To assess calf muscle constitution in chronic Achilles tendon disease (ATD) using two-point Dixon-based MRI (2pt-MRIDIXON).

This retrospective study analyzed 91 patients (36 females; 57.0 ± 14.4 years) with midportion or insertional chronic ATD who underwent clinical MRI of the Achilles tendon (AT), including 2pt-MRIDIXON for quantitative assessment of calf muscle fat content (MFC). Additionally, two radiologists qualitatively assessed MFC, AT quality, and co-pathologies. 2pt-MRIDIXON-derived fat fractions (FF) were related to patients' demographics and qualitative imaging findings.

The overall mean FF derived from 2pt-MRIDIXON of the triceps surae muscle was 11.2 ± 9.3%. Comparing midportion and insertional ATD, there was no significant difference regarding fatty muscle infiltration assessed with 2pt-MRIDIXON (P ≥ .47) or qualitative grading (P ≥ .059). More severe AT thickening (11 vs.9 mm, P < .001) and complete tears (29 vs. 9%, P = .025) were significantly more common in midportion ATD, while partial tears were significantly more frequent in insertional ATD (55 vs. 31%, P = .027). Soleus muscle edema was more prevalent in midportion than insertional ATD (40 vs. 9%, P = .002). In contrast, insertional ATD more commonly featured bone marrow edema (61 vs. 2%), Haglund's deformity (67 vs. 0%), and retrocalcaneal bursitis (82 vs. 43%) (P ≤ .002). Significant correlations (P ≤ .001) were demonstrated between FF, AT diameter, age (both in midportion and insertional ATD), and body mass index (in midportion ATD only) (ρ range = 0.53-0.61).

In chronic ATD, calf MFC was statistically equivalent (approximately 11%), irrespective of the localization of tendon damage. More severe tendon thickening and complete tears were more common in midportion ATD, and, vice versa, partial AT tears were significantly more frequent in insertional ATD.

To develop an accurate and precise liver 3DT 1 $$ {T}_1 $$ mapping method using only scanner-agnostic sequences.

While the spoiled gradient-recalled echo sequence is widely available on clinical scanners, variable flip angleT 1 $$ {T}_1 $$ mapping methods based on this sequence provide biasedT 1 $$ {T}_1 $$ estimates, with the largest systematic error arising fromB 1 + $$ {B}_1^{+} $$ inhomogeneities. To correct for this, the flip angle was mapped using a 2D gradient-echo double-angle method approach. To correct for the confounding effect of fat on liverT 1 $$ {T}_1 $$ andB 1 + $$ {B}_1^{+} $$ , Dixon and fat saturation techniques were used in combination with the variable flip angle and theB 1 + $$ {B}_1^{+} $$ map acquisitions, respectively. TheT 1 $$ {T}_1 $$ andB 1 + $$ {B}_1^{+} $$ mapping methods were validated with aT 1 $$ {T}_1 $$ -phantom against gold standard methods. An intra- and inter-repeatability study was conducted at 3T in 10 healthy individuals' livers.

The developed 3DT 1 $$ {T}_1 $$ mapping method achieved an excellent agreement with the gold standard, with a weighted root mean squared normalized error below 2.8%. In vivo, a medianT 1 $$ {T}_1 $$ standard deviation of 31 ms and an interquartile range of [27, 39] ms was achieved across all measurements, including the intra- and inter-repeatability study data. A within-subject standard deviation forT 1 $$ {T}_1 $$ of 21 ± 5 ms had a corresponding repeatability coefficient of 60 ms. The measuredT 1 $$ {T}_1 $$ values agree well with MOLLI and SASHAT 1 $$ {T}_1 $$ mapping methods, with averageT 1 $$ {T}_1 $$ differences of 5%.

Accurate and precise 3DT 1 $$ {T}_1 $$ liver measurements can lead the way to the wider adoption of a clinically feasibleT 1 $$ {T}_1 $$ measurement as a marker of hepatic fibro-inflammation.

Water-fat separation MRI techniques use frequency differences between water and fat encoded in the phase of the MR signal. Similarly, phase-contrast MRI (2D PC-MRI) uses phase differences to estimate blood flow velocity. This study proposes to enhance efficiency by acquiring both images in a single scan, resulting in co-registered images of water-fat species and velocity. This work introduces a method that combines phase-contrast with T2*-IDEAL to acquire water-fat components and velocity images in a single MR acquisition. We developed a phase-contrast multi-echo (PCME-MRI) acquisition to obtain IDEAL MR images with velocity encoding. Our T2*-IDEAL method estimates velocity and separates water-fat components by considering three chemical species: fat concentration and two water components with velocity information. The proposed PC T2*-IDEAL method was validated with a numerical phantom and 2D MR axial images of the neck in 14 healthy volunteers, measuring blood flow in the carotid arteries and water-fat components around the region of interest. In volunteers, the median and range MAE when comparing PC T2*-IDEAL and standard T2*-IDEAL fat fraction was 0.06± $$ \pm $$ 0.02. The median and range of velocity for PC T2*-IDEAL were 8.44 and [6.23, 10.6] mL, compared to 7.16 and [4.79, 8.78] mL obtained by 2D PC-MRI. Numerical phantom simulations demonstrated similar results in water-fat components and velocity information compared to standard T2*-IDEAL and 2D PC-MRI methods. Volunteer images showed accurate estimations of water-fat components and differences in velocity information using PC T2*-IDEAL in comparison with standard 2D PC-MRI.

To evaluate the effectiveness of fat suppression techniques experimentally and illustrate their influence on the accuracy of PRFS MR-thermometry.

The residual magnitudes of the main fat peaks are measured using a water-fat decomposition algorithm in an oil phantom and in vivo in swine bone marrow, either with spectral fat saturation (FS), water excitation (WE) or fast water excitation (FWE), as implemented on 1.5 T whole-body clinical MRIs. Thermometry experiments in tissue-mimicking oil-water phantoms (10 and 30 % fat) allow determining temperature errors in PRFS MR-thermometry with no fat suppression, FS and WE, compared against reference fiber optic thermometry.

WE attenuates the signal of the main methylene fat peak more than FS (2 % and 22 % amplitude attenuation in the oil phantom, respectively), while the olefinic and glycerol peaks surrounding the water peak remain unaltered with both FS and WE. Within the 37 °C to 60 °C temperature range explored, FS and WE strongly attenuate temperature errors compared to PRFS without fat suppression. The residual fat signal after FS and WE leads to errors in PRFS thermometry, that increase with the fat content and oscillate with TE and temperature. In our tests limited to a single MR provider, fat suppression with WE appears to suppress fat signal more effectively.

We propose a protocol to quantify the remaining fraction of each spectral fat peak after fat suppression. In PRFS thermometry, despite spectral fat suppression, the remnant fat signal leads to temperature underestimation or overestimation depending on TE, fat fraction and temperature range. Fat suppression techniques should be evaluated specifically for quantitative MRI methods such as PRFS thermometry.

Ultrashort echo time (UTE) allows imaging of tissues with short relaxation times, but it comes with the expense of long scan times. Magnitude images of UTE magnetic resonance imaging (MRI) are widely used in pulmonary imaging due to excellent parenchymal signal, but have insufficient contrast for other anatomical regions of the thorax. Our work investigates the value of UTE phase images (UTE-Ps)-generated simultaneously from the acquired UTE signal used for the magnitude images-for the detection of thoracic lymph nodes based on water-fat contrast. It employs an advanced imaging sequence and reconstruction allowing isotropic 3D UTE MRI in clinically acceptable scan times.

