Time-division multiplexing (TDM) sequence removes bias in T2 estimation and relaxation-diffusion measurements.

PURPOSE: To compare the performance of multi-echo (ME) and time-division multiplexing (TDM) sequences for accelerated relaxation-diffusion MRI (rdMRI) acquisition and to examine their reliability in estimating accurate rdMRI microstructure measures. METHOD: The ME, TDM, and the reference single-echo (SE) sequences with six TEs were implemented using Pulseq with single-band (SB) and multi-band 2 (MB2) acceleration factors. On a diffusion phantom, the image intensities of the three sequences were compared, and the differences were quantified using the normalized RMS error (NRMSE). Shinnar-Le Roux (SLR) pulses were implemented for the SB-ME and SB-SE sequences to investigate the impact of slice profiles on ME sequences. For the in-vivo brain scan, besides the image intensity comparison and T2-estimates, different methods were used to assess sequence-related effects on microstructure estimation, including the relaxation diffusion imaging moment (REDIM) and the maximum-entropy relaxation diffusion distribution (MaxEnt-RDD). RESULTS: TDM performance was similar to the gold standard SE acquisition, whereas ME showed greater biases (3-4× larger NRMSEs for phantom, 2× for in-vivo). T2 values obtained from TDM closely matched SE, whereas ME sequences underestimated the T2 relaxation time. TDM provided similar diffusion and relaxation parameters as SE using REDIM, whereas SB-ME exhibited a 60% larger bias in the map and on average 3.5× larger bias in the covariance between relaxation-diffusion coefficients. CONCLUSION: Our analysis demonstrates that TDM provides a more accurate estimation of relaxation-diffusion measurements while accelerating the acquisitions by a factor of 2 to 3.

Pulsed MPI Relaxometry of Brownian and Néel Field-Dependent Relaxation in Superparamagnetic Magnetite Nanoparticles Confirm Theory and Simulations.

Superparamagnetic iron oxide nanoparticles (SPIOs) are used as tracers in Magnetic Particle Imaging (MPI). It is crucial to understand the magnetic properties of SPIOs for optimizing MPI imaging contrast, resolution, and sensitivity. Brownian and Néel relaxation theory developed in the early 1950s posits that relaxation times can vary with particle size, shell thickness, medium viscosity, and the applied field strength. Magnetic relaxation can soon provide a unique imaging capability, the ability to distinguish bound from unbound MPI tracers in vivo. Yet experimental validation of these theories has not been completed. In this paper, a novel method of pulsed magnetic field relaxometry is used to directly probe the relaxation behavior of superparamagnetic magnetite nanoparticles over a spectrum of magnetic field amplitudes, providing the first experimental validation of theoretical relaxation models. It is also shown that closed-form approximations generated in the early 1970s accurately match both data and numerical Fokker Planck computational models, which are computationally burdensome. This means researchers can trust these approximations for future modeling. All the findings can be translated to sinusoidal excitations used in conventional MPI scanning trajectories.

Very-long T2-weighted imaging of the non-lesional brain tissue in multiple sclerosis patients.

The purpose of this study is to demonstrate that T2-weighted imaging with very long echo time (TE > 300 ms) can provide relevant information in neurodegenerative/inflammatory disorder. Twenty patients affected by relapsing-remitting multiple sclerosis with stable disease course underwent 1.5 T 3D FLAIR, 3D T1-weighted, and a multi-echo sequence with 32 echoes (TE = 10-320 ms). Focal lesions (FL) were identified on FLAIR. T1-images were processed to segment deep gray matter (dGM), white matter (WM), FL sub-volumes with T1 hypo-intensity (T1FL), and dGM volumes (atrophy). Clinical-radiological parameters included Expanded Disability Status Scale (EDSS), disease duration, patient age, T1FL, and dGM atrophy. Correlation analysis was performed between the mean signal intensity (SI) computed on the non-lesional dGM and WM at different TE versus the clinical-radiological parameters. Multivariable linear regressions were fitted to the data to assess the association between the dependent variable EDSS and the independent variables obtained by T1FL lesion load and the mean SI of dGM and WM at the different TE. A clear trend is observed, with a systematic strengthening of the significance of the correlation at longer TE for all the relationships with the clinical-radiological parameters, becoming significant (p < 0.05) for EDSS, T1FL volumes, and dGM atrophy. Multivariable linear regressions show that at shorter TE, the SI of the T2-weighted sequences is not relevant for describing the EDSS variability while the T1FL volumes are relevant, and vice versa, at very-long TEs (around 300 ms); the SI of the T2-weighted sequences significantly (p < 0.05) describes the EDSS variability. By very long TE, the SI primarily originates from water with a T2 longer than 250 ms and/or free water, which may be arising from the perivascular space (PVS). Very-long T2-weighting might detect dilated PVS and represent an unexplored MR approach in neurofluid imaging of neurodegenerative/inflammatory diseases.

