Comparing in planta accumulation with microbial routes to set targets for a cost-competitive bioeconomy.

Plants and microbes share common metabolic pathways for producing a range of bioproducts that are potentially foundational to the future bioeconomy. However, in planta accumulation and microbial production of bioproducts have never been systematically compared on an economic basis to identify optimal routes of production. A detailed technoeconomic analysis of four exemplar compounds (4-hydroxybenzoic acid [4-HBA], catechol, muconic acid, and 2-pyrone-4,6-dicarboxylic acid [PDC]) is conducted with the highest reported yields and accumulation rates to identify economically advantaged platforms and breakeven targets for plants and microbes. The results indicate that in planta mass accumulation ranging from 0.1 to 0.3 dry weight % (dwt%) can achieve costs comparable to microbial routes operating at 40 to 55% of maximum theoretical yields. These yields and accumulation rates are sufficient to be cost competitive if the products are sold at market prices consistent with specialty chemicals ($20 to $50/kg). Prices consistent with commodity chemicals will require an order-of-magnitude-greater accumulation rate for plants and/or yields nearing theoretical maxima for microbial production platforms. This comparative analysis revealed that the demonstrated accumulation rates of 4-HBA (3.2 dwt%) and PDC (3.0 dwt%) in engineered plants vastly outperform microbial routes, even if microbial platforms were to reach theoretical maximum yields. Their recovery and sale as part of a lignocellulosic biorefinery could enable biofuel prices to be competitive with petroleum. Muconic acid and catechol, in contrast, are currently more attractive when produced microbially using a sugar feedstock. Ultimately, both platforms can play an important role in replacing fossil-derived products.

Expression of dehydroshikimate dehydratase in poplar induces transcriptional and metabolic changes in the phenylpropanoid pathway.

Modification of lignin in feedstocks via genetic engineering aims to reduce biomass recalcitrance to facilitate efficient conversion processes. These improvements can be achieved by expressing exogenous enzymes that interfere with native biosynthetic pathways responsible for the production of the lignin precursors. In planta expression of a bacterial 3-dehydroshikimate dehydratase in poplar trees reduced lignin content and altered the monomer composition, which enabled higher yields of sugars after cell wall polysaccharide hydrolysis. Understanding how plants respond to such genetic modifications at the transcriptional and metabolic levels is needed to facilitate further improvement and field deployment. In this work, we acquired fundamental knowledge on lignin-modified poplar expressing 3-dehydroshikimate dehydratase using RNA-seq and metabolomics. The data clearly demonstrate that changes in gene expression and metabolite abundance can occur in a strict spatiotemporal fashion, revealing tissue-specific responses in the xylem, phloem, or periderm. In the poplar line that exhibited the strongest reduction in lignin, we found that 3% of the transcripts had altered expression levels and ~19% of the detected metabolites had differential abundance in the xylem from older stems. The changes affected predominantly the shikimate and phenylpropanoid pathways as well as secondary cell wall metabolism, and resulted in significant accumulation of hydroxybenzoates derived from protocatechuate and salicylate.

Ectopic Production of 3,4-Dihydroxybenzoate in Planta Affects Cellulose Structure and Organization.

Lignocellulosic biomass is a highly sustainable and largely carbon dioxide neutral feedstock for the production of biofuels and advanced biomaterials. Although thermochemical pretreatment is typically used to increase the efficiency of cell wall deconstruction, genetic engineering of the major plant cell wall polymers, especially lignin, has shown promise as an alternative approach to reduce biomass recalcitrance. Poplar trees with reduced lignin content and altered composition were previously developed by overexpressing bacterial 3-dehydroshikimate dehydratase (QsuB) enzyme to divert carbon flux from the shikimate pathway. In this work, three transgenic poplar lines with increasing QsuB expression levels and different lignin contents were studied using small-angle neutron scattering (SANS) and wide-angle X-ray scattering (WAXS). SANS showed that although the cellulose microfibril cross-sectional dimension remained unchanged, the ordered organization of the microfibrils progressively decreased with increased QsuB expression. This was correlated with decreasing total lignin content in the QsuB lines. WAXS showed that the crystallite dimensions of cellulose microfibrils transverse to the growth direction were not affected by the QsuB expression, but the crystallite dimensions parallel to the growth direction were decreased by ∼20%. Cellulose crystallinity was also decreased with increased QsuB expression, which could be related to high levels of 3,4-dihydroxybenzoate, the product of QsuB expression, disrupting microfibril crystallization. In addition, the cellulose microfibril orientation angle showed a bimodal distribution at higher QsuB expression levels. Overall, this study provides new structural insights into the impact of ectopic synthesis of small-molecule metabolites on cellulose organization and structure that can be used for future efforts aimed at reducing biomass recalcitrance.

