Rapid quantitative magnetization transfer imaging: Utilizing the hybrid state and the generalized Bloch model

PURPOSE

To explore efficient encoding schemes for quantitative magnetization transfer (qMT) imaging with few constraints on model parameters.

THEORY AND METHODS

We combine two recently proposed models in a Bloch-McConnell equation: the dynamics of the free spin pool are confined to the hybrid state, and the dynamics of the semi-solid spin pool are described by the generalized Bloch model. We numerically optimize the flip angles and durations of a train of radio frequency pulses to enhance the encoding of three qMT parameters while accounting for all eight parameters of the two-pool model. We sparsely sample each time frame along this spin dynamics with a three-dimensional radial koosh-ball trajectory, reconstruct the data with subspace modeling, and fit the qMT model with a neural network for computational efficiency.

RESULTS

We extracted qMT parameter maps of the whole brain with an effective resolution of 1.24 mm from a 12.6-min scan. In lesions of multiple sclerosis subjects, we observe a decreased size of the semi-solid spin pool and longer relaxation times, consistent with previous reports.

CONCLUSION

The encoding power of the hybrid state, combined with regularized image reconstruction, and the accuracy of the generalized Bloch model provide an excellent basis for efficient quantitative magnetization transfer imaging with few constraints on model parameters.

DTI-MR fingerprinting for rapid high-resolution whole-brain T1 , T2 , proton density, ADC, and fractional anisotropy mapping

PURPOSE

This study aims to develop a high-efficiency and high-resolution 3D imaging approach for simultaneous mapping of multiple key tissue parameters for routine brain imaging, including T1 , T2 , proton density (PD), ADC, and fractional anisotropy (FA). The proposed method is intended for pushing routine clinical brain imaging from weighted imaging to quantitative imaging and can also be particularly useful for diffusion-relaxometry studies, which typically suffer from lengthy acquisition time.

METHODS

To address challenges associated with diffusion weighting, such as shot-to-shot phase variation and low SNR, we integrated several innovative data acquisition and reconstruction techniques. Specifically, we used M1-compensated diffusion gradients, cardiac gating, and navigators to mitigate phase variations caused by cardiac motion. We also introduced a data-driven pre-pulse gradient to cancel out eddy currents induced by diffusion gradients. Additionally, to enhance image quality within a limited acquisition time, we proposed a data-sharing joint reconstruction approach coupled with a corresponding sequence design.

RESULTS

The phantom and in vivo studies indicated that the T1 and T2 values measured by the proposed method are consistent with a conventional MR fingerprinting sequence and the diffusion results (including diffusivity, ADC, and FA) are consistent with the spin-echo EPI DWI sequence.

CONCLUSION

The proposed method can achieve whole-brain T1 , T2 , diffusivity, ADC, and FA maps at 1-mm isotropic resolution within 10 min, providing a powerful tool for investigating the microstructural properties of brain tissue, with potential applications in clinical and research settings.

Bi-component dictionary matching for MR fingerprinting for efficient quantification of fat fraction and water T1 in skeletal muscle

PURPOSE

To propose an efficient bi-component MR fingerprinting (MRF) fitting method using a Variable Projection (VARPRO) strategy, applied to the quantification of fat fraction (FF) and water T1 (T 1 H 2 0 $$ \mathrm{T}{1}_{{\mathrm{H}}_20} $$ ) in skeletal muscle tissues.

METHODS

The MRF signals were analyzed in a two-step process by comparing them to the elements of separate water and fat dictionaries (bi-component dictionary matching). First, each pair of water and fat dictionary elements was fitted to the acquired signal to determine an optimal FF that was used to merge the fingerprints in a combined water/fat dictionary. Second, standard dictionary matching was applied to the combined dictionary for determining the remaining parameters. A clustering method was implemented to further accelerate the fitting. Accuracy, precision, and matching time of this approach were evaluated on both numerical and in vivo datasets, and compared to the reference dictionary-matching approach that includes FF as a dictionary parameter.

RESULTS

In numerical phantoms, all MRF parameters showed high correlation with ground truth for the reference and the bi-component method (R2  > 0.98). In vivo, the estimated parameters from the proposed method were highly correlated with those from the reference approach (R2  > 0.997). The bi-component method achieved an acceleration factor of up to 360 compared to the reference dictionary matching.

CONCLUSION

The proposed bi-component fitting approach enables a significant acceleration of the reconstruction of MRF parameter maps for fat-water imaging, while maintaining comparable precision and accuracy to the reference on FF andT 1 H 2 0 $$ \mathrm{T}{1}_{{\mathrm{H}}_20} $$ estimation.

Fast in vivo assay of creatine kinase activity in the human brain by 31 P magnetic resonance fingerprinting

A new and efficient magnetisation transfer 31 P magnetic resonance fingerprinting (MT-31 P-MRF) approach is introduced to measure the creatine kinase metabolic ratek CK between phosphocreatine (PCr) and adenosine triphosphate (ATP) in human brain. The MRF framework is extended to overcome challenges in conventional 31 P measurement methods in the human brain, enabling reduced acquisition time and specific absorption rate (SAR). To address the challenge of creating and matching large multiparametric dictionaries in an MRF scheme, a nested iteration interpolation method (NIIM) is introduced. As the number of parameters to estimate increases, the size of the dictionary grows exponentially. NIIM can reduce the computational load by breaking dictionary matching into subsolutions of linear computational order. MT-31 P-MRF combined with NIIM providesT 1 PCr ,T 1 ATP andk CK estimates in good agreement with those obtained by the exchange kinetics by band inversion transfer (EBIT) method and literature values. Furthermore, the test-retest reproducibility results showed that MT-31 P-MRF achieves a similar or better coefficient of variation (<12%) forT 1 ATP andk CK measurements in 4 min 15 s, than EBIT with 17 min 4 s scan time, enabling a fourfold reduction in scan time. We conclude that MT-31 P-MRF in combination with NIIM is a fast, accurate, and reproducible approach for in vivok CK assays in the human brain, which enables the potential to investigate energy metabolism in a clinical setting.

Repeatability of Quantitative Knee Cartilage T1 , T2 , and T1ρ Mapping With 3D-MRI Fingerprinting

BACKGROUND

Three-dimensional MR fingerprinting (3D-MRF) techniques have been recently described for simultaneous multiparametric mapping of knee cartilage. However, investigation of repeatability remains limited.

PURPOSE

To assess the intra-day and inter-day repeatabilities of knee cartilage T1 , T2 , and T1ρ maps using a 3D-MRF sequence for simultaneous measurement.

STUDY TYPE

Prospective.

SUBJECTS

Fourteen healthy subjects (35.4 ± 9.3 years, eight males), scanned on Day 1 and Day 7.

FIELD STRENGTH/SEQUENCE

3 T/3D-MRF, T1 , T2 , and T1ρ maps.

ASSESSMENT

The acquisition of 3D-MRF cartilage (simultaneous acquisition of T1 , T2 , and T1ρ maps) were acquired using a dictionary pattern-matching approach. Conventional cartilage T1 , T2 , and T1ρ maps were acquired using variable flip angles and a modified 3D-Turbo-Flash sequence with different echo and spin-lock times, respectively, and were fitted using mono-exponential models. Each sequence was acquired on Day 1 and Day 7 with two scans on each day.

STATISTICAL TESTS

The mean and SD for cartilage T1 , T2 , and T1ρ were calculated in five manually segmented regions of interest (ROIs), including lateral femur, lateral tibia, medial femur, medial tibia, and patella cartilages. Intra-subject and inter-subject repeatabilities were assessed using coefficient of variation (CV) and intra-class correlation coefficient (ICC), respectively, on the same day and among different days. Regression and Bland-Altman analysis were performed to compare maps between the conventional and 3D-MRF sequences.

RESULTS

The CV in all ROIs was lower than 7.4%, 8.4%, and 7.5% and the ICC was higher than 0.56, 0.51, and 0.52 for cartilage T1 , T2 , and T1ρ , respectively. The MRF results had a good agreement with the conventional methods with a linear regression slope >0.61 and R2  > 0.59.

CONCLUSION

The 3D-MRF sequence had high intra-subject and inter-subject repeatabilities for simultaneously measuring knee cartilage T1 , T2 , and T1ρ with good agreement with conventional sequences.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 1.

Assessment of MRF for simultaneous T1 and T2 quantification and water-fat separation in the liver at 0.55 T

OBJECTIVE

The goal of this work was to assess the feasibility of performing MRF in the liver on a 0.55 T scanner and to examine the feasibility of water-fat separation using rosette MRF at 0.55 T.

