Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 66
Filtrar
1.
Med Image Anal ; 79: 102428, 2022 07.
Artigo em Inglês | MEDLINE | ID: mdl-35500498

RESUMO

A key factor for assessing the state of the heart after myocardial infarction (MI) is to measure whether the myocardium segment is viable after reperfusion or revascularization therapy. Delayed enhancement-MRI or DE-MRI, which is performed 10 min after injection of the contrast agent, provides high contrast between viable and nonviable myocardium and is therefore a method of choice to evaluate the extent of MI. To automatically assess myocardial status, the results of the EMIDEC challenge that focused on this task are presented in this paper. The challenge's main objectives were twofold. First, to evaluate if deep learning methods can distinguish between non-infarct and pathological exams, i.e. exams with or without hyperenhanced area. Second, to automatically calculate the extent of myocardial infarction. The publicly available database consists of 150 exams divided into 50 cases without any hyperenhanced area after injection of a contrast agent and 100 cases with myocardial infarction (and then with a hyperenhanced area on DE-MRI), whatever their inclusion in the cardiac emergency department. Along with MRI, clinical characteristics are also provided. The obtained results issued from several works show that the automatic classification of an exam is a reachable task (the best method providing an accuracy of 0.92), and the automatic segmentation of the myocardium is possible. However, the segmentation of the diseased area needs to be improved, mainly due to the small size of these areas and the lack of contrast with the surrounding structures.


Assuntos
Aprendizado Profundo , Infarto do Miocárdio , Meios de Contraste , Humanos , Imageamento por Ressonância Magnética/métodos , Infarto do Miocárdio/diagnóstico por imagem , Miocárdio/patologia
2.
Front Artif Intell ; 5: 813842, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35586223

RESUMO

Sharing labeled data is crucial to acquire large datasets for various Deep Learning applications. In medical imaging, this is often not feasible due to privacy regulations. Whereas anonymization would be a solution, standard techniques have been shown to be partially reversible. Here, synthetic data using a Generative Adversarial Network (GAN) with differential privacy guarantees could be a solution to ensure the patient's privacy while maintaining the predictive properties of the data. In this study, we implemented a Wasserstein GAN (WGAN) with and without differential privacy guarantees to generate privacy-preserving labeled Time-of-Flight Magnetic Resonance Angiography (TOF-MRA) image patches for brain vessel segmentation. The synthesized image-label pairs were used to train a U-net which was evaluated in terms of the segmentation performance on real patient images from two different datasets. Additionally, the Fréchet Inception Distance (FID) was calculated between the generated images and the real images to assess their similarity. During the evaluation using the U-Net and the FID, we explored the effect of different levels of privacy which was represented by the parameter ϵ. With stricter privacy guarantees, the segmentation performance and the similarity to the real patient images in terms of FID decreased. Our best segmentation model, trained on synthetic and private data, achieved a Dice Similarity Coefficient (DSC) of 0.75 for ϵ = 7.4 compared to 0.84 for ϵ = ∞ in a brain vessel segmentation paradigm (DSC of 0.69 and 0.88 on the second test set, respectively). We identified a threshold of ϵ <5 for which the performance (DSC <0.61) became unstable and not usable. Our synthesized labeled TOF-MRA images with strict privacy guarantees retained predictive properties necessary for segmenting the brain vessels. Although further research is warranted regarding generalizability to other imaging modalities and performance improvement, our results mark an encouraging first step for privacy-preserving data sharing in medical imaging.

3.
J Card Surg ; 2022 May 24.
Artigo em Inglês | MEDLINE | ID: mdl-35610730

RESUMO

Improvementsin medical imaging and a steady increase in computing power are leading to new possibilities in the field of cardiovascular interventions. Interventions can be planned in advance in greater detail, even to the point of simulating procedures. Nevertheless, all techniques are at an early stage of development. It is of utmost importance that tools, especially if they can be used as decision support are intensively validated and their accuracy is demonstrated. In our commentary, we summarize current techniques for impprovements in planning and guiding of procedures, but also critically discuss the downsides of these techniques. Following the work of Kenichi and colleagues, we also discuss necessary steps in advancing new tools and techniques, particularly as they are used in routine clinical practice. We also discuss the role of artificial intelligence, which could play a crucial role in this context in the future.

4.
Front Cardiovasc Med ; 9: 829512, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35360025

RESUMO

The quality and acceptance of machine learning (ML) approaches in cardiovascular data interpretation depends strongly on model design and training and the interaction with the clinical experts. We hypothesize that a software infrastructure for the training and application of ML models can support the improvement of the model training and provide relevant information for understanding the classification-relevant data features. The presented solution supports an iterative training, evaluation, and exploration of machine-learning-based multimodal data interpretation methods considering cardiac MRI data. Correction, annotation, and exploration of clinical data and interpretation of results are supported through dedicated interactive visual analytics tools. We test the presented concept with two use cases from the ACDC and EMIDEC cardiac MRI image analysis challenges. In both applications, pre-trained 2D U-Nets are used for segmentation, and classifiers are trained for diagnostic tasks using radiomics features of the segmented anatomical structures. The solution was successfully used to identify outliers in automatic segmentation and image acquisition. The targeted curation and addition of expert annotations improved the performance of the machine learning models. Clinical experts were supported in understanding specific anatomical and functional characteristics of the assigned disease classes.

