Iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL): application with fast spin-echo imaging

A fat fraction phantom for establishing new convolutional neural network to determine the pancreatic fat deposition

The determination of fat fraction based on Magnetic Resonance Imaging (MRI) requires extremely accurate data reconstruction for the assessment of pancreatic fat accumulation in medical diagnostics and biological research. In this study, the signal model of the oil and water emulsion was created with a 3.0 T field strength. We examined the quantification of the fat fraction from phantom and the intrapancreatic fat fraction using the techniques of magnetic resonance spectroscopy (MRS) and Iterative Decomposition with Echo Asymmetry and Least-Squares estimate (IDEAL) in magnetic resonance imaging (MRI). Additionally, we contrasted expert manual pancreatic fat assessment with MRS and IDEAL pancreatic fat fraction quantification. There was a strong connection between the true fat volume fraction and the fat fraction from IDEAL and MRS (R² = 0.99 and 0.99, respectively). For both phantom and in vivo measurements, Pearson's correlation and linear regression analysis were used. The findings of the in vivo assessment revealed a variable correlation between the pancreatic fat fraction MRI readings. We also used MR-opsy for manual pancreatic fat fraction segmentation since it read pancreatic fat fractions more accurately than IDEAL and MRS, which aided in the development of machine learning's ability to assess pancreatic fat automatically.

Hyperpolarized Metabolic and Parametric CMR Imaging of Longitudinal Metabolic-Structural Changes in Experimental Chronic Infarction

BACKGROUND

Prolonged ischemia and myocardial infarction are followed by a series of dynamic processes that determine the fate of the affected myocardium toward recovery or necrosis. Metabolic adaptions are considered to play a vital role in the recovery of salvageable myocardium in the context of stunned and hibernating myocardium.

OBJECTIVES

The potential of hyperpolarized pyruvate cardiac magnetic resonance (CMR) alongside functional and parametric CMR as a tool to study the complex metabolic-structural interplay in a longitudinal study of chronic myocardial infarction in an experimental pig model is investigated.

METHODS

Metabolic imaging using hyperpolarized [1-¹³C] pyruvate and proton-based CMR including cine, T₁/T₂ relaxometry, dynamic contrast-enhanced, and late gadolinium enhanced imaging were performed on clinical 3.0-T and 1.5-T MR systems before infarction and at 6 days and 5 and 9 weeks postinfarction in a longitudinal study design. Chronic myocardial infarction in pigs was induced using catheter-based occlusion and compared with healthy controls.

RESULTS

Metabolic image data revealed temporarily elevated lactate-to-bicarbonate ratios at day 6 in the infarcted relative to remote myocardium. The temporal changes of lactate-to-bicarbonate ratios were found to correlate with changes in T₂ and impaired local contractility. Assessment of pyruvate dehydrogenase flux via the hyperpolarized [¹³C] bicarbonate signal revealed recovery of aerobic cellular respiration in the hibernating myocardium, which correlated with recovery of local radial strain.

CONCLUSIONS

This study demonstrates the potential of hyperpolarized CMR to longitudinally detect metabolic changes after cardiac infarction over days to weeks. Viable myocardium in the area at risk was identified based on restored pyruvate dehydrogenase flux.

Influence of patient-specific factors when comparing multifidus fat infiltration between chronic low back pain patients and asymptomatic controls

Introduction

Many studies have attempted to link multifidus (MF) fat infiltration with muscle quality and chronic low back pain (cLBP), but there is no consensus on these relationships.

Methods

In this cross-sectional cohort study, 39 cLBP patients and 18 asymptomatic controls were included. The MF muscle was manually segmented at each lumbar disc level and fat fraction (FF) measurements were taken from the corresponding advanced imaging water-fat images. We assessed the distribution patterns of MF fat from L1L2 to L5S1 and compared these patterns between groups. The sample was stratified by age, sex, body mass index (BMI), subject-reported pain intensity (VAS), and subject-reported low back pain disability (oswestry disability index, ODI).

Results

Older patients had significantly different MF FF distribution patterns compared to older controls (p < 0.0001). Male patients had 34.8% higher mean lumbar spine MF FF compared to male controls (p = 0.0006), significantly different MF FF distribution patterns (p = 0.028), 53.7% higher mean MF FF measurements at L2L3 (p = 0.037), and 50.6% higher mean MF FF measurements at L3L4 (p = 0.041). Low BMI patients had 29.7% higher mean lumbar spine MF FF compared to low BMI controls (p = 0.0077). High BMI patients only had 4% higher mean lumbar spine MF FF compared to high BMI controls (p = 0.7933). However, high BMI patients had significantly different MF FF distribution patterns compared to high BMI controls (p = 0.0324). Low VAS patients did not significantly differ from the control cohort for any of our outcomes of interest; however, high VAS patients had 24.3% higher mean lumbar spine MF FF values (p = 0.0011), significantly different MF FF distribution patterns (p < 0.0001), 34.7% higher mean MF FF at L2L3 (p = 0.040), and 34.6% higher mean MF FF at L3L4 (p = 0.040) compared to the control cohort. Similar trends were observed for ODI.

Conclusions

This study suggests that when the presence of paraspinal muscle fat infiltration is not characteristic of an individual's age, sex, and BMI, it may be associated with lower back pain.

Assessment of Fat Fractions in the Tongue, Soft Palate, Pharyngeal Wall, and Parapharyngeal Fat Pad by the GOOSE and DIXON Methods

OBJECTIVE

The 2-point DIXON method is widely used to assess fat fractions (FFs) in magnetic resonance images (MRIs) of the tongue, pharyngeal wall, and surrounding tissues in patients with obstructive sleep apnea (OSA). However, the method is semiquantitative and is susceptible to B0 field inhomogeneities and R2* confounding factors. Using the method, although several studies have shown that patients with OSA have increased fat deposition around the pharyngeal cavity, conflicting findings was also reported in 1 study. This discrepancy necessitates that we examine the FF estimation method used in the earlier studies and seek a more accurate method to measure FFs.

MATERIALS AND METHODS

We examined the advantages of using the GOOSE (globally optimal surface estimation) method to replace the 2-point DIXON method for quantifying fat in the tongue and surrounding tissues on MRIs. We first used phantoms with known FFs (true FFs) to validate the GOOSE method and examine the errors in the DIXON method. Then, we compared the 2 methods in the tongue, soft palate, pharyngeal wall, and parapharyngeal fat pad of 63 healthy participants to further assess the errors caused by the DIXON method. Six participants were excluded from the comparison of the tongue FFs because of technical failures. Paired Student t tests were performed on FFs to detect significant differences between the 2 methods. All measures were obtained using 3 T Siemens MRI scanners.

RESULTS

In the phantoms, the FFs measured by GOOSE agreed with the true FF, with only a 1.2% mean absolute error. However, the same measure by DIXON had a 10.5% mean absolute error. The FFs obtained by DIXON were significantly lower than those obtained by GOOSE (P < 0.0001) in the human participants. We found strong correlations between GOOSE and DIXON in the tongue (R2 = 0.90), soft palate (R2 = 0.66), and parapharyngeal fat pad (R2 = 0.88), but the correlation was weaker in the posterior pharyngeal walls (R2 = 0.32) in participants.

CONCLUSIONS

The widely used 2-point DIXON underestimated FFs, relative to GOOSE, in phantom measurements and tissues studied in vivo. Thus, an advanced method, such as GOOSE, that uses multiecho complex data is preferred for estimating FF.

Making the invisible visible-ultrashort echo time magnetic resonance imaging: Technical developments and applications

Magnetic resonance imaging (MRI) uses a large magnetic field and radio waves to generate images of tissues in the body. Conventional MRI techniques have been developed to image and quantify tissues and fluids with long transverse relaxation times (T2s), such as muscle, cartilage, liver, white matter, gray matter, spinal cord, and cerebrospinal fluid. However, the body also contains many tissues and tissue components such as the osteochondral junction, menisci, ligaments, tendons, bone, lung parenchyma, and myelin, which have short or ultrashort T2s. After radio frequency excitation, their transverse magnetizations typically decay to zero or near zero before the receiving mode is enabled for spatial encoding with conventional MR imaging. As a result, these tissues appear dark, and their MR properties are inaccessible. However, when ultrashort echo times (UTEs) are used, signals can be detected from these tissues before they decay to zero. This review summarizes recent technical developments in UTE MRI of tissues with short and ultrashort T2 relaxation times. A series of UTE MRI techniques for high-resolution morphological and quantitative imaging of these short-T2 tissues are discussed. Applications of UTE imaging in the musculoskeletal, nervous, respiratory, gastrointestinal, and cardiovascular systems of the body are included.

Quantitative muscle MRI captures early muscle degeneration in calpainopathy

To evaluate differences in qMRI parameters of muscle diffusion tensor imaging (mDTI), fat-fraction (FF) and water T2 time in leg muscles of calpainopathy patients (LGMD R1/D4) compared to healthy controls, to correlate those findings to clinical parameters and to evaluate if qMRI parameters show muscle degeneration in not-yet fatty infiltrated muscles. We evaluated eight thigh and seven calf muscles of 19 calpainopathy patients and 19 healthy matched controls. MRI scans were performed on a 3T MRI including a mDTI, T2 mapping and mDixonquant sequence. Clinical assessment was done with manual muscle testing, patient questionnaires (ACTIVLIM, NSS) as well as gait analysis. Average FF was significantly different in all muscles compared to controls (p < 0.001). In muscles with less than 8% FF a significant increase of FA (p < 0.005) and decrease of RD (p < 0.004) was found in high-risk muscles of calpainopathy patients. Water T2 times were increased within the low- and intermediate-risk muscles (p ≤ 0.045) but not in high-risk muscles (p = 0.062). Clinical assessments correlated significantly with qMRI values: QMFM vs. FF: r = - 0.881, p < 0.001; QMFM versus FA: r = - 0.747, p < 0.001; QMFM versus MD: r = 0.942, p < 0.001. A good correlation of FF and diffusion metrics to clinical assessments was found. Diffusion metrics and T2 values are promising candidates to serve as sensitive early and non-invasive methods to capture early muscle degeneration in non-fat-infiltrated muscles in calpainopathies.