MATERIALS AND METHODS

Spiral and rosette MRF sequences were implemented on a commercial 0.55 T scanner. The accuracy of both sequences in T1 and T2 quantification was validated in the ISMRM/NIST system phantom. The efficacy of rosette MRF in water-fat separation was evaluated in simulations and water/oil phantoms. Both spiral and rosette MRF were performed in the liver of healthy subjects.

RESULTS

In the ISMRM/NIST phantom, both spiral and rosette MRF achieved good agreement with reference values in T1 and T2 measurements. In addition, rosette MRF enables water-fat separation and can generate water- and fat- specific T1 maps, T2 maps, and proton density images from the same dataset for a spatial resolution of 1.56 × 1.56 × 5mm3 within the acquisition time of 15 s.

CONCLUSION

It is feasible to measure T1 and T2 simultaneously in the liver using MRF on a 0.55 T system with lower performance gradients compared to state-of-the-art 1.5 T and 3 T systems within an acquisition time of 15 s. In addition, rosette MRF enables water-fat separation along with T1 and T2 quantification with no time penalty.

MRF: a tool to overcome the barrier of inconsistent genome annotations and perform comparative genomics studies for the largest animal DNA virus

BACKGROUND

The genome of the largest known animal virus, the white spot syndrome virus (WSSV) responsible for huge economic losses and loss of employment in aquaculture, suffers from inconsistent annotation nomenclature. Novel genome sequence, circular genome and variable genome length led to nomenclature inconsistencies. Since vast knowledge has already accumulated in the past two decades with inconsistent nomenclature, the insights gained on a genome could not be easily extendable to other genomes. Therefore, the present study aims to perform comparative genomics studies in WSSV on uniform nomenclature.

METHODS

We have combined the standard mummer tool with custom scripts to develop missing regions finder (MRF) that documents the missing genome regions and coding sequences in virus genomes in comparison to a reference genome and in its annotation nomenclature. The procedure was implemented as web tool and in command-line interface. Using MRF, we have documented the missing coding sequences in WSSV and explored their role in virulence through application of phylogenomics, machine learning models and homologous genes.

RESULTS

We have tabulated and depicted the missing genome regions, missing coding sequences and deletion hotspots in WSSV on a common annotation nomenclature and attempted to link them to virus virulence. It was observed that the ubiquitination, transcription regulation and nucleotide metabolism might be essentially required for WSSV pathogenesis; and the structural proteins, VP19, VP26 and VP28 are essential for virus assembly. Few minor structural proteins in WSSV would act as envelope glycoproteins. We have also demonstrated the advantage of MRF in providing detailed graphic/tabular output in less time and also in handling of low-complexity, repeat-rich and highly similar regions of the genomes using other virus cases.

CONCLUSIONS

Pathogenic virus research benefits from tools that could directly indicate the missing genomic regions and coding sequences between isolates/strains. In virus research, the analyses performed in this study provides an advancement to find the differences between genomes and to quickly identify the important coding sequences/genomes that require early attention from researchers. To conclude, the approach implemented in MRF complements similarity-based tools in comparative genomics involving large, highly-similar, length-varying and/or inconsistently annotated viral genomes.

GPU accelerated grouped magnetic resonance fingerprinting using clustering techniques

Magnetic Resonance Fingerprinting (MRF) is a new quantitative technique of Magnetic Resonance Imaging (MRI). Conventionally, MRF requires sequential correlation of the acquired MRF signals with all the signals of (a large sized) MRF dictionary. This is a computationally intensive matching process and is a major challenge in MRF image reconstruction. This paper introduces the use of clustering techniques (to reduce the effective size of MRF dictionary) by splitting MRF dictionary into multiple small sized MRF dictionary components called MRF signal groups. The proposed method has been further optimized for parallel processing to reduce the computation time of MRF pattern matching. A multi-core GPU based parallel framework has been developed that enables the MRF algorithm to process multiple MRF signals simultaneously. Experiments have been performed on human head and phantom datasets. The results show that the proposed method accelerates the conventional MRF (MATLAB based) reconstruction time up to 25× with single-core CPU implementation, 300× with multi- core CPU implementation and 1035× with the proposed multi-core GPU based framework by keeping the SNR of the resulting images in a clinically acceptable range. Furthermore, experimental results show that the memory requirements of MRF dictionary get significantly reduced (due to efficient memory utilization) in the proposed method.

Obscurant Segmentation in Long Wave Infrared Images Using GLCM Textures

The benefits of autonomous image segmentation are readily apparent in many applications and garners interest from stakeholders in many fields. The wide range of benefits encompass applications ranging from medical diagnosis, where the shape of the grouped pixels increases diagnosis accuracy, to autonomous vehicles where the grouping of pixels defines roadways, traffic signs, other vehicles, etc. It even proves beneficial in many phases of machine learning, where the resulting segmentation can be used as inputs to the network or as labels for training. The majority of the available image segmentation algorithmic development and results focus on visible image modalities. Therefore, in this treatment, the authors present the results of a study designed to identify and improve current semantic methods for infrared scene segmentation. Specifically, the goal is to propose a novel approach to provide tile-based segmentation of occlusion clouds in Long Wave Infrared images. This work complements the collection of well-known semantic segmentation algorithms applicable to thermal images but requires a vast dataset to provide accurate performance. We document performance in applications where the distinction between dust cloud tiles and clear tiles enables conditional processing. Therefore, the authors propose a Gray Level Co-Occurrence Matrix (GLCM) based method for infrared image segmentation. The main idea of our approach is that GLCM features are extracted from local tiles in the image and used to train a binary classifier to provide indication of tile occlusions. Our method introduces a new texture analysis scheme that is more suitable for image segmentation than the solitary Gabor segmentation or Markov Random Field (MRF) scheme. Our experimental results show that our algorithm performs well in terms of accuracy and a better inter-region homogeneity than the pixel-based infrared image segmentation algorithms.

LncRNA MRF drives the regulatory function on monocyte recruitment and polarization through HNRNPD-MCP1 axis in mesenchymal stem cells

Background

Mesenchymal stem cells (MSCs) exhibit two bidirectional immunomodulatory abilities: proinflammatory and anti-inflammatory regulatory effects. Long noncoding RNAs (lncRNAs) have important functions in the immune system. Previously, we performed high-throughput sequencing comparing lncRNA expression profiles between MSCs cocultured with or without CD14+ monocytes and screened out a new lncRNA termed lncRNA MCP1 regulatory factor (MRF). However, the mechanism of MRF in MSCs is still unknown.

Methods

MRF expression was quantified via qRT–PCR. RNA interference and lentiviruses were used to regulate MRF expression. The immunomodulatory effects of MSCs on monocytes were evaluated via monocyte migration and macrophage polarization assays. RNA pull-down and mass spectrometry were utilized to identify downstream factors of MRF. A dual-luciferase reporter assay was applied to analyze the transcription factors regulating MRF. qRT–PCR, western blotting and ELISAs were used to assess MCP1 expression. A human monocyte adoptive transfer mouse model was applied to verify the function of MRF in vivo.

Results

MRF was upregulated in MSCs during coculture with CD14+ monocytes. MRF increased monocyte recruitment by upregulating the expression of monocyte chemotactic protein (MCP1). Knockdown of MRF enhanced the regulatory effect of MSCs on restraining M1 polarization and facilitating M2 polarization. Mechanistically, MRF bound to the downstream protein heterogeneous nuclear ribonucleoprotein D (HNRNPD) to upregulate MCP1 expression, and the transcription factor interferon regulatory factor 1 (IRF1) activated MRF transcription early during coculture. The human monocyte adoptive transfer model showed that MRF downregulation in MSCs inhibited monocyte chemotaxis and enhanced the effects of MSCs to inhibit M1 macrophage polarization and promote M2 polarization in vivo.

Conclusion

We identified the new lncRNA MRF, which exhibits proinflammatory characteristics. MRF regulates the ability of MSCs to accelerate monocyte recruitment and modulate macrophage polarization through the HNRNPD-MCP1 axis and initiates the proinflammatory regulatory process in MSCs, suggesting that MRF is a potential target to improve the clinical effect of MSC-based therapy or correct MSC-related immunomodulatory dysfunction under pathological conditions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12929-022-00858-3.

