Usability and accuracy of two different aortic annulus sizing software programs in patients undergoing transcatheter aortic valve replacement.

BACKGROUND: Semi-automated software is essential for planning and prosthesis selection prior transcatheter aortic valve replacement (TAVR). Reliable data on the usability of software programs for planning a TAVR is missing. The aim of this study was to compare software programs 'Valve Assist 2' (GE Healthcare) and 3mensio 'Structural Heart' (Pie Medical Imaging) regarding usability and accuracy of prosthesis size selection in program-inexperienced users. METHODS: Thirty-one participants (n = 31) were recruited and divided into program-inexperienced users (beginners) (n = 22) and experts (n = 9). After software training, beginners evaluated 3 patient cases in 129 measurements (n = 129) using either Valve Assist 2 (n = 11) or Structural Heart (n = 11) on 2 test days (T1, T2). System Usability Scale (SUS) and ISONORM 9241/110-S (ISONORM) questionnaire were used after the test. The valve size selected by each beginner was compared with the valve size selected from expert group. RESULTS: Valve Assist 2 had higher SUS Score: median 78.75 (25th, 75th percentile: 67.50, 85.00) compared to Structural Heart: median 65.00 (25th, 75th percentile: 47.50, 73.75), (p < 0,001, r = 0.557). Also, Valve Assist 2 showed a higher ISONORM score: median 1.05 (25th, 75th percentile: - 0.19, 1.71) compared to Structural Heart with a median 0.05 (25th, 75th percentile: - 0.49, 0.13), (p = 0.036, r = 0.454). Correctly selected valve sizes were stable over time using Valve Assist 2: 72.73% to 69.70% compared to Structural Heart program: 93.94% to 40% (χ2 (1) = 21.10, p < 0.001, φ = 0.579). CONCLUSION: The study shows significant better usability scores for Valve Assist 2 compared to 3mensio Structural Heart in program-inexperienced users.

Perfect Match: Radiomics and Artificial Intelligence in Cardiac Imaging.

Cardiovascular diseases remain a significant health burden, with imaging modalities like echocardiography, cardiac computed tomography, and cardiac magnetic resonance imaging playing a crucial role in diagnosis and prognosis. However, the inherent heterogeneity of these diseases poses challenges, necessitating advanced analytical methods like radiomics and artificial intelligence. Radiomics extracts quantitative features from medical images, capturing intricate patterns and subtle variations that may elude visual inspection. Artificial intelligence techniques, including deep learning, can analyze these features to generate knowledge, define novel imaging biomarkers, and support diagnostic decision-making and outcome prediction. Radiomics and artificial intelligence thus hold promise for significantly enhancing diagnostic and prognostic capabilities in cardiac imaging, paving the way for more personalized and effective patient care. This review explores the synergies between radiomics and artificial intelligence in cardiac imaging, following the radiomics workflow and introducing concepts from both domains. Potential clinical applications, challenges, and limitations are discussed, along with solutions to overcome them.

CT-derived Fractional Flow Reserve: How, When, and Where to use this Novel Cardiac Imaging Tool.

Fractional flow reserve computed tomography (FFRCT) is a novel imaging modality. It utilizes computational fluid dynamics analysis of coronary blood flow obtained from CCTA images to estimate the decrease in pressure across coronary stenosis during the maximum hyperemia. The FFRCT can serve as a valuable tool in the assessment of coronary artery disease (CAD). This non-invasive option can be used as an alternative to the invasive fractional Flow Reserve (FFR) evaluation, which is presently considered the gold standard for evaluating the physiological significance of coronary stenoses. It can help in several clinical situations, including Assessment of Acute and stable chest pain, virtual planning for coronary stenting, and treatment decision-making. Although FFRCT has demonstrated potential clinical applications as a non-invasive imaging technique, it is also crucial to acknowledge its limitations in clinical practice. As a result, it is imperative to meticulously evaluate the advantages and drawbacks of FFRCT individually and contemplate its application in combination with other diagnostic examinations and clinical data.