5.
Med Image Anal ; 78: 102396, 2022 05.
Artigo em Inglês | MEDLINE | ID: mdl-35231850

RESUMO

Deep learning requires large labeled datasets that are difficult to gather in medical imaging due to data privacy issues and time-consuming manual labeling. Generative Adversarial Networks (GANs) can alleviate these challenges enabling synthesis of shareable data. While 2D GANs have been used to generate 2D images with their corresponding labels, they cannot capture the volumetric information of 3D medical imaging. 3D GANs are more suitable for this and have been used to generate 3D volumes but not their corresponding labels. One reason might be that synthesizing 3D volumes is challenging owing to computational limitations. In this work, we present 3D GANs for the generation of 3D medical image volumes with corresponding labels applying mixed precision to alleviate computational constraints. We generated 3D Time-of-Flight Magnetic Resonance Angiography (TOF-MRA) patches with their corresponding brain blood vessel segmentation labels. We used four variants of 3D Wasserstein GAN (WGAN) with: 1) gradient penalty (GP), 2) GP with spectral normalization (SN), 3) SN with mixed precision (SN-MP), and 4) SN-MP with double filters per layer (c-SN-MP). The generated patches were quantitatively evaluated using the Fréchet Inception Distance (FID) and Precision and Recall of Distributions (PRD). Further, 3D U-Nets were trained with patch-label pairs from different WGAN models and their performance was compared to the performance of a benchmark U-Net trained on real data. The segmentation performance of all U-Net models was assessed using Dice Similarity Coefficient (DSC) and balanced Average Hausdorff Distance (bAVD) for a) all vessels, and b) intracranial vessels only. Our results show that patches generated with WGAN models using mixed precision (SN-MP and c-SN-MP) yielded the lowest FID scores and the best PRD curves. Among the 3D U-Nets trained with synthetic patch-label pairs, c-SN-MP pairs achieved the highest DSC (0.841) and lowest bAVD (0.508) compared to the benchmark U-Net trained on real data (DSC 0.901; bAVD 0.294) for intracranial vessels. In conclusion, our solution generates realistic 3D TOF-MRA patches and labels for brain vessel segmentation. We demonstrate the benefit of using mixed precision for computational efficiency resulting in the best-performing GAN-architecture. Our work paves the way towards sharing of labeled 3D medical data which would increase generalizability of deep learning models for clinical use.


Assuntos
Processamento de Imagem Assistida por Computador , Angiografia por Ressonância Magnética , Humanos , Processamento de Imagem Assistida por Computador/métodos , Imageamento Tridimensional
6.
Sci Rep ; 12(1): 2001, 2022 02 07.
Artigo em Inglês | MEDLINE | ID: mdl-35132102

RESUMO

Magnetic resonance elastography (MRE) for measuring viscoelasticity heavily depends on proper tissue segmentation, especially in heterogeneous organs such as the prostate. Using trained network-based image segmentation, we investigated if MRE data suffice to extract anatomical and viscoelastic information for automatic tabulation of zonal mechanical properties of the prostate. Overall, 40 patients with benign prostatic hyperplasia (BPH) or prostate cancer (PCa) were examined with three magnetic resonance imaging (MRI) sequences: T2-weighted MRI (T2w), diffusion-weighted imaging (DWI), and MRE-based tomoelastography, yielding six independent sets of imaging data per patient (T2w, DWI, apparent diffusion coefficient, MRE magnitude, shear wave speed, and loss angle maps). Combinations of these data were used to train Dense U-nets with manually segmented masks of the entire prostate gland (PG), central zone (CZ), and peripheral zone (PZ) in 30 patients and to validate them in 10 patients. Dice score (DS), sensitivity, specificity, and Hausdorff distance were determined. We found that segmentation based on MRE magnitude maps alone (DS, PG: 0.93 ± 0.04, CZ: 0.95 ± 0.03, PZ: 0.77 ± 0.05) was more accurate than magnitude maps combined with T2w and DWI_b (DS, PG: 0.91 ± 0.04, CZ: 0.91 ± 0.06, PZ: 0.63 ± 0.16) or T2w alone (DS, PG: 0.92 ± 0.03, CZ: 0.91 ± 0.04, PZ: 0.65 ± 0.08). Automatically tabulated MRE values were not different from ground-truth values (P>0.05). In conclusion, MRE combined with Dense U-net segmentation allows tabulation of quantitative imaging markers without manual analysis and independent of other MRI sequences and can thus contribute to PCa detection and classification.