In our prospective study, 42 patients with 136 lymph nodes had undergone venous computed tomography and pulmonary MRI scans with UTE within a 14-day interval. 3D isotropic UTE images were acquired using FLORET (fermat looped, orthogonally encoded trajectories). Background-corrected phase images (UTE-P) and magnitude images were reconstructed simultaneously from the UTE-Signal. Three radiologists performed a blinded reading in which all lymph nodes with a short-axis diameter (SAD) of at least 0.5 cm were detected. Detection rates and performance metrics of UTE-P for all lymph node regions and for pathologic (SAD ≥10 mm) and nonpathologic lymph nodes (SAD <10 mm) were calculated using computed tomography as a reference. The interreader agreement defined as the presence or absence of lymph nodes based on patient and region was calculated using Fleiss kappa (κ).

In the phase images, pathologic lymph nodes in the mediastinal and hilar region were detected with a high diagnostic confidence due to the achieved water-fat contrast (average sensitivity, specificity, positive predictive value, and negative predictive value of 95.83% [confidence interval (CI), 92.76%-98.91%], 100%, 100%, and 99.32% [CI, 98.08%-100%]). Stepwise inclusion of all lymph node regions and nonpathologic lymph nodes was associated with a moderate decrease resulting in an average sensitivity, specificity, positive predictive value, and negative predictive value of 77.9% (CI, 70.9%-84.7%), 99.4% (CI, 98.7%-99.9%), 97.0% (CI, 93.4%-99.7%), and 94.7% (CI, 92.8%-96.4%) for the inclusion of all lymph nodes sizes and regions. Interreader agreement was almost perfect (κ = 0.92).

Pathological lymph nodes in the mediastinal and hilar region can be detected in phase-images with high diagnostic confidence, thanks to the ability of the phase images to depict water-fat contrast in combination with high spatial 3D resolution, extending the clinical applicability of UTE into the simultaneous assessment of lung parenchyma and lymph nodes.

To implement a flexible framework, named HydrOptiFrame, for the design and optimization of time-efficient water-excitation (WE) RF pulses using B-spline interpolation, and to characterize their lipid suppression performance.

An evolutionary optimization algorithm was used to design WE RF pulses. The algorithm minimizes a composite loss function that quantifies the fat-water contrast using Bloch equation simulations. In a first study, B-spline interpolated optimized (BSIO) pulses designed with HydrOptiFrame with durations of 1 and 0.76 ms were generated for 3 T and characterized in healthy volunteers' knees. The femoral bone marrow SNR was compared to that obtained with to 1-1 WE and lipid insensitive binomial off resonant excitation (LIBRE) pulses. In a second study, in the heart at 1.5 T, the water-fat contrast ratio and coronary artery vessel length obtained with a 2.56 ms BSIO pulse was compared to 1-1 WE and LIBRE pulses in free-running cardiovascular MR.

The 1 ms BSIO pulse resulted in higher fat suppression and lower contrast ratio (CR) in the bone marrow than the state-of-the-art pulses (4.1 ± 0.2 vs. 4.7 ± 0.4 and 4.4 ± 0.3 for the BSIO, the 1-1 WE and LIBRE respectively, p < 0.05 vs. both) at 3 T. At 1.5 T, the BSIO pulse resulted in a higher blood-epicardial fat CR (3.8 ± 1.3 vs. 1.6 ± 0.6 and 2.4 ± 1.1 for the BSIO, 1-1 WE and LIBRE, respectively, p < 0.05 vs. both) and longer traceable left coronary artery vessel length (8.7 ± 1.4 cm vs. 7.0 ± 1.0 cm [p = 0.04] and 7.5 ± 1.2 cm [p = 0.09]).

The HydrOptiFrame framework offers a new opportunity to design WE RF pulses that are robust to B0 inhomogeneity at multiple magnetic field strengths and for variable RF pulse durations.

Bone marrow lesions (BML) are abnormalities in the bone marrow identified on magnetic resonance imaging (MRI) and can generally be classified as traumatic or atraumatic. This review focuses on atraumatic bone marrow edema syndromes (BMES) and their imaging evaluation. The MRI remains the modality of choice for assessing BMES, particularly using fluid-sensitive sequences although other sequences such as Dixon and T1-weighted imaging can be of further assistance. Emerging evidence supports dual-energy CT (DECT) as a reliable alternative, with high sensitivity and specificity for detecting bone marrow edema. The term BMES is a collective term for conditions, such as transient osteoporosis (TO) and regional migratory osteoporosis (RMO), predominantly affect weight-bearing bones in middle-aged individuals and pregnant or postpartum females. Subchondral insufficiency fractures of the knee (SIFK) are a key subset of BMES. These fractures most commonly involve the medial femoral condyle (MFC) and are associated with risk factors, such as meniscal root tears and extrusion of the meniscal body. The MRI findings typically include bone marrow edema-like signals and subchondral fracture lines, with additional features, such as secondary osteonecrosis in advanced cases. Prognostic indicators are crucial for stratifying patients and guiding management. Low-grade or reversible lesions often resolve with conservative treatment, whereas high-grade or irreversible lesions may require surgical intervention.Avascular necrosis, another atraumatic BML entity, differs from BMES by its association with systemic factors, such as steroid use or alcohol abuse. Accurate imaging, particularly in the early stages, is vital to distinguish between reversible and irreversible lesions, facilitating timely and appropriate management.

To accelerate 3D whole-heart joint T1/T2 mapping for myocardial tissue characterization using an end-to-end deep learning algorithm for joint motion estimation and model-based motion-corrected reconstruction of multi-contrast undersampled data.

A free-breathing high-resolution motion-compensated 3D joint T1/T2 water/fat sequence is employed. The sequence consists of the acquisition of four interleaved volumes with 2-echo encoding, resulting in eight volumes with different contrasts. An end-to-end non-rigid motion-corrected reconstruction network is used to estimate high quality motion-corrected reconstructions from the eight multi-contrast undersampled data for subsequent joint T1/T2 mapping. Reconstruction with the proposed approach was compared against state-of-the-art motion-corrected HD-PROST reconstruction.

The proposed approach yields images with good visual agreement compared to the reference reconstructions. The comparison of the quantitative values in the T1 and T2 maps showed the absence of systematic errors, and a small bias of -6.35 ms and -1.8 ms, respectively. The proposed reconstruction time was 24 seconds in comparison to 2.5 hours with motion-corrected HD-PROST, resulting in a reconstruction speed-up of over 370 times.

In conclusion, this study presents a promising method for efficient whole-heart myocardial tissue characterization. Specifically, the research highlights the potential of the multi-contrast end-to-end deep learning algorithm for joint motion estimation and model-based motion-corrected reconstruction of multi-contrast undersampled data. The findings underscore its ability to compute T1 and T2 values with good agreement when compared to the reference motion-corrected HD-PROST method, while substantially reducing reconstruction time.

Understanding lipid digestion is crucial for promoting human health. Traditional methods for studying lipolysis face challenges in sample representativeness and pre-treatment, and cannot measure real-time lipolysis in vivo. Thus, non-invasive techniques like magnetic resonance imaging (MRI) need to be developed. This study assessed the MRI water-fat separation method for monitoring in vitro intestinal digestion of dairy cream, supported by high-performance thin-layer chromatography (HP-TLC) and time-domain nuclear magnetic resonance (TD-NMR). A clear distinction was found between the T2 of undigested lipids (∼120 ms) and lipolytic products (0.1-15 ms). The short T2 of lipolytic products likely results from semi-crystalline structures formed with bile salts. While MRI methods cannot detect such fast-relaxing protons, it effectively quantified lipolysis by tracking the residual undigested lipids, showing high correlation with HP-TLC results (R2 = 0.93 and 0.95 for 13-s and 6-min MRI methods, respectively). The rapid 13-s MRI method offers strong potential for future in vivo applications.

To improve tissue contrast visualization in water-only images from two-point turbo spin-echo (TSE) Dixon MRI using dark-fat image processing and evaluate in retrospectively acquired clinical knee images.