Aortic geometry and long-term outcome in patients with a repaired coarctation.

OBJECTIVE: This study aims to compare aortic morphology between repaired coarctation patients and controls, and to identify aortic morphological risk factors for hypertension and cardiovascular events (CVEs) in coarctation patients. METHODS: Repaired coarctation patients with computed tomography angiography (CTA) or magnetic resonance angiography (MRA) were included, followed-up and compared with sex-matched and age-matched controls. Three-dimensional aortic shape was reconstructed using patients' CTA or MRA, or four-dimensional flow cardiovascular magnetic resonance in controls, and advanced geometrical characteristics were calculated and visualised using statistical shape modelling. In patients, we examined the association of geometrical characteristics with (1) baseline hypertension, using multivariable logistic regression; and (2) cardiovascular events (CVE, composite of aortic complications, coronary artery disease, ventricular arrhythmias, heart failure hospitalisation, stroke, transient ischaemic attacks and cardiovascular death), using multivariable Cox regression. The least absolute shrinkage and selection operator (LASSO) method selected the most informative multivariable model. RESULTS: Sixty-five repaired coarctation patients (23 years (IQR 19-38)) were included, of which 44 (68%) patients were hypertensive at baseline. After a median follow-up of 8.7 years (IQR 4.8-15.4), 27 CVEs occurred in 20 patients. Aortic arch dimensions were smaller in patients compared with controls (diameter p<0.001, wall surface area p=0.026, volume p=0.007). Patients had more aortic arch torsion (p<0.001) and a higher curvature (p<0.001). No geometrical characteristics were associated with hypertension. LASSO selected left ventricular mass, male sex, tortuosity and age for the multivariable model. Left ventricular mass (p=0.014) was independently associated with CVE, and aortic tortuosity showed a trend towards significance (p=0.070). CONCLUSION: Repaired coarctation patients have a smaller aortic arch and a more tortuous course of the aorta compared with controls. Besides left ventricular mass index, geometrical features might be of importance in long-term risk assessment in coarctation patients.

Combined brain-heart MRI identifies cardiac and white matter lesions in patients with systemic lupus erythematosus and/or antiphospholipid syndrome: A pilot study.

BACKGROUND: Antiphospholipid syndrome (APS) can occur primarily (PAPS) or secondary to another autoimmune disease (SAPS), most commonly systemic lupus erythematosus (SLE). Recently, we reported that subclinical brain involvement was highly prevalent in patients with autoimmune diseases, including SLE. We aimed to investigate whether patients with SLE, PAPS or SAPS and cardiac symptoms showed differences in cardiac/brain involvement based on combined brain-heart magnetic resonance imaging (MRI). METHODS: We prospectively recruited 15 patients with SAPS (86 % with SLE) and 3 patients with PAPS and compared their MRI findings to those of 13 patients with SLE from our previous publication. All patients underwent routine cardiovascular/neurological examination and standard echocardiography. RESULTS: No patients had abnormalities in routine clinical workup/echocardiography. The vast majority had white matter hyperintensities (WMHs) and all had evidence of myocardial fibrosis and/or inflammation. Patients with SAPS had a lower median WMH number [1.00 (1.00, 2.00)] than those with PAPS [3.00 (2.50, 3.00)] or SLE [2.00 (2.00, 3.00)] (p = 0.010). Subcortical and deep WM were highly prevalent. Periventricular WMHs were more frequent in patients with SLE [6 (46.2 %)] or PAPS [2 (66.7 %)] (p = 0.023). Higher lesion burdens (1 WMH vs. 2 WMHs vs. ≥ WMHs) were associated with the presence of cardiac fibrosis [3 (33.3 %) vs. 10 (83.3) vs. 7 (77.8), p = 0.039] and affected the deep and periventricular WM (p < 0.001 for both). CONCLUSION: In patients with PAPS, SAPS or SLE, cardiac symptoms and normal routine workup, combined brain-heart MRI identified abnormalities in both organs in the majority of patients. Combined brain-heart MRI offers excellent diagnostic value, but its incorporation into routine clinical practice should be further investigated. Clinical relevance statement Combined brain-heart magnetic resonance imaging in antiphospholipid syndrome may help to assess the presence of abnormalities in both organs.

