Evaluation of a novel composite of expanded polystyrene with rGO and SEBS-g-MA.

This study displays the effect of reduced graphene oxide (rGO) nanofiller and polystyrene-b-poly(ethylene-ran-butylene)-b-polystyrene-grafted maleic anhydride (SEBS-g-MA) on the optical, thermal, and mechanical features of expanded polystyrene (EPS). First, the thin films of pristine EPS and composites were prepared using solution cast method. The prepared films were subjected to fourier-transform infrared (FTIR), SEM, UV-visible spectrophotometer, thermogravimetric analysis/differential scanning calorimetry, and universal testing machine for structural, morphological, optical, thermal, and mechanical characterizations. Optical study revealed a significant increase in refractive index and absorption of composites than EPS. Indirect band-gap energy of EPS (~4.08 eV) was reduced to ~1.61 eV for rGO composite and ~ 2.23 eV for composite composed of rGO and SEBS-g-MA. Thermal analyses presented improvement in characterization temperatures such as T10, T50, Tp, Tm, and Tg of composites, which ultimately lead to the thermal stability of prepared composites than pristine EPS. Stress-strain curves displayed higher yield strength (46.62 MPa), Young's modulus (96.29 MPa), and strain at break (0.54%) for EPS+rGO composite than pure EPS having stress at break (1.01 MPa), Young's modulus (12.44 MPa), and strain at break (0.08%). Moreover, ductility with relatively higher strain at break (0.61%) and lower Young's modulus (79.32 MPa) and yield strength (32.98 MPa) was noticed in EPS+rGO+SEBS-g-MA composite than EPS+rGO composite film. Morphological analysis revealed a change in globular morphology of EPS and inhomogeneous dispersion of rGO in EPS to homogeneously dispersed rGO in EPS matrix without globules owing to the addition of SEBS-g-MA. The increase in compatibility of EPS and rGO due to SEBS-g-MA was also observed in FTIR spectra. RESEARCH HIGHLIGHTS: Here, the solution casting approach was used to create the composite film of EPS and rGO with globules of various sizes. After adding SEBS-g-MA, the shape altered to globular free films exhibiting homogenous dispersion of rGO in EPS matrix. An optical investigation showed that composite materials had a significantly higher refractive index and absorption than EPS. The optical, thermal, and mechanical investigations suggest that the produced composites may be a great substitute for virgin EPS, allowing for a wider range of applications.

Microstructure Evolution during High-Pressure Torsion in a 7xxx AlZnMgZr Alloy.

A homogenized, supersaturated AlZnMgZr alloy was processed via severe plastic deformation (SPD) using a high-pressure torsion (HPT) technique for different revolutions at room temperature to obtain an ultrafine-grained (UFG) microstructure. The microstructure and mechanical properties of the UFG samples were then studied using transmission electron microscopy (TEM), differential scanning calorimetry (DSC), and tensile and hardness measurements. The main purpose was to study the effect of shear strain on the evolution of the microstructure of the investigated alloy. We found a very interesting evolution of the decomposed microstructure in a wide range of shear strains imposed by HPT. While the global properties, such as the average grain size (~200 nm) and hardness (~2200 MPa) appeared unchanged, the local microstructure was continuously transformed. After 1 turn of HPT, the decomposed UFG structure contained relatively large precipitates inside grains. In the sample processed by five turns in HPT, the segregation of Zn atoms into grain boundaries (GBs) was also observed. After 10 turns, more Zn atoms were segregated into GBs and only smaller-sized precipitates were observed inside grains. The intensive solute segregations into GBs may significantly affect the ductility of the material, leading to its ultralow-temperature superplasticity. Our findings pave the way for achieving advanced microstructural and mechanical properties in nanostructured metals and alloys by engineering their precipitation and segregation by means of applying different HPT regimes.

The Use of Thermoporometry in the Study of Frost Resistance of Rocks.