PortiK: A computer vision based solution for real-time automatic solid waste characterization - Application to an aluminium stream

In Material Recovery Facilities (MRFs), recyclable municipal solid waste is turned into a precious commodity. However, effective recycling relies on effective waste sorting, which is still a challenge to sustainable development of our society. To help the operations improve and optimise their process, this paper describes PortiK, a solution for automatic waste analysis. Based on image analysis and object recognition, it allows for continuous, real-time, non-intrusive measurements of mass composition of waste streams. The end-to-end solution is detailed with all the steps necessary for the system to operate, from hardware specifications and data collection to supervisory information obtained by deep learning and statistical analysis. The overall system was tested and validated in an operational environment in a material recovery facility. PortiK monitored an aluminium can stream to estimate its purity. Aluminium cans were detected with 91.2% precision and 90.3% recall, respectively, resulting in an underestimation of the number of cans by less than 1%. Regarding contaminants (i.e. other types of waste), precision and recall were 80.2% and 78.4%, respectively, giving an 2.2% underestimation. Based on five sample analyses where pieces of waste were counted and weighed per batch, the detection results were used to estimate purity and its confidence level. The estimation error was calculated to be within ±7% after 5 minutes of monitoring and ±5% after 8 hours. These results have demonstrated the feasibility and the relevance of the proposed solution for online quality control of aluminium can stream.

Simultaneous 3D acquisition of 1 H MRF and 23 Na MRI

PURPOSE

To develop a 3D MR technique to simultaneously acquire proton multiparametric maps (T₁ , T₂ , and proton density) and sodium density weighted images over the whole brain.

METHODS

We implemented a 3D stack-of-stars MR pulse sequence which consists of interleaved proton (¹ H) and sodium (²³ Na) excitations, tailored slice encoding gradients that can encode the same slice for both nuclei, and simultaneous readout with different radial trajectories (¹ H, full-radial; ²³ Na, center-out radial). The receive chain of our 7T scanner was modified to enable simultaneous acquisition of ¹ H and ²³ Na signal. A heuristically optimized flip angle train was implemented for proton MR fingerprinting (MRF). The SNR and the accuracy of proton T₁ and T₂ were evaluated in phantoms. Finally, in vivo application of the method was demonstrated in five healthy subjects.

RESULTS

The SNR for the simultaneous measurement was almost identical to that for the single-nucleus measurements (<2% change). The proton T₁ and T₂ maps remained similar to the results from a reference 2D MRF technique (normalized RMS error in T₁ ≈ 4.2% and T₂ ≈ 11.3%). Measurements in healthy subjects corroborated these results and demonstrated the feasibility of our method for in vivo application. The in vivo T₁ values measured using our method were lower than the results measured by other conventional techniques.

CONCLUSIONS

With the 3D simultaneous implementation, we were able to acquire sodium and proton density weighted images in addition to proton T₁ , T₂ , and B1+ from ¹ H MRF that covers the whole brain volume within 21 min.

Optimized multi-axis spiral projection MR fingerprinting with subspace reconstruction for rapid whole-brain high-isotropic-resolution quantitative imaging

PURPOSE

To improve image quality and accelerate the acquisition of 3D MR fingerprinting (MRF).

METHODS

Building on the multi-axis spiral-projection MRF technique, a subspace reconstruction with locally low-rank constraint and a modified spiral-projection spatiotemporal encoding scheme called tiny golden-angle shuffling were implemented for rapid whole-brain high-resolution quantitative mapping. Reconstruction parameters such as the locally low-rank regularization parameter and the subspace rank were tuned using retrospective in vivo data and simulated examinations. B₀ inhomogeneity correction using multifrequency interpolation was incorporated into the subspace reconstruction to further improve the image quality by mitigating blurring caused by off-resonance effect.

RESULTS

The proposed MRF acquisition and reconstruction framework yields high-quality 1-mm isotropic whole-brain quantitative maps in 2 min at better quality compared with 6-min acquisitions of prior approaches. The proposed method was validated to not induce bias in T₁ and T₂ mapping. High-quality whole-brain MRF data were also obtained at 0.66-mm isotropic resolution in 4 min using the proposed technique, where the increased resolution was shown to improve visualization of subtle brain structures.

CONCLUSIONS

The proposed tiny golden-angle shuffling, MRF with optimized spiral-projection trajectory and subspace reconstruction enables high-resolution quantitative mapping in ultrafast acquisition time.

Master regulators of skeletal muscle lineage development and pluripotent stem cells differentiation

In vertebrates, the skeletal muscles of the body and their associated stem cells originate from muscle progenitor cells, during development. The specification of the muscles of the trunk, head and limbs, relies on the activity of distinct genetic hierarchies. The major regulators of trunk and limb muscle specification are the paired-homeobox transcription factors PAX3 and PAX7. Distinct gene regulatory networks drive the formation of the different muscles of the head. Despite the redeployment of diverse upstream regulators of muscle progenitor differentiation, the commitment towards the myogenic fate requires the expression of the early myogenic regulatory factors MYF5, MRF4, MYOD and the late differentiation marker MYOG. The expression of these genes is activated by muscle progenitors throughout development, in several waves of myogenic differentiation, constituting the embryonic, fetal and postnatal phases of muscle growth. In order to achieve myogenic cell commitment while maintaining an undifferentiated pool of muscle progenitors, several signaling pathways regulate the switch between proliferation and differentiation of myoblasts. The identification of the gene regulatory networks operating during myogenesis is crucial for the development of in vitro protocols to differentiate pluripotent stem cells into myoblasts required for regenerative medicine.

Toward magnetic resonance fingerprinting for low-field MR-guided radiation therapy

PURPOSE

The acquisition of multiparametric quantitative magnetic resonance imaging (qMRI) is becoming increasingly important for functional characterization of cancer prior to- and throughout the course of radiation therapy. The feasibility of a qMRI method known as magnetic resonance fingerprinting (MRF) for rapid T₁ and T₂ mapping was assessed on a low-field MR-linac system.

METHODS

A three-dimensional MRF sequence was implemented on a 0.35T MR-guided radiotherapy system. MRF-derived measurements of T₁ and T₂ were compared to those obtained with gold standard single spin echo methods, and the impacts of the radiofrequency field homogeneity and scan times ranging between 6 and 48 min were analyzed by acquiring between 1 and 8 spokes per time point in a standard quantitative system phantom. The short-term repeatability of MRF was assessed over three measurements taken over a 10-h period. To evaluate transferability, MRF measurements were acquired on two additional MR-guided radiotherapy systems. Preliminary human volunteer studies were performed.

RESULTS

The phantom benchmarking studies showed that MRF is capable of mapping T₁ and T₂ values within 8% and 10% of gold standard measures, respectively, at 0.35T. The coefficient of variation of T₁ and T₂ estimates over three repeated scans was < 5% over a broad range of relaxation times. The T₁ and T₂ times derived using a single-spoke MRF acquisition across three scanners were near unity and mean percent errors in T₁ and T₂ estimates using the same phantom were < 3%. The mean percent differences in T₁ and T₂ as a result of truncating the scan time to 6 min over the large range of relaxation times in the system phantom were 0.65% and 4.05%, respectively.

CONCLUSIONS

The technical feasibility and accuracy of MRF on a low-field MR-guided radiation therapy device has been demonstrated. MRF can be used to measure accurate T₁ and T₂ maps in three dimensions from a brief 6-min scan, offering strong potential for efficient and reproducible qMRI for future clinical trials in functional plan adaptation and tumor/normal tissue response assessment.

Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology

Omics methodologies are widely used in toxicological research to understand modes and mechanisms of toxicity. Increasingly, these methodologies are being applied to questions of regulatory interest such as molecular point-of-departure derivation and chemical grouping/read-across. Despite its value, widespread regulatory acceptance of omics data has not yet occurred. Barriers to the routine application of omics data in regulatory decision making have been: 1) lack of transparency for data processing methods used to convert raw data into an interpretable list of observations; and 2) lack of standardization in reporting to ensure that omics data, associated metadata and the methodologies used to generate results are available for review by stakeholders, including regulators. Thus, in 2017, the Organisation for Economic Co-operation and Development (OECD) Extended Advisory Group on Molecular Screening and Toxicogenomics (EAGMST) launched a project to develop guidance for the reporting of omics data aimed at fostering further regulatory use. Here, we report on the ongoing development of the first formal reporting framework describing the processing and analysis of both transcriptomic and metabolomic data for regulatory toxicology. We introduce the modular structure, content, harmonization and strategy for trialling this reporting framework prior to its publication by the OECD.