Clinical knee MRI datasets from 36 patients were retrospectively compiled under IRB approval. The dark-fat water-only images were generated and compared with the conventional water-only images from two-point TSE-Dixon MRI. The water-only images from 20 patients were analyzed: (i) qualitatively by two experienced musculoskeletal radiologists, for overall image quality, fat suppression, anatomical visualization, and the absence of artifacts, using Wilcoxon rank tests, and (ii) quantitatively using apparent signal-to-noise ratio (aSNR) and apparent contrast-to-noise ratio (aCNR) from regions of interest (ROIs) with paired t-test. In the remaining 16 patients, the number of cruciate ligament tears identified on MRI was tabulated and compared with arthroscopy results.

Compared to conventional water-only images, dark-fat water-only images showed improved fat suppression (reader 1, P < 0.0001; reader 2, P < 0.05), improved overall image quality by reader 1 (P < 0.001), and improved visualization of the sciatic nerve for reader 1 (P < 0.01), while there were no significant differences for the other anatomical structures. aSNR was significantly reduced for bone marrow fat (P < 0.0001), and aCNR between meniscus and articular cartilage was significantly improved (P < 0.0001). There were a higher number of posterior cruciate ligament tears identified in MRI compared to arthroscopy.

Dark-fat processed water-only images improved fat suppression and tissue contrast visualization, particularly sciatic nerves, compared to conventional water-only images from two-point TSE-Dixon MR imaging.

Magnetization-prepared rapid gradient-echo (MP-RAGE) sequences are routinely acquired for brain exams, providing high conspicuity for enhancing lesions. Vessels, however, also appear bright, which can complicate the detection of small lesions. T1RESS (T1 relaxation-enhanced steady-state) sequences have been proposed as an alternative to MP-RAGE, offering improved lesion conspicuity and suppression of blood vessels. This work aims to evaluate the performance of radial T1RESS variants for motion-robust contrast-enhanced brain MRI.

Radial stack-of-stars sampling was implemented for steady-state free-precession-based rapid T1RESS acquisition with saturation recovery preparation. Three variants were developed using a balanced steady-state free-precession readout (bT1RESS), an unbalanced fast imaging steady precession (FISP) readout (uT1RESS-FISP), and an unbalanced reversed FISP readout (uT1RESS-PSIF). Image contrast was evaluated in numerical simulations and phantom experiments. The motion robustness of radial T1RESS was demonstrated with a motion phantom. Four patients and six healthy volunteers were scanned at 3 T and 0.55 T. Extensions were developed combining T1RESS with GRASP for dynamic imaging, with GRAPPA for accelerated scans, and with Dixon for fat/water separation.

In simulations and phantom scans, uT1RESS-FISP provided higher signal intensity for regions with lower T1 values (<500 ms) compared with MP-RAGE. In motion experiments, radial uT1RESS-FISP showed fewer artifacts than MP-RAGE and Cartesian uT1RESS-FISP. In patients, both unbalanced uT1RESS variants provided higher lesion conspicuity than MP-RAGE. Blood vessels appeared bright with MP-RAGE, gray with uT1RESS-FISP, and dark with uT1RESS-PSIF. At 0.55 T, bT1RESS provided high signal-to-noise ratio T1-weighted images without banding artifacts. Lastly, dynamic T1RESS images with a temporal resolution of 10.14 seconds/frame were generated using the GRASP algorithm.

Radial T1RESS sequences offer improved lesion conspicuity and motion robustness and enable dynamic imaging for contrast-enhanced brain MRI. Both uT1RESS variants showed higher tumor-to-brain contrast than MP-RAGE and may find application as alternative techniques for imaging uncooperative patients with small brain lesions.

Hereditary transthyretin amyloid polyneuropathy (ATTRv-PN) is a rare and progressive neurodegenerative disorder characterized by axonal neuropathy and amyloid deposits. Early detection of disease onset and progression is crucial for timely therapeutic intervention. Quantitative MRI (qMRI) can be used to measure potential biomarkers. Intraepineurial fat fraction (ieFF) may reflect lipid droplets in amyloid deposits as described in histological studies or the replacement of nerve fiber loss with fatty-rich interfascicular epineurium. This study investigates the potential utility of ieFF as a novel imaging-related biomarker in differentiating ATTRv-PN, asymptomatic carriers (ATTRv-C), and healthy controls (HCs).

Fifty-three patients with TTR mutations were imaged (31 ATTRv-PN patients, 22 ATTRv-C, and 24 HC) and both clinical and electrophysiological parameters were quantified. 3D volume, ieFF, and magnetization transfer ratio (MTR) were quantified in sciatic and tibial nerves using qMRI.

Symptomatic ATTRv-PN patients exhibited significantly higher ieFF in both sciatic (32.4% IQR [24.4-38.1]) and tibial nerves (13.7%, IQR [9.97-20.7]) compared to controls (sciatic 22.3%, IQR [16.6-28.5]; tibial 9.74%, IQR [6.36-12.5]) (p < 0.05). ieFF values were positively correlated in both uni and multivariate analyses with the main clinical scores and electrophysiological measures. ATTRv-C also showed increased ieFF values compared to controls (p < 0.05). Comparatively, MTR and nerve volumes exhibited less pronounced differences across groups.

This study demonstrates that ieFF effectively differentiates symptomatic and asymptomatic ATTRv patients from HC and correlates strongly with electrophysiological and clinical severity parameters. Furthermore, we compare ieFF with conventional qMRI biomarkers, highlighting its superior potential for monitoring nerve structural impairment.

Segmentation of individual thigh muscles in MRI images is essential for monitoring neuromuscular diseases and quantifying relevant biomarkers such as fat fraction (FF). Deep learning approaches such as U-Net have demonstrated effectiveness in this field. However, the impact of reducing neural network complexity remains unexplored in the FF quantification in individual muscles.

U-Net architectures with different complexities have been compared for the quantification of the fat fraction in each muscle group selected in the central part of the thigh region. The corresponding performance has been assessed in terms of Dice score (DSC) and FF quantification error. The database contained 1450 thigh images from 59 patients and 14 healthy subjects (age: 47 ± 17 years, sex: 36F, 37M). Ten individual muscles were segmented in each image. The performance of each model was compared to nnU-Net, a complex architecture with 4.35 × 107 parameters, 12.8 Gigabytes of peak memory usage and 167 h of training time.

As expected, nnU-Net achieved the highest DSC (94.77 ± 0.13%). A simpler U-Net (5.81 × 105 parameters, 2.37 Gigabytes, 14 h of training time) achieved a lower DSC but still above 90%. Surprisingly, both models achieved a comparable FF estimation.

The poor correlation between observed DSC and FF indicates that less complex architectures, reducing GPU memory utilization and training time, can still accurately quantify FF.