From an engineering point of view, it is important to know the factors influencing the frost resistance of rocks with porosity above 2% due to their different frost resistance. The article focused on frost durability research using the thermoporometry method (TMP) and the assessment of water phase transition in the pore spaces of selected rocks. For this purpose, the differential scanning calorimetry method (DSC) was used with the adoption of an original algorithm for eliminating the thermal inertia of the measurement system. The results of the DSC method were supplemented with the results of pore size distribution using the mercury intrusion porosimetry method (MIP) and standard rock frost resistance tests. Based on the research carried out using the thermoporometry method, it was confirmed that the ability of water to freeze in the temperature range from -5 °C to -20 °C was important, as well as the ability of rocks to increase the degree of water saturation during freeze-thaw cycles. Based on calorimetric tests combined with thermoporometry, in the case of non-frost-resistant rocks, a significant (dominant) share of pores with a radius of under 10 nm (amounting to over 0.008 cm3/cm3) was found. Pore connections in the water freezing process do not influence the investigated rocks' frost resistance.

SPINNED: Simulation-based physics-informed neural network for deconvolution of dynamic susceptibility contrast MRI perfusion data.

PURPOSE: To propose the simulation-based physics-informed neural network for deconvolution of dynamic susceptibility contrast (DSC) MRI (SPINNED) as an alternative for more robust and accurate deconvolution compared to existing methods. METHODS: The SPINNED method was developed by generating synthetic tissue residue functions and arterial input functions through mathematical simulations and by using them to create synthetic DSC MRI time series. The SPINNED model was trained using these simulated data to learn the underlying physical relation (deconvolution) between the DSC-MRI time series and the arterial input functions. The accuracy and robustness of the proposed SPINNED method were assessed by comparing it with two common deconvolution methods in DSC MRI data analysis, circulant singular value decomposition, and Volterra singular value decomposition, using both simulation data and real patient data. RESULTS: The proposed SPINNED method was more accurate than the conventional methods across all SNR levels and showed better robustness against noise in both simulation and real patient data. The SPINNED method also showed much faster processing speed than the conventional methods. CONCLUSION: These results support that the proposed SPINNED method can be a good alternative to the existing methods for resolving the deconvolution problem in DSC MRI. The proposed method does not require any separate ground-truth measurement for training and offers additional benefits of quick processing time and coverage of diverse clinical scenarios. Consequently, it will contribute to more reliable, accurate, and rapid diagnoses in clinical applications compared with the previous methods including those based on supervised learning.

Hemodynamic property incorporated brain tumor segmentation by deep learning and density-based analysis of dynamic susceptibility contrast-enhanced magnetic resonance imaging (MRI).

Background: Magnetic resonance imaging (MRI) is a primary non-invasive imaging modality for tumor segmentation, leveraging its exceptional soft tissue contrast and high resolution. Current segmentation methods typically focus on structural MRI, such as T1-weighted post-contrast-enhanced or fluid-attenuated inversion recovery (FLAIR) sequences. However, these methods overlook the blood perfusion and hemodynamic properties of tumors, readily derived from dynamic susceptibility contrast (DSC) enhanced MRI. This study introduces a novel hybrid method combining density-based analysis of hemodynamic properties in time-dependent perfusion imaging with deep learning spatial segmentation techniques to enhance tumor segmentation. Methods: First, a U-Net convolutional neural network (CNN) is employed on structural images to delineate a region of interest (ROI). Subsequently, Hierarchical Density-Based Scans (HDBScan) are employed within the ROI to augment segmentation by exploring intratumoral hemodynamic heterogeneity through the investigation of tumor time course profiles unveiled in DSC MRI. Results: The approach was tested and evaluated using a cohort of 513 patients from the open-source University of Pennsylvania glioblastoma database (UPENN-GBM) dataset, achieving a 74.83% Intersection over Union (IoU) score when compared to structural-only segmentation. The algorithm also exhibited increased precision and localized predictions of heightened segmentation boundary complexity, resulting in a 146.92% increase in contour complexity (ICC) compared to the reference standard provided by the UPENN-GBM dataset. Importantly, segmenting tumors with the developed new approach uncovered a negative correlation of the tumor volume with the scores in the Karnofsky Performance Scale (KPS) clinically used for assessing the functional status of patients (-0.309), which is not observed with the prevailing segmentation standard. Conclusions: This work demonstrated that including hemodynamic properties of tissues from DSC MRI can improve existing structural or morphological feature-based tumor segmentation techniques with additional information on tumor biology and physiology. This approach can also be applied to other clinical indications that use perfusion MRI for diagnosis or treatment monitoring.

Differential scanning calorimetry in drug-membrane interactions.

