Kinect-based Gesture Recognition in Volumetric Visualisation of Heart from Cardiac Magnetic Resonance (CMR) Imaging

2014 ◽  
pp. 79-92 ◽  
Author(s):  
Ahmad Hoirul Basori ◽  
Mohamad Rafiq bin Dato’ Abdul Kadir ◽  
Rosli Mohd Ali ◽  
Farhan Mohamed ◽  
Suhaini Kadiman
Keyword(s):  
Cardiac Magnetic Resonance ◽  
Magnetic Resonance ◽  
Gesture Recognition ◽  
Cmr Imaging

scholarly journals Incremental value of feature-tracking cardiac magnetic resonance imaging in detecting myocardial dysfunction in patients with idiopathic ventricular arrhythmias

2021 ◽  
Vol 22 (Supplement_1) ◽  
Author(s):  
C Nikolaidou ◽  
C Kotanidis ◽  
J Leal-Pelado ◽  
K Kouskouras ◽  
VP Vassilikos ◽  
...  
Keyword(s):  
Cardiac Magnetic Resonance ◽  
Magnetic Resonance ◽  
Ventricular Arrhythmias ◽  
Feature Tracking ◽  
Myocardial Dysfunction ◽  
Global Longitudinal Strain ◽  
Left Ventricular ◽  
Volume Index ◽  
Control Subjects ◽  
Cmr Imaging

Abstract Funding Acknowledgements Type of funding sources: None. Introduction Cardiac magnetic resonance (CMR) imaging can identify the underlying substrate in patients with ventricular arrhythmias (VAs) and normal echocardiography. Myocardial strain has emerged as a superior index of systolic performance compared to ejection fraction (EF), with an incremental prognostic value in many cardiac diseases. Purpose To assess myocardial deformation using 2-D feature-tracking CMR strain imaging (CMR-FT) in patients with frequent VAs (≥500 ventricular premature contractions (VPC)/24 hours; and/or non-sustained ventricular tachycardia), and structurally normal hearts on echocardiography without evidence of coronary artery disease. Methods Sixty-eight consecutive patients (mean age 46 ± 16 years; 54% female) and 72 healthy controls matched for age and body surface area were included in the study. CMR imaging was performed on a 1.5T Magnetom Avanto (Siemens, Erlangen, Germany) scanner using a standard cardiac protocol. Results CMR showed normal findings in 30 patients (44%), while 16 (24%) had previous myocarditis, 6 (9%) had a diagnosis of non-ischaemic cardiomyopathy (NICM), 15 (22%) were diagnosed with VPC-related cardiomyopathy, and 1 patient had subendocardial infarction [excluded from strain analysis]. Mean left ventricular EF (LVEF) in patients was 62% ± 6% and right ventricular EF 64% ± 6% (vs. 65% ± 3% and 66% ± 4% in controls, respectively). Compared to control subjects, patients with VAs had impaired peak LV global radial strain (GRS) (28.88% [IQR: 25.87% to 33.97%] vs. 36.65% [IQR:33.19% to 40.2%], p < 0.001) and global circumferential strain (GCS) (-17.73% [IQR: -19.8% to -16.33%] vs. -20.66% [IQR: -21.72% to -19.6%], p < 0.001, Panel A). Peak LV GRS could differentiate patients with previous myocarditis from patients with NICM and those with VPC-related cardiomyopathy (Panel B). Peak LV GCS could differentiate patients with previous myocarditis from patients with NICM (Panel C). Peak LV GRS showed excellent diagnostic accuracy in detecting patients from control subjects (Panel D). In a multivariable regression model, subjects with a low GRS (<29.91%-determined by the Youden’s index) had 5-fold higher odds of having VAs (OR:4.99 [95%CI: 1.2-21.95]), after adjusting for LVEF, LV end-diastolic volume index, age, sex, BMI, smoking, hypertension, and dyslipidaemia. Peak LV global longitudinal strain (GLS) and RV strain indices were not statistically different between patients and controls. Conclusion Peak LV GRS and GCS are impaired in patients with frequent idiopathic VAs and can detect myocardial contractile dysfunction in patients with different underlying substrates. Our findings suggest that LV strain indices on CMR-FT constitute independent markers of myocardial dysfunction on top and independently of EF. Abstract Figure.

scholarly journals Identification and prognostication of the substrate of ventricular arrhythmia with cardiac magnetic resonance (CMR) imaging in patients with normal echocardiography

