Ultrashort echo time MRI detects significantly lower collagen but higher pore water in the tibial cortex of female patients with osteopenia and osteoporosis.

Ultrashort echo time (UTE) MRI can quantify the major proton pool densities in cortical bone, including total (TWPD), bound (BWPD), and pore water (PWPD) proton densities, as well as the macromolecular proton density (MMPD), associated with the collagen content, which is calculated using macromolecular fraction (MMF) from UTE magnetization transfer (UTE-MT) modeling. This study aimed to investigate the differences in water and collagen contents in tibial cortical bone, between female osteopenia (OPe) patients, osteoporosis (OPo) patients, and young participants (Young). Being postmenopausal and above 55 years old were the inclusion criteria for OPe and OPo groups. The tibial shaft of fourteen OPe (72.5 ± 6.8 years old), thirty-one OPo (72.0 ± 6.4 years old), and thirty-one young subjects (28.0 ± 6.1 years old) were scanned using a knee coil on a clinical 3 T scanner. Basic UTE, inversion recovery UTE, and UTE-MT sequences were performed. Investigated biomarkers were compared between groups using Kruskal-Wallis test. Spearman's correlation coefficients were calculated between the total hip dual-energy x-ray absorptiometry (DXA) T-score and UTE-MRI results. MMF, BWPD, and MMPD were significantly lower in OPo patients than in the young group. Whereas T1, TWPD, and PWPD were significantly higher in OPo patients. The largest OPo/Young average percentage differences were found in MMF (41.9%), PWPD (103.5%), and MMPD (64.0%). PWPD was significantly higher (50.7%), while BWPD was significantly lower (16.4%) in OPe than the Young group on average. MMF was found to be significantly lower (27%) in OPo patients compared with OPe group. T1, MMF, TWPD, PWPD, and MMPD values significantly correlated with the total hip DXA T-scores (provided by the patients and only available for OPe and OPo patients). DXA T-score showed the highest correlations with PWPD (R = 0.55) and MMF (R = 0.56) values. TWPD, PWPD, and MMF estimated using the UTE-MRI sequences were recommended to evaluate individuals with OPe and OPo.

Ultrashort echo time (UTE) is an MRI technique that can quantify the water and collagen content of cortical bone. Water in the bone can be found residing in pores (pore water) or bound to the bone matrix (bound water). We investigated the differences in water and collagen contents of tibial cortical bone, between female osteopenia patients, osteoporosis patients, and young participants. Bound water and collagen contents were significantly lower in osteoporosis patients than in the young group. Whereas total water and pore water contents were significantly higher in osteoporosis patients. Pore water was significantly higher, while bound water was significantly lower in osteopenia than in the Young group. Collagen content was found to be significantly lower in osteoporosis patients compared with the osteopenia group. The estimated water and collagen contents were significantly correlated with the total hip bone densitometry measures in the patients.

Fast dual-echo estimation of apparent long T2 fraction using ultrashort echo time magnetic resonance imaging in tibialis tendons and its osteoporosis-related differences in women.

