α-stable distributions are a family of well-known probability distributions. However, the lack of closed analytical expressions hinders their application. Currently, several tools have been developed ...to numerically evaluate their density and distribution functions or to estimate their parameters, but available solutions either do not reach sufficient precision on their evaluations or are excessively slow for practical purposes. Moreover, they do not take full advantage of the parallel processing capabilities of current multi-core machines. Other solutions work only on a subset of the α-stable parameter space. In this paper we present an R package and a C/C++ library with a MATLAB front-end that permit parallelized, fast and high precision evaluation of density, distribution and quantile functions, as well as random variable generation and parameter estimation of α-stable distributions in their whole parameter space. The described library can be easily integrated into third party developments.
Artificial intelligence (AI) has experienced substantial progress over the last ten years in many fields of application, including healthcare. In hepatology and pancreatology, major attention to date ...has been paid to its application to the assisted or even automated interpretation of radiological images, where AI can generate accurate and reproducible imaging diagnosis, reducing the physicians' workload. AI can provide automatic or semi-automatic segmentation and registration of the liver and pancreatic glands and lesions. Furthermore, using radiomics, AI can introduce new quantitative information which is not visible to the human eye to radiological reports. AI has been applied in the detection and characterization of focal lesions and diffuse diseases of the liver and pancreas, such as neoplasms, chronic hepatic disease, or acute or chronic pancreatitis, among others. These solutions have been applied to different imaging techniques commonly used to diagnose liver and pancreatic diseases, such as ultrasound, endoscopic ultrasonography, computerized tomography (CT), magnetic resonance imaging, and positron emission tomography/CT. However, AI is also applied in this context to many other relevant steps involved in a comprehensive clinical scenario to manage a gastroenterological patient. AI can also be applied to choose the most convenient test prescription, to improve image quality or accelerate its acquisition, and to predict patient prognosis and treatment response. In this review, we summarize the current evidence on the application of AI to hepatic and pancreatic radiology, not only in regard to the interpretation of images, but also to all the steps involved in the radiological workflow in a broader sense. Lastly, we discuss the challenges and future directions of the clinical application of AI methods.
Diffusion-weighted imaging (DWI) is a fundamental sequence not only in neuroimaging but also in oncologic imaging and has emerging applications for MRI evaluation of the chest. DWI can be used in ...clinical practice to enhance lesion conspicuity, tissue characterization, and treatment response. While the spatial resolution of DWI is in the order of millimeters, changes in diffusion can be measured on the micrometer scale. As such, DWI sequences can provide important functional information to MRI evaluation of the chest but require careful optimization of acquisition parameters, notably selection of
values, application of parallel imaging, fat saturation, and motion correction techniques. Along with assessment of morphologic and other functional features, evaluation of DWI signal attenuation and apparent diffusion coefficient maps can aid in tissue characterization. DWI is a noninvasive noncontrast acquisition with an inherent quantitative nature and excellent reproducibility. The outstanding contrast-to-noise ratio provided by DWI can be used to improve detection of pulmonary, mediastinal, and pleural lesions, to identify the benign nature of complex cysts, to characterize the solid portions of cystic lesions, and to classify chest lesions as benign or malignant. DWI has several advantages over fluorine 18 (
F)-fluorodeoxyglucose PET/CT in the assessment, TNM staging, and treatment monitoring of lung cancer and other thoracic neoplasms with conventional or more recently developed therapies.
RSNA, 2023 Quiz questions for this article are available in the supplemental material.
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We aim to validate four-dimensional flow cardiovascular magnetic resonance (4D flow CMR) peak velocity tracking methods for measuring the peak velocity of mitral inflow against Doppler ...echocardiography.
Fifty patients were recruited who had 4D flow CMR and Doppler Echocardiography. After transvalvular flow segmentation using established valve tracking methods, peak velocity was automatically derived using three-dimensional streamlines of transvalvular flow. In addition, a static-planar method was used at the tip of mitral valve to mimic Doppler technique.
Peak E-wave mitral inflow velocity was comparable between TTE and the novel 4D flow automated dynamic method (0.9 ± 0.5 vs 0.94 ± 0.6 m/s; p = 0.29) however there was a statistically significant difference when compared with the static planar method (0.85 ± 0.5 m/s; p = 0.01). Median A-wave peak velocity was also comparable across TTE and the automated dynamic streamline (0.77 ± 0.4 vs 0.76 ± 0.4 m/s; p = 0.77). A significant difference was seen with the static planar method (0.68 ± 0.5 m/s; p = 0.04). E/A ratio was comparable between TTE and both the automated dynamic and static planar method (1.1 ± 0.7 vs 1.15 ± 0.5 m/s; p = 0.74 and 1.15 ± 0.5 m/s; p = 0.5 respectively). Both novel 4D flow methods showed good correlation with TTE for E-wave (dynamic method; r = 0.70; P < 0.001 and static-planar method; r = 0.67; P < 0.001) and A-wave velocity measurements (dynamic method; r = 0.83; P < 0.001 and static method; r = 0.71; P < 0.001). The automated dynamic method demonstrated excellent intra/inter-observer reproducibility for all parameters.