Differential Scanning Calorimetry (DSC) is a central technique in investigating drug - membrane interactions, a critical component of pharmaceutical research. DSC measures the heat difference between a sample of interest and a reference as a function of temperature or time, contributing essential knowledge on the thermally induced phase changes in lipid membranes and how these changes are affected by incorporating pharmacological substances. The manuscript discusses the use of phospholipid bilayers, which can form structures like unilamellar and multilamellar vesicles, providing a simplified yet representative membrane model to investigate the complex dynamics of how drugs interact with and penetrate cellular barriers. The manuscript consolidates data from various studies, providing a comprehensive understanding of the mechanisms underlying drug - membrane interactions, the determinants that influence these interactions, and the crucial role of DSC in elucidating these components. It further explores the interactions of specific classes of drugs with phospholipid membranes, including non-steroidal anti-inflammatory drugs, anticancer agents, natural products with antioxidant properties, and Alzheimer's disease therapeutics. The manuscript underscores the critical importance of DSC in this field and the need for continued research to improve our understanding of these interactions, acting as a valuable resource for researchers.

Thermo-Structural Characterization of Phase Transitions in Amorphous Griseofulvin: From Sub-Tg Relaxation and Crystal Growth to High-Temperature Decomposition.

The processes of structural relaxation, crystal growth, and thermal decomposition were studied for amorphous griseofulvin (GSF) by means of thermo-analytical, microscopic, spectroscopic, and diffraction techniques. The activation energy of ~395 kJ·mol-1 can be attributed to the structural relaxation motions described in terms of the Tool-Narayanaswamy-Moynihan model. Whereas the bulk amorphous GSF is very stable, the presence of mechanical defects and micro-cracks results in partial crystallization initiated by the transition from the glassy to the under-cooled liquid state (at ~80 °C). A key aspect of this crystal growth mode is the presence of a sufficiently nucleated vicinity of the disrupted amorphous phase; the crystal growth itself is a rate-determining step. The main macroscopic (calorimetrically observed) crystallization process occurs in amorphous GSF at 115-135 °C. In both cases, the common polymorph I is dominantly formed. Whereas the macroscopic crystallization of coarse GSF powder exhibits similar activation energy (~235 kJ·mol-1) as that of microscopically observed growth in bulk material, the activation energy of the fine GSF powder macroscopic crystallization gradually changes (as temperature and/or heating rate increase) from the activation energy of microscopic surface growth (~105 kJ·mol-1) to that observed for the growth in bulk GSF. The macroscopic crystal growth kinetics can be accurately described in terms of the complex mechanism, utilizing two independent autocatalytic Sesták-Berggren processes. Thermal decomposition of GSF proceeds identically in N2 and in air atmospheres with the activation energy of ~105 kJ·mol-1. The coincidence of the GSF melting temperature and the onset of decomposition (both at 200 °C) indicates that evaporation may initiate or compete with the decomposition process.

A review on advancement of cocrystallization approach and a brief on screening, formulation and characterization of the same.

The objective of this review is, to discuss recent advancements in screening methods for co-formers, evaluation cum confirmation methods and co-crystallization with examples. Co-crystals are considered as a new form of an old drug entity. Co-crystals improve the stability, hygroscopicity, solubility, dissolution, and physicochemical properties of pure drugs without altering chemical and pharmacological properties. Advancement in co-crystal formulation methods like electrospray and laser-irradiation methods are showing potential for solvent-free co-crystallization and tends to give better yield and lesser loss of materials. Screening methods are also transformed from trial and error to in-silico methods, which facilitate the selection process by reducing the time of screening and increasing the number of co-formers to be screened. Advanced evaluation methods like Raman and solid-state NMR spectroscopy provide a better understanding of crystal lattice by pinpointing the interaction between drug/co-former molecules. The same evaluation methods can also differentiate between the formation of salt and co-crystals. Co-crystals are helping open a new door in pharmaceutical industries in the field of formulation for the improvement of physicochemical properties in existing old molecules and several new molecules. With a motto of "making a good drug better", co-crystals show scope for vast research and give researchers an ocean of opportunities to make the impossible, possible.

Numerical Simulation of Polyacrylamide Hydrogel Prepared via Thermally Initiated Frontal Polymerization.