Multiomics study of nonalcoholic fatty liver disease

Nonalcoholic fatty liver (NAFL) and its sequelae are growing health problems. We performed a genome-wide association study of NAFL, cirrhosis and hepatocellular carcinoma, and integrated the findings with expression and proteomic data. For NAFL, we utilized 9,491 clinical cases and proton density fat fraction extracted from 36,116 liver magnetic resonance images. We identified 18 sequence variants associated with NAFL and 4 with cirrhosis, and found rare, protective, predicted loss-of-function variants in MTARC1 and GPAM, underscoring them as potential drug targets. We leveraged messenger RNA expression, splicing and predicted coding effects to identify 16 putative causal genes, of which many are implicated in lipid metabolism. We analyzed levels of 4,907 plasma proteins in 35,559 Icelanders and 1,459 proteins in 47,151 UK Biobank participants, identifying multiple proteins involved in disease pathogenesis. We show that proteomics can discriminate between NAFL and cirrhosis. The present study provides insights into the development of noninvasive evaluation of NAFL and new therapeutic options.

Paraspinal Muscle in Chronic Low Back Pain: Comparison Between Standard Parameters and Chemical Shift Encoding-Based Water-Fat MRI

BACKGROUND

Paraspinal musculature (PSM) is increasingly recognized as a contributor to low back pain (LBP), but with conventional MRI sequences, assessment is limited. Chemical shift encoding-based water-fat MRI (CSE-MRI) enables the measurement of PSM fat fraction (FF), which may assist investigations of chronic LBP.

PURPOSE

To investigate associations between PSM parameters from conventional MRI and CSE-MRI and between PSM parameters and pain.

STUDY TYPE

Prospective, cross-sectional.

POPULATION

Eighty-four adults with chronic LBP (44.6 ± 13.4 years; 48 males).

FIELD STRENGTH/SEQUENCE

3-T, T1-weighted fast spin-echo and iterative decomposition of water and fat with echo asymmetry and least squares estimation sequences.

ASSESSMENT

T1-weighted images for Goutallier classification (GC), muscle volume, lumbar indentation value, and muscle-fat index, CSE-MRI for FF extraction (L1/2-L5/S1). Pain was self-reported using a visual analogue scale (VAS). Intra- and/or interreader agreement was assessed for MRI-derived parameters.

STATISTICAL TESTS

Mixed-effects and linear regression models to 1) assess relationships between PSM parameters (entire cohort and subgroup with GC grades 0 and 1; statistical significance α = 0.0025) and 2) evaluate associations of PSM parameters with pain (α = 0.05). Intraclass correlation coefficients (ICCs) for intra- and/or interreader agreement.

RESULTS

The FF showed excellent intra- and interreader agreement (ICC range: 0.97-0.99) and was significantly associated with GC at all spinal levels. Subgroup analysis suggested that early/subtle changes in PSM are detectable with FF but not with GC, given the absence of significant associations between FF and GC (P-value range: 0.036 at L5/S1 to 0.784 at L2/L3). Averaged over all spinal levels, FF and GC were significantly associated with VAS scores.

DATA CONCLUSION

In the absence of FF, GC may be the best surrogate for PSM quality. Given the ability of CSE-MRI to detect muscle alterations at early stages of PSM degeneration, this technique may have potential for further investigations of the role of PSM in chronic LBP.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY STAGE: 2.

Deep Learning-Based Water-Fat Separation from Dual-Echo Chemical Shift-Encoded Imaging

Conventional water–fat separation approaches suffer long computational times and are prone to water/fat swaps. To solve these problems, we propose a deep learning-based dual-echo water–fat separation method. With IRB approval, raw data from 68 pediatric clinically indicated dual echo scans were analyzed, corresponding to 19382 contrast-enhanced images. A densely connected hierarchical convolutional network was constructed, in which dual-echo images and corresponding echo times were used as input and water/fat images obtained using the projected power method were regarded as references. Models were trained and tested using knee images with 8-fold cross validation and validated on out-of-distribution data from the ankle, foot, and arm. Using the proposed method, the average computational time for a volumetric dataset with ~400 slices was reduced from 10 min to under one minute. High fidelity was achieved (correlation coefficient of 0.9969, l1 error of 0.0381, SSIM of 0.9740, pSNR of 58.6876) and water/fat swaps were mitigated. I is of particular interest that metal artifacts were substantially reduced, even when the training set contained no images with metallic implants. Using the models trained with only contrast-enhanced images, water/fat images were predicted from non-contrast-enhanced images with high fidelity. The proposed water–fat separation method has been demonstrated to be fast, robust, and has the added capability to compensate for metal artifacts.

Two fully automated data-driven 3D whole-breast segmentation strategies in MRI for MR-based breast density using image registration and U-Net with a focus on reproducibility

Presence of higher breast density (BD) and persistence over time are risk factors for breast cancer. A quantitatively accurate and highly reproducible BD measure that relies on precise and reproducible whole-breast segmentation is desirable. In this study, we aimed to develop a highly reproducible and accurate whole-breast segmentation algorithm for the generation of reproducible BD measures. Three datasets of volunteers from two clinical trials were included. Breast MR images were acquired on 3 T Siemens Biograph mMR, Prisma, and Skyra using 3D Cartesian six-echo GRE sequences with a fat-water separation technique. Two whole-breast segmentation strategies, utilizing image registration and 3D U-Net, were developed. Manual segmentation was performed. A task-based analysis was performed: a previously developed MR-based BD measure, MagDensity, was calculated and assessed using automated and manual segmentation. The mean squared error (MSE) and intraclass correlation coefficient (ICC) between MagDensity were evaluated using the manual segmentation as a reference. The test-retest reproducibility of MagDensity derived from different breast segmentation methods was assessed using the difference between the test and retest measures (Δ2-1), MSE, and ICC. The results showed that MagDensity derived by the registration and deep learning segmentation methods exhibited high concordance with manual segmentation, with ICCs of 0.986 (95%CI: 0.974-0.993) and 0.983 (95%CI: 0.961-0.992), respectively. For test-retest analysis, MagDensity derived using the registration algorithm achieved the smallest MSE of 0.370 and highest ICC of 0.993 (95%CI: 0.982-0.997) when compared to other segmentation methods. In conclusion, the proposed registration and deep learning whole-breast segmentation methods are accurate and reliable for estimating BD. Both methods outperformed a previously developed algorithm and manual segmentation in the test-retest assessment, with the registration exhibiting superior performance for highly reproducible BD measurements.

Radiomics analysis of the optic nerve for detecting dysthyroid optic neuropathy, based on water-fat imaging

Objective

Detecting dysthyroid optic neuropathy (DON) in the early stages is vital for clinical decision-making. The aim of this study was to determine the feasibility of using an optic-nerve-based radiomics nomogram on water-fat imaging for detecting DON.

Methods

This study included 104 orbits (83 in the training cohort) from 59 DON patients and 131 orbits (80 in the training cohort) from 69 thyroid-associated ophthalmopathy (TAO) without DON patients. Radiomic features were extracted from the optic-nerve T2-weighted water-fat images for each patient. Selected radiomics features were retrained to construct the radiomic signature model and calculate the radiomic score (Rad-score). The conventional MRI evaluation model was constructed based on apical crowding sign, optic-nerve stretching sign and muscle index. The radiomics nomogram model combining the Rad-score and conventional MRI evaluation factors was then developed. Predictive performance of the three models was assessed using ROC curves.

Results

Eight radiomics features from water-fat imaging were selected to build the radiomics signature. The radiomics nomogram (based on Rad-score, apical crowding sign and optic-nerve stretching sign) had superior diagnostic performance than did the conventional MRI evaluation model (AUC in the training set: 0.92 vs 0.80, the validation set:0.88 vs 0.75). Decision curve analysis confirmed the clinical usefulness of the radiomics nomogram.

Conclusions

This optic-nerve-based radiomics nomogram showed better diagnostic performance than conventional MRI evaluation for differentiating DON from TAO without DON. The changes of the optic-nerve itself may deserve more consideration in the clinical decision-making process.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13244-022-01292-7.

Effect of pulsed electromagnetic field as an intervention for patients with quadriceps weakness after anterior cruciate ligament reconstruction: a double-blinded, randomized-controlled trial

Background

The ultimate goal of anterior cruciate ligament reconstructions (ACLR) is to fulfil the return-to-play (RTP) criteria. Quadriceps muscle strength is one of the key determinants for a patient’s successful return-to-play after ACLR. Quadriceps muscle atrophy can persist beyond the completion of the rehabilitation program in almost half the patients and the reason behind this is still unknown. There are emerging evidences showing that pulsed electromagnetic field (PEMF) can modulate mitochondrial activities for muscle gain. PEMF exposure on top of regular exercise training may promote muscle regeneration and tissue healing.

Methods

This is a double-blinded, randomized controlled trial to investigate the effects of PEMF treatment during the postoperative period on quadriceps muscle strength in ACL injured patient. Adult patients (aged 18–30) with a unilateral ACL injury, total quadriceps muscle volume is equal or more than 7% deficit on involved leg compared with uninvolved leg, sporting injury with a Tegner score of 7+, and both knees without a history of injury/prior surgery will be recruited. To estimate the improvement of patients, isokinetic muscle assessment, ultrasound imaging and MRI for quadriceps muscle thickness, self-reported outcomes with questionnaires, KT-1000 for knee laxity and biomechanical analysis, and Xtreme CT for bone mineral density will be performed. To investigate the mechanism of PEMF therapy on increasing quadriceps strength, samples of blood serum will be drawn before and after intervention.

Discussion

This is the first trial evaluating the effects of PEMF on quadriceps muscle recovery after ACLR. The proposed study addresses a huge research gap by evaluating practical use of PEMF as part of rehabilitation. The proposed study will provide much needed scientific support in the use of this noninvasive treatment modality to facilitate recovery of quadriceps strength after PEMF.