Greater walking automaticity facilitates maintenance of gait speed without prefrontal cortex (PFC) resources. Brain aging may cause shifts to more attentional gait with greater engagement of the PFC. Nigrostriatal dopaminergic integrity likely facilitates walking automaticity and maintenance of gait speed during attentional dual-tasks. Older adults (n=201; age=74.9; 63.2% women, gait speed=1.10 m/s) completed a dual-task protocol of saying every other letter of the alphabet while walking. PFC activation was measured by functional near-infrared spectroscopy. Four groups were defined based on PFC activation (increased during dual-task, PFC+, or not, PFC-) and gait speed performance (maintained during dual-task, gait+, or slowed, gait-). To compare nigrostriatal dopaminergic integrity across groups, we assessed binding of the type-2 vesicular monoamine transporter (VMAT2) density in the sensorimotor and associative striatum using [11C]-(+)-α-dihydrotetrabenazine (DTBZ) positron emission tomography. Multinomial regression estimated adjusted associations of DTBZ binding with group membership. We hypothesized that DTBZ binding was highest for those who maintained gait speed without additional PFC activation when switching from single- to dual-task (PFC-/gait+; i.e., highest gait automaticity). In bivariate analyses, the PFC-/gait+ group had the highest DTBZ binding in the sensorimotor striatum (p=0.05); binding in the associative striatum was similar across groups (p=0.1). Results were similar in adjusted regression analyses; DTBZ binding in sensorimotor striatum was associated with lower likelihood to be in the PFC-/gait- (OR=0.28; 95% CI: 0.08, 0.94) or the PFC+/gait+ (OR=0.29; 95% CI: 0.10, 0.84) groups compared to PFC-/gait+ reference group. These results provide support for dopaminergic involvement in sustaining gait automaticity at older ages.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a common cause of liver disease worldwide. In patients with MASLD, liver fibrosis stage is the most significant predictor of mortality; therefore, early identification of patients at the greatest risk of advanced fibrosis is essential. Noninvasive tests predict advanced fibrosis and are recommended for use in primary care settings to determine which patients would benefit most from specialty care. The adoption of these tools is not widespread, and several studies have reported underrecognition of cirrhosis in patients with MASLD and diabetes. The finding of hepatic steatosis on imaging performed for evaluation of nonliver conditions may present an avenue for opportunistic screening to identify more patients with MASLD. This article will review recommendations for when hepatic steatosis is found on imaging and noninvasive tests that can be used to help predict fibrosis staging. This is a significant area of research because a new treatment for MASLD has been approved, and other treatments may follow.

Preoperative intramuscular fat (IMF) is a strong predictor of tendon failure after a rotator cuff repair. Due to the contemporary labor intensive and time-dependent manual segmentation required for quantitative assessment of IMF, clinical implementation remains a challenge. The emergence of accurate three-dimensional evaluation of the rotator cuff may permit implementation with greater inter-rater reliability than common subjective scales (eg, Goutallier classification (GC)). Here, we developed and validated a convolutional neural network (CNN) model for auto-segmentation of the shoulder on Dixon magnetic resonance imaging. Also, we aimed to assess the agreement among GC, two-dimensional (2D), and 3D IMF, including their discriminatory ability for the identification of muscles above an IMF threshold shown to negatively impact surgical outcomes (ie, GC ≥ 3).

This study retrospectively obtained fat-water Dixon shoulder magnetic resonance imagings between March 2023 and March 2024 to develop and validate a CNN model for the segmentation of individual rotator cuff muscles and surrounding tissues. The CNN model was trained using a modified U-Net architecture (n = 80) and tested on an external dataset (n = 25). Accuracy was primarily evaluated using the Dice Similarity Coefficient (DSC) compared to manual segmentation. Reliability was evaluated by the intraclass correlation coefficient (ICC2,1) and discriminatory ability was evaluated by the area under the receiver operating characteristic curve.

The model after training (37 male and 43 female, mean age = 55.8 ± 15.6 years) and testing (15 male and 10 female, mean age = 56.6 ± 19.7 years) produced DSCs of ≥0.89 except for teres minor (DSC = 0.86 ± 0.03). The model demonstrated excellent reliability for volume (ICC2,1 ≥ 0.93) and good to excellent reliability for IMF (ICC2,1 ≥ 0.80), with the exceptions of teres major volume (ICC2,1 = 0.82, 95% CI: 0.63-0.92, P < .001) and subscapularis IMF (ICC2,1 = 0.55, 95% CI: 0.22-0.77, P < .001). 3D IMF but not 2D IMF was associated with GC for the supraspinatus, subscapularis, and infraspinatus (U ≥ 4.02, P < .045). The proposed CNN model's IMF outputs produced excellent discriminatory capability of muscles above the IMF threshold shown to negatively impact outcomes (receiver operating characteristic curve ≥0.93).

The development of a CNN model allows for efficient, accurate segmentation of muscle and bone, enabling reliable evaluation of muscle quality. The model demonstrates that 2D evaluation of IMF is insufficient for differentiating between rotator cuff muscles on either side of a clinically meaningful IMF threshold on the GC scheme, whereas 3D IMF shows excellent discriminant validity across all rotator cuff muscles.

Muscle atrophy occurs with extended exposure to microgravity. This study quantified the overall muscle size, lean muscle area and fat infiltration changes pre- to post-flight that occur in the thoracic and lumbar spine with long-duration spaceflight. Pre- and post-flight magnetic resonance imaging (MRI) scans were obtained from 9 crewmembers on long-duration (≥6 months) International Space Station (ISS) missions. Muscle size was measured by the cross-sectional area (CSA) and lean muscle tissue by the functional cross-sectional area (FCSA). Muscle-fat infiltration (MFI) was measured by the mean pixel intensities of the MRI in fat and water phases. A mixed model with random subject effect was used to analyze pre- to post-flight changes. Significant decreases were seen in the quadratus lumborum muscle size (-1.8 ± 0.6% per month, p = 0.002) and lean muscle tissue content in the paraspinal muscles (-0.7 ± 0.2% per month, p ≤ 0.001). Fat infiltration increased significantly in the transversospinalis (+4.1 ± 1.0% per month, p ≤ 0.01) muscle. Treadmill exercise had a tendency to reduce fat content in the paraspinal and quadratus lumborum muscles, while counteracting muscle build-up only in the paraspinal muscles. Cycle ergometer exercise suggested benefits for the psoas muscle. Resistance training appeared to benefit lean muscle mass of most thoracolumbar muscles. Our findings highlight the need for countermeasures to prevent muscle atrophy and detrimental effects in muscle composition during long-duration spaceflight.

Fat-signal suppression is essential for breast diffusion magnetic resonance imaging (or diffusion-weighted MRI, DWI) as the very low diffusion coefficient of fat tends to decrease absolute diffusion coefficient (ADC) values. Among several methods, the STIR (short-tau inversion recovery) method is a popular approach, but signal suppression/attenuation is not specific to fat contrary to other methods such as SPAIR (spectral adiabatic (or attenuated) inversion recovery). This article focuses on those two techniques to illustrate the importance of appropriate fat suppression in breast DWI, briefly presenting the pros and cons of both approaches.

We show here through simulation and data acquired in a dedicated breast DWI phantom made of vials with water and various concentrations of polyvinylpyrrolidone (PVP) how ADC values obtained with STIR DWI may be biased toward tissue components with the longest T1 values: ADC values obtained with STIR fat suppression may be over/underestimated depending on the T1 and ADC profile within tissues. This bias is also illustrated in two clinical examples.

Fat-specific methods should be preferred over STIR for fat-signal suppression in breast DWI, such as SPAIR which also provides a higher sensitivity than STIR for lesion detection. One should remain aware, however, that efficient fat-signal suppression with SPAIR requires good B0 shimming to avoid ADC underestimation from residual fat contamination.

The spectral adiabatic (or attenuated) inversion recovery (SPAIR) method should be preferred over short-tau inversion recovery (STIR) for fat suppression in breast DWI.

Fat-signal suppression is essential for breast DWI; the SPAIR method is recommended. Short-tau inversion recovery (STIR) is not specific to fat; as a result, SNR is decreased and ADC values may be over- or underestimated. The STIR fat-suppression method must not be used after the injection of gadolinium-based contrast agents.

The objective of this study was to develop a new MRI technique for non-invasive, free-breathing imaging of glycogen in the human liver using the nuclear Overhauser effect (NOE).

The proposed method, called GraspNOE-Dixon, uses a novel MRI sequence that combines steady-state saturation-transfer preparation with multi-echo golden-angle radial stack-of-stars sampling. Multi-echo acquisition enables fat/water-separated imaging for quantification of water-specific NOE. Image reconstruction is performed using the improved golden-angle radial sparse parallel imaging (GRASP-Pro) technique to exploit spatiotemporal correlations in dynamic images. To evaluate the proposed technique, imaging experiments were first performed on glycogen phantoms, followed by in vivo studies involving healthy volunteers and patients with fatty liver disease. In addition, a comparative assessment of signal changes before and after a 12-h fasting period was performed.