Traditional polymer curing techniques present challenges such as a slow processing speed, high energy consumption, and considerable initial investment. Frontal polymerization (FP), a novel approach, transforms monomers into fully cured polymers through a self-sustaining exothermic reaction, which enhances speed, efficiency, and safety. This study focuses on acrylamide hydrogels, synthesized via FP, which hold significant potential for biomedical applications and 3D printing. Heat conduction is critical in FP, particularly due to its influence on the temperature distribution and reaction rate mechanisms, which affect the final properties of polymers. Therefore, a comprehensive analysis of heat conduction and chemical reactions during FP is presented through the establishment of mathematical models and numerical methods. Existing research on FP hydrogel synthesis primarily explores chemical modifications, with limited studies on numerical modeling. By utilizing Differential Scanning Calorimetry (DSC) data on the curing kinetics of polymerizable deep eutectic solvents (DES), this paper employs Malek's model selection method to establish an autocatalytic reaction model for FP synthesis. In addition, the finite element method is used to solve the reaction-diffusion model, examining the temperature evolution and curing degree during synthesis. The results affirm the nth-order autocatalytic model's accuracy in studying acrylamide monomer curing kinetics. Additionally, factors such as trigger temperature and solution initial temperature were found to influence the FP reaction's frontal propagation speed. The model's predictions on acrylamide hydrogel synthesis align with experimental data, filling the gap in numerical modeling for hydrogel FP synthesis and offering insights for future research on numerical models and temperature control in the FP synthesis of high-performance hydrogels.

A Novel Method to Enhance the Mechanical Properties of Polyacrylonitrile Nanofiber Mats: An Experimental and Numerical Investigation.

This study addresses the challenge of enhancing the transverse mechanical properties of oriented polyacrylonitrile (PAN) nanofibers, which are known for their excellent longitudinal tensile strength, without significantly compromising their inherent porosity, which is essential for effective filtration. This study explores the effects of doping PAN nanofiber composites with varying concentrations of polyvinyl alcohol (PVA) (0.5%, 1%, and 2%), introduced into the PAN matrix via a dip-coating method. This approach ensured a random distribution of PVA within the nanofiber mat, aiming to leverage the synergistic interactions between PAN fibers and PVA to improve the composite's overall performance. This synergy is primarily manifested in the structural and functional augmentation of the PAN nanofiber mats through localized PVA agglomerations, thin films between fibers, and coatings on the fibers themselves. Comprehensive evaluation techniques were employed, including scanning electron microscopy (SEM) for morphological insights; transverse and longitudinal mechanical testing; a thermogravimetric analysis (TGA) for thermal stability; and differential scanning calorimetry (DSC) for thermal behavior analyses. Additionally, a finite element method (FEM) analysis was conducted on a numerical simulation of the composite. Using our novel method, the results demonstrated that a minimal concentration of the PVA solution effectively preserved the porosity of the PAN matrix while significantly enhancing its mechanical strength. Moreover, the numerical simulations showed strong agreement with the experimental results, validating the effectiveness of PVA doping in enhancing the mechanical properties of PAN nanofiber mats without sacrificing their functional porosity.

Textural, rheological, melting properties, particle size distribution, and NMR relaxometry of cocoa hazelnut spread with inulin-stevia addition as sugar replacer.

This study investigated the influence of substituting 60, 80, and 100% of the sugar in traditional cocoa hazelnut paste (control) formulation with inulin-stevia (90:10, w/w) mixture on textural and rheological characteristics, melting behavior, water activity (aw), particle size distribution (PSD), and color. Textural, rheological, melting properties, and color of samples were analyzed after 1, 2, and 3 months of storage at 11°C. Nuclear magnetic resonance (NMR) relaxometry experiments were also performed to understand the interaction of new ingredients with oil. Replacement of sugar with inulin-stevia gave darker color, reduced Casson yield stress, and changed the textural parameters and melting profile of the samples depending on the level but did not create a remarkable effect on PSD and Casson plastic viscosity. Increasing inulin-stevia content yielded lower aw and higher T2a values indicating decreased mobility of water. Complete removal of sugar caused low spreadability. The results showed that an 80% replacement level yielded a product with similar textural parameters and fat-melting mouth feeling compared to control sample. Cocoa hazelnut spreads prepared with inulin and stevia showed good textural stability during storage.

Regression analysis for the determination of microplastics in sediments using differential scanning calorimetry.