Assuntos
Técnicas de Imagem por Elasticidade/métodos , Elasticidade , Próstata/diagnóstico por imagem , Próstata/fisiopatologia , Viscosidade , Imagem de Difusão por Ressonância Magnética/métodos , Imagem de Tensor de Difusão/métodos , Humanos , Masculino , Hiperplasia Prostática/diagnóstico por imagem , Hiperplasia Prostática/fisiopatologia , Neoplasias da Próstata/diagnóstico por imagem , Neoplasias da Próstata/fisiopatologia , Sensibilidade e Especificidade
7.
Med Image Anal ; 77: 102333, 2022 04.
Artigo em Inglês | MEDLINE | ID: mdl-34998111

RESUMO

The Cerebral Aneurysm Detection and Analysis (CADA) challenge was organized to support the development and benchmarking of algorithms for detecting, analyzing, and risk assessment of cerebral aneurysms in X-ray rotational angiography (3DRA) images. 109 anonymized 3DRA datasets were provided for training, and 22 additional datasets were used to test the algorithmic solutions. Cerebral aneurysm detection was assessed using the F2 score based on recall and precision, and the fit of the delivered bounding box was assessed using the distance to the aneurysm. The segmentation quality was measured using the Jaccard index and a combination of different surface distance measures. Systematic errors were analyzed using volume correlation and bias. Rupture risk assessment was evaluated using the F2 score. 158 participants from 22 countries registered for the CADA challenge. The U-Net-based detection solutions presented by the community show similar accuracy compared to experts (F2 score 0.92), with a small number of missed aneurysms with diameters smaller than 3.5 mm. In addition, the delineation of these structures, based on U-Net variations, is excellent, with a Jaccard score of 0.92. The rupture risk estimation methods achieved an F2 score of 0.71. The performance of the detection and segmentation solutions is equivalent to that of human experts. The best results are obtained in rupture risk estimation by combining different image-based, morphological, and computational fluid dynamic parameters using machine learning methods. Furthermore, we evaluated the best methods pipeline, from detecting and delineating the vessel dilations to estimating the risk of rupture. The chain of these methods achieves an F2-score of 0.70, which is comparable to applying the risk prediction to the ground-truth delineation (0.71).


Assuntos
Aneurisma Intracraniano , Algoritmos , Angiografia Cerebral/métodos , Humanos , Imageamento Tridimensional/métodos , Aneurisma Intracraniano/diagnóstico por imagem , Raios X
8.
Int J Comput Assist Radiol Surg ; 17(3): 507-519, 2022 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-35066774

RESUMO

PURPOSE: Careful assessment of the aortic root is paramount to select an appropriate prosthesis for transcatheter aortic valve implantation (TAVI). Relevant information about the aortic root anatomy, such as the aortic annulus diameter, can be extracted from pre-interventional CT. In this work, we investigate a neural network-based approach for segmenting the aortic root as a basis for obtaining these parameters. METHODS: To support valve prosthesis selection, geometric measures of the aortic root are extracted from the patient's CT scan using a cascade of convolutional neural networks (CNNs). First, the image is reduced to the aortic root, valve, and left ventricular outflow tract (LVOT); within that subimage, the aortic valve and ascending aorta are segmented; and finally, the region around the aortic annulus. From the segmented annulus region, we infer the annulus orientation using principal component analysis (PCA). The area-derived diameter of the annulus is approximated based on the segmentation of the aortic root and LVOT and the plane orientation resulting from the PCA. RESULTS: The cascade of CNNs was trained using 90 expert-annotated contrast-enhanced CT scans routinely acquired for TAVI planning. Segmentation of the aorta and valve within the region of interest achieved an F1 score of 0.94 on the test set of 36 patients. The area-derived diameter within the annulus region was determined with a mean error below 2 mm between the automatic measurement and the diameter derived from annotations. The calculated diameters and resulting errors are comparable to published results of alternative approaches. CONCLUSIONS: The cascaded neural network approach enabled the assessment of the aortic root with a relatively small training set. The processing time amounts to 30 s per patient, facilitating time-efficient, reproducible measurements. An extended training data set, including different levels of calcification or special cases (e.g., pre-implanted valves), could further improve this method's applicability and robustness.


Assuntos
Estenose da Valva Aórtica , Implante de Prótese de Valva Cardíaca , Próteses Valvulares Cardíacas , Substituição da Valva Aórtica Transcateter , Aorta , Valva Aórtica/diagnóstico por imagem , Valva Aórtica/cirurgia , Estenose da Valva Aórtica/diagnóstico por imagem , Estenose da Valva Aórtica/cirurgia , Cateterismo Cardíaco/métodos , Implante de Prótese de Valva Cardíaca/métodos , Humanos , Redes Neurais de Computação , Tomografia Computadorizada por Raios X/métodos , Substituição da Valva Aórtica Transcateter/métodos
9.
J Thorac Imaging ; 37(1): 42-48, 2022 Jan 01.
Artigo em Inglês | MEDLINE | ID: mdl-33492047

