Quantitative T2 Mapping of Acute Pancreatitis.

BACKGROUND: Quantification of the T2 signal by means of T2 mapping in acute pancreatitis (AP) has the potential to quantify the parenchymal edema. Quantitative T2 mapping may overcome the limitations of previously reported scoring systems for reliable assessment of AP. PURPOSE: To evaluate MR-derived pancreatic T2 mapping values in AP and correlate them with markers of disease severity. STUDY TYPE: Prospective single-center study. POPULATION: 76 adults with AP (20-91 years, females/males: 39/37). FIELD STRENGTH/SEQUENCE: Fat suppressed multiecho spin-echo prototype sequence to quantify T2 signal at 3T MRI. ASSESSMENT: The severity of AP was assessed clinically, biologically, and by contrast-enhanced CT (CECT) performed 48-72 hours after symptom onset. MRI was then performed ≤24 hours after CT. Two readers blinded to any clinical information independently evaluated the T2 values by placing three regions of interest inside the pancreatic head, body, and tail on the T2 mapping MR sequence. Results were compared with corresponding CECT images as the standard and clinical severity parameters, using the length of hospital stay as our primary endpoint. STATISTICAL TESTS: Continuous variables were compared using the Spearman's rank correlation coefficient, analysis of variance (ANOVA) or Student's t-test. RESULTS: T2 values significantly correlated with the length of hospital stay (rs (74) = 0.29), CT severity index (CTSI) (rs (73) = 0.61; CTSI 0-3: 72 ± 14 msec, CTSI 4-10: 88 ± 15), intensive care unit (ICU) admission (t(2.77) = -3.41) and presence of organ failure (t(6.72) = -3.42), whereas the CTSI and Ranson score were not significantly related with ICU admission (CTSI: P = 0.24; Ranson score: P = 0.24) and organ failure (CTSI: P = 0.11; Ranson score P = 0.11). CONCLUSION: T2 mapping correlates with AP severity parameters and is useful for assessing the severity of AP with higher sensitivity than the usual clinical and radiological scoring systems. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 2.

Brain morphometry in older adults with and without dementia using extremely rapid structural scans.

T1-weighted structural MRI is widely used to measure brain morphometry (e.g., cortical thickness and subcortical volumes). Accelerated scans as fast as one minute or less are now available but it is unclear if they are adequate for quantitative morphometry. Here we compared the measurement properties of a widely adopted 1.0 mm resolution scan from the Alzheimer's Disease Neuroimaging Initiative (ADNI = 5'12'') with two variants of highly accelerated 1.0 mm scans (compressed-sensing, CSx6 = 1'12''; and wave-controlled aliasing in parallel imaging, WAVEx9 = 1'09'') in a test-retest study of 37 older adults aged 54 to 86 (including 19 individuals diagnosed with a neurodegenerative dementia). Rapid scans produced highly reliable morphometric measures that largely matched the quality of morphometrics derived from the ADNI scan. Regions of lower reliability and relative divergence between ADNI and rapid scan alternatives tended to occur in midline regions and regions with susceptibility-induced artifacts. Critically, the rapid scans yielded morphometric measures similar to the ADNI scan in regions of high atrophy. The results converge to suggest that, for many current uses, extremely rapid scans can replace longer scans. As a final test, we explored the possibility of a 0'49'' 1.2 mm CSx6 structural scan, which also showed promise. Rapid structural scans may benefit MRI studies by shortening the scan session and reducing cost, minimizing opportunity for movement, creating room for additional scan sequences, and allowing for the repetition of structural scans to increase precision of the estimates.

SPARCQ: A new approach for fat fraction mapping using asymmetries in the phase-cycled balanced SSFP signal profile.

PURPOSE: To develop SPARCQ (Signal Profile Asymmetries for Rapid Compartment Quantification), a novel approach to quantify fat fraction (FF) using asymmetries in the phase-cycled balanced SSFP (bSSFP) profile. METHODS: SPARCQ uses phase-cycling to obtain bSSFP frequency profiles, which display asymmetries in the presence of fat and water at certain TRs. For each voxel, the measured signal profile is decomposed into a weighted sum of simulated profiles via multi-compartment dictionary matching. Each dictionary entry represents a single-compartment bSSFP profile with a specific off-resonance frequency and relaxation time ratio. Using the results of dictionary matching, the fractions of the different off-resonance components are extracted for each voxel, generating quantitative maps of water and FF and banding-artifact-free images for the entire image volume. SPARCQ was validated using simulations, experiments in a water-fat phantom and in knees of healthy volunteers. Experimental results were compared with reference proton density FFs obtained with 1 H-MRS (phantoms) and with multiecho gradient-echo MRI (phantoms and volunteers). SPARCQ repeatability was evaluated in six scan-rescan experiments. RESULTS: Simulations showed that FF quantification is accurate and robust for SNRs greater than 20. Phantom experiments demonstrated good agreement between SPARCQ and gold standard FFs. In volunteers, banding-artifact-free quantitative maps and water-fat-separated images obtained with SPARCQ and ME-GRE demonstrated the expected contrast between fatty and non-fatty tissues. The coefficient of repeatability of SPARCQ FF was 0.0512. CONCLUSION: SPARCQ demonstrates potential for fat quantification using asymmetries in bSSFP profiles and may be a promising alternative to conventional FF quantification techniques.