Evaluation experiments on glycogen phantoms showed a robust linear correlation between the NOE signal and glycogen concentration. In vivo experiments demonstrated motion-robust NOE-weighted images, with potential for further acceleration. In subjects with varying liver fat content, the fat/water separation approach resulted in distortion-free Z-spectra, enabling the quantification of glycogen NOE. An approximately one-third reduction in the NOE signal was observed following a 12-h fasting period, consistent with a decrease in glycogen level.

This study introduces a clinically feasible imaging technique, GraspNOE-Dixon, for free-breathing volumetric multi-echo imaging of hepatic glycogen at 3 T. The motion robust imaging technique developed here may also have applications in other body areas beyond liver imaging.

Idiopathic inflammatory myopathies (IIMs) are muscle disorders characterized by proximal weakness of the skeletal muscles, inflammation in muscle, and autoimmunity. The classic subgroups in IIMs include dermatomyositis, inclusion body myositis, immune-mediated necrotizing myopathy, and polymyositis (PM). PM is increasingly recognized as a rare subtype and often included in overlap myositis, the antisynthetase syndrome when no rash is present, or misdiagnosed inclusion body myositis. Magnetic resonance imaging (MRI) has played an increasingly important role in IIM diagnosis and assessment. Although conventional MRI provides qualitative information that is helpful for diagnosis, its application for the quantitative assessment of disease activity is challenging. Therefore, advanced quantitative MRI techniques have been implemented in the past 10 years to highlight potential new applications of disease monitoring in IIM. The aim of this review is to examine the role of quantitative MRI techniques in evaluating the key imaging features of IIM, mainly muscle edema and muscle damage (fatty replacement and/or muscle atrophy).

Spinal muscular atrophy is a severe, progressive autosomal recessive neuromuscular disorder associated with neuromuscular scoliosis. When bracing is not sufficient to control the deformity, early spinal surgery is required. To the best of our knowledge, no work in the literature have assessed modifications in spinal and thigh muscles of subjects with type 2 spinal muscular atrophy (SMA2) following spinal surgery.

This study aimed to better understand modifications in the spinal and thigh muscles of subjects with SMA2 and early onset scoliosis, before and after minimally invasive fusionless surgery.

20 SMA2 patients with confirmed scoliosis on bi-planar low-dose X-ray were included: 10 preoperative and 10 postoperative patients with a minimal follow-up of 5 years after surgery. The surgery consisted of a bilateral sliding rod construct extended from T1 to the sacrum, through a minimally invasive approach. All subjects had fat/water separation muscle magnetic resonance imaging from the spine to the thigh. The percentage of fat degeneration was compared before and after surgery. A quality-of-life survey was performed.

Fat infiltration was diffuse and symmetric in both groups of patients, and on average six times more compared to control subjects previously published at thigh level. Adductors, sartorius, and gracilis were less affected with respectively, 51%, 56%, and 57% of fat fraction before surgery. Comparing the preoperative and postoperative groups, fat infiltration was higher in sartorius and multifidus after surgery (p < 0.05). No significant difference was found for the other muscles studied. These results did not affect quality of life.

This is the first study to compare fat infiltration of spinal and thigh muscles of SMA2 patients before and after minimally invasive surgery. Our results demonstrate that muscles were globally preserved apart from multifidus and sartorius which were more affected.

Space agencies plan crewed missions to the Moon and Mars. However, microgravity-induced lumbopelvic deconditioning, characterized by an increased fat fraction (FF) due to reduced physical activity, poses a significant challenge to spine health. This study investigates the spatial distribution of FF in the lumbopelvic muscles to identify the most affected regions by deconditioning, utilizing a computer-vision model and a tile-based approach to assess FF changes. Twenty-four healthy individuals (8 F) were recruited, and automatic segmentation of the lumbopelvic muscles was applied before and after 59 days of head-down tilt bed rest (HDTBR + 59) and 13 days of reconditioning (R + 13). Axial Dixon sequence images were acquired from 3 T magnetic resonance imaging. FF in the lumbar multifidus (LM), lumbar erector spinae (LES), quadratus lumborum, psoas major, gluteus maximus (GMax), gluteus medius (GMed), and gluteus minimus (GMin) muscles from the upper margin of L1 vertebra to the inferior border of GMax muscle were automatically derived using a computer-vision model. Lumbar muscles were segmented into eight tiles (superficial and deep, lateral to medial), and gluteal muscles into regions (anterior/superior for GMed and GMin, superior/inferior for GMax). At HDTBR + 59, the deep centrolateral region at L5/S1 for LM (18.7 ± 15.7%, P < 0.001; d = 0.97) and the deep medial region at Upper L4 for LES (5.4 ± 5.9%, P < 0.001; d = 0.34) showed the largest increase in FF compared with baseline data collection. These regions did not recover at R + 13 (P < 0.05; d ≥ 0.25). These findings highlight the need to target deep fascicles of LM and LES in countermeasure strategies to mitigate microgravity-induced lumbopelvic deconditioning, optimizing spine health, and performance.NEW & NOTEWORTHY This study reveals novel insights into fat fraction changes in lumbopelvic muscles after 60 days of head-down bed rest and 13 days of reconditioning. Lipids increased in the deep regions of the lumbar multifidus (LM) and lumbar erector spinae (LES), particularly at lower vertebral levels, and persisted after reconditioning. These findings highlight the need to target deep fascicles of LM and LES in future countermeasures to mitigate microgravity-induced deconditioning and optimize spine health.

Measuring the intracellular pH (pHi) is of interest for brain tumor diagnostics. Common metrics of CEST imaging like the amide proton transfer-weighted (APTw) MTRasym are pHi sensitive and allow differentiating malignant tumor from healthy tissue. Yet, the image contrast also depends on additional magnetization transfer effects and T1. In contrast, the apparent exchange-dependent relaxation (AREX) provides a T1 corrected exchange rate of the amide protons. As AREX still depends on amide proton density, its pHi sensitivity remains ambiguous. Hence, we conducted this study to assess the influence of pathologic tissue changes on the pHi sensitivity of AREX in vivo. Patients with newly diagnosed intra-axial brain tumors were prospectively recruited and underwent conventional MRI, quantitative T1 relaxometry, APT-CEST and 31P-MRS on a 3T MRI scanner. Tumors were segmented into contrast-enhancing tumor (CE), surrounding T2 hyperintensity (T2-H) and contralateral normal appearing white matter (CNAWM). T1 mapping and APT-CEST metrics were correlated with 31P-MRS-derived pHi maps (Pearson's correlation). Without differentiating tissue subtypes, pHi did not only correlate significantly with MTRasym (r = 0.46) but also with T1 (r = 0.49). Conversely, AREX only correlated poorly with pHi (r = 0.17). Analyzing different tissue subtypes separately revealed a tissue dependency of the pHi sensitivity of AREX with a significant correlation (r = 0.6) in CNAWM and no correlation in T2-H or CE (r = -0.11/-0.24). CE showed significantly increased MTRasym, pHi, and T1 compared with CNAWM (p < 0.001). In our study, the pHi sensitivity of AREX was limited to CNAWM. The lack of sensitivity in CE and T2-H is probably attributable to altered amide and water proton concentrations in these tissues. Conversely, the correlation of pHi with MTRasym may be explained by the coincidental contrast increase through increased T1 and amide proton density. Therefore, limited structural deviations from CNAWM might be a perquisite for the use of CEST contrasts as pHi-marker.