Application of deep learning reconstruction in abdominal magnetic resonance cholangiopancreatography for image quality improvement and acquisition time reduction.

PURPOSE: To compare deep learning (DL)-based and conventional reconstruction through subjective and objective analysis and ascertain whether DL-based reconstruction improves the quality and acquisition speed of clinical abdominal magnetic resonance imaging (MRI). METHODS: The 124 patients who underwent abdominal MRI between January and July 2021 were retrospectively studied. For each patient, two-dimensional axial T2-weighted single-shot fast spin-echo MRI images with or without fat saturation were reconstructed using DL-based and conventional methods. The subjective image quality scores and objective metrics, including signal-to-noise ratios (SNRs) and contrast-to-noise ratios (CNRs) of the images were analysed. An explorative analysis was performed to compare 20 patients' MRI images with site routine settings, high-resolution settings and high-speed settings. Paired t tests and Wilcoxon signed-rank tests were used for subjective and objective comparisons. RESULTS: A total of 144 patients were evaluated (mean age, 62.2 ± 14.1 years; 83 men). The MRI images reconstructed using DL-based methods had higher SNRs and CNRs than did those reconstructed using conventional methods (all p < 0.01). The subjective scores of the images reconstructed using DL-based methods were higher than those of the images reconstructed using conventional methods (p < 0.01), with significantly lower variation (p < 0.01). Exploratory analysis revealed that the DL-based reconstructions with thin slice thickness and higher temporal resolution had the highest image quality and were associated with the shortest scan times. CONCLUSIONS: DL-based reconstruction methods can be used to improve the quality with higher stability and accelerate the acquisition of abdominal MRI.

Shared decision-making and patient decision aids in choosing first-line targeted therapy for metastatic colorectal cancer in Taiwan.

INTRODUCTION: In Taiwan, given the discrepancy between current treatment guidelines and reimbursement options, patients might require a tool to support their decision-making process when selecting a regimen for metastatic colorectal cancer, especially therapeutic strategies, and subsequent costs, along with efficacy and safety outcomes. Therefore, we developed a patient decision aid (PDA) to support patients in choosing between treatment options recommended based on the current evidence and those reimbursed by the Taiwanese National Health Insurance. METHODS: By carefully reviewing the updated data and then interpreting the clinical tool, we conducted a needs assessment using a serial questionnaire to test for a step-by-step adjustment of the PDA. RESULTS: Patients, their relatives, and medical team members were most concerned about outcomes, such as overall survival, progression-free survival, objective response rate, tumor shrinkage to resectable status, total medical cost, severe gastrointestinal perforation, and severe skin reaction. After a serial alpha test for quality, we performed quantitative evaluation and beta tests, revealing average scores of more than 4 points (on a scale of 1-5) for both perceptibility and utility. CONCLUSIONS: The present findings suggest that PDAs are useful and supplement the shared decision-making practice, helping patients make decisions about preferences and consider the pros and cons of treatment regimens, along with insurance reimbursement options.

Discriminating subcortical ischemic vascular disease and Alzheimer's disease by diffusion kurtosis imaging in segregated thalamic regions.

Differentiating between subcortical ischemic vascular disease (SIVD), Alzheimer's disease (AD), and normal cognition (NC) remains a challenge, and reliable neuroimaging biomarkers are needed. The current study, therefore, investigated the discriminative ability of diffusion kurtosis imaging (DKI) metrics in segregated thalamic regions and compare with diffusion tensor imaging (DTI) metrics. Twenty-three SIVD patients, 30 AD patients, and 24 NC participants underwent brain magnetic resonance imaging. The DKI metrics including mean kurtosis (MK), axial kurtosis (Kaxial ) and radial kurtosis (Kradial ) and the DTI metrics including diffusivity and fractional anisotropy (FA) were measured within the whole thalamus and segregated thalamic subregions. Strategic correlations by group, thalamo-frontal connectivity, and canonical discriminant analysis (CDA) were used to demonstrate the discriminative ability of DKI for SIVD, AD, and NC. Whole and segregated thalamus analysis suggested that DKI metrics are less affected by white matter hyperintensities compared to DTI metrics. Segregated thalamic analysis showed that MK and Kradial were notably different between SIVD and AD/NC. The correlation analysis between Kaxial and MK showed a nonsignificant relationship in SIVD group, a trend of negative relationship in AD group, and a significant positive relationship in NC group. A wider spatial distribution of thalamo-frontal connectivity differences across groups was shown by MK compared to FA. CDA showed a discriminant power of 97.4% correct classification using all DKI metrics. Our findings support that DKI metrics could be more sensitive than DTI metrics to reflect microstructural changes within the gray matter, hence providing complementary information for currently outlined pathogenesis of SIVD and AD.