Submillimeter T1 atlas for subject-specific abnormality detection at 7T.

PURPOSE: Studies at 3T have shown that T1 relaxometry enables characterization of brain tissues at the single-subject level by comparing individual physical properties to a normative atlas. In this work, an atlas of normative T1 values at 7T is introduced with 0.6 mm isotropic resolution and its clinical potential is explored in comparison to 3T. METHODS: T1 maps were acquired in two separate healthy cohorts scanned at 3T and 7T. Using transfer learning, a template-based brain segmentation algorithm was adapted to ultra-high field imaging data. After segmenting brain tissues, volumes were normalized into a common space, and an atlas of normative T1 values was established by modeling the T1 inter-subject variability. A method for single-subject comparisons restricted to white matter and subcortical structures was developed by computing Z-scores. The comparison was applied to eight patients scanned at both field strengths for proof of concept. RESULTS: The proposed method for morphometry delivered segmentation masks without statistically significant differences from those derived with the original pipeline at 3T and achieved accurate segmentation at 7T. The established normative atlas allowed characterizing tissue alterations in single-subject comparisons at 7T, and showed greater anatomical details compared with 3T results. CONCLUSION: A high-resolution quantitative atlas with an adapted pipeline was introduced and validated. Several case studies on different clinical conditions showed the feasibility, potential and limitations of high-resolution single-subject comparisons based on quantitative MRI atlases. This method in conjunction with 7T higher resolution broadens the range of potential applications of quantitative MRI in clinical practice.

Assessment of idiopathic inflammatory myopathy using a deep learning method for muscle T2 mapping segmentation.

OBJECTIVE: To investigate the utility of an automatic deep learning (DL) method for segmentation of T2 maps in patients with idiopathic inflammatory myopathy (IIM) against healthy controls, and also the association of quantitative T2 values in patients with laboratory and pulmonary findings. METHODS: Structural MRI and T2 mapping of bilateral thigh muscles from patients with IIM and healthy volunteers were segmented using dedicated software based on a pre-trained convolutional neural network. Incremental and federated learning were implemented for continuous adaptation and improvement. Muscle T2 values derived from DL segmentation were compared between patients and healthy controls, and T2 values of patients were further analyzed with serum muscle enzymes, and interstitial lung disease (ILD) which was diagnosed and graded based on chest HRCT. RESULTS: Overall, 64 patients (27 patients with dermatomyositis, 29 with polymyositis, and 8 with antisynthetase syndrome (ASS)) and 10 healthy controls were included. By using DL-based muscle segmentation, T2 values generated from T2 maps accurately differentiated patients from those of controls (p < 0.001) with a cutoff value of 36.4 ms (sensitivity 96.9%, and specificity 100%). In patients with IIM, muscle T2 values positively correlated with all the serum muscle enzymes (all p < 0.05). ILD score of patients with ASS was markedly higher than that of those without ASS (p = 0.011), while dissociation between the severity of muscular involvement and ILD was observed (p = 0.080). CONCLUSION: Automatic DL could be used to segment thigh muscles and help quantitatively assess muscular inflammation of IIM through T2 mapping. KEY POINTS: • Muscle T2 mapping automatically segmented by deep learning can differentiate IIM from healthy controls. • T2 value, an indicator of active muscle inflammation, positively correlates with serum muscle enzymes. • T2 mapping can detect muscle disease in patients with normal muscle enzyme levels.

Morphological assessment of cartilage and osteoarthritis in clinical practice and research: Intermediate-weighted fat-suppressed sequences and beyond.