Fast turbo spin echo (TSE) Dixon method, which acquires both in-phase and opposed-phase in a single echo train, resulting in a 50% reduction in imaging times compared to the TSE Dixon method. However, it has been observed that the Fast TSE Dixon method exhibits degraded resolution characteristics when scanned under the same parameters as the TSE Dixon method. This study aimed to reveal suitable scan parameters for the Fast TSE Dixon method by examining its resolution characteristics when altering the parameter of the receiver bandwidth (BW) and asymmetric echoes related to sampling time.

The BW was adjusted to 400, 600, 800, and 1000 Hz/pixel for the TSE Dixon and Fast TSE Dixon methods. In addition, the parameter of asymmetric echoes was changed to on (weak), and off of the Fast TSE Dixon method. The modulation transfer function (MTF) of each sequence was assessed using the edge spread function in the frequency encoding direction and phase encoding direction.

The findings indicated that the MTFs of the TSE Dixon method remained constant despite alterations in the sampling time. Conversely, the MTFs of the Fast TSE Dixon method showed that resolution characteristics improved by shortening sampling time when the BW was expanded, and the asymmetric echoes were changed to on.

We revealed suitable scan parameters for the Fast TSE Dixon method have been found to improve resolution characteristics by shortening sampling time when the BW was expanded and the asymmetric echoes were changed to on.

Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD), formerly known as Non-Alcoholic Fatty Liver Disease (NAFLD), is a chronic liver disorder associated with disturbances in lipid metabolism. The disease is prevalent worldwide, particularly closely linked with metabolic syndromes such as obesity and diabetes. Magnetic Resonance Proton Density Fat Fraction (MRI-PDFF), serving as a non-invasive and highly quantitative imaging assessment tool, holds promising applications in the diagnosis and research of MASLD. This paper aims to comprehensively review and summarize the applications and research progress of MRI-PDFF technology in MASLD, analyze its strengths and challenges, and anticipate its future developments in clinical practice.

MRI-guidance of cardiac catheterization is currently performed using one or multiple 2D imaging planes, which may be suboptimal for catheter navigation, especially in patients with complex anatomies. The purpose of the work was to develop a robust real-time 3D catheter tracking method and 3D visualization strategy for improved MRI-guidance of cardiac catheterization procedures.

A fast 3D tracking technique was developed using continuous acquisition of two orthogonal 2D-projection images. Each projection corresponds to a gradient echo stack of slices with only the central k-space lines being collected for each slice. To enhance catheter contrast, a saturation pulse is added ahead of the projection pair. An offline image processing algorithm was developed to identify the 2D coordinates of the balloon in each projection image and to estimate its corresponding 3D coordinates. Post-processing includes background signal suppression using an atlas of background 2D-projection images. 3D visualization of the catheter and anatomy is proposed using three live sagittal, coronal, and axial (MPR) views and 3D rendering. The technique was tested in a subset of a catheterization step in three patients undergoing MRI-guided cardiac catheterization using a passive balloon catheter.

The extraction of the catheter balloon 3D coordinates was successful in all patients and for the majority of time-points (accuracy >96%). This tracking method enabled a novel 3D visualization strategy for passive balloon catheter, providing enhanced anatomical context during catheter navigation.

The proposed tracking strategy shows promise for robust tracking of passive balloon catheter and may enable enhanced visualization during MRI-guided cardiac catheterization.

Selective homonuclear proton correlation NMR spectroscopy (COSY) provides a useful detection tool for elucidating molecular structures and identifying chemical compositions in 1D spectroscopic patterns. However, conventional 1D selective COSY experiments highly rely on the performance of selective excitation on targeted signals and their applications generally suffer from spectral congestion in complex chemical and biological samples. Herein, based on the concept of targeted excitation on coupled proton pairs and spectroscopic separation on their respective COSY responses, we propose a 1D selective NMR approach that is capable of individually recording direct coupling correlation information of targeted proton groups for analyses on complex samples, free of spectral congestion. The performance of the proposed approach is demonstrated on a medicine sample, a biological molecule, and a real metabonomics sample of human serum. This approach shows a promising analytical technique for structural studies and component analyses in chemical and biological applications. Keywords: NMR spectroscopy, Correlation spectroscopy, Targeted signal excitation, Spectral congestion, Molecular structure analysis.

To investigate the accuracy of proton density fat fraction (PDFF) measurement using chemical shift-encoded MRI (CSE-MRI) with fast imaging techniques in a phantom.

A 1.5T imaging system (Prodiva; Philips Healthcare) and PDFF phantom (Fat Fraction Phantom Model 300; Calimetrix) were used in this study. The acquisitions without fast imaging techniques (conventional acquisition), with parallel imaging in phase-encode direction (SENSE acquisition), with compressed sensing (CS-SENSE acquisition), and with parallel imaging in both phase-encode and slice-encode direction (Dual-SENSE acquisition) were performed. The following acceleration factors in SENSE and CS-SENSE acquisition were used: 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, and 8.0. For Dual-SENSE acquisition, the same acceleration factors (1.5, 2.0, 3.0, 4.0, 5.0) were set in each of the two directions. The relationships between reference PDFF values and PDFF measurements obtained using each acquisition were assessed using linear regression analysis and Bland-Altman analysis.

According to the linear regression analysis, the slopes and intercepts of regression lines were from 0.87 to 1.02 and from 0.06% to 3.55%, respectively. According to Bland-Altman analysis, there were fixed bias between reference PDFF values and PDFF measurements obtained using SENSE acquisition with reduction factor 8.0 and Dual-SENSE acquisition with reduction factor 5.0. For CS-SENSE acquisition with reduction factor from 7.0 to 8.0, SENSE acquisition with reduction factor from 3.0 to 8.0, and Dual-SENSE acquisition with reduction factor from 2.0 to 5.0, some vials had ±1.5% or more errors between the reference PDFF values and PDFF measurements in the range of 0% to 50% PDFF.

In CS-SENSE acquisition, the accuracy of PDFF measurement was maintained within 1.5% up to a reduction factor 6.0. The accuracy of PDFF measurement was maintained within 1.5% up to a reduction factor 2.0 in SENSE acquisition and a reduction factor 1.5 in Dual-SENSE acquisition.

The aim of this study was to compare the diagnostic performance of T2 mapping and Dixon in thyroid-associated ophthalmopathy's disease activity.

Published studies were collected by systematically searching the databases PubMed, Embase, Cochrane Library, Google Scholar, Medline, Web of Science, CNKI, VIP, and WANFANG. The sensitivities, specificities, likelihood ratios, and diagnostic odds ratio (DOR) were confirmed. The symmetric receiver operator characteristic curve (SROC) was used to assess the threshold of T2 mapping and Dixon. Fagan's nomogram was drawn. Meta-regression and subgroup analyses were applied to distinguish the sources of heterogeneity among the included studies. The review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement.

A total of 17 studies were included, comprising 1,455 participants. The combined sensitivity of T2 mapping was 0.70 [95% CI (0.65-0.75)], specificity was 0.84 [95% CI (0.75-0.90)], area under the SROC curve (AUC) was 0.78 [95% CI (0.75-0.82)], and DOR was 12. The combined sensitivity of Dixon was 0.74 [95% CI (0.58-0.85)], specificity was 0.80 [95% CI (0.58-0.93)], AUC was 0.83 [95% CI (0.80-0.86)], and DOR was 11.66. The Deeks' funnel plot showed no existing publication bias. The prospective design, partial verification bias, and blinding contributed to the heterogeneity in specificity and sensitivity. The post-test probability of T2 mapping in TAO patients' disease activity was 75%, and the post-test probability of Dixon in TAO was 87%.

Compared with T2 mapping, Dixon presented a significantly higher sensitivity and AUC for detecting TAO disease activity. Dixon is expected to further improve the accuracy of diagnosis of TAO's disease activity.

To establish an image acquisition and post-processing workflow for the determination of the proton density fat fraction (PDFF) in calf muscle tissue at 7 T.

