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

Distortion-free water-fat separated diffusion-weighted imaging using spatiotemporal joint reconstruction

PURPOSE

Diffusion-weighted imaging (DWI) suffers from geometric distortion and chemical shift artifacts due to the commonly used Echo Planar Imaging (EPI) trajectory. Even with fat suppression in DWI, severe B0 and B1 variations can result in residual fat, which becomes both a source of image artifacts and a confounding factor in diffusion-weighted contrast in distinguishing benign and malignant tissues. This work presents a method for acquiring distortion-free diffusion-weighted images using spatiotemporal acquisition and joint reconstruction. Water-fat separation is performed by chemical-shift encoding.

METHODS

Spatiotemporal acquisition is employed to obtain distortion-free images at a series of echo times. Chemical-shift encoding is used for water-fat separation. Reconstruction and separation are performed jointly in the spat-spectral domain. To address the shot-to-shot motion-induced phase in DWI, an Fast Spin Echo (FSE)-based phase navigator is incorporated into the sequence to obtain distortion-free phase information. The proposed method was validated in phantoms and in vivo for the brain, head and neck, and breast.

RESULTS

The proposed method enables the acquisition of distortion-free diffusion-weighted images in the presence of B0 field inhomogenieties commonly observed in the body. Water and fat components are separated with no obvious spectral leakage artifacts. The estimated Apparent Diffusion Coefficient (ADC) is comparable to that of multishot DW-EPI.

CONCLUSION

Distortion-free, water-fat separated diffusion-weighted images in body can be obtained through the utilization of spatiotemporal acquisition and joint reconstruction methods.

Lesion-mimicking DIXON swap artifact in contrast-enhanced subtraction breast MRI

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.

Prospective longitudinal cohort study of quantitative muscle magnetic resonance imaging in a healthy control population

Quantitative muscle magnetic resonance imaging (qMRI) is a valuable methodology for assessing muscular injuries and neuromuscular disorders. Notably, muscle diffusion tensor imaging (DTI) gives insights into muscle microstructural and macrostructural characteristics. However, the long-term reproducibility and robustness of these measurements remain relatively unexplored. The purpose of this prospective longitudinal cohort study was to assess the long-term robustness and range of variation of qMRI parameters, especially DTI metrics, in the lower extremity muscles of healthy controls under real-life conditions. Twelve volunteers (seven females, age 44.1 ± 12.1 years, body mass index 23.3 ± 2.0 kg/m2) underwent five leg muscle MRI sessions every 20 ± 4 weeks over a total period of 1.5 years. A multiecho gradient-echo Dixon-based sequence, a multiecho spin-echo T2-mapping sequence, and a spin-echo echo planar imaging diffusion-weighted sequence were acquired bilaterally with a Philips 3-T Achieva MR System using a 16-channel torso coil. Fifteen leg muscles were segmented in both lower extremities. qMRI parameters, including fat fraction (FF), water T2 relaxation time, and the diffusion metrics fractional anisotropy (FA) and mean diffusivity (MD), were evaluated. Coefficients of variance (wsCV) and intraclass correlation coefficients (ICCs) were calculated to assess the reproducibility of qMRI parameters. The standard error of measurement (SEM) and the minimal detectable change (MDC) were calculated to determine the range of variation. All tests were applied to all muscles and, subsequently, to each muscle separately. wsCV showed good reproducibility (≤ 10%) for all qMRI parameters in all muscles. The ICCs revealed excellent agreement between time points (FF = 0.980, water T2 = 0.941, FA = 0.952, MD = 0.948). Random measurement errors assessed by SEM and the MDC were low (< 12%). In conclusion, in this study, we showed that qMRI parameters in healthy volunteers living normal lives are stable over 18 months, thereby defining a benchmark for the expected range of variation over time.

Mapping the amplitude and phase of dissolved 129Xe red blood cell signal oscillations with keyhole spectroscopic lung imaging

PURPOSE

To assess the regional amplitude and phase of dissolved 129Xe red blood cell (RBC) signal oscillations in the lung vasculature with keyhole spectroscopic imaging and to compare with previous methodology, which does not account for oscillation phase.

METHODS

129Xe gas transfer was measured with a four-echo 3D radial spectroscopic imaging sequence. Keyhole reconstruction-based RBC signal oscillation amplitude mapping was applied retrospectively to data acquired from 28 healthy volunteers, 4 chronic thromboembolic pulmonary hypertension (CTEPH) patients, and 5 patients who were hospitalized due to COVID-19 pneumonia and had residual lung abnormalities. Using a sliding window keyhole reconstruction, maps of RBC oscillation amplitude were corrected for regional phase difference. Repeatability of the phase-adjusted oscillation amplitude was assessed in 8 healthy volunteers across three scans.

RESULTS

With sliding window keyhole reconstruction, regional phase differences were observed in the RBC signal oscillations: mean phase = (0.27 ± 0.19) rad in healthy volunteers, (0.24 ± 0.13) rad in CTEPH patients, and (0.33 ± 0.19) rad in patients with post-COVID-19 residual lung abnormality. The oscillation amplitude and phase maps were more heterogeneous (i.e., they showed increased coefficient of variation) for the CTEPH patients. The RBC oscillation amplitude was repeatable, and the mean three-scan coefficient of variation was smaller when the phase adjustment was made (0.07 ± 0.04 compared with 0.16 ± 0.05).

CONCLUSION

Sliding window keyhole reconstruction of radial dissolved 129Xe imaging reveals regional phase differences in the RBC oscillations, which are not captured when performing two phase keyhole reconstruction. This regional phase information may reflect the hemodynamic effect of the cardiac pulse wave in the pulmonary microvasculature.

Quantitative muscle magnetic resonance imaging in limb-girdle muscular dystrophy type R1 (LGMDR1): A prospective longitudinal cohort study

Limb-girdle muscular dystrophy (LGMD) type R1 (LGMDR1) is the most common subtype of LGMD in Europe. Prospective longitudinal data, including clinical assessments and new biomarkers such as quantitative magnetic resonance imaging (qMRI), are needed to evaluate the natural course of the disease and therapeutic options. We evaluated eight thigh and seven leg muscles of 13 LGMDR1 patients (seven females, mean age 36.7 years, body mass index 23.9 kg/m2) and 13 healthy age- and gender-matched controls in a prospective longitudinal design over 1 year. Clinical assessment included testing for muscle strength with quick motor function measure (QMFM), gait analysis and patient questionnaires (neuromuscular symptom score, activity limitation [ACTIVLIM]). MRI scans were performed on a 3-T MRI scanner, including a Dixon-based sequence, T2 mapping and diffusion tensor imaging. The qMRI values of fat fraction (FF), water T2 relaxation time (T2), fractional anisotropy, mean diffusivity, axial diffusivity and radial diffusivity were analysed. Within the clinical outcome measures, significant deterioration between baseline and follow-up was found for ACTIVLIM (p = 0.029), QMFM (p = 0.012). Analysis of qMRI parameters of the patient group revealed differences between time points for both FF and T2 when analysing all muscles (FF: p < 0.001; T2: p = 0.016). The highest increase of fat replacement was found in muscles with an FF of between 10% and 50% at baseline. T2 in muscles with low-fat replacement increased significantly. No significant differences were found for the diffusion metrics. Significant correlations between qMRI metrics and clinical assessments were found at baseline and follow-up, while only T2 changes in thigh muscles correlated with changes in ACTIVLIM over time (ρ = -0.621, p < 0.05). Clinical assessments can show deterioration of the general condition of LGMDR1 patients. qMRI measures can give additional information about underlying pathophysiology. Further research is needed to establish qMRI outcome measures for clinical trials.

Fatty acid composition MRI of epicardial adipose tissue: Methods and detection of proinflammatory biomarkers in ST-segment elevation myocardial infarction patients

PURPOSE

To develop a method for quantifying the fatty acid composition (FAC) of human epicardial adipose tissue (EAT) using accelerated MRI and identify its potential for detecting proinflammatory biomarkers in patients with ST-segment elevation myocardial infarction (STEMI).

METHODS

A multi-echo radial gradient-echo sequence was developed for accelerated imaging during a breath hold using a locally low-rank denoising technique to reconstruct undersampled images. FAC mapping was achieved by fitting the multi-echo images to a multi-resonance complex signal model based on triglyceride characterization. Validation of the method was assessed using a phantom comprised of multiple oils. In vivo imaging was performed in STEMI patients (n = 21; 14 males/seven females). FAC was quantified in EAT, subcutaneous AT, and abdominal visceral AT.

RESULTS

Phantom validation demonstrated strong correlations (r > 0.97) and statistical significance (p < 0.0001) between measured and reference proton density fat fraction and FAC values. In vivo imaging of STEMI patients revealed a distinct EAT FAC profile compared to subcutaneous AT and abdominal visceral AT. EAT FAC parameters had significant correlations with left ventricular (LV) end-diastolic volume index (p < 0.05), LV end-systolic volume index (p < 0.05), and LV mass index (p < 0.05).

CONCLUSIONS

Accelerated MRI enabled accurate quantification of human EAT FAC. The relationships between the EAT FAC profile and LV structure and function in STEMI patients suggest the potential of EAT FAC MRI as a biomarker for adipose tissue quality and inflammatory status in cardiovascular disease.