Background: Tendon and bone comprise a critical interrelating unit. Bone loss, including that seen with osteopenia (OPe) or osteoporosis (OPo), may be associated with a reduction in tendon quality, though this remains incompletely investigated. Clinical magnetic resonance imaging (MRI) sequences cannot directly detect signals from tendons because of the very short T2. Clinical MRI may detect high-graded abnormalities by changes in the adjacent structures like bone. However, ultrashort echo time MRI (UTE-MRI) can capture high signals from all tendons. To determine if the long T2 fraction, as measured by a dual-echo UTE-MRI sequence, is a sensitive quantitative technique to the age- and bone-loss-related changes of the lower leg tendons. Methods: This is a cross-sectional study conducted between January 2018 to February 2020 in the lower legs of 14 female patients with OPe [72±6 years old, body mass index (BMI) =25.8±6.2 kg/m2] and 31 female patients with OPo (73±6 years old, BMI=22.0±3.8 kg/m2), as well as 30 female subjects with normal bone (Normal, 35±18 years old, BMI =23.2±4.3 kg/m2), were imaged on a 3T clinical scanner using a dual-echo 3D Cones UTE sequence. We defined the apparent long T2 signal fraction (aFrac-LongT2) of tendons as the ratio between the signal at the second echo time (TE =2.2 ms) to the UTE signal. The average aFrac-LongT2 and the cross-sectional area were calculated for the anterior tibialis tendons (ATTs) and the posterior tibialis tendons (PTTs). The Kruskal-Wallis rank test was used to compare the differences in aFrac-LongT2 and the cross-sectional area of the tendons between the groups. Results: The aFrac-LongT2 of the ATTs and PTTs were significantly higher in the OPo group compared with the Normal group (22.2% and 34.8% in the ATT and PTT, respectively, P<0.01). The cross-sectional area in the ATTs was significantly higher for the OPo group than in the Normal group (Normal/OPo difference was 28.7, P<0.01). Such a difference for PTTs did not reach the significance level. Mean aFrac-LongT2 and cross-sectional area in the OPe group were higher than the Normal group and lower than the OPo group. However, the differences did not show statistical significance, likely due to the higher BMI in the OPe group. Conclusions: Dual-echo UTE-MRI is a rapid quantification technique, and aFrac-LongT2 values showed significant differences in tendons between Normal and OPo patients.

More accurate trabecular bone imaging using UTE MRI at the resonance frequency of fat.

High-resolution magnetic resonance imaging (HR-MRI) has been increasingly used to assess the trabecular bone structure. High susceptibility at the marrow/bone interface may significantly reduce the marrow's apparent transverse relaxation time (T2*), overestimating trabecular bone thickness. Ultrashort echo time MRI (UTE-MRI) can minimize the signal loss caused by susceptibility-induced T2* shortening. However, UTE-MRI is sensitive to chemical shift artifacts, which manifest as spatial blurring and ringing artifacts partially due to non-Cartesian sampling. In this study, we proposed UTE-MRI at the resonance frequency of fat to minimize marrow-related chemical shift artifacts and the overestimation of trabecular thickness. Cubes of trabecular bone from six donors (75 ± 4 years old) were scanned using a 3 T clinical scanner at the resonance frequencies of fat and water, respectively, using 3D UTE sequences with five TEs (0.032, 1.1, 2.2, 3.3, and 4.4 ms) and a clinical 3D gradient echo (GRE) sequence at 0.2 × 0.2 × 0.4 mm3 voxel size. Trabecular bone thickness was measured in 30 regions of interest (ROIs) per sample. MRI results were compared with thicknesses obtained from micro-computed tomography (µCT) at 50 µm3 voxel size. Linear regression models were used to calculate the coefficient of determination between MRI- and µCT-based trabecular thickness. All MRI-based trabecular thicknesses showed significant correlations with µCT measurements. The correlations were higher (examined with paired Student's t-test, P < 0.01) for 3D UTE images performed at the fat frequency (R2 = 0.59-0.74, P < 0.01) than those at the water frequency (R2 = 0.18-0.52, P < 0.01) and clinical GRE images (R2 = 0.39-0.47, P < 0.01). Significantly reduced correlations were observed with longer TEs. This study highlighted the feasibility of UTE-MRI at the fat frequency for a more accurate assessment of trabecular bone thickness.

Deep Convolutional Neural Network for Dedicated Regions-of-Interest Based Multi-Parameter Quantitative Ultrashort Echo Time (UTE) Magnetic Resonance Imaging of the Knee Joint.