Trial registration

ClinicalTrials.gov NCT05184023. Registered on 5 January 2022

Supplementary Information

The online version contains supplementary material available at 10.1186/s13063-022-06674-2.

People living with HIV have low trabecular bone mineral density, high bone marrow adiposity, and poor trabecular bone microarchitecture at the proximal femur

People living with HIV (PLWH) have increased risk of osteoporosis and fractures. We assessed the proximal femur of PLWH and age-matched seronegative controls using quantitative computed tomography and magnetic resonance imaging. Results suggest that the trabecular compartment is compromised at fracture-prone regions in the proximal femur of PLWH.

INTRODUCTION

People living with HIV (PLWH) have increased risk of osteoporosis and fractures. However, studies assessing the main determinants of bone strength in the proximal femur exclude this vulnerable population. We assessed the proximal femur of 40 PLWH and 26 age-matched seronegative controls using quantitative computed tomography and magnetic resonance imaging.

METHODS

We examined cortical volumetric bone mineral density (Ct.vBMD), trabecular vBMD (Tb.vBMD), cortical thickness (Ct.Th), bone marrow adiposity (BMA), and trabecular number, separation, and bone volume fraction. Parametric comparisons between the two groups were made for the femoral head, femoral neck, trochanter, and total hip using linear regression adjusting for several covariates, including metrics of body composition. In addition, we investigated the associations of BMA with Tb.vBMD and trabecular microarchitecture with Spearman's rank partial correlations.

RESULTS

PLWH had lower Tb.vBMD and deteriorated trabecular microarchitecture in the femoral neck, trochanter and total hip, and elevated BMA in the femoral head, femoral neck, and total hip. Ct.vBMD and Ct.Th were not significantly different between the two groups. BMA was significantly associated with lower Tb.vBMD and deteriorated trabecular microarchitecture in both groups albeit at different femoral regions.

CONCLUSIONS

Our findings suggest that the trabecular, and not the cortical, compartment is compromised in the proximal femur of PLWH. The observed impairments in fracture-prone regions in PLWH indicate lower femoral strength and suggest higher fracture risk. The inverse associations of BMA with trabecular bone density and microarchitecture quality agree with findings at other anatomic sites and in other populations, suggesting that excess BMA possibly due to a switch from the osteoblast to the adipocyte lineage may be implicated in the pathogenesis of bone fragility at the femur in PLWH.

Robustness and stability of volume-based tractography in a multicenter setting

Muscle diffusion tensor imaging (mDTI)-based tractography is a promising tool with which to detect subclinical changes in muscle injuries and to evaluate pathophysiology in neuromuscular diseases. Classic region of interest (ROI)-based tractography is very time-consuming and requires an examiner with extensive experience. (Semi)automatic approaches such as volume-based tractography (VBT) can diminish this problem but its robustness and stability are unknown. The aim of the current study was to assess the performance of VBT in a multicenter setting and to evaluate semiautomatic segmentation approaches in the analysis of VBT-derived data in terms of the comparability of the outcome measures. Five traveling volunteers underwent 3-T mDTI of seven calf muscles of both legs at six different MR sites. Tract properties and diffusion metrics were calculated using VBT. Within-subject coefficients of variance (wsCVs) and intraclass correlation coefficients (ICCs) were calculated to assess the multicenter reproducibility of tract properties such as tract density (TD), mean tract length, volume and tract propagation angle, and diffusion metrics such as fractional anisotropy, mean diffusivity, axial diffusivity (λ₁ ) and radial diffusivity in traveling subjects. Furthermore, 50 individual datasets from five different centers (10 datasets per center) were pooled to assess the feasibility of VBT with manual and semiautomatic segmentation. To assess the differences of tract properties and diffusion metrics between segmentation approaches an ANOVA was performed, and ICC and Bland-Altman plots were analyzed. wsCVs and ICCs showed good reproducibility of the tract properties TD and volume, as well as diffusion metrics. ANOVA showed no significant differences between manual and semiautomatic approaches. ICCs were excellent (≥ 0.992) and Bland-Altman analysis did not reveal any systemic bias between the methods. Tract properties and diffusion metrics derived from VBT showed good comparability among centers. Semiautomatic approaches revealed excellent agreement with gold standard of manual segmentation. These findings suggest that pooling data from different centers to construct a reference database for tractography results is feasible using semiautomatic segmentation approaches.

Associations between moderate alcohol consumption, brain iron, and cognition in UK Biobank participants: Observational and mendelian randomization analyses

BACKGROUND

Brain iron deposition has been linked to several neurodegenerative conditions and reported in alcohol dependence. Whether iron accumulation occurs in moderate drinkers is unknown. Our objectives were to investigate evidence in support of causal relationships between alcohol consumption and brain iron levels and to examine whether higher brain iron represents a potential pathway to alcohol-related cognitive deficits.

METHODS AND FINDINGS

Observational associations between brain iron markers and alcohol consumption (n = 20,729 UK Biobank participants) were compared with associations with genetically predicted alcohol intake and alcohol use disorder from 2-sample mendelian randomization (MR). Alcohol intake was self-reported via a touchscreen questionnaire at baseline (2006 to 2010). Participants with complete data were included. Multiorgan susceptibility-weighted magnetic resonance imaging (9.60 ± 1.10 years after baseline) was used to ascertain iron content of each brain region (quantitative susceptibility mapping (QSM) and T2*) and liver tissues (T2*), a marker of systemic iron. Main outcomes were susceptibility (χ) and T2*, measures used as indices of iron deposition. Brain regions of interest included putamen, caudate, hippocampi, thalami, and substantia nigra. Potential pathways to alcohol-related iron brain accumulation through elevated systemic iron stores (liver) were explored in causal mediation analysis. Cognition was assessed at the scan and in online follow-up (5.82 ± 0.86 years after baseline). Executive function was assessed with the trail-making test, fluid intelligence with puzzle tasks, and reaction time by a task based on the "Snap" card game. Mean age was 54.8 ± 7.4 years and 48.6% were female. Weekly alcohol consumption was 17.7 ± 15.9 units and never drinkers comprised 2.7% of the sample. Alcohol consumption was associated with markers of higher iron (χ) in putamen (β = 0.08 standard deviation (SD) [95% confidence interval (CI) 0.06 to 0.09], p < 0.001), caudate (β = 0.05 [0.04 to 0.07], p < 0.001), and substantia nigra (β = 0.03 [0.02 to 0.05], p < 0.001) and lower iron in the thalami (β = -0.06 [-0.07 to -0.04], p < 0.001). Quintile-based analyses found these associations in those consuming >7 units (56 g) alcohol weekly. MR analyses provided weak evidence these relationships are causal. Genetically predicted alcoholic drinks weekly positively associated with putamen and hippocampus susceptibility; however, these associations did not survive multiple testing corrections. Weak evidence for a causal relationship between genetically predicted alcohol use disorder and higher putamen susceptibility was observed; however, this was not robust to multiple comparisons correction. Genetically predicted alcohol use disorder was associated with serum iron and transferrin saturation. Elevated liver iron was observed at just >11 units (88 g) alcohol weekly c.f. <7 units (56 g). Systemic iron levels partially mediated associations of alcohol intake with brain iron. Markers of higher basal ganglia iron associated with slower executive function, lower fluid intelligence, and slower reaction times. The main limitations of the study include that χ and T2* can reflect changes in myelin as well as iron, alcohol use was self-reported, and MR estimates can be influenced by genetic pleiotropy.

CONCLUSIONS

To the best of our knowledge, this study represents the largest investigation of moderate alcohol consumption and iron homeostasis to date. Alcohol consumption above 7 units weekly associated with higher brain iron. Iron accumulation represents a potential mechanism for alcohol-related cognitive decline.

Multi-parametric quantitative magnetic resonance imaging of the upper arm muscles of patients with spinal muscular atrophy

Quantitative magnetic resonance imaging (qMRI) is frequently used to map the disease state and disease progression in the lower extremity muscles of patients with spinal muscular atrophy (SMA). This is in stark contrast to the almost complete lack of data on the upper extremity muscles, which are essential for carrying out daily activities. The aim of this study was therefore to assess the disease state in the upper arm muscles of patients with SMA in comparison with healthy controls by quantitative assessment of fat fraction, diffusion indices, and water T2 relaxation times, and to relate these measures to muscle force. We evaluated 13 patients with SMA and 15 healthy controls with a 3-T MRI protocol consisting of DIXON, diffusion tensor imaging, and T2 sequences. qMRI measures were compared between groups and related to muscle force measured with quantitative myometry. Fat fraction was significantly increased in all upper arm muscles of the patients with SMA compared with healthy controls and correlated negatively with muscle force. Additionally, fat fraction was heterogeneously distributed within the triceps brachii (TB) and brachialis muscle, but not in the biceps brachii muscle. Diffusion indices and water T2 relaxation times were similar between patients with SMA and healthy controls, but we did find a slightly reduced mean diffusivity (MD), λ1, and λ3 in the TB of patients with SMA. Furthermore, MD was positively correlated with muscle force in the TB of patients with SMA. The variation in fat fraction further substantiates the selective vulnerability of muscles. The reduced diffusion tensor imaging indices, along with the positive correlation of MD with muscle force, point to myofiber atrophy. Our results show the feasibility of qMRI to map the disease state in the upper arm muscles of patients with SMA. Longitudinal data in a larger cohort are needed to further explore qMRI to map disease progression and to capture the possible effects of therapeutic interventions.

Deep learning-based quantitative susceptibility mapping (QSM) in the presence of fat using synthetically generated multi-echo phase training data

PURPOSE

To enable a fast and automatic deep learning-based QSM reconstruction of tissues with diverse chemical shifts, relevant to most regions outside the brain.

