA. It suggested that in middle-aged patients, the identification of high risk characteristics at CT may have a prognostic value in term of cardiovascular events occurrence at follow-up even if the rate of events strictly linked to CCAA is low.

DEep LearnIng-based QuaNtification of epicardial adipose tissue predicts MACE in patients undergoing stress CMR.

BACKGROUND AND AIMS: This study investigated the additional prognostic value of epicardial adipose tissue (EAT) volume for major adverse cardiovascular events (MACE) in patients undergoing stress cardiac magnetic resonance (CMR) imaging. METHODS: 730 consecutive patients [mean age: 63 ± 10 years; 616 men] who underwent stress CMR for known or suspected coronary artery disease were randomly divided into derivation (n = 365) and validation (n = 365) cohorts. MACE was defined as non-fatal myocardial infarction and cardiac deaths. A deep learning algorithm was developed and trained to quantify EAT volume from CMR. EAT volume was adjusted for height (EAT volume index). A composite CMR-based risk score by Cox analysis of the risk of MACE was created. RESULTS: In the derivation cohort, 32 patients (8.7 %) developed MACE during a follow-up of 2103 days. Left ventricular ejection fraction (LVEF) < 35 % (HR 4.407 [95 % CI 1.903-10.202]; p<0.001), stress perfusion defect (HR 3.550 [95 % CI 1.765-7.138]; p<0.001), late gadolinium enhancement (LGE) (HR 4.428 [95%CI 1.822-10.759]; p = 0.001) and EAT volume index (HR 1.082 [95 % CI 1.045-1.120]; p<0.001) were independent predictors of MACE. In a multivariate Cox regression analysis, adding EAT volume index to a composite risk score including LVEF, stress perfusion defect and LGE provided additional value in MACE prediction, with a net reclassification improvement of 0.683 (95%CI, 0.336-1.03; p<0.001). The combined evaluation of risk score and EAT volume index showed a higher Harrel C statistic as compared to risk score (0.85 vs. 0.76; p<0.001) and EAT volume index alone (0.85 vs.0.74; p<0.001). These findings were confirmed in the validation cohort. CONCLUSIONS: In patients with clinically indicated stress CMR, fully automated EAT volume measured by deep learning can provide additional prognostic information on top of standard clinical and imaging parameters.

Exploring the Long-Term Disability Outcomes in Trauma Patients: Study Protocol.

Objectives: Post-discharge patient-reported outcomes from trauma registries can be used to measure trauma care quality. However, studies reflecting the Asian experience are limited. Therefore, we aim to develop a digital trauma registry to prospectively capture patient-reported outcomes (PROs) at one-, three-, six-, and twelve-months post-injury in Pakistan. Methods: We will use a cohort study design to develop a digital trauma registry at two tertiary care facilities (Aga Khan University Hospital & Jinnah Postgraduate Medical Center) in Karachi, Pakistan. The registry will include all admitted adult trauma patients (≥18 years). Data collection will be digital using tablets, with mortality, level of disability, and functional status, quality of life being the outcomes. Telephonic interviews will be conducted with the patients and caregivers for follow-up data collection. Discussion: The high disability burden following accidental trauma imposes a significant burden and cost on individuals and society. Therefore, the trauma registry would fill this gap by capturing post-discharge long-term PROs. It will provide the injured patient's post-discharge situation, challenges, and future directions for incorporating long-term PROs in low-resource settings. Including long-term measures in routine follow-ups will provide insights into physical, social, and policy barriers and help advance injury care research.

Coronary bypass surgery guided by computed tomography in a low-risk population.

