Moving Towards a 5d Cardiac Model

Saïd²,

2020

Heliyon

Self Cite

A comparative study has been depicted between the contour and topographic watershed segmentation approach for short-axis 5D cardiac sequences with MRI for medical decision. The fifth dimension has been defined as the excitation of pixels based on the gray scale around the myocardium without consideration of the morphological structure of the heart in 3D and fourth dimension (time). Three patients were performed the first is healthy, the second has a genetic disease, and the third had a heart failure syndrome for a dimension ROI ¼ 150mm, average age is 54 years old, and mean of weight ¼ 86 kg. A contouring and watershed segmentation algorithm for a sample of 63 Cine Fiesta MRI sequences for short-axis cuts with Matlab and its in-box toolbox complements was implemented. For a healthy patient 13.4% tolerance rate for the estimation of the stroke fraction, 6.4% for a patient with genetic disease, 8.7% error rate for a patient with heart failure symptom. The results show that the regurgitation fraction by the contour approach for a patient case with symptom of the presence of a genetic disease is 0.0335% for an aortic valve, 0.248% for a mitral valve, an error rate 0.16% for estimating this parameter for the aortic orifice with the watershed segmentation approach. In return, for a patient with suspected heart failure (stenosis or regurgitation) the regurgitation fraction is estimated by 0% for aortic valve, 1.49 e þ 03 % for a mitral valve, an error rate 11.76% compared to the watershed segmentation approach. The results are validated clinically. The Optimization of the topographic watershed approach with mutual information was simulated for the extraction of measurements (ejection fraction, regurgitation rate) within the left ventricle for three patient types (healthy, genetic pathology and heart failure). The results are considered interesting compared to the clinical assessment.

Section: Approach For Cardiac Imaging Dimension Conditions Of Acquisimentioning

confidence: 99%

Evaluation of the active contour and topographic watershed segmentation “assessment of the systolic ejection fraction in the left ventricular for medical assistance in 5D short axis cine MRI”

Saïd²,

2020

Heliyon

Self Cite

“…Our concept of 5D cardiac imaging is dissimilar, based on the reconstruction and the registration approach of cine-MRI sequences (Sakly et al 2019). The 5D modeling is composed of 3D (x, y, z) images combined with the criteria of time (t r ) and the blood flow dimension as function of time (f(t f )).…”

Section: Related Workmentioning

confidence: 99%

“…Sopra et al propose to develop an electrocardiogram (ECG)-gated, motion-resolved 5D compressed sensing whole-heart sparse MRI methodology into an automated, optimized, and fully self-gated free-running framework in which external gating or triggering devices are no longer needed. In our recent book (Sakly et al 2020a) and some of our research work (Sakly et al 2019(Sakly et al , 2020b, the 5D approach for medical decision-making in cardiac imaging with MRI was once depicted. The main contribution is to develop a 5D model, which relies upon on five dimensions: anatomical shape of the coronary heart in 3D, temporal dimensions as properly as a useful dimension of blood flow for the prognosis of stenosis and valvular leakage.…”

Section: Introductionmentioning

confidence: 99%

Reconstruction of 5D cardiac MRI through the blood flow registration: simulation of the fifth dimension and assessment of the left ventricular ejection fraction

Saïd²,

Netw Model Anal Health Inform Bioinforma

2020

Self Cite

In this paper, a medical decision approach for cardiac MRI by the registration algorithm and the reconstruction of 5D stacks for cine MRI sequences was developed. The estimation of the ejection fraction of the left ventricle (LVFE) was developed as an example. This study included 18 patients who underwent 1.5 T cardiac MRI for different etiologies: a total of 395 series and 18,483 scans was tested. The estimated values with the classical method of segmentation by contour with extreme (LVFE) in the sample was compared. A registration algorithm was implemented, with mean elapsed time registration = 0.5 s. The range of (LVFE) varied between [20 and 87%] shows that the results are satisfactory for the experts by comparing with the clinical assessment for the study of the anomalies of myocardial contractility and kinetic abnormalities and the error rate was significantly reduced. At baseline, the correlation between the clinical assessment of the LVFE with the 5D approach was consistent with 0.92, and with a 1.39% error rate mean for the sample studied, a mean = 60.34, the probability = 0.46 and the standard deviation was estimated to be 20.33 and about 21.78 for the LVFE with the 5D approach. Therefore, the 5D stacks approach applied to cine-cardiac MRI sequences for medical decision-making was implemented in the left ventricle with cardiac MRI. This approach shows its effectiveness in improving the accuracy of computation of LVFE. This approach seems to be very interesting, but needs to be validated in a larger sample study.

“…As demonstrated in Table 1, the complexity of their characterization is reflected in the diversity of the fifth dimension. In this study, we developed the concept and modeling of the 5D cardiac system (3D model + temporal dimension functional dimension of the flow) detailed in our research work mentioned in [13,14]. This strategy consists of reconstructing a 3D geometry of the descending aorta and diffusing a 2D viscous laminar fluid to detect the zones of narrowing.…”

Section: Introductionmentioning

confidence: 99%

Medical Decision Making for Cardiac MRI with CFD “Detection of Severe Stenosis Using a 5D Model of the Descending Aorta”

Saïd²,

2021

BioMedInformatics

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The aim of this study is to develop a reliable 5D (x, y, z, time, flow dimension) model for medical decision making. Sophisticated techniques for the assessment of serious stenosis were developed using time-dependent instantaneous pressure gradients through the aorta (flow rate, Reynolds number, velocity, etc.). A 74 cardiac MRI scan and 3057 scans were performed on a 10-year-old patient with congenital valve and valvular aortic stenosis on sensitive MRI and coarctation (operated and then dilated) in the sense of shone syndrome. The occlusion rate was estimated to be 80.5%. The stenosis area was approximately 15 mm long and 10 mm high. The fluid solver (NS) exhibited a significant shear stress of −3.735 × 10−5 Pa within the first 10 iterations. There was a significant drop in the flux mass of −0.0050 (kg/s), as well as high blood turbulence in vortex field lines and low geometry Reynolds cells. The fifth dimension was used for negative velocity prediction (−81.4 cm/s). The discoveries of the 5D aortic simulation are convincing based on the evaluation of its physical and biomedical features.