We proposed an end-to-end deep learning convolutional neural network (DCNN) for region-of-interest based multi-parameter quantification (RMQ-Net) to accelerate quantitative ultrashort echo time (UTE) MRI of the knee joint with automatic multi-tissue segmentation and relaxometry mapping. The study involved UTE-based T1 (UTE-T1) and Adiabatic T1ρ (UTE-AdiabT1ρ) mapping of the knee joint of 65 human subjects, including 20 normal controls, 29 with doubtful-minimal osteoarthritis (OA), and 16 with moderate-severe OA. Comparison studies were performed on UTE-T1 and UTE-AdiabT1ρ measurements using 100%, 43%, 26%, and 18% UTE MRI data as the inputs and the effects on the prediction quality of the RMQ-Net. The RMQ-net was modified and retrained accordingly with different combinations of inputs. Both ROI-based and voxel-based Pearson correlation analyses were performed. High Pearson correlation coefficients were achieved between the RMQ-Net predicted UTE-T1 and UTE-AdiabT1ρ results and the ground truth for segmented cartilage with acceleration factors ranging from 2.3 to 5.7. With an acceleration factor of 5.7, the Pearson r-value achieved 0.908 (ROI-based) and 0.945 (voxel-based) for UTE-T1, and 0.733 (ROI-based) and 0.895 (voxel-based) for UTE-AdiabT1ρ, correspondingly. The results demonstrated that RMQ-net can significantly accelerate quantitative UTE imaging with automated segmentation of articular cartilage in the knee joint.

AI-based automated detection and stability analysis of traumatic vertebral body fractures on computed tomography.

PURPOSE: We developed and tested a neural network for automated detection and stability analysis of vertebral body fractures on computed tomography (CT). MATERIALS AND METHODS: 257 patients who underwent CT were included in this Institutional Review Board (IRB) approved study. 463 fractured and 1883 non-fractured vertebral bodies were included, with 190 fractures unstable. Two readers identified vertebral body fractures and assessed their stability. A combination of a Hierarchical Convolutional Neural Network (hNet) and a fracture Classification Network (fNet) was used to build a neural network for the automated detection and stability analysis of vertebral body fractures on CT. Two final test settings were chosen: one with vertebral body levels C1/2 included and one where they were excluded. RESULTS: The mean age of the patients was 68 ± 14 years. 140 patients were female. The network showed a slightly higher diagnostic performance when excluding C1/2. Accordingly, the network was able to distinguish fractured and non-fractured vertebral bodies with a sensitivity of 75.8 % and a specificity of 80.3 %. Additionally, the network determined the stability of the vertebral bodies with a sensitivity of 88.4 % and a specificity of 80.3 %. The AUC was 87 % and 91 % for fracture detection and stability analysis, respectively. The sensitivity of our network in indicating the presence of at least one fracture / one unstable fracture within the whole spine achieved values of 78.7 % and 97.2 %, respectively, when excluding C1/2. CONCLUSION: The developed neural network can automatically detect vertebral body fractures and evaluate their stability concurrently with a high diagnostic performance.

Bone Biomarkers Based on Magnetic Resonance Imaging.

Magnetic resonance imaging (MRI) is increasingly used to evaluate the microstructural and compositional properties of bone. MRI-based biomarkers can characterize all major compartments of bone: organic, water, fat, and mineral components. However, with a short apparent spin-spin relaxation time (T2*), bone is invisible to conventional MRI sequences that use long echo times. To address this shortcoming, ultrashort echo time MRI sequences have been developed to provide direct imaging of bone and establish a set of MRI-based biomarkers sensitive to the structural and compositional changes of bone. This review article describes the MRI-based bone biomarkers representing total water, pore water, bound water, fat fraction, macromolecular fraction in the organic matrix, and surrogates for mineral density. MRI-based morphological bone imaging techniques are also briefly described.

Bi-Exponential 3D UTE-T1ρ Relaxation Mapping of Ex Vivo Human Knee Patellar Tendon at 3T.

Introduction: The objective of this study was to assess the bi-exponential relaxation times and fractions of the short and long components of the human patellar tendon ex vivo using three-dimensional ultrashort echo time T1ρ (3D UTE-T1ρ) imaging. Materials and Methods: Five cadaveric human knee specimens were scanned using a 3D UTE-T1ρ imaging sequence on a 3T MR scanner. A series of 3D UTE-T1ρ images were acquired and fitted using single-component and bi-component models. Single-component exponential fitting was performed to measure the UTE-T1ρ value of the patellar tendon. Bi-component analysis was performed to measure the short and long UTE-T1ρ values and fractions. Results: The single-component analysis showed a mean single-component UTE-T1ρ value of 8.4 ± 1.7 ms for the five knee patellar tendon samples. Improved fitting was achieved with bi-component analysis, which showed a mean short UTE-T1ρ value of 5.5 ± 0.8 ms with a fraction of 77.6 ± 4.8%, and a mean long UTE-T1ρ value of 27.4 ± 3.8 ms with a fraction of 22.4 ± 4.8%. Conclusion: The 3D UTE-T1ρ sequence can detect the single- and bi-exponential decay in the patellar tendon. Bi-component fitting was superior to single-component fitting.