Social media for cardiac imagers: a review.

Cardiac imaging plays a pivotal role in the diagnosis and management of cardiovascular diseases. In the burgeoning landscape of digital technology and social media platforms, it becomes essential for cardiac imagers to know how to effectively increase the visibility and the impact of their activity. With the availability of social sites like X (formerly Twitter), Instagram and Facebook, cardiac imagers can now reach a wider audience and engage with peers, sharing their findings, insights, and discussions. The integration of persistent identifiers, such as Digital Object Identifiers (DOIs), facilitates traceability and citation of cardiac imaging publications across various digital platforms, further enhancing their discoverability. To maximize visibility, practical advice is provided, including the use of visually engaging infographics and videos, as well as the strategic implementation of relevant hashtags and keywords. These techniques can significantly improve the discoverability of cardiac imaging research through search engine optimization and social media algorithms. Tracking impact and engagement is crucial in the digital age, and this review discusses various metrics and tools to gauge the reach and influence of cardiac imaging publications. This includes traditional citation-based metrics and altmetrics. Moreover, this review underscores the importance of creating and updating professional profiles on social platforms and participating in relevant scientific communities online. The adoption of digital technology, social platforms, and a strategic approach to publication sharing can empower cardiac imaging professionals to enhance the visibility and impact of their research, ultimately advancing the field and improving patient care.

Competence of radiologists in cardiac CT and MR imaging in Europe: insights from the ESCR Registry.

RATIONALE: To provide an overview of the current status of cardiac multimodality imaging practices in Europe and radiologist involvement using data from the European Society of Cardiovascular Radiology (ESCR) MRCT-registry. MATERIALS AND METHODS: Numbers on cardiac CT and MRI examinations were extracted from the MRCT-registry of the ESCR, entered between January 2011 and October 2023 (n = 432,265). Data collection included the total/annual numbers of examinations, indications, complications, and reporting habits. RESULTS: Thirty-two countries contributed to the MRCT-registry, including 29 European countries. Between 2011 and 2022, there was a 4.5-fold increase in annually submitted CT examinations, from 3368 to 15,267, and a 3.8-fold increase in MRI examinations, from 3445 to 13,183. The main indications for cardiac CT were suspected coronary artery disease (CAD) (59%) and transcatheter aortic valve replacement planning (21%). The number of patients with intermediate pretest probability who underwent CT for suspected CAD showed an increase from 61% in 2012 to 82% in 2022. The main MRI indications were suspected myocarditis (26%), CAD (21%), and suspected cardiomyopathy (19%). Adverse event rates were very low for CT (0.3%) and MRI (0.7%) examinations. Reporting of CT and MRI examinations was performed mainly by radiologists (respectively 76% and 71%) and, to a lesser degree, in consensus with non-radiologists (19% and 27%, respectively). The remaining examinations (4.9% CT and 1.7% MRI) were reported by non-radiological specialties or in separate readings of radiologists and non-radiologists. CONCLUSIONS: Real-life data on cardiac imaging in Europe using the largest available MRCT-registry demonstrate a considerable increase in examinations over the past years, the vast majority of which are read by radiologists. These findings indicate that radiologists contribute to meeting the increasing demands of competent and effective care in cardiac imaging to a relevant extent. CLINICAL RELEVANCE STATEMENT: The number of cardiac CT and MRI examinations has risen over the past years, and radiologists read the vast majority of these studies as recorded in the MRCT-registry. KEY POINTS: • The number of cardiac imaging examinations is constantly increasing. • Radiologists play a central role in providing cardiac CT and MR imaging services to a large volume of patients. • Cardiac CT and MR imaging examinations performed and read by radiologists show a good safety profile.

