Automatic Characterization of Myocardial Perfusion in Contrast Enhanced MRI

The use of contrast medium in cardiac MRI allows joining the high-resolution anatomical information provided by standard magnetic resonance with functional information obtained by means of the perfusion of contrast agent in myocardial tissues. The current approach to perfusion MRI characterization is the qualitative one, based on visual inspection of images. Moving to quantitative analysis requires extraction of numerical indices of myocardium perfusion by analysis of time/intensity curves related to the area of interest. The main problem in quantitative image sequence analysis is the heart movement, mainly due to patient respiration. We propose an automatic procedure based on image registration, segmentation of the myocardium, and extraction and analysis of time/intensity curves. The procedure requires a minimal user interaction, is robust with respect to the user input, and allows effective characterization of myocardial perfusion. The algorithm was tested on cardiac MR images acquired from voluntaries and in clinical routine

A fast and accurate simulator for the design of birdcage coils in MRI

The birdcage coils are extensively used in MRI systems since they introduce a high signal to noise ratio and a high radiofrequency magnetic field homogeneity that guarantee a large field of view. The present article describes the implementation of a birdcage coil simulator, operating in high-pass and low-pass modes, using magnetostatic analysis of the coil. Respect to other simulators described in literature, our simulator allows to obtain in short time not only the dominant frequency mode, but also the complete resonant frequency spectrum and the relevant magnetic field pattern with high accuracy. Our simulator accounts for all the inductances including the mutual inductances between conductors. Moreover, the inductance calculation includes an accurately birdcage geometry description and the effect of a radiofrequency shield. The knowledge of all the resonance modes introduced by a birdcage coil is twofold useful during birdcage coil design: - higher order modes should be pushed far from the fundamental one, - for particular applications, it is necessary to localize other resonant modes (as the Helmholtz mode) jointly to the dominant mode. The knowledge of the magnetic field pattern allows to a priori verify the field homogeneity created inside the coil, when varying the coil dimension and mainly the number of the coil legs. The coil is analyzed using equivalent circuit method. Finally, the simulator is validated by implementing a low-pass birdcage coil and comparing our data with the literature

Correction to: Measured PET Data Characterization with the Negative Binomial Distribution Model

The article "Measured PET Data Characterization with the Negative Binomial Distribution Model", written by Maria Filomena Santarelli, Vincenzo Positano, Luigi Landini was originally published Online First without open access. After publication in volume [37], issue [3], page [299-312] the author decided to opt for Open Choice and to make the article an open access publication. Therefore, the copyright of the article has been changed to © The Author(s) [2018] and the article is forthwith distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made

The influence of noise in dynamic PET direct reconstruction

In the present work a study is carried out in order to assess the efficiency of the direct reconstruction algorithms on noisy dynamic PET data. The study is performed via Monte Carlo simulations of a uniform cylindrical phantom whose emission values change in time according to a kinetic law. After generating the relevant projection data and properly adding the effects of different noise sources on them, the direct reconstruction and parametric estimation algorithm is applied. The resulting kinetic parameters and reconstructed images are then quantitatively evaluated with appropriate indexes. The simulation is repeated considering different sources of noise and different values of them. The results obtained allow us to affirm that the direct reconstruction algorithm tested maintains a good efficiency also in presence of noise

Automatic PET-CT Image Registration Method Based on Mutual Information and Genetic Algorithms

Hybrid PET/CT scanners can simultaneously visualize coronary artery disease as revealed by computed tomography (CT) and myocardial perfusion as measured by positron emission tomography (PET). Manual registration is usually required in clinical practice to compensate spatial mismatch between datasets. In this paper, we present a registration algorithm that is able to automatically align PET/CT cardiac images. The algorithm bases on mutual information (MI) as registration metric and on genetic algorithm as optimization method. A multiresolution approach was used to optimize the processing time. The algorithm was tested on computerized models of volumetric PET/CT cardiac data and on real PET/CT datasets. The proposed automatic registration algorithm smoothes the pattern of the MI and allows it to reach the global maximum of the similarity function. The implemented method also allows the definition of the correct spatial transformation that matches both synthetic and real PET and CT volumetric datasets

Technological innovations in magnetic resonance for early detection of cardiovascular diseases

Most recent technical innovations in cardiovascular MR imaging (CMRI) are presented in this review. They include hardware and software developments, and novelties in parametric mapping. All these recent improvements lead to high spatial and temporal resolution and quantitative information on the heart structure and function. They make it achievable ambitious goals in the field of mapletic resonance, such as the early detection of cardiovascular pathologies. In this review article, we present recent innovations in CMRI, emphasizing the progresses performed and the solutions proposed to some yet opened technical problems

A Conway–Maxwell–Poisson (CMP) model to address data dispersion on positron emission tomography

Positron emission tomography (PET) in medicine exploits the properties of positron-emitting unstable nuclei. The pairs of γ- rays emitted after annihilation are revealed by coincidence detectors and stored as projections in a sinogram. It is well known that radioactive decay follows a Poisson distribution; however, deviation from Poisson statistics occurs on PET projection data prior to reconstruction due to physical effects, measurement errors, correction of deadtime, scatter, and random coincidences. A model that describes the statistical behavior of measured and corrected PET data can aid in understanding the statistical nature of the data: it is a prerequisite to develop efficient reconstruction and processing methods and to reduce noise. The deviation from Poisson statistics in PET data could be described by the Conway-Maxwell-Poisson (CMP) distribution model, which is characterized by the centring parameter λ and the dispersion parameter ν, the latter quantifying the deviation from a Poisson distribution model. In particular, the parameter ν allows quantifying over-dispersion (ν<1) or under-dispersion (ν>1) of data. A simple and efficient method for λ and ν parameters estimation is introduced and assessed using Monte Carlo simulation for a wide range of activity values. The application of the method to simulated and experimental PET phantom data demonstrated that the CMP distribution parameters could detect deviation from the Poisson distribution both in raw and corrected PET data. It may be usefully implemented in image reconstruction algorithms and quantitative PET data analysis, especially in low counting emission data, as in dynamic PET data, where the method demonstrated the best accuracy

Improvement of Magnetic Resonance Imaging at Low Field using a Birdcage Coil

The main goal of this research was to demonstrate the utility of using a transmitter-receiver birdcage coil for magnetic resonance imaging at very low static field (0.18 T). As well known, the SNR decreases with frequency, thus reducing the image quality at very low field. Moreover, we would expect that the birdcage coil Q factor reduces with fre-quency. But, from experimental evidence, we proved that at low frequency (7.66 MHz), the Q factor for a well-designed birdcage coil reverses the trend, reach-ing unexpected high values. It is a prerequisite to use low static magnetic field in microimaging applica-tions for small animals experiments

A fast algorithm for phased array image reconstruction in Magnetic Resonance Imaging

Abstract: Radiofrequency receiver coils in magnetic resonance imaging systems are used to pick up the signals emitted by the nuclei. Surface coils provide a high signal-to-noise ratio because of their small sensitive region but the usable field of view is also limited to the size of the sensitive region. Using coil array permits to obtain high SNR and a large region of sensitivity: the outputs from the receiver channels are combined in order to construct a single composite image from the data of many coils. For the image construction, usually sum-of-squares (SoS) method is used, which combines data without the knowledge of the coils sensitivity but it is known to provide low contrast images. In this work we investigate and test on MR images a simple method (SUPER algorithm) which uses an estimation of coils field maps to combine the data from the phased array elements to yield an image with higher contrast respect to the usual SoS