Echo times (TEs) of the applied vendor-provided multi-echo gradient echo sequence were optimized based on simulations of the effective number of signal averages (NSA*). The resulting parameters were validated by measurements in phantom and in healthy calf muscle tissue (n = 12). Additionally, methods to reduce phase errors arising at 7 T were evaluated. Finally, PDFF values measured at 7 T in calf muscle tissue of healthy subjects (n = 9) and patients with fatty replacement of muscle tissue (n = 3) were compared to 3 T results.

Simulations, phantom and in vivo measurements showed the importance of using optimized TEs for the fat-water separation at 7 T. Fat-water swaps could be mitigated using a phase demodulation with an additional B0 map, or by shifting the TEs to longer values. Muscular PDFF values measured at 7 T were comparable to measurements at 3 T in both healthy subjects and patients with increased fatty replacement.

PDFF determination in calf muscle tissue is feasible at 7 T using a chemical shift-based approach with optimized acquisition and post-processing parameters.

The volume of the implant is the most critical element of breast reconstruction, so it is necessary to accurately assess the preoperative volume of the healthy and affected breasts and select the appropriate implant for placement. Accurate and automated methods for quantitative assessment of breast volume can optimize breast reconstruction surgery and assist physicians in clinical decision making. The aim of this study was to develop an artificial intelligence model for automated segmentation of the breast and measurement of volume.

A total of 249 subjects undergoing breast reconstruction surgery were enrolled in this study. Subjects underwent preoperative breast MRI, and the breast region manually outlined by the imaging physician served as the gold standard for volume measurement by the automated segmentation model. In this study, we developed three automated algorithms for automatic segmentation of breast regions, including a simple alignment model, an alignment dynamic encoding model, and a deep learning model. The volumetric agreement between the three automated segmentation algorithms and the breast regions manually segmented by imaging physicians was evaluated by calculating the mean square error (MSE) and intragroup correlation coefficient (ICC), and the reproducibility of the automated segmentation of the breast regions was assessed by the test-retest step.

The three breast automated segmentation models developed in this study (simple registration model, dynamic programming model, and deep learning model) showed strong ICC with manual segmentation of the breast region, with MSEs of 1.124, 0.693, and 0.781, and ICCs of 0.975 (95% CI, 0.869-0.991), 0.986 (95% CI, 0.967-0.996), and 0.983 (95% CI, 0.961-0.992), respectively. Regarding the test-retest results of breast volume, the dynamic programming model performed the best with an MSE of 0.370 and an ICC of 0.993 (95% CI, 0.982-0.997), followed by the deep learning algorithm with an MSE of 0.741 and an ICC of 0.983 (95% CI, 0.956-0.993), and the simple registration algorithm with an MSE of 0.763 and an ICC of 0.982 (95% CI, 0.949-0.993). The reproducibility of the breast region segmented by the three automated algorithms was higher than that of manual segmentation by different radiologists.

The three automated breast segmentation algorithms developed in this study generate accurate and reliable breast regions, enable highly reproducible breast region segmentation and automated volume measurements, and provide a valuable tool for surgical selection of appropriate prostheses.

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Spectroscopic imaging, rooted in Dixon's two-echo spin sequence to distinguish water and fat, has evolved significantly in acquisition and processing. Yet precise fat quantification remains a persistent challenge in ongoing research. With adequate phase characterization and correction, the fat composition models will impact measurements of fatty tissue. However, the effect of the used fat model in low-fat regions such as healthy muscle is unknown. In this study, we investigate the effect of assumed fat composition, in terms of chain length and double bond count, on fat fraction quantification in healthy muscle, while addressing phase and relaxometry confounders. For this purpose, we acquired bilateral thigh datasets from 38 healthy volunteers. Fat fractions were estimated using the IDEAL algorithm employing three different fat models fitted with and without the initial phase constrained. After data processing and model fitting, we used a convolutional neural net to automatically segment all thigh muscles and subcutaneous fat to evaluate the fitted parameters. The fat composition was compared with those reported in the literature. Overall, all the observed estimated fat composition values fall within the range of previously reported fatty acid composition based on gas chromatography measurements. All methods and models revealed different estimates of the muscle fat fractions in various evaluated muscle groups. Lateral differences changed from 0.5% to 5.3% in the hamstring muscle groups depending on the chosen method. The lowest observed left-right differences in each muscle group were all for the fat model estimating the number of double bonds with the initial phase unconstrained. With this model, the left-right differences were 0.64% ± 0.31%, 0.50% ± 0.27%, and 0.50% ± 0.40% for the quadriceps, hamstrings, and adductors muscle groups, respectively. Our findings suggest that a fat model estimating double bond numbers while allowing separate phases for each chemical species, given some assumptions, yields the best fat fraction estimate for our dataset.

Fat-referenced magnetic resonance imaging (MRI) has emerged as a promising volumetric technique for measuring muscular volume and fat in neuromuscular disorders, but the experience in inflammatory myopathies remains limited. Therefore, this work aimed at describing how sporadic inclusion body myositis (sIBM) manifests on standardized volumetric fat-referenced MRI muscle measurements, including within-scanner repeatability, natural progression rate, and relationship to clinical parameters.

Ten sIBM patients underwent whole-leg Dixon MRI at baseline (test-retest) and after 12 months. The lean muscle volume (LMV), muscle fat fraction (MFF), and muscle fat infiltration (MFI) of the quadriceps, hamstrings, adductors, medial gastrocnemius, and tibialis anterior were computed. Clinical assessments of IBM Functional Rating Scale (IBMFRS) and knee extension strength were also performed. The baseline test-retest MRI measurements were used to estimate the within-subject standard deviation (sw). 12-month changes were derived for all parameters.

The MRI measurements showed high repeatability in all muscles; sw ranged from 2.7 to 18.0 mL for LMV, 0.7-1.3 percentage points (pp) for MFF, and 0.2-0.7 pp for MFI. Over 12 months, average LMV decreased by 7.4% while MFF and MFI increased by 3.8 pp and 1.8 pp, respectively. Mean IBMFRS decreased by 2.4 and mean knee extension strength decreased by 32.8 N.

The MRI measurements showed high repeatability and 12-month changes consistent with muscle atrophy and fat replacement as well as a decrease in both muscle strength and IBMFRS. Our findings suggest that fat-referenced MRI measurements are suitable for assessing disease progression and treatment response in inflammatory myopathies.

In accelerated MRI, the robust artificial-neural-network for k-space interpolation (RAKI) method is an attractive learning-based reconstruction that does not require additional training data. This study was focused on obtaining high quality MR images from regular under-sampled multi-coil k-space data using a high-pass filtered RAKI (HP-RAKI) reconstruction without any extra training data. MRI scan from human subjects was under-sampled with a regular pattern using skipped phase encoding and a fully sampled k-space center. A high-pass (HP) filter was applied in k-space to reduce image support to facilitate linear prediction. The HP filtered k-space center was used to train the RAKI network without any extra training data. The unacquired k-space data can be predicted from a trained RAKI network with optimized parameters. Final reconstruction was obtained after performing an inverse HP filtering for the predicted k-space data. This HP-RAKI method can be extended to corresponding residual structure (HP-rRAKI). HP-RAKI was compared with GRAPPA, HP-GRAPPA, RAKI and MW-RAKI algorithms, and HP-rRAKI was compared with corresponding residual extensions, including rRAKI and MW-rRAKI, all qualitatively and quantitatively using visual inspection and such metrics as SSIM and PSNR. HP-RAKI and HP-rRAKI were found to be effective in reconstructing MR images even at high acceleration factors. HP-RAKI and HP-rRAKI compared favorably with other algorithms. Using high-pass filtered central k-space data for training, HP-RAKI offers higher reconstruction quality for regularly under-sampled multi-coil k-space data without any extra training data. It has shown promising capabilities for fast MRI applications, especially those lacking fully sampled training data.

