Prediction of left ventricular thrombus after myocardial infarction: a cardiac magnetic resonance-based prospective registry.

Background: Left ventricular thrombus (LVTh) is a severe complication after ST-segment elevation myocardial infarction (STEMI).

Objectives: We aim to predict LVTh occurrence by cardiac magnetic resonance (CMR) using clinical, echocardiographic, and electrocardiographic (ECG) variables readily available at admission.

Methods: We included 590 reperfused STEMI patients who underwent early (1-week) and/or late (6-month) CMR in our institution.

Prognostic role of persistent angina after percutaneous revascularization in chronic coronary syndrome with altered angiography and stress CMR.

Introduction And Objectives: In patients with established chronic coronary syndrome (CCS), the significance of persistent angina is controversial. We aimed to evaluate the prognostic role of persistent angina in symptomatic CCS patients with abnormal stress cardiovascular magnetic resonance (CMR) and altered angiographic findings undergoing percutaneous revascularization.

Methods: We analyzed 334 CCS patients with Canadian Cardiovascular Society angina class ≥2, perfusion deficits on stress CMR and severe lesions in angiography who underwent medical therapy optimization plus CMR-guided percutaneous revascularization.

Brain dynamics supported by a hierarchy of complex correlation patterns defining a robust functional architecture.

Functional magnetic resonance imaging (fMRI) provides insights into cognitive processes with significant clinical potential. However, delays in brain region communication and dynamic variations are often overlooked in functional network studies. We demonstrate that networks extracted from fMRI cross-correlation matrices, considering time lags between signals, show remarkable reliability when focusing on statistical distributions of network properties.

Impact of Epicardial Adipose Tissue on Infarct Size and Left Ventricular Systolic Function in Patients with Anterior ST-Segment Elevation Myocardial Infarction.

We aimed to assess the correlation of cardiovascular magnetic resonance (CMR)-derived epicardial adipose tissue (EAT) with infarct size (IS) and residual systolic function in ST-segment elevation myocardial infarction (STEMI). We enrolled patients discharged for a first anterior reperfused STEMI submitted to undergo CMR. EAT, left ventricular (LV) ejection fraction (LVEF), and IS were quantified at the 1-week ( = 221) and at 6-month CMR ( = 167).

A Software Tool for the Measurement of the Aortic Annulus Area by Means of Computed Tomography Image Analysis for the Planning of Transcatheter Aortic Valve Replacement (TAVR).

Cardiovascular diseases (CVD) are the leading cause of death globally, being the heart valve complications one of the five most common heart problems. The aim of this study is the development of a MATLAB-based software tool to obtain several measurements derived from the aortic annulus for the planning of transcatheter aortic valve replacement (TAVR). The proposed software tool utilizes computed tomography (CT) images to reconstruct a volume of the patient.

Breast Cancer Diagnosis Using Texture and Shape Features in MRI.

Contrast-enhanced magnetic resonance (MR) breast imaging represents a tool with great potential for the detection, evaluation and diagnosis of breast cancer (BC). Due to its high sensitivity and in combination with medical imaging biomarkers, it can overcome setbacks and limitations manifested in other diagnostic modalities such as mammography or ultrasound. In order to aid and assist clinicians in the diagnosis of BC, a methodology based on the extraction of 2D texture and 3D shape features in MR images is proposed.

Deep Learning-Based Predictive Model for Revascularization of Chronic Total Occlusions on Angiographic Imaging.

Revascularization of chronic total occlusions (CTO) is currently one of the most complex procedures in percutaneous coronary intervention (PCI), requiring the use of specific devices and a high level of experience to obtain good results. Once the clinical indication for extensive ischemia or angina uncontrolled with medical treatment has been established, the decision to perform coronary intervention is not simple, since this procedure has a higher rate of complications than non-PCI percutaneous intervention, higher ionizing radiation doses and a lower success rate. However, CTO revascularization has been shown to be helpful in symptomatic improvement of angina, reduction of ischemic burden, or improvement of ejection fraction.