Whole knee joint mapping using a phase modulated UTE adiabatic T1ρ (PM-UTE-AdiabT1ρ ) sequence.

PURPOSE: To develop a 3D phase modulated UTE adiabatic T1ρ (PM-UTE-AdiabT1ρ ) sequence for whole knee joint mapping on a clinical 3 T scanner. METHODS: This new sequence includes six major features: (1) a magnetization reset module, (2) a train of adiabatic full passage pulses for spin locking, (3) a phase modulation scheme (i.e., RF cycling pair), (4) a fat saturation module, (5) a variable flip angle scheme, and (6) a 3D UTE Cones sequence for data acquisition. A simple exponential fitting was used for T1ρ quantification. Phantom studies were performed to investigate PM-UTE-AdiabT1ρ 's sensitivity to compositional changes and reproducibility as well as its correlation with continuous wave-T1ρ measurement. The PM-UTE-AdiabT1ρ technique was then applied to five ex vivo and five in vivo normal knees to measure T1ρ values of femoral cartilage, meniscus, posterior cruciate ligament, anterior cruciate ligament, patellar tendon, and muscle. RESULTS: The phantom study demonstrated PM-UTE-AdiabT1ρ 's high sensitivity to compositional changes, its high reproducibility, and its strong linear correlation with continuous wave-T1ρ measurement. The ex vivo and in vivo knee studies demonstrated average T1ρ values of 105.6 ± 8.4 and 77.9 ± 3.9 ms for the femoral cartilage, 39.2 ± 5.1 and 30.1 ± 2.2 ms for the meniscus, 51.6 ± 5.3 and 29.2 ± 2.4 ms for the posterior cruciate ligament, 79.0 ± 9.3 and 52.0 ± 3.1 ms for the anterior cruciate ligament, 19.8 ± 4.5 and 17.0 ± 1.8 ms for the patellar tendon, and 91.1 ± 8.8 and 57.6 ± 2.8 ms for the muscle, respectively. CONCLUSION: The 3D PM-UTE-AdiabT1ρ sequence allows volumetric T1ρ assessment for both short and long T2 tissues in the knee joint on a clinical 3 T scanner.

Achilles tendon and enthesis assessment using ultrashort echo time magnetic resonance imaging (UTE-MRI) T1 and magnetization transfer (MT) modeling in psoriatic arthritis.

The purpose of this study is to investigate the use of ultrashort echo time (UTE) magnetic resonance imaging (MRI) techniques (T1 and magnetization transfer [MT] modeling) for imaging of the Achilles tendons and entheses in patients with psoriatic arthritis (PsA) compared with asymptomatic volunteers. The heels of twenty-six PsA patients (age 59 ± 15 years, 41% female) and twenty-seven asymptomatic volunteers (age 33 ± 11 years, 47% female) were scanned in the sagittal plane with UTE-T1 and UTE-MT modeling sequences on a 3-T clinical scanner. UTE-T1 and macromolecular proton fraction (MMF; the main outcome of MT modeling) were calculated in the tensile portions of the Achilles tendon and at the enthesis (close to the calcaneus bone). Mann-Whitney-U tests were used to examine statistically significant differences between the two cohorts. UTE-T1 in the entheses was significantly higher for the PsA group compared with the asymptomatic group (967 ± 145 vs. 872 ± 133 ms, p < 0.01). UTE-T1 in the tendons was also significantly higher for the PsA group (950 ± 145 vs. 850 ± 138 ms, p < 0.01). MMF in the entheses was significantly lower in the PsA group compared with the asymptomatic group (15% ± 3% vs. 18% ± 3%, p < 0.01). MMF in the tendons was also significantly lower in the PsA group compared with the asymptomatic group (17% ± 4% vs. 20% ± 5%, p < 0.01). Percentage differences in MMF between the asymptomatic and PsA groups (-16.6% and -15.0% for the enthesis and tendon, respectively) were higher than the T1 differences (10.8% and 11.7% for the enthesis and tendon, respectively). The results suggest higher T1 and lower MMF in the Achilles tendons and entheses in PsA patients compared with the asymptomatic group. This study highlights the potential of UTE-T1 and UTE-MT modeling for quantitative evaluation of entheses and tendons in PsA patients.