In-planta production of the biodegradable polyester precursor 2-pyrone-4,6-dicarboxylic acid (PDC): Stacking reduced biomass recalcitrance with value-added co-product.

2-Pyrone-4,6-dicarboxylic acid (PDC), a chemically stable intermediate that naturally occurs during microbial degradation of lignin by bacteria, represents a promising building block for diverse biomaterials and polyesters such as biodegradable plastics. The lack of a chemical synthesis method has hindered large-scale utilization of PDC and metabolic engineering approaches for its biosynthesis have recently emerged. In this study, we demonstrate a strategy for the production of PDC via manipulation of the shikimate pathway using plants as green factories. In tobacco leaves, we first showed that transient expression of bacterial feedback-resistant 3-deoxy-D-arabinoheptulosonate 7-phosphate synthase (AroG) and 3-dehydroshikimate dehydratase (QsuB) produced high titers of protocatechuate (PCA), which was in turn efficiently converted into PDC upon co-expression of PCA 4,5-dioxygenase (PmdAB) and 4-carboxy-2-hydroxymuconate-6-semialdehyde dehydrogenase (PmdC) derived from Comamonas testosteroni. We validated that stable expression of AroG in Arabidopsis in a genetic background containing the QsuB gene enhanced PCA content in plant biomass, presumably via an increase of the carbon flux through the shikimate pathway. Further, introducing AroG and the PDC biosynthetic genes (PmdA, PmdB, and PmdC) into the Arabidopsis QsuB background, or introducing the five genes (AroG, QsuB, PmdA, PmdB, and PmdC) stacked on a single construct into wild-type plants, resulted in PDC titers of ~1% and ~3% dry weight in plant biomass, respectively. Consistent with previous studies of plants expressing QsuB, all PDC producing lines showed strong reduction in lignin content in stems. This low lignin trait was accompanied with improvements of biomass saccharification efficiency due to reduced cell wall recalcitrance to enzymatic degradation. Importantly, most transgenic lines showed no reduction in biomass yields. Therefore, we conclude that engineering plants with the proposed de-novo PDC pathway provides an avenue to enrich biomass with a value-added co-product while simultaneously improving biomass quality for the supply of fermentable sugars. Implementing this strategy into bioenergy crops has the potential to support existing microbial fermentation approaches that exploit lignocellulosic biomass feedstocks for PDC production.

The impact of edema and fiber crossing on diffusion MRI metrics assessed in an ex vivo nerve phantom: Multi-tensor model vs. diffusion orientation distribution function.

Diffusion tensor imaging (DTI) has been employed for over 2 decades to noninvasively quantify central nervous system diseases/injuries. However, DTI is an inadequate simplification of diffusion modeling in the presence of coexisting inflammation, edema and crossing nerve fibers. We employed a tissue phantom using fixed mouse trigeminal nerves coated with various amounts of agarose gel to mimic crossing fibers in the presence of vasogenic edema. Diffusivity measures derived by DTI and diffusion basis spectrum imaging (DBSI) were compared at increasing levels of simulated edema and degrees of fiber crossing. Furthermore, we assessed the ability of DBSI, diffusion kurtosis imaging (DKI), generalized q-sampling imaging (GQI), q-ball imaging (QBI) and neurite orientation dispersion and density imaging to resolve fiber crossing, in reference to the gold standard angles measured from structural images. DTI-computed diffusivities and fractional anisotropy were significantly confounded by gel-mimicked edema and crossing fibers. Conversely, DBSI calculated accurate diffusivities of individual fibers regardless of the extent of simulated edema and degrees of fiber crossing angles. Additionally, DBSI accurately and consistently estimated crossing angles in various conditions of gel-mimicked edema when compared with the gold standard (r2 = 0.92, P = 1.9 × 10-9 , bias = 3.9°). Small crossing angles and edema significantly impact the diffusion orientation distribution function, making DKI, GQI and QBI less accurate in detecting and estimating fiber crossing angles. Lastly, we used diffusion tensor ellipsoids to demonstrate that DBSI resolves the confounds of edema and crossing fibers in the peritumoral edema region from a patient with lung cancer metastasis, while DTI failed. In summary, DBSI is able to separate two crossing fibers and accurately recover their diffusivities in a complex environment characterized by increasing crossing angles and amounts of gel-mimicked edema. DBSI also indicated better angular resolution compared with DKI, QBI and GQI.