What is the optimal schedule for multiparametric MRS? A magnetic resonance fingerprinting perspective

Clinical magnetic resonance spectroscopy (MRS) mainly concerns itself with the quantification of metabolite concentrations. Metabolite relaxation values, which reflect the microscopic state of specific cellular and sub-cellular environments, could potentially hold additional valuable information, but are rarely acquired within clinical scan times. By varying the flip angle, repetition time and echo time in a preset way (termed a schedule), and matching the resulting signals to a pre-generated dictionary - an approach dubbed magnetic resonance fingerprinting - it is possible to encode the spins' relaxation times into the acquired signal, simultaneously quantifying multiple tissue parameters for each metabolite. Herein, we optimized the schedule to minimize the averaged root mean square error (RMSE) across all estimated parameters: concentrations, longitudinal and transverse relaxation time, and transmitter inhomogeneity. The optimal schedules were validated in phantoms and, subsequently, in a cohort of healthy volunteers, in a 4.5 mL parietal white matter single voxel and an acquisition time under 5 minutes. The average intra-subject, inter-scan coefficients of variation (CVs) for metabolite concentrations, T₁ and T₂ relaxation times were found to be 3.4%, 4.6% and 4.7% in-vivo, respectively, averaged over all major singlets. Coupled metabolites were quantified using the short echo time schedule entries and spectral fitting, and reliable estimates of glutamate+glutamine, glutathione and myo-inositol were obtained.

Bayesian uncertainty quantification for magnetic resonance fingerprinting

Magnetic Resonance Fingerprinting (MRF) is a promising technique for fast quantitative imaging of human tissue. In general, MRF is based on a sequence of highly undersampled MR images which are analyzed with a pre-computed dictionary. MRF provides valuable diagnostic parameters such as the $T_1$ and $T_2$ MR relaxation times. However, uncertainty characterization of dictionary-based MRF estimates for $T_1$ and $T_2$ has not been achieved so far, which makes it challenging to assess if observed differences in these estimates are significant and may indicate pathological changes of the underlying tissue. We propose a Bayesian approach for the uncertainty quantification of dictionary-based MRF which leads to probability distributions for $T_1$ and $T_2$ in every voxel. The distributions can be used to make probability statements about the relaxation times, and to assign uncertainties to their dictionary-based MRF estimates. All uncertainty calculations are based on the pre-computed dictionary and the observed sequence of undersampled MR images, and they can be calculated in short time. The approach is explored by analyzing MRF measurements of a phantom consisting of several tubes across which MR relaxation times are constant. The proposed uncertainty quantification is quantitatively consistent with the observed within-tube variability of estimated relaxation times. Furthermore, calculated uncertainties are shown to characterize well observed differences between the MRF estimates and the results obtained from high-accurate reference measurements. These findings indicate that a reliable uncertainty quantification is achieved. We also present results for simulated MRF data and an uncertainty quantification for an in vivo MRF measurement. MATLAB$^{\scriptsize \text{\textregistered}}$ source code implementing the proposed approach is made available.

Quantitative Skeletal Muscle Imaging Using 3D MR Fingerprinting With Water and Fat Separation

BACKGROUND

Quantitative muscle MRI is a robust tool to monitor intramuscular fatty replacement and disease activity in patients with neuromuscular disorders (NMDs).

PURPOSE

To implement a 3D sequence for quantifying simultaneously fat fraction (FF) and water T₁ (T_1,H2O ) in the skeletal muscle, evaluate regular undersampling in the partition-encoding direction, and compare it to a recently proposed 2D MR fingerprinting sequence with water and fat separation (MRF T₁ -FF).

STUDY TYPE

Prospective.

PHANTOM/SUBJECTS

Seventeen-vial phantom at different FF and T_1,H2O , 11 healthy volunteers, and 6 subjects with different NMDs.

FIELD STRENGTH/SEQUENCE

3T/3D MRF T₁ -FF, 2D MRF T₁ -FF, STEAM MRS ASSESSMENT: FF and T_1,H2O measured with the 2D and 3D sequences were compared in the phantom and in vivo at different undersampling factors (US). Data were acquired in healthy subjects before and after plantar dorsiflexions and at rest in patients.

STATISTICAL TESTS

Linear correlations, Bland-Altman analysis, two-way repeated measures analysis of variance (ANOVA), Student's t-test.

RESULTS

Up to a US factor of 3, the undersampled acquisitions were in good agreement with the fully sampled sequence (R²  ≥ 0.98, T_1,H2O bias ≤10 msec, FF bias ≤4 × 10^-4 ) both in phantom and in vivo. The 2D and 3D MRF T₁ -FF sequences provided comparable T_1,H2O and FF values (R²  ≥ 0.95, absolute T_1,H2O bias ≤35 msec, and absolute FF bias ≤0.003). The plantar dorsiflexion induced a significant increase of T_1,H2O in the tibialis anterior and extensor digitorum (relative increase of +10.8 ± 1.7% and + 7.7 ± 1.4%, respectively, P < 0.05), that was accompanied by a significant reduction of FF in the tibialis anterior (relative decrease of -16.3 ± 4.0%, P < 0.05). Some subjects with NMDs presented increased and heterogeneous T_1,H2O and FF values throughout the leg.

DATA CONCLUSION

Quantitative 3D T_1,H2O and FF maps covering the entire leg were obtained within acquisition times compatible with clinical research (4 minutes 20 seconds) and a 1 × 1 × 5 mm³ spatial resolution.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 2.

Improved MR fingerprinting for relaxation measurement in the presence of semisolid magnetization transfer

PURPOSE

To characterize and minimize the magnetization transfer (MT) effect in MR fingerprinting (MRF) relaxation measurements with a 2-pool (2P) MT model of multiple tissue types.

THEORY AND METHODS

Semisolid MT effect in MRF was modeled using 2P Bloch-McConnell equations. The combinations of MT parameters of multiple tissues (white [WM] and gray matter [GM]) were used to build the MRF dictionary. Both 1-pool (1P) and 2P models were simulated to characterize the dependence on MT. Relaxations measured using MRF with spin-echo saturation-recovery (SR) or inversion-recovery preparations were compared with conventional SR-prepared T1 and multiple spin-echo T2 measurements. The simulations results were validated with phantoms and brain tissue samples.

RESULTS

The MRF signal was different from the 1P and 2P models. 1P MRF produced significantly (P < .05) underestimated T1 in WM (20-30%) and GM (7-10%), while 2P MRF measured consistent T1 and T2 in both WM and GM with conventional measurements (pairwise test P > .1; correlated P < .05). Simulations showed that SR-prepared MRF measuring T1 had much less errors against the variation of the macromolecular fraction. Compared with inversion-recovery preparation, SR-prepared MRF produced higher relaxation correlations (R > 0.9) with conventional measurements in both WM and GM across samples, suggesting that SR-prepared MRF was less sensitive to the compositive effect of multiple MT parameters variations.

CONCLUSIONS

2P MRF using a combination of MT parameters for multiple tissue types can measure consistent relaxations with conventional methods. With the 2P models, SR-prepared MRF would provide an option for robust relaxation measurement under heterogeneous MT.

Semantic-Based Building Extraction from LiDAR Point Clouds Using Contexts and Optimization in Complex Environment

The extraction of buildings has been an essential part of the field of LiDAR point clouds processing in recent years. However, it is still challenging to extract buildings from huge amount of point clouds due to the complicated and incomplete structures, occlusions and local similarities between different categories in a complex environment. Taking the urban and campus scene as examples, this paper presents a versatile and hierarchical semantic-based method for building extraction using LiDAR point clouds. The proposed method first performs a series of preprocessing operations, such as removing ground points, establishing super-points and using them as primitives for subsequent processing, and then semantically labels the raw LiDAR data. In the feature engineering process, considering the purpose of this article is to extract buildings, we tend to choose the features extracted from super-points that can describe building for the next classification. There are a portion of inaccurate labeling results due to incomplete or overly complex scenes, a Markov Random Field (MRF) optimization model is constructed for postprocessing and segmentation results refinement. Finally, the buildings are extracted from the labeled points. Experimental verification was performed on three datasets in different scenes, our results were compared with the state-of-the-art methods. These evaluation results demonstrate the feasibility and effectiveness of the proposed method for extracting buildings from LiDAR point clouds in multiple environments.

Simultaneous proton magnetic resonance fingerprinting and sodium MRI

PURPOSE

The goal of this work is to demonstrate a method for the simultaneous acquisition of proton multiparametric maps (T1 , T2 , and proton density) and sodium density images in 1 single scan. We hope that the development of such capabilities will help to ease the implementation of sodium MRI in clinical trials and provide more opportunities for researchers to investigate metabolism through sodium MRI.

METHODS

We developed a sequence based on magnetic resonance fingerprinting (MRF), which contains interleaved proton (1 H) and sodium (23 Na) excitations followed by a simultaneous center-out radial readout for both nuclei. The receive chain of a 7T scanner was modified to enable simultaneous acquisition of 1 H and 23 Na signal. The obtained signal-to-noise ratio (SNR) was evaluated, and the accuracy of both proton T1 , T2 , and B 1 + and sodium density maps were verified in phantoms. Finally, the method was demonstrated in 2 healthy subjects.