Evaluation of gadolinium deposition in cortical bone using three-dimensional ultrashort echo time quantitative susceptibility mapping: A preliminary study.

The aim of the current study was to investigate the feasibility of three-dimensional ultrashort echo time quantitative susceptibility mapping (3D UTE-QSM) for the assessment of gadolinium (Gd) deposition in cortical bone. To this end, 40 tibial bovine cortical bone specimens were divided into five groups then soaked in phosphate-buffered saline (PBS) solutions with five different Gd concentrations of 0, 0.4, 0.8, 1.2, and 1.6 mmol/L for 48 h. Additionally, eight rabbits were randomly allocated into three groups, consisting of a normal-dose macrocyclic gadolinium-based contrast agent (GBCA) group (n = 3), a high-dose macrocyclic GBCA group (n = 3), and a control group (n = 2). All bovine and rabbit tibial bone samples underwent magnetic resonance imaging (MRI) on a 3-T clinical MR system. A 3D UTE-Cones sequence was utilized to acquire images with five different echo times (i.e., 0.032, 0.2, 0.4, 0.8, and 1.2 ms). The UTE images were subsequently processed with the morphology-enabled dipole inversion algorithm to yield a susceptibility map. The average susceptibility was calculated in three regions of interest in the middle of each specimen, and the Pearson's correlation between the estimated susceptibility and Gd concentration was calculated. The bone samples soaked in PBS with higher Gd concentrations exhibited elevated susceptibility values. A mean susceptibility value of -2.47 ± 0.23 ppm was observed for bovine bone soaked in regular PBS, while the mean QSM value increased to -1.75 ± 0.24 ppm for bone soaked in PBS with the highest Gd concentration of 1.6 mmol/L. A strong positive correlation was observed between Gd concentrations and QSM values. The mean susceptibility values of rabbit tibial specimens in the control group, normal-dose GBCA group, and high-dose GBCA group were -4.11 ± 1.52, -3.85 ± 1.33, and -3.39 ± 1.35 ppm, respectively. In conclusion, a significant linear correlation between Gd in cortical bone and QSM values was observed. The preliminary results suggest that 3D UTE-QSM may provide sensitive noninvasive assessment of Gd deposition in cortical bone.

Ultrashort echo time pulse sequences for visualization of deep peripheral fasciae and epimysium in porcine models with histologic correlations.

Background: The deep peripheral fascia and epimysium are vital for muscle and tendon support, but their tight proton composition results in hypointense signals in conventional spin echo sequences. Ultrashort echo time (UTE) magnetic resonance imaging (MRI), using microsecond TE values, may visualize these structures. The purpose of this study was to evaluate whether UTE pulse sequence with a three-dimensional cone trajectory (3D UTE), with or without fat suppression (FS), can be used to visualize the fascia and epimysium using porcine lower legs as an example. Methods: The anterior soft tissues of porcine lower legs were dissected and partially separated into distinct layers to expose the deep peripheral fascia, epimysium, and muscle. Axial 3D UTE and 3D UTE FS imaging using dual-echo acquisition and echo subtraction were performed both before and after dissection. Prior to dissection, the thickness, signal-to-noise ratios (SNRs), and contrast-to-noise ratios (CNRs) of structures believed to be deep peripheral fascia and epimysium were measured in both 3D UTE and 3D UTE FS. Post-dissection images were also analyzed to measure the SNRs and CNRs for the deep peripheral fascia and epimysium. Histological evaluations were carried out to verify the identities of the deep peripheral fascia and epimysium, as well as their thickness, and these measurements were compared to imaging findings. Results: In pre-dissection images obtained with 3D UTE and 3D UTE FS, both the deep peripheral fascia and epimysium exhibited high signal intensity. In the subtraction images, the mean thickness of the deep fascia was 0.87 mm, and that of the epimysium was 0.80 mm when imaged with 3D UTE. This is compared to measurements of 0.77 and 0.22 mm in 3D UTE FS, respectively. Histological analyses confirmed the thickness of the deep peripheral fascia and epimysium as 0.65 and 0.14 mm, respectively. In the post-dissection images, the deep fascia continued to display high signal intensity when compared with adjacent soft tissues, consistent with the histological findings. Meanwhile, the epimysium showed very low CNRs. Conclusions: 3D UTE and 3D UTE FS can be used to visualize the deep peripheral fascia with high signal intensity and contrast but are insufficient to show signal intensity in the epimysium.