Automatic pipeline for segmentation of LV myocardium on quantitative MR T1 maps using deep learning model and computation of radial T1 and ECV values.

Native T1 mapping is a non-invasive technique used for early detection of diffused myocardial abnormalities, and it provides baseline tissue characterization. Post-contrast T1 mapping enhances tissue differentiation, enables extracellular volume (ECV) calculation, and improves myocardial viability assessment. Accurate and precise segmenting of the left ventricular (LV) myocardium on T1 maps is crucial for assessing myocardial tissue characteristics and diagnosing cardiovascular diseases (CVD). This study presents a deep learning (DL)-based pipeline for automatically segmenting LV myocardium on T1 maps and automatic computation of radial T1 and ECV values. The study employs a multicentric dataset consisting of retrospective multiparametric MRI data of 332 subjects to develop and assess the performance of the proposed method. The study compared DL architectures U-Net and Deep Res U-Net for LV myocardium segmentation, which achieved a dice similarity coefficient of 0.84 ± 0.43 and 0.85 ± 0.03, respectively. The dice similarity coefficients computed for radial sub-segmentation of the LV myocardium on basal, mid-cavity, and apical slices were 0.77 ± 0.21, 0.81 ± 0.17, and 0.61 ± 0.14, respectively. The t-test performed between ground truth vs. predicted values of native T1, post-contrast T1, and ECV showed no statistically significant difference (p > 0.05) for any of the radial sub-segments. The proposed DL method leverages the use of quantitative T1 maps for automatic LV myocardium segmentation and accurately computing radial T1 and ECV values, highlighting its potential for assisting radiologists in objective cardiac assessment and, hence, in CVD diagnostics.

Simultaneous whole-liver water T 1 $$ {\mathrm{T}}_1 $$ and T 2 $$ {\mathrm{T}}_2 $$ mapping with isotropic resolution during free-breathing.

