Automated co-registration and subtraction techniques have been shown to be useful in the assessment of longitudinal changes in multiple sclerosis (MS) lesion burden, but the majority depend on T2-fluid-attenuated inversion recovery sequences. We aimed to investigate the use of a novel automated temporal color complement imaging (CCI) map overlapped on 3D double inversion recovery (DIR), and to assess its diagnostic performance for detecting disease progression in patients with multiple sclerosis (MS) as compared to standard review of serial 3D DIR images. We developed a fully automated system that co-registers and compares baseline to follow-up 3D DIR images and outputs a pseudo-color RGB map in which red pixels indicate increased intensity values in the follow-up image (i.e., progression; new/enlarging lesion), blue-green pixels represent decreased intensity values (i.e., disappearing/shrinking lesion), and gray-scale pixels reflect unchanged intensity values. Three neuroradiologists blinded to clinical information independently reviewed each patient using standard DIR images alone and using CCI maps based on DIR images at two separate exams. Seventy-six follow-up examinations from 60 consecutive MS patients who underwent standard 3 T MR brain MS protocol that included 3D DIR were included. Median cohort age was 38.5 years, with 46 women, 59 relapsing–remitting type MS, and median follow-up interval of 250 days (interquartile range: 196–394 days). Lesion progression was detected in 67.1

Accelerated magnetic resonance imaging techniques reduce signal acquisition time by undersampling k-space. A fundamental problem in accelerated magnetic resonance imaging is the recovery of quality images from undersampled k-space data. Current state-of-the-art recovery algorithms exploit the spatial and temporal structures in underlying images to improve the reconstruction quality. In recent years, compressed sensing theory has helped formulate mathematical principles and conditions that ensure recovery of (structured) sparse signals from undersampled, incoherent measurements. In this article, a new recovery algorithm, motion-adaptive spatio-temporal regularization, is presented that uses spatial and temporal structured sparsity of MR images in the compressed sensing framework to recover dynamic MR images from highly undersampled k-space data. In contrast to existing algorithms, our proposed algorithm models temporal sparsity using motion-adaptive linear transformations between neighboring images. The efficiency of motion-adaptive spatio-temporal regularization is demonstrated with experiments on cardiac magnetic resonance imaging for a range of reduction factors. Results are also compared with k-t FOCUSS with motion estimation and compensation-another recently proposed recovery algorithm for dynamic magnetic resonance imaging. .

PURPOSE:To analyze and optimize the signal-to-noise ratio (SNR) for the "Noquist" method for acceleration of cine magnetic resonance imaging in the presence of partially static field of view, designing practical methods for selection of optimal or near-optimal sample sets to allow reliable application of the method for variable image dimensions.METHODS:To investigate the impact of the Noquist method and its experimental parameters on the SNR in the image reconstructed from reduced data, and to explore optimization of methods for highest SNR stability, three different optimization parameters have been selected: the condition of the forward matrix (R(cond)) as it defines the propagation of noise into the reconstructed image, and the maximum (Φ(maxD)) and the mean (Φ(meanD)) linear noise amplification factor of the dynamic field-of-view (FOV) region. As SNR in a Noquist reconstruction is often not uniform across the FOV and since dynamic regions may contain the part of the image more clinically relevant, primarily these noise levels are targeted for optimization. Using these three optimization parameters, three experiments were conducted: characterization of Noquist SNR properties as a function of important image size parameters; for sufficiently small image dimensions, employment of exhaustive search using lexicographical algorithms to visit all possibilities under the cine imaging constraint that equal numbers of views are acquired at each time point of the sequence; and, departing from an hypothetically optimal pattern, generation and evaluation of SNR characteristics of a series of random variations to that optimal pattern.RESULTS:The impact of favorable sparse data selection is illustrated, and SNR properties are characterized as a function of relevant acquisition parameters. Optimal data selection is investigated by exhaustive methods for small image sizes, and compared with algorithmic selection patterns. Observations from these experiments are confirmed by further studies on data selection for realistic image dimensions and an optimal selection algorithm is proposed. Sixty-four cases of small image sizes were analyzed through exhaustive search with a total of 527 984 141 matrix inversions called in the process, evaluating several SNR parameters for each case. An algorithm, named "Stairwell," that permits to design image dimensions with optimal SNR characteristics is presented, evaluated and compared with cases analyzed through exhaustive search. In 71.9% of the cases exhaustively studied, the Stairwell algorithm yielded optimal solutions. For no case did the deviation from optimum exceed 3.2% (R(cond)), 1.0% (Φ(meanD)), and 4.9% (Φ(maxD)).CONCLUSIONS:We have demonstrated SNR-optimality of the "Stairwell" selection algorithm for small image dimensions, and performed additional experiments which all support hypothesized optimality of the algorithm for any image dimensions that satisfy certain symmetry constraints for Noquist reduced-data cine MR imaging. Furthermore, we have presented overall SNR characteristics associated with use of the Noquist method by this algorithm for practical clinical image dimensions. Additionally, observations from our optimization experiments allow us to formulate recommendations for dimensioning Noquist image acquisition parameters which guarantee stable inversion. Moreover, these results allow prediction of the anticipated SNR properties of the reconstruction for given image dimensions (S,D,T), relative to SNR in a conventional full-grid acquisition.