The T1-weighted GRE (gradient recalled echo) sequence with the Dixon technique for water/fat separation is an essential component of abdominal MRI (magnetic resonance imaging), useful in detecting tumors and characterizing hemorrhage/fat content. Unfortunately, the current implementation of this sequence suffers from several problems: (1) low resolution to maintain high pixel bandwidth and minimize chemical shift; (2) image blurring due to respiratory motion; (3) water/fat swapping due to the natural ambiguity between fat and water peaks; and (4) off-resonance fat blurring due to the multipeak nature of the fat spectrum. The goal of this study was to evaluate the image quality of water/fat separation using a high-resolution 3-point Dixon golden angle radial acquisition with retrospective motion compensation and multipeak fat modeling in children undergoing abdominal MRI.

Twenty-two pediatric patients (4.2 ± 2.3 years) underwent abdominal MRI on a 3 T scanner with routine abdominal protocol and with a 3-point Dixon radial-VIBE (volumetric interpolated breath-hold examination) sequence. Field maps were calculated using 3D graph-cut optimization followed by fat and water calculation from k-space data by iteratively solving an optimization problem. A 6-peak fat model was used to model chemical shifts in k-space. Residual respiratory motion was corrected through soft-gating by weighting each projection based on the estimated respiratory motion from the center of the k-space. Reconstructed images were reviewed by 3 pediatric radiologists on a PACS (picture archiving and communication systems) workstation. Subjective image quality and water/fat swapping artifact were scored by each pediatric radiologist using a 5-point Likert scale. The VoL (variance of Laplacian) of the reconstructed images was used to objectively quantify image sharpness.

Based on the overall Likert scores, the images generated using the described method were significantly superior to those reconstructed by the conventional 2-point Dixon technique ( P < 0.05). Water/fat swapping artifact was observed in 14 of 22 patients using 2-point Dixon, and this artifact was not present when using the proposed method. Image sharpness was significantly improved using the proposed framework.

In smaller patients, a high-quality water/fat separation with sharp visualization of fine details is critical for diagnostic accuracy. High-resolution golden angle radial-VIBE 3-point Dixon acquisition with 6-peak fat model and soft-gated motion correction offers improved image quality at the expense of an additional ~1-minute acquisition time. Thus, this technique offers the potential to replace the conventional 2-point Dixon technique.

Colorectal cancer cells containing mobile lipids are said to be an early indicator of chemotherapy effects. The objective of the study was to examine the frequency and clinical relevance of intratumoral fat deposition in colorectal liver metastases (CRLM) post-chemotherapy using dual-echo chemical shift gradient-echo magnetic resonance imaging (MRI).

A retrospective analysis of 98 patients with CRLM diagnosed between 2017 and 2022 (69 M, mean age 62.87 ± 10.73 years old) who had an MRI after chemotherapy was performed. On dual-echo chemical shift gradient-echo MRI, intratumoral fat deposition of CRLM was evaluated. A signal intensity drop of ≥ 12% in opposed-phase images vs. in-phase images indicated intratumoral fat. After chemotherapy, the presence of fat deposition was correlated with patients' overall survival.

Before and after chemotherapy, 0 (0%) and 29 (29.59%) patients exhibited intratumoral fat. The number of CRLM ranged from 1 to 25 with a median of 3 and a mean size of 32.58 ± 22.95 mm. The groups had statistically different survival times. Overall survival was shorter for patients with intratumoral fat deposition in CRLM (32 months (24-60, 95% CI)) than for patients without fat deposition in CRLM (48 months (36-NA, 95% CI)).

In our group, nearly 30% of CRLM patients exhibited intratumoral fat after chemotherapy. Patients with intratumoral fat deposition in CRLM have a shorter overall survival time. The presence of fat in CRLM correlates with a poor long-term prognosis.

Breast cancer is the most common cancer in women; approximately 1 in 8 women is diagnosed with breast cancer in their lifetime. Some women are at significantly higher risk of developing breast cancer, including women carrying mutations in the BRCA1/2, TP53, or other genes and women with other risk factors. Women with a high lifetime risk for breast cancer are frequently offered annual breast magnetic resonance imaging (MRI) examinations for early breast cancer detection. Breast MRI is commonly performed using a multiparametric imaging protocol, including dynamic contrast-enhanced T1-weighted acquisitions. The dynamic contrast-enhanced T1-weighted acquisitions are frequently transformed into subtraction series, allowing the focused visualization of areas with high signal intensity and masses associated with elevated contrast agent uptake, which are among the hallmarks of suspicious findings. Here, we report a case in which a suspicious lesion-mimicking swap artifact occurred using a T1-weighted contrast-enhanced DIXON acquisition technique in a high-risk breast cancer screening MRI examination.

To introduce an alternative idea for fat suppression that is suited both for low-field applications where conventional fat-suppression approaches become ineffective due to narrow spectral separation and for applications with strong B0 homogeneities.

Separation of fat and water is achieved by sweeping the frequency of RF saturation pulses during continuous radial acquisition and calculating frequency-resolved images using regularized iterative reconstruction. Voxel-wise signal-response curves are extracted that reflect tissue's response to RF saturation at different frequencies and allow the classification into fat or water. This information is then utilized to generate water-only composite images. The principle is demonstrated in free-breathing abdominal and neck examinations using stack-of-stars 3D balanced SSFP (bSSFP) and gradient-recalled echo (GRE) sequences at 0.55 and 3T. Moreover, a potential extension toward quantitative fat/water separation is described.

Experiments with a proton density fat fraction (PDFF) phantom validated the reliability of fat/water separation using signal-response curves. As demonstrated for abdominal imaging at 0.55T, the approach resulted in more uniform fat suppression without loss of water signal and in improved CSF-to-fat signal ratio. Moreover, the approach provided consistent fat suppression in 3T neck exams where conventional spectrally-selective fat saturation failed due to strong local B0 inhomogeneities. The feasibility of simultaneous fat/water quantification has been demonstrated in a PDFF phantom.

The proposed principle achieves reliable fat suppression in low-field applications and adapts to high-field applications with strong B0 inhomogeneity. Moreover, the principle potentially provides a basis for developing an alternative approach for PDFF quantification.

Fatigability in community-dwelling older adults is highly prevalent and disabling, but lacks a treatment. Greater nigrostriatal dopaminergic signaling can ameliorate performance fatigability in healthy young adults, but its role in community-dwelling older adults is not known. We hypothesized that higher nigrostriatal dopaminergic integrity would be associated with lower performance fatigability, independent of cardiopulmonary and musculoskeletal energetics and other health conditions.

In 125 older adults participating in the Study of Muscle, Mobility and Aging, performance fatigability was measured as performance deterioration during a fast 400 m walk (% slowing down from the 2nd to the 9th lap). Nigrostriatal DA integrity was measured using (+)-[11C] dihydrotetrabenazine (DTBZ) PET imaging. The binding signal was obtained separately for the subregions regulating sensorimotor (posterior putamen), reward (ventral striatum), and executive control processes (dorsal striatum). Multivariable linear regression models of performance fatigability (dependent variable) estimated the coefficients of dopamine integrity in striatal subregions, adjusted for demographics, comorbidities, and cognition. Models were further adjusted for skeletal muscle energetics (via biopsy) and cardiopulmonary fitness (via cardiopulmonary exercise testing).

Higher [11C]-DTBZ binding in the posterior putamen was significantly associated with lower performance fatigability (demographic-adjusted standardized β = -1.08, 95% CI: -1.96, -0.20); results remained independent of adjustment for other covariates, including cardiopulmonary and musculoskeletal energetics. Associations with other striatal subregions were not significant.

Dopaminergic integrity in the sensorimotor striatum may influence performance fatigability in older adults without clinically overt diseases, independent of other aging systems.