Magnetic resonance imaging (MRI) is widely regarded as the primary modality for the morphological assessment of cartilage and all other joint tissues involved in osteoarthritis. 2D fast spin echo fat-suppressed intermediate-weighted (FSE FS IW) sequences with a TE between 30 and 40ms have stood the test of time and are considered the cornerstone of MRI protocols for clinical practice and trials. These sequences offer a good balance between sensitivity and specificity and provide appropriate contrast and signal within the cartilage as well as between cartilage, articular fluid, and subchondral bone. Additionally, FS IW sequences enable the evaluation of menisci, ligaments, synovitis/effusion, and bone marrow edema-like signal changes. This review article provides a rationale for the use of FSE FS IW sequences in the morphological assessment of cartilage and osteoarthritis, along with a brief overview of other clinically available sequences for this indication. Additionally, the article highlights ongoing research efforts aimed at improving FSE FS IW sequences through 3D acquisitions with enhanced resolution, shortened examination times, and exploring the potential benefits of different magnetic field strengths. While most of the literature on cartilage imaging focuses on the knee, the concepts presented here are applicable to all joints. KEY POINTS: 1. MRI is currently considered the modality of reference for a "whole-joint" morphological assessment of osteoarthritis. 2. Fat-suppressed intermediate-weighted sequences remain the keystone of MRI protocols for the assessment of cartilage morphology, as well as other structures involved in osteoarthritis. 3. Trends for further development in the field of cartilage and joint imaging include 3D FSE imaging, faster acquisition including AI-based acceleration, and synthetic imaging providing multi-contrast sequences.

Evaluating reproducibility and subject-specificity of microstructure-informed connectivity.

Tractography enables identifying and evaluating the healthy and diseased brain's white matter pathways from diffusion-weighted magnetic resonance imaging data. As previous evaluation studies have reported significant false-positive estimation biases, recent microstructure-informed tractography algorithms have been introduced to improve the trade-off between specificity and sensitivity. However, a major limitation for characterizing the performance of these techniques is the lack of ground truth brain data. In this study, we compared the performance of two relevant microstructure-informed tractography methods, SIFT2 and COMMIT, by assessing the subject specificity and reproducibility of their derived white matter pathways. Specifically, twenty healthy young subjects were scanned at eight different time points at two different sites. Subject specificity and reproducibility were evaluated using the whole-brain connectomes and a subset of 29 white matter bundles. Our results indicate that although the raw tractograms are more vulnerable to the presence of false-positive connections, they are highly reproducible, suggesting that the estimation bias is subject-specific. This high reproducibility was preserved when microstructure-informed tractography algorithms were used to filter the raw tractograms. Moreover, the resulting track-density images depicted a more uniform coverage of streamlines throughout the white matter, suggesting that these techniques could increase the biological meaning of the estimated fascicles. Notably, we observed an increased subject specificity by employing connectivity pre-processing techniques to reduce the underlaying noise and the data dimensionality (using principal component analysis), highlighting the importance of these tools for future studies. Finally, no strong bias from the scanner site or time between measurements was found. The largest intraindividual variance originated from the sole repetition of data measurements (inter-run).

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

PURPOSE: To develop a 3D MR technique to simultaneously acquire proton multiparametric maps (T1 , T2 , and proton density) and sodium density weighted images over the whole brain. METHODS: We implemented a 3D stack-of-stars MR pulse sequence which consists of interleaved proton (1 H) and sodium (23 Na) excitations, tailored slice encoding gradients that can encode the same slice for both nuclei, and simultaneous readout with different radial trajectories (1 H, full-radial; 23 Na, center-out radial). The receive chain of our 7T scanner was modified to enable simultaneous acquisition of 1 H and 23 Na signal. A heuristically optimized flip angle train was implemented for proton MR fingerprinting (MRF). The SNR and the accuracy of proton T1 and T2 were evaluated in phantoms. Finally, in vivo application of the method was demonstrated in five healthy subjects. RESULTS: The SNR for the simultaneous measurement was almost identical to that for the single-nucleus measurements (<2% change). The proton T1 and T2 maps remained similar to the results from a reference 2D MRF technique (normalized RMS error in T1 ≈ 4.2% and T2 ≈ 11.3%). Measurements in healthy subjects corroborated these results and demonstrated the feasibility of our method for in vivo application. The in vivo T1 values measured using our method were lower than the results measured by other conventional techniques. CONCLUSIONS: With the 3D simultaneous implementation, we were able to acquire sodium and proton density weighted images in addition to proton T1 , T2 , and B1+ from 1 H MRF that covers the whole brain volume within 21 min.

Optimization of magnetization transfer contrast for EPI FLAIR brain imaging.