2021 ◽  
Vol 22 (Supplement_1) ◽  
Author(s):  
S Younus ◽  
H Maqsood ◽  
A Gulraiz ◽  
MD Khan ◽  
R Awais
Keyword(s):  
Heart Disease ◽  
Ventricular Tachycardia ◽  
Cardiac Magnetic Resonance ◽  
Chest Pain ◽  
Magnetic Resonance ◽  
Ventricular Arrhythmia ◽  
Heart Diseases ◽  
Sustained Ventricular Tachycardia ◽  
Structural Heart Diseases ◽  
Cmr Imaging

Abstract Funding Acknowledgements Type of funding sources: Other. Main funding source(s): Self Introduction Malignant ventricular arrhythmia contributes to approximately half of the sudden cardiac deaths. In common practice, echocardiography is used to identify structural heart diseases that are the most frequent substrate of VA. Identification and prognostication of structural heart diseases are very important as they are the main determinant of poor prognosis of ventricular arrhythmia. Purpose : The objective of this study is to determine whether cardiac magnetic resonance (CMR) may identify structural heart disease (SHD) in patients with ventricular arrhythmia who had no pathology observed on echocardiography. Methods : A total of 864 consecutive patients were enrolled in this single-center prospective study with significant ventricular arrhythmia. VA was characterized as >1000 ventricular ectopic beats per 24 hours, non-sustained ventricular arrhythmia, sustained ventricular arrhythmia, and no pathological lesion on echocardiography. The primary endpoint was the detection of SHD with CMR. Secondary endpoints were a composite of CMR detection of SHD and abnormal findings not specific for a definite SHD diagnosis. Results : CMR studies were used to diagnose SHD in 212 patients (24.5%) and abnormal findings not specific for a definite SHD diagnosis in 153 patients (17.7%). Myocarditis (n = 84) was the more frequent disease, followed by arrhythmogenic cardiomyopathy (n = 51), ischemic heart disease (n = 32), dilated cardiomyopathy (n = 17), hypertrophic cardiomyopathy (n = 12), congenital cardiac disease (n = 08), left ventricle noncompaction (n = 5), and pericarditis (n = 3). The strongest univariate and multivariate predictors of SHD on CMR images were chest pain (odds ratios [OR]: 2.5 and 2.33, respectively) and sustained ventricular tachycardia (ORs: 2.62 and 2.21, respectively). Conclusion : Our study concludes that SHD was able to be identified on CMR imaging in a significant number of patients with malignant VA and completely normal echocardiography. Chest pain and sustained ventricular tachycardia were the two strongest predictors of positive CMR imaging results. Abstract Figure. Distribution of different SHD

Ischemic and non-ischemic dilated cardiomyopathy

Open Medicine ◽  
2014 ◽  
Vol 9 (1) ◽  
pp. 15-20 ◽  
Author(s):  
Giovanni Fazio ◽  
Federica Vernuccio ◽  
Emanuele Grassedonio ◽  
Giuseppe Grutta ◽  
Giuseppe Lo Re ◽  
...  
Keyword(s):  
Cardiac Magnetic Resonance ◽  
Magnetic Resonance ◽  
Dilated Cardiomyopathy ◽  
High Sensitivity ◽  
Left Ventricular ◽  
Ischemic Disease ◽  
Coronary Imaging ◽  
Diagnostic Potential ◽  
Non Ischemic Dilated Cardiomyopathy ◽  
Cmr Imaging

AbstractDilated Cardiomyopathy is a high-incident disease, which diagnosis of and treatments are clinical priority. The aim of our study was to evaluate the diagnostic potential of cardiac magnetic resonance (CMR) imaging; echocardiography and the biochemical parameters that can help us differentiate between the post-ischemic and non-ischemic dilated cardiomyopathy. Materials and methods. The study enrolled 134 patients with dilated cardiomyopathy: 74 with the post-ischemic form and 60 with the non-ischemic one. All patients underwent a coronary imaging test, with echocardiogram, cardiac magnetic resonance and a blood test. Pro-inflammatory cytokines were evaluated using Luminex kit. Data was compared between the two groups. Results. Echocardiography allowed recognition of Left Ventricular Non Compaction in 2 patients. Longitudinal and circumferential strains were significantly different in the two groups (p<0.05). Using CMR imaging a post-myocarditis scar was diagnosed in 2 patients and a post-ischemic scar in 95% of patients with the chronic ischemic disease. The interleukin IL-1, IL-6 and TNF-α levels were higher in the post-ischemic group compared with the non-ischemic one. Conclusions. The use of second level techniques with a high sensitivity and specificity would help distinguish among different sub-forms of dilated cardiomyopathy.