This research addresses the growing need for fast and cost-efficient methods for microplastic (MP) analysis. We present a thermo-analytical method that enables the identification and quantification of different polymer types in sediment and sand composite samples based on their phase transition behavior. Differential scanning calorimetry (DSC) was performed, and the results were evaluated by using different regression models. The melting and crystallization enthalpies or the change in heat capacity at the glass transition point were measured as regression analysis data. Ten milligrams of sea sand was spiked with 0.05 to 1.5 mg of microplastic particles (size: 100 to 200 µm) of the semi-crystalline polymers LD-PE, HD-PE, PP, PA6, and PET, and the amorphous polymers PS and PVC. The results showed that a two-factorial regression enabled the unambiguous identification and robust quantification of different polymer types. The limits of quantification were 0.13 to 0.33 mg and 0.40 to 1.84 mg per measurement for semi-crystalline and amorphous polymers, respectively. Moreover, DSC is robust with regard to natural organic matrices and allows the fast and non-destructive analysis of microplastic within the analytical limits. Hence, DSC could expand the range of analytical methods for microplastics and compete with perturbation-prone chemical analyses such as thermal extraction-desorption gas chromatography-mass spectrometry or spectroscopic methods. Further work should focus on potential changes in phase transition behavior in more complex matrices and the application of DSC for MP analysis in environmental samples.

Comparison of computed tomography perfusion and magnetic resonance dynamic susceptibility contrast perfusion-weighted imaging in canine brain.

Brain perfusion allows for the evaluation of cerebral hemodynamics, particularly in brain infarcts and tumors. Computed tomography (CT) perfusion (CTP) provides reliable data; however, it has a limited scan field of view and radiation exposure. Magnetic resonance (MR) perfusion provides detailed imaging of small structures and a wide scan field of view. However, no study has compared CTP and MR perfusion and assessed the correlation between the perfusion parameters measured using CTP and MR perfusion. The aim of the present study was to assess the correlation and agreement of the cerebral perfusion derived from dynamic susceptibility contrast (DSC)-MRI and CTP in dogs. In this crossover design study, the cerebral blood volume (CBV), cerebral blood flow (CBF), mean transit time, and time to peak were measured in the temporal cerebral cortex, caudate nucleus, thalamus, piriform lobe, and hippocampus using CTP and DSC-MRI in six healthy beagle dogs and a dog with a pituitary tumor. On the color map of healthy beagles, blood vessels and the perivascular brain parenchyma appeared as red-green, indicating high perfusion, and the areas distant from the vessels appeared as green-blue, indicating low perfusion levels in CTP and DSC-MRI. CTP parameters were highest in the piriform lobe (CBF = 121.11 ± 12.78 mL/100 g/min and CBV = 8.70 ± 2.04 mL/100 g) and lowest in the thalamus (CBF = 63.75 ± 25.24 mL/100 g/min and CBV = 4.02 ± 0.55 mL/100 g). DSC-MRI parameters were also highest in the piriform lobe (CBF = 102.31 ± 14.73 mL/100 g/min and CBV = 3.17 ± 1.23 mL/100 g) and lowest in the thalamus (CBF = 37.73 ± 25.11 mL/100 g/min and CBV = 0.81 ± 0.44 mL/100 g) although there was no statistical correlation in the quantitative perfusion parameters between CTP and DSC-MRI. In a dog with a pituitary tumor, the color map of the tumor appeared as a red scale, indicating high perfusion and higher CBF and CBV on CTP (149 mL/100 g and 20 mL/100 g/min) and on DSC-MRI (116.3 mL/100 g and 15.32 mL/100 g/min) compared to those measured in healthy dogs. These findings indicate that DSC-MRI and CTP maps exhibit comparability and interchangeability in the assessment of canine brain perfusion.

Characterization of Beeswax and Rice Bran Wax Oleogels Based on Different Types of Vegetable Oils and Their Impact on Wheat Flour Dough Technological Behavior during Bun Making.

Five varieties of vegetable oil underwent oleogelation with two types of wax as follows: beeswax (BW) and rice bran wax (RW). The oleogels were analyzed for their physicochemical, thermal, and textural characteristics. The oleogels were used in the bun dough recipe at a percentage level of 5%, and the textural and rheological properties of the oleogel doughs were analyzed using dynamic and empirical rheology devices such as the Haake rheometer, the Rheofermentometer, and Mixolab. The thermal properties of beeswax oleogels showed a melting peak at a lower temperature for all the oils used compared with that of the oleogels containing rice bran wax. Texturally, for both waxes, as the percentage of wax increased, the firmness of the oleogels increased proportionally, which indicates better technological characteristics for the food industry. The effect of the addition of oleogels on the viscoelastic properties of the dough was measured as a function of temperature. All dough samples showed higher values for G' (storage modulus) than those of G″ (loss modulus) in the temperature range of 20-90 °C, suggesting a solid, elastic-like behavior of all dough samples with the addition of oleogels. The influence of the beeswax and rice bran oleogels based on different types of vegetable oils on the thermo-mechanical properties of wheat flour dough indicated that the addition of oleogels in dough recipes generally led to higher dough stability and lower values for the dough development time and those related to the dough's starch characteristics. Therefore, the addition of oleogels in dough recipes inhibits the starch gelatinization process and increases the shelf life of bakery products.