Biological markers of brain network connectivity and pain sensitivity distinguish low coping from high coping Veterans with persistent post-traumatic headache

Headache is the most common type of pain following mild traumatic brain injury. Roughly half of those with persistent post-traumatic headache (PPTH) also report neck pain which is associated with greater severity and functional impact of headache. This observational cohort study aimed to identify biological phenotypes to help inform mechanism-based approaches in the management of PPTH with and without concomitant neck pain. Thirty-three military Veterans (mean (SD) = 37±16 years, 29 males) with PPTH completed a clinical assessment, quantitative sensory testing, and magnetic resonance imaging of the brain and cervical spine. Multidimensional phenotyping was performed using a Random Forest analysis and Partitioning Around Medoids (PAM) clustering of input features from three biologic domains: 1) resting state functional connectivity (rsFC) of the periaqueductal gray (PAG), 2) quality and size of cervical muscles, and 3) mechanical pain sensitivity and central modulation of pain. Two subgroups were distinguished by biological features that included forehead pressure pain threshold and rsFC between the PAG and selected nodes within the default mode, salience, and sensorimotor networks. Compared to the High Pain Coping group, the Low Pain Coping group exhibited higher pain-related anxiety (p=0.009), higher pain catastrophizing (p=0.004), lower pain self-efficacy (p=0.010), and greater headache-related disability (p=0.012). Findings suggest that greater functional connectivity of pain modulation networks involving the PAG combined with impairments in craniofacial pain sensitivity, but not cervical muscle health, distinguish a clinically important subgroup of individuals with PPTH who are less able to cope with pain and more severely impacted by headache.

Enabling SENSE accelerated 2D CSI for hyperpolarized carbon-13 imaging

As hyperpolarized (HP) carbon-13 (13C) metabolic imaging is clinically translated, there is a need for easy-to-implement, fast, and robust imaging techniques. However, achieving high temporal resolution without decreasing spatial and/or spectral resolution, whilst maintaining the usability of the imaging sequence is challenging. Therefore, this study looked to accelerate HP 13C MRI by combining a well-established and robust sequence called two-dimensional Chemical Shift Imaging (2D CSI) with prospective under sampling and SENSitivity Encoding (SENSE) reconstruction. Due to the low natural abundance of 13C, the sensitivity maps cannot be pre-acquired for the reconstruction. As such, the implementation of sodium (23Na) sensitivity maps for SENSE reconstructed 13C CSI was demonstrated in a phantom and in vivo in the pig kidney. Results showed that SENSE reconstruction using 23Na sensitivity maps corrected aliased images with a four-fold acceleration. With high temporal resolution, the kidney spectra produced a detailed metabolic arrival and decay curve, useful for further metabolite kinetic modelling or denoising. Metabolic ratio maps were produced in three pigs demonstrating the technique's ability for repeat metabolic measurements. In cases with unknown metabolite spectra or limited HP MRI specialist knowledge, this robust acceleration method ensures comprehensive capture of metabolic signals, mitigating the risk of missing spectral data.

Automated evaluation of hip abductor muscle quality and size in hip osteoarthritis: Localized muscle regions are strongly associated with overall muscle quality

Limited information exists regarding abductor muscle quality variation across its length and which locations are most representative of overall muscle quality. This is exacerbated by time-intensive processes for manual muscle segmentation, which limits feasibility of large cohort analyses. The purpose of this study was to develop an automated and localized analysis pipeline that accurately estimates hip abductor muscle quality and size in individuals with mild-to-moderate hip osteoarthritis (OA) and identifies regions of each muscle which provide best estimates of overall muscle quality. Forty-four participants (age 52.7 ± 16.1 years, BMI 23.7 ± 3.4 kg/m2, 14 males) with and without mild-to-moderate radiographic hip OA were recruited for this study. Unilateral hip magnetic resonance (MR) images were acquired on a 3.0 T MR scanner and included axial T1-weighted fast spin echo and 3D axial Iterative Decomposition of water and fat with Echo Asymmetry and Least-squares estimation (IDEAL-IQ) spoiled gradient-recalled echo (SPGR) with multi-peak fat spectrum modeling and single T2* correction. A three dimensional (3D) V-Net convolutional neural network was trained to automatically segment the gluteus medius (GMED), gluteus minimus (GMIN), and tensor fascia lata (TFL) on axial IDEAL-IQ. Agreement between manual and automatic segmentation and associations between axial fat fraction (FF) estimated from IDEAL-IQ and overall muscle FF were evaluated. Dice scores for automatic segmentation were 0.94, 0.87, and 0.91 for GMED, GMIN, and TFL, respectively. GMED, GMIN, and TFL volumetric and FF measures were strongly correlated (r: 0.92-0.99) between automatic and manual segmentations, where all values fell within the 95% limits of agreement of [-9.79 cm3, 17.43 cm3] and [-1.99%, 2.89%], respectively. Axial FF was significantly associated with overall FF with the strongest correlations at 50%, 50%, and 65% the length of the GMED, GMIN, and TFL muscles, respectively (r: 0.93-0.97). An automated and localized analysis can provide efficient and accurate estimates of hip abductor muscle quality and size across muscle length. Specific regions of the muscle may be used to estimate overall muscle quality in an abbreviated evaluation of muscle quality.

Application of Quantitative MRI in Thyroid Eye Disease: Imaging Techniques and Clinical Practices

Thyroid eye disease (TED) is a complex autoimmune disorder that impairs various orbital structures, leading to cosmetic damage and vision loss. Magnetic resonance imaging (MRI) is a fundamental diagnostic tool utilized in clinical settings of TED, for its accurate demonstration of orbital lesions and indication of disease conditions. The application of quantitative MRI has brought a new prospect to the management and research of TED, offering more detailed information on morphological and functional changes in the orbit. Therefore, many researchers concentrated on the implementation of different quantitative MRI techniques on TED for the exploration of clinical practices. Despite the abundance of studies utilizing quantitative MRI in TED, there remain considerable barriers and disputes on the best exploitation of this tool. This could possibly be attributed to the complexity of TED and the fast development of MRI techniques. It is necessary that clinical and radiological aspects of quantitative MRI in TED be better integrated into comprehensive insights. Hence, this review traces back 30 years of publications regarding quantitative MRI utilized in TED and elucidates this promising application in the facets of imaging techniques and clinical practices. We believe that a deeper understanding of the application of quantitative MRI in TED will enhance the efficacy of the multidisciplinary management of TED. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 3.

Parameter optimization for proton density fat fraction quantification in skeletal muscle tissue at 7 T

OBJECTIVE

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.

MATERIALS AND METHODS

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.

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.

CONCLUSION

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

Fat-suppression T2 relaxation time and water fraction predict response to intravenous glucocorticoid therapy for thyroid-associated ophthalmopathy

OBJECTIVE

To investigate the value of fat-suppression (FS) T2 relaxation time (T2RT) derived from FS T2 mapping and water fraction (WF) derived from T2 IDEAL to predict the treatment response to intravenous glucocorticoids (IVGC) in patients with thyroid-associated ophthalmopathy (TAO) based on texture analysis.

MATERIALS AND METHODS

In this study, 89 patients clinically diagnosed with active and moderate-to-severe TAO were enroled (responsive group, 48 patients; unresponsive group, 41 patients). The baseline clinical characteristics and texture features were compared between the two groups. Multivariate analysis was performed to identify the independent predictors of treatment response to IVGC. ROC analysis and the DeLong test were used to assess and compare the predictive performance of different models.

RESULTS

The responsive group exhibited significantly shorter disease duration and higher 90th percentile of FS T2RT and kurtosis of WF in the extraocular muscle (EOM) and 95th percentile of WF in the orbital fat (OF) than the unresponsive group. Model 2 (disease duration + WF; AUC, 0.816) and model 3 (disease duration + FS T2RT + WF; AUC, 0.823) demonstrated superior predictive efficacy compared to model 1 (disease duration + FS T2RT; AUC, 0.756), while there was no significant difference between models 2 and 3.

CONCLUSIONS

The orbital tissues of responders exhibited more oedema and heterogeneity. Furthermore, OF is as valuable as EOM for assessing the therapeutic efficacy of IVGC. Finally, WF derived from T2 IDEAL processed by texture analysis can provide valuable information for predicting the treatment response to IVGC in patients with active and moderate-to-severe TAO.

CLINICAL RELEVANCE STATEMENT

The texture features of FS T2RT and WF are different between responders and non-responders, which can be the predictive tool for treatment response to IVGC.

KEY POINTS

Texture analysis can be used for predicting response to IVGC in TAO patients. TAO patients responsive to IVGC show more oedema and heterogeneity in the orbital tissues. WF from T2 IDEAL is a tool to predict the therapeutic response of TAO.

A Prediction Model for Detecting Dysthyroid Optic Neuropathy Based on Clinical Factors and Imaging Markers of the Optic Nerve and Cerebrospinal Fluid in the Optic Nerve Sheath

OBJECTIVE

This study aimed to develop and test a model for predicting dysthyroid optic neuropathy (DON) based on clinical factors and imaging markers of the optic nerve and cerebrospinal fluid (CSF) in the optic nerve sheath.

METHODS

This retrospective study included patients with thyroid-associated ophthalmopathy (TAO) without DON and patients with TAO accompanied by DON at our hospital. The imaging markers of the optic nerve and CSF in the optic nerve sheath were measured on the water-fat images of each patient and, together with clinical factors, were screened by Least absolute shrinkage and selection operator. Subsequently, we constructed a prediction model using multivariate logistic regression. The accuracy of the model was verified using receiver operating characteristic curve analysis.