METHODS

A UNET was trained to reconstruct susceptibility maps using synthetically generated, unwrapped, multi-echo phase data as input. The RMS error with respect to synthetic validation data was computed. The method was tested on two in vivo knee and two pelvis data sets. Comparisons were made to a conventional fat-water separation pipeline by applying a commonly used graph-cut algorithm, both without and with an extended mask for background field removal (FWS-CONV-QSM and FWS-MASK-CONV-QSM, respectively). Several regions of interest were segmented and compared. Furthermore, the approach was tested on a prostate cancer patient receiving low-dose-rate brachytherapy, to detect and localize the seeds by MRI.

RESULTS

The RMS error was 0.292 ppm with FWS-CONV-QSM and 0.123 ppm for the UNET approach. Susceptibility maps were reconstructed much faster (< 10 s) and completely automatically (no background masking needed) by the UNET compared with the other applied techniques (5 min 51 s and 22 min 44 s for CONV-QSM and FWS-MASK-CONV-QSM, respectively. Background artifacts, fat-water swaps, and hypointense artifacts between I-125 seeds of a patient receiving low-dose brachytherapy in the prostate were largely reduced in the UNET approach.

CONCLUSIONS

Deep learning-based QSM reconstruction, trained solely with synthetic data, is well-suited to rapidly reconstructing high-quality susceptibility maps in the presence of fat without needing masking for background field removal.

Accelerating multi-echo chemical shift encoded water-fat MRI using model-guided deep learning

PURPOSE

To accelerate chemical shift encoded (CSE) water-fat imaging by applying a model-guided deep learning water-fat separation (MGDL-WF) framework to the undersampled k-space data.

METHODS

A model-guided deep learning water-fat separation framework is proposed for the acceleration using Cartesian/radial undersampling data. The proposed MGDL-WF combines the power of CSE water-fat imaging model and data-driven deep learning by jointly using a multi-peak fat model and a modified residual U-net network. The model is used to guide the image reconstruction, and the network is used to capture the artifacts induced by the undersampling. A data consistency layer is used in MGDL-WF to ensure the output images to be consistent with the k-space measurements. A Gauss-Newton iteration algorithm is adapted for the gradient updating of the networks.

RESULTS

Compared with the compressed sensing water-fat separation (CS-WF) algorithm/2-step procedure algorithm, the MGDL-WF increased peak signal-to-noise ratio (PSNR) by 5.31/5.23, 6.11/4.54, and 4.75 dB/1.88 dB with Cartesian sampling, and by 4.13/6.53, 2.90/4.68, and 1.68 dB/3.48 dB with radial sampling, at acceleration rates (R) of 4, 6, and 8, respectively. By using MGDL-WF, radial sampling increased the PSNR by 2.07 dB at R = 8, compared with Cartesian sampling.

CONCLUSIONS

The proposed MGDL-WF enables exploiting features of the water images and fat images from the undersampled multi-echo data, leading to improved performance in the accelerated CSE water-fat imaging. By using MGDL-WF, radial sampling can further improve the image quality with comparable scan time in comparison with Cartesian sampling.

Pancreatic iron quantification with MR imaging: a practical guide

Accurate determination of pancreatic iron status is crucial for preventing impairment of the exocrine and endocrine function of the pancreas and for prospectively stratifying the cardiac iron risk. The following article should be a sort of practical guide for radiologists interested in quantifying pancreatic iron overload by Magnetic Resonance Imaging (MRI). After a brief background on iron-deposition diseases, we will describe basic principles and relative advantages and disadvantages of the more widely used and clinically feasible MRI-based techniques for pancreatic iron assessment. These methods can be classified into signal intensity ratio (SIR) and relaxometry methods. We will examine different technical aspects representing the key for accurate and precise relaxation time measurement.

On quantification errors of R 2 * $$ {R}_2^{\ast } $$ and proton density fat fraction mapping in trabecularized bone marrow in the static dephasing regime

PURPOSE

To study the effect of field inhomogeneity distributions in trabecularized bone regions on the gradient echo (GRE) signal with short TEs and to characterize quantification errors on R 2 * $$ {R}_2^{\ast } $$ and proton density fat fraction (PDFF) maps when using a water-fat model with an exponential R 2 * $$ {R}_2^{\ast } $$ decay model at short TEs.

METHODS

Field distortions were simulated based on a trabecular bone micro CT dataset. Simulations were performed for different bone volume fractions (BV/TV) and for different bone-fat composition values. A multi-TE UTE acquisition was developed to acquire multiple UTEs with random order to minimize eddy currents. The acquisition was validated in phantoms and applied in vivo in a volunteer's ankle and knee. Chemical shift encoded MRI (CSE-MRI) based on a Cartesian multi-TE GRE scan was acquired in the spine of patients with metastatic bone disease.

RESULTS

Simulations showed that signal deviations from the exponential signal decay at short TEs were more prominent for a higher BV/TV. UTE multi-TE measurements reproduced in vivo the simulation-based predicted behavior. In regions with high BV/TV, the presence of field inhomogeneities induced an R 2 * $$ {R}_2^{\ast } $$ underestimation in trabecularized bone marrow when using CSE-MRI at 3T with a short TE.

CONCLUSION

R 2 * $$ {R}_2^{\ast } $$ can be underestimated when using short TEs (<2 ms at 3 T) and a water-fat model with an exponential R 2 * $$ {R}_2^{\ast } $$ decay model in multi-echo GRE acquisitions of trabecularized bone marrow.

The relationship between quantitative magnetic resonance imaging of the ankle plantar flexors, muscle function during walking and maximal strength in people with neuromuscular diseases

BACKGROUND

Progression of plantar flexor weakness in neuromuscular diseases is usually monitored by muscle strength measurements, although they poorly relate to muscle function during walking. Pathophysiological changes such as intramuscular adipose tissue affect dynamic muscle function independent from isometric strength. Diffusion tensor imaging and T2 imaging are quantitative MRI measures reflecting muscular pathophysiological changes, and are therefore potential biomarkers to monitor plantar flexor functioning during walking in people with neuromuscular diseases.

METHODS

In fourteen individuals with plantar flexor weakness diffusion tensor imaging and T2 scans of the plantar flexors were obtained, and the diffusion indices fractional anisotropy and mean diffusivity calculated. With a dynamometer, maximal isometric plantar flexor strength was measured. 3D gait analysis was used to assess maximal ankle moment and power during walking.

FINDINGS

Fractional anisotropy, mean diffusivity and T2 relaxation time all moderately correlated with maximal plantar flexor strength (r > 0.512). Fractional anisotropy and mean diffusivity were not related with ankle moment or power (r < 0.288). T2 relaxation time was strongly related to ankle moment (r = -0.789) and ankle power (r = -0.798), and moderately related to maximal plantar flexor strength (r < 0.600).

INTERPRETATION

In conclusion, T2 relaxation time, indicative of multiple pathophysiological changes, was strongly related to plantar flexor function during walking, while fractional anisotropy and mean diffusivity, indicative of fiber size, only related to maximal plantar flexor strength. This indicates that these measures may be suitable to monitor muscle function and gain insights into the pathophysiological changes underlying a poor plantar flexor functioning during gait in people with neuromuscular diseases.

Evaluation of a Whole-Liver Dixon-Based MRI Approach for Quantification of Liver Fat in Patients with Type 2 Diabetes Treated with Two Isocaloric Different Diets

Dixon-based methods for the detection of fatty liver have the advantage of being non-invasive, easy to perform and analyze, and to provide a whole-liver coverage during the acquisition. The aim of the study was to assess the feasibility of a whole-liver Dixon-based approach for liver fat quantification in type 2 diabetes (T2D) patients who underwent two different isocaloric dietary treatments: a diet rich in monosaturated fatty acids (MUFA) and a multifactorial diet. Thirty-nine T2D patients were randomly assigned to MUFA diet (n = 21) and multifactorial diet (n = 18). The mean values of the proton density fat fraction (PDFF) over the whole liver and over the ROI corresponding to that chosen for MRS were compared to MRS-PDFF using Spearman’s correlation (ρ). Before–after changes in percentage of liver volume corresponding to MRI-PDFF above thresholds associated with hepatic steatosis (LV%TH, with TH = 5.56%, 7.97% and 8.8%) were considered to assess the proposed approach and compared between diets using Wilcoxon rank-sum test. Statistical significance set at p < 0.05. A strong linear relationship was found between MRS-PDFF and MRI-PDFFs (ρ = 0.85, p < 0.0001). Changes in LV%TH% were significantly higher (p < 0.05) in the multifactorial diet than in MUFA diet (25% vs. 9%, 35% vs. 12%, and 38% vs. 13% decrease, respectively, for TH = 5.56%, 7.97%, and 8.8%) and this was reproducible compared to results obtained using the standard liver fat analysis. A volumetric approach based on Dixon method could be an effective, non-invasive technique that could be used for the quantitative analysis of hepatic steatosis in T2D patients.

Motion-compensated fat-water imaging for 3D cardiac MRI at ultra-high fields

PURPOSE

Respiratory motion-compensated (MC) 3D cardiac fat-water imaging at 7T.

METHODS

Free-breathing bipolar 3D triple-echo gradient-recalled-echo (GRE) data with radial phase-encoding (RPE) trajectory were acquired in 11 healthy volunteers (7M\4F, 21-35 years, mean: 30 years) with a wide range of body mass index (BMI; 19.9-34.0 kg/m² ) and volunteer tailored B 1 + shimming. The bipolar-corrected triple-echo GRE-RPE data were binned into different respiratory phases (self-navigation) and were used for the estimation of non-rigid motion vector fields (MF) and respiratory resolved (RR) maps of the main magnetic field deviations (ΔB₀ ). RR ΔB₀ maps and MC ΔB₀ maps were compared to a reference respiratory phase to assess respiration-induced changes. Subsequently, cardiac binned fat-water images were obtained using a model-based, respiratory motion-corrected image reconstruction.