PURPOSE: To develop and validate a data acquisition scheme combined with a motion-resolved reconstruction and dictionary-matching-based parameter estimation to enable free-breathing isotropic resolution self-navigated whole-liver simultaneous water-specific T 1 $$ {\mathrm{T}}_1 $$ ( wT 1 $$ {\mathrm{wT}}_1 $$ ) and T 2 $$ {\mathrm{T}}_2 $$ ( wT 2 $$ {\mathrm{wT}}_2 $$ ) mapping for the characterization of diffuse and oncological liver diseases. METHODS: The proposed data acquisition consists of a magnetization preparation pulse and a two-echo gradient echo readout with a radial stack-of-stars trajectory, repeated with different preparations to achieve different T 1 $$ {\mathrm{T}}_1 $$ and T 2 $$ {\mathrm{T}}_2 $$ contrasts in a fixed acquisition time of 6 min. Regularized reconstruction was performed using self-navigation to account for motion during the free-breathing acquisition, followed by water-fat separation. Bloch simulations of the sequence were applied to optimize the sequence timing for B 1 $$ {B}_1 $$ insensitivity at 3 T, to correct for relaxation-induced blurring, and to map T 1 $$ {\mathrm{T}}_1 $$ and T 2 $$ {\mathrm{T}}_2 $$ using a dictionary. The proposed method was validated on a water-fat phantom with varying relaxation properties and in 10 volunteers against imaging and spectroscopy reference values. The performance and robustness of the proposed method were evaluated in five patients with abdominal pathologies. RESULTS: Simulations demonstrate good B 1 $$ {B}_1 $$ insensitivity of the proposed method in measuring T 1 $$ {\mathrm{T}}_1 $$ and T 2 $$ {\mathrm{T}}_2 $$ values. The proposed method produces co-registered wT 1 $$ {\mathrm{wT}}_1 $$ and wT 2 $$ {\mathrm{wT}}_2 $$ maps with a good agreement with reference methods (phantom: wT 1 = 1 . 02 wT 1,ref - 8 . 93 ms , R 2 = 0 . 991 $$ {\mathrm{wT}}_1=1.02\kern0.1em {\mathrm{wT}}_{1,\mathrm{ref}}-8.93\kern0.1em \mathrm{ms},{R}^2=0.991 $$ ; wT 2 = 1 . 03 wT 2,ref + 0 . 73 ms , R 2 = 0 . 995 $$ {\mathrm{wT}}_2=1.03\kern0.1em {\mathrm{wT}}_{2,\mathrm{ref}}+0.73\kern0.1em \mathrm{ms},{R}^2=0.995 $$ ). The proposed wT 1 $$ {\mathrm{wT}}_1 $$ and wT 2 $$ {\mathrm{wT}}_2 $$ mapping exhibits good repeatability and can be robustly performed in patients with pathologies. CONCLUSIONS: The proposed method allows whole-liver wT 1 $$ {\mathrm{wT}}_1 $$ and wT 2 $$ {\mathrm{wT}}_2 $$ quantification with high accuracy at isotropic resolution in a fixed acquisition time during free-breathing.

Characterizing T1 in the fetal brain and placenta over gestational age at 0.55T.

PURPOSE: T1 mapping and T1-weighted contrasts have a complimentary but currently under utilized role in fetal MRI. Emerging clinical low field scanners are ideally suited for fetal T1 mapping. The advantages are lower T1 values which results in higher efficiency and reduced field inhomogeneities resulting in a decreased requirement for specialist tools. In addition the increased bore size associated with low field scanners provides improved patient comfort and accessibility. This study aims to demonstrate the feasibility of fetal brain T1 mapping at 0.55T. METHODS: An efficient slice-shuffling inversion-recovery echo-planar imaging (EPI)-based T1-mapping and postprocessing was demonstrated for the fetal brain at 0.55T in a cohort of 38 fetal MRI scans. Robustness analysis was performed and placental measurements were taken for validation. RESULTS: High-quality T1 maps allowing the investigation of subregions in the brain were obtained and significant correlation with gestational age was demonstrated for fetal brain T1 maps ( p < 0 . 05 $$ p<0.05 $$ ) as well as regions-of-interest in the deep gray matter and white matter. CONCLUSIONS: Efficient, quantitative T1 mapping in the fetal brain was demonstrated on a clinical 0.55T MRI scanner, providing foundations for both future research and clinical applications including low-field specific T1-weighted acquisitions.

T2*-Relaxometry MRI to Assess Third Trimester Placental and Fetal Brain Oxygenation and Placental Characteristics in Healthy Fetuses and Fetuses With Congenital Heart Disease.