RESUMO

BACKGROUND: Aortic stiffness is associated with a higher incidence of cardiovascular events including stroke. The primary aim of this study was to evaluate whether increased pulse wave velocity (PWV), a marker of stiffness, is an independent predictor of aortic atheroma. The secondary aim was to test whether increased PWV reinforces retrograde blood flow from the descending aorta (DAo), a mechanism of stroke. METHODS: We performed a cross-sectional case-control study with prospective data acquisition. In all, 40 stroke and 60 ophthalmic patients matched for age and cardiovascular risk factors were included. Multicontrast magnetic resonance imaging (MRI) protocol of the aorta tailored to allow a detailed plaque analysis using 3-dimensional (D) T1-weighted bright blood, T2-weighted and proton density-weighted black blood, and hemodynamic assessment using 4D flow MRI was applied. Individual PWV was calculated based on 4D flow MRI data using the time-to-foot of the blood flow waveform. The extent of maximum retrograde blood flow from the proximal DAo into the arch was quantified. RESULTS: PWV was higher in stroke patients compared with controls (7.62±2.59 vs. 5.96±2.49 m/s; P=0.005) and in patients with plaques (irrespective of thickness) compared with patients without plaques (7.47±2.89 vs. 5.62±1.89 m/s; P=0.002). Increased PWV was an independent predictor of plaque prevalence and contributed significantly to a predictor model explaining 36.5% (Nagelkerke R2) of the variance in plaque presence. Maximum retrograde flow extent from the proximal DAo was not correlated with PWV. CONCLUSIONS: Aortic stiffness was higher in stroke patients and associated with a higher prevalence of plaques. Increased PWV was an independent predictor of plaque presence. Accordingly, regional PWV seems to be a valuable biomarker for the assessment and management of aortic atherosclerosis. However, no association was found for increased retrograde flow extent from the DAo.


Assuntos
Aterosclerose , Acidente Vascular Cerebral , Aorta/diagnóstico por imagem , Aorta Torácica/diagnóstico por imagem , Aterosclerose/diagnóstico por imagem , Velocidade do Fluxo Sanguíneo , Estudos de Casos e Controles , Estudos Transversais , Hemodinâmica , Humanos , Imageamento por Ressonância Magnética , Estudos Prospectivos , Análise de Onda de Pulso , Acidente Vascular Cerebral/diagnóstico por imagem
10.
Circulation ; 144(24): 1926-1939, 2021 12 14.
Artigo em Inglês | MEDLINE | ID: mdl-34762513

RESUMO

BACKGROUND: Many heart diseases can result in reduced pumping capacity of the heart muscle. A mismatch between ATP demand and ATP production of cardiomyocytes is one of the possible causes. Assessment of the relation between myocardial ATP production (MVATP) and cardiac workload is important for better understanding disease development and choice of nutritional or pharmacologic treatment strategies. Because there is no method for measuring MVATP in vivo, the use of physiology-based metabolic models in conjunction with protein abundance data is an attractive approach. METHOD: We developed a comprehensive kinetic model of cardiac energy metabolism (CARDIOKIN1) that recapitulates numerous experimental findings on cardiac metabolism obtained with isolated cardiomyocytes, perfused animal hearts, and in vivo studies with humans. We used the model to assess the energy status of the left ventricle of healthy participants and patients with aortic stenosis and mitral valve insufficiency. Maximal enzyme activities were individually scaled by means of protein abundances in left ventricle tissue samples. The energy status of the left ventricle was quantified by the ATP consumption at rest (MVATP[rest]), at maximal workload (MVATP[max]), and by the myocardial ATP production reserve, representing the span between MVATP(rest) and MVATP(max). RESULTS: Compared with controls, in both groups of patients, MVATP(rest) was increased and MVATP(max) was decreased, resulting in a decreased myocardial ATP production reserve, although all patients had preserved ejection fraction. The variance of the energetic status was high, ranging from decreased to normal values. In both patient groups, the energetic status was tightly associated with mechanic energy demand. A decrease of MVATP(max) was associated with a decrease of the cardiac output, indicating that cardiac functionality and energetic performance of the ventricle are closely coupled. CONCLUSIONS: Our analysis suggests that the ATP-producing capacity of the left ventricle of patients with valvular dysfunction is generally diminished and correlates positively with mechanical energy demand and cardiac output. However, large differences exist in the energetic state of the myocardium even in patients with similar clinical or image-based markers of hypertrophy and pump function. Registration: URL: https://www.clinicaltrials.gov; Unique identifiers: NCT03172338 and NCT04068740.


Assuntos
Trifosfato de Adenosina/metabolismo , Doenças das Valvas Cardíacas/metabolismo , Ventrículos do Coração/metabolismo , Modelos Cardiovasculares , Miocárdio/metabolismo , Miócitos Cardíacos/metabolismo , Idoso , Feminino , Humanos , Masculino , Pessoa de Meia-Idade
11.
Front Cardiovasc Med ; 8: 723860, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34765650