RESULTS

The 3D cardiac fat-water imaging at 7T was successfully demonstrated. Local respiration-induced frequency shifts in MC ΔB₀ maps are small compared to the chemical shifts used in the multi-peak model. Compared to the reference exhale ΔB₀ map these changes are in the order of 10 Hz on average. Cardiac binned MC fat-water reconstruction reduced respiration induced blurring in the fat-water images, and flow artifacts are reduced in the end-diastolic fat-water separated images.

CONCLUSION

This work demonstrates the feasibility of 3D fat-water imaging at UHF for the entire human heart despite spatial and temporal B 1 + and B₀ variations, as well as respiratory and cardiac motion.

Genetic and environmental influences of variation in diffusion MRI measures of white matter microstructure

Quantitative neuroimaging studies in twin samples can investigate genetic contributions to brain structure and microstructure. Diffusion tensor imaging (DTI) studies with twin samples have shown moderate to high heritability in white matter microstructure. This study investigates the genetic and environmental contributions of another widely used diffusion MRI model not yet applied to twin studies, neurite orientation dispersion and density imaging (NODDI). The NODDI model is a multicompartment model of the diffusion-weighted MRI signal, providing estimates of neurite density (ND) and the orientation dispersion index (ODI). A cohort of monozygotic (MZ) and same-sex dizygotic (DZ) twins (N = 460 individuals) between 13 and 24 years of age were scanned with a multi-shell diffusion weighted imaging protocol. Select white matter (WM) regions of interest (ROI) were extracted. Biometric structural equation modeling estimated the relative contributions from additive genetic (A) and common (C) and unique environmental (E) factors. Genetic factors for the NODDI measures accounted for 91% and 65% of the variation of global ND and ODI, respectively, compared with 83% for FA. We observed higher heritability for ND than both FA and ODI in 25 of 30 discrete white matter regions that we examined, suggesting ND may be more sensitive to underlying genetic sources of variation. This study demonstrated that genetic factors play a key role in the development of white matter microstructure using both DTI and NODDI.

Current human brain applications and challenges of dynamic hyperpolarized carbon-13 labeled pyruvate MR metabolic imaging

The ability of hyperpolarized carbon-13 MR metabolic imaging to acquire dynamic metabolic information in real time is crucial to gain mechanistic insights into metabolic pathways, which are complementary to anatomic and other functional imaging methods. This review presents the advantages of this emerging functional imaging technology, describes considerations in clinical translations, and summarizes current human brain applications. Despite rapid development in methodologies, significant technological and physiological related challenges continue to impede broader clinical translation.

Spurious phase correction in rapid metabolic imaging

IDEAL-type magnetic resonance spectroscopic imaging (MRSI) sequences require the acquisition of several datasets using optimized sampling in the time domain to reconstruct metabolite maps. Each unitary scan consists of a selective slice (2D) or slab (3D) excitation followed by an evolution time and then the acquisition of the spatially encoded signal. It is critical that the phase variation during the evolution time for each scan is only dependent on chemical shifts. In this paper, we described the apparition of spurious phase due to either the transmit or the receive frequency. The presence of this unwanted phase depends on (i) where the commutation between these two frequencies is performed and (ii) how it is done, as there are two phase commutation modes: continuous and coherent. We present the correction needed in function of the different cases. It appears that some solutions are universal. However, it is critical to know which case is implemented on the MRI scanner, which is not always easy information to have. We illustrated several cases with our preclinical MRI by using the IDEAL spiral method on a 13C phantom.

Partial Fourier reconstruction of complex MR images using complex-valued convolutional neural networks

PURPOSE

To provide a complex-valued deep learning approach for partial Fourier (PF) reconstruction of complex MR images.

METHODS

Conventional PF reconstruction methods, such as projection onto convex sets (POCS), uses low-resolution image phase information from the central symmetrically sampled k-space for image reconstruction. However, this smooth phase constraint undermines the phase estimation accuracy in presence of rapid local phase variations, causing image artifacts and limiting the extent of PF reconstruction. Using both magnitude and phase characteristics in big complex image datasets, we propose a complex-valued deep learning approach with an unrolled network architecture for PF reconstruction that iteratively reconstructs PF sampled data and enforces data consistency. We evaluate our approach for reconstructing both spin-echo and gradient-echo data.

RESULTS

The proposed method outperformed the iterative POCS PF reconstruction method. It produced better artifact suppression and recovery of both image magnitude and phase details in presence of local phase changes. No noise amplification was observed even for highly PF reconstruction. Moreover, the network trained on axial brain data could reconstruct sagittal and coronal brain and knee data. This method could be extended to 2D PF reconstruction and joint multi-slice PF reconstruction.

CONCLUSION

Our proposed method can effectively reconstruct MR data even at low PF fractions, yielding high-fidelity magnitude and phase images. It presents a valuable alternative to conventional PF reconstruction, especially for phase-sensitive 2D or 3D MRI applications.

Magnetization-prepared spoiled gradient-echo snapshot imaging for efficient measurement of R2 -R1ρ in knee cartilage

PURPOSE

To validate the potential of quantifying R₂ -R_1ρ using one pair of signals with T_1ρ preparation and T₂ preparation incorporated to magnetization-prepared angle-modulated partitioned k-space spoiled gradient-echo snapshots (MAPSS) acquisition and to find an optimal preparation time (T_prep ) for in vivo knee MRI.

METHODS

Bloch equation simulations were first performed to assess the accuracy of quantifying R₂ -R_1ρ using T_1ρ - and T₂ -prepared signals with an equivalent T_prep . For validation of this technique in comparison to the conventional approach that calculates R₂ -R_1ρ after estimating both T₂ and T_1ρ , phantom experiments and in vivo validation with five healthy subjects and five osteoarthritis patients were performed at a clinical 3T scanner.

RESULTS

Bloch equation simulations demonstrated that the accuracy of this efficient R₂ -R_1ρ quantification method and the optimal T_prep can be affected by image signal-to-noise ratio (SNR) and tissue relaxation times, but quantification can be closest to the reference with an around 25 ms T_prep for knee cartilage. Phantom experiments demonstrated that the proposed method can depict R₂ -R_1ρ changes with agarose gel concentration. With in vivo data, significant correlation was observed between cartilage R₂ -R_1ρ measured from the conventional and the proposed methods, and a T_prep of 25.6 ms provided the most agreement by Bland-Altman analysis. R₂ -R_1ρ was significantly lower in patients than in healthy subjects for most cartilage compartments.

CONCLUSION

As a potential biomarker to indicate cartilage degeneration, R₂ -R_1ρ can be efficiently measured using one pair of T_1ρ -prepared and T₂ -prepared signals with an optimal T_prep considering cartilage relaxation times and image SNR.

Whole-body muscle MRI in McArdle disease

This study describes muscle involvement on whole-body MRI (WB-MRI) scans at different stages of McArdle disease. WB-MRI was performed on fifteen genetically confirmed McArdle disease patients between ages 25 to 80. The degree of fatty substitution was scored for 60 muscles using Mercuri's classification. All patients reported an intolerance to exercise and episodes of rhabdomyolysis. A mild fixed muscle weakness was observed in 13/15 patients with neck flexor weakness in 7/15 cases, and proximal muscle weakness in 6/15 cases. A moderate scapular winging was observed in five patients. A careful review of the MRI scans, as well as hierarchical clustering of patients by Mercuri scores, pointed out recurrent muscle changes particularly in the subscapularis, anterior serratus, erector spinae and quadratus femoris muscles. WB-MRI imaging provides clinically relevant information and is a useful tool to orient toward the diagnosis of McArdle disease.

Association of Quadriceps Adiposity With an Increase in Knee Cartilage, Meniscus, or Bone Marrow Lesions Over Three Years

OBJECTIVE

To evaluate the association of fatty infiltration of the quadriceps and vastus medialis (VM) with an increase in knee cartilage, meniscus, or bone marrow lesions, using magnetic resonance imaging (MRI) in knee osteoarthritis (OA) over 3 years.

METHODS

Participants (n = 69) with and without radiographic knee OA underwent MRI at baseline and 3 years later. Chemical shift-based water/fat MRI was used to quantify the intramuscular fat fraction and the lean anatomical cross-sectional area (ACSA) for the VM and entire quadriceps muscles. MRI images of the knee were analyzed using the semiquantitative modified whole-organ MRI score (mWORMS) grading to assess change in lesions in the articular cartilage, meniscus, and bone marrow. Logistic regression was used to assess whether baseline quadriceps and VM fat fraction and lean ACSA were associated with an increase in mWORMS scores. Odds ratios (ORs) were adjusted for age, sex, and body mass index.

RESULTS

Overall, of the 69 subjects, 43 (62%) had an increase in cartilage lesions (26 of 43), meniscus lesions (19 of 43), or bone marrow lesions (22 of 43) scores. The quadriceps (OR 2.13 [95% confidence interval (95% CI) 1.09-4.15]) and VM (OR 2.05 [95% CI 1.25-3.36]) fat fraction were both associated with an increase in cartilage, meniscus, or bone marrow lesion scores over 3 years. The association of quadriceps or VM lean ACSA with the outcomes was not significant.

CONCLUSION

These longitudinal findings using quantitative MRI methods for assessment of muscle adiposity highlight the role of quadriceps adiposity, specifically in the VM, in knee OA progression. However, studies in larger cohorts are needed to confirm these findings.

Evaluation of Glypican-3 Expression in Hepatocellular Carcinoma by Using IDEAL IQ Magnetic Resonance Imaging

RATIONALE AND OBJECTIVES

To investigate the value of iterative decomposition of water and fat with echo asymmetry and least squares estimation (IDEAL IQ) and gadolinium-ethoxybenzyl-diethylenetriamine (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI) for evaluating Glypican-3 (GPC3) expression in hepatocellular carcinoma (HCC).