BACKGROUND AND AIMS: In patients with three-vessel disease and/or left main disease, selecting revascularization strategy based on coronary computed tomography angiography (CCTA) has a high level of virtual agreement with treatment decisions based on invasive coronary angiography (ICA). METHODS: In this study, coronary artery bypass grafting (CABG) procedures were planned based on CCTA without knowledge of ICA. The CABG strategy was recommended by a central core laboratory assessing the anatomy and functionality of the coronary circulation. The primary feasibility endpoint was the percentage of operations performed without access to the ICA. The primary safety endpoint was graft patency on 30-day follow-up CCTA. Secondary endpoints included topographical adequacy of grafting, major adverse cardiac and cerebrovascular (MACCE), and major bleeding events at 30 days. The study was considered positive if the lower boundary of confidence intervals (CI) for feasibility was ≥75% (NCT04142021). RESULTS: The study enrolled 114 patients with a mean (standard deviation) anatomical SYNTAX score and Society of Thoracic Surgery score of 43.6 (15.3) and 0.81 (0.63), respectively. Unblinding ICA was required in one case yielding a feasibility of 99.1% (95% CI 95.2%-100%). The concordance and agreement in revascularization planning between the ICA- and CCTA-Heart Teams was 82.9% with a moderate kappa of 0.58 (95% CI 0.50-0.66) and between the CCTA-Heart Team and actual treatment was 83.7% with a substantial kappa of 0.61 (95% CI 0.53-0.68). The 30-day follow-up CCTA in 102 patients (91.9%) showed an anastomosis patency rate of 92.6%, whilst MACCE was 7.2% and major bleeding 2.7%. CONCLUSIONS: CABG guided by CCTA is feasible and has an acceptable safety profile in a selected population of complex coronary artery disease.

Predictors of adverse cardiac events of coronary myocardial bridging diagnosed with computed tomography angiography.

AIMS: Myocardial bridging (MB) is a frequent congenital anomaly of the epicardial coronary arteries commonly considered a benign condition. However, in some cases a complex interplay between anatomical, clinical and physiology factors may lead to adverse events, including sudden cardiac death. Coronary CT angiography (CCTA) emerged as the gold standard noninvasive imaging technique for the evaluation of MB. Aim of the study was to evaluate MB prevalence and anatomical features in a large population of patients who underwent CCTA for suspected CAD and to identify potential anatomical and clinical predictors of adverse cardiac events at long-term follow-up. METHODS AND RESULTS: Two-hundred and six patients (mean age 60.3 ± 11.8 years, 128 male) with MB diagnosed at CCTA were considered. A long MB was defined as ≥25 mm of overlying myocardium, whereas a deep MB as ≥2 mm of overlying myocardium. The study endpoint was the sum of the following adverse events: cardiac death, bridge-related acute coronary syndrome, hospitalization for angina or bridge-related ventricular arrhythmias and MB surgical treatment. Of the 206 patients enrolled in the study, 9 were lost to follow-up, whereas 197 (95.6%) had complete follow-up (mean 7.01 ± 3.0 years) and formed the analytic population. Nineteen bridge-related events occurred in 18 patients (acute coronary syndrome in 7, MB surgical treatment in 2 and hospitalization for bridge-related events in 10). Typical angina at the time of diagnosis and long MB resulted as significant independent predictors of adverse outcome. CONCLUSIONS: Typical angina and MB length ≥ 25 mm were independent predictors of cardiac events.

Dengue Cases Presenting to the Emergency Department of a Tertiary Care Hospital in Late 2021: A Cross-Sectional Study in Karachi.

Objectives: Dengue Fever (DF) is an arboviral disease caused by the Dengue virus (DENV). This study aims to assess the association of dengue prevalence with patients' residential areas and hematological laboratory findings (Total platelet count, immunoglobulins, and dengue antigens) during COVID-19 pandemic. Methods: A retrospective study was conducted at the Emergency department of Jinnah Postgraduate Medical Center, Karachi from October to December 2021. All the patients irrespective of their ages presenting to the ED with either of the following complaints: fever; GIT problems; vomiting; body ache; bleeding were included in our study. Results: Our study comprised 189 patients in total in which the females (n = 172) outnumbered the males (n = 17). Out of all, 84.7% of the patients were febrile having a low-grade fever on average. Korangi district had the most dengue cases, while Keamari had the fewest. There was no significant association reported between mean platelet count, mean TLC, and mean hemoglobin levels with dengue positivity. Conclusion: There is a concerning rise in DF cases in Karachi, particularly in the Korangi district. Despite the COVID-19 pandemic, DF demands urgent attention.

A fully automated deep learning approach for coronary artery segmentation and comprehensive characterization.