This paper introduces a novel method for accelerated dynamic image acquisition for cardiac MRI. This method combines two different formalisms for reconstruction from sparse data by incorporation of prior information. Parallel imaging uses information about coil geometry in imaging systems with multiple receiver coils. Reduced field of view (rFOV) imaging exploits knowledge about static regions in a dynamic image scene. The novel method combines the SPACE-RIP implementation of parallel imaging with the Noquist rFOV imaging method, which both use a direct inversion model for image reconstruction. The theory is presented for integrated application of these methods, and results are presented of supporting experiments with simulated and real MRI data, retrospectively subsampled to generate sparse data sets. Successful application of the method confirms multiplicative combined acceleration.

This study evaluates reliability of current technology for measurement of renal arterial blood flow by breath-held velocity-encoded MRI. Overall accuracy was determined by comparing MRI measurements with known flow in controlled-flow-loop phantom studies. Measurements using prospective and retrospective gating methods were compared in phantom studies with pulsatile flow, not revealing significant differences. Phantom study results showed good accuracy, with deviations from true flow consistently below 13% for vessel diameters 3mm and above. Reproducibility in human subjects was evaluated by repeated studies in six healthy control subjects, comparing immediate repetition of the scan, repetition of the scan plane scouting, and week-to-week variation in repeated studies. The standard deviation in the 4-week protocol of repeated in vivo measurements of single-kidney renal flow in normal subjects was 59.7 mL/min, corresponding with an average coefficient of variation of 10.55%. Comparison of renal arterial blood flow reproducibility with and without gadolinium contrast showed no significant differences in mean or standard deviation. A breakdown among error components showed corresponding marginal standard deviations (coefficients of variation) 23.8 mL/min (4.21%) for immediate repetition of the breath-held flow scan, 39.13 mL/min (6.90%) for repeated plane scouting, and 40.76 mL/min (7.20%) for weekly fluctuations in renal blood flow.

BACKGROUND:Congenital bicuspid aortic valve (BAV) is a significant risk factor for serious complications including valve dysfunction, aortic dilatation, dissection, and sudden death. Clinical tools for identification and monitoring of BAV patients at high risk for development of aortic dilatation, an early complication, are not available.METHODS:This paper reports an investigation in 18 pediatric BAV patients and 10 normal controls of links between abnormal blood flow patterns in the ascending aorta and aortic dilatation using velocity-encoded cardiovascular magnetic resonance. Blood flow patterns were quantitatively expressed in the angle between systolic left ventricular outflow and the aortic root channel axis, and also correlated with known biochemical markers of vessel wall disease.RESULTS:The data confirm larger ascending aortas in BAV patients than in controls, and show more angled LV outflow in BAV (17.54 +/- 0.87 degrees) than controls (10.01 +/- 1.29) (p = 0.01). Significant correlation of systolic LV outflow jet angles with dilatation was found at different levels of the aorta in BAV patients STJ: r = 0.386 (N = 18, p = 0.048), AAO: r = 0.536 (N = 18, p = 0.022), and stronger correlation was found with patients and controls combined into one population: SOV: r = 0.405 (N = 28, p = 0.033), STJ: r = 0.562 (N = 28, p = 0.002), and AAO r = 0.645 (N = 28, p < 0.001). Dilatation and the flow jet angle were also found to correlate with plasma levels of matrix metallo-proteinase 2.CONCLUSIONS:The results of this study provide new insights into the pathophysiological processes underlying aortic dilatation in BAV patients. These results show a possible path towards the development of clinical risk stratification protocols in order to reduce morbidity and mortality for this common congenital heart defect.