RESUMO

Introduction: Carotid geometry and wall shear stress (WSS) have been proposed as independent risk factors for the progression of carotid atherosclerosis, but this has not yet been demonstrated in larger longitudinal studies. Therefore, we investigated the impact of these biomarkers on carotid wall thickness in patients with high cardiovascular risk. Methods: Ninety-seven consecutive patients with hypertension, at least one additional cardiovascular risk factor and internal carotid artery (ICA) plaques (wall thickness ≥ 1.5 mm and degree of stenosis ≤ 50%) were prospectively included. They underwent high-resolution 3D multi-contrast and 4D flow MRI at 3 Tesla both at baseline and follow-up. Geometry (ICA/common carotid artery (CCA)-diameter ratio, bifurcation angle, tortuosity and wall thickness) and hemodynamics [WSS, oscillatory shear index (OSI)] of both carotid bifurcations were measured at baseline. Their predictive value for changes of wall thickness 12 months later was calculated using linear regression analysis for the entire study cohort (group 1, 97 patients) and after excluding patients with ICA stenosis ≥10% to rule out relevant inward remodeling (group 2, 61 patients). Results: In group 1, only tortuosity at baseline was independently associated with carotid wall thickness at follow-up (regression coefficient = -0.52, p < 0.001). However, after excluding patients with ICA stenosis ≥10% in group 2, both ICA/CCA-ratio (0.49, p < 0.001), bifurcation angle (0.04, p = 0.001), tortuosity (-0.30, p = 0.040), and WSS (-0.03, p = 0.010) at baseline were independently associated with changes of carotid wall thickness at follow-up. Conclusions: A large ICA bulb and bifurcation angle and low WSS seem to be independent risk factors for the progression of carotid atherosclerosis in the absence of ICA stenosis. By contrast, a high carotid tortuosity seems to be protective both in patients without and with ICA stenosis. These biomarkers may be helpful for the identification of patients who are at particular risk of wall thickness progression and who may benefit from intensified monitoring and treatment.

12.
Comput Biol Med ; 131: 104254, 2021 04.
Artigo em Inglês | MEDLINE | ID: mdl-33618105

RESUMO

Anonymization and data sharing are crucial for privacy protection and acquisition of large datasets for medical image analysis. This is a big challenge, especially for neuroimaging. Here, the brain's unique structure allows for re-identification and thus requires non-conventional anonymization. Generative adversarial networks (GANs) have the potential to provide anonymous images while preserving predictive properties. Analyzing brain vessel segmentation, we trained 3 GANs on time-of-flight (TOF) magnetic resonance angiography (MRA) patches for image-label generation: 1) Deep convolutional GAN, 2) Wasserstein-GAN with gradient penalty (WGAN-GP) and 3) WGAN-GP with spectral normalization (WGAN-GP-SN). The generated image-labels from each GAN were used to train a U-net for segmentation and tested on real data. Moreover, we applied our synthetic patches using transfer learning on a second dataset. For an increasing number of up to 15 patients we evaluated the model performance on real data with and without pre-training. The performance for all models was assessed by the Dice Similarity Coefficient (DSC) and the 95th percentile of the Hausdorff Distance (95HD). Comparing the 3 GANs, the U-net trained on synthetic data generated by the WGAN-GP-SN showed the highest performance to predict vessels (DSC/95HD 0.85/30.00) benchmarked by the U-net trained on real data (0.89/26.57). The transfer learning approach showed superior performance for the same GAN compared to no pre-training, especially for one patient only (0.91/24.66 vs. 0.84/27.36). In this work, synthetic image-label pairs retained generalizable information and showed good performance for vessel segmentation. Besides, we showed that synthetic patches can be used in a transfer learning approach with independent data. This paves the way to overcome the challenges of scarce data and anonymization in medical imaging.


Assuntos
Sistema Cardiovascular , Angiografia por Ressonância Magnética , Encéfalo/diagnóstico por imagem , Humanos , Processamento de Imagem Assistida por Computador
13.
Circ Cardiovasc Imaging ; 14(2): e011523, 2021 02.
Artigo em Inglês | MEDLINE | ID: mdl-33591212

RESUMO

BACKGROUND: Pharmacological stress testing can help to uncover pathological hemodynamic conditions and is, therefore, used in the clinical routine to assess patients with structural heart diseases such as aortic coarctation with borderline indication for treatment. The aim of this study was to develop and test a reduced-order model predicting dobutamine stress induced pressure gradients across the coarctation. METHODS: The reduced-order model was developed based on n=21 imaging data sets of patients with aortic coarctation and a meta-analysis of subjects undergoing dobutamine stress testing. Within an independent test cohort of n=21 patients with aortic coarctation, the results of the model were compared with dobutamine stress testing during catheterization. RESULTS: In n=19 patients responding to dobutamine stress testing, pressure gradients across the coarctation during dobutamine stress increased from 15.7±5.1 to 33.6±10.3 mm Hg (paired t test, P<0.001). The model-predicted pressure gradients agreed with catheter measurements with a mean difference of -2.2 mm Hg and a limit of agreement of ±11.16 mm Hg according to Bland-Altman analysis. Significant equivalence between catheter-measured and simulated pressure gradients during stress was found within the study cohort (two 1-sided tests of equivalence with a noninferiority margin of 5.0 mm Hg, 33.6±10.33 versus 31.5±11.15 mm Hg, P=0.021). CONCLUSIONS: The developed reduced-order model can instantly predict dobutamine-induced hemodynamic changes with accuracy equivalent to heart catheterization in patients with aortic coarctation. The method is easy to use, available as a web-based calculator, and provides a promising alternative to conventional stress testing in the clinical routine. Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT02591940.


