Resolution enhancement, noise suppression, and joint T2* decay estimation in dual-echo sodium-23 MR imaging using anatomically guided reconstruction.

PURPOSE: Sodium MRI is challenging because of the low tissue concentration of the 23 Na nucleus and its extremely fast biexponential transverse relaxation rate. In this article, we present an iterative reconstruction framework using dual-echo 23 Na data and exploiting anatomical prior information (AGR) from high-resolution, low-noise, 1 H MR images. This framework enables the estimation and modeling of the spatially varying signal decay due to transverse relaxation during readout (AGRdm), which leads to images of better resolution and reduced noise resulting in improved quantification of the reconstructed 23 Na images. METHODS: The proposed framework was evaluated using reconstructions of 30 noise realizations of realistic simulations of dual echo twisted projection imaging (TPI) 23 Na data. Moreover, three dual echo 23 Na TPI brain datasets of healthy controls acquired on a 3T Siemens Prisma system were reconstructed using conventional reconstruction, AGR and AGRdm. RESULTS: Our simulations show that compared to conventional reconstructions, AGR and AGRdm show improved bias-noise characteristics in several regions of the brain. Moreover, AGR and AGRdm images show more anatomical detail and less noise in the reconstructions of the experimental data sets. Compared to AGR and the conventional reconstruction, AGRdm shows higher contrast in the sodium concentration ratio between gray and white matter and between gray matter and the brain stem. CONCLUSION: AGR and AGRdm generate 23 Na images with high resolution, high levels of anatomical detail, and low levels of noise, potentially enabling high-quality 23 Na MR imaging at 3T.

Ryanodine channel complex stabilizer compound S48168/ARM210 as a disease modifier in dystrophin-deficient mdx mice: proof-of-concept study and independent validation of efficacy.

Muscle fibers lacking dystrophin undergo a long-term alteration of Ca2+ homeostasis, partially caused by a leaky Ca2+ release ryanodine (RyR) channel. S48168/ARM210, an RyR calcium release channel stabilizer (a Rycal compound), is expected to enhance the rebinding of calstabin to the RyR channel complex and possibly alleviate the pathologic Ca2+ leakage in dystrophin-deficient skeletal and cardiac muscle. This study systematically investigated the effect of S48168/ARM210 on the phenotype of mdx mice by means of a first proof-of-concept, short (4 wk), phase 1 treatment, followed by a 12-wk treatment (phase 2) performed in parallel by 2 independent laboratories. The mdx mice were treated with S48168/ARM210 at two different concentrations (50 or 10 mg/kg/d) in their drinking water for 4 and 12 wk, respectively. The mice were subjected to treadmill sessions twice per week (12 m/min for 30 min) to unmask the mild disease. This testing was followed by in vivo forelimb and hindlimb grip strength and fatigability measurement, ex vivo extensor digitorum longus (EDL) and diaphragm (DIA) force contraction measurement and histologic and biochemical analysis. The treatments resulted in functional (grip strength, ex vivo force production in DIA and EDL muscles) as well as histologic improvement after 4 and 12 wk, with no adverse effects. Furthermore, levels of cellular biomarkers of calcium homeostasis increased. Therefore, these data suggest that S48168/ARM210 may be a safe therapeutic option, at the dose levels tested, for the treatment of Duchenne muscular dystrophy (DMD).-Capogrosso, R. F., Mantuano, P., Uaesoontrachoon, K., Cozzoli, A., Giustino, A., Dow, T., Srinivassane, S., Filipovic, M., Bell, C., Vandermeulen, J., Massari, A. M., De Bellis, M., Conte, E., Pierno, S., Camerino, G. M., Liantonio, A., Nagaraju, K., De Luca, A. Ryanodine channel complex stabilizer compound S48168/ARM210 as a disease modifier in dystrophin-deficient mdx mice: proof-of-concept study and independent validation of efficacy.

Chronic urinary obstruction: evaluation of dynamic contrast-enhanced MR urography for measurement of split renal function.