RESULTS

In total, 80 orbits from 44 DON patients and 90 orbits from 45 TAO patients were included in our study. Two variables (optic nerve subarachnoid space and the volume of the CSF in the optic nerve sheath) were found to be independent predictive factors and were included in the prediction model. In the development cohort, the mean area under the curve (AUC) was 0.994, with a sensitivity of 0.944, specificity of 0.967, and accuracy of 0.901. Moreover, in the validation cohort, the AUC was 0.960, the sensitivity was 0.889, the specificity was 0.893, and the accuracy was 0.890.

CONCLUSIONS

A combined model was developed using imaging data of the optic nerve and CSF in the optic nerve sheath, serving as a noninvasive potential tool to predict DON.

Tailored and universal parallel transmit broadband pulses for homogeneous 3D excitation of the human heart at 7T

PURPOSE

To research and evaluate the performance of broadband tailored kT-point pulses (TP) and universal pulses (UP) for homogeneous excitation of the human heart at 7T.

METHODS

Relative 3DB 1 + $$ {\mathrm{B}}_1^{+} $$ -maps of the thorax were acquired from 29 healthy volunteers. TP and UP were designed using the small-tip-angle approximation for a different composition of up to seven resonance frequencies. TP were computed for each of the 29B 1 + $$ {\mathrm{B}}_1^{+} $$ -maps, and UPs were calculated using 22B 1 + $$ {\mathrm{B}}_1^{+} $$ -maps and tested in seven testcases. The performance of the pulses was analyzed using the coefficient of variation (CV) in the 3D heart volumes. The 3D gradient-echo (GRE) scans were acquired for the seven testcases to qualitatively validate theB 1 + $$ {\mathrm{B}}_1^{+} $$ -predictions.

RESULTS

Single- and double-frequency optimized pulses achieved homogeneity in flip angle (FA) for the frequencies they were optimized for, while the broadband pulses achieved uniformity in FA across a 1300 Hz frequency range.

CONCLUSION

Broadband TP and UP can be used for homogeneous excitation of the heart volume across a 1300 Hz frequency range, including the water and the main six fat peaks, or with longer pulse durations and higher FAs for a smaller transmit bandwidth. Moreover, despite large inter-volunteer variations, broadband UP can be used for calibration-free 3D heart FA homogenization in time-critical situations.

The effect of fat model variation on muscle fat fraction quantification in a cross-sectional cohort

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.

Feasibility of identifying proliferative active bone marrow with fat fraction MRI and multi-energy CT

Objective.Active bone marrow (ABM) can serve as both an organ at risk and a target in external beam radiotherapy.18F-fluorothymidine (FLT) PET is the current gold standard for identifying proliferative ABM but it is not approved for human use, and PET scanners are not always available to radiotherapy clinics. Identifying ABM through other, more accessible imaging modalities will allow more patients to receive treatment specific to their ABM distribution. Multi-energy CT (MECT) and fat-fraction MRI (FFMRI) show promise in their ability to characterize bone marrow adiposity, but these methods require validation for identifying proliferative ABM.Approach.Six swine subjects were imaged using FFMRI, fast-kVp switching (FKS) MECT and sequential-scanning (SS) MECT to identify ABM volumes relative to FLT PET-derived ABM volumes. ABM was contoured on FLT PET images as the region within the bone marrow with a SUV above the mean. Bone marrow was then contoured on the FFMRI and MECT images, and thresholds were applied within these contours to determine which threshold produced the best agreement with the FLT PET determined ABM contour. Agreement between contours was measured using the Dice similarity coefficient (DSC).Main results.FFMRI produced the best estimate of the PET ABM contour. Compared to FLT PET ABM volumes, the FFMRI, SS MECT and FKS MECT ABM contours produced average peak DSC of 0.722 ± 0.080, 0.619 ± 0.070, and 0.464 ± 0.080, respectively. The ABM volume was overestimated by 40.51%, 97.63%, and 140.13% by FFMRI, SS MECT and FKS MECT, respectively.Significance.This study explored the ability of FFMRI and MECT to identify the proliferative relative to ABM defined by FLT PET. Of the methods investigated, FFMRI emerged as the most accurate approximation to FLT PET-derived active marrow contour, demonstrating superior performance by both DSC and volume comparison metrics. Both FFMRI and SS MECT show promise for providing patient-specific ABM treatments.

Accurate actual flip angle imaging (AFI) in the presence of fat

PURPOSE

To investigate the effect of incomplete fat spoiling on the accuracy of B1 mapping with actual flip angle imaging (AFI) and to propose a method to minimize the errors using the chemical shift properties of fat.

THEORY AND METHODS

Diffusion-based dephasing is the main spoiling mechanism exploited in AFI. However, a very low diffusion in fat may make the spoiling insufficient, leading to ghosts in the B1 maps. As the errors retain the chemical-shift signature of fat, their impact can be minimized using chemical-shift-based fat signal removal from AFI acquisition modified to include multi-echo readout. The source of the errors and the proposed correction were studied in simulations and phantom and in-vivo imaging experiments.

RESULTS

Our results support that AFI artifacts are caused by the incomplete fat spoiling present in clinically attractive short TR acquisition regimes. The correction eliminated the ghosting and significantly improved the B1 mapping accuracy as well as the accuracy of R1 mapping performed with AFI-derived B1 maps.

CONCLUSIONS

The incomplete fat signal spoiling may be a source of AFI B1 mapping errors, especially in subjects with high fat content. Achieving complete fat spoiling requires longer TR, which is undesirable in clinical applications. The proposed approach based on fat signal removal can reduce errors without significant prolongation of the AFI pulse sequence. We propose that, when attaining complete fat spoiling is not feasible, AFI mapping should be performed in a multi-echo regime with appropriate fat separation or suppression to minimize these errors.

MRI-based Deep Learning Models for Preoperative Breast Volume and Density Assessment Assisting Breast Reconstruction

BACKGROUND

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.

MATERIAL AND METHODS

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.

RESULTS

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.

CONCLUSION

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.

NO LEVEL ASSIGNED

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Effects of cortisol administration on heart rate variability and functional connectivity across women with different depression histories

Abnormalities within the hypothalamic-pituitary-adrenal (HPA) axis and autonomic nervous system have been implicated in depression. Studies have reported glucocorticoid insensitivity and reduced heart rate variability (HRV) in depressive disorders. However, little is known about the effects of cortisol on HRV and resting-state functional connectivity (rsFC) of the central autonomic network (CAN) in depression. We collected resting-state fMRI and cardiac data for women with different depression histories (n = 61) after administration of cortisol and placebo using a double-blind crossover design. We computed rsFC for R-amygdala and L-amygdala seeds and assessed the change in HRV after cortisol (cortisol-placebo). Analyses examined the effects of acute cortisol administration on HRV and rsFC of the R-amygdala and L-amygdala. There was a significant interaction between HRV and treatment for rsFC between the amygdala and CAN regions. We found lower rsFC between the L-amygdala and putamen for those with a greater decrease in HRV after cortisol. There was also reduced rsFC between the R-amygdala and dorsomedial prefrontal cortex, putamen, middle cingulate cortex, insula, and cerebellum in those with lower HRV after cortisol. These results remained significant after adjusting for depression symptoms, age, and race. Our findings suggest that the effect of cortisol on CAN connectivity is related to its effects on HRV. Overall, these results could inform transdiagnostic interventions targeting HRV and the stress response systems across clinical and non-clinical populations.

Relating pre-treatment non-Gaussian intravoxel incoherent motion diffusion-weighted imaging to human papillomavirus status and response in oropharyngeal carcinoma

Background and purpose

Diffusion-weighted imaging (DWI) is a promising technique for response assessment in head-and-neck cancer. Recently, we optimized Non-Gaussian Intravoxel Incoherent Motion Imaging (NG-IVIM), an extension of the conventional apparent diffusion coefficient (ADC) model, for the head and neck. In the current study, we describe the first application in a group of patients with human papillomavirus (HPV)-positive and HPV-negative oropharyngeal squamous cell carcinoma. The aim of this study was to relate ADC and NG-IVIM DWI parameters to HPV status and clinical treatment response.

Materials and methods

Thirty-six patients (18 HPV-positive, 18 HPV-negative) were prospectively included. Presence of progressive disease was scored within one year. The mean pre-treatment ADC and NG-IVIM parameters in the gross tumor volume were compared between HPV-positive and HPV-negative patients. In HPV-negative patients, ADC and NG-IVIM parameters were compared between patients with and without progressive disease.

Results

ADC, the NG-IVIM diffusion coefficient D, and perfusion fraction f were significantly higher, while pseudo-diffusion coefficient D* and kurtosis K were significantly lower in the HPV-negative compared to HPV-positive patients. In the HPV-negative group, a significantly lower D was found for patients with progressive disease compared to complete responders. No relation with ADC was observed.

Conclusion

The results of our single-center study suggest that ADC is related to HPV status, but not an independent response predictor. The NG-IVIM parameter D, however, was independently associated to response in the HPV-negative group. Noteworthy in the opposite direction as previously thought based on ADC.

Diffusion tensor imaging combined with chemical shift-encoded sequence to quantify the adaptive changes of calf muscles in amateur marathoners

PURPOSE

Calf muscles play an important role in marathon race, and the incidence of injury is high in this process. This study prospectively quantified diffusion tensor metrics, muscle fat fraction (MFF) and cross-sectional area (CSA) of calf muscles induced by endurance exercise in amateur marathoners, and the potential mechanisms underlying the changes in these parameters were analyzed.

