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.

Assessing the quality of life in Hydrocephalic children: A study from Tertiary Care Hospitals in Pakistan.

BACKGROUND: Hydrocephalus is a neurological disease with higher prevalence in the pediatric population, often managed by placing a shunt. This hollow tube drains excess cerebrospinal fluid from the brain to other body parts, resulting in several complications, including neurological and psychometric manifestations and a compromised quality-of-life (QoL). This study aimed to evaluate QoL in patients with hydrocephalus shunt placement within the pediatric population. METHODS: This prospective observational study was conducted in two major Pakistani tertiary care hospitals. A total of 100 subjects were enrolled, of which 52 were found eligible. A validated questionnaire, HOQ, was used to evaluate patients' QoL. RESULTS: This study included pediatric patients with a mean age of 6.54 and a standard deviation of ± 2.64. The male-to-female ratio was 27:25. 2% of patients had congenital or tumor-induced hydrocephalus, while cases of meningitis, encephalocele, and encephalitis accounted for 8, 4, and 2 percent respectively. Myelomeningocele had the highest prevalence at 16%. The overall health scores range from 0.39 to 0.51. Social, cognitive, and physical health scores have mean values of 0.54, 0.50, and 0.48, respectively. The minimum physical health score is 0.17, indicating the most significant impact of hydrocephalus on physical function. CONCLUSION: This study highlights variations in hydrocephalus severity among pediatric patients, impacting their overall QoL, primarily physical and behavioral functioning. Worse health outcomes were associated with frequent seizures, prolonged hospital stays for diagnosis and treatment, shunt infections, increased number of shunt catheters, and longer travel distances to medical facilities.

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.

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.

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.

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.

Enhancing cardiovascular risk stratification: Radiomics of coronary plaque and perivascular adipose tissue - Current insights and future perspectives.

Radiomics, the quantitative extraction and mining of features from radiological images, has recently emerged as a promising source of non-invasive image-based cardiovascular biomarkers, potentially revolutionizing diagnostics and risk assessment. This review explores its application within coronary plaques and pericoronary adipose tissue, particularly focusing on plaque characterization and cardiac events prediction. By shedding light on the current state-of-the-art, achievements, and prospective avenues, this review contributes to a deeper understanding of the evolving landscape of radiomics in the context of coronary arteries. Finally, open challenges and existing gaps are emphasized to underscore the need for future efforts aimed at ensuring the robustness and reliability of radiomics studies, facilitating their clinical translation.

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.

Beyond Stress Ischemia: Unveiling the Multifaceted Nature of Coronary Vulnerable Plaques Using Cardiac Computed Tomography.

Historically, cardiovascular prevention has been predominantly focused on stress-induced ischemia, but recent trials have challenged this paradigm, highlighting the emerging role of vulnerable, non-flow-limiting coronary plaques, leading to a shift towards integrating plaque morphology with functional data into risk prediction models. Coronary computed tomography angiography (CCTA) represents a high-resolution, low-risk, and largely available non-invasive modality for the precise delineation of plaque composition, morphology, and inflammatory activity, further enhancing our ability to stratify high-risk plaque and predict adverse cardiovascular outcomes. Coronary artery calcium (CAC) scoring, derived from CCTA, has emerged as a promising tool for predicting future cardiovascular events in asymptomatic individuals, demonstrating incremental prognostic value beyond traditional cardiovascular risk factors in terms of myocardial infarction, stroke, and all-cause mortality. Additionally, CCTA-derived information on adverse plaque characteristics, geometric characteristics, and hemodynamic forces provides valuable insights into plaque vulnerability and seems promising in guiding revascularization strategies. Additionally, non-invasive assessments of epicardial and pericoronary adipose tissue (PCAT) further refine risk stratification, adding prognostic significance to coronary artery disease (CAD), correlating with plaque development, vulnerability, and rupture. Moreover, CT imaging not only aids in risk stratification but is now emerging as a screening tool able to monitor CAD progression and treatment efficacy over time. Thus, the integration of CAC scoring and PCAT evaluation into risk stratification algorithms, as well as the identification of high-risk plaque morphology and adverse geometric and hemodynamic characteristics, holds promising results for guiding personalized preventive interventions, helping physicians in identifying high-risk individuals earlier, tailoring lifestyle and pharmacological interventions, and improving clinical outcomes in their patients.

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.

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

BACKGROUND: Studies evaluating the systematic use of cardiac computed tomography (CCT) for the preprocedural assessment of myocardial fibrosis are limited. Their implementation in the electrophysiology workflow has not been extensively described. OBJECTIVE: This study aimed to explore the degree of concordance between CCT and electroanatomic mapping (EAM) for the evaluation of cardiac fibrosis in patients undergoing endo-epicardial ventricular tachycardia (VT) ablation. METHODS: From November 2017 to December 2021, patients undergoing endo-epicardial VT catheter ablation with CCT as the only source of preprocedural scar assessment were prospectively enrolled. After image integration, myocardial fibrosis detected with CCT was compared with low-voltage areas identified by endo-epicardial EAM. Postprocedural VT recurrences of this approach were evaluated after at least 1 year of follow-up. RESULTS: The study enrolled 35 patients (mean age, 60.7 ± 13.2 years; 94.2% male). The most common underlying arrhythmic substrate was dilated cardiomyopathy (48.6%). CCT was employed for contraindications to cardiac magnetic resonance, such as unstable VTs (31.4%) or nonconditional implantable cardioverter-defibrillators (28.6%), 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 techniques both overall (Cohen κ for agreement, 0.933) and in per-segment analysis (κ ranging from 0.796 to 1.0). Ischemic patients showed the best correlation (κ = 1.000), whereas myocarditis showed the worst (κ = 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%. CONCLUSION: A CCT-based preprocedural assessment before VT ablation is feasible, showing high diagnostic concordance with EAM in detecting myocardial fibrosis.