PURPOSE: To evaluate the impact of magnetization transfer (MT) on brain tissue contrast in turbo-spin-echo (TSE) and EPI fluid-attenuated inversion recovery (FLAIR) images, and to optimize an MT-prepared EPI FLAIR pulse sequence to match the tissue contrast of a clinical reference TSE FLAIR protocol. METHODS: Five healthy volunteers underwent 3T brain MRI, including single slice TSE FLAIR, multi-slice TSE FLAIR, EPI FLAIR without MT-preparation, and MT-prepared EPI FLAIR with variations of the MT-preparation parameters, including number of preparation pulses, pulse amplitude, and resonance offset. Automated co-registration and gray matter (GM) versus white matter (WM) segmentation was performed using a T1-MPRAGE acquisition, and the GM versus WM signal intensity ratio (contrast ratio) was calculated for each FLAIR acquisition. RESULTS: Without MT preparation, EPI FLAIR showed poor tissue contrast (contrast ratio = 0.98), as did single slice TSE FLAIR. Multi-slice TSE FLAIR provided high tissue contrast (contrast ratio = 1.14). MT-prepared EPI FLAIR closely approximated the contrast of the multi-slice TSE FLAIR images for two combinations of the MT-preparation parameters (contrast ratio = 1.14). Optimized MT-prepared EPI FLAIR provided a 50% reduction in scan time compared to the reference TSE FLAIR acquisition. CONCLUSION: Optimized MT-prepared EPI FLAIR provides comparable brain tissue contrast to the multi-slice TSE FLAIR images used in clinical practice.

Data-driven myelin water imaging based on T1 and T2 relaxometry.

Long acquisition times preclude the application of multiecho spin echo (MESE) sequences for myelin water fraction (MWF) mapping in daily clinical practice. In search of alternative methods, previous studies of interest explored the biophysical modeling of MWF from measurements of different tissue properties that can be obtained in scan times shorter than those required for the MESE. In this work, a novel data-driven estimation of MWF maps from fast relaxometry measurements is proposed and investigated. T1 and T2 relaxometry maps were acquired in a cohort of 20 healthy subjects along with a conventional MESE sequence. Whole-brain quantitative mapping was achieved with a fast protocol in 6 min 24 s. Reference MWF maps were derived from the MESE sequence (TA = 11 min 17 s) and their data-driven estimation from relaxometry measurements was investigated using three different modeling strategies: two general linear models (GLMs) with linear and quadratic regressors, respectively; a random forest regression model; and two deep neural network architectures, a U-Net and a conditional generative adversarial network (cGAN). Models were validated using a 10-fold crossvalidation. The resulting maps were visually and quantitatively compared by computing the root mean squared error (RMSE) between the estimated and reference MWF maps, the intraclass correlation coefficients (ICCs) between corresponding MWF values in different brain regions, and by performing Bland-Altman analysis. Qualitatively, the estimated maps appear to generally provide a similar, yet more blurred MWF contrast in comparison with the reference, with the cGAN model best capturing MWF variabilities in small structures. By estimating the average adjusted coefficient of determination of the GLM with quadratic regressors, we showed that 87% of the variability in the MWF values can be explained by relaxation times alone. Further quantitative analysis showed an average RMSE smaller than 0.1% for all methods. The ICC was greater than 0.81 for all methods, and the bias smaller than 2.19%. It was concluded that this work confirms the notion that relaxometry parameters contain a large part of the information on myelin water and that MWF maps can be generated from T1 /T2 data with minimal error. Among the investigated modeling approaches, the cGAN provided maps with the best trade-off between accuracy and blurriness. Fast relaxometry, like the 6 min 24 s whole-brain protocol used in this work in conjunction with machine learning, may thus have the potential to replace time-consuming MESE acquisitions.

Q-Dixon and GRAPPATINI T2 Mapping Parameters: A Whole Spinal Assessment of the Relationship Between Osteoporosis and Intervertebral Disc Degeneration.