BACKGROUND: Congenital heart disease (CHD) has been linked to impaired placental and fetal brain development. Assessing the placenta and fetal brain in parallel may help further our understanding of the relationship between development of these organs. HYPOTHESIS: 1) Placental and fetal brain oxygenation are correlated, 2) oxygenation in these organs is reduced in CHD compared to healthy controls, and 3) placental structure is altered in CHD. STUDY TYPE: Retrospective case-control. POPULATION: Fifty-one human fetuses with CHD (32 male; median [IQR] gestational age [GA] = 32.0 [30.9-32.9] weeks) and 30 from uncomplicated pregnancies with normal birth outcomes (18 male; median [IQR] GA = 34.5 [31.9-36.7] weeks). FIELD STRENGTH/SEQUENCE: 1.5 T single-shot multi-echo-gradient-echo echo-planar imaging. ASSESSMENT: Masking was performed using an automated nnUnet model. Mean brain and placental T2* and quantitative measures of placental texture, volume, and morphology were calculated. STATISTICAL TESTS: Spearman's correlation coefficient for determining the association between brain and placental T2*, and between brain and placental characteristics with GA. P-values for comparing brain T2*, placenta T2*, and placental characteristics between groups derived from ANOVA. Significance level P < 0.05. RESULTS: There was a significant positive association between placental and fetal brain T2* (⍴ = 0.46). Placental and fetal brain T2* showed a significant negative correlation with GA (placental T2* ⍴ = -0.65; fetal brain T2* ⍴ = -0.32). Both placental and fetal brain T2* values were significantly reduced in CHD, after adjusting for GA (placental T2*: control = 97 [±24] msec, CHD = 83 [±23] msec; brain T2*: control = 218 [±26] msec, CHD = 202 [±25] msec). Placental texture and morphology were also significantly altered in CHD (Texture: control = 0.84 [0.83-0.87], CHD = 0.80 [0.78-0.84]; Morphology: control = 9.9 [±2.2], CHD = 10.8 [±2.0]). For all fetuses, there was a significant positive association between placental T2* and placental texture (⍴ = 0.46). CONCLUSION: Placental and fetal brain T2* values are associated in healthy fetuses and those with CHD. Placental and fetal brain oxygenation are reduced in CHD. Placental appearance is significantly altered in CHD and shows associations with placental oxygenation, suggesting altered placental development and function may be related. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 3.

Microstructural characterization of multiple sclerosis lesion phenotypes using multiparametric longitudinal analysis.

BACKGROUND AND OBJECTIVES: In multiple sclerosis (MS), slowly expanding lesions were shown to be associated with worse disability and prognosis. Their timely detection from cross-sectional data at early disease stages could be clinically relevant to inform treatment planning. Here, we propose to use multiparametric, quantitative MRI to allow a better cross-sectional characterization of lesions with different longitudinal phenotypes. METHODS: We analysed T1 and T2 relaxometry maps from a longitudinal cohort of MS patients. Lesions were classified as enlarging, shrinking, new or stable based on their longitudinal volumetric change using a newly developed automated technique. Voxelwise deviations were computed as z-scores by comparing individual patient data to T1, T2 and T2/T1 normative values from healthy subjects. We studied the distribution of microstructural properties inside lesions and within perilesional tissue. RESULTS AND CONCLUSIONS: Stable lesions exhibited the highest T1 and T2 z-scores in lesion tissue, while the lowest values were observed for new lesions. Shrinking lesions presented the highest T1 z-scores in the first perilesional ring while enlarging lesions showed the highest T2 z-scores in the same region. Finally, a classification model was trained to predict the longitudinal lesion type based on microstructural metrics and feature importance was assessed. Z-scores estimated in lesion and perilesional tissue from T1, T2 and T2/T1 quantitative maps carry discriminative and complementary information to classify longitudinal lesion phenotypes, hence suggesting that multiparametric MRI approaches are essential for a better understanding of the pathophysiological mechanisms underlying disease activity in MS lesions.

Three-dimensional simultaneous T1 and T2* relaxation times and quantitative susceptibility mapping at 3 T: A multicenter validation study.