Assuntos
Coartação Aórtica/diagnóstico , Cateterismo Cardíaco/métodos , Dobutamina/farmacologia , Teste de Esforço/métodos , Hemodinâmica/fisiologia , Adolescente , Adulto , Coartação Aórtica/fisiopatologia , Cardiotônicos/farmacologia , Criança , Feminino , Humanos , Masculino , Estudos Prospectivos , Adulto Jovem
14.
Int J Comput Assist Radiol Surg ; 16(1): 125-132, 2021 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-33098536

RESUMO

PURPOSE: Decision support systems for mitral valve disease are an important step toward personalized surgery planning. A simulation of the mitral valve apparatus is required for decision support. Building a model of the chordae tendineae is an essential component of a mitral valve simulation. Due to image quality and artifacts, the chordae tendineae cannot be reliably detected in medical imaging. METHODS: Using the position-based dynamics framework, we are able to realistically simulate the opening and closing of the mitral valve. Here, we present a heuristic method for building an initial chordae model needed for a successful simulation. In addition to the heuristic, we present an interactive editor to refine the chordae model and to further improve pathology reproduction as well as geometric approximation of the closed valve. RESULTS: For evaluation, five mitral valves were reconstructed based on image sequences of patients scheduled for mitral valve surgery. We evaluated the approximation of the closed valves using either just the heuristic chordae model or a manually refined model. Using the manually refined models, prolapse was correctly reproduced in four of the five cases compared to two of the five cases when using the heuristic. In addition, using the editor improved the approximation in four cases. CONCLUSIONS: Our approach is suitable to create realistically parameterized mitral valve apparatus reconstructions for the simulation of normally and abnormally closing valves in a decision support system.


Assuntos
Cordas Tendinosas/cirurgia , Simulação por Computador , Insuficiência da Valva Mitral/cirurgia , Valva Mitral/cirurgia , Modelos Anatômicos , Cordas Tendinosas/patologia , Humanos , Valva Mitral/patologia , Insuficiência da Valva Mitral/patologia
15.
Sci Rep ; 10(1): 18894, 2020 11 03.
Artigo em Inglês | MEDLINE | ID: mdl-33144605

RESUMO

In patients with aortic coarctation it would be desirable to assess pressure gradients as well as information about blood flow profiles at rest and during exercise. We aimed to assess the hemodynamic responses to physical exercise by combining MRI-ergometry with computational fluid dynamics (CFD). MRI was performed on 20 patients with aortic coarctation (13 men, 7 women, mean age 21.5 ± 13.7 years) at rest and during ergometry. Peak systolic pressure gradients, wall shear stress (WSS), secondary flow degree (SFD) and normalized flow displacement (NFD) were calculated using CFD. Stroke volume was determined based on MRI. On average, the pressure gradient was 18.0 ± 16.6 mmHg at rest and increased to 28.5 ± 22.6 mmHg (p < 0.001) during exercise. A significant increase in cardiac index was observed (p < 0.001), which was mainly driven by an increase in heart rate (p < 0.001). WSS significantly increased during exercise (p = 0.006), whereas SFD and NFD remained unchanged. The combination of MRI-ergometry with CFD allows assessing pressure gradients as well as flow profiles during physical exercise. This concept has the potential to serve as an alternative to cardiac catheterization with pharmacological stress testing and provides hemodynamic information valuable for studying the pathophysiology of aortic coarctation.


Assuntos
Coartação Aórtica/fisiopatologia , Teste de Esforço/métodos , Adolescente , Adulto , Coartação Aórtica/diagnóstico por imagem , Velocidade do Fluxo Sanguíneo , Criança , Ergometria , Estudos de Viabilidade , Feminino , Frequência Cardíaca , Hemodinâmica , Humanos , Hidrodinâmica , Imageamento por Ressonância Magnética , Masculino , Estudos Prospectivos , Estresse Mecânico , Adulto Jovem
16.
J Cardiovasc Magn Reson ; 22(1): 67, 2020 09 10.
Artigo em Inglês | MEDLINE | ID: mdl-32912285