METHOD

In this prospective study, 35 marathoners (27 males, 8 females; mean age (standard deviation, SD), 38.92 (4.83) years) and 26 controls (18 males, 8 females; mean age (SD), 38.35 (6.75) years) underwent magnetic resonance imaging (MRI) from September 2022 to March 2023. The diffusion tensor eigenvalues (λ1, λ2, λ3), radial diffusivity (RD), fractional anisotropy (FA), MFF and CSA of calf muscles were compared between marathoners and controls. A binary logistic regression model with gender correction was performed analyze the relationship between marathon exercise and DTI parameters, CSA and MFF of calf muscles.

RESULTS

Interobserver agreement was good (κ = 0.71). The results of binary logistic regression model with gender correction showed that the regression coefficients of FA values in anterior group of calf (AC), soleus (SOL), medial gastrocnemius (MG) and lateral gastrocnemius (LG) were negative, and the odds ratios (OR) were 0.33, 0.45, 0.35, 0.05, respectively (P < 0.05). The OR of RD in SOL and λ2 in external group of calf (EC) were relatively higher, 3.74 and 3.26, respectively (P < 0.05). CSA was greater in SOL of marathoners, with an OR value of 1.00(P < 0.05). The MFF in AC and LG was lower in marathoners and OR of two indexes were -0.69 and -0.59, respectively (P < 0.05).

CONCLUSIONS

Diffusion tensor imaging (DTI) combined with chemical shift-encoded sequence can noninvasively detect and quantify the adaptive changes of calf muscle morphology, microstructure and tissue composition induced by long-term running training in amateur marathoners.

Evaluation of Neuromuscular Diseases and Complaints by Quantitative Muscle MRI

Background: Quantitative muscle MRI (qMRI) is a promising tool for evaluating and monitoring neuromuscular disorders (NMD). However, the application of different imaging protocols and processing pipelines restricts comparison between patient cohorts and disorders. In this qMRI study, we aim to compare dystrophic (limb-girdle muscular dystrophy), inflammatory (inclusion body myositis), and metabolic myopathy (Pompe disease) as well as patients with post-COVID-19 conditions suffering from myalgia to healthy controls. Methods: Ten subjects of each group underwent a 3T lower extremity muscle MRI, including a multi-echo, gradient-echo, Dixon-based sequence, a multi-echo, spin-echo (MESE) T2 mapping sequence, and a spin-echo EPI diffusion-weighted sequence. Furthermore, the following clinical assessments were performed: Quick Motor Function Measure, patient questionnaires for daily life activities, and 6-min walking distance. Results: Different involvement patterns of conspicuous qMRI parameters for different NMDs were observed. qMRI metrics correlated significantly with clinical assessments. Conclusions: qMRI metrics are suitable for evaluating patients with NMD since they show differences in muscular involvement in different NMDs and correlate with clinical assessments. Still, standardisation of acquisition and processing is needed for broad clinical use.

The Amputated Limb Gluteus Medius is Biomechanically Disadvantaged in Patients with Unilateral Transfemoral Amputation

Patients with transfemoral amputation (TFA) are at an increased risk of secondary musculoskeleteal comorbidities, primarily due to asymmetric joint loading. Amputated limb muscle weakness is also prevalent in the TFA population, yet all factors that contribute to muscle strength and thus joint loading are not well understood. Our objective was to bilaterally compare gluteus medius (GMED) muscle factors (volume, fatty infiltration, moment arm) that all contribute to joint loading in patients with TFA. Quantitative magnetic resonance (MR) images of the hip were collected from eight participants with unilateral TFA (2M/6F; age: 47.3 ± 14.7 y/o; BMI: 25.4 ± 5.3 kg/m2; time since amputation: 20.6 ± 15.0 years) and used to calculate normalized GMED muscle volume and fatty infiltration. Six participants participated in an instrumented gait analysis session that collected whole-body kinematics during overground walking. Subject-specific musculoskeletal models were used to calculate bilateral GMED (anterior, middle, posterior) moment arms and frontal plane hip joint angles across three gait cycles. Differences in volume, fatty infiltration, hip adduction-abduction angle, and peak moment arms were compared between limbs using paired Cohen's d effect sizes. Volume was smaller by 36.3 ± 18.8% (d = 1.7) and fatty infiltration was greater by 6.4 ± 7.8% (d = 0.8) in the amputated limb GMED compared to the intact limb. The amputated limb GMED abduction moment arms were smaller compared to the intact limb for both overground walking (anterior: d = 0.9; middle: d = 0.1.2) and during normal range of motion (anterior: d = 0.8; middle: d = 0.8) while bilateral hip adduction-abduction angles were similar during overground walking (d = 0.5). These results indicate that in patients with TFA, the amputated limb GMED is biomechanically disadvantaged compared to the intact limb, which may contribute to the etiology of secondary comorbidities. This population might benefit from movement retraining to lengthen the amputated limb GMED abduction moment arm during gait.

Kidney R2* Mapping for Noninvasive Evaluation of Iron Overload in Paroxysmal Nocturnal Hemoglobinuria

PURPOSE

The kidney iron deposition can cause kidney damage and renal insufficiency in paroxysmal nocturnal hemoglobinuria (PNH) patients. Assessment of iron deposition in the kidney is essential for the early diagnosis of renal damage in PNH patients. The purpose of this study was to evaluate kidney R2* (T2* reciprocals) values in PNH patients using the iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL-IQ).

METHODS

Two radiologists measured the R2* values of the renal cortex in 14 PNH patients and 13 healthy volunteers using IDEAL-IQ. Lactate dehydrogenase (LDH), a reliable marker of intravascular hemolysis, was also measured in all participants.

RESULTS

The kidney R2* values were significantly higher in PNH patients compared with those in healthy volunteers (P < 0.001). High inter-operator reproducibility of the measurements was also acquired using IDEAL-IQ. LDH levels were also significantly higher in PNH patients compared with those in healthy volunteers (P < 0.001). Kidney R2* values strongly correlated with LDH levels in PNH patients.

CONCLUSION

IDEAL-IQ has a possibility of becoming a useful method for the noninvasive evaluation of renal iron overload in PNH patients.

Multi-echo-based fat artifact correction for CEST MRI at 7 T

PURPOSE

CEST MRI is influenced by fat signal, which can reduce the apparent CEST contrast or lead to pseudo-CEST effects. Our goal was to develop a fat artifact correction based on multi-echo fat-water separation that functions stably for 7 T knee MRI data.

METHODS

Our proposed algorithm utilizes the full complex data and a phase demodulation with an off-resonance map estimation based on the Z-spectra prior to fat-water separation to achieve stable fat artifact correction. Our method was validated and compared to multi-echo-based methods originally proposed for 3 T by Bloch-McConnell simulations and phantom measurements. Moreover, the method was applied to in vivo 7 T knee MRI examinations and compared to Gaussian fat saturation and a published single-echo Z-spectrum-based fat artifact correction method.

RESULTS

Phase demodulation prior to fat-water separation reduced the occurrence of fat-water swaps. Utilizing the complex signal data led to more stable correction results than working with magnitude data, as was proposed for 3 T. Our approach reduced pseudo-nuclear Overhauser effects compared to the other correction methods. Thus, the mean asymmetry contrast at 3.5 ppm in cartilage over five volunteers increased from -9.2% (uncorrected) and -10.6% (Z-spectrum-based) to -1.5%. Results showed higher spatial stability than with the fat saturation pulse.

CONCLUSION

Our work demonstrates the feasibility of multi-echo-based fat-water separation with an adaptive fat model for fat artifact correction for CEST MRI at 7 T. Our approach provided better fat artifact correction throughout the entire spectrum and image than the fat saturation pulse or Z-spectrum-based correction method for both phantom and knee imaging results.

Pathophysiological Mechanisms and Clinical Associations of Non-Alcoholic Fatty Pancreas Disease

Non-Alcoholic Fatty Pancreas disease (NAFPD), characterized by fat accumulation in pancreatic tissue, is an emerging clinical entity. However, the clinical associations, the underlying molecular drivers, and the pathophysiological mechanisms of NAFPD have not yet been characterized in detail. The NAFPD spectrum not only includes infiltration and accumulation of fat within and between pancreatic cells but also involves several inflammatory processes, dysregulation of physiological metabolic pathways, and hormonal defects. A deeper understanding of the underlying molecular mechanisms is key to correlate NAFPD with clinical entities including non-alcoholic fatty liver disease, metabolic syndrome, diabetes mellitus, atherosclerosis, as well as pancreatic cancer and pancreatitis. The aim of this review is to examine the pathophysiological mechanisms of NAFPD and to assess the possible causative/predictive risk factors of NAFPD-related clinical syndromes.

Advanced Hyperpolarized 13C Metabolic Imaging Protocol for Patients with Gliomas: A Comprehensive Multimodal MRI Approach

This study aimed to implement a multimodal 1H/HP-13C imaging protocol to augment the serial monitoring of patients with glioma, while simultaneously pursuing methods for improving the robustness of HP-13C metabolic data. A total of 100 1H/HP [1-13C]-pyruvate MR examinations (104 HP-13C datasets) were acquired from 42 patients according to the comprehensive multimodal glioma imaging protocol. Serial data coverage, accuracy of frequency reference, and acquisition delay were evaluated using a mixed-effects model to account for multiple exams per patient. Serial atlas-based HP-13C MRI demonstrated consistency in volumetric coverage measured by inter-exam dice coefficients (0.977 ± 0.008, mean ± SD; four patients/11 exams). The atlas-derived prescription provided significantly improved data quality compared to manually prescribed acquisitions (n = 26/78; p = 0.04). The water-based method for referencing [1-13C]-pyruvate center frequency significantly reduced off-resonance excitation relative to the coil-embedded [13C]-urea phantom (4.1 ± 3.7 Hz vs. 9.9 ± 10.7 Hz; p = 0.0007). Significantly improved capture of tracer inflow was achieved with the 2-s versus 5-s HP-13C MRI acquisition delay (p = 0.007). This study demonstrated the implementation of a comprehensive multimodal 1H/HP-13C MR protocol emphasizing the monitoring of steady-state/dynamic metabolism in patients with glioma.