Pre-TAVI imaging: an Italian survey by the CT PRotocol optimization (CT-PRO) group.

PURPOSE: The purpose of this survey was to evaluate the current state-of-art of pre-TAVI imaging in a large radiological professional community. METHODS: Between December 2022 and January 2023 all members of the Italian Society of Medical and Interventional Radiology (SIRM) were invited by the CT PRotocol Optimization group (CT-PRO group) to complete an online 24-item questionnaire about pre-TAVI imaging. RESULTS: 557 SIRM members participated in the survey. The greatest part of respondents were consultant radiologists employed in public hospitals and 84% claimed to routinely perform pre-TAVI imaging at their institutions. The most widespread acquisition protocol consisted of an ECG-gated CT angiography (CTA) scan of the aortic root and heart followed by a non-ECG-synchronized CTA of the thorax, abdomen, and pelvis. Contrast agent administration was generally tailored on the patient's body weight with a preference for using high concentration contrast media. The reports were commonly written by radiologists with expertise in cardiovascular imaging, and included all the measurements suggested by current guidelines for adequate pre-procedural planning. About 60% of the subjects affirmed that the Heart Team is present at their institutions, however only 7% of the respondents regularly attended the multidisciplinary meetings. CONCLUSIONS: This survey defines the current pre-TAVI imaging practice in a large radiological professional community. Interestingly, despite the majority of radiologists follow the current guidelines regarding acquisition and reporting of pre-TAVI imaging studies, there is still a noteworthy absence from multidisciplinary meetings and from the Heart Team.

Value Creation Through Artificial Intelligence and Cardiovascular Imaging: A Scientific Statement From the American Heart Association.

Multiple applications for machine learning and artificial intelligence (AI) in cardiovascular imaging are being proposed and developed. However, the processes involved in implementing AI in cardiovascular imaging are highly diverse, varying by imaging modality, patient subtype, features to be extracted and analyzed, and clinical application. This article establishes a framework that defines value from an organizational perspective, followed by value chain analysis to identify the activities in which AI might produce the greatest incremental value creation. The various perspectives that should be considered are highlighted, including clinicians, imagers, hospitals, patients, and payers. Integrating the perspectives of all health care stakeholders is critical for creating value and ensuring the successful deployment of AI tools in a real-world setting. Different AI tools are summarized, along with the unique aspects of AI applications to various cardiac imaging modalities, including cardiac computed tomography, magnetic resonance imaging, and positron emission tomography. AI is applicable and has the potential to add value to cardiovascular imaging at every step along the patient journey, from selecting the more appropriate test to optimizing image acquisition and analysis, interpreting the results for classification and diagnosis, and predicting the risk for major adverse cardiac events.

Coronary Artery Calcification: Current Concepts and Clinical Implications.

Coronary artery calcification (CAC) accompanies the development of advanced atherosclerosis. Its role in atherosclerosis holds great interest because the presence and burden of coronary calcification provide direct evidence of the presence and extent of coronary artery disease; furthermore, CAC predicts future events independently of concomitant conventional cardiovascular risk factors and to a greater extent than any other noninvasive biomarker of this disease. Nevertheless, the relationship between CAC and the susceptibility of a plaque to provoke a thrombotic event remains incompletely understood. This review summarizes the current understanding and literature on CAC. It outlines the pathophysiology of CAC and reviews laboratory, histopathological, and genetic studies, as well as imaging findings, to characterize different types of calcification and to elucidate their implications. Some patterns of calcification such as microcalcification portend increased risk of rupture and cardiovascular events and may improve prognosis assessment noninvasively. However, contemporary computed tomography cannot assess early microcalcification. Limited spatial resolution and blooming artifacts may hinder estimation of degree of coronary artery stenosis. Technical advances such as photon counting detectors and combination with nuclear approaches (eg, NaF imaging) promise to improve the performance of cardiac computed tomography. These innovations may speed achieving the ultimate goal of providing noninvasively specific and clinically actionable information.