MATERIALS AND METHODS

Seventy-six patients with histopathologic diagnosis of HCC were retrospectively included in this study. In all patients IDEAL IQ and Gd-EOB-DTPA-enhanced MRI were performed preoperatively using a 3 T MRI system. For an identical slice through the liver of each patient a region of interest was drawn on the tumor in the hepatobiliary phase image and copied to the R2* map and fat fraction map produced by IDEAL IQ. A Mann-Whitney U test was used to compare the region of interest values of R2*, fat fraction and uptake of Gd-EOB-DTPA values between patients with positive and negative GPC3 expression HCC. Receiver operating characteristic analysis was used to determine the diagnostic performances of each of the MRI parameters in evaluating GPC3 expression and histological grade in HCC.

RESULTS

R2* value was significantly higher in cases of positive than negative GPC3 expression HCCs (p < 0.001), whereas there were no significant differences in fat fraction and uptake of Gd-EOB-DTPA between the 2 groups (both p > 0.05). R2* value had higher areas under receiver operating characteristic (0.881), sensitivity (85.96%), and specificity (84.21%) compared to the fat fraction and uptake of Gd-EOB-DTPA.

CONCLUSION

R2* value yielded from IDEAL IQ could reliably predict GPC3 expression in HCC prior to surgery.

Pediatric skeletal diffusion-weighted magnetic resonance imaging: part 1 - technical considerations and optimization strategies

Diffusion-weighted MRI, or DWI, is a fast, quantitative technique that is easily integrated into a morphological MR acquisition. The ability of DWI to aid in detecting multifocal skeletal pathology and in characterizing tissue cellularity to a level beyond that possible with other techniques makes it a niche component of multiparametric MR imaging of the skeleton. Besides its role in disease detection and establishing cellularity and character of osseous lesions, DWI continues to be examined as a surrogate biomarker for therapeutic response of several childhood bone tumors. There is increasing interest in harnessing DWI as a potential substitute to alternative modes of imaging evaluation that involve radiation or administration of intravenous contrast agent or radiopharmaceuticals, for example in early detection and diagnosis of capital femoral epiphyseal ischemia in cases of Legg-Calvé-Perthes disease, or diagnosis and staging of lymphoma. The expected evolution of skeletal diffusivity characteristics with maturation and the unique disease processes that affect the pediatric skeleton necessitate a pediatric-specific discussion. In this article, the author examines the developmentally appropriate normal appearances, technique, artifacts and pitfalls of pediatric skeletal DWI.

Bloch Simulation of a Three-point Dixon Experiment Using a Four-dimensional Numerical Phantom

A 4D numerical phantom, which is defined in the 3D spatial axes and the resonance frequency axis, is indispensable for Bloch simulations of biological tissues with complex distribution of materials. In this study, a 4D numerical phantom was created using MR image datasets of a biological sample containing water and fat, and the Bloch simulations were performed using the 4D numerical phantom. As a result, 3D images of the sample containing water and fat were successfully reproduced, which demonstrated the usefulness of the concept of the 4D numerical phantom.

Regularized joint water-fat separation with B0 map estimation in image space for 2D-navigated interleaved EPI based diffusion MRI

Purpose

To develop a new water–fat separation and B₀ estimation algorithm to effectively suppress the multiple resonances of fat signal in EPI. This is especially relevant for DWI where fat is often a confounding factor.

Methods

Water–fat separation based on chemical‐shift encoding enables robust fat suppression in routine MRI. However, for EPI the different chemical‐shift displacements of the multiple fat resonances along the phase‐encoding direction can be problematic for conventional separation algorithms. This work proposes a suitable model approximation for EPI under B₀ and fat off‐resonance effects, providing a feasible multi‐peak water–fat separation algorithm. Simulations were performed to validate the algorithm. In vivo validation was performed in 6 volunteers, acquiring spin‐echo EPI images in the leg (B₀ homogeneous) and head‐neck (B₀ inhomogeneous) regions, using a TE‐shifted interleaved EPI sequence with/without diffusion sensitization. The results are numerically and statistically compared with voxel‐independent water–fat separation and fat saturation techniques to demonstrate the performance of the proposed algorithm.

Results

The reference separation algorithm without the proposed spatial shift correction caused water–fat ambiguities in simulations and in vivo experiments. Some spectrally selective fat saturation approaches also failed to suppress fat in regions with severe B₀ inhomogeneities. The proposed algorithm was able to achieve improved fat suppression for DWI data and ADC maps in the head–neck and leg regions.

Conclusion

The proposed algorithm shows improved suppression of the multi‐peak fat components in multi‐shot interleaved EPI applications compared to the conventional fat saturation approaches and separation algorithms.

Prediction of treatment response to intravenous glucocorticoid in patients with thyroid-associated ophthalmopathy using T2 mapping and T2 IDEAL

PURPOSE

To investigate the performance of combined T2 mapping and T2 iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) in orbital tissues to predict the therapeutic efficacy of intravenous glucocorticoids (IVGCs) for active and moderate-to-severe thyroid-associated ophthalmopathy (TAO).

METHOD

Sixty-three active and moderate-to-severe TAO patients (responsive group, n = 35; unresponsive group, n = 28) who underwent orbital MRI before receiving IVGCs were retrospectively enrolled. Baseline clinical characteristics and imaging parameters were analyzed and compared between the two groups of different therapeutic efficacy. Binary logistic regression analysis was conducted to determine the independent predictors, the predictive performance of which was evaluated using receiver operating characteristic curve analysis.

RESULTS

The mean T2 relaxation time of extraocular muscle (EOM-T2RT_mean) (P = 0.001), maximum T2RT of EOM (EOM-T2RT_max) (P = 0.001), mean water fraction of EOM (EOM-WF_mean) (P < 0.001), maximum WF of EOM (EOM-WF_max) (P < 0.001) and exophthalmos (P = 0.007) were significantly higher in the responsive group than in the unresponsive group. EOM-T2RT_mean (P < 0.001) and EOM-WF_max (P < 0.001) were determined as independent predictors for responsive patients with TAO in the multivariable analysis. Combining EOM-T2RT_mean ≥ 77.1 and EOM-WF_max ≥ 91.52 demonstrated optimal efficiency for prediction (area under the curve = 0.844) and optimal predictive sensitivity (77.1%). Setting EOM-WF_max ≥ 91.52 achieved the optimal predictive specificity (89.3%).

CONCLUSIONS

Pretherapeutic quantitative measurements, based on combining T2 mapping and T2 IDEAL in orbital tissues, are valuable for predicting IVGC treatment response in active and moderate-to-severe TAO. EOM-T2RT_mean and EOM-WF_max may become promising IVGC treatment response predictors.

Repeatability and accuracy of various region-of-interest sampling strategies for hepatic MRI proton density fat fraction quantification

PURPOSE

To evaluate repeatability of ROI-sampling strategies for quantifying hepatic proton density fat fraction (PDFF) and to assess error relative to the 9-ROI PDFF.

METHODS

This was a secondary analysis in subjects with known or suspected nonalcoholic fatty liver disease who underwent MRI for magnitude-based hepatic PDFF quantification. Each subject underwent three exams, each including three acquisitions (nine acquisitions total). An ROI was placed in each hepatic segment on the first acquisition of the first exam and propagated to other acquisitions. PDFF was calculated for each of 511 sampling strategies using every combination of 1, 2, …, all 9 ROIs. Intra- and inter-exam intra-class correlation coefficients (ICCs) and repeatability coefficients (RCs) were estimated for each sampling strategy. Mean absolute error (MAE) was estimated relative to the 9-ROI PDFF. Strategies that sampled both lobes evenly ("balanced") were compared with those that did not ("unbalanced") using two-sample t tests.

RESULTS

The 29 enrolled subjects (23 male, mean age 24 years) had mean 9-ROI PDFF 11.8% (1.1-36.3%). With more ROIs, ICCs increased, RCs decreased, and MAE decreased. Of the 60 balanced strategies with 4 ROIs, all (100%) achieved inter- and intra-exam ICCs > 0.998, 55 (92%) achieved intra-exam RC < 1%, 50 (83%) achieved inter-exam RC < 1%, and all (100%) achieved MAE < 1%. Balanced sampling strategies had higher ICCs and lower RCs, and lower MAEs than unbalanced strategies in aggregate (p < 0.001 for comparisons between balanced vs. unbalanced strategies).

CONCLUSION

Repeatability improves and error diminishes with more ROIs. Balanced 4-ROI strategies provide high repeatability and low error.

Predictive value of combined computed tomography volumetry and magnetic resonance elastography for major complications after liver resection

PURPOSE

To retrospectively compare the predictive value of computed tomography volumetry (CTV), magnetic resonance elastography (MRE) of the liver, and their combination for major complications after liver resection.

METHODS

We enrolled 108 consecutive patients who underwent anatomical liver resection for liver tumors and preoperative contrast-enhanced CT and MRE. The future liver remnant (FLR) ratio was calculated by CTV, while the liver stiffness measurement (LSM) was obtained by MRE. FLR ratio alone, LSM alone, and combined FLR ratio and LSM were evaluated to predict major complications (Clavien-Dindo grade ≥ IIIa). Univariate and multivariate analyses of hepatic biochemical parameters and imaging data were performed to identify predictors of major complications. Receiver operating characteristic analyses of FLR ratio, LSM, and their combination were performed, and the sensitivity and specificity were calculated.

RESULTS

Twenty-two (20.4%) of the 108 patients experienced major complications. According to multiple regression analysis, the FLR ratio (odds ratio [OR] 0.96, 95% confidence interval [CI] 0.91-0.99, p = 0.040) and LSM (OR 1.72, 95% CI 1.01-2.94, p = 0.047) were independent predictors of major complications. The combined FLR ratio and LSM were predictive of major complications, with an area under the curve (AUC) of 0.818, sensitivity of 68.2%, and specificity of 84.9%. The AUC and specificity for combined FLR ratio and LSM were larger than those for FLR ratio (AUC: 0.711, specificity: 80.2%) and LSM (AUC: 0.793, specificity: 80.2%).

CONCLUSION

Combined CTV and MRE analysis can improve the AUC and specificity for predicting major complications after anatomical liver resection.