RESULTS

The SNR obtained using the simultaneous measurement was almost identical to single-nucleus measurements (<1% change). Similarly, the proton T1 and T2 maps remained stable (normalized root mean square error in T1 ≈ 2.2%, in T2 ≈ 1.4%, and B 1 + ≈ 5.4%), which indicates that the proposed sequence and hardware have no significant effects on the signal from either nucleus. In vivo measurements corroborated these results and demonstrated the feasibility of our method for in vivo application.

CONCLUSIONS

With the proposed approach, we were able to simultaneously acquire sodium density images in addition to proton T1 , T2 , and B 1 + maps as well as proton density images.

A Perspective on MR Fingerprinting

This article reviews the basic concept of MR fingerprinting (MRF) with the goal of highlighting MRF's key contributions, putting them in the context of other quantitative MRI literature, and refining MRF's terminology. The article discusses the robustness and flexibility of MRF's signature dictionary-matching reconstruction along with more advanced MRF reconstructions. A key feature of MRF is the lack of assumptions about the signal evolution, which gives scientists the flexibility to tailor sequences for their needs. The article argues that the concept of unique fingerprints does not capture the requirements for successful parameter mapping and that an analysis of the signal's derivatives with respect to biophysical parameters, such as relaxation times, is more informative, as it allows one to evaluate the efficiency of a pulse sequence. The article points at the source of MRF's efficiency, namely, flip angle variations at the time scale of the relaxation times, and reveals that MRF's advantages are strongest at long scan times, as required for 3D imaging. Further, it outlines how MRF's flexibility can be used to design mutually tailored pulse sequences and biophysical models with the goal of improving the reproducibility of parameter mapping biological tissue. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 1.

MR fingerprinting for water T1 and fat fraction quantification in fat infiltrated skeletal muscles

PURPOSE

To develop a fast MR fingerprinting (MRF) sequence for simultaneous estimation of water T1 (T1_H2O ) and fat fraction (FF) in fat infiltrated skeletal muscles.

METHODS

The MRF sequence for T1_H2O and FF quantification (MRF T1-FF) comprises a 1400 radial spokes echo train, following nonselective inversion, with varying echo and repetition time, as well as prescribed flip angle. Undersampled frames were reconstructed at different acquisition time-points by nonuniform Fourier transform, and a bi-component model based on Bloch simulations applied to adjust the signal evolution and extract T1_H2O and FF. The sequence was validated on a multi-vial phantom, in three healthy volunteers and five patients with neuromuscular diseases. We evaluated the agreement between MRF T1-FF parameters and reference values and confounding effects due to B0 and B1 inhomogeneities.

RESULTS

In phantom, T1_H2O and FF were highly correlated with references values measured with multi-inversion time inversion recovery-stimulated echo acquisition mode and Dixon, respectively (R² > 0.99). In vivo, T1_H2O and FF determined by the MRF T1-FF sequence were also correlated with reference values (R² = 0.98 and 0.97, respectively). The precision on T1_H2O was better than 5% for muscles where FF was less than 0.4. Both T1_H2O and FF values were not confounded by B0 nor B1 inhomogeneities.

CONCLUSION

The MRF T1-FF sequence derived T1_H2O and FF values in voxels containing a mixture of water and fat protons. This method can be used to comprehend and characterize the effects of tissue water compartmentation and distribution on muscle T1 values in patients affected by chronic fat infiltration.

Regulation and evolution of muscle development in tunicates

For more than a century, studies on tunicate muscle formation have revealed many principles of cell fate specification, gene regulation, morphogenesis, and evolution. Here, we review the key studies that have probed the development of all the various muscle cell types in a wide variety of tunicate species. We seize this occasion to explore the implications and questions raised by these findings in the broader context of muscle evolution in chordates.

Optimized quantification of spin relaxation times in the hybrid state

PURPOSE

The optimization and analysis of spin ensemble trajectories in the hybrid state-a state in which the direction of the magnetization adiabatically follows the steady state while the magnitude remains in a transient state.

METHODS

Numerical optimizations were performed to find spin ensemble trajectories that minimize the Cramér-Rao bound for T 1 -encoding, T 2 -encoding, and their weighted sum, respectively, followed by a comparison between the Cramér-Rao bounds obtained with our optimized spin-trajectories, Look-Locker sequences, and multi-spin-echo methods. Finally, we experimentally tested our optimized spin trajectories with in vivo scans of the human brain.

RESULTS

After a nonrecurring inversion segment on the southern half of the Bloch sphere, all optimized spin trajectories pursue repetitive loops on the northern hemisphere in which the beginning of the first and the end of the last loop deviate from the others. The numerical results obtained in this work align well with intuitive insights gleaned directly from the governing equation. Our results suggest that hybrid-state sequences outperform traditional methods. Moreover, hybrid-state sequences that balance T 1 - and T 2 -encoding still result in near optimal signal-to-noise efficiency for each relaxation time. Thus, the second parameter can be encoded at virtually no extra cost.

CONCLUSIONS

We provided new insights into the optimal encoding processes of spin relaxation times in order to guide the design of robust and efficient pulse sequences. We found that joint acquisitions of T 1 and T 2 in the hybrid state are substantially more efficient than sequential encoding techniques.

The application of magnetic resonance fingerprinting to single voxel proton spectroscopy

Magnetic resonance fingerprinting has been proposed as a method for undersampling k-space while simultaneously yielding multiparametric tissue maps. In the context of single voxel spectroscopy, fingerprinting can provide a unified framework for parameter estimation. We demonstrate the utility of such a magnetic resonance spectroscopic fingerprinting (MRSF) framework for simultaneously quantifying metabolite concentrations, T₁ and T₂ relaxation times and transmit inhomogeneity for major singlets of N-acetylaspartate, creatine and choline. This is achieved by varying T_R , T_E and the flip angle of the first pulse in a PRESS sequence between successive excitations (i.e. successive T_R values). The need for multiparametric schemes such as MRSF for accurate medical diagnostics is demonstrated with the aid of realistic in vivo simulations; these show that certain schemes lead to substantial increases to the area under receiver operating characteristics of metabolite concentrations, when viewed as classifiers of pathologies. Numerical simulations and phantom and in vivo experiments using several different schedules of variable length demonstrate superior precision and accuracy for metabolite concentrations and longitudinal relaxation, and similar performance for the quantification of transverse relaxation.

Chemical exchange saturation transfer fingerprinting for exchange rate quantification

PURPOSE

There is an increased interest to determine the exchange rate using CEST to provide pH information. However, current CEST quantification methods require lengthy scan times and do not address magnetization transfer effects. The purpose of this work was to apply the magnetic resonance fingerprinting (MRF) concept to CEST to achieve more efficient and accurate exchange rate quantification.

METHODS

The proposed CEST fingerprinting method used varying saturation powers and saturation times to create unique signal evolutions for different exchange rates. The acquired signal was matched to a predefined dictionary to determine the exchange rate. The magnetization transfer effects were also addressed in the framework of CEST fingerprinting: The simulated dictionary could predict the signal curves without magnetization transfer effects, and comparing the dictionary to the acquired signals allowed the correction of the magnetization transfer effects. The CEST fingerprinting method was compared with the conventional pulsed quantitative CEST method using omega plots in the creatine phantom study.

RESULTS

The CEST fingerprinting method has a significantly reduced scan time (10 minutes versus 50 minutes) while providing more accurate exchange rate quantification using literature values as the reference.

CONCLUSION

In this study, we demonstrate that CEST fingerprinting is more efficient (5 times faster) compared with pulsed quantitative CEST. It is also shown that the results of the proposed CEST fingerprinting technique are much closer to the literature values than pulsed quantitative CEST at 3 T.

Zinc depletion induces ribosome hibernation in mycobacteria

Mycobacteria as well as other bacteria remodel their ribosomes in response to zinc depletion by replacing zinc-binding ribosomal proteins with zinc-free paralogues, releasing zinc for other metabolic processes. In this study, we show that the remodeled ribosome acquires a structurally stable but functionally inactive and aminoglycoside-resistant state in zinc-starved Mycobacterium smegmatis. Conversely, M. smegmatis cells that are growth arrested in zinc-rich conditions have unstable ribosomes and reduced survival. We further provide evidence for ribosome remodeling in Mycobacterium tuberculosis in host tissues, suggesting that ribosome hibernation occurs during TB infections. Our findings could offer insights into mechanisms of persistence and antibiotic tolerance of mycobacterial infections.

