ROBERTO NERY DANTAS JUNIOR
Projetos de Pesquisa
Unidades Organizacionais
LIM/65, Hospital das Clínicas, Faculdade de Medicina
4 resultados
Resultados de Busca
Agora exibindo 1 - 4 de 4
- Siamese pyramidal deep learning network for strain estimation in 3D cardiac cine-MR(2023) GRAVES, Catharine V.; REBELO, Marina F. S.; MORENO, Ramon A.; DANTAS-JR, Roberto N.; JR, Antonildes N. Assuncao; NOMURA, Cesar H.; GUTIERREZ, Marco A.Strain represents the quantification of regional tissue deformation within a given area. Myocardial strain has demonstrated considerable utility as an indicator for the assessment of cardiac function. Notably, it exhibits greater sensitivity in detecting subtle myocardial abnormalities compared to conventional cardiac function indices, like left ventricle ejection fraction (LVEF). Nonetheless, the estimation of strain poses considerable challenges due to the necessity for precise tracking of myocardial motion throughout the complete cardiac cycle. This study introduces a novel deep learning-based pipeline, designed to automatically and accurately estimate myocardial strain from three-dimensional (3D) cine-MR images. Consequently, our investigation presents a comprehensive pipeline for the precise quantification of local and global myocardial strain. This pipeline incorporates a supervised Convolutional Neural Network (CNN) for accurate segmentation of the cardiac muscle and an unsupervised CNN for robust left ventricle motion tracking, enabling the estimation of strain in both artificial phantoms and real cine-MR images. Our investigation involved a comprehensive comparison of our findings with those obtained from two commonly utilized commercial software in this field. This analysis encompassed the examination of both intra- and inter-user variability. The proposed pipeline exhibited demonstrable reliability and reduced divergence levels when compared to alternative systems. Additionally, our approach is entirely independent of previous user data, effectively eliminating any potential user bias that could influence the strain analyses.
- Myocardial T1 mapping and extracellular volume quantification in patients with left ventricular non-compaction cardiomyopathy(2018) ARAUJO-FILHO, Jose A. B.; ASSUNCAO JR., Antonildes N.; MELO, Marcelo D. Tavares de; BIERE, Loic; LIMA, Camila R.; DANTAS JR., Roberto N.; NOMURA, Cesar H.; SALEMI, Vera M. C.; JEROSCH-HEROLD, Michael; PARGA, Jose R.Aims From pathophysiological mechanisms to risk stratification and management, much debate and discussion persist regarding left ventricular non-compaction cardiomyopathy (LVNC). This study aimed to characterize myocardial T1 mapping and extracellular volume (ECV) fraction by cardiovascular magnetic resonance (CMR), and investigate how these biomarkers relate to left ventricular ejection fraction (LVEF) and ventricular arrhythmias (VA) in LVNC. Methods and results Patients with LVNC (n = 36) and healthy controls (n = 18) were enrolled to perform a CMR with T1 mapping. ECV was quantified in LV segments without late gadolinium enhancement (LGE) areas to investigate diffuse myocardial fibrosis. Patients with LVNC had slightly higher native T1 (1024 +/- 43ms vs. 995 +/- 22 ms, P = 0.01) and substantially expanded ECV (28.0 +/- 4.5% vs. 23.5 +/- 2.2%, P < 0.001) compared to controls. The ECV was independently associated with LVEF (beta = -1.3, P = 0.001). Among patients without LGE, VAs were associated with higher ECV (27.7% with VA vs. 25.8% without VA, P = 0.002). Conclusion In LVNC, tissue characterization by T1 mapping suggests an extracellular expansion by diffuse fibrosis in myocardium without LGE, which was associated with myocardial dysfunction and VA, but not with the amount of noncompacted myocardium.