BACKGROUND: The relationship between osteoporosis and intervertebral disc (IVD) degeneration remains controversial. Novel quantitative Dixon (Q-Dixon) and GRAPPATINI T2 mapping techniques have shown potential for evaluating the biochemical components of the spine. PURPOSE: To investigate the correlation of osteoporosis with IVD degeneration in postmenopausal women. STUDY TYPE: Prospective. SUBJECTS: A total of 105 postmenopausal females (mean age, 65 years; mean body mass index, 26 kg/m2 ). FIELD STRENGTH/SEQUENCE: 3 T; sagittal; 6-echo Q-Dixon, multiecho spin-echo GRAPPATINI T2 mapping, turbo spin echo (TSE) T1-weighted and TSE T2-weighted sequences. ASSESSMENT: The subjects were divided into normal (N = 47), osteopenia (N = 28), and osteoporosis (N = 30) groups according to quantitative computed tomography examination. The Pfirrmann grade of each IVD was obtained. Region of interest analysis was performed separately by two radiologists (X.L., with 10 years of experience, and S.C., with 20 years of experience) on a fat fraction map and T2 map to calculate the bone marrow fat fraction (BMFF) from the L1 to L5 vertebrae and the T2 values of each adjacent IVD separately. STATISTICAL TESTS: One-way analysis of variance, post-hoc comparisons, and Kruskal-Wallis H tests were performed to evaluate the differences in the magnetic resonance imaging parameters between the groups. The relationships between BMFF and the IVD features were analyzed using the Spearman correlation analysis and linear regression models. RESULTS: There were significant differences in BMFF among the three groups. The osteoporosis group had higher BMFF values (64.5 ± 5.9%). No significant correlation was found between BMFF and Pfirrmann grade (r = 0.251, P = 0.06). BMFF was significantly negatively correlated with the T2 of the adjacent IVD from L1 to L3 (r = -0.731; r = -0.637; r = -0.547), while significant weak correlations were found at the L4 to L5 levels (r = -0.337; r = -0.278). DATA CONCLUSION: This study demonstrated that osteoporosis is associated with IVD degeneration. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 4.

Value of T2 Mapping MRI for Prostate Cancer Detection and Classification.

BACKGROUND: Currently, multi-parametric prostate MRI (mpMRI) consists of a qualitative T2 , diffusion weighted, and dynamic contrast enhanced imaging. Quantification of T2 imaging might further standardize PCa detection and support artificial intelligence solutions. PURPOSE: To evaluate the value of T2 mapping to detect prostate cancer (PCa) and to differentiate PCa aggressiveness. STUDY TYPE: Retrospective single center cohort study. POPULATION: Forty-four consecutive patients (mean age 67 years; median PSA 7.9 ng/mL) with mpMRI and verified PCa by subsequent targeted plus systematic MR/ultrasound (US)-fusion biopsy from February 2019 to December 2019. FIELD STRENGTH/SEQUENCE: Standardized mpMRI at 3 T with an additionally acquired T2 mapping sequence. ASSESSMENT: Primary endpoint was the analysis of quantitative T2 values and contrast differences/ratios (CD/CR) between PCa and benign tissue. Secondary objectives were the correlation between T2 values, ISUP grade, apparent diffusion coefficient (ADC) value, and PI-RADS, and the evaluation of thresholds for differentiating PCa and clinically significant PCa (csPCa). STATISTICAL TESTS: Mann-Whitney test, Spearman's rank (rs ) correlation, receiver operating curves, Youden's index (J), and AUC were performed. Statistical significance was defined as P < 0.05. RESULTS: Median quantitative T2 values were significantly lower for PCa in PZ (85 msec) and PCa in TZ (75 msec) compared to benign PZ (141 msec) or TZ (97 msec) (P < 0.001). CD/CR between PCa and benign PZ (51.2/1.77), respectively TZ (19.8/1.29), differed significantly (P < 0.001). The best T2 -mapping threshold for PCa/csPCa detection was for TZ 81/86 msec (J = 0.929/1.0), and for PZ 110 msec (J = 0.834/0.905). Quantitative T2 values of PCa did not correlate significantly with the ISUP grade (rs  = 0.186; P = 0.226), ADC value (rs  = 0.138; P = 0.372), or PI-RADS (rs  = 0.132; P = 0.392). DATA CONCLUSION: Quantitative T2 values could differentiate PCa in TZ and PZ and might support standardization of mpMRI of the prostate. Different thresholds seem to apply for PZ and TZ lesions. However, in the present study quantitative T2 values were not able to indicate PCa aggressiveness. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

T2 mapping for the characterization of prostate lesions.

PURPOSE: Purpose of this study is to evaluate the diagnostic accuracy of quantitative T2/ADC values in differentiating between PCa and lesions showing non-specific inflammatory infiltrates and atrophy, features of chronic prostatitis, as the most common histologically proven differential diagnosis. METHODS: In this retrospective, single-center cohort study, we analyzed 55 patients suspected of PCa, who underwent mpMRI (3T) including quantitative T2 maps before robot-assisted mpMRI-TRUS fusion prostate biopsy. All prostate lesions were scored according to PI-RADS v2.1. Regions of interest (ROIs) were annotated in focal lesions and normal prostate tissue. Quantitative mpMRI values from T2 mapping and ADC were compared using two-tailed t tests. Receiver operating characteristic curves (ROCs) and cutoff were calculated to differentiate between PCa and chronic prostatitis. RESULTS: Focal lesions showed significantly lower ADC and T2 mapping values than normal prostate tissue (p < 0.001). PCa showed significantly lower ADC and T2 values than chronic prostatitis (p < 0.001). ROC analysis revealed areas under the receiver operating characteristic curves (AUCs) of 0.85 (95% CI 0.74-0.97) for quantitative ADC values and 0.84 (95% CI 0.73-0.96) for T2 mapping. A significant correlation between ADC and T2 values was observed (r = 0.70; p < 0.001). CONCLUSION: T2 mapping showed high diagnostic accuracy for differentiating between PCa and chronic prostatitis, comparable to the performance of ADC values.