RESUMO

BACKGROUND: The posterior wall of the proximal internal carotid artery (ICA) is the predilection site for the development of stenosis. To optimally prevent stroke, identification of new risk factors for plaque progression is of high interest. Therefore, we studied the impact of carotid geometry and wall shear stress on cardiovascular magnetic resonance (CMR)-depicted wall thickness in the ICA of patients with high cardiovascular disease risk. METHODS: One hundred twenty-one consecutive patients ≥50 years with hypertension, ≥1 additional cardiovascular risk factor and ICA plaque ≥1.5 mm thickness and < 50% stenosis were prospectively included. High-resolution 3D-multi-contrast (time of flight, T1, T2, proton density) and 4D flow CMR were performed for the assessment of morphological (bifurcation angle, ICA/common carotid artery (CCA) diameter ratio, tortuosity, and wall thickness) and hemodynamic parameters (absolute/systolic wall shear stress (WSS), oscillatory shear index (OSI)) in 242 carotid bifurcations. RESULTS: We found lower absolute/systolic WSS, higher OSI and increased wall thickness in the posterior compared to the anterior wall of the ICA bulb (p < 0.001), whereas this correlation disappeared in ≥10% stenosis. Higher carotid tortuosity (regression coefficient = 0.764; p < 0.001) and lower ICA/CCA diameter ratio (regression coefficient = - 0.302; p < 0.001) were independent predictors of increased wall thickness even after adjustment for cardiovascular risk factors. This association was not found for bifurcation angle, WSS or OSI in multivariate regression analysis. CONCLUSIONS: High carotid tortuosity and low ICA diameter were independent predictors for wall thickness of the ICA bulb in this cross-sectional study, whereas this association was not present for WSS or OSI. Thus, consideration of geometric parameters of the carotid bifurcation could be helpful to identify patients at increased risk of carotid plaque generation. However, this association and the potential benefit of WSS measurement need to be further explored in a longitudinal study.


Assuntos
Doenças das Artérias Carótidas/diagnóstico por imagem , Artéria Carótida Interna/diagnóstico por imagem , Hemodinâmica , Angiografia por Ressonância Magnética , Idoso , Doenças das Artérias Carótidas/fisiopatologia , Artéria Carótida Interna/fisiopatologia , Estudos Transversais , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Placa Aterosclerótica , Valor Preditivo dos Testes , Prognóstico , Estudos Prospectivos , Fluxo Sanguíneo Regional , Fatores de Risco , Estresse Mecânico
17.
NPJ Digit Med ; 3: 92, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32665977

RESUMO

Wrist-worn devices with heart rate monitoring have become increasingly popular. Although current guidelines advise to consider clinical symptoms and exercise tolerance during decision-making in heart disease, it remains unknown to which extent wearables can help to determine such functional capacity measures. In clinical settings, the 6-minute walk test has become a standardized diagnostic and prognostic marker. We aimed to explore, whether 6-minute walk distances can be predicted by wrist-worn devices in patients with different stages of mitral and aortic valve disease. A total of n = 107 sensor datasets with 1,019,748 min of recordings were analysed. Based on heart rate recordings and literature information, activity levels were determined and compared to results from a 6-minute walk test. The percentage of time spent in moderate activity was a predictor for the achievement of gender, age and body mass index-specific 6-minute walk distances (p < 0.001; R 2 = 0.48). The uncertainty of these predictions is demonstrated.

18.
MAGMA ; 33(5): 613-626, 2020 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-32152793

RESUMO

OBJECTIVES: To investigate the potential value of adding a tagged three-chamber (3Ch) cine to clinical hypertrophic cardiomyopathy (HCM) magnetic resonance imaging (MRI) protocols, including to help distinguish HCM patients with regionally impaired cardiac function. METHODS: Forty-eight HCM patients, five patients with "septal knuckle" (SK), and 20 healthy volunteers underwent MRI at 1.5T; a tagged 3Ch cine was added to the protocol. Regional strain, myocardial wall thickness, and mitral valve leaflet lengths were measured in the 3Ch view. RESULTS: In HCM, we found a reduced tangential strain with decreased diastolic relaxation in both hypertrophied (p = 0.003) and remote segments (p = 0.035). Strain in the basal septum correlated with the length of the coaptation zone + residual leaflet (r = 0.48, p < 0.001). In the basal free wall, patients with SK had faster relaxation compared to HCM patients with septal hypertrophy. DISCUSSION: The 3Ch tagged MRI sequence provides useful information for the examination of suspected HCM patients, with minimal additional time cost. Local wall function is closely associated with morphological changes of the mitral apparatus measured in the same plane and may provide insights into mechanisms of obstruction. The additional strain information may be helpful when analyzing local myocardial wall motion patterns in the presence of SK.


Assuntos
Cardiomiopatia Hipertrófica , Imagem Cinética por Ressonância Magnética , Cardiomiopatia Hipertrófica/patologia , Feminino , Fibrose , Humanos , Imageamento por Ressonância Magnética , Miocárdio/patologia
19.
Comput Methods Programs Biomed ; 184: 105277, 2020 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-31891904