Imaging patients with myocardial infarction with non-obstructive coronary arteries (MINOCA).

Myocardial infarction with non-obstructive coronary arteries (MINOCA) defines a heterogeneous group of atherosclerotic and non-atherosclerotic conditions, causing myocardial injury in the absence of obstructive coronary artery disease. Unveiling the mechanisms subtended to the acute event is often challenging; a multimodality imaging approach is helpful to aid the diagnosis. Invasive coronary imaging with intravascular ultrasound or optical coherence tomography should be used, when available, during index angiography to detect plaque disruption or spontaneous coronary artery dissection. Cardiovascular magnetic resonance has instead a key role among the non-invasive modalities, allowing the differentiation between MINOCA and its non-ischaemic mimics and providing prognostic information. This educational paper will provide a comprehensive review of the strengths and limitations of each imaging modality in the evaluation of patients with a working diagnosis of MINOCA.

Comparison of Intracardiac Echocardiography Versus Transesophageal Echocardiography for Guidance During Transcatheter Aortic Valve Replacement.

BACKGROUND AND OBJECTIVES: Evidence regarding the efficacy and safety of intracardiac echocardiography (ICE) for guidance during transcatheter aortic valve replacement (TAVR) is limited. This study aimed to compare the clinical efficacy and safety of ICE versus transesophageal echocardiography (TEE) for guiding TAVR. METHODS: This prospective cohort study included patients who underwent TAVR from August 18, 2015, to June 31, 2021. Eligible patients were stratified by echocardiographic modality (ICE or TEE) and anesthesia mode (monitored anesthesia care [MAC] or general anesthesia [GA]). Primary outcome was the 1-year composite of all-cause mortality, rehospitalization for cardiovascular cause, or stroke, according to the Valve Academic Research Consortium-3 (VARC-3) definition. Propensity score matching was performed, and study outcomes were analyzed for the matched cohorts. RESULTS: Of the 359 eligible patients, 120 patients were matched for the ICE-MAC and TEE-GA groups, respectively. The incidence of primary outcome was similar between matched groups (18.3% vs. 20.0%; adjusted hazard ratio, 0.94; 95% confidence interval [CI], 0.53-1.68; p=0.843). ICE-MAC and TEE-GA also had similar incidences of moderate-to-severe paravalvular regurgitation (PVR) (4.2% vs. 5.0%; adjusted odds ratio, 0.83; 95% CI, 0.23-2.82; p=0.758), new permanent pacemaker implantation, and VARC-3 types 2-4 bleeding. CONCLUSIONS: ICE was comparable to TEE for guidance during TAVR for the composite clinical efficacy outcome, with similar incidences of moderate-to-severe PVR, new permanent pacemaker implantation, and major bleeding. These results suggest that ICE could be a safe and effective alternative echocardiographic modality to TEE for guiding TAVR.

Quantitative metrics of the LV trabeculated layer by cardiac CT and cardiac MRI in patients with suspected noncompaction cardiomyopathy.