Brain MRI findings in neurologically symptomatic COVID-19 patients: a systematic review and meta-analysis.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has been associated with nervous system involvement, with more than one-third of COVID-19 patients experiencing neurological manifestations. Utilizing a systematic review, this study aims to summarize brain MRI findings in COVID-19 patients presenting with neurological symptoms. METHODS: Systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) checklist. The electronic databases of PubMed/MEDLINE, Embase, Scopus, and Web of Science were systematically searched for literature addressing brain MRI findings in COVID-19 patients with neurological symptoms. RESULTS: 25 publications containing a total number of 3118 COVID-19 patients with neurological symptoms who underwent MRI were included. The most common MRI findings and the respective pooled incidences in decreasing order were acute/subacute infarct (22%), olfactory bulb abnormalities (22%), white matter abnormalities (20%), cerebral microbleeds (17%), grey matter abnormalities (12%), leptomeningeal enhancement (10%), ADEM (Acute Disseminated Encephalomyelitis) or ADEM-like lesions (10%), non-traumatic ICH (10%), cranial neuropathy (8%), cortical gray matter signal changes compatible with encephalitis (8%), basal ganglia abnormalities (5%), PRES (Posterior Reversible Encephalopathy Syndrome) (3%), hypoxic-ischemic lesions (4%), venous thrombosis (2%), and cytotoxic lesions of the corpus callosum (2%). CONCLUSION: The present study revealed that a considerable proportion of patients with COVID-19 might harbor neurological abnormalities detectable by MRI. Among various findings, the most common MRI alterations are acute/subacute infarction, olfactory bulb abnormalities, white matter abnormalities, and cerebral microbleeds.

Correction: Lombardi et al. AcidoCEST-UTE MRI Reveals an Acidic Microenvironment in Knee Osteoarthritis. Int. J. Mol. Sci. 2022, 23, 4466.

In the original publication, there was a mistake in Figure 1 as published [...].

Clinical evaluation of white matter lesions on 3D inversion recovery ultrashort echo time MRI in multiple sclerosis.

Background: We clinically evaluated the quality of white matter lesions (WML) of the cerebrum on 3D inversion recovery ultrashort echo time (IR-UTE) magnetic resonance imaging (MRI) in multiple sclerosis (MS) patients. Methods: Forty-nine patients with MS were included in this study. A 3T MRI scanner was used. Two radiologists (readers) evaluated the quality of WML on IR-UTE images using a three-point Likert scale (1-good quality, 2-moderate quality, 3-insufficient quality). They also rated other WML-related factors potentially influencing WML quality using another three-point Likert scale (1-no/minor impact, 2-moderate impact, 3-high impact). Another reader rated the presence of WML on IR-UTE to evaluate the diagnostic value (right/false positive and false negative) of IR-UTE in detecting WML. Signal intensity ratios (SIRs) derived from WML signal intensities and WML sizes were also determined and analyzed. Results: Two hundred and seventy-five MS lesions were evaluated. 87% of the lesions were rated Likert 1 on IR-UTE (P<0.01). WML rated Likert 2 and 3 presented near the grey matter (GM) in 58% of the cases (n=21), with 14 lesions being ≤2 mm (P=0.03). 62.5% of the WML rated Likert 2/3 were in the temporal lobe (P=0.02). The mean SIR of WML on IR-UTE was 1.14±0.22, while the mean SIR on fluid-attenuated inversion recovery (FLAIR) was 6.97±1.88. There was no significant correlation of SIRs between IR-UTE and FLAIR (R=0.14, P=0.245). 92.4% of the WML were correctly detected on IR-UTE (n=254). 19 out of the 21 false positive/negative rated WML were located near the GM or in the temporal lobe. WML presented 7.7% smaller in mean on IR-UTE compared to FLAIR. Factors affecting WML quality with a moderate or high impact (Likert 2 and 3) were not found. Conclusions: Most WML are clearly detectable on IR-UTE sequences. The main limitations are WML in the temporal lobe and near the GM.