Comparison of Multivendor Single-Voxel MR Spectroscopy Data Acquired in Healthy Brain at 26 Sites.

Background The hardware and software differences between MR vendors and individual sites influence the quantification of MR spectroscopy data. An analysis of a large data set may help to better understand sources of the total variance in quantified metabolite levels. Purpose To compare multisite quantitative brain MR spectroscopy data acquired in healthy participants at 26 sites by using the vendor-supplied single-voxel point-resolved spectroscopy (PRESS) sequence. Materials and Methods An MR spectroscopy protocol to acquire short-echo-time PRESS data from the midparietal region of the brain was disseminated to 26 research sites operating 3.0-T MR scanners from three different vendors. In this prospective study, healthy participants were scanned between July 2016 and December 2017. Data were analyzed by using software with simulated basis sets customized for each vendor implementation. The proportion of total variance attributed to vendor-, site-, and participant-related effects was estimated by using a linear mixed-effects model. P values were derived through parametric bootstrapping of the linear mixed-effects models (denoted Pboot). Results In total, 296 participants (mean age, 26 years ± 4.6; 155 women and 141 men) were scanned. Good-quality data were recorded from all sites, as evidenced by a consistent linewidth of N-acetylaspartate (range, 4.4-5.0 Hz), signal-to-noise ratio (range, 174-289), and low Cramér-Rao lower bounds (≤5%) for all of the major metabolites. Among the major metabolites, no vendor effects were found for levels of myo-inositol (Pboot > .90), N-acetylaspartate and N-acetylaspartylglutamate (Pboot = .13), or glutamate and glutamine (Pboot = .11). Among the smaller resonances, no vendor effects were found for ascorbate (Pboot = .08), aspartate (Pboot > .90), glutathione (Pboot > .90), or lactate (Pboot = .28). Conclusion Multisite multivendor single-voxel MR spectroscopy studies performed at 3.0 T can yield results that are coherent across vendors, provided that vendor differences in pulse sequence implementation are accounted for in data analysis. However, the site-related effects on variability were more profound and suggest the need for further standardization of spectroscopic protocols. © RSNA, 2020 Online supplemental material is available for this article.

Big GABA II: Water-referenced edited MR spectroscopy at 25 research sites.

Accurate and reliable quantification of brain metabolites measured in vivo using 1H magnetic resonance spectroscopy (MRS) is a topic of continued interest. Aside from differences in the basic approach to quantification, the quantification of metabolite data acquired at different sites and on different platforms poses an additional methodological challenge. In this study, spectrally edited γ-aminobutyric acid (GABA) MRS data were analyzed and GABA levels were quantified relative to an internal tissue water reference. Data from 284 volunteers scanned across 25 research sites were collected using GABA+ (GABA + co-edited macromolecules (MM)) and MM-suppressed GABA editing. The unsuppressed water signal from the volume of interest was acquired for concentration referencing. Whole-brain T1-weighted structural images were acquired and segmented to determine gray matter, white matter and cerebrospinal fluid voxel tissue fractions. Water-referenced GABA measurements were fully corrected for tissue-dependent signal relaxation and water visibility effects. The cohort-wide coefficient of variation was 17% for the GABA + data and 29% for the MM-suppressed GABA data. The mean within-site coefficient of variation was 10% for the GABA + data and 19% for the MM-suppressed GABA data. Vendor differences contributed 53% to the total variance in the GABA + data, while the remaining variance was attributed to site- (11%) and participant-level (36%) effects. For the MM-suppressed data, 54% of the variance was attributed to site differences, while the remaining 46% was attributed to participant differences. Results from an exploratory analysis suggested that the vendor differences were related to the unsuppressed water signal acquisition. Discounting the observed vendor-specific effects, water-referenced GABA measurements exhibit similar levels of variance to creatine-referenced GABA measurements. It is concluded that quantification using internal tissue water referencing is a viable and reliable method for the quantification of in vivo GABA levels.