Revisiting the T2 spectrum imaging inverse problem: Bayesian regularized non-negative least squares.

Multi-echo T2 magnetic resonance images contain information about the distribution of T2 relaxation times of compartmentalized water, from which we can estimate relevant brain tissue properties such as the myelin water fraction (MWF). Regularized non-negative least squares (NNLS) is the tool of choice for estimating non-parametric T2 spectra. However, the estimation is ill-conditioned, sensitive to noise, and highly affected by the employed regularization weight. The purpose of this study is threefold: first, we want to underline that the apparently innocuous use of two alternative parameterizations for solving the inverse problem, which we called the standard and alternative regularization forms, leads to different solutions; second, to assess the performance of both parameterizations; and third, to propose a new Bayesian regularized NNLS method (BayesReg). The performance of BayesReg was compared with that of two conventional approaches (L-curve and Chi-square (X2) fitting) using both regularization forms. We generated a large dataset of synthetic data, acquired in vivo human brain data in healthy participants for conducting a scan-rescan analysis, and correlated the myelin content derived from histology with the MWF estimated from ex vivo data. Results from synthetic data indicate that BayesReg provides accurate MWF estimates, comparable to those from L-curve and X2, and with better overall stability across a wider signal-to-noise range. Notably, we obtained superior results by using the alternative regularization form. The correlations reported in this study are higher than those reported in previous studies employing the same ex vivo and histological data. In human brain data, the estimated maps from L-curve and BayesReg were more reproducible. However, the T2 spectra produced by BayesReg were less affected by over-smoothing than those from L-curve. These findings suggest that BayesReg is a good alternative for estimating T2 distributions and MWF maps.

Probing myelin content of the human brain with MRI: A review.

Rapid and efficient transmission of electric signals among neurons of vertebrates is ensured by myelin-insulating sheaths surrounding axons. Human cognition, sensation, and motor functions rely on the integrity of these layers, and demyelinating diseases often entail serious cognitive and physical impairments. Magnetic resonance imaging radically transformed the way these disorders are monitored, offering an irreplaceable tool to noninvasively examine the brain structure. Several advanced techniques based on MRI have been developed to provide myelin-specific contrasts and a quantitative estimation of myelin density in vivo. Here, the vast offer of acquisition strategies developed to date for this task is reviewed. Advantages and pitfalls of the different approaches are compared and discussed.

Fast and high-resolution myelin water imaging: Accelerating multi-echo GRASE with CAIPIRINHA.

PURPOSE: Although several MRI methods have been explored to achieve in vivo myelin quantification, imaging the whole brain in clinically acceptable times and sufficiently high resolution remains challenging. To address this problem, this work investigates the acceleration of multi-echo T2 acquisitions based on the multi-echo gradient and spin echo (GRASE) sequence using CAIPIRINHA undersampling and adapted k-space reordering patterns. METHODS: A prototype multi-echo GRASE sequence supporting CAIPIRINHA parallel imaging was implemented. Multi-echo T2 data were acquired from 12 volunteers using the implemented sequence (1.6 × 1.6 × 1.6 mm3 , 84 slices, acquisition time [TA] = 10:30 min) and a multi-echo spin echo (MESE) sequence as reference (1.6 × 1.6 × 3.2 mm3 , single-slice, TA = 5:41 min). Myelin water fraction (MWF) maps derived from both acquisitions were compared via correlation and Bland-Altman analyses. In addition, scan-rescan datasets were acquired to evaluate the repeatability of the derived maps. RESULTS: Resulting maps from the MESE and multi-echo GRASE sequences were found to be correlated (r = 0.83). The Bland-Altman analysis revealed a mean bias of -0.2% (P = .24) with the limits of agreement ranging from -3.7% to 3.3%. The Pearson's correlation coefficient among MWF values obtained from the scan-rescan datasets was found to be 0.95 and the mean bias equal to 0.11% (P = .32), indicating good repeatability of the retrieved maps. CONCLUSION: By combining a 3D multi-echo GRASE sequence with CAIPIRINHA sampling, whole-brain MWF maps were obtained in 10:30 min with 1.6 mm isotropic resolution. The good correlation with conventional MESE-based maps demonstrates that the implemented sequence may be a promising alternative to time-consuming MESE acquisitions.