PURPOSE: To evaluate if measurement of split renal function ( SRF split renal function ) with dynamic contrast material-enhanced ( DCE dynamic contrast enhanced ) magnetic resonance (MR) urography is equivalent to that with renal scintigraphy ( RS renal scintigraphy ) in patients suspected of having chronic urinary obstruction. MATERIALS AND METHODS: The study protocol was approved by the institutional ethics committee of the coordinating center on behalf of all participating centers. Informed consent was obtained from all adult patients or both parents of children. This prospective, comparative study included 369 pediatric and adult patients from 14 university hospitals who were suspected of having chronic or intermittent urinary obstruction, and data from 295 patients with complete data were used for analysis. SRF split renal function was measured by using the area under the curve and the Patlak-Rutland methods, including successive review by a senior and an expert reviewer and measurement of intra- and interobserver agreement for each technique. An equivalence test for mean SRF split renal function was conducted with an α of 5%. RESULTS: Reproducibility was substantial to almost perfect for both methods. Equivalence of DCE dynamic contrast enhanced MR urography and RS renal scintigraphy for measurement of SRF split renal function was shown in patients with moderately dilated kidneys (P < .001 with the Patlak-Rutland method). However, in severely dilated kidneys, the mean SRF split renal function measurement was underestimated by 4% when DCE dynamic contrast enhanced MR urography was used compared with that when RS renal scintigraphy was used. Age and type of MR imaging device had no significant effect. CONCLUSION: For moderately dilated kidneys, equivalence of DCE dynamic contrast enhanced MR urography to RS renal scintigraphy was shown, with a standard deviation of approximately 12% between the techniques, making substitution of DCE dynamic contrast enhanced MR urography for RS renal scintigraphy acceptable. For severely dilated kidneys, a mean underestimation of SRF split renal function of 4% should be expected with DCE dynamic contrast enhanced MR urography, making substitution questionable.

Use of dynamic reconstruction for parametric Patlak imaging in dynamic whole body PET.

Dynamic whole body (DWB) PET acquisition protocols enable the use of whole body parametric imaging for clinical applications. In FDG imaging, accurate parametric images of PatlakKican be complementary to regular standardised uptake value images and improve on current applications or enable new ones. In this study we consider DWB protocols implemented on clinical scanners with a limited axial field of view with the use of multiple whole body sweeps. These protocols result in temporal gaps in the dynamic data which produce noisier and potentially more biased parametric images, compared to single bed (SB) dynamic protocols. Dynamic reconstruction using the Patlak model has been previously proposed to overcome these limits and shown improved DWB parametric images ofKi. In this work, we propose and make use of a spectral analysis based model for dynamic reconstruction and parametric imaging of PatlakKi. Both dynamic reconstruction methods were evaluated for DWB FDG protocols and compared against 3D reconstruction based parametric imaging from SB dynamic protocols. This work was conducted on simulated data and results were tested against real FDG dynamic data. We showed that dynamic reconstruction can achieve levels of parametric image noise and bias comparable to 3D reconstruction in SB dynamic studies, with the spectral model offering additional flexibility and further reduction of image noise. Comparisons were also made between step and shoot and continuous bed motion (CBM) protocols, which showed that CBM can achieve lower parametric image noise due to reduced acquisition temporal gaps. Finally, our results showed that dynamic reconstruction improved VOI parametric mean estimates but did not result to fully converged values before resulting in undesirable levels of noise. Additional regularisation methods need to be considered for DWB protocols to ensure both accurate quantification and acceptable noise levels for clinical applications.

Groundwater level and electrical conductivity datasets acquired within pumping tests on Ilovik Island in Croatia.

The small karst island of Ilovik is the most southern of inhabited islands in the Croatian part of the Adriatic Sea. During summer tourist season the number of inhabitants increases significantly, and securing the additional freshwater quantities was needed. Given the hydrogeological and geomorphological setting of the island, possibility of brackish groundwater exploitation was considered. Hence, borehole drilling accompanied with pumping tests at three specified locations was carried out. During the pumping tests in two campaigns, groundwater level was measured manually every 2 hours in boreholes, while groundwater electric conductivity and temperature were periodically measured in situ. The sea level was observed at the reference point located near port. Given dataset consists of electrical conductivity, temperature, groundwater and seawater levels. The research article connected with these data (Terzic et al., 2020) provides hydrogeological interpretation of brackish groundwater lens on small karst island.

Reconstruction, analysis and interpretation of posterior probability distributions of PET images, using the posterior bootstrap.