Cardiac magnetic resonance reveals concealed structural heart disease in patients with frequent premature ventricular contractions and normal echocardiography: A systematic review.

Premature ventricular contractions (PVCs) are a common form of arrhythmic events, often representing an idiopathic and benign condition without further therapeutic interventions. However, in certain circumstances PVCs may represent the epiphenomenon of a concealed structural heart disease (SHD). Surface 12­leads EKG and 24-h dynamic EKG are necessary to assess their main characteristics such as site of origin, frequency and complexity. Echocardiography represents the first-line imaging tool recommended to evaluate cardiac structures and function. Cardiac Magnetic Resonance (CMR) is recognized as a superior modality for detecting structural cardiac alterations, that might evade detection by conventional echocardiography. Moreover, in specific populations such as athletes, CMR may have a crucial role to exclude a concealed SHD and the risk of serious arrhythmic events during sport activity. Some clinical characteristics such as male sex, older age or family history of sudden cardiac death (SCD) or cardiomyopathy, and some electrocardiographic features of PVCs, in particular a right branch bundle block (RBBB) with superior/intermediate axis morphology, the reproducibility of VAs during exercise test (ET) or the evidence of complex ventricular arrhythmias, may warrant a CMR evaluation, due to the high probability of SHD. In this systematic review our objective was to provide an exhaustive overview on the role of CMR in detecting a concealed SHD in patients with high daily burden of PVCs and a normal echocardiographic evaluation, paving the way for a more extensive utilization of CMR in presence of certain high-risk clinical and/or EKG features identified during the diagnostic workup.

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.

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.

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.

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.

STress computed tomogRaphy perfusion and stress cArdiac magnetic resonance for ThE manaGement of suspected or known coronarY artery disease: resources and outcomes impact.

BACKGROUND: The aim of this study is to describe resources and outcomes of coronary computed tomography angiography plus Stress CT perfusion (CCTA â€‹+ â€‹Stress-CTP) and stress cardiovascular magnetic resonance (Stress-CMR) in symptomatic patients with suspected or known CAD. METHODS: Six hundred and twenty-four consecutive symptomatic patients with intermediate to high-risk pretest likelihood for CAD or previous history of revascularization referred to our hospital for clinically indicated CCTA â€‹+ â€‹Stress-CTP or Stress-CMR were enrolled. Stress-CTP scans were performed in 223 patients while 401 patients performed Stress-CMR. Patient follow-up was performed at 1 year after index test performance. Endpoints were all cardiac events, as a combined endpoint of revascularization, non-fatal MI and death, and hard cardiac events, as combined endpoint of non-fatal MI and death. RESULTS: Twenty-nine percent of patients who underwent CCTA â€‹+ â€‹Stress-CTP received revascularization, 7% of subjects assessed with Stress-CMR were treated invasively, and a low number of non-fatal MI and death was observed with both strategies (hard events in 0.4% of patients that had CCTA â€‹+ â€‹Stress-CTP as index test, and in 3% of patients evaluated with Stress-CMR). According to the predefined endpoints, CCTA â€‹+ â€‹Stress-CTP group showed high rate of all cardiac events and low rate of hard cardiac events, respectively. The cumulative costs were 1970 â€‹± â€‹2506 Euro and 733 â€‹± â€‹1418 Euro for the CCTA â€‹+ â€‹Stress-CTP group and Stress-CMR group, respectively. CONCLUSIONS: The use of CCTA â€‹+ â€‹Stress-CTP strategy was associated with high referral to revascularization but with a favourable trend in terms of hard cardiac events and diagnostic yield in identifying individuals at lower risk of adverse events despite the presence of CAD.

PROGnostic RolE of strain measurements in stress cardiac MRI in predicting major adverse cardiac events.

OBJECTIVES: We aimed to investigate the role of feature-tracking (FT) strain in long-term risk stratification of patients with known or suspected coronary artery disease (CAD) who underwent stress cardiac MRI with dipyridamole; to determine if contrast-free stress cardiac MRI with strain measurements could provide comparable prognostic value to myocardial perfusion. MATERIALS AND METHODS: This retrospective study included consecutive patients with stable symptoms suggesting possible cardiac ischemia who underwent stress cardiac MRI with dipyridamole. The mean follow-up period was 5.8 years ±1.2 [SD]. FT cardiac MRI analysis was performed for each patient to obtain 2D global peak circumferential strain (GCS). The primary outcome measure was major adverse cardiac events (MACE), defined as nonfatal myocardial infarction and cardiac death. RESULTS: A total of 729 patients (mean age, 63 years ±10 [SD]; 616 males) were included. MACE occurred in 70 (9.6%) patients. The presence of late gadolinium enhancement (LGE) ([HR] 2.74, [95% CI: 1.53, 4.88]; P < .001) and stress GCS (HR, 1.06 [95% CI: 1.01, 1.12]; P = .016) were independently associated with MACE. A model based on contrast-free assessment of LVEF and stress GCS showed similar performance for predicting MACE than LVEF and perfusion (P = .056). CONCLUSIONS: In patients with known or suspected CAD undergoing stress cardiac MRI with dipyridamole, GCS and LGE presence were independent predictors of MACE. Contrast-free stress cardiac MRI with stress GCS measurement offered prognostic value akin to myocardial perfusion assessment. CLINICAL RELEVANCE STATEMENT: Stress global circumferential strain represented an additional method to predict major adverse cardiac events in patients undergoing stress cardiac MRI, even without the use of contrast agents. This would be of particular significance in patients with severe renal impairment.

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.

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.