Bacteria respond to zinc starvation by replacing ribosomal proteins that have the zinc-binding CXXC motif (C+) with their zinc-free (C−) paralogues. Consequences of this process beyond zinc homeostasis are unknown. Here, we show that the C− ribosome in Mycobacterium smegmatis is the exclusive target of a bacterial protein Y homolog, referred to as mycobacterial-specific protein Y (MPY), which binds to the decoding region of the 30S subunit, thereby inactivating the ribosome. MPY binding is dependent on another mycobacterial protein, MPY recruitment factor (MRF), which is induced on zinc depletion, and interacts with C− ribosomes. MPY binding confers structural stability to C− ribosomes, promoting survival of growth-arrested cells under zinc-limiting conditions. Binding of MPY also has direct influence on the dynamics of aminoglycoside-binding pockets of the C− ribosome to inhibit binding of these antibiotics. Together, our data suggest that zinc limitation leads to ribosome hibernation and aminoglycoside resistance in mycobacteria. Furthermore, our observation of the expression of the proteins of C− ribosomes in Mycobacterium tuberculosis in a mouse model of infection suggests that ribosome hibernation could be relevant in our understanding of persistence and drug tolerance of the pathogen encountered during chemotherapy of TB.

Low-rank magnetic resonance fingerprinting

PURPOSE

Magnetic resonance fingerprinting (MRF) is a relatively new approach that provides quantitative MRI measures using randomized acquisition. Extraction of physical quantitative tissue parameters is performed offline, without the need of patient presence, based on acquisition with varying parameters and a dictionary generated according to the Bloch equation simulations. MRF uses hundreds of radio frequency (RF) excitation pulses for acquisition, and therefore, a high undersampling ratio in the sampling domain (k-space) is required for reasonable scanning time. This undersampling causes spatial artifacts that hamper the ability to accurately estimate the tissue's quantitative values. In this work, we introduce a new approach for quantitative MRI using MRF, called magnetic resonance fingerprinting with low rank (FLOR).

METHODS

We exploit the low-rank property of the concatenated temporal imaging contrasts, on top of the fact that the MRF signal is sparsely represented in the generated dictionary domain. We present an iterative recovery scheme that consists of a gradient step followed by a low-rank projection using the singular value decomposition.

RESULTS

Experimental results consist of retrospective sampling that allows comparison to a well defined reference, and prospective sampling that shows the performance of FLOR for a real-data sampling scenario. Both experiments demonstrate improved parameter accuracy compared to other compressed-sensing and low-rank based methods for MRF at 5% and 9% sampling ratios for the retrospective and prospective experiments, respectively.

CONCLUSIONS

We have shown through retrospective and prospective experiments that by exploiting the low-rank nature of the MRF signal, FLOR recovers the MRF temporal undersampled images and provides more accurate parameter maps compared to previous iterative approaches.

Low rank alternating direction method of multipliers reconstruction for MR fingerprinting

PURPOSE

The proposed reconstruction framework addresses the reconstruction accuracy, noise propagation and computation time for magnetic resonance fingerprinting.

METHODS

Based on a singular value decomposition of the signal evolution, magnetic resonance fingerprinting is formulated as a low rank (LR) inverse problem in which one image is reconstructed for each singular value under consideration. This LR approximation of the signal evolution reduces the computational burden by reducing the number of Fourier transformations. Also, the LR approximation improves the conditioning of the problem, which is further improved by extending the LR inverse problem to an augmented Lagrangian that is solved by the alternating direction method of multipliers. The root mean square error and the noise propagation are analyzed in simulations. For verification, in vivo examples are provided.

RESULTS

The proposed LR alternating direction method of multipliers approach shows a reduced root mean square error compared to the original fingerprinting reconstruction, to a LR approximation alone and to an alternating direction method of multipliers approach without a LR approximation. Incorporating sensitivity encoding allows for further artifact reduction.

CONCLUSION

The proposed reconstruction provides robust convergence, reduced computational burden and improved image quality compared to other magnetic resonance fingerprinting reconstruction approaches evaluated in this study. Magn Reson Med 79:83-96, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Phase unwinding for dictionary compression with multiple channel transmission in magnetic resonance fingerprinting

PURPOSE

Magnetic Resonance Fingerprinting reconstructions can become computationally intractable with multiple transmit channels, if the B₁⁺ phases are included in the dictionary. We describe a general method that allows to omit the transmit phases. We show that this enables straightforward implementation of dictionary compression to further reduce the problem dimensionality.

METHODS

We merged the raw data of each RF source into a single k-space dataset, extracted the transceiver phases from the corresponding reconstructed images and used them to unwind the phase in each time frame. All phase-unwound time frames were combined in a single set before performing SVD-based compression. We conducted synthetic, phantom and in-vivo experiments to demonstrate the feasibility of SVD-based compression in the case of two-channel transmission.

RESULTS

Unwinding the phases before SVD-based compression yielded artifact-free parameter maps. For fully sampled acquisitions, parameters were accurate with as few as 6 compressed time frames. SVD-based compression performed well in-vivo with highly under-sampled acquisitions using 16 compressed time frames, which reduced reconstruction time from 750 to 25min.

CONCLUSION

Our method reduces the dimensions of the dictionary atoms and enables to implement any fingerprint compression strategy in the case of multiple transmit channels.

DNA-binding domain of myelin-gene regulatory factor: purification, crystallization and X-ray analysis. Corrigendum

An extra affiliation is added for the authors of the article by Wu et al. [(2017), Acta Cryst. F73, 393-397].

Comparison of image intensity, local, and multi-atlas priors in brain tissue classification

PURPOSE

Automated and accurate tissue classification in three-dimensional brain magnetic resonance images is essential in volumetric morphometry or as a preprocessing step for diagnosing brain diseases. However, noise, intensity in homogeneity, and partial volume effects limit the classification accuracy of existing methods. This paper provides a comparative study on the contributions of three commonly used image information priors for tissue classification in normal brains: image intensity, local, and multi-atlas priors.

METHODS

We compared the effectiveness of the three priors by comparing the four methods modeling them: K-Means (KM), KM combined with a Markov Random Field (KM-MRF), multi-atlas segmentation (MAS), and the combination of KM, MRF, and MAS (KM-MRF-MAS). The key parameters and factors in each of the four methods are analyzed, and the performance of all the models is compared quantitatively and qualitatively on both simulated and real data.

RESULTS

The KM-MRF-MAS model that combines the three image information priors performs best.

CONCLUSIONS

The image intensity prior is insufficient to generate reasonable results for a few images. Introducing local and multi-atlas priors results in improved brain tissue classification. This study provides a general guide on what image information priors can be used for effective brain tissue classification.

A supervoxel based random forest synthesis framework for bidirectional MR/CT synthesis

Synthesizing magnetic resonance (MR) and computed tomography (CT) images (from each other) has important implications for clinical neuroimaging. The MR to CT direction is critical for MRI-based radiotherapy planning and dose computation, whereas the CT to MR direction can provide an economic alternative to real MRI for image processing tasks. Additionally, synthesis in both directions can enhance MR/CT multi-modal image registration. Existing approaches have focused on synthesizing CT from MR. In this paper, we propose a multi-atlas based hybrid method to synthesize T1-weighted MR images from CT and CT images from T1-weighted MR images using a common framework. The task is carried out by: (a) computing a label field based on supervoxels for the subject image using joint label fusion; (b) correcting this result using a random forest classifier (RF-C); (c) spatial smoothing using a Markov random field; (d) synthesizing intensities using a set of RF regressors, one trained for each label. The algorithm is evaluated using a set of six registered CT and MR image pairs of the whole head.

DNA-binding domain of myelin-gene regulatory factor: purification, crystallization and X-ray analysis

The myelin sheath, which envelops axons in the vertebrate central nervous system, is crucial for the rapid conduction of action potentials. Myelin-gene regulatory factor (MRF) is a recently identified transcription factor that is required for myelin-sheath formation. Loss of MRF leads to demyelinating diseases and motor learning deficiency. MRF is a membrane-bound transcription factor that undergoes autocleavage from the endoplasmic reticulum membrane. The N-terminus of MRF contains a DNA-binding domain (DBD) that functions as a homotrimer. In this study, the MRF DBD was cloned, purified and crystallized in order to understand the molecular mechanism that regulates the transcription of myelin genes. Selenomethionine was subsequently introduced into the crystals to obtain the phases for the MRF DBD structure. The native and selenomethionine-labelled crystals exhibited diffraction to 2.50 and 2.51 Å resolution, respectively. The crystals belonged to space group P321 and the selenomethionine-labelled crystals had unit-cell parameters a = 104.0, b = 104.0, c = 46.7 Å, α = 90, β = 90, γ = 120°. The calculated Matthews coefficient was 3.04 Å3 Da-1 and the solvent content was 59.5%, indicating the presence of one MRF DBD molecule in the asymmetric unit.