We aimed to determine the intra-site repeatability and cross-site reproducibility of T1 and T2* relaxation times and quantitative susceptibility (χ) values obtained through quantitative parameter mapping (QPM) at 3 T. This prospective study included three 3-T scanners with the same hardware and software platform at three sites. The brains of twelve healthy volunteers were scanned three times using QPM at three sites. Intra-site repeatability and cross-site reproducibility were evaluated based on voxel-wise and region-of-interest analyses. The within-subject coefficient of variation (wCV), within-subject standard deviation (wSD), linear regression, Bland-Altman plot, and intraclass correlation coefficient (ICC) were used for evaluation. The intra-site repeatability wCV was 11.9 ± 6.86% for T1 and 3.15 ± 0.03% for T2*, and wSD of χ at 3.35 ± 0.10 parts per billion (ppb). Intra-site ICC(1,k) values for T1, T2*, and χ were 0.878-0.904, 0.972-0.976, and 0.966-0.972, respectively, indicating high consistency within the same scanner. Linear regression analysis revealed a strong agreement between measurements from each site and the site-average measurement, with R-squared values ranging from 0.79 to 0.83 for T1, 0.94-0.95 for T2*, and 0.95-0.96 for χ. The cross-site wCV was 13.4 ± 5.47% for T1 and 3.69 ± 2.25% for T2*, and cross-site wSD of χ at 4.08 ± 3.22 ppb. The cross-site ICC(2,1) was 0.707, 0.913, and 0.902 for T1, T2*, and χ, respectively. QPM provides T1, T2*, and χ values with an intra-site repeatability of <12% and cross-site reproducibility of <14%. These findings may contribute to the development of multisite studies.

Dynamics for High-Sensitivity Detection of Free Radicals in Primary Bronchial Epithelial Cells upon Stimulation with Cigarette Smoke Extract.

Chronic obstructive pulmonary disease (COPD), the third leading cause of death worldwide, is caused by chronic exposure to toxic particles and gases, such as cigarette smoke. Free radicals, which are produced during a stress response to toxic particles, play a crucial role in disease progression. Measuring these radicals is difficult since the complex mixture of chemicals within cigarette smoke interferes with radical detection. We used a new quantum sensing technique called relaxometry to measure free radicals with nanoscale resolution on cells from COPD patients and healthy controls exposed to cigarette smoke extract (CSE) or control medium. Epithelial cells from COPD patients display a higher free radical load than those from healthy donors and are more vulnerable to CSE. We show that epithelial cells of COPD patients are more susceptible to the damaging effects of cigarette smoke, leading to increased release of free radicals.

Improved quantitative parameter estimation for prostate T2 relaxometry using convolutional neural networks.

OBJECTIVE: Quantitative parameter mapping conventionally relies on curve fitting techniques to estimate parameters from magnetic resonance image series. This study compares conventional curve fitting techniques to methods using neural networks (NN) for measuring T2 in the prostate. MATERIALS AND METHODS: Large physics-based synthetic datasets simulating T2 mapping acquisitions were generated for training NNs and for quantitative performance comparisons. Four combinations of different NN architectures and training corpora were implemented and compared with four different curve fitting strategies. All methods were compared quantitatively using synthetic data with known ground truth, and further compared on in vivo test data, with and without noise augmentation, to evaluate feasibility and noise robustness. RESULTS: In the evaluation on synthetic data, a convolutional neural network (CNN), trained in a supervised fashion using synthetic data generated from naturalistic images, showed the highest overall accuracy and precision amongst the methods. On in vivo data, this best performing method produced low-noise T2 maps and showed the least deterioration with increasing input noise levels. DISCUSSION: This study showed that a CNN, trained with synthetic data in a supervised manner, may provide superior T2 estimation performance compared to conventional curve fitting, especially in low signal-to-noise regions.

Verifying the cytotoxicity of a biodegradable zinc alloy with nanodiamond sensors.

Metals are widely utilized as implant materials for bone fixtures as well as stents. Biodegradable versions of these implants are highly desirable since patients do not have to undergo a second surgery for the materials to be removed. Attractive options for such materials are zinc silver alloys since they also offer the benefit of being antibacterial. However, it is important to investigate the effect of the degradation products of such alloys on the surrounding cells, taking into account silver cytotoxicity. Here we investigated zinc alloyed with 1 % of silver (Zn1Ag) and how differently concentrated extracts (1 %-100 %) of this material impact human umbilical vein endothelial cells (HUVECs). More specifically, we focused on free radical generation and oxidative stress as well as the impact on cell viability. To determine free radical production we used diamond-based quantum sensing as well as conventional fluorescent assays. The viability was assessed by observing cell morphology and the metabolic activity via the MTT assay. We found that 1 % and 10 % extracts are well tolerated by the cells. However, at higher extract concentrations we observed severe impact on cell viability and oxidative stress. We were also able to show that quantum sensing was able to detect significant free radical generation even at the lowest tested concentrations.