Non-contrast-enhanced magnetic resonance angiography of facial arteries for pre-operative evaluation of vascularized submental lymph node flaps.

BACKGROUND: The aim of this study was to compare non-contrast-enhanced 3D phase contrast magnetic resonance angiography (3D PC-MRA) and conventional intravenous administration of contrast media, i.e., contrast-enhanced MRA (CE-MRA), to evaluate the courses of facial arteries for the preparation of vascularized submental lymph node flap (VSLN flap) transfer. METHODS: The head and neck regions of 20 patients with limb lymphedema were imaged using a 3 T MRI scanner. To improve the evaluation of facial artery courses, MRA was fused with anatomical structures generated by high-resolution T1-weighted imaging. The diagnostic and image qualities of facial arteries for VSLN flap planning were independently rated by two radiologists. Interobserver agreement was evaluated using Cohen's kappa. Differences between 3D PC-MRA and CE-MRA in terms of the diagnostic quality of facial arteries were evaluated using McNemar's test. RESULTS: Cohen's kappa indicated fair to good interobserver agreement for the diagnostic and image qualities of the bilateral facial arteries. No significant difference in terms of the diagnostic quality of the left and right facial arteries between 3D PC-MRA and CE-MRA, respectively, was identified. CONCLUSIONS: Non-contrast 3D PC-MRA is a reliable method for the evaluation of facial artery courses prior to VSLN flap transfer and could serve as an alternative to CE-MRA for patients with renal insufficiency or severe adverse reactions to contrast media.

Big GABA: Edited MR spectroscopy at 24 research sites.

Magnetic resonance spectroscopy (MRS) is the only biomedical imaging method that can noninvasively detect endogenous signals from the neurotransmitter γ-aminobutyric acid (GABA) in the human brain. Its increasing popularity has been aided by improvements in scanner hardware and acquisition methodology, as well as by broader access to pulse sequences that can selectively detect GABA, in particular J-difference spectral editing sequences. Nevertheless, implementations of GABA-edited MRS remain diverse across research sites, making comparisons between studies challenging. This large-scale multi-vendor, multi-site study seeks to better understand the factors that impact measurement outcomes of GABA-edited MRS. An international consortium of 24 research sites was formed. Data from 272 healthy adults were acquired on scanners from the three major MRI vendors and analyzed using the Gannet processing pipeline. MRS data were acquired in the medial parietal lobe with standard GABA+ and macromolecule- (MM-) suppressed GABA editing. The coefficient of variation across the entire cohort was 12% for GABA+ measurements and 28% for MM-suppressed GABA measurements. A multilevel analysis revealed that most of the variance (72%) in the GABA+ data was accounted for by differences between participants within-site, while site-level differences accounted for comparatively more variance (20%) than vendor-level differences (8%). For MM-suppressed GABA data, the variance was distributed equally between site- (50%) and participant-level (50%) differences. The findings show that GABA+ measurements exhibit strong agreement when implemented with a standard protocol. There is, however, increased variability for MM-suppressed GABA measurements that is attributed in part to differences in site-to-site data acquisition. This study's protocol establishes a framework for future methodological standardization of GABA-edited MRS, while the results provide valuable benchmarks for the MRS community.

B1 Field Correction of T1 Estimation Should Be Considered for Breast Dynamic Contrast-enhanced MR Imaging Even at 1.5 T.