Compressed sensing with signal averaging for improved sensitivity and motion artifact reduction in fluorine-19 MRI.

Fluorine-19 (19 F) MRI of injected perfluorocarbon emulsions (PFCs) allows for the non-invasive quantification of inflammation and cell tracking, but suffers from a low signal-to-noise ratio and extended scan time. To address this limitation, we tested the hypotheses that a 19 F MRI pulse sequence that combines a specific undersampling regime with signal averaging has both increased sensitivity and robustness against motion artifacts compared with a non-averaged fully sampled pulse sequence, when both datasets are reconstructed with compressed sensing. As a proof of principle, numerical simulations and phantom experiments were performed on selected variable ranges to characterize the point spread function of undersampling patterns, as well as the vulnerability to noise of undersampling and reconstruction parameters with paired numbers of x signal averages and acceleration factor x (NAx-AFx). The numerical simulations demonstrated that a probability density function that uses 25% of the samples to fully sample the k-space central area allowed for an optimal balance between limited blurring and artifact incoherence. At all investigated noise levels, the Dice similarity coefficient (DSC) strongly depended on the regularization parameters and acceleration factor. In phantoms, the motion robustness of an NA8-AF8 undersampling pattern versus NA1-AF1 was evaluated with simulated and real motion patterns. Differences were assessed with the DSC, which was consistently higher for the NA8-AF8 compared with the NA1-AF1 strategy, for both simulated and real cyclic motion patterns (P < 0.001). Both strategies were validated in vivo in mice (n = 2) injected with perfluoropolyether. Here, the images displayed a sharper delineation of the liver with the NA8-AF8 strategy than with the NA1-AF1 strategy. In conclusion, we validated the hypotheses that in 19 F MRI the combination of undersampling and averaging improves both the sensitivity and the robustness against motion artifacts.

Differentiation between benign and malignant vertebral compression fractures using qualitative and quantitative analysis of a single fast spin echo T2-weighted Dixon sequence.

OBJECTIVES: To determine and compare the qualitative and quantitative diagnostic performance of a single sagittal fast spin echo (FSE) T2-weighted Dixon sequence in differentiating benign and malignant vertebral compression fractures (VCF), using multiple readers and different quantitative methods. METHODS: From July 2014 to June 2020, 95 consecutive patients with spine MRI performed prior to cementoplasty for acute VCFs were retrospectively included. VCFs were categorized as benign (n = 63, mean age = 76 ± 12 years) or malignant (n = 32, mean age = 63 ± 12 years) with a best valuable comparator as a reference. Qualitative analysis was independently performed by four radiologists by categorizing each VCF as either benign or malignant using only the image sets provided by FSE T2-weighted Dixon sequences. Quantitative analysis was performed using two different regions of interest (ROI1-2) and three methods (signal drop, fat fraction (FF) from ROIs, FF maps). Diagnostic performance was compared using ROC curves analyses. Interobserver agreement was assessed using kappa statistics and intraclass correlation coefficients (ICC). RESULTS: The qualitative diagnostic performance ranged from area under the curve (AUC) = 0.97 (95% CI: 0.91-1.00) to AUC = 0.99 (95% CI: 0.95-1.0). The quantitative diagnostic performance ranged from AUC = 0.82 (95% CI: 0.73-0.89) to AUC = 0.97 (95% CI: 0.91-0.99). Pairwise comparisons showed no statistical difference in diagnostic performance (all p > 0.0013, Bonferroni-corrected p < 0.0011). All five cases with disagreement among the readers were correctly diagnosed at quantitative analysis using ROI2. Interobserver agreement was excellent for both qualitative and quantitative analyses. CONCLUSIONS: A single FSE T2-weighted Dixon sequence can be used to differentiate benign and malignant VCF with high diagnostic performance using both qualitative and quantitative analyses, which can provide complementary information. KEY POINTS: • Qualitative analysis of a single FSE T2-weighted Dixon sequence yields high diagnostic performance and excellent observer agreement for differentiating benign and malignant compression fractures. • The same FSE T2-weighted Dixon sequence allows quantitative assessment with high diagnostic performance. • Quantitative data can readily be extracted from the FSE T2-weighted Dixon sequence and may provide complementary information to the qualitative analysis, which may be useful in doubtful cases.