Changes in lumbar muscle diffusion tensor indices with age

Objective

To investigate differences in diffusion tensor imaging (DTI) parameters and proton density fat fraction (PDFF) in the spinal muscles of younger and older adult males.

Methods

Twelve younger (19-30 years) and 12 older (61-81years) healthy, physically active male participants underwent T1W, T2W, Dixon and DTI of the lumbar spine. The eigenvalues (λ1, λ2, and λ3), fractional anisotropy (FA), and mean diffusivity (MD) from the DTI together with the PDFF were determined in the multifidus, medial and lateral erector spinae (ESmed, ESlat), and quadratus lumborum (QL) muscles. A two-way ANOVA was used to investigate differences with age and muscle and t-tests for differences in individual muscles with age.

Results

The ANOVA gave significant differences with age for all DTI parameters and the PDFF (P < .01) and with muscle (P < .01) for all DTI parameters except for λ1 and for the PDFF. The mean of the eigenvalues and MD were lower and the FA higher in the older age group with differences reaching statistical significance for all DTI measures for ESlat and QL (P < .01) but only in ESmed for λ3 and MD (P < .05).

Conclusions

Differences in DTI parameters of muscle with age result from changes in both in the intra- and extra-cellular space and cannot be uniquely explained in terms of fibre length and diameter.

Advances in knowledge

Previous studies looking at age have used small groups with uneven age spacing. Our study uses two well defined and separated age groups.

Quantitative muscle MRI in sporadic inclusion body myositis (sIBM): A prospective cohort study

Background

Sporadic inclusion body myositis (sIBM) is the predominant idiopathic inflammatory myopathy (IIM) in older people. Limitations of classical clinical assessments have been discussed as possible explanations for failed clinical trials, underlining the need for more sensitive outcome measures. Quantitative muscle MRI (qMRI) is a promising candidate for evaluating and monitoring sIBM.

Objective

Longitudinal assessment of qMRI in sIBM patients.

Methods

We evaluated fifteen lower extremity muscles of 12 sIBM patients (5 females, mean age 69.6, BMI 27.8) and 12 healthy age- and gender-matched controls. Seven patients and matched controls underwent a follow-up evaluation after one year. Clinical assessment included testing for muscle strength with Quick Motor Function Measure (QMFM), IBM functional rating scale (IBM-FRS), and gait analysis (6-minute walking distance). 3T-MRI scans of the lower extremities were performed, including a Dixon-based sequence, T2 mapping and Diffusion Tensor Imaging. The qMRI-values fat-fraction (FF), water T2 relaxation time (wT2), fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (λ1), and radial diffusivity (RD) were analysed.

Results

Compared to healthy controls, significant differences for all qMRI parameters averaged over all muscles were found in sIBM using a MANOVA (p < 0.001). In low-fat muscles (FF < 10%), a significant increase of wT2 and FA with an accompanying decrease of MD, λ1, and RD was observed (p≤0.020). The highest correlation with clinical assessments was found for wT2 values in thigh muscles (r≤-0.634). Significant changes of FF (+3.0%), wT2 (+0.6 ms), MD (-0.04 10-3mm2/s), λ1 (-0.05 10-3mm2/s), and RD (-0.03 10-3mm2/s) were observed in the longitudinal evaluation of sIBM patients (p≤0.001). FA showed no significant change (p = 0.242).

Conclusion

qMRI metrics correlate with clinical findings and can reflect different ongoing pathophysiological mechanisms. While wT2 is an emerging marker of disease activity, the role of diffusion metrics, possibly reflecting changes in fibre size and intracellular deposits, remains subject to further investigations.

Quo Vadis Hyperpolarized 13C MRI?

Over the last two decades, hyperpolarized 13C MRI has gained significance in both preclinical and clinical studies, hereby relying on technologies like PHIP-SAH (ParaHydrogen-Induced Polarization-Side Arm Hydrogenation), SABRE (Signal Amplification by Reversible Exchange), and dDNP (dissolution Dynamic Nuclear Polarization), with dDNP being applied in humans. A clinical dDNP polarizer has enabled studies across 24 sites, despite challenges like high cost and slow polarization. Parahydrogen-based techniques like SABRE and PHIP offer faster, more cost-efficient alternatives but require molecule-specific optimization. The focus has been on imaging metabolism of hyperpolarized probes, which requires long T1, high polarization and rapid contrast generation. Efforts to establish novel probes, improve acquisition techniques and enhance data analysis methods including artificial intelligence are ongoing. Potential clinical value of hyperpolarized 13C MRI was demonstrated primarily for treatment response assessment in oncology, but also in cardiology, nephrology, hepatology and CNS characterization. In this review on biomedical hyperpolarized 13C MRI, we summarize important and recent advances in polarization techniques, probe development, acquisition and analysis methods as well as clinical trials. Starting from those we try to sketch a trajectory where the field of biomedical hyperpolarized 13C MRI might go.

Muscle diffusion MRI reveals autophagic buildup in a mouse model for Pompe disease

Quantitative muscle MRI is increasingly important in the non-invasive evaluation of neuromuscular disorders and their progression. Underlying histopathotological alterations, leading to changes in qMRI parameters are incompletely unraveled. Early microstructural differences of unknown origin reflected by Diffusion MRI in non-fat infiltrated muscles were detected in Pompe patients. This study employed a longitudinal approach with a Pompe disease mouse model to investigate the histopathological basis of these changes. Monthly scans of Pompe (Gaa6neo/6neo) and wildtype mice (age 1-8 months) were conducted using diffusion MRI, T2-mapping, and Dixon-based water-fat imaging on a 7 T scanner. Immunofluorescence studies on quadriceps muscles were analyzed for lysosomal accumulations and autophagic buildup and correlated with MRI outcome measures. Fat fraction and water-T2 did not differ between groups and remained stable over time. In Pompe mice, fractional anisotropy increased, while mean diffusivity (MD) and radial diffusivity (RD) decreased in all observed muscles. Autophagic marker and muscle fibre diameter revealed significant negative correlations with reduced RD and MD, while lysosomal marker did not show any change or correlation. Using qMRI, we showed diffusion changes in muscles of presymptomatic Pompe mice without fat-infiltrated muscles and correlated them to autophagic markers and fibre diameter, indicating diffusion MRI reveals autophagic buildup.

High-sensitivity deuterium metabolic MRI differentiates acute pancreatitis from pancreatic cancers in murine models

Deuterium metabolic imaging (DMI) is a promising tool for investigating a tumor's biology, and eventually contribute in cancer diagnosis and prognosis. In DMI, [6,6'-2H2]-glucose is taken up and metabolized by different tissues, resulting in the formation of HDO but also in an enhanced formation of [3,3'-2H2]-lactate at the tumor site as a result of the Warburg effect. Recent studies have shown DMI's suitability to highlight pancreatic cancer in murine models by [3,3'-2H2]-lactate formation; an important question is whether DMI can also differentiate between these tumors and pancreatitis. This differentiation is critical, as these two diseases are hard to distinguish today radiologically, but have very different prognoses requiring distinctive treatments. Recent studies have shown the limitations that hyperpolarized MRI faces when trying to distinguish these pancreatic diseases by monitoring the [1-13C1]-pyruvate→[1-13C1]-lactate conversion. In this work, we explore DMI's capability to achieve such differentiation. Initial tests used a multi-echo (ME) SSFP sequence, to identify any metabolic differences between tumor and acute pancreatitis models that had been previously elicited very similar [1-13C1]-pyruvate→[1-13C1]-lactate conversion rates. Although ME-SSFP provides approximately 5 times greater signal-to-noise ratio (SNR) than the standard chemical shift imaging (CSI) experiment used in DMI, no lactate signal was observed in the pancreatitis model. To enhance lactate sensitivity further, we developed a new, weighted-average, CSI-SSFP approach for DMI. Weighted-average CSI-SSFP improved DMI's SNR by another factor of 4 over ME-SSFP-a sensitivity enhancement that sufficed to evidence natural abundance 2H fat in abdominal images, something that had escaped the previous approaches even at ultrahigh (15.2 T) MRI fields. Despite these efforts to enhance DMI's sensitivity, no lactate signal could be detected in acute pancreatitis models (n = 10; [3,3'-2H2]-lactate limit of detection < 100 µM; 15.2 T). This leads to the conclusion that pancreatic tumors and acute pancreatitis may be clearly distinguished by DMI, based on their different abilities to generate deuterated lactate.

An experimental study for quantitative assessment of fatty infiltration and blood flow perfusion in quadriceps muscle of rats using IDEAL-IQ and BOLD-MRI for early diagnosis of sarcopenia

BACKGROUND

Severe sarcopenia may result in severe disability. Early diagnosis is currently the key to enhancing the treatment of sarcopenia, and there is an urgent need for a highly sensitive and dependable tool to evaluate the course of early sarcopenia in clinical practice. This study aims to investigate longitudinally the early diagnosability of magnetic resonance imaging (MRI)-based fat infiltration and blood flow perfusion technology in sarcopenia progression.