Purpose To prospectively quantify the effect of T1 estimation in fat by B1 correction in breast magnetic resonance (MR) imaging at 1.5 T and to examine the subsequent quantitative dynamic contrast material-enhanced parameters in breast cancer with and without B1 correction. Materials and Methods This study had institutional review board approval, and informed consent was obtained from 72 patients with breast cancer before breast MR imaging studies were performed between January and July 2015. B1+ field and variable flip angle (FA) mapping were included in the dynamic contrast-enhanced breast MR imaging protocol with a 1.5-T MR imaging system. Precontrast T1 relaxation in fat and breast tumors was computed with and without B1 correction. The pharmacokinetic parameters of breast cancer were calculated by using the Tofts model with T1 values before and after B1 correction. The Mann-Whitney U test and linear regression model were used for statistical analysis. Results The FA was 19% higher in the left breast and 3% lower in the right breast than the prescribed value. This 22% average FA difference created a 43% T1 estimation bias in fat between the breasts. The T1 variation in fat was reduced to 0.96% after B1 correction. There was a 50% overestimation and a 7% underestimation of tumor T1 in the left breast and the right, respectively, associated with B1 error. Assuming T1 after B1 correction represents the true tumor T1, 41% underestimation in the left breast and 10% overestimation in the right without B1 correction were seen in the dynamic contrast-enhanced parameters (including the volume transfer constant, or Ktrans, fraction of extracellular extravascular space, or ve, and blood normalized initial area under the gadolinium concentration curve to 90 seconds, or IAUGCBN90). Conclusion B1 correction for more accurate T1 values should be considered for quantitative dynamic contrast-enhanced breast MR imaging, even at 1.5 T, to offset significant systemic error. © RSNA, 2016.

Complete proteomic-based enzyme reaction and inhibition kinetics reveal how monolignol biosynthetic enzyme families affect metabolic flux and lignin in Populus trichocarpa.

We established a predictive kinetic metabolic-flux model for the 21 enzymes and 24 metabolites of the monolignol biosynthetic pathway using Populus trichocarpa secondary differentiating xylem. To establish this model, a comprehensive study was performed to obtain the reaction and inhibition kinetic parameters of all 21 enzymes based on functional recombinant proteins. A total of 104 Michaelis-Menten kinetic parameters and 85 inhibition kinetic parameters were derived from these enzymes. Through mass spectrometry, we obtained the absolute quantities of all 21 pathway enzymes in the secondary differentiating xylem. This extensive experimental data set, generated from a single tissue specialized in wood formation, was used to construct the predictive kinetic metabolic-flux model to provide a comprehensive mathematical description of the monolignol biosynthetic pathway. The model was validated using experimental data from transgenic P. trichocarpa plants. The model predicts how pathway enzymes affect lignin content and composition, explains a long-standing paradox regarding the regulation of monolignol subunit ratios in lignin, and reveals novel mechanisms involved in the regulation of lignin biosynthesis. This model provides an explanation of the effects of genetic and transgenic perturbations of the monolignol biosynthetic pathway in flowering plants.

Elucidation of Xylem-Specific Transcription Factors and Absolute Quantification of Enzymes Regulating Cellulose Biosynthesis in Populus trichocarpa.

Cellulose, the main chemical polymer of wood, is the most abundant polysaccharide in nature.1 The ability to perturb the abundance and structure of cellulose microfibrils is of critical importance to the pulp and paper industry as well as for the textile, wood products, and liquid biofuels industries. Although much has been learned at the transcript level about the biosynthesis of cellulose, a quantitative understanding at the proteome level has yet to be established. The study described herein sought to identify the proteins directly involved in cellulose biosynthesis during wood formation in Populus trichocarpa along with known xylem-specific transcription factors involved in regulating these key proteins. Development of an effective discovery proteomic strategy through a combination of subcellular fractionation of stem differentiating xylem tissue (SDX) with recently optimized FASP digestion protocols, StageTip fractionation, as well as optimized instrument parameters for global proteomic analysis using the quadrupole-orbitrap mass spectrometer resulted in the deepest proteomic coverage of SDX protein from P. trichocarpa with 9,146 protein groups being identified (1% FDR). Of these, 20 cellulosic/hemicellulosic enzymes and 43 xylem-specific transcription factor groups were identified. Finally, selection of surrogate peptides led to an assay for absolute quantification of 14 cellulosic proteins in SDX of P. trichocarpa.

In vivo imaging of paraCEST agents using frequency labeled exchange transfer MRI.

PURPOSE: A main obstacle to in vivo applications of paramagnetic chemical exchange saturation transfer (paraCEST) is interference from endogenous tissue magnetization transfer contrast (MTC). The suitability of excitation-based frequency labeled exchange transfer (FLEX) to separate out such MTC effects in vivo was tested. METHODS: The FLEX sequence measures modulation of the water signal based on the chemical shift evolution of solute proton magnetization as a function of evolution time. Time-domain analysis of this water signal allows identification of different solute components and provides a mechanism to separate out the rapidly decaying MTC components with short effective transverse relaxation time ( T2*) values. RESULTS: FLEX imaging of paraCEST agents was possible in vitro in phantoms and in vivo in mouse kidneys and bladder. The results demonstrated that FLEX is capable of separating out the MTC signal from tissues in vivo while providing a quantitative exchange rate for the rapidly exchanging paraCEST water protons by fitting the FLEX time-domain signal to FLEX theory. CONCLUSIONS: The first in vivo FLEX images of a paraCEST agent were acquired, which allowed separation of the tissue MTC components. These results show that FLEX imaging has potential for imaging the distribution of functional paraCEST agents in biological tissues.