Clinical implementation of accelerated T2 mapping: Quantitative magnetic resonance imaging as a biomarker for annular tear and lumbar disc herniation.

OBJECTIVES: This study evaluates GRAPPATINI, an accelerated T2 mapping sequence combining undersampling and model-based reconstruction to facilitate the clinical implementation of T2 mapping of the lumbar intervertebral disc. METHODS: Fifty-eight individuals (26 females, 32 males, age 23.3 ± 8.0 years) were prospectively examined at 3 T. This cohort study consisted of 19 patients, 20 rowers, and 19 volunteers. GRAPPATINI was conducted with the same parameters as a conventional 2D multi-echo spin-echo (MESE) sequence in 02:27 min instead of 13:18 min. Additional T2 maps were calculated after discarding the first echo (T2-WO1ST) and only using even echoes (T2-EVEN). Segmentation was done on the four most central slices. The resulting T2 values were compared for all four measurements. RESULTS: T2-GRAPPATINI, T2-MESE, T2-EVEN, and T2-WO1ST of the nucleus pulposus of normal discs differed significantly from those of bulging discs or herniated discs (all p < 0.001). For the posterior annular region, only T2-GRAPPATINI showed a significant difference (p = 0.011) between normal and herniated discs. There was a significant difference between T2-GRAPPATINI, T2-MESE, T2-EVEN, and T2-WO1ST of discs with and without an annular tear for the nucleus pulposus (all p < 0.001). The nucleus pulposus' T2 at different degeneration states showed significant differences between all group comparisons of Pfirrmann grades for T2-GRAPPATINI (p = 0.000-0.018), T2-MESE (p = 0.000-0.015), T2-EVEN (p = 0.000-0.019), and T2-WO1ST (p = 0.000-0.015). CONCLUSIONS: GRAPPATINI facilitates the use of T2 values as quantitative imaging biomarkers to detect disc pathologies such as degeneration, lumbar disc herniation, and annular tears while simultaneously shortening the acquisition time from 13:18 to 2:27 min. KEY POINTS: • T2-GRAPPATINI, T2-MESE, T2-EVEN, and T2-WO1ST of the nucleus pulposus of normal discs differed significantly from those of discs with bulging or herniation (all p < 0.001). • The investigated T2 mapping techniques differed significantly in discs with and without annular tearing (all p < 0.001). • The nucleus pulposus' T2 showed significant differences between different stages of degeneration in all group comparisons for T2-GRAPPATINI (p = 0.000-0.018), T2-MESE (p = 0.000-0.015), T2-EVEN (p = 0.000-0.019), and T2-WO1ST (p = 0.000-0.015).

Normal volumetric and T1 relaxation time values at 1.5 T in segmented pediatric brain MRI using a MP2RAGE acquisition.

OBJECTIVES: This study introduced a tailored MP2RAGE-based brain acquisition for a comprehensive assessment of the normal maturing brain. METHODS: Seventy normal patients (35 girls and 35 boys) from 1 to 16 years of age were recruited within a prospective monocentric study conducted from a single University Hospital. Brain MRI examinations were performed at 1.5 T using a 20-channel head coil and an optimized 3D MP2RAGE sequence with a total acquisition time of 6:36 min. Automated 38 region segmentation was performed using the MorphoBox (template registration, bias field correction, brain extraction, and tissue classification) which underwent a major adaptation of three age-group T1-weighted templates. Volumetry and T1 relaxometry reference ranges were established using a logarithmic model and a modified Gompertz growth respectively. RESULTS: Detailed automated brain segmentation and T1 mapping were successful in all patients. Using these data, an age-dependent model of normal brain maturation with respect to changes in volume and T1 relaxometry was established. After an initial rapid increase until 24 months of life, the total intracranial volume was found to converge towards 1400 mL during adolescence. The expected volumes of white matter (WM) and cortical gray matter (GM) showed a similar trend with age. After an initial major decrease, T1 relaxation times were observed to decrease progressively in all brain structures. The T1 drop in the first year of life was more pronounced in WM (from 1000-1100 to 650-700 ms) than in GM structures. CONCLUSION: The 3D MP2RAGE sequence allowed to establish brain volume and T1 relaxation time normative ranges in pediatrics. KEY POINTS: • The 3D MP2RAGE sequence provided a reliable quantitative assessment of brain volumes and T1 relaxation times during childhood. • An age-dependent model of normal brain maturation was established. • The normative ranges enable an objective comparison to a normal cohort, which can be useful to further understand, describe, and identify neurodevelopmental disorders in children.