METHODS

48 Sprague-Dawley rats were randomly assigned into six groups that were based on different periods of dexamethasone (DEX) injection (0, 2, 4, 6, 8, 10 days). Multimodal MRI was scanned to assess muscle mass. Grip strength and swimming exhaustion time of rats were measured to assess muscle strength and function. Immunofluorescence staining for CD31 was employed to assess skeletal muscle capillary formation, and western blot was used to detect vascular endothelial growth factor-A (VEGF-A) and muscle ring finger-1 (MuRF-1) protein expression. Subsequently, we analyzed the correlation between imaging and histopathologic parameters. A receiver operating characteristic (ROC) analysis was conducted to assess the effectiveness of quantitative MRI parameters for discriminating diagnosis in both pre- and post-modeling of DEX-induced sarcopenic rats.

RESULTS

Significant differences were found in PDFF, R2* and T2 values on day 2 of DEX-induction compared to the control group, occurring prior to the MRI-CSA values and limb grip strength on day 6 of induction and swimming exhaustion time on day 8 of induction. There is a strong correlation between MRI-CSA with HE-CSA values (r = 0.67; p < 0.001), oil red O (ORO) area with PDFF (r = 0.67; p < 0.001), microvascular density (MVD) (r = -0.79; p < 0.001) and VEGF-A (r = -0.73; p < 0.001) with R2*, MuRF-1 with MRI-CSA (r = -0.82; p < 0.001). The AUC of PDFF, R2*, and T2 values used for modeling evaluation are 0.81, 0.93, and 0.98, respectively.

CONCLUSION

Imaging parameters PDFF, R2*, and T2 can be used to sensitively evaluate early pathological changes in sarcopenia. The successful construction of a sarcopenia rat model can be assessed when PDFF exceeds 1.25, R2* exceeds 53.85, and T2 exceeds 33.88.

Deep Learning for Inference of Hepatic Proton Density Fat Fraction From T1-Weighted In-Phase and Opposed-Phase MRI: Retrospective Analysis of Population-Based Trial Data

BACKGROUND. The confounder-corrected chemical shift-encoded MRI (CSE-MRI) sequence used to determine proton density fat fraction (PDFF) for hepatic fat quantification is not widely available. As an alternative, hepatic fat can be assessed by a two-point Dixon method to calculate signal fat fraction (FF) from conventional T1-weighted in- and opposed-phase (IOP) images, although signal FF is prone to biases, leading to inaccurate quantification. OBJECTIVE. The purpose of this study was to compare hepatic fat quantification by use of PDFF inferred from conventional T1-weighted IOP images and deep-learning convolutional neural networks (CNNs) with quantification by use of two-point Dixon signal FF with CSE-MRI PDFF as the reference standard. METHODS. This study entailed retrospective analysis of data from 292 participants (203 women, 89 men; mean age, 53.7 ± 12.0 [SD] years) enrolled at two sites from September 1, 2017, to December 18, 2019, in the Strong Heart Family Study (a prospective population-based study of American Indian communities). Participants underwent liver MRI (site A, 3 T; site B, 1.5 T) including T1-weighted IOP MRI and CSE-MRI (used to reconstruct CSE PDFF and CSE R2* maps). With CSE PDFF as reference, a CNN was trained in a random sample of 218 (75%) participants to infer voxel-by-voxel PDFF maps from T1-weighted IOP images; testing was performed in the other 74 (25%) participants. Parametric values from the entire liver were automatically extracted. Per-participant median CNN-inferred PDFF and median two-point Dixon signal FF were compared with reference median CSE-MRI PDFF by means of linear regression analysis, intraclass correlation coefficient (ICC), and Bland-Altman analysis. The code is publicly available at github.com/kang927/CNN-inference-of-PDFF-from-T1w-IOP-MR. RESULTS. In the 74 test-set participants, reference CSE PDFF ranged from 1% to 32% (mean, 11.3% ± 8.3% [SD]); reference CSE R2* ranged from 31 to 457 seconds-1 (mean, 62.4 ± 67.3 seconds-1 [SD]). Agreement metrics with reference to CSE PDFF for CNN-inferred PDFF were ICC = 0.99, bias = -0.19%, 95% limits of agreement (LoA) = (-2.80%, 2.71%) and for two-point Dixon signal FF were ICC = 0.93, bias = -1.11%, LoA = (-7.54%, 5.33%). CONCLUSION. Agreement with reference CSE PDFF was better for CNN-inferred PDFF from conventional T1-weighted IOP images than for two-point Dixon signal FF. Further investigation is needed in individuals with moderate-to-severe iron overload. CLINICAL IMPACT. Measurement of CNN-inferred PDFF from widely available T1-weighted IOP images may facilitate adoption of hepatic PDFF as a quantitative bio-marker for liver fat assessment, expanding opportunities to screen for hepatic steatosis and nonalcoholic fatty liver disease.

Deuterium imaging of the Warburg effect at sub-millimolar concentrations by joint processing of the kinetic and spectral dimensions

Deuterium metabolic imaging (DMI) is a promising molecular MRI approach, which follows the administration of deuterated substrates and their metabolization. [6,6'-2 H2 ]-glucose for instance is preferentially converted in tumors to [3,3'-2 H2 ]-lactate as a result of the Warburg effect, providing a distinct resonance whose mapping using time-resolved spectroscopic imaging can diagnose cancer. The MR detection of low-concentration metabolites such as lactate, however, is challenging. It has been recently shown that multi-echo balanced steady-state free precession (ME-bSSFP) increases the signal-to-noise ratio (SNR) of these experiments approximately threefold over regular chemical shift imaging; the present study examines how DMI's sensitivity can be increased further by advanced processing methods. Some of these, such as compressed sensing multiplicative denoising and block-matching/3D filtering, can be applied to any spectroscopic/imaging methods. Sensitivity-enhancing approaches were also specifically tailored to ME-bSSFP DMI, by relying on priors related to the resonances' positions and to features of the metabolic kinetics. Two new methods are thus proposed that use these constraints for enhancing the sensitivity of both the spectral images and the metabolic kinetics. The ability of these methods to improve DMI is evidenced in pancreatic cancer studies carried at 15.2 T, where suitable implementations of the proposals imparted eightfold or more SNR improvement over the original ME-bSSFP data, at no informational cost. Comparisons with other propositions in the literature are briefly discussed.

Fat distribution measurements by chemical shift-encoded transition region extraction predict the risk of hyperglycaemia, dyslipidaemia and metabolic syndrome in mice

Metabolically healthy or unhealthy obesity is closely related to metabolic syndrome (MetS). To validate a more accurate diagnostic method for obesity that reflects the risk of metabolic disorders in a pre-clinical mouse model, C57BL/6J mice were fed high-sucrose-high-fat and chow diets for 12 weeks to induce obesity. MRI was performed and analysed by chemical shift-encoded fat-water separation based on the transition region extraction method. Abdominal fat was divided into upper and lower abdominal regions at the horizontal lower border of the liver. Blood samples were collected, and the glucose level, lipid profile, liver function, HbA1c and insulin were tested. k-means clustering and stepwise logistic regression were applied to validate the diagnosis of hyperglycaemia, dyslipidaemia and MetS, and to ascertain the predictive effect of MRI-derived parameters to the metabolic disorders. Pearson or Spearman correlation was used to assess the relationship between MRI-derived parameters and metabolic traits. The receiver-operating characteristic curve was used to evaluate the diagnostic effect of each logistic regression model. A two-sided p value less than 0.05 was considered to indicate statistical significance for all tests. We made the precise diagnosis of obesity, dyslipidaemia, hyperglycaemia and MetS in mice. In all, 14 mice could be diagnosed as having MetS, and the levels of body weight, HbA1c, triglyceride, total cholesterol and low-density lipoprotein cholesterol were significantly higher than in the normal group. Upper abdominal fat better predicted dyslipidaemia (odds ratio, OR = 2.673; area under the receiver-operating characteristic curve, AUCROC  = 0.9153) and hyperglycaemia (OR = 2.456; AUCROC  = 0.9454), and the abdominal visceral adipose tissue (VAT) was better for predicting MetS risk (OR = 1.187; AUCROC  = 0.9619). We identified the predictive effect of fat volume and distribution in dyslipidaemia, hyperglycaemia and MetS. The upper abdominal fat played a better predictive role for the risk of dyslipidaemia and hyperglycaemia, and the abdominal VAT played a better predictive role for the risk of MetS.

Hepatic MR imaging using IDEAL-IQ sequence: Will Gd-EOB-DTPA interfere with reproductivity of fat fraction quantification?

BACKGROUND

Iterative decomposition of water and fat with echo asymmetry and least squares estimation quantification sequence (IDEAL-IQ) is based on chemical shift-based water and fat separation technique to get proton density fat fraction. Multiple studies have shown that using IDEAL-IQ to test the stability and repeatability of liver fat is acceptable and has high accuracy.

AIM

To explore whether Gadoxetate Disodium (Gd-EOB-DTPA) interferes with the measurement of the hepatic fat content quantified with the IDEAL-IQ and to evaluate the robustness of this technique.

METHODS

IDEAL-IQ was used to quantify the liver fat content at 3.0T in 65 patients injected with Gd-EOB-DTPA contrast. After injection, IDEAL-IQ was estimated four times, and the fat fraction (FF) and R2* were measured at the following time points: Pre-contrast, between the portal phase (70 s) and the late phase (180 s), the delayed phase (5 min) and the hepatobiliary phase (20 min). One-way repeated-measures analysis was conducted to evaluate the difference in the FFs between the four time points. Bland-Altman plots were adopted to assess the FF changes before and after injection of the contrast agent. P < 0.05 was considered statistically significant.