Thermosensitive In Situ Gelling Poloxamers/Hyaluronic Acid Gels for Hydrocortisone Ocular Delivery.

This study endeavored to overcome the physiological barriers hindering optimal bioavailability in ophthalmic therapeutics by devising drug delivery platforms that allow therapeutically effective drug concentrations in ocular tissues for prolonged times. Thermosensitive drug delivery platforms were formulated by blending poloxamers (F68 and F127) with low-molecular-weight hyaluronic acid (HA) in various concentrations and loaded with hydrocortisone (HC). Among the formulations examined, only three were deemed suitable based on their desirable gelling properties at a temperature close to the eye's surface conditions while also ensuring minimal gelation time for swift ocular application. Rheological analyses unveiled the ability of the formulations to develop gels at suitable temperatures, elucidating the gel-like characteristics around the physiological temperature essential for sustained drug release. The differential scanning calorimetry findings elucidated intricate hydrogel-water interactions, indicating that HA affects the water-polymer interactions within the gel by increasing the platform hydrophilicity. Also, in vitro drug release studies demonstrated significant hydrocortisone release within 8 h, governed by an anomalous transport mechanism, prompting further investigation for optimized release kinetics. The produced platforms offer promising prospects for efficacious ocular drug delivery, addressing pivotal challenges in ocular therapeutics and heralding future advancements in the domain.

Effect of DMSO on Structural Properties of DMPC and DPPC Liposome Suspensions.

The study and characterization of the biophysical properties of membranes and drug-membrane interactions represent a critical step in drug development, as biological membranes act as a barrier that the drug must overcome to reach its active site. Liposomes are widely used in drug delivery to circumvent the poor aqueous solubility of most drugs, improving systemic bioavailability and pharmacokinetics. Further, they can be targeted to deliver to specific disease sites, thus decreasing drug load, and reducing side effects and poor adherence to treatment. To improve drug solubility during liposome preparation, DMSO is the most widely used solvent. This raises concern about the potential effect of DMSO on membranes and leads us to investigate, using DSC and EPR, the influence of DMSO on the behavior of lipid model membranes of DMPC and DPPC. In addition, we tested the influence of DMSO on drug-membrane interaction, using compounds with different hydrophobicity and varying DMSO content, using the same experimental techniques. Overall, it was found that with up to 10% DMSO, changes in the bilayer fluidity or the thermotropic properties of the studied liposomes were not significant, within the experimental uncertainty. For higher concentrations of DMSO, there is a stabilization of both the gel and the rippled gel phases, and increased bilayer fluidity of DMPC and DPPC liposomes leading to an increase in membrane permeability.

Practical guidance to identify and troubleshoot suboptimal DSC-MRI results.

Relative cerebral blood volume (rCBV) derived from dynamic susceptibility contrast (DSC) perfusion MR imaging (pMRI) has been shown to be a robust marker of neuroradiological tumor burden. Recent consensus recommendations in pMRI acquisition strategies have provided a pathway for pMRI inclusion in diverse patient care centers, regardless of size or experience. However, even with proper implementation and execution of the DSC-MRI protocol, issues will arise that many centers may not easily recognize or be aware of. Furthermore, missed pMRI issues are not always apparent in the resulting rCBV images, potentiating inaccurate or missed radiological diagnoses. Therefore, we gathered from our database of DSC-MRI datasets, true-to-life examples showcasing the breakdowns in acquisition, postprocessing, and interpretation, along with appropriate mitigation strategies when possible. The pMRI issues addressed include those related to image acquisition and postprocessing with a focus on contrast agent administration, timing, and rate, signal-to-noise quality, and susceptibility artifact. The goal of this work is to provide guidance to minimize and recognize pMRI issues to ensure that only quality data is interpreted.