The uncertainty of reconstructed PET images remains difficult to assess and to interpret for the use in diagnostic and quantification tasks. Here we provide (1) an easy-to-use methodology for uncertainty assessment for almost any Bayesian model in PET reconstruction from single datasets and (2) a detailed analysis and interpretation of produced posterior image distributions. We apply a recent posterior bootstrap framework to the PET image reconstruction inverse problem and obtain simple parallelizable algorithms based on random weights and on existing maximuma posteriori(MAP) (posterior maximum) optimization-based algorithms. Posterior distributions are produced, analyzed and interpreted for several common Bayesian models. Their relationship with the distribution of the MAP image estimate over multiple dataset realizations is exposed. The coverage properties of posterior distributions are validated. More insight is obtained for the interpretation of posterior distributions in order to open the way for including uncertainty information into diagnostic and quantification tasks.

Time-of-flight (TOF) implementation for PET reconstruction in practice.

The time-of-flight (TOF) feature of PET scanners has been used for a long time in PET reconstruction, but many implementational aspects are still incomplete or ambiguous in the literature. Here we formalize and present theoretical and practical implementation details for the reconstruction of clinical TOF histogram and list-mode data using ML-EM. Relevant aspects include the computation of the TOF component of the system matrix, the processing of TOF bins, the use of estimations of random and scattered coincidences, and differences between histogram and list-mode ML-EM TOF reconstruction. Several approaches and approximations have been implemented in the CASToR platform and compared for OSEM reconstructions of patient data from the GE Signa PET/MR scanner. Differences between implementations are not larger than the typical bias in clinical data reconstruction. The largest difference and contrast loss occur when the processing of histogram TOF bins is simplified, and list-mode reconstruction is most sensitive to the truncation of the Gaussian TOF probability distribution.

PET Reconstruction of the Posterior Image Probability, Including Multimodal Images.

In PET image reconstruction, it would be useful to obtain the entire posterior probability distribution of the image, because it allows for both estimating image intensity and assessing the uncertainty of the estimation, thus leading to more reliable interpretation. We propose a new entirely probabilistic model: the prior is a distribution over possible smooth regions (distance-driven Chinese restaurant process), and the posterior distribution is estimated using a Gibbs Markov chain Monte Carlo sampler. Data from other modalities (here one or several MR images) are introduced into the model as additional observed data, providing side information about likely smooth regions in the image. The reconstructed image is the posterior mean, and the uncertainty is presented as an image of the size of 95% posterior intervals. The reconstruction was compared with the maximum-likelihood expectation-maximization and OSEM algorithms, with and without post-smoothing, and with a penalized ML or MAP method that also uses additional images from other modalities. Qualitative and quantitative tests were performed on realistic simulated data with statistical replicates and on several clinical examinations presenting pathologies. The proposed method presents appealing properties in terms of obtained bias, variance, spatial regularization, and use of multimodal data, and produces, in addition, potentially valuable uncertainty information.

CASToR: a generic data organization and processing code framework for multi-modal and multi-dimensional tomographic reconstruction.

In tomographic medical imaging (PET, SPECT, CT), differences in data acquisition and organization are a major hurdle for the development of tomographic reconstruction software. The implementation of a given reconstruction algorithm is usually limited to a specific set of conditions, depending on the modality, the purpose of the study, the input data, or on the characteristics of the reconstruction algorithm itself. It causes restricted or limited use of algorithms, differences in implementation, code duplication, impractical code development, and difficulties for comparing different methods. This work attempts to address these issues by proposing a unified and generic code framework for formatting, processing and reconstructing acquired multi-modal and multi-dimensional data. The proposed iterative framework processes in the same way elements from list-mode (i.e. events) and histogrammed (i.e. sinogram or other bins) data sets. Each element is processed separately, which opens the way for highly parallel execution. A unique iterative algorithm engine makes use of generic core components corresponding to the main parts of the reconstruction process. Features that are specific to different modalities and algorithms are embedded into specific components inheriting from the generic abstract components. Temporal dimensions are taken into account in the core architecture. The framework is implemented in an open-source C++ parallel platform, called CASToR (customizable and advanced software for tomographic reconstruction). Performance assessments show that the time loss due to genericity remains acceptable, being one order of magnitude slower compared to a manufacturer's software optimized for computational efficiency for a given system geometry. Specific optimizations were made possible by the underlying data set organization and processing and allowed for an average speed-up factor ranging from 1.54 to 3.07 when compared to more conventional implementations. Using parallel programming, an almost linear speed-up increase (factor of 0.85 times number of cores) was obtained in a realistic clinical PET setting. In conclusion, the proposed framework offers a substantial flexibility for the integration of new reconstruction algorithms while maintaining computation efficiency.