- A combined deep-learning approach to fully automatic left ventricle segmentation in cardiac magnetic resonance imaging(2019) MORENO, Ramon A.; REBELO, Marina F. S. de Sa; CARVALHO, Talles; ASSUNCAO-JR, Antonildes N.; JR, Roberto N. Dantas; VAL, Renata do; MARIN, Angela S.; BORDIGNOM, Adriano; NOMURA, Cesar H.; GUTIERREZ, Marco A.In clinical practice, cardiac magnetic resonance imaging (CMR) is considered the gold-standard imaging modality for the evaluation of function and structure of the left ventricle (LV). However, the quantification of LV parameters in all frames, even when performed by experienced radiologists, is very time consuming mainly due to the inhomogeneity of cardiac structures within each image, the variability of the cardiac structures across subjects and the complicated global/regional temporal deformation of the myocardium during the cardiac cycle. In this work, we employed a combination of two convolutional neural networks (CNN) to develop a fully automatic LV segmentation method for Short Axis CMR datasets. The first CNN defines the region of interest (ROI) of the cardiac chambers based on You Only Look Once (YOLO) network. The output of YOLO net is used to filter the image and feed the second CNN, based on U-Net network, which segments the myocardium and the blood pool. The method was validated in CMR exams of 59 individuals from an institutional clinical protocol. Segmentation results, evaluated by metrics Percentage of Good Contours, Dice Index and Average Perpendicular distance, were 98,59% +/- 4,28%, 0,93 +/- 0,06 and 0,72 mm +/- 0,62 mm, respectively, for the LV epicardium, and 94,98% +/- 14,04%, 0,86 +/- 0,13 and 1,19 mm +/- 1,29 mm, respectively, for the LV endocardium. The combination of two CNNs demonstrated good performance in terms of the evaluated metrics when compared to literature results.
- Association between perivascular inflammation and downstream myocardial perfusion in patients with suspected coronary artery disease(2020) NOMURA, Cesar H.; ASSUNCAO-JR, Antonildes N.; GUIMARAES, Patricia O.; LIBERATO, Gabriela; MORAIS, Thamara C.; FAHEL, Mateus G.; GIORGI, Maria C. P.; MENEGHETTI, Jose C.; PARGA, Jose R.; DANTAS-JR, Roberto N.; CERRI, Giovanni G.Aims To investigate the association between pericoronary adipose tissue (PCAT) computed tomography (CT) attenuation derived from coronary computed tomography angiography (CTA) and coronary flow reserve (CFR) by positron emission tomography (PET) in patients with suspected coronary artery disease (CAD). Methods and results PCAT CT attenuation was measured in proximal segments of all major epicardial coronary vessels of 105 patients with suspected CAD. We evaluated the relationship between PCAT CT attenuation and other quantitative/qualitative CT-derived anatomic parameters with CFR by PET. Overall, the mean age was 60 +/- 12 years and 93% had intermediate pre-test probability of obstructive CAD. Obstructive CAD (>= 50% stenosis) was detected in 37 (35.2%) patients and impaired CFR (<2.0) in 32 (30.5%) patients. On a per-vessel analysis (315 vessels), obstructive CAD, non-calcified plaque volume, and PCAT CT attenuation were independently associated with CFR. In patients with coronary calcium score (CCS) <100, those with high-PCAT CT attenuation presented significantly lower CFR values than those with low-PCAT CT attenuation (2.47 +/- 0.95 vs. 3.13 +/- 0.89, P = 0.003). Among those without obstructive CAD, CFR was significantly lower in patients with high-PCAT CT attenuation (2.51 +/- 0.95 vs. 3.02 +/- 0.84, P = 0.021). Conclusion Coronary perivascular inflammation by CTA was independently associated with downstream myocardial perfusion by PET. In patients with low CCS or without obstructive CAD, CFR was lower in the presence of higher perivascular inflammation. PCAT CT attenuation might help identifying myocardial ischaemia particularly among patients who are traditionally considered non-high risk for future cardiovascular events.