Blood compatibility of poly(propylene glycol diester) and its water structure observed by differential scanning calorimetry and 2H-nuclear magnetic resonance spectroscopy.

Recently, we applied solution 2H-nuclear magnetic resonance spectroscopy (2H NMR) to analyze the water (deuterium oxide, D2O) structure in several biopolymers at ambient temperature. We established that polymers with good blood compatibility (i.e. poly(2-methoxyethyl acrylate) (PMEA)) have water observed at high magnetic fields (upfield) compared with bulk water. Polymers containing poly(propylene glycol) (PPG) or poly(propylene oxide) (PPO) exhibit good compatibility; however, the reason for this remains unclear. In addition, reports on the blood compatibility of PPO/PPG are limited. Therefore, PPG diester (PPGest) was prepared as a model polymer, and its blood compatibility and water structure were investigated. PPGest exhibited excellent blood compatibility. The water in PPGest was observed upfield by 2H NMR, and it was defined as non-freezing water via differential scanning calorimetry. Based on these observations, the relationship between the blood compatibility and water structure of PPGest is discussed by comparing with those of PMEA, and the reason for the good performance of PPG/PPO-based polymers is discussed.

Non-invasive perfusion MR imaging of the human brain via breath-holding.

Dynamic susceptibility contrast (DSC) MRI plays a pivotal role in the accurate diagnosis and prognosis of several neurovascular diseases, but is limited by its reliance on gadolinium, an intravascularly injected chelated metal. Here, we determined the feasibility of measuring perfusion using a DSC analysis of breath-hold-induced gradient-echo-MRI signal changes. We acquired data at both 3 T and 7 T from ten healthy participants who engaged in eight consecutive breath-holds. By pairing a novel arterial input function strategy with a standard DSC MRI analysis, we measured the cerebral blood volume, flow, and transit delay, and found values to agree with those documented in the literature using gadolinium. We also observed voxel-wise agreement between breath-hold and arterial spin labeling measures of cerebral blood flow. Breath-holding resulted in significantly higher contrast-to-noise (6.2 at 3 T vs. 8.5 at 7 T) and gray matter-to-white matter contrast at higher field strength. Finally, using a simulation framework to assess the effect of dynamic vasodilation on perfusion estimation, we found global perfusion underestimation of 20-40%. For the first time, we have assessed the feasibility of and limitations associated with using breath-holds for perfusion estimation with DSC. We hope that the methods and results presented in this study will help pave the way toward contrast-free perfusion imaging, in both basic and clinical research.

Comparison of dynamic susceptibility contrast (DSC) using gadolinium and iron-based contrast agents in high-grade glioma at high-field MRI.

PURPOSE: To compare DSC-MRI using Gadolinium (GBCA) and Ferumoxytol (FBCA) in high-grade glioma at 3T and 7T MRI field strengths. We hypothesized that using FBCA at 7T would enhance the performance of DSC, as measured by contrast-to-noise ratio (CNR). METHODS: Ten patients (13 lesions) were assigned to 3T (6 patients, 6 lesions) or 7T (4 patients, 7 lesions). All lesions received 0.1 mmol/kg of GBCA on day 1. Ten lesions (4 at 3T and 6 at 7T) received a lower dose (0.6 mg/kg) of FBCA, followed by a higher dose (1.0-1.2 mg/kg), while 3 lesions (2 at 3T and 1 at 7T) received only a higher dose on Day 2. CBV maps with leakage correction for GBCA but not for FBCA were generated. The CNR and normalized CBV (nCBV) were analyzed on enhancing and non-enhancing high T2W lesions. RESULTS: Regardless of FBCA dose, GBCA showed higher CNR than FBCA at 7T, which was significant for high-dose FBCA (p < .05). Comparable CNR between GBCA and high-dose FBCA was observed at 3T. There was a trend toward higher CNR for FBCA at 3T than 7T. GBCA also showed nCBV twice that of FBCA at both MRI field strengths with significance at 7T. CONCLUSION: GBCA demonstrated higher image conspicuity, as measured by CNR, than FBCA on 7T. The stronger T2* weighting realized with higher magnetic field strength, combined with FBCA, likely results in more signal loss rather than enhanced performance on DSC. However, at clinical 3T, both GBCA and FBCA, particularly a dosage of 1.0-1.2 mg/kg (optimal for perfusion imaging), yielded comparable CNR.