Deep Learning Segmentation of Lower Extremities Radiographs for an Automatic Leg Length Discrepancy Measurement.

Leg length measurement is relevant for the early diagnostic and treatment of discrepancies as they are related with orthopedic and biomechanical changes. Simple radiology constitutes the gold standard on which radiologists perform manual lower limb measurements. It is a simple task but represents an inefficient use of their time, expertise and knowledge that could be spent in more complex labors.

Alcohol-induced damage to the fimbria/fornix reduces hippocampal-prefrontal cortex connection during early abstinence.

Alcohol dependence is characterized by a gradual reduction in cognitive control and inflexibility to contingency changes. The neuroadaptations underlying this aberrant behavior are poorly understood. Using an animal model of alcohol use disorders (AUD) and complementing diffusion-weighted (dw)-MRI with quantitative immunohistochemistry and electrophysiological recordings, we provide causal evidence that chronic intermittent alcohol exposure affects the microstructural integrity of the fimbria/fornix, decreasing myelin basic protein content, and reducing the effective communication from the hippocampus (HC) to the prefrontal cortex (PFC).

Clinical results of lumbar sympathetic blocks in lower limb complex regional pain syndrome using infrared thermography as a support tool.

Aim: To describe the clinical outcomes for a group of complex regional pain syndrome patients using infrared thermography as an intraprocedural support tool when undertaking fluoroscopy-guided lumbar sympathetic blocks.

Subjects: 27 patients with lower limb complex regional pain syndrome accompanied by severe pain and persistent functional impairment.

Methods: A series of three fluoroscopic-guided lumbar sympathetic blocks with local anesthetic and corticoids using infrared thermography as an intraprocedural support tool were performed.

Application of machine learning algorithms in thermal images for an automatic classification of lumbar sympathetic blocks.

Purpose: There are no previous studies developing machine learning algorithms in the classification of lumbar sympathetic blocks (LSBs) performance using infrared thermography data. The objective was to assess the performance of different machine learning algorithms to classify LSBs carried out in patients diagnosed with lower limbs Complex Regional Pain Syndrome as successful or failed based on the evaluation of thermal predictors.

Methods: 66 LSBs previously performed and classified by the medical team were evaluated in 24 patients.

Impact of Persistent Microvascular Obstruction Late After STEMI on Adverse LV Remodeling: A CMR Study.

Background: Little is known about the occurrence and implications of persistent microvascular obstruction (MVO) after reperfused ST-segment elevation myocardial infarction (STEMI).

Objectives: The authors used cardiac magnetic resonance (CMR) to characterize the impact of persistent MVO on adverse left ventricular remodeling (ALVR).

Methods: A prospective registry of 471 STEMI patients underwent CMR 7 (IQR: 5-10) days and 198 (IQR: 167-231) days after infarction.

MRI texture-based radiomics analysis for the identification of altered functional networks in alcoholic patients and animal models.

Alcohol use disorder (AUD) is a complex condition representing a leading risk factor for death, disease and disability. Its high prevalence and severe health consequences make necessary a better understanding of the brain network alterations to improve diagnosis and treatment. The purpose of this study was to evaluate the potential of resting-state fMRI 3D texture features as a novel source of biomarkers to identify AUD brain network alterations following a radiomics approach.

Prognostic value of cardiac magnetic resonance early after ST-segment elevation myocardial infarction in older patients.

Background: older patients with ST-segment elevation myocardial infarction (STEMI) represent a very high-risk population. Data on the prognostic value of cardiac magnetic resonance (CMR) in this scenario are scarce.

Methods: the registry comprised 247 STEMI patients over 70 years of age treated with percutaneous intervention and included in a multicenter registry.

Texture Analysis in MRI of the Knee for an Early Diagnosis of Osteoarthritis.

Osteoarthritis is one of the most disabling diseases in developed countries. Its etiology is not firmly established, and the diagnosis is made by observing radiographs, assigning a degree of severity based on the information displayed. For this reason, the diagnosis is usually late and determined by the subjectivity of the doctor, which implies a restriction of the treatment.