Ascl2 inhibits myogenesis by antagonizing the transcriptional activity of myogenic regulatory factors

Myogenic regulatory factors (MRFs), including Myf5, MyoD (Myod1) and Myog, are muscle-specific transcription factors that orchestrate myogenesis. Although MRFs are essential for myogenic commitment and differentiation, timely repression of their activity is necessary for the self-renewal and maintenance of muscle stem cells (satellite cells). Here, we define Ascl2 as a novel inhibitor of MRFs. During mouse development, Ascl2 is transiently detected in a subpopulation of Pax7⁺ MyoD⁺ progenitors (myoblasts) that become Pax7⁺ MyoD^- satellite cells prior to birth, but is not detectable in postnatal satellite cells. Ascl2 knockout in embryonic myoblasts decreases both the number of Pax7⁺ cells and the proportion of Pax7⁺ MyoD^- cells. Conversely, overexpression of Ascl2 inhibits the proliferation and differentiation of cultured myoblasts and impairs the regeneration of injured muscles. Ascl2 competes with MRFs for binding to E-boxes in the promoters of muscle genes, without activating gene transcription. Ascl2 also forms heterodimers with classical E-proteins to sequester their transcriptional activity on MRF genes. Accordingly, MyoD or Myog expression rescues myogenic differentiation despite Ascl2 overexpression. Ascl2 expression is regulated by Notch signaling, a key governor of satellite cell self-renewal. These data demonstrate that Ascl2 inhibits myogenic differentiation by targeting MRFs and facilitates the generation of postnatal satellite cells.

Pseudo Steady-State Free Precession for MR-Fingerprinting

PURPOSE

This article discusses the signal behavior in the case the flip angle in steady-state free precession sequences is continuously varied as suggested for MR-fingerprinting sequences. Flip angle variations prevent the establishment of a steady state and introduce instabilities regarding to magnetic field inhomogeneities and intravoxel dephasing. We show how a pseudo steady state can be achieved, which restores the spin echo nature of steady-state free precession.

METHODS

Based on geometrical considerations, relationships between the flip angle, repetition and echo time are derived that suffice to the establishment of a pseudo steady state. The theory is tested with Bloch simulations as well as phantom and in vivo experiments.

RESULTS

A typical steady-state free precession passband can be restored with the proposed conditions. The stability of the pseudo steady state is demonstrated by comparing the evolution of the signal of a single isochromat to one resulting from a spin ensemble. As confirmed by experiments, magnetization in a pseudo steady state can be described with fewer degrees of freedom compared to the original fingerprinting and the pseudo steady state results in more reliable parameter maps.

CONCLUSION

The proposed conditions restore the spin-echo-like signal behavior typical for steady-state free precession in fingerprinting sequences, making this approach more robust to B₀ variations. Magn Reson Med 77:1151-1161, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Making muscle: Morphogenetic movements and molecular mechanisms of myogenesis in Xenopus laevis

Xenopus laevis offers unprecedented access to the intricacies of muscle development. The large, robust embryos make it ideal for manipulations at both the tissue and molecular level. In particular, this model system can be used to fate map early muscle progenitors, visualize cell behaviors associated with somitogenesis, and examine the role of signaling pathways that underlie induction, specification, and differentiation of muscle. Several characteristics that are unique to X. laevis include myogenic waves with distinct gene expression profiles and the late formation of dermomyotome and sclerotome. Furthermore, myogenesis in the metamorphosing frog is biphasic, facilitating regeneration studies. In this review, we describe the morphogenetic movements that shape the somites and discuss signaling and transcriptional regulation during muscle development and regeneration. With recent advances in gene editing tools, X. laevis remains a premier model organism for dissecting the complex mechanisms underlying the specification, cell behaviors, and formation of the musculature system.

MR fingerprinting with simultaneous B1 estimation

PURPOSE

MR fingerprinting (MRF) can be used for quantitative estimation of physical parameters in MRI. Here, we extend the method to incorporate B1 estimation.

METHODS

The acquisition is based on steady state free precession MR fingerprinting with a Cartesian trajectory. To increase the sensitivity to the B1 profile, abrupt changes in flip angle were introduced in the sequence. Slice profile and B1 effects were included in the dictionary and the results from two- and three-dimensional (3D) acquisitions were compared. Acceleration was demonstrated using retrospective undersampling in the phase encode directions of 3D data exploiting redundancy between MRF frames at the edges of k-space.

RESULTS

Without B1 estimation, T2 and B1 were inaccurate by more than 20%. Abrupt changes in flip angle improved B1 maps. T1 and T2 values obtained with the new MRF methods agree with classical spin echo measurements and are independent of the B1 field profile. When using view sharing reconstruction, results remained accurate (error <10%) when sampling under 10% of k-space from the 3D data.

CONCLUSION

The methods demonstrated here can successfully measure T1, T2, and B1. Errors due to slice profile can be substantially reduced by including its effect in the dictionary or acquiring data in 3D. Magn Reson Med 76:1127-1135, 2016. © 2015 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Expression of myogenic regulatory factors in chicken embryos during somite and limb development

The expression of the myogenic regulatory factors (MRFs), Myf5, MyoD, myogenin (Mgn) and MRF4 have been analysed during the development of chicken embryo somites and limbs. In somites, Myf5 is expressed first in somites and paraxial mesoderm at HH stage 9 followed by MyoD at HH stage 12, and Mgn and MRF4 at HH stage 14. In older somites, Myf5 and MyoD are also expressed in the ventrally extending myotome prior to Mgn and MRF4 expression. In limb muscles a similar temporal sequence is observed with Myf5 expression detected first in forelimbs at HH stage 22, MyoD at HH stage 23, Mgn at HH stage 24 and MRF4 at HH stage 30. This report describes the precise time of onset of expression of each MRF in somites and limbs during chicken embryo development, and provides a detailed comparative timeline of MRF expression in different embryonic muscle groups.

GraSP: geodesic Graph-based Segmentation with Shape Priors for the functional parcellation of the cortex

Resting-state functional MRI is a powerful technique for mapping the functional organization of the human brain. However, for many types of connectivity analysis, high-resolution voxelwise analyses are computationally infeasible and dimensionality reduction is typically used to limit the number of network nodes. Most commonly, network nodes are defined using standard anatomic atlases that do not align well with functional neuroanatomy or regions of interest covering a small portion of the cortex. Data-driven parcellation methods seek to overcome such limitations, but existing approaches are highly dependent on initialization procedures and produce spatially fragmented parcels or overly isotropic parcels that are unlikely to be biologically grounded. In this paper, we propose a novel graph-based parcellation method that relies on a discrete Markov Random Field framework. The spatial connectedness of the parcels is explicitly enforced by shape priors. The shape of the parcels is adapted to underlying data through the use of functional geodesic distances. Our method is initialization-free and rapidly segments the cortex in a single optimization. The performance of the method was assessed using a large developmental cohort of more than 850 subjects. Compared to two prevalent parcellation methods, our approach provides superior reproducibility for a similar data fit. Furthermore, compared to other methods, it avoids incoherent parcels. Finally, the method's utility is demonstrated through its ability to detect strong brain developmental effects that are only weakly observed using other methods.

Antagonistic regulation of p57kip2 by Hes/Hey downstream of Notch signaling and muscle regulatory factors regulates skeletal muscle growth arrest

A central question in development is to define how the equilibrium between cell proliferation and differentiation is temporally and spatially regulated during tissue formation. Here, we address how interactions between cyclin-dependent kinase inhibitors essential for myogenic growth arrest (p21(cip1) and p57(kip2)), the Notch pathway and myogenic regulatory factors (MRFs) orchestrate the proliferation, specification and differentiation of muscle progenitor cells. We first show that cell cycle exit and myogenic differentiation can be uncoupled. In addition, we establish that skeletal muscle progenitor cells require Notch signaling to maintain their cycling status. Using several mouse models combined with ex vivo studies, we demonstrate that Notch signaling is required to repress p21(cip1) and p57(kip2) expression in muscle progenitor cells. Finally, we identify a muscle-specific regulatory element of p57(kip2) directly activated by MRFs in myoblasts but repressed by the Notch targets Hes1/Hey1 in progenitor cells. We propose a molecular mechanism whereby information provided by Hes/Hey downstream of Notch as well as MRF activities are integrated at the level of the p57(kip2) enhancer to regulate the decision between progenitor cell maintenance and muscle differentiation.