OBJECTIVES: To compare cardiac computed tomography (CCT) and cardiac magnetic resonance (CMR) for the quantitative assessment of the left ventricular (LV) trabeculated layer in patients with suspected noncompaction cardiomyopathy (NCCM). MATERIALS AND METHODS: Subjects with LV excessive trabeculation who underwent both CMR and CCT imaging as part of the prospective international multicenter NONCOMPACT clinical study were included. For each subject, short-axis CCT and CMR slices were matched. Four quantitative metrics were estimated: 1D noncompacted-to-compacted ratio (NCC), trabecular-to-myocardial area ratio (TMA), trabecular-to-endocardial cavity area ratio (TCA), and trabecular-to-myocardial volume ratio (TMV). In 20 subjects, end-diastolic and mid-diastolic CCT images were compared for the quantification of the trabeculated layer. Relationships between the metrics were investigated using linear regression models and Bland-Altman analyses. RESULTS: Forty-eight subjects (49.9 ± 12.8 years; 28 female) were included in this study. NCC was moderately correlated (r = 0.62), TMA and TMV were strongly correlated (r = 0.78 and 0.78), and TCA had excellent correlation (r = 0.92) between CMR and CCT, with an underestimation bias from CCT of 0.3 units, and 5.1, 4.8, and 5.4 percent-points for the 4 metrics, respectively. TMA, TCA, and TMV had excellent correlations (r = 0.93, 0.96, 0.94) and low biases (- 3.8, 0.8, - 3.8 percent-points) between the end-diastolic and mid-diastolic CCT images. CONCLUSIONS: TMA, TCA, and TMV metrics of the LV trabeculated layer in patients with suspected NCCM demonstrated high concordance between CCT and CMR images. TMA and TCA were highly reproducible and demonstrated minimal differences between mid-diastolic and end-diastolic CCT images. CLINICAL RELEVANCE STATEMENT: The results indicate similarity of CCT to CMR for quantifying the LV trabeculated layer, and the small differences in quantification between end-diastole and mid-diastole demonstrate the potential for quantifying the LV trabeculated layer from clinically performed coronary CT angiograms. KEY POINTS: • Data on cardiac CT for quantifying the left ventricular trabeculated layer are limited. • Cardiac CT yielded highly reproducible metrics of the left ventricular trabeculated layer that correlated well with metrics defined by cardiac MR. • Cardiac CT appears to be equivalent to cardiac MR for the quantification of the left ventricular trabeculated layer.

Fusion Modeling: Combining Clinical and Imaging Data to Advance Cardiac Care.

In addition to the traditional clinical risk factors, an increasing amount of imaging biomarkers have shown value for cardiovascular risk prediction. Clinical and imaging data are captured from a variety of data sources during multiple patient encounters and are often analyzed independently. Initial studies showed that fusion of both clinical and imaging features results in superior prognostic performance compared with traditional scores. There are different approaches to fusion modeling, combining multiple data resources to optimize predictions, each with its own advantages and disadvantages. However, manual extraction of clinical and imaging data is time and labor intensive and often not feasible in clinical practice. An automated approach for clinical and imaging data extraction is highly desirable. Convolutional neural networks and natural language processing can be utilized for the extraction of electronic medical record data, imaging studies, and free-text data. This review outlines the current status of cardiovascular risk prediction and fusion modeling; and in addition gives an overview of different artificial intelligence approaches to automatically extract data from images and electronic medical records for this purpose.

Cardiac dysfunction in survivors of sepsis: a scoping review.

BACKGROUND: Sepsis is associated with an increased risk of adverse cardiovascular events in a magnitude comparable to other major cardiovascular risk factors. Sepsis is one of the most common reasons for intensive care admission and survivors often have significant functional limitations following discharge. However, it is not clear to what extent chronic cardiovascular dysfunction might mediate these functional impairments, or how we might screen and manage these patients at risk of chronic cardiovascular disease. We conducted a scoping review to map existing evidence and identify research gaps relating to cardiovascular dysfunction following sepsis. METHODS: We conducted a systematic search of MEDLINE, Embase and CINAHL databases using a concept, context, population (CoCoPop) framework. Studies examining cardiovascular outcomes or symptoms following an episode of sepsis in adults were included. Data were mapped based on the population assessed, cardiovascular outcomes examined, inclusion of objective measures of cardiac dysfunction such as biomarkers or cardiovascular imaging, or whether cardiovascular symptoms or patient-reported functional outcomes measures were recorded. RESULTS: We identified 11 210 articles of which 70 were eligible for full text review and 28 were included in final analysis. Across our dataset, a wide range of incident cardiovascular outcomes were reported in the literature including incidence of congestive heart failure (13/28), arrhythmia (6/28), myocardial infarction (24/28) or cardiovascular death or all-cause mortality (20/28). Only 39% (11/28) of articles reported objective measures of cardiovascular function and only one article related cardiovascular function to functional impairment via patient-reported outcome measures. CONCLUSION: There are significant gaps in our understanding of cardiac dysfunction following sepsis . While the research highlights the strong association of sepsis with a variety of adverse cardiovascular outcomes, further prospective work is required to understand the mechanisms that mediate this phenomenon and how we can best identify and manage patients at risk.