Myocardial T1 mapping using an instantaneous signal loss simulation modeling and a Bayesian estimation method: A robust T1 extraction method free of tuning parameters.

The Instantaneous Signal Loss Simulation (InSiL) model is a promising alternative to the classical mono-exponential fitting of the Modified Look-Locker Inversion-recovery (MOLLI) sequence in cardiac T1 mapping applications, which achieves better accuracy and is less sensitive to heart rate (HR) variations. Classical non-linear least squares (NLLS) estimation methods require some parameters of the model to be fixed a priori in order to give reliable T1 estimations and avoid outliers. This introduces further bias in the estimation, reducing the advantages provided by the InSiL model. In this paper, a novel Bayesian estimation method using a hierarchical model is proposed to fit the parameters of the InSiL model. The hierarchical Bayesian modeling has a shrinkage effect that works as a regularizer for the estimated values, by pulling spurious estimated values toward the group-mean, hence reducing greatly the number of outliers. Simulations, physical phantoms, and in-vivo human cardiac data have been used to show that this approach estimates accurately all the InSiL parameters, and achieve high precision estimation of the T1 compared to the classical MOLLI model and NLLS InSiL estimation.

Assessment of water relaxometry of meat under different ageing processes using time domain nuclear magnetic resonance relaxometry.

This study assessed water relaxometry of beef exposed to different ageing techniques by examining the inner and surface regions using time-domain nuclear magnetic resonance (TD-NMR) relaxometry. Beef strip loins were aged under vacuum (Wet), under vacuum using moisture absorbers (Abs), under vacuum using moisture absorbers and with mechanical tenderisation (AbsTend), or without any packaging (Dry). The ageing technique significantly influenced various meat parameters, including dehydration, total loss, and the moisture content of the meat surface. The transverse (T2) relaxation times provided a more sensitive indicator of the changes in meat water relaxometry than the longitudinal (T1) relaxation times. The Dry samples exhibited distinct differences in the T2 signals between the surface and inner regions of the meat. In particular, for the inner region, there were significant differences in signal areas between the Wet and Dry samples, and the Abs and AbsTend samples were positioned closely together between the Dry and Wet samples. The principal component analysis supported these findings: it indicated some differentiation among the ageing techniques in the score plot, but the differentiation was more pronounced when analysing the surface region. Additionally, there was a strong correlation between dehydration and the T2 values, leading to a clustering of the samples based on the ageing technique. The overlap between the Abs and AbsTend samples, situated between the Dry and Wet samples, suggests the potential of these treatments to produce meat with properties that are intermediate to Wet and Dry meat. Furthermore, tenderisation did not lead to greater dehydration.

Universal 1H Spin-Lattice NMR Relaxation Features of Sugar-A Step towards Quality Markers.

1H fast field-cycling and time-domain nuclear magnetic resonance relaxometry studies have been performed for 15 samples of sugar of different kinds and origins (brown, white, cane, beet sugar). The extensive data set, including results for crystal sugar and sugar/water mixtures, has been thoroughly analyzed, with a focus on identifying relaxation contributions associated with the solid and liquid fractions of the systems and non-exponentiality of the relaxation processes. It has been observed that 1H spin-lattice relaxation rates for crystal sugar (solid) vary between 0.45 s-1 and 0.59 s-1, and the relaxation process shows only small deviations from exponentiality (a quantitative measure of the exponentiality has been provided). The 1H spin-lattice relaxation process for sugar/water mixtures has turned out to be bi-exponential, with the relaxation rates varying between about 13 s-1-17 s-1 (for the faster component) and about 2.1 s-1-3.5 s-1 (for the slower component), with the ratio between the amplitudes of the relaxation contributions ranging between 2.8 and 4.2. The narrow ranges in which the parameters vary make them a promising marker of the quality and authenticity of sugar.