Coronary computed tomography angiography (CCTA) allows detailed assessment of early markers associated with coronary artery disease (CAD), such as coronary artery calcium (CAC) and tortuosity (CorT). However, their analysis can be time-demanding and biased. We present a fully automated pipeline that performs (i) coronary artery segmentation and (ii) CAC and CorT objective analysis. Our method exploits supervised learning for the segmentation of the lumen, and then, CAC and CorT are automatically quantified. 281 manually annotated CCTA images were used to train a two-stage U-Net-based architecture. The first stage employed a 2.5D U-Net trained on axial, coronal, and sagittal slices for preliminary segmentation, while the second stage utilized a multichannel 3D U-Net for refinement. Then, a geometric post-processing was implemented: vessel centerlines were extracted, and tortuosity score was quantified as the count of branches with three or more bends with change in direction forming an angle >45°. CAC scoring relied on image attenuation. CAC was detected by setting a patient specific threshold, then a region growing algorithm was applied for refinement. The application of the complete pipeline required <5 min per patient. The model trained for coronary segmentation yielded a Dice score of 0.896 and a mean surface distance of 1.027 mm compared to the reference ground truth. Tracts that presented stenosis were correctly segmented. The vessel tortuosity significantly increased locally, moving from proximal, to distal regions (p < 0.001). Calcium volume score exhibited an opposite trend (p < 0.001), with larger plaques in the proximal regions. Volume score was lower in patients with a higher tortuosity score (p < 0.001). Our results suggest a linked negative correlation between tortuosity and calcific plaque formation. We implemented a fast and objective tool, suitable for population studies, that can help clinician in the quantification of CAC and various coronary morphological parameters, which is helpful for CAD risk assessment.

Prevalence and prognosis of structural heart disease among athletes with negative T waves and normal transthoracic echocardiography.

INTRODUCTION: The aim of the present study was to evaluate the prevalence and prognosis of structural heart disease (SHD) among competitive athletes with negative T waves without pathological findings at transthoracic echocardiogram. METHODS: From a prospective register of 450 athletes consecutively evaluated during a second-level cardiological examination, we retrospectively identified all subjects with the following inclusion criteria: (1) not previously known cardiovascular disease; (2) negative T waves in leads other than V1-V2; (3) normal transthoracic echocardiogram. Patients underwent cardiac MRI and CT. The primary endpoint was the diagnosis of definite SHD after multimodality imaging evaluation. A follow-up was collected for a combined end-point of sudden death, resuscitated sudden cardiac death and hospitalization for any cardiovascular causes. RESULTS: A total of 55 competitive athletes were finally enrolled (50 males, 90%) with a mean age of 27.5 ± 14.1 years. Among the population enrolled 16 (29.1%) athletes had a final diagnosis of SHD. At multivariate analysis, only deep negative T waves remained statistically significant [OR (95% CI) 7.81 (1.24-49.08), p = 0.0285]. Contemporary identification of deep negative T waves and complex arrhythmias in the same patients appeared to have an incremental diagnostic value. No events were collected at 49.3 ± 12.3 months of follow-up. CONCLUSIONS: In a cohort of athletes with negative T waves at ECG, cardiac MRI (and selected use of cardiac CT) enabled the identification of 16 (29.1%) subjects with SHD despite normal transthoracic echocardiography. Deep negative T waves and complex ventricular arrhythmias were the only clinical characteristic associated with SHD diagnosis.

Murray law-based quantitative flow ratio to assess left main bifurcation stenosis: selecting the angiographic projection matters.

Murray law-based quantitative flow ratio (µQFR) assesses fractional flow reserve (FFR) in bifurcation lesions using a single angiographic view, enhancing the feasibility of analysis; however, accuracy may be compromised in suboptimal angiographic projections. FFRCT is a well-validated non-invasive method measuring FFR from coronary computed tomographic angiography (CCTA). We evaluated the feasibility of µQFR in left main (LM) bifurcations, the impact of the optimal/suboptimal fluoroscopic view with respect to CCTA, and its diagnostic concordance with FFRCT. In 300 patients with three-vessel disease, the values of FFRCT and µQFR were compared at distal LM, proximal left anterior descending artery (pLAD) and circumflex artery (pLCX). The optimal viewing angle of LM bifurcation was defined on CCTA by 3-dimensional coordinates and converted into a 2-dimensional fluoroscopic view. The best fluoroscopic projection was considered the closest angulation to the optimal viewing angle on CCTA. µQFR was successfully computed in 805 projections. In the best projections, µQFR sensitivity was 88.2% (95% CI 76.1-95.6) and 84.8% (71.1-93.7), and specificity was 96.8% (93.8-98.6) and 97.2% (94.4-98.9), in pLAD and pLCX, respectively, with regard to FFRCT. The AUC of µQFR for predicting FFRCT ≤ 0.80 tended to be improved using the best versus suboptimal projections (0.94 vs. 0.89 [p = 0.048] in pLAD; 0.94 vs. 0.88 [p = 0.075] in pLCX). Computation of µQFR in LM bifurcations using a single angiographic view showed high feasibility from post-hoc analysis of coronary angiograms obtained for clinical purposes. The fluoroscopic viewing angle influences the diagnostic performance of physiological assessment using a single angiographic view.