Deep-learning-based biomarker of spinal cartilage endplate health using ultra-short echo time magnetic resonance imaging.

Background: T2* relaxation times in the spinal cartilage endplate (CEP) measured using ultra-short echo time magnetic resonance imaging (UTE MRI) reflect aspects of biochemical composition that influence the CEP's permeability to nutrients. Deficits in CEP composition measured using T2* biomarkers from UTE MRI are associated with more severe intervertebral disc degeneration in patients with chronic low back pain (cLBP). The goal of this study was to develop an objective, accurate, and efficient deep-learning-based method for calculating biomarkers of CEP health using UTE images. Methods: Multi-echo UTE MRI of the lumbar spine was acquired from a prospectively enrolled cross-sectional and consecutive cohort of 83 subjects spanning a wide range of ages and cLBP-related conditions. CEPs from the L4-S1 levels were manually segmented on 6,972 UTE images and used to train neural networks utilizing the u-net architecture. CEP segmentations and mean CEP T2* values derived from manually- and model-generated segmentations were compared using Dice scores, sensitivity, specificity, Bland-Altman, and receiver-operator characteristic (ROC) analysis. Signal-to-noise (SNR) and contrast-to-noise (CNR) ratios were calculated and related to model performance. Results: Compared with manual CEP segmentations, model-generated segmentations achieved sensitives of 0.80-0.91, specificities of 0.99, Dice scores of 0.77-0.85, area under the receiver-operating characteristic curve values of 0.99, and precision-recall (PR) AUC values of 0.56-0.77, depending on spinal level and sagittal image position. Mean CEP T2* values and principal CEP angles derived from the model-predicted segmentations had low bias in an unseen test dataset (T2* bias =0.33±2.37 ms, angle bias =0.36±2.65°). To simulate a hypothetical clinical scenario, the predicted segmentations were used to stratify CEPs into high, medium, and low T2* groups. Group predictions had diagnostic sensitivities of 0.77-0.86 and specificities of 0.86-0.95. Model performance was positively associated with image SNR and CNR. Conclusions: The trained deep learning models enable accurate, automated CEP segmentations and T2* biomarker computations that are statistically similar to those from manual segmentations. These models address limitations with inefficiency and subjectivity associated with manual methods. Such techniques could be used to elucidate the role of CEP composition in disc degeneration etiology and guide emerging therapies for cLBP.

MRI-based porosity index (PI) and suppression ratio (SR) in the tibial cortex show significant differences between normal, osteopenic, and osteoporotic female subjects.