Cardiac Magnetic Resonance (CMR) Imaging

2016 ◽  
pp. 219-242
Author(s):  
Marcello Panagia ◽  
Jonathan Scheske ◽  
Brian Ghoshhajra ◽  
Sanjeev A. Francis
Keyword(s):  
Cardiac Magnetic Resonance ◽  
Magnetic Resonance ◽  
Cmr Imaging

scholarly journals Prognostic value of texture analysis from cardiac magnetic resonance imaging in patients with Takotsubo syndrome: a machine learning based proof-of-principle approach

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Manoj Mannil ◽  
Ken Kato ◽  
Robert Manka ◽  
Jochen von Spiczak ◽  
Benjamin Peters ◽  
...  
Keyword(s):  
Machine Learning ◽  
Cardiac Magnetic Resonance ◽  
Magnetic Resonance ◽  
Dimension Reduction ◽  
Texture Analysis ◽  
Prognostic Value ◽  
Takotsubo Syndrome ◽  
Proof Of Principle ◽  
Cmr Imaging

AbstractCardiac magnetic resonance (CMR) imaging has become an important technique for non-invasive diagnosis of takotsubo syndrome (TTS). The long-term prognostic value of CMR imaging in TTS has not been fully elucidated yet. This study sought to evaluate the prognostic value of texture analysis (TA) based on CMR images in patients with TTS using machine learning. In this multicenter study (InterTAK Registry), we investigated CMR imaging data of 58 patients (56 women, mean age 68 ± 12 years) with TTS. CMR imaging was performed in the acute to subacute phase (median time after symptom onset 4 days) of TTS. TA of the left ventricle was performed using free-hand regions-of-interest in short axis late gadolinium-enhanced and on T2-weighted (T2w) images. A total of 608 TA features adding the parameters age, gender, and body mass index were included. Dimension reduction was performed removing TA features with poor intra-class correlation coefficients (ICC ≤ 0.6) and those being redundant (correlation matrix with Pearson correlation coefficient r > 0.8). Five common machine-learning classifiers (artificial neural network Multilayer Perceptron, decision tree J48, NaïveBayes, RandomForest, and Sequential Minimal Optimization) with tenfold cross-validation were applied to assess 5-year outcome including major adverse cardiac and cerebrovascular events (MACCE). Dimension reduction yielded 10 TA features carrying prognostic information, which were all based on T2w images. The NaïveBayes machine learning classifier showed overall best performance with a sensitivity of 82.9% (confidence interval (CI) 80–86.2), specificity of 83.7% (CI 75.7–92), and an area-under-the receiver operating characteristics curve of 0.88 (CI 0.83–0.92). This proof-of-principle study is the first to identify unique T2w-derived TA features that predict long-term outcome in patients with TTS. These features might serve as imaging prognostic biomarkers in TTS patients.

scholarly journals Role of Cardiac Magnetic Resonance Imaging in the Evaluation of Athletes with Premature Ventricular Beats

2022 ◽  
Vol 11 (2) ◽  
pp. 426
Author(s):  
Giulia Brunetti ◽  
Alberto Cipriani ◽  
Martina Perazzolo Marra ◽  
Manuel De Lazzari ◽  
Barbara Bauce ◽  
...  
Keyword(s):  
Cardiac Magnetic Resonance ◽  
Magnetic Resonance ◽  
Training Session ◽  
Left Ventricular ◽  
Special Focus ◽  
Premature Ventricular Beats ◽  
Myocardial Substrate ◽  
Diagnostic Work ◽  
Cmr Imaging

Premature ventricular beats (PVBs) in athletes are not rare. The risk of PVBs depends on the presence of an underlying pathological myocardial substrate predisposing the subject to sudden cardiac death. The standard diagnostic work-up of athletes with PVBs includes an examination of family and personal history, resting electrocardiogram (ECG), 24 h ambulatory ECG (possibly with a 12-lead configuration and including a training session), maximal exercise testing and echocardiography. Despite its fundamental role in the diagnostic assessment of athletes with PVBs, echocardiography has very limited sensitivity in detecting the presence of non-ischemic left ventricular scars, which can be revealed only through more in-depth studies, particularly with the use of contrast-enhanced cardiac magnetic resonance (CMR) imaging. The morphology, complexity and exercise inducibility of PVBs can help estimate the probability of an underlying heart disease. Based on these features, CMR imaging may be indicated even when echocardiography is normal. This review focuses on interpreting PVBs, and on the indication and role of CMR imaging in the diagnostic evaluation of athletes, with a special focus on non-ischemic left ventricular scars that are an emerging substrate of cardiac arrest during sport.

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