RESUMO

BACKGROUND AND OBJECTIVE: Cardiovascular imaging is an exponentially growing field with aspects ranging from image acquisition and analysis to disease characterization, and evaluation of therapy approaches.The transfer of innovative new technological and algorithmic solutions into clinical practice is still slow. In addition to the verification of solutions, their integration in the clinical processing workflow must be enabled for the assessment of clinical impact and risks. The goal of our software platform for cardiac image processing - CAIPI - is to support researchers from different specialties such as imaging physics, computer science, and medicine by a common extensible platform to address typical challenges and hurdles in interdisciplinary cardiovascular imaging research. It provides an integrated solution for method comparison, integrated analysis, and validation in the clinical context. The interface concept enables a combination with existing frameworks that address specific aspects of the pipeline, such as modeling (e.g., OpenCMISS, CARP) or image reconstruction (Gadgetron). METHODS: In our platform, we developed a concept for import, integration, and management of cardiac image data. The integration approach considers the spatiotemporal properties of the beating heart through a specific data model. The solution is based on MeVisLab and provides functionalities for data retrieval and storage. Two types of plugins can be added. While ToolPlugins usually provide processing algorithms such as image correction and segmentation, AnalysisPlugins enable interactive data exploration and reporting. GUI integration concepts are presented for both plugin types. We developed domain-specific reporting and visualization tools (e.g., AHA segment model) to enable validation studies by clinical experts. The platform offers plugins for calculating and reporting quantitative parameters such as cardiac function, which can be used to, e.g., evaluate the effect of processing algorithms on clinical parameters. Export functionalities include quantitative measurements to Excel, image data to PACS, and STL models to modeling and simulation tools. RESULTS: To demonstrate the applicability of this concept both for method development and clinical application, we present use cases representing different problems along the innovation chain in cardiac MR imaging. Validation of an image reconstruction method (MRI T1 mapping) Validation of an image correction method for real-time 2D-PC MRI Comparison of quantification methods for blood flow analysis Training and integration of machine learning solutions with expert annotations Clinical studies with new imaging techniques (flow measurements in the carotid arteries and peripheral veins as well as cerebral spinal fluid). CONCLUSION: The presented platform can be used in interdisciplinary teams, in which engineers or data scientists perform the method validation, followed by clinical research studies in patient collectives. The demonstrated use cases show how it enables the transfer of innovations through validation in the cardiovascular application context.


Assuntos
Sistema Cardiovascular/diagnóstico por imagem , Imageamento por Ressonância Magnética/métodos , Software , Algoritmos , Velocidade do Fluxo Sanguíneo , Humanos , Interpretação de Imagem Assistida por Computador/métodos , Armazenamento e Recuperação da Informação , Reprodutibilidade dos Testes
20.
J Thorac Cardiovasc Surg ; 159(3): 798-810.e1, 2020 03.
Artigo em Inglês | MEDLINE | ID: mdl-31078313

RESUMO

OBJECTIVE: The aim of this study was to compare aortic flow patterns in patients after David valve-sparing aortic root replacement with physiologically shaped sinus prostheses or conventional tube grafts in healthy volunteers. METHODS: Twelve patients with sinus prostheses (55 ± 15 years), 6 patients with tube grafts (58 ± 12 years), 12 age-matched, healthy volunteers (55 ± 6 years), and 6 young, healthy volunteers (25 ± 3 years) were examined with time-resolved 3-dimensional magnetic resonance phase contrast imaging (4D Flow MRI). Primary and secondary helical, as well as vortical flow patterns, were evaluated. Aortic arch anatomy as a flow influencing factor was determined. RESULTS: Compared with volunteers, both sinus prostheses and tube grafts developed more than 4 times as many secondary flow patterns in the ascending aorta (sinus prostheses n = 1.6 ± 0.8; tube grafts n = 1.3 ± 0.6; age-matched, healthy volunteers n = 0.3 ± 0.5; young, healthy volunteers n = 0; P ≤ .012) associated with a kinking of the prosthesis itself or at its distal anastomosis. As opposed to round aortic arches in volunteers (n = 16/18), cubic or gothic-shaped arches predominated in patients (n = 16/18, P < .001). In all but 3 volunteers, 2 counter-rotating helices were confirmed in the ascending aorta and were defined as a primary flow pattern. This primary flow pattern did not develop in patients who underwent valve-sparing aortic root replacement. CONCLUSIONS: In patients after valve-sparing aortic root replacement, there was an increased number of secondary flow patterns in the ascending aorta. This seems to be related to surgically altered aortic geometry with kinking. Because flow alterations are known to affect wall shear stress, there seems to be an increased risk for vessel wall remodeling. Compared with previous 4D Flow MRI studies, primary flow patterns in the ascending aorta in healthy subjects were confirmed to be more complex. This underlines the importance of thorough examination of 4D Flow MRI data.


Assuntos
Aorta/cirurgia , Aneurisma Aórtico/cirurgia , Implante de Prótese Vascular/instrumentação , Prótese Vascular , Hemodinâmica , Imageamento Tridimensional , Angiografia por Ressonância Magnética , Imagem de Perfusão/métodos , Adulto , Idoso , Aorta/diagnóstico por imagem , Aorta/fisiopatologia , Aneurisma Aórtico/diagnóstico por imagem , Aneurisma Aórtico/fisiopatologia , Valva Aórtica/diagnóstico por imagem , Valva Aórtica/fisiopatologia , Velocidade do Fluxo Sanguíneo , Implante de Prótese Vascular/efeitos adversos , Estudos de Casos e Controles , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Modelos Cardiovasculares , Modelagem Computacional Específica para o Paciente , Projetos Piloto , Valor Preditivo dos Testes , Desenho de Prótese , Falha de Prótese , Fluxo Sanguíneo Regional , Fatores de Tempo , Resultado do Tratamento
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA
...