Automated dynamic peak velocity tracing method using 4D flow CMR is comparable to Doppler echocardiography for mitral inflow assessment and has excellent reproducibility for clinical use.
•4D flow CMR shows good agreement with doppler echocardiography for mitral inflow peak velocity measurement.•This study suggests that 4D flow CMR is highly reproducible in mitral inflow peak velocity measurement.•4D flow CMR is an accurate and reliable non-invasive imaging method for left ventricular diastolic assessment.
The role of inflammation in cardiovascular pathophysiology has gained a lot of research interest in recent years. Cardiovascular Magnetic Resonance has been a powerful tool in the non-invasive ...assessment of inflammation in several conditions. More recently, Ultrasmall superparamagnetic particles of iron oxide have been successfully used to evaluate macrophage activity and subsequently inflammation on a cellular level. Current evidence from research studies provides encouraging data and confirms that this evolving method can potentially have a huge impact on clinical practice as it can be used in the diagnosis and management of very common conditions such as coronary artery disease, ischaemic and non-ischaemic cardiomyopathy, myocarditis and atherosclerosis. Another important emerging concept is that of myocardial energetics. With the use of phosphorus magnetic resonance spectroscopy, myocardial energetic compromise has been proved to be an important feature in the pathophysiological process of several conditions including diabetic cardiomyopathy, inherited cardiomyopathies, valvular heart disease and cardiac transplant rejection. This unique tool is therefore being utilized to assess metabolic alterations in a wide range of cardiovascular diseases. This review systematically examines these state-of-the-art methods in detail and provides an insight into the mechanisms of action and the clinical implications of their use.
Cardiovascular magnetic resonance (CMR) imaging is a versatile tool that has established itself as the reference method for functional assessment and tissue characterisation. CMR helps to diagnose, ...monitor disease course and sub-phenotype disease states. Several emerging CMR methods have the potential to offer a personalised medicine approach to treatment. CMR tissue characterisation is used to assess myocardial oedema, inflammation or thrombus in various disease conditions. CMR derived scar maps have the potential to inform ablation therapy-both in atrial and ventricular arrhythmias. Quantitative CMR is pushing boundaries with motion corrections in tissue characterisation and first-pass perfusion. Advanced tissue characterisation by imaging the myocardial fibre orientation using diffusion tensor imaging (DTI), has also demonstrated novel insights in patients with cardiomyopathies. Enhanced flow assessment using four-dimensional flow (4D flow) CMR, where time is the fourth dimension, allows quantification of transvalvular flow to a high degree of accuracy for all four-valves within the same cardiac cycle. This review discusses these emerging methods and others in detail and gives the reader a foresight of how CMR will evolve into a powerful clinical tool in offering a precision medicine approach to treatment, diagnosis, and detection of disease.
Diffusion-tensor imaging (DTI) has been used in the assessment of the central nervous system for the past 3 decades and has demonstrated great utility for the functional assessment of normal and ...pathologic white matter. Recent technical advances have permitted the expansion of DTI applications to the spinal cord. MRI of the spinal cord has traditionally been limited to conventional sequences, which provide information regarding changes in the anatomic shape of a structure or its signal intensity, suggesting the presence of a pathologic entity. However, conventional MRI lacks the ability to provide pathophysiologic information. DTI of the spinal cord can deliver pathophysiologic information on a molecular basis and thereby has several adjunctive uses. These advantages have yet to be fully evaluated, and therefore spinal DTI lacks widespread adoption. The barriers to implementation include a lack of understanding of the underlying physics principles needed to make necessary technical adjustments to obtain diagnostic images, as well as the need for standardization of protocols and postprocessing methods. The authors provide a comprehensive review of the physics of spinal cord DTI and the technical adjustments required to obtain diagnostic images and describe tips and tricks for accurate postprocessing. The primary clinical applications for spinal cord DTI are reviewed.
RSNA, 2020 See discussion on this article by Smith.
•Highly efficient implementation of a 3D+t groupwise registration problem based on the free-form deformation paradigm.•New implementation based on simple convolutional operations, which leads to a ...great reduction in the execution time.•Proposed implementation affects the evaluation of deformations and gradients during the optimization process of image registration.
Background and Objective:This paper proposes a new and highly efficient implementation of 3D+t groupwise registration based on the free-form deformation paradigm. Methods:Deformation is posed as a cascade of 1D convolutions, achieving great reduction in execution time for evaluation of transformations and gradients. Results:The proposed method has been applied to 4D cardiac MRI and 4D thoracic CT monomodal datasets. Results show an average runtime reduction above 90%, both in CPU and GPU executions, compared with the classical tensor product formulation. Conclusions:Our implementation, although fully developed for the metric sum of squared differences, can be extended to other metrics and its adaptation to multiresolution strategies is straightforward. Therefore, it can be extremely useful to speed up image registration procedures in different applications where high dimensional data are involved.
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