Accurate Whole-Brain Segmentation for Alzheimer's Disease Combining an Adaptive Statistical Atlas and Multi-atlas

Accurate segmentation of whole brain MR images including the cortex, white matter and subcortical structures is challenging due to inter-subject variability and the complex geometry of brain anatomy. However a precise solution would enable accurate, objective measurement of structure volumes for disease quantification. Our contribution is three-fold. First we construct an adaptive statistical atlas that combines structure specific relaxation and spatially varying adaptivity. Second we integrate an isotropic pairwise class-specific MRF model of label connectivity. Together these permit precise control over adaptivity, allowing many structures to be segmented simultaneously with superior accuracy. Third, we develop a framework combining the improved adaptive statistical atlas with a multi-atlas method which achieves simultaneous accurate segmentation of the cortex, ventricles, and sub-cortical structures in severely diseased brains, a feat not attained in [18]. We test the proposed method on 46 brains including 28 diseased brain with Alzheimer's and 18 healthy brains. Our proposed method yields higher accuracy than state-of-the-art approaches on both healthy and diseased brains.

Contribution of cooperative sector recycling to greenhouse gas emissions reduction: a case study of Ribeirão Pires, Brazil

Solid waste, including municipal waste and its management, is a major challenge for most cities and among the key contributors to climate change. Greenhouse gas emissions can be reduced through recovery and recycling of resources from the municipal solid waste stream. In São Paulo, Brazil, recycling cooperatives play a crucial role in providing recycling services including collection, separation, cleaning, stocking, and sale of recyclable resources. The present research attempts to measure the greenhouse gas emission reductions achieved by the recycling cooperative Cooperpires, as well as highlight its socioeconomic benefits. Methods include participant observation, structured interviews, questionnaire application, and greenhouse gas accounting of recycling using a Clean Development Mechanism methodology. The results show that recycling cooperatives can achieve important energy savings and reductions in greenhouse gas emissions, and suggest there is an opportunity for Cooperpires and other similar recycling groups to participate in the carbon credit market. Based on these findings, the authors created a simple greenhouse gas accounting calculator for recyclers to estimate their emissions reductions.

Experts reviews of the multidisciplinary consensus conference colon and rectal cancer 2012: science, opinions and experiences from the experts of surgery

The first multidisciplinary consensus conference on colon and rectal cancer was held in December 2012, achieving a majority of consensus for diagnostic and treatment decisions using the Delphi Method. This article will give a critical appraisal of the topics discussed during the meeting and in the consensus document by well-known leaders in surgery that were involved in this multidisciplinary consensus process. Scientific evidence, experience and opinions are collected to support multidisciplinary teams (MDT) with arguments for medical decision-making in diagnosis, staging and treatment strategies for patients with colon or rectal cancer. Surgery is the cornerstone of curative treatment for colon and rectal cancer. Standardizing treatment is an effective instrument to improve outcome of multidisciplinary cancer care for patients with colon and rectal cancer. In this article, a review of the following focuses; Perioperative care, age and colorectal surgery, obstructive colorectal cancer, stenting, surgical anatomical considerations, total mesorectal excision (TME) surgery and training, surgical considerations for locally advanced rectal cancer (LARC) and local recurrent rectal cancer (LRRC), surgery in stage IV colorectal cancer, definitions of quality of surgery, transanal endoscopic microsurgery (TEM), laparoscopic colon and rectal surgery, preoperative radiotherapy and chemoradiotherapy, and how about functional outcome after surgery?

Effects of Ureaplasma parvum lipoprotein multiple-banded antigen on pregnancy outcome in mice

Ureaplasma spp. are members of the family Mycoplasmataceae and have been considered to be associated with chorioamnionitis and preterm delivery. However, it is unclear whether Ureaplasma spp. have virulence factors related to these manifestations. The purpose of the present study was to determine whether the immunogenic protein multiple-banded antigen (MBA) from Ureaplasma parvum is a virulence factor for preterm delivery. We partially purified MBA from a type strain and clinical isolates of U. parvum, and also synthesized a diacylated lipopeptide derived from U. parvum, UPM-1. Using luciferase assays, both MBA-rich fraction MRF and UPM-1 activated the NF-κB pathway via TLR2. UPM-1 upregulated IL-1β, IL-6, IL-12p35, TNF-α, MIP2, LIX, and iNOS in mouse peritoneal macrophage. MRF or UPM-1 was injected into uteri on day 15 of gestation on pregnant C3H/HeN mice. The intrauterine MRF injection group had a significantly higher incidence of intrauterine fetal death (IUFD; 38.5%) than the control group (14.0%). Interestingly, intrauterine injection of UPM-1 caused preterm deliveries at high concentration (80.0%). In contrast, a low concentration of UPM-1 induced a significantly higher rate of fetal deaths (55.2%) than the control group (14.0%). The placentas of the UPM-1 injection group showed neutrophil infiltration and increased iNOS protein expression. Our data indicate that MBA from the clinical isolate of U. parvum is a potential virulence factor for IUFD and preterm delivery in mice and that the N-terminal diacylated lipopeptide is essential for the initiation of inflammation.

The combination of glycosaminoglycans and fibrous proteins improves cell proliferation and early differentiation of bovine primary skeletal muscle cells

Primary muscle cell model systems from farm animals are widely used to acquire knowledge about muscle development, muscle pathologies, overweight issues and tissue regeneration. The morphological properties of a bovine primary muscle cell model system, in addition to cell proliferation and differentiation features, were characterized using immunocytochemistry, western blotting and real-time PCR. We observed a reorganization of the Golgi complex in differentiated cells. The Golgi complex transformed to a highly fragmented network of small stacks of cisternae positioned throughout the myotubes as well as around the nucleus. Different extracellular matrix (ECM) components were used as surface coatings in order to improve cell culture conditions. Our experiments demonstrated improved proliferation and early differentiation for cells grown on surface coatings containing a mixture of both glycosaminoglycans (GAGs) and fibrous proteins. We suggest that GAGs and fibrous proteins mixed together into a composite biomaterial can mimic a natural ECM, and this could improve myogenesis for in vitro cell cultures.

Responsive neurostimulation for the treatment of medically intractable epilepsy

With an annual incidence of 50/100,000 people, nearly 1% of the population suffers from epilepsy. Treatment with antiepileptic medication fails to achieve seizure remission in 20-30% of patients. One treatment option for refractory epilepsy patients who would not otherwise be surgical candidates is electrical stimulation of the brain, which is a rapidly evolving and reversible adjunctive therapy. Therapeutic stimulation can involve direct stimulation of the brain nuclei or indirect stimulation of peripheral nerves. There are three stimulation modalities that have class I evidence supporting their uses: vagus nerve stimulation (VNS), stimulation of the anterior nuclei of the thalamus (ANT), and, the most recently developed, responsive neurostimulation (RNS). While the other treatment modalities outlined deliver stimulation regardless of neuronal activity, the RNS administers stimulation only if triggered by seizure activity. The lower doses of stimulation provided by such responsive devices can not only reduce power consumption, but also prevent adverse reactions caused by continuous stimulation, which include the possibility of habituation to long-term stimulation. RNS, as an investigational treatment for medically refractory epilepsy, is currently under review by the FDA. Eventually systems may be developed to enable activation by neurochemical triggers or to wirelessly transmit any information gathered. We review the mechanisms, the current status, the target options, and the prospects of RNS for the treatment of medically intractable epilepsy.

Accurate segmentation of brain images into 34 structures combining a non-stationary adaptive statistical atlas and a multi-atlas with applications to Alzheimer's disease

Accurate segmentation of the 30+ subcortical structures in MR images of whole diseased brains is challenging due to inter-subject variability and complex geometry of brain anatomy. However a clinically viable solution yielding precise segmentation of the structures would enable: 1) accurate, objective measurement of structure volumes many of which are associated with diseases such as Alzheimer's, 2) therapy monitoring and 3) drug development. Our contributions are two-fold. First we construct an extended adaptive statistical atlas method (EASA) to use a non-stationary relaxation factor rather than a global one. This permits finer control over adaptivity allowing 34 structures to be simultaneously segmented rather than just 4 as in [13]. Second we use the output of a weighted majority voting (WMV) label fusion multi-atlas method as the input to EASA in a hybrid WMV-EASA approach. We assess our proposed approaches on 18 healthy subjects in the public IBSR database and on 9 subjects with Alzheimer's disease in the AIBL database. EASA is shown to produce state-of-the-art accuracy on healthy brains in a fraction of the time of comparable methods, while our hybrid WMV-EASA visibly improves segmentation accuracy for structures throughout the diseased brains.