Joint diffusional kurtosis magnetic resonance imaging analysis of white matter and the thalamus to identify subcortical ischemic vascular disease.

Identifying subcortical ischemic vascular disease (SIVD) in older adults is important but challenging. Growing evidence suggests that diffusional kurtosis imaging (DKI) can detect SIVD-relevant microstructural pathology, and a systematic assessment of the discriminant power of DKI metrics in various brain tissue microstructures is urgently needed. Therefore, the current study aimed to explore the value of DKI and diffusion tensor imaging (DTI) metrics in detecting early-stage SIVD by combining multiple diffusion metrics, analysis strategies, and clinical-radiological constraints. This prospective study compared DKI with diffusivity and macroscopic imaging evaluations across the aging spectrum including SIVD, Alzheimer's disease (AD), and cognitively normal (NC) groups. Using a white matter atlas and segregated thalamus analysis with considerations of the pre-identified macroscopic pathology, the most effective diffusion metrics were selected and then examined using multiple clinical-radiological constraints in a two-group or three-group paradigm. A total of 122 participants (mean age, 74.6 ± 7.38 years, 72 women) including 42 with SIVD, 50 with AD, and 30 NC were evaluated. Fractional anisotropy, mean kurtosis, and radial kurtosis were critical metrics in detecting early-stage SIVD. The optimal selection of diffusion metrics showed 84.4-100% correct classification of the results in a three-group paradigm, with an area under the curve of .909-.987 in a two-group paradigm related to SIVD detection (all P < .001). We therefore concluded that greatly resilient to the effect of pre-identified macroscopic pathology, the combination of DKI/DTI metrics showed preferable performance in identifying early-stage SIVD among adults across the aging spectrum.

The impact of ZTE-based MR attenuation correction compared to CT-AC in 18F-FBPA PET before boron neutron capture therapy.

Tumor-to-normal ratio (T/N) measurement of 18F-FBPA is crucial for patient eligibility to receive boron neutron capture therapy. This study aims to compare the difference in standard uptake value ratios on brain tumors and normal brains using PET/MR ZTE and atlas-based attenuation correction with the current standard PET/CT attenuation correction. Regarding the normal brain uptake, the difference was not significant between PET/CT and PET/MR attenuation correction methods. The T/N ratio of PET/CT-AC, PET/MR ZTE-AC and PET/MR AB-AC were 2.34 ± 0.95, 2.29 ± 0.88, and 2.19 ± 0.80, respectively. The T/N ratio comparison showed no significance using PET/CT-AC and PET/MR ZTE-AC. As for the PET/MRI AB-AC, significantly lower T/N ratio was observed (- 5.18 ± 9.52%; p < 0.05). The T/N difference between ZTE-AC and AB-AC was also significant (4.71 ± 5.80%; p < 0.01). Our findings suggested PET/MRI imaging using ZTE-AC provided superior quantification on 18F-FBPA-PET compared to atlas-based AC. Using ZTE-AC on 18F-FBPA-PET /MRI might be crucial for BNCT pre-treatment planning.

Modulation of CEST images in vivo by T1 relaxation: a new approach in the design of responsive PARACEST agents.

A novel approach for the design of responsive paramagnetic chemical exchange saturation transfer (PARACEST) magnetic resonance imaging (MRI) agents has been developed where the signal is "turned on" by altering the longitudinal relaxation time (T1) of bulk water protons. To demonstrate this approach, a model Eu(DOTA-tetraamide) complex (DOTA = 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid) containing two nitroxide free radical units was synthesized. The nitroxide groups substantially shortened the T1 of the bulk water protons which, in turn, resulted in quenching of the CEST signal. Reduction of paramagnetic nitroxide moieties to a diamagnetic species resulted in the appearance of CEST. The modulation of CEST by T1 relaxation provides a new platform for designing biologically responsive MRI agents.