Magnetic resonance imaging (MRI) is the preferred imaging modality for visualization of intracranial soft tissues. Surgical planning, and increasingly surgical navigation, use high resolution 3-D patient-specific structural maps of the brain. However, the process of MRI is a multi-parameter tomographic technique where high resolution imagery competes against high contrast and reasonable acquisition times. Resolution enhancement techniques based on super-resolution are particularly well-suited in solving the problems of resolution when high contrast with reasonable times for MRI acquisitions are needed. Super-resolution is the concept of reconstructing a high resolution image from a set of low-resolution images taken at different viewpoints or foci. The MRI encoding techniques that produce high resolution imagery are often sub-optimal for the desired contrast needed for visualization of some structures in the brain. A novel super-resolution reconstruction framework for MRI is proposed in this thesis. Its purpose is to produce images of both high resolution and high contrast desirable for image-guided minimally invasive brain surgery. The input data are multiple 2-D multi-slice Inversion Recovery MRI scans acquired at orientations with regular angular spacing rotated around a common axis. Inspired by the computed tomography domain, the reconstruction is a 3-D volume of isotropic high resolution, where the inversion process resembles a projection reconstruction problem. Iterative algorithms for reconstruction are based on the projection onto convex sets formalism. Results demonstrate resolution enhancement in simulated phantom studies, and in ex- and in-vivo human brain scans, carried out on clinical scanners. In addition, a novel motion correction method is applied to volume registration using an iterative technique in which super-resolution reconstruction is estimated in a given iteration following motion correction in the preceding iteration. A comparison study of our method with previously published methods in super-resolution shows favorable characteristics of the proposed approach.

A novel super-resolution reconstruction (SRR) framework in magnetic resonance imaging (MRI) is proposed. Its purpose is to produce images of both high resolution and high contrast desirable for image-guided minimally invasive brain surgery. The input data are multiple 2-D multislice inversion recovery MRI scans acquired at orientations with regular angular spacing rotated around a common frequency encoding axis. The output is a 3-D volume of isotropic high resolution. The inversion process resembles a localized projection reconstruction problem. Iterative algorithms for reconstruction are based on the projection onto convex sets (POCS) formalism. Results demonstrate resolution enhancement in simulated phantom studies, and ex vivo and in vivo human brain scans, carried out on clinical scanners. A comparison with previously published SRR methods shows favorable characteristics in the proposed approach.

A comparison study is presented of two methods for MRI reconstruction using super-resolution techniques which combine multiple multi-slice stacks into a single high- resolution 3-D image volume. Sampling configurations are compared involving stacks with parallel orientations at different sub-pixel offset locations, and stacks with regularly distributed slice orientations. Results from experiments with simulated and real MRI data suggest that different stack orientations perform better than parallel stacks.

-1 contains identical blocks of inverse Fourier coefficients. Noquist reduces this model by representing the static part of the FOV only once in the entire sequence, since it is identical in all frames. The total size of the cine image is thus reduced from T(NS+ND) to NS+TND. This propagates into accordingly reduced size requirements for each of the equally-sized temporal k-space sample vectors F for each time point to ND+NS/T. Selection of a subset of k-space views in each frame is constrained by the requirement to keep matrix M invertible. SENSE: An image f is observed by a receiver coil c with sensitivity Sc as the product fc=f.Sc, with corresponding Fourier data Fc=Mfc. With complete prior knowledge of Sc at all image locations for each of C independent receiver coils, complete conventional sampling of Fc yields C-fold redundant data. Accordingly, reduction of the number of acquired k-space views by a factor R up to C may present a feasible image reconstruction problem. Recovery of f from the reduced Fourier data sets Fc, simultaneously acquired from all C coils, may be achieved through different strategies, with different constraints in flexibility in sampling patterns and computational complexity.