Improving deuterium metabolic imaging (DMI) signal-to-noise ratio by spectroscopic multi-echo bSSFP: A pancreatic cancer investigation

PURPOSE

Deuterium metabolic imaging (DMI) maps the uptake of deuterated precursors and their conversion into lactate and other markers of tumor metabolism. Even after leveraging ² H's short T₁ s, DMI's signal-to-noise ratio (SNR) is limited. We hypothesize that a multi-echo balanced steady-state free precession (ME-bSSFP) approach would increase SNR compared to chemical shift imaging (CSI), while achieving spectral isolation of the metabolic precursors and products.

METHODS

Suitably tuned ² H ME-bSSFP (five echo times [TEs], ΔTE = 2.2 ms, repetition time [TR]/flip-angle = 12 ms/60°) was implemented at 15.2T and compared to CSI (TR/flip-angle = 95 ms/90°) regarding SNR and spectral isolation, in simulations, in deuterated phantoms and for the in vivo diagnosis of a mouse tumor model of pancreatic adenocarcinoma (N = 10).

RESULTS

Simulations predicted an SNR increase vs. CSI of 3-5, and that the peaks of ² H-water, ² H_6,6' -glucose, and ² H_3,3' -lactate can be well isolated by ME-bSSFP; phantoms confirmed this. In vivo, at equal spatial resolution (1.25 × 1.25 mm² ) and scan time (10 min), ² H_6,6' -glucose's and ² H_3,3' -lactate's SNR were indeed higher for bSSFP than for CSI, three-fold for glucose (57 ± 30 vs. 19 ± 11, P < .001), doubled for water (13 ± 5 vs. 7 ± 3, P = .005). The time courses and overall localization of all metabolites agreed well, comparing CSI against ME-bSSFP. However, a clearer localization of glucose in kidneys and bladder, the detection of glucose-avid rims in certain tumors, and a heterogeneous pattern of intra-tumor lactate production could only be observed using ME-bSSFP's higher resolution.

CONCLUSIONS

ME-bSSFP provides greater SNR per unit time than CSI, providing for higher spatial resolution mapping of glucose uptake and lactate production in tumors.

MRI-Based Quantitative R2* Mapping at 3 Tesla Reflects Hepatic Iron Overload and Pathogenesis in Nonalcoholic Fatty Liver Disease Patients

BACKGROUND

The role of hepatic iron overload (HIO) in nonalcoholic fatty liver disease (NAFLD) pathogenesis has not been fully elucidated.

PURPOSE

This study aimed to investigate the effect of HIO and examine the diagnostic usefulness of magnetic resonance imaging (MRI)-based R2^* quantification in evaluating hepatic iron content (HIC) and pathological findings in NAFLD.

STUDY TYPE

Prospective and retrospective.

POPULATION

A prospective study of 168 patients (age, 57.2 ± 15.0; male/female, 80/88) and a retrospective validation study of 202 patients (age, 57.0 ± 14.4; male/female, 113/89) with liver-biopsy-confirmed NAFLD were performed.

FIELD STRENGTH/SEQUENCE

3 T; chemical-shift encoded multi-echo gradient echo.

ASSESSMENT

Using liver tissues obtained by liver biopsy, HIC was prospectively evaluated in 168 patients by atomic absorption spectrometry. Diagnostic accuracies of HIC and R2^* for grading hepatic inflammation plus ballooning (HIB) as an indicator of NAFLD activity were assessed.

STATISTICAL TESTS

Student's t-test and analysis of variance (ANOVA) with Scheffe's multiple testing correction for univariate comparisons; multivariate logistic analysis. P-value less than 0.05 is statistically significant.

RESULTS

HIC was significantly correlated with HIB grades (r = 0.407). R2^* was significantly correlated with HIC (r = 0.557) and HIB grades (r = 0.569). R2^* mapped an area under the receiver operating characteristic (AUROC; 0.774) for HIC ≥808 ng/mL (median value) with cutoff value of 62.5 s^-1 . In addition, R2^* mapped AUROC of HIB for grades ≥3 was 0.799 with cutoff value of 58.5 s^-1 . When R2^* was <62.5 s^-1 , R2^* correlated weakly with HIC (r = 0.372) as it was affected by fat deposition and did not correlate with HIB grades (P = 0.052). Conversely, when R2^* was ≥62.5 s^-1 , a significant correlation of R2^* with HIC (r = 0.556) and with HIB grades was observed (P < 0.0001) with being less affected by fat deposition.

DATA CONCLUSION

R2^*  ≥ 62.5 s^-1 is a promising modality for non-invasive diagnosis of clinically important high grades (≥3) of HIB associated with increased HIC.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY STAGE: 2.

Genetic architecture of 11 organ traits derived from abdominal MRI using deep learning

Cardiometabolic diseases are an increasing global health burden. While socioeconomic, environmental, behavioural, and genetic risk factors have been identified, a better understanding of the underlying mechanisms is required to develop more effective interventions. Magnetic resonance imaging (MRI) has been used to assess organ health, but biobank-scale studies are still in their infancy. Using over 38,000 abdominal MRI scans in the UK Biobank, we used deep learning to quantify volume, fat, and iron in seven organs and tissues, and demonstrate that imaging-derived phenotypes reflect health status. We show that these traits have a substantial heritable component (8-44%) and identify 93 independent genome-wide significant associations, including four associations with liver traits that have not previously been reported. Our work demonstrates the tractability of deep learning to systematically quantify health parameters from high-throughput MRI across a range of organs and tissues, and use the largest-ever study of its kind to generate new insights into the genetic architecture of these traits.

Quantitative Muscle MRI in Patients with Neuromuscular Diseases-Association of Muscle Proton Density Fat Fraction with Semi-Quantitative Grading of Fatty Infiltration and Muscle Strength at the Thigh Region

(1) Background and Purpose: The skeletal muscles of patients suffering from neuromuscular diseases (NMD) are affected by atrophy, hypertrophy, fatty infiltration, and edematous changes. Magnetic resonance imaging (MRI) is an important tool for diagnosis and monitoring. Concerning fatty infiltration, T₁-weighted or T₂-weighted DIXON turbo spin echo (TSE) sequences enable a qualitative assessment of muscle involvement. To achieve higher comparability, semi-quantitative grading scales, such as the four-point Mercuri scale, are commonly applied. However, the evaluation remains investigator-dependent. Therefore, effort is being invested to develop quantitative MRI techniques for determination of imaging markers such as the proton density fat fraction (PDFF). The present work aims to assess the diagnostic value of PDFF in correlation to Mercuri grading and clinically determined muscle strength in patients with myotonic dystrophy type 2 (DM2), limb girdle muscular dystrophy type 2A (LGMD2A), and adult Pompe disease. (2) Methods: T₂-weighted two-dimensional (2D) DIXON TSE and chemical shift encoding-based water-fat MRI were acquired in 13 patients (DM2: n = 5; LGMD2A: n = 5; Pompe disease: n = 3). Nine different thigh muscles were rated in all patients according to the Mercuri grading and segmented to extract PDFF values. Muscle strength was assessed according to the British Medical Research Council (BMRC) scale. For correlation analyses between Mercuri grading, muscle strength, and PDFF, the Spearman correlation coefficient (r_s) was computed. (3) Results: Mean PDFF values ranged from 7% to 37% in adults with Pompe disease and DM2 and up to 79% in LGMD2A patients. In all three groups, a strong correlation of the Mercuri grading and PDFF values was observed for almost all muscles (r_s > 0.70, p < 0.05). PDFF values correlated significantly to muscle strength for muscle groups responsible for knee flexion (r_s = -0.80, p < 0.01). (4) Conclusion: In the small, investigated patient cohort, PDFF offers similar diagnostic precision as the clinically established Mercuri grading. Based on these preliminary data, PDFF could be further considered as an MRI-based biomarker in the assessment of fatty infiltration of muscle tissue in NMD. Further studies with larger patient cohorts are needed to advance PDFF as an MRI-based biomarker in NMD, with advantages such as its greater dynamic range, enabling the assessment of subtler changes, the amplified objectivity, and the potential of direct correlation to muscle function for selected muscles.

Water-fat magnetic resonance imaging of adipose tissue compartments in the normal third trimester fetus

BACKGROUND

Assessment of fetal adipose tissue gives information about the future metabolic health of an individual, with evidence that the development of this tissue has regional heterogeneity.

OBJECTIVE

To assess differences in the proton density fat fraction (PDFF) between fetal adipose tissue compartments in the third trimester using water-fat magnetic resonance imaging (MRI).

MATERIALS AND METHODS

Water-fat MRI was performed in a 1.5-T scanner. Fetal adipose tissue was segmented into cheeks, thorax, abdomen, upper arms, forearms, thighs and lower legs. PDFF and R2* values were measured in each compartment.

RESULTS

Twenty-eight women with singleton pregnancies were imaged between 28 and 38 weeks of gestation. At 30 weeks' gestation (n=22), the PDFF was statistically different between the compartments (P<0.0001), with the highest PDFF in cheeks, followed by upper arms, thorax, thighs, forearms, lower legs and abdomen. There were no statistical differences in the rate of PDFF change with gestational age between the white adipose tissue compartments (P=0.97). Perirenal brown adipose tissue had a different PDFF and R2* compared to white adipose tissue, while the rate of R2* change did not significantly change with gestational age between white adipose tissue compartments (P=0.96).

CONCLUSION

Fetal adipose tissue accumulates lipids at a similar rate in all white adipose tissue compartments. PDFF variances between the compartments suggest that accumulation begins at different gestational ages, starting with cheeks, followed by extremities, trunk and abdomen. Additionally, MRI was able to detect differences in the PDFF between fetal brown adipose tissue and white adipose tissue.

[Comparison of 1H-MRS, Dixon fat-water separation and Z-spectral imaging for quantification of brown adipose tissue in rats]

OBJECTIVE

To evaluate the performance of 1H-magnetic resonance spectroscopy (1H-MRS), Dixon fat-water separation and Z-spectral magnetic resonance imaging (ZS-MRI) for quantification of fat content in phantoms and brown adipose tissues in rats.