RESULTS

The assessment of the FF at the four time points in the liver, spleen and spine showed no significant differences, and the measurements of hepatic FF yielded good consistency between T1 and T2 [95% confidence interval: -0.6768%, 0.6658%], T1 and T3 (-0.3900%, 0.3178%), and T1 and T4 (-0.3750%, 0.2825%). R2* of the liver, spleen and spine increased significantly after injection (P < 0.0001).

CONCLUSION

Using the IDEAL-IQ sequence to measure the FF, we can obtain results that will not be affected by Gd-EOB-DTPA. The high reproducibility of the IDEAL-IQ sequence makes it available in the scanning interval to save time during multiphase examinations.

Assessment of MRF for simultaneous T1 and T2 quantification and water-fat separation in the liver at 0.55 T

OBJECTIVE

The goal of this work was to assess the feasibility of performing MRF in the liver on a 0.55 T scanner and to examine the feasibility of water-fat separation using rosette MRF at 0.55 T.

MATERIALS AND METHODS

Spiral and rosette MRF sequences were implemented on a commercial 0.55 T scanner. The accuracy of both sequences in T1 and T2 quantification was validated in the ISMRM/NIST system phantom. The efficacy of rosette MRF in water-fat separation was evaluated in simulations and water/oil phantoms. Both spiral and rosette MRF were performed in the liver of healthy subjects.

RESULTS

In the ISMRM/NIST phantom, both spiral and rosette MRF achieved good agreement with reference values in T1 and T2 measurements. In addition, rosette MRF enables water-fat separation and can generate water- and fat- specific T1 maps, T2 maps, and proton density images from the same dataset for a spatial resolution of 1.56 × 1.56 × 5mm3 within the acquisition time of 15 s.

CONCLUSION

It is feasible to measure T1 and T2 simultaneously in the liver using MRF on a 0.55 T system with lower performance gradients compared to state-of-the-art 1.5 T and 3 T systems within an acquisition time of 15 s. In addition, rosette MRF enables water-fat separation along with T1 and T2 quantification with no time penalty.

Emerging concepts in the detection of liver fibrosis in non-alcoholic fatty liver disease

INTRODUCTION

The non-invasive identification of liver fibrosis related to Non-Alcoholic Fatty Liver Disease is crucial for risk-stratification of patients. Currently, the reference standard to stage hepatic fibrosis relies on liver biopsy, but multiple approaches are developed to allow for non-invasive diagnosis and risk stratification. Non-invasive tests, including blood-based scores and vibration-controlled transient elastography, have been widely validated and represent a good surrogate for risk stratification according to recent European and American guidelines.

AREAS COVERED

Novel approaches are based on 'liquid' biomarkers of liver fibrogenesis, including collagen-derived markers (PRO-C3 or PRO-C6), or 'multi-omics' technologies (e.g. proteomic-based molecules or miRNA testing), bearing the advantage of tailoring the intrahepatic disease activity. Alternative approaches are based on 'dry' biomarkers, including magnetic resonance-based tools (including proton density fat fraction, magnetic resonance elastography, or corrected T1), which reach similar accuracy of liver histology and will potentially help identify the best candidates for pharmacological treatment of fibrosing non-alcoholic steatohepatitis.

EXPERT OPINION

In the near future, the sequential use of non-invasive tests, as well as the complimentary use of liquid and dry biomarkers according to the clinical need (diagnosis, risk stratification, and prognosis, or treatment response) will guide and improve the management of this liver disease.

Associations between vertebral bone marrow fat and sagittal spine alignment as assessed by chemical shift-encoding-based water-fat MRI

BACKGROUND

The relationship between sagittal spine alignment and vertebral bone marrow fat is unknown. We aimed to assess the relationship between vertebral bone marrow fat and sagittal spine alignment using chemical shift-encoding-based water-fat magnetic resonance imaging (MRI).

METHODS

A total of 181 asymptomatic volunteers were recruited for whole spine X-ray and lumbar MRI. Spine typing was performed according to the Roussouly classification and measurement of vertebral fat fraction based on the chemical shift-encoding-based water-fat MRI. One-way analysis of variance (ANOVA) was used to analyze the differences in vertebral fat fraction between spine types. The post hoc least significant difference (LSD) test was utilized for subgroup comparison after ANOVA.

RESULTS

Overall, the vertebral fat fraction increased from L1 to L5 and was the same for each spine type. The vertebral fat fraction was the highest in type 1 and lowest in type 4 at all levels. ANOVA revealed statistically significant differences in fat fraction among different spine types at L4 and L5 (P < .05). The post hoc LSD test showed that the fat fraction of L4 was significantly different (P < .05) between type 1 and type 4 as well as between type 2 and type 4. The fat fraction of L5 was significantly different between type 1 and type 3, between type 1 and type 4, and between type 2 and type 4 (P < .05).

CONCLUSION

Our study found that vertebral bone marrow fat is associated with sagittal spine alignment, which may serve as a new additional explanation for the association of sagittal alignment with spinal degeneration.

QSM Throughout the Body

Magnetic materials in tissue, such as iron, calcium, or collagen, can be studied using quantitative susceptibility mapping (QSM). To date, QSM has been overwhelmingly applied in the brain, but is increasingly utilized outside the brain. QSM relies on the effect of tissue magnetic susceptibility sources on the MR signal phase obtained with gradient echo sequence. However, in the body, the chemical shift of fat present within the region of interest contributes to the MR signal phase as well. Therefore, correcting for the chemical shift effect by means of water-fat separation is essential for body QSM. By employing techniques to compensate for cardiac and respiratory motion artifacts, body QSM has been applied to study liver iron and fibrosis, heart chamber blood and placenta oxygenation, myocardial hemorrhage, atherosclerotic plaque, cartilage, bone, prostate, breast calcification, and kidney stone.

CEST-MRI for body oncologic imaging: are we there yet?

Chemical exchange saturation transfer (CEST) MRI has gained recognition as a valuable addition to the molecular imaging and quantitative biomarker arsenal, especially for characterization of brain tumors. There is also increasing interest in the use of CEST-MRI for applications beyond the brain. However, its translation to body oncology applications lags behind those in neuro-oncology. The slower migration of CEST-MRI to non-neurologic applications reflects the technical challenges inherent to imaging of the torso. In this review, we discuss the application of CEST-MRI to oncologic conditions of the breast and torso (i.e., body imaging), emphasizing the challenges and potential solutions to address them. While data are still limited, reported studies suggest that CEST signal is associated with important histology markers such as tumor grade, receptor status, and proliferation index, some of which are often associated with prognosis and response to therapy. However, further technical development is still needed to make CEST a reliable clinical application for body imaging and establish its role as a predictive and prognostic biomarker.

Free-Breathing Liver Fat, R₂* and B₀ Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-Based Reconstruction

This work introduced a stack-of-radial multi-echo asymmetric-echo MRI sequence for free-breathing liver volumetric acquisition. Regularized model-based reconstruction was implemented in Berkeley Advanced Reconstruction Toolbox (BART) to jointly estimate all physical parameter maps (water, fat, R2∗ , and B0 field inhomogeneity maps) and coil sensitivity maps from self-gated k -space data. Specifically, locally low rank and temporal total variation regularization were employed directly on physical parameter maps. The proposed free-breathing radial technique was tested on a water/fat & iron phantom, a young volunteer, and obesity/diabetes/hepatic steatosis patients. Quantitative fat fraction and R2∗ accuracy were confirmed by comparing our technique with the reference breath-hold Cartesian scan. The multi-echo radial sampling sequence achieves fast k -space coverage and is robust to motion. Moreover, the proposed motion-resolved model-based reconstruction allows for free-breathing liver fat and R2∗ quantification in multiple motion states. Overall, our proposed technique offers a convenient tool for non-invasive liver assessment with no breath holding requirement.

Quantitative muscle magnetic resonance imaging depicts microstructural abnormalities but no signs of inflammation or dystrophy in post-COVID-19 condition

BACKGROUND AND PURPOSE

Post-COVID-19 condition (PCC) has high impact on quality of life, with myalgia and fatigue affecting at least 25% of PCC patients. This case-control study aims to noninvasively assess muscular alterations via quantitative muscle magnetic resonance imaging (MRI) as possible mechanisms for ongoing musculoskeletal complaints and premature exhaustion in PCC.

METHODS

Quantitative muscle MRI was performed on a 3 Tesla MRI scanner of the whole legs in PCC patients compared to age- and sex-matched healthy controls, including a Dixon sequence to determine muscle fat fraction (FF), a multi-echo spin-echo sequence for quantitative water mapping reflecting putative edema, and a diffusion-weighted spin-echo echo-planar imaging sequence to assess microstructural alterations. Clinical examination, nerve conduction studies, and serum creatine kinase were performed in all patients. Quantitative muscle MRI results were correlated to the results of the 6-min walk test and standardized questionnaires assessing quality of life, fatigue, and depression.

RESULTS

Twenty PCC patients (female: n = 15, age = 48.8 ± 10.1 years, symptoms duration = 13.4 ± 4.2 months, body mass index [BMI] = 28.8 ± 4.7 kg/m² ) were compared to 20 healthy controls (female: n = 15, age = 48.1 ± 11.1 years, BMI = 22.9 ± 2.2 kg/m² ). Neither FF nor T2 revealed signs of muscle degeneration or inflammation in either study groups. Diffusion tensor imaging (DTI) revealed reduced mean, axial, and radial diffusivity in the PCC group.