Faster acquisition of cinO imaging sequences remains of critical importance for continued development of advanced applications in cardiac MRI. Parallel imaging and partial-Fourier techniques offer important benefits and are now widely available, but have limitations in attainable acceleration, and may not always be compatible with phase-sensitive data such as phase velocity encoded studies. Further improvement in acquisition speed, compatible with flow encoding, may be obtained through reduced field of view methods, which use the presence of static field of view (FOV) regions in dynamic images as prior information for data reduction. We have recently proposed the fiNoquistfl rFOV method [1], which uniquely preserves full spatiotemporal resolution by a direct inversion approach and is flexible with respect to dynamic FOV size and location. In a dynamic reconstruction problem with N

Image-guided neurosurgery depends on both high image contrast and resolution. With pre-operative images, surgeons can precisely navigate using specialized instruments to in-vivo targets of interest such as the globus pallidus or subthalamic regions. Current MR imaging techniques, however, do not offer the full resolution and contrast-to-noise requirements needed by these surgical methods. This paper examines a technique based on projections onto convex sets (POCS) and relies on superresolution restoration that reaches high contrast and resolution for deep brain stimulator implantation surgery. An inversion process is introduced for combining multiple scans at different orientations with downsampled measurements producing a single data volume of high resolution and contrast

Abstract In 1946, the phenomenon of nuclear magnetic resonance (NMR) was first observed independently by Felix Bloch and Edward Purcell. NMR is a phenomenon exhibited by atoms with an odd number of protons or neutrons which possess nuclear spin angular momentum. In the classical description the phenomenon can be described as spinning charged spheres which produce a small magnetic moment. Developments in NMR over the decades that followed, including the spin echo and different RF pulse sequences, led to widespread use of NMR spectroscopy, a method of analyzing the composition of chemical samples. In 1970, Raymond Damadian discovered the basis for using NMR as a tool for in‐vivo cancer diagnosis. In 1973, Paul Lauterbur proposed the use of gradient magnetic fields for spatial encoding of NMR signals to form the first magnetic resonance images. Magnetic resonance imaging (MRI) has since developed rapidly into a widely used clinical imaging modality, and is now used to image virtually every part of the body in clinical practice. MRI has the important advantage over X‐ray imaging modalities that it does not use ionizing radiation. MRI also allows arbitrary selection of the scan plane and true three‐dimensional imaging. Unlike any other medical imaging modalities, image contrast in MRI is based on multiple physical parameters, resulting in the unique ability to generate excellent soft‐tissue contrast that can be tailored for specific applications.

A technique for identifying hypometabolism from Positron Emission Tomography (PET) brain images, which accounts for patient-specific anatomical variations, scanner physical properties, and expected normal variances in metabolism, has been developed and used to identify unilateral temporal lobe seizure foci in epileptics. This method was able to distinguish the epileptogenic focus in three seizure patients with unilateral seizure onset, while demonstrating no hypometabolism in three patients with bilateral seizure onset or in the ten normal volunteers.

The objective of this study was to investigate the prevalence of hepatic cysts by age and gender in patients with early autosomal-dominant polycystic kidney disease (ADPKD) and to determine whether hepatic cyst volume is related to renal and renal cyst volumes by using magnetic resonance imaging (MRI). A total of 230 patients with ADPKD (94 men and 136 women) who were aged 15 to 46 yr and had relatively preserved renal function were studied. MRI images of the kidney and liver were obtained to measure renal, renal cyst, and hepatic cyst volumes. These volume measurements and hepatic cyst prevalence were compared in all patients and in subgroups on the basis of gender and age (15 to 24, 25 to 34, and 35 to 46 yr). The overall prevalence of hepatic cysts was 83%; the prevalence was 58, 85, and 94% in the sequential age groups and 85% in women and 79% in men. The prevalence was related directly to renal volume (chi(2) = 4.30, P = 0.04) and to renal cyst volume (chi(2) = 5.59, P = 0.02). The total hepatic cyst volume was significantly greater in women than in men (a logarithmic transformation mean of 5.27 versus 1.94 ml; P = 0.003). The average hepatic cyst volume was 0.25, 5.75, and 22.78 ml in sequential age groups. Hepatic cysts are evident in 94% of patients who are older than 35 yr and in 55% of individuals who are younger than 25 yr. Hepatic cysts are more prevalent and larger in total cyst volume in women than in men. Hepatic cyst prevalence and aggregate total hepatic cyst volume increased with age.

A novel technique called "Noquist" is introduced for the acceleration of dynamic cardiac magnetic resonance imaging (CMRI). With the use of this technique, a more sparsely sampled dynamic image sequence is reconstructed correctly, without Nyquist foldover artifact. Unlike most other reduced field-of-view (rFOV) methods, Noquist does not rely on data substitution or temporal interpolation to reconstruct the dynamic image sequence. The proposed method reduces acquisition time in dynamic MRI scans by eliminating the data redundancy associated with static regions in the dynamic scene. A reduction of imaging time is achieved by a fraction asymptotically equal to the static fraction of the FOV, by omitting acquisition of an appropriate subset of phase-encoding views from a conventional equidistant Cartesian acquisition grid. The theory behind this method is presented along with sample reconstructions from real and simulated data. Noquist is compared with conventional cine imaging by retrospective selection of a reduced data set from a full-grid conventional image sequence. In addition, a comparison is presented, using real and simulated data, of our technique with an existing rFOV technique that uses temporal interpolation. The experimental results confirm the theory, and demonstrate that Noquist reduces scan time for cine MRI while fully preserving both spatial and temporal resolution, but at the cost of a reduced signal-to-noise ratio (SNR).