Assessment and management of heart failure in patients with chronic kidney disease.

Heart failure (HF) and chronic kidney disease (CKD) are two pathological conditions with a high prevalence in the general population. When they coexist in the same patient, a strict interplay between them is observed, such that patients affected require a clinical multidisciplinary and personalized management. The diagnosis of HF and CKD relies on signs and symptoms of the patient but several additional tools, such as blood-based biomarkers and imaging techniques, are needed to clarify and discriminate the main characteristics of these diseases. Improved survival due to new recommended drugs in HF has increasingly challenged physicians to manage patients with multiple diseases, especially in case of CKD. However, the safe administration of these drugs in patients with HF and CKD is often challenging. Knowing up to which values ​​of creatinine or renal clearance each drug can be administered is fundamental. With this review we sought to give an insight on this sizable and complex topic, in order to get clearer ideas and a more precise reference about the diagnostic assessment and therapeutic management of HF and CKD.

Rationale and design of the CONFIRM2 (Quantitative COroNary CT Angiography Evaluation For Evaluation of Clinical Outcomes: An InteRnational, Multicenter Registry) study.

BACKGROUND: In the last 15 years, large registries and several randomized clinical trials have demonstrated the diagnostic and prognostic value of coronary computed tomography angiography (CCTA). Advances in CT scanner technology and developments of analytic tools now enable accurate quantification of coronary artery disease (CAD), including total coronary plaque volume and low attenuation plaque volume. The primary aim of CONFIRM2, (Quantitative COroNary CT Angiography Evaluation For Evaluation of Clinical Outcomes: An InteRnational, Multicenter Registry) is to perform comprehensive quantification of CCTA findings, including coronary, non-coronary cardiac, non-cardiac vascular, non-cardiac findings, and relate them to clinical variables and cardiovascular clinical outcomes. DESIGN: CONFIRM2 is a multicenter, international observational cohort study designed to evaluate multidimensional associations between quantitative phenotype of cardiovascular disease and future adverse clinical outcomes in subjects undergoing clinically indicated CCTA. The targeted population is heterogenous and includes patients undergoing CCTA for atherosclerotic evaluation, valvular heart disease, congenital heart disease or pre-procedural evaluation. Automated software will be utilized for quantification of coronary plaque, stenosis, vascular morphology and cardiac structures for rapid and reproducible tissue characterization. Up to 30,000 patients will be included from up to 50 international multi-continental clinical CCTA sites and followed for 3-4 years. SUMMARY: CONFIRM2 is one of the largest CCTA studies to establish the clinical value of a multiparametric approach to quantify the phenotype of cardiovascular disease by CCTA using automated imaging solutions.

Progression of non-obstructive coronary plaque: a practical CCTA-based risk score from the PARADIGM registry.

OBJECTIVES: No clear recommendations are endorsed by the different scientific societies on the clinical use of repeat coronary computed tomography angiography (CCTA) in patients with non-obstructive coronary artery disease (CAD). This study aimed to develop and validate a practical CCTA risk score to predict medium-term disease progression in patients at a low-to-intermediate probability of CAD. METHODS: Patients were part of the Progression of AtheRosclerotic PlAque Determined by Computed Tomographic Angiography Imaging (PARADIGM) registry. Specifically, 370 (derivation cohort) and 219 (validation cohort) patients with two repeat, clinically indicated CCTA scans, non-obstructive CAD, and absence of high-risk plaque (≥ 2 high-risk features) at baseline CCTA were included. Disease progression was defined as the new occurrence of ≥ 50% stenosis and/or high-risk plaque at follow-up CCTA. RESULTS: In the derivation cohort, 104 (28%) patients experienced disease progression. The median time interval between the two CCTAs was 3.3 years (2.7-4.8). Odds ratios for disease progression derived from multivariable logistic regression were as follows: 4.59 (95% confidence interval: 1.69-12.48) for the number of plaques with spotty calcification, 3.73 (1.46-9.52) for the number of plaques with low attenuation component, 2.71 (1.62-4.50) for 25-49% stenosis severity, 1.47 (1.17-1.84) for the number of bifurcation plaques, and 1.21 (1.02-1.42) for the time between the two CCTAs. The C-statistics of the model were 0.732 (0.676-0.788) and 0.668 (0.583-0.752) in the derivation and validation cohorts, respectively. CONCLUSIONS: The new CCTA-based risk score is a simple and practical tool that can predict mid-term CAD progression in patients with known non-obstructive CAD. CLINICAL RELEVANCE STATEMENT: The clinical implementation of this new CCTA-based risk score can help promote the management of patients with non-obstructive coronary disease in terms of timing of imaging follow-up and therapeutic strategies. KEY POINTS: • No recommendations are available on the use of repeat CCTA in patients with non-obstructive CAD. • This new CCTA score predicts mid-term CAD progression in patients with non-obstructive stenosis at baseline. • This new CCTA score can help guide the clinical management of patients with non-obstructive CAD.