MR Relaxometry for Discriminating Malignant Ovarian Cystic Tumors: A Prospective Multicenter Cohort Study.

BACKGROUND: Endometriosis-associated ovarian cancer (EAOC) is a well-known type of cancer that arises from ovarian endometrioma (OE). OE contains iron-rich fluid in its cysts due to repeated hemorrhages in the ovaries. However, distinguishing between benign and malignant tumors can be challenging. We conducted a retrospective study on magnetic resonance (MR) relaxometry of cyst fluid to distinguish EAOC from OE and reported that this method showed good accuracy. The purpose of this study is to evaluate the accuracy of a non-invasive method in re-evaluating pre-surgical diagnosis of malignancy by a prospective multicenter cohort study. METHODS: After the standard diagnosis process, the R2 values were obtained using a 3T system. Data on the patients were then collected through the Case Report Form (CRF). Between December 2018 and March 2023, six hospitals enrolled 109 patients. Out of these, 81 patients met the criteria required for the study. RESULTS: The R2 values calculated using MR relaxometry showed good discriminating ability with a cut-off of 15.74 (sensitivity 80.6%, specificity 75.0%, AUC = 0.750, p < 0.001) when considering atypical or borderline tumors as EAOC. When atypical and borderline cases were grouped as OE, EAOC could be distinguished with a cut-off of 16.87 (sensitivity 87.0%, specificity 61.1%). CONCLUSIONS: MR relaxometry has proven to be an effective tool for discriminating EAOC from OE. Regular use of this method is expected to provide significant insights for clinical practice.

Time-division multiplexing (TDM) sequence removes bias in T2 estimation and relaxation-diffusion measurements.

Purpose: To compare the performance of multi-echo (ME) and time-division multiplexing (TDM) sequences for accelerated relaxation-diffusion MRI (rdMRI) acquisition and to examine their reliability in estimating accurate rdMRI microstructure measures. Method: The ME, TDM, and the reference single-echo (SE) sequences with six echo times (TE) were implemented using Pulseq with single-band (SB-) and multi-band 2 (MB2-) acceleration factors. On a diffusion phantom, the image intensities of the three sequences were compared, and the differences were quantified using the normalized root mean squared error (NRMSE). For the in-vivo brain scan, besides the image intensity comparison and T2-estimates, different methods were used to assess sequence-related effects on microstructure estimation, including the relaxation diffusion imaging moment (REDIM) and the maximum-entropy relaxation diffusion distribution (MaxEnt-RDD). Results: TDM performance was similar to the gold standard SE acquisition, whereas ME showed greater biases (3-4× larger NRMSEs for phantom, 2× for in-vivo). T2 values obtained from TDM closely matched SE, whereas ME sequences underestimated the T2 relaxation time. TDM provided similar diffusion and relaxation parameters as SE using REDIM, whereas SB-ME exhibited a 60% larger bias in the map and on average 3.5× larger bias in the covariance between relaxation-diffusion coefficients. Conclusion: Our analysis demonstrates that TDM provides a more accurate estimation of relaxation-diffusion measurements while accelerating the acquisitions by a factor of 2 to 3.

Dynamic water profile in various type of cheese analysed by means of Nuclear Magnetic Resonance relaxometry.

