Comparative analysis of in situ and ex situ postmortem brain MRI: Evaluating volumetry, DTI, and relaxometry.

PURPOSE: To compare postmortem in situ with ex situ MRI parameters, including volumetry, diffusion tensor imaging (DTI), and relaxometry for assessing methodology-induced alterations, which is a crucial prerequisite when performing MRI biomarker validation. METHODS: MRI whole-brain scans of five deceased patients with amyotrophic lateral sclerosis were performed at 3 T. In situ scans were conducted within 32 h after death (SD 18 h), and ex situ scans after brain extraction and 3 months of formalin fixation. The imaging protocol included MP2RAGE, DTI, and multi-contrast spin-echo and multi-echo gradient-echo sequences. Volumetry, fractional anisotropy, mean diffusivity, T1, T2, and T 2 * $$ {T}_2^{\ast } $$ have been assessed for specific brain regions. RESULTS: When comparing ex situ to in situ values, the following results were obtained. Deep gray matter as well as the thalamus and the hippocampus showed a reduced volume. Fractional anisotropy was reduced in the cortex and the whole brain. Mean diffusivity was decreased in white matter and deep gray matter. T1 and T2 were reduced in all investigated structures, whereas T 2 * $$ {T}_2^{\ast } $$ was increased in the cortex. CONCLUSION: The results of this study show that the volumes and MRI parameters of several brain regions are potentially affected by tissue extraction and subsequent formalin fixation, suggesting that methodological alterations are present in ex situ MRI. To avoid overlap of indistinguishable methodological and disease-related changes, we recommend performing in situ postmortem MRI as an additional intermediate step for in vivo MRI biomarker validation.

Quantum Sensing Unravels Antioxidant Efficacy Within PCL/Matrigel Skin Equivalents.

Skin equivalents (SE) that recapitulate biological and mechanical characteristics of the native tissue are promising platforms for assessing cosmetics and studying fundamental biological processes. Methods to achieve SEs with well-organized structure, and ideal biological and mechanical properties are limited. Here, the combination of melt electrowritten PCL scaffolds and cell-laden Matrigel to fabricate SE is described. The PCL scaffold provides ideal structural and mechanical properties, preventing deformation of the model. The model consists of a top layer for seeding keratinocytes to mimic the epidermis, and a bottom layer of Matrigel-based dermal compartment with fibroblasts. The compressive modulus and the biological properties after 3-day coculture indicate a close resemblance with the native skin. Using the SE, a testing system to study the damage caused by UVA irradiation and evaluate antioxidant efficacy is established. The effectiveness of Tea polyphenols (TPs) and L-ascorbic acid (Laa) is compared based on free radical generation. TPs are demonstrated to be more effective in downregulating free radical generation. Further, T1 relaxometry is used to detect the generation of free radicals at a single-cell level, which allows tracking of the same cell before and after UVA treatment.

Comparison of test-retest reproducibility of DESPOT and 3D-QALAS for water T 1 and T 2 mapping.

Purpose: Relaxometry, specifically T 1 and T 2 mapping, has become an essential technique for assessing the properties of biological tissues related to various physiological and pathological conditions. Many techniques are being used to estimate T 1 and T 2 relaxation times, ranging from the traditional inversion or saturation recovery and spin-echo sequences to more advanced methods. Choosing the appropriate method for a specific application is critical since the precision and accuracy of T 1 and T 2 measurements are influenced by a variety of factors including the pulse sequence and its parameters, the inherent properties of the tissue being examined, the MRI hardware, and the image reconstruction. The aim of this study is to evaluate and compare the test-retest reproducibility of two advanced MRI relaxometry techniques (Driven Equilibrium Single Pulse Observation of T 1 and T 2, DESPOT, and 3D Quantification using an interleaved Look-Locker acquisition Sequence with a T 2 preparation pulse, QALAS), for T 1 and T 2 mapping in a healthy volunteer cohort. Methods: 10 healthy volunteers underwent brain MRI at 1.3 mm3 isotropic resolution, acquiring DESPOT and QALAS data (~11.8 and ~5 minutes duration, including field maps, respectively), test-retest with subject repositioning, on a 3.0 Tesla Philips Ingenia Elition scanner. To reconstruct the T 1 and T 2 maps, we used an equation-based algorithm for DESPOT and a dictionary-based algorithm that incorporates inversion efficiency and B 1 -field inhomogeneity for QALAS. The test-retest reproducibility was assessed using the coefficient of variation (CoV), intraclass correlation coefficient (ICC) and Bland-Altman plots. Results: Our results indicate that both the DESPOT and QALAS techniques demonstrate good levels of test-retest reproducibility for T 1 and T 2 mapping across the brain. Higher whole-brain voxel-to-voxel ICCs are observed in QALAS for T 1 (0.84 ± 0.039) and in DESPOT for T 2 (0.897 ± 0.029). The Bland-Altman plots show smaller bias and variability of T 1 estimates for QALAS (mean of -0.02 s, and upper and lower limits of -0.14 and 0.11 s, 95% CI) than for DESPOT (mean of -0.02 s, and limits of -0.31 and 0.27 s). QALAS also showed less variability (mean 1.08 ms, limits -1.88 to 4.04 ms) for T 2 compared to DESPOT (mean of 2.56 ms, and limits -17.29 to 22.41 ms). The within-subject CoVs for QALAS range from 0.6% (T 2 in CSF) to 5.8% (T 2 in GM), while for DESPOT they range from 2.1% (T 2 in CSF) to 6.7% (T 2 in GM). The between-subject CoVs for QALAS range from 2.5% (T 2 in GM) to 12% (T 2 in CSF), and for DESPOT they range from 3.7% (T 2 in WM) to 9.3% (T 2 in CSF). Conclusion: Overall, QALAS demonstrated better reproducibility for T 1 and T 2 measurements than DESPOT, in addition to reduced acquisition time.