A comparison of intracardiac echocardiography and transesophageal echocardiography for guiding device closure of ostium secundum atrial septal defect: A 15-year experience.

BACKGROUND AND AIM: Our aim was to evaluate the fluoroscopy time (FT), procedure time (PT) safety and efficacy when using intracardiac echocardiography (ICE) in comparison to transesophageal echocardiography (TEE) guidance for transcatheter closure of Ostium Secundum Atrial Septal Defect (OS-ASD). METHOD: Ninety patients (n = 90) diagnosed with OS-ASD underwent transcatheter closure between March 2006 and October 2021. Fifty-seven patients were treated under ICE guidance, while 33 patients were treated under TEE guidance. RESULTS: Mean age was 43 ± 15 years and 42 ± 10 years in the ICE and TEE groups, respectively. The majority of patients had a centrally placed defect. Median FT was 8.40 min versus 11.70 min (p < .001) in the ICE group compared to the TEE group, respectively. Median PT was 43 min versus 94 min (p < .001) in the ICE group compared to the TEE group, respectively. Both ICE and TEE provided high quality images. All interventions were completed successfully, except for one patient in the ICE group who experienced a device migration, the development of atrial tachycardia in one patient and atrial fibrillation in two patients in the ICE group which spontaneously cardioverted. There were no other complications. CONCLUSION: This study on a consistent cohort of patients with OS-ASD undergoing percutaneous closure suggests that use of ICE is safe and efficacious. Compared to TEE, ICE demonstrated significantly shorter FT and PT, decreasing the entire duration of the procedure and x-ray exposure. No relevant differences were observed in terms of success rate and complications.

CAD-RADS scoring of coronary CT angiography with Multi-Axis Vision Transformer: A clinically-inspired deep learning pipeline.

BACKGROUND AND OBJECTIVE: The standard non-invasive imaging technique used to assess the severity and extent of Coronary Artery Disease (CAD) is Coronary Computed Tomography Angiography (CCTA). However, manual grading of each patient's CCTA according to the CAD-Reporting and Data System (CAD-RADS) scoring is time-consuming and operator-dependent, especially in borderline cases. This work proposes a fully automated, and visually explainable, deep learning pipeline to be used as a decision support system for the CAD screening procedure. The pipeline performs two classification tasks: firstly, identifying patients who require further clinical investigations and secondly, classifying patients into subgroups based on the degree of stenosis, according to commonly used CAD-RADS thresholds. METHODS: The pipeline pre-processes multiplanar projections of the coronary arteries, extracted from the original CCTAs, and classifies them using a fine-tuned Multi-Axis Vision Transformer architecture. With the aim of emulating the current clinical practice, the model is trained to assign a per-patient score by stacking the bi-dimensional longitudinal cross-sections of the three main coronary arteries along channel dimension. Furthermore, it generates visually interpretable maps to assess the reliability of the predictions. RESULTS: When run on a database of 1873 three-channel images of 253 patients collected at the Monzino Cardiology Center in Milan, the pipeline obtained an AUC of 0.87 and 0.93 for the two classification tasks, respectively. CONCLUSION: According to our knowledge, this is the first model trained to assign CAD-RADS scores learning solely from patient scores and not requiring finer imaging annotation steps that are not part of the clinical routine.