CONCLUSIONS

Quantitative muscle MRI did not depict any signs of ongoing inflammation or dystrophic process in the skeletal muscles in PCC patients. However, differences observed in muscle DTI depict microstructural abnormalities, which may reflect potentially reversible fiber hypotrophy due to deconditioning. Further longitudinal and interventional studies should prove this hypothesis.

Quantitative muscle MRI displays clinically relevant myostructural abnormalities in long-term ICU-survivors: a case-control study

BACKGROUND

Long-term data on ICU-survivors reveal persisting sequalae and a reduced quality-of-life even after years. Major complaints are neuromuscular dysfunction due to Intensive care unit acquired weakness (ICUAW). Quantitative MRI (qMRI) protocols can quantify muscle alterations in contrast to standard qualitative MRI-protocols.

METHODS

Using qMRI, the aim of this study was to analyse persisting myostructural abnormalities in former ICU patients compared to controls and relate them to clinical assessments. The study was conducted as a cohort/case-control study. Nine former ICU-patients and matched controls were recruited (7 males; 54.8y ± 16.9; controls: 54.3y ± 11.1). MRI scans were performed on a 3T-MRI including a mDTI, T2 mapping and a mDixonquant sequence. Water T2 times, fat-fraction and mean values of the eigenvalue (λ₁), mean diffusivity (MD), radial diffusivity (RD) and fractional anisotropy (FA) were obtained for six thigh and seven calf muscles bilaterally. Clinical assessment included strength testing, electrophysiologic studies and a questionnaire on quality-of-life (QoL). Study groups were compared using a multivariate general linear model. qMRI parameters were correlated to clinical assessments and QoL questionnaire using Pearson´s correlation.

RESULTS

qMRI parameters were significantly higher in the patients for fat-fraction (p < 0.001), water T2 time (p < 0.001), FA (p = 0.047), MD (p < 0.001) and RD (p < 0.001). Thighs and calves showed a different pattern with significantly higher water T2 times only in the calves. Correlation analysis showed a significant negative correlation of muscle strength (MRC sum score) with FA and T2-time. The results were related to impairment seen in QoL-questionnaires, clinical testing and electrophysiologic studies.

CONCLUSION

qMRI parameters show chronic next to active muscle degeneration in ICU survivors even years after ICU therapy with ongoing clinical relevance. Therefore, qMRI opens new doors to characterize and monitor muscle changes of patients with ICUAW. Further, better understanding on the underlying mechanisms of the persisting complaints could contribute the development of personalized rehabilitation programs.

MAGORINO: Magnitude-only fat fraction and R* 2 estimation with Rician noise modeling

PURPOSE

Magnitude-based fitting of chemical shift-encoded data enables proton density fat fraction (PDFF) and R 2 * $$ {R}_2^{\ast } $$ estimation where complex-based methods fail or when phase data are inaccessible or unreliable. However, traditional magnitude-based fitting algorithms do not account for Rician noise, creating a source of bias. To address these issues, we propose an algorithm for magnitude-only PDFF and R 2 * $$ {R}_2^{\ast } $$ estimation with Rician noise modeling (MAGORINO).

METHODS

Simulations of multi-echo gradient-echo signal intensities are used to investigate the performance and behavior of MAGORINO over the space of clinically plausible PDFF, R 2 * $$ {R}_2^{\ast } $$ , and SNR values. Fitting performance is assessed through detailed simulation, including likelihood function visualization, and in a multisite, multivendor, and multi-field-strength phantom data set and in vivo.

RESULTS

Simulations show that Rician noise-based magnitude fitting outperforms existing Gaussian noise-based fitting and reveals two key mechanisms underpinning the observed improvement. First, the likelihood functions exhibit two local optima; Rician noise modeling increases the chance that the global optimum corresponds to the ground truth. Second, when the global optimum corresponds to ground truth for both noise models, the optimum from Rician noise modeling is closer to ground truth. Multisite phantom experiments show good agreement of MAGORINO PDFF with reference values, and in vivo experiments replicate the performance benefits observed in simulation.

CONCLUSION

The MAGORINO algorithm reduces Rician noise-related bias in PDFF and R 2 * $$ {R}_2^{\ast } $$ estimation, thus addressing a key limitation of existing magnitude-only fitting methods. Our results offer insight into the importance of the noise model for selecting the correct optimum when multiple plausible optima exist.

Patterns of Vertebral Bone Marrow Edema in the Normal Healing Process of Lumbar Interbody Fusion: Baseline Data for Diagnosis of Pathological Events

STUDY DESIGN

Retrospective investigation using a prospectively collected database.

OBJECTIVE

To examine the appearance and characteristics of vertebral bone marrow edema (BME) in the normal healing of lumbar interbody fusion.

SUMMARY OF BACKGROUND DATA

Although BME in pathological spinal conditions has been well-documented, the patterns and characteristics of BME in the normal healing process of spinal fusion remains unexplored.

MATERIALS AND METHODS

We reviewed imaging from 225 patients with normal healing following posterior lumbar interbody fusion or transforaminal lumbar interbody fusion. BME was identified on magnetic resonance imaging at the third postoperative week and categorized with respect to its appearance, including assessment of area and extension within the relevant vertebrae.

RESULTS

Three hundred eighty-nine of the 450 instrumented vertebrae (86.4%) displayed evidence BME. All instances of BME were associated with the area of contact with the endplate. The average extent of BME was 32.7±1.0%. BME within normal healing following interbody fusion could be categorized into four types: no edema (13.6%), anterior corner (36.6%), around-the-cage focal (48.0%), and diffuse (1.8%). Anterior corner BME was significantly associated with instances of single cage placement than in dual cages (42.6% vs. 24.7%, P =0.0002). Single cages had a significantly higher rate of BME than dual cages (92.0% vs. 75.3%, P <0.0001). The extent of BME was significantly greater in the single cage cohort (36.9% vs. 24.2% in dual cages, P <0.0001).

CONCLUSIONS

This serves as the first study demonstrating the patterns of BME associated with normal healing following lumbar interbody fusion procedures. Anterior corner BME and around-the-cage focal BME were the most common patterns encountered, with diffuse BME a relatively rare pattern. These findings might contribute to the better differentiation of postoperative pathological events from normal healing following lumbar interbody fusion.

LEVEL OF EVIDENCE

4.

Relationship of liver fat content with systemic metabolism and chronic complications in patients with type 2 diabetes mellitus

OBJECTIVE

This study investigated the correlation of liver fat content (LFC) with metabolic characteristics and its association with chronic complications in type 2 diabetes mellitus (T2DM) patients.

METHODS

Eighty-one prospectively enrolled T2DM patients were divided into non-alcoholic fatty liver disease (NAFLD) group and the non-NAFLD group according to the presence of NAFL complications. LFC was determined by MRI IDEAL-IQ Sequence, and patients were divided into 4 groups according to LFC by quartile method. Basic information, metabolic indexes, and occurrence of chronic complications in different groups were analyzed and compared.

RESULTS

BMI, SBP, DBP, TG, ALT, AST, GGT, UA, HbA1c, FCP, 2 h CP, HOMA-IR, and HOMA-IS in the NAFLD group were significantly higher than the non-NAFLD group (P < 0.05). The incidences of chronic complications in the NAFLD group were higher than in the non-NAFLD group but not statistically significant (P > 0.05). BMI, SBP, DBP, TC, TG, ALT, AST, FCP, 2 h CP, HOMA-IR, and HOMA-IS showed significant differences between the patients with different LFC, and these indexes were significantly higher in patients with higher LFC than those with lower LFC (P < 0.05). Moreover, diabetes duration, TC, HOMA-IR, and LFC were the risk factors for ASCVD complications, while diabetes duration, TG, and LDL-C were risk factors for DN complications. Also, diabetes duration and SBP were risk factors for both DR and DPN complications in T2DM patients (P < 0.05).

CONCLUSION

LFC is positively correlated with the severity of the systemic metabolic disorder and chronic complications in T2DM patients.

Multi-echo gradient echo pulse sequences: which is best for PRFS MR thermometry guided hyperthermia?

PURPOSE

MR thermometry (MRT) enables noninvasive temperature monitoring during hyperthermia treatments. MRT is already clinically applied for hyperthermia treatments in the abdomen and extremities, and devices for the head are under development. In order to optimally exploit MRT in all anatomical regions, the best sequence setup and post-processing must be selected, and the accuracy needs to be demonstrated.

METHODS

MRT performance of the traditionally used double-echo gradient-echo sequence (DE-GRE, 2 echoes, 2D) was compared to multi-echo sequences: a 2D fast gradient-echo (ME-FGRE, 11 echoes) and a 3D fast gradient-echo sequence (3D-ME-FGRE, 11 echoes). The different methods were assessed on a 1.5 T MR scanner (GE Healthcare) using a phantom cooling down from 59 °C to 34 °C and unheated brains of 10 volunteers. In-plane motion of volunteers was compensated by rigid body image registration. For the ME sequences, the off-resonance frequency was calculated using a multi-peak fitting tool. To correct for B0 drift, the internal body fat was selected automatically using water/fat density maps.

RESULTS

The accuracy of the best performing 3D-ME-FGRE sequence was 0.20 °C in phantom (in the clinical temperature range) and 0.75 °C in volunteers, compared to DE-GRE values of 0.37 °C and 1.96 °C, respectively.

CONCLUSION

For hyperthermia applications, where accuracy is more important than resolution or scan-time, the 3D-ME-FGRE sequence is deemed the most promising candidate. Beyond its convincing MRT performance, the ME nature enables automatic selection of internal body fat for B0 drift correction, an important feature for clinical application.