Lo que marca la diferencia entre la resonancia magnética (RM) y otras modalidades de imagen médica es que el usuario tiene completo control sobre la forma de adquirir los datos y cómo éstos pueden manipularse para mostrar la imagen final. El radiólogo puede modificar la resolución, el tamaño del campo de visión, el contraste, la velocidad de la adquisición, la influencia de los artefactos y tantos otros muchos parámetros que contribuyen a formar la imagen final. El artífice de este control se conoce como espacio-k, y no es más que la matriz de datos sin procesar obtenida a la salida del equipo de RM antes de la aplicación de la transformada de Fourier, la cual proveerá de la imagen final reconstruida. Este control que proporciona el espacio-kforzará la necesidad por parte del usuario de comprender los conceptos y los mecanismos ligados a éste. Sólo de esta forma le podrá sacar el máximo rendimiento a la resolución espacial, resolución temporal y calidad final de la imagen. El principal problema radica en que el espacio-kes un concepto abstracto. Aunque su contenido se puede visualizar, sus datos tienen poco sentido y no poseen una relación aparente con la imagen de RM. Por otra parte, la construcción matemática que lo describe con detalle es sofisticada y complicada y no da a entender, de una forma intuitiva, de lo que se trata. Este artículo analizará este concepto poco conocido, aunque ampliamente utilizado en RM. What marks the difference between magnetic resonance (MR) and other medical imaging techniques is that the user has complete control over both the way in which data is acquired and how it can be manipulated in presenting the final image. The radiologist can modify resolution, field size, contrast, acquisition speed, artifact influence, and many other parameters which contribute in producing the final image. The vehicle of this control is known as k-space, and is nothing more than a matrix of unprocessed output data from the MR unit before applying Fourier transformation, which will in turn provide a final reconstructed image. The user would necessarily be required to understand those concepts and mechanisms related to k-space. Only then could optimum results be yielded in regard to spatial resolution, temporal resolution and image quality. The principal problem lies in the fact that k-space is an abstract concept. Although its content can be visualized, the data of which it is comprised makes little sense and suggests no apparent relation to MR imaging. On the other hand, the mathematical construction used to describe it in detail is sophisticated and complicated, and does not easily lend itself to an intuitive understanding of precisely what it is that k-space entails. This article analyzes this little known yet widely used concept in MR imaging.

Whether changes in renal blood flow (RBF) are associated with and possibly contribute to cystic disease progression in autosomal dominant polycystic kidney disease (ADPKD) has not been ascertained. The Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease (CRISP) was created to develop imaging techniques and analyses to evaluate progression. A total of 131 participants with early ADPKD had measurements of RBF and total kidney (TKV) and cyst (TCV) volumes by magnetic resonance and of GFR by iothalamate clearance at baseline and 1, 2, and 3 yr. The effects of age, gender, body mass index, hypertension status, mean arterial pressure (MAP), TKV, TCV, RBF, renal vascular resistance (RVR), GFR, serum uric acid, HDL and LDL cholesterol, 24-h urine volume, sodium (UNaE) and albumin (UAE) excretions, and estimated protein intake were examined at baseline on TKV, TCV, and GFR slopes. TKV and TCV increased, RBF decreased, and GFR remained stable. TKV, TCV, RVR, serum uric acid, UAE, UNaE, age, body mass index, MAP, and estimated protein intake were positively and RBF and GFR negatively correlated with TKV and TCV slopes. TKV, RBF, UNaE, and UAE were independent predictors of TKV and TCV slopes (structural disease progression). TKV, TCV, RVR, and MAP were negatively and RBF positively correlated with GFR slopes. Regression to the mean confounded the analysis of GFR slopes. TKV and RBF were independent predictors of GFR decline (functional disease progression). In ADPKD, RBF reduction (1) parallels TKV increase, (2) precedes GFR decline, and (3) predicts structural and functional disease progression.