The aim of the study was to enquire to which extend 1H spin-lattice Nuclear Magnetic Resonance relaxometry data collected over a broad range of resonance frequencies (from 10kHz to 10MHz) have the potential to be used for assessing quality and authenticity of different categories of cheese. The following cheeses were selected mozzarella (M), processed cheese (C), pizza cheese (P) and pizza cheese with modified fat phase (PC), low-fat cheese (LF) and long ripened cheese (R). The cheeses from different production plants (1,2,3) and various cheese production batches (a, b, c) were used in the study. The samples from each group were subjected to instrumental composition analysis (FoodScan analyzer type 78810, FOSS, Hillerod, Denmark), water activity assessment (AQUA LAB 4TEV analyzer, type S40001855, USA) and determination of the NMRD profiles (SMARtracer FFC relaxometer, Stelar S.r.l, Italy, 2017). The state and dynamics of water present in products as free and bound water largely determines the properties of food products, including cheeses. NMR relaxometry studies of cheese enable to reveal relaxation features characteristic of specific categories of cheese. Consequently, the studies can be treated as a step toward exploiting NMR relaxometry for accessing quality and authenticity of cheese. It was shown that at low resonance frequencies, the lower the moisture, the larger the relaxation rate. The durability and quality of cheeses depend on the presence and condition of water, so it is necessary to find a relationship between the presence, condition and mobility of water in cheeses, to increase and improve the quality and extend the shelf life.

Assessment of bone tissue cytoarchitectonics by 2D 1H NMR relaxometry maps.

Bone is a complex tissue that fulfills the role of a resistance structure. This quality is most commonly assessed by bone densitometry, but bone strength may not only be related to bone mineral density but also to the preservation of bone cytoarchitectonics. The study included two groups of rats, ovariectomized and non-ovariectomized. Each group was divided into three batches: control, simvastatin-treated, and fenofibrate-treated. In the ovariectomized group, hypolipidemic treatment was instituted at 12 weeks post ovariectomy. One rat from each of the 6 batches was sacrificed 8 weeks after the start of treatment in the group. The experimental study was performed using a Bruker Minispec mq 20 spectrometer operating at a frequency of 20 MHz, subsequently also performed by 1H T2-T2 molecular exchange maps. The results were represented by T2-T2 molecular exchange maps that showed, comparatively, both pore size and their interconnectivity at the level of the femoral epiphysis, being able to evaluate both the effect of estrogen on bone tissue biology and the effect of the lipid-lowering medication, simvastatin, and fenofibrate, in both the presence and absence of estrogen. T2-T2 molecular exchange maps showed that the absence of estrogen results in an increase in bone tissue pore size and interconnectivity. In the presence of estrogen, lipid-lowering medication, both simvastatin and fenofibrate alter bone tissue cytoarchitectonics by reducing pore interconnectivity. In the absence of estrogen, fenofibrate improves bone tissue cytoarchitectonics, the T2-T2 molecular exchange map being similar to that of non-osteoporotic bone tissue.

A straightforward procedure to build a non-toxic relaxometry phantom with desired T1 and T2 times at 3T.

OBJECTIVE: To prepare and analyze soy-lecithin-agar gels for non-toxic relaxometry phantoms with tissue-like relaxation times at 3T. METHODS: Phantoms mimicking the relaxation times of various tissues (gray and white matter, kidney cortex and medulla, spleen, muscle, liver) were built and tested with a clinical 3T whole-body MR scanner. Simple equations were derived to calculate the appropriate concentrations of soy lecithin and agar in aqueous solutions to achieve the desired relaxation times. Phantoms were tested for correspondence between measurements and calculated T1 and T2 values, reproducibility, spatial homogeneity, and temporal stability. T1 and T2 mapping techniques and a 3D T1-weighted sequence with high spatial resolution were applied. RESULTS: Except for the liver relaxation phantom, all phantoms were successfully and reproducibly produced. Good agreement was found between the targeted and measured relaxation times. The percentage deviations from the targeted relaxation times were less than 3% for T1 and less than 6.5% for T2. In addition, the phantoms were homogeneous and had little to no air bubbles. However, the phantoms were unstable over time: after a storage period of 4 weeks, mold growth and also changes in relaxation times were detected in almost all phantoms. CONCLUSION: Soy-lecithin-agar gels are a non-toxic material for the construction of relaxometry phantoms with tissue-like relaxation times. They are easy to prepare, inexpensive and allow independent adjustment of T1 and T2. However, there is still work to be done to improve the long-term stability of the phantoms.