Cardiac MR modelling of systolic and diastolic blood pressure.

AIMS: Blood pressure (BP) is a crucial factor in cardiovascular health and can affect cardiac imaging assessments. However, standard outpatient cardiovascular MR (CMR) imaging procedures do not typically include BP measurements prior to image acquisition. This study proposes that brachial systolic BP (SBP) and diastolic BP (DBP) can be modelled using patient characteristics and CMR data. METHODS: In this multicentre study, 57 patients from the PREFER-CMR registry and 163 patients from other registries were used as the derivation cohort. All subjects had their brachial SBP and DBP measured using a sphygmomanometer. Multivariate linear regression analysis was applied to predict brachial BP. The model was subsequently validated in a cohort of 169 healthy individuals. RESULTS: Age and left ventricular ejection fraction were associated with SBP. Aortic forward flow, body surface area and left ventricular mass index were associated with DBP. When applied to the validation cohort, the correlation coefficient between CMR-derived SBP and brachial SBP was (r=0.16, 95% CI 0.011 to 0.305, p=0.03), and CMR-derived DBP and brachial DBP was (r=0.27, 95% CI 0.122 to 0.403, p=0.0004). The area under the curve (AUC) for CMR-derived SBP to predict SBP>120 mmHg was 0.59, p=0.038. Moreover, CMR-derived DBP to predict DBP>80 mmHg had an AUC of 0.64, p=0.002. CONCLUSION: CMR-derived SBP and DBP models can estimate brachial SBP and DBP. Such models may allow efficient prospective collection, as well as retrospective estimation of BP, which should be incorporated into assessments due to its critical effect on load-dependent parameters.

Electrovectorcardiographic study of left ventricular aneurysm in ischemic heart disease.

The aim was to characterize the electrovectorcardiographic pattern of ventricular aneurysms in ischemic cardiopathy by analyzing the cardiac ventricular repolarization. The medical records of 2,670 individuals were analyzed in this cross-sectional study. A test phase included 33 patients who underwent transthoracic echocardiogram with ultrasonic enhancing agent, electrocardiogram, and vectorcardiogram (aneurysm group - n = 22, and akinesia group - n = 11). In the validation phase, cardiac magnetic resonance imaging established the left ventricle segmental contractility in 16 patients who underwent electrocardiographic and vectorcardiographic tests (aneurysm group, n = 8, and akinesia group, n = 8). The variables studied were the presence of the T-wave plus-minus pattern and the T-wave loop anterior-posterior pattern in V2-V4. The diagnostic indices used were sensitivity, specificity, and predictive values, with their respective 95% confidence intervals. During the test and validation phases, the analysis of the presence of the T-wave plus-minus pattern identified the aneurysm group with a sensitivity of 91% vs. 87% and specificity of 91% vs. 87% (p < 0.0001 vs. p = 0.01), respectively. Meanwhile, the T-wave loop anterior-posterior pattern evidenced sensitivity of 95% vs. 77% and specificity of 91% vs. 87% (p < 0.0001 vs. p = 0.04), respectively. The electrovectorcardiographic parameters showed high accuracy for recognizing left ventricular aneurysms in ischemic heart disease.