OBJECTIVE

First, six water-oil mixture phantoms with different fat fractions (0, 20%, 40%, 60%, 80% and 100%) were prepared and placed in a 50-mL centrifuge tube. ZS-MRI, 1H-MRS and Dixon's method were used to quantitatively evaluate the fat content of the phantom, and the results were compared against the actual fat fractions. Then, ZS-MRI and Dixon's method were used to collect the data in the interscapular region of 6 rats, the fat-water distribution map was calculated, and the results were compared with 1H-MRS.

OBJECTIVE

ZS-MRI accurately quantified fat contents in the phantoms (Y=0.95*X+1.48). ZS-MRI was capable of distinguishing brown adipose tissue from white adipose tissue and defining the spatial distribution of the adipose tissue, and the results were highly consistent with those obtained by Dixon's method. No significant differences were found in the results derived by ZS-MRI and 1H-MRS for quantification of brown adipose tissue (P=0.35).

OBJECTIVE

ZS-MRI can generate an artifact-free fat distribution map for quantitative measurement of the content and distribution of brown adipose tissues in rats.

The diagnostic value of the IDEAL-T2WI sequence in dysthyroid optic neuropathy: a quantitative analysis of the optic nerve and cerebrospinal fluid in the optic nerve sheath

OBJECTIVES

To evaluate the optic nerve and CSF in the optic nerve sheath as imaging markers of dysthyroid optic neuropathy (DON).

METHODS

In this single-centre retrospective study, orbital images of 30 consecutive participants (54 orbits) with DON, 30 patients (60 orbits) with thyroid-associated ophthalmopathy (TAO) without DON, and 19 healthy controls (HCs; 38 orbits) were analysed. The diameter and cross-sectional area of the optic nerve and its sheath, water fraction of the optic nerve, and volume of the fluid in the optic nerve sheath were measured and compared. The associations between MR parameters and clinical measures were assessed using correlation analysis.

RESULTS

The diameter and water fraction of the optic nerve (3 mm and 6 mm behind the eyeball), optic nerve subarachnoid space (ONSS) (3 mm and 6 mm behind the eyeball), and subarachnoid fluid volume in the optic nerve sheath were significantly greater in the DON group than in the TAO group (p < 0.01) or HC group (p < 0.01). ROC analysis showed that ONSS 3 mm behind the eyeball (ONSS3) was a robust predictor of DON (AUC = 0.957, sensitivity = 0.907, specificity = 0.9). Water fraction of the optic nerve 3 mm behind the eyeball (water fraction3) had the best specificity (0.967). Water fraction3, fluid volume in the optic nerve sheath, and optic nerve diameter (3 mm behind the eyeball) were correlated with clinical measures (i.e. clinical activity score, mean defect, and pattern standard deviation).

CONCLUSIONS

Increased water fraction of the optic nerve and ONSS3 are promising and easily accessible radiological markers for diagnosing DON.

KEY POINTS

• The water fraction of the optic nerve and optic nerve subarachnoid space (ONSS) are greater in patients with dysthyroid optic neuropathy (DON) than in patients with thyroid-associated ophthalmopathy (TAO) without DON. • The optic nerve and the cerebrospinal fluid in the optic nerve sheath measures are associated with visual dysfunction. • The water fraction of the optic nerve and ONSS may be promising imaging markers for diagnosing DON.

Cortisol effects on brain functional connectivity during emotion processing in women with depression

BACKGROUND

Depression is associated with altered functional connectivity and altered cortisol sensitivity, but the effects of cortisol on functional connectivity in depression are unknown. Previous research shows that brief cortisol augmentation (CORT) has beneficial neurocognitive effects in depression.

METHODS

We investigated the effects of CORT (20mg oral cortisol) on functional connectivity during emotion processing in women with depression. Participants included 75 women with no depression or a depressive disorder. In a double-blind, crossover study, we used functional magnetic resonance imaging to measure effects of CORT vs. placebo on task-based functional connectivity during presentation of emotionally-laden images. We performed psychophysiological interaction (PPI) to test interactions among depression severity, cortisol administration, and task-dependent functional connectivity using the hippocampus and amygdala as seeds.

RESULTS

During the presentation of negative images, CORT (vs. placebo) increased functional connectivity between the hippocampus and putamen in association with depression severity. During the presentation of positive pictures CORT increased functional connectivity between the hippocampus and middle frontal gyrus as well as superior temporal gyrus in association with depression.

LIMITATIONS

Because cortisol was pharmacologically manipulated, results cannot be extrapolated to endogenous increases in cortisol levels. The sample did not permit investigation of differences due to race, ethnicity, or sex. Co-morbidities such as anxiety or PTSD were not accounted for.

CONCLUSIONS

The results suggest that CORT has normalizing effects on task-dependent functional connectivity in women with depression during emotion processing. Increasing cortisol availability or signaling may have therapeutic benefits within affective disorders.

Preliminary analysis of interaction of the fat fraction in the sacroiliac joint among sex, age, and body mass index in a normal Chinese population

Objective

Iterative decomposition of water and fat with echo asymmetry and least-squares estimation-iron quantification (IDEAL-IQ) is a noninvasive and objective method used to quantitatively measure fat content. Although this technique has been used in the entire abdomen, IDEAL-IQ findings in the sacroiliac joint (SIJ) have rarely been reported. This preclinical study was performed to quantify the amount of fat in the SIJ in healthy volunteers by IDEAL-IQ.

Methods

From April to November 2017, 60 healthy volunteers with low back pain were included in this retrospective study. The participants were allocated into groups by age (15–30, 31–50, and ≥51 years), sex (male and female), and body mass index (BMI) (<18.5, 18.5–23.9, and ≥24.0 kg/m²). The iliac-side (Fi) and sacral-side (Fs) fat fractions were obtained in all groups. Two- and three-factor multivariate analyses were performed to analyze the effects of sex, age, and BMI on the Fi and Fs.

Results

The interaction among sex, age, and BMI had no statistically significant effect on the dependent variable. Both Fi and Fs were significantly influenced by age. Fs was significantly influenced by sex.

Conclusion

The IDEAL-IQ sequence can be used to quantitatively assess the SIJ fat content in healthy volunteers.

Accelerated MR spectroscopic imaging-a review of current and emerging techniques

Over more than 30 years in vivo MR spectroscopic imaging (MRSI) has undergone an enormous evolution from theoretical concepts in the early 1980s to the robust imaging technique that it is today. The development of both fast and efficient sampling and reconstruction techniques has played a fundamental role in this process. State-of-the-art MRSI has grown from a slow purely phase-encoded acquisition technique to a method that today combines the benefits of different acceleration techniques. These include shortening of repetition times, spatial-spectral encoding, undersampling of k-space and time domain, and use of spatial-spectral prior knowledge in the reconstruction. In this way in vivo MRSI has considerably advanced in terms of spatial coverage, spatial resolution, acquisition speed, artifact suppression, number of detectable metabolites and quantification precision. Acceleration not only has been the enabling factor in high-resolution whole-brain 1 H-MRSI, but today is also common in non-proton MRSI (31 P, 2 H and 13 C) and applied in many different organs. In this process, MRSI techniques had to constantly adapt, but have also benefitted from the significant increase of magnetic field strength boosting the signal-to-noise ratio along with high gradient fidelity and high-density receive arrays. In combination with recent trends in image reconstruction and much improved computation power, these advances led to a number of novel developments with respect to MRSI acceleration. Today MRSI allows for non-invasive and non-ionizing mapping of the spatial distribution of various metabolites' tissue concentrations in animals or humans, is applied for clinical diagnostics and has been established as an important tool for neuro-scientific and metabolism research. This review highlights the developments of the last five years and puts them into the context of earlier MRSI acceleration techniques. In addition to 1 H-MRSI it also includes other relevant nuclei and is not limited to certain body regions or specific applications.

Single-shot RARE with Dixon: Application to robust abdominal imaging with uniform fat and water separation at 3T

PURPOSE

To develop a true single shot turbo spin echo (SShTSE) acquisition with Dixon for robust T₂ -weighted abdominal imaging with uniform fat and water separation at 3T.

METHODS

The in-phase (IP) and out-of-phase (OP) echoes for Dixon processing were acquired in the same repetition time of a SShTSE using partial echoes. A phase-preserved bi-directional homodyne reconstruction was developed to compensate the partial echo and the partial phase encoding of SShTSE. With IRB approval, the SShTSE-Dixon was compared against standard SShTSE, without and with fat suppression using spectral adiabatic inversion recovery (SPAIR) in 5 healthy volunteers and 5 patients. The SNR and contrast ratio (CR) of spleen to liver were compared among different acquisitions.

RESULTS

The bi-directional homodyne reconstruction successfully minimized ringing artifacts because of partial acquisitions. SShTSE-Dixon achieved uniform fat suppression compared to SShTSE-SPAIR with fat suppression failures of 1/10 versus 10/10 in the axial plane and 0/5 versus 5/5 in the coronal plane, respectively. The SNRs of the liver (12.2 ± 4.9 vs. 11.7 ± 5.2; P = .76) and spleen (25.9 ± 11.6 vs. 23.7 ± 9.7; P = .14) were equivalent between fat-suppressed images (SShTSE-Dixon water-only and SShTSE-SPAIR). The SNRs of liver (14.4 ± 5.7 vs. 13.4 ± 5.0; P = .60) and spleen (26.5 ± 10.1 vs. 25.7 ± 8.5; P = .56) were equivalent between non-fat-suppressed images (SShTSE-Dixon IP and SShTSE). The CRs of spleen to liver were also similar between fat-suppressed images (2.6 ± 0.4 vs. 2.5 ± 0.5; P =.92) and non-fat-suppressed images (2.3 ± 0.6 vs. 2.2 ± 0.4; P =.84).

CONCLUSION

SShTSE-Dixon generates robust abdominal T₂ -weighted images at 3T with and without uniform fat suppression, along with perfectly co-registered fat-only images in a single acquisition.