Multiclass Classification of Prostate Tumors Following an MR Image Analysis-Based Radiomics Approach.

Prostate cancer is one of the most common cancers in men, with symptoms that may be confused with those caused by benign prostatic hyperplasia. One of the key aspects of treating prostate cancer is its early detection, increasing life expectancy and improving the quality of life of those patients. However, the tests performed are often invasive, resulting in a biopsy.

Analysis of New Biomarkers for the Study of Schizophrenia Following a Radiomics Approach on MR and PET Imaging.

Traditionally, the diagnosis of schizophrenia was based on the psychiatrist's introspective diagnosis through clinical stratification factors and score-scales, which led to heterogeneity and discrepancy in the symptoms and results. However, there are many studies trying to improve and assist in how its diagnosis could be performed. To objectively classify schizophrenia patients it is required to determine quantitative biomarkers of the disease.

Synthetic Generation of Cardiac MR Images Combining Convolutional Variational Autoencoders and Style Transfer.

The number of studies in the medical field that uses machine learning and deep learning techniques has been increasing in the last years. However, these techniques require a huge amount of data that can be difficult and expensive to obtain. This specially happens with cardiac magnetic resonance (MR) images.

Development of an Image-Based Methodology for the Evaluation of Histopathological Features in Human Meningioma.

Meningioma is the most common intracranial tumor in adulthood. With a clear female predominance and a recurrence rate that reaches 20%, it is, despite being considered a benign tumor, a pathology that greatly compromises post-diagnosis quality of life. Its prone to recur or progress to a higher degree is difficult to predict in the absence of obvious histological criteria.

Detection and Classification of Myocardial Infarction Transmurality Using Cardiac MR Image Analysis and Machine Learning Algorithms.

The presence of abnormalities when the left ventricle is deformed is related to the patients' prognosis after a first myocardial infarction. These deformations can be detected by performing a cardiac magnetic resonance (CMR) study. Currently, late gadolinium enhancement (LGE) is considered to be the gold standard when performing CMR imaging.

End-systole and end-diastole detection in short axis cine MRI using a fully convolutional neural network with dilated convolutions.

The correct assessment and characterization of heart anatomy and functionality is usually done through inspection of magnetic resonance image cine sequences. In the clinical setting it is especially important to determine the state of the left ventricle. This requires the measurement of its volume in the end-diastolic and end-systolic frames within the sequence trough segmentation methods.

Low-Power Lossless Data Compression for Wireless Brain Electrophysiology.

Wireless electrophysiology opens important possibilities for neuroscience, especially for recording brain activity in more natural contexts, where exploration and interaction are not restricted by the usual tethered devices. The limiting factor is transmission power and, by extension, battery life required for acquiring large amounts of neural electrophysiological data. We present a digital compression algorithm capable of reducing electrophysiological data to less than 65.

Brain Network Allostasis after Chronic Alcohol Drinking Is Characterized by Functional Dedifferentiation and Narrowing.

Alcohol use disorder (AUD) causes complex alterations in the brain that are poorly understood. The heterogeneity of drinking patterns and the high incidence of comorbid factors compromise mechanistic investigations in AUD patients. Here we used male Marchigian Sardinian alcohol-preferring (msP) rats, a well established animal model of chronic alcohol drinking, and a combination of longitudinal resting-state fMRI and manganese-enhanced MRI to provide objective measurements of brain connectivity and activity, respectively.

Sex Effect in the Decision to Perform Invasive Coronary Angiography in Patients With Chronic Coronary Syndrome After Undergoing Vasodilator Stress MRI.

Background: Stress cardiac MRI permits comprehensive evaluation of patients with known or suspected chronic coronary syndromes (CCS). The impact of sex on the use of invasive cardiac angiography (ICA) after vasodilator stress cardiac MRI is unclear.

Purpose: To evaluate the impact of sex on ICA use after vasodilator stress cardiac MRI.