T2-relaxometry in a large cohort of hereditary transthyretin amyloidosis with polyneuropathy.

BACKGROUND: Previously, T2-relaxation time (T2app) and proton spin density (ρ) detected nerve injury in a small group of ATTRv amyloidosis. Here, we aim to quantify peripheral nerve impairment in a large cohort of symptomatic and asymptomatic ATTRv amyloidosis and correlate T2-relaxometry markers with clinical parameters and nerve conduction studies (NCS). METHODS: Eighty participants with pathologic variants of the transthyretin gene (TTRv) and 40 controls prospectively underwent magnetic resonance neurography. T2-relaxometry was performed, allowing to calculate tibial ρ, T2app and cross-sectional-area (CSA). Detailed clinical examinations and NCS of tibial and peroneal nerves were performed. RESULTS: Forty participants were classified as asymptomatic TTRv-carriers, 40 as symptomatic patients with polyneuropathy. ρ, T2app and CSA were significantly higher in symptomatic ATTRv amyloidosis (484.2 ± 14.8 a.u.; 70.6 ± 1.8 ms; 25.7 ± 0.9 mm2) versus TTRv-carriers (413.1 ± 9.4 a.u., p < 0.0001; 62.3 ± 1.3 ms, p = 0.0002; 19.0 ± 0.8 mm2, p < 0.0001) and versus controls (362.6 ± 7.5 a.u., p < 0.0001; 59.5 ± 1.0 ms, p < 0.0001; 15.4 ± 0.5 mm2, p < 0.0001). Only ρ and CSA differentiated TTRv-carriers from controls. ρ and CSA correlated with NCS in TTRv-carriers, while T2app correlated with NCS in symptomatic ATTRv amyloidosis. Both ρ and T2app correlated with clinical score. CONCLUSION: ρ and CSA can detect early nerve injury and correlate with electrophysiology in asymptomatic TTRv-carriers. T2app increases only in symptomatic ATTRv amyloidosis in whom it correlates with clinical scores and electrophysiology. Our results suggest that T2-relaxometry can provide biomarkers for disease- and therapy-monitoring in the future.

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.

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.

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.

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.

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.

Color Maps: Facilitating the Clinical Impact of Quantitative MRI.

Presenting quantitative data using non-standardized color maps potentially results in unrecognized misinterpretation of data. Clinically meaningful color maps should intuitively and inclusively represent data without misleading interpretation. Uniformity of the color gradient for color maps is critically important. Maximal color and lightness contrast, readability for color vision-impaired individuals, and recognizability of the color scheme are highly desirable features. This article describes the use of color maps in five key quantitative MRI techniques: relaxometry, diffusion-weighted imaging (DWI), dynamic contrast-enhanced (DCE)-MRI, MR elastography (MRE), and water-fat MRI. Current display practice of color maps is reviewed and shortcomings against desirable features are highlighted. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.

Simultaneous Multiparameter Mapping of the Liver in a Single Breath-Hold or Respiratory-Triggered Acquisition Using Multi-Inversion Spin and Gradient Echo MRI.

BACKGROUND: Quantitative parametric mapping is an increasingly important tool for noninvasive assessment of chronic liver disease. Conventional parametric mapping techniques require multiple breath-held acquisitions and provide limited anatomic coverage. PURPOSE: To investigate a multi-inversion spin and gradient echo (MI-SAGE) technique for simultaneous estimation of T1, T2, and T2* of the liver. STUDY TYPE: Prospective. SUBJECTS: Sixteen research participants, both adult and pediatric (age 17.5 ± 4.6 years, eight male), with and without known liver disease (seven asymptomatic healthy controls, two fibrotic liver disease, five steatotic liver disease, and two fibrotic and steatotic liver disease). FIELD STRENGTH/SEQUENCE: 1.5 T, single breath-hold and respiratory triggered MI-SAGE, breath-hold modified Look-Locker inversion recovery (MOLLI, T1 mapping), breath-hold gradient and spin echo (GRASE, T2 mapping), and multiple gradient echo (mGRE, T2* mapping) sequences. ASSESSMENT: Agreement between hepatic T1, T2, and T2* estimated using MI-SAGE and conventional parametric mapping sequences was evaluated. Repeatability and reproducibility of MI-SAGE were evaluated using a same-session acquisition and second-session acquisition. STATISTICAL TESTS: Bland-Altman analysis with bias assessment and limits of agreement (LOA) and intraclass correlation coefficients (ICC). RESULTS: Hepatic T1, T2, and T2* estimates obtained using the MI-SAGE technique had mean biases of 72 (LOA: -22 to 166) msec, -3 (LOA: -10 to 5) msec, and 2 (LOA: -5 to 8) msec (single breath-hold) and 36 (LOA: -43 to 120) msec, -3 (LOA: -17 to 11) msec, and 4 (LOA: -3 to 11) msec (respiratory triggered), respectively, in comparison to conventional acquisitions using MOLLI, GRASE, and mGRE. All MI-SAGE estimates had strong repeatability and reproducibility (ICC > 0.72). DATA CONCLUSION: Hepatic T1, T2, and T2* estimates obtained using an MI-SAGE technique were comparable to conventional methods, although there was a 12%/6% for breath-hold/respiratory triggered underestimation of T1 values compared to MOLLI. Both respiratory triggered and breath-hold MI-SAGE parameter maps demonstrated strong repeatability and reproducibility. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 2.

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.

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.

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.

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.

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.

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.

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.

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.

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.