Introduction: Ultrashort echo time (UTE) MRI enables quantitative assessment of cortical bone. The signal ratio in dual-echo UTE imaging, known as porosity index (PI), as well as the signal ratio between UTE and inversion recovery UTE (IR-UTE) imaging, known as the suppression ratio (SR), are two rapid UTE-based bone evaluation techniques developed to reduce the time demand and cost in future clinical studies. The goal of this study was to investigate the performance of PI and SR in detecting bone quality differences between subjects with osteoporosis (OPo), osteopenia (OPe), and normal bone (Normal). Methods: Tibial midshaft of fourteen OPe (72 ± 6 years old), thirty-one OPo (72 ± 6 years old), and thirty-seven Normal (36 ± 19 years old) subjects were scanned using dual-echo UTE and IR-UTE sequences on a clinical 3T scanner. Measured PI, SR, and bone thickness were compared between OPo, OPe, and normal bone (Normal) subjects using the Kruskal-Wallis test by ranks. Spearman's rank correlation coefficients were calculated between dual-energy x-ray absorptiometry (DEXA) T-score and UTE-MRI results. Results: PI was significantly higher in the OPo group compared with the Normal (24.1%) and OPe (16.3%) groups. SR was significantly higher in the OPo group compared with the Normal (41.5%) and OPe (21.8%) groups. SR differences between the OPe and Normal groups were also statistically significant (16.2%). Cortical bone was significantly thinner in the OPo group compared with the Normal (22.0%) and OPe (13.0%) groups. DEXA T-scores in subjects were significantly correlated with PI (R=-0.32), SR (R=-0.50), and bone thickness (R=0.51). Discussion: PI and SR, as rapid UTE-MRI-based techniques, may be useful tools to detect and monitor bone quality changes, in addition to bone morphology, in individuals affected by osteoporosis.

The signal intensity variation of multiple sclerosis (MS) lesions on magnetic resonance imaging (MRI) as a potential biomarker for patients' disability: A feasibility study.

Introduction: Although many lesion-based MRI biomarkers in multiple sclerosis (MS) patients were investigated, none of the previous studies dealt with the signal intensity variations (SIVs) of MS lesions. In this study, the SIVs of MS lesions on direct myelin imaging and standard clinical sequences as possible MRI biomarkers for disability in MS patients were assessed. Methods: Twenty seven MS patients were included in this prospective study. IR-UTE, FLAIR, and MPRAGE sequences were employed on a 3T scanner. Regions of interest (ROIs) were manually drawn within the MS lesions, and the cerebrospinal fluid (CSF) and signal intensity ratios (SIR) were calculated from the derived values. Variations coefficients were determined from the standard deviations (Coeff 1) and the absolute differences (Coeff 2) of the SIRs. Disability grade was assessed by the expanded disability status scale (EDSS). Cortical/gray matter, subcortical, infratentorial, and spinal lesions were excluded. Results: The mean diameter of the lesions was 7.8 ± 1.97 mm, while the mean EDSS score was 4.5 ± 1.73. We found moderate correlations between the EDSS and Coeff 1 and 2 on IR-UTE and MPRAGE images. Accordingly, Pearson's correlations on IR-UTE were R = 0.51 (p = 0.007) and R = 0.49 (p = 0.01) for Coeff 1 and 2, respectively. For MPRAGE, Pearson's correlations were R = 0.5 (p = 0.008) and R = 0.48 (p = 0.012) for Coeff 1 and 2, respectively. For FLAIR, only poor correlations could be found. Conclusion: The SIVs of MS lesions on IR-UTE and MPRAGE images, assessed by Coeff 1 and 2, could be used as novel potential MRI biomarkers for patients' disability.

Robust Assessment of Macromolecular Fraction (MMF) in Muscle with Differing Fat Fraction Using Ultrashort Echo Time (UTE) Magnetization Transfer Modeling with Measured T1.

Magnetic resonance imaging (MRI) is widely regarded as the most comprehensive imaging modality to assess skeletal muscle quality and quantity. Magnetization transfer (MT) imaging can be used to estimate the fraction of water and macromolecular proton pools, with the latter including the myofibrillar proteins and collagen, which are related to the muscle quality and its ability to generate force. MT modeling combined with ultrashort echo time (UTE-MT modeling) may improve the evaluation of the myotendinous junction and regions with fibrotic tissues in the skeletal muscles, which possess short T2 values and higher bound-water concentration. The fat present in muscle has always been a source of concern in macromolecular fraction (MMF) calculation. This study aimed to investigate the impact of fat fraction (FF) on the estimated MMF in bovine skeletal muscle phantoms embedded in pure fat. MMF was calculated for several regions of interest (ROIs) with differing FFs using UTE-MT modeling with and without T1 measurement and B1 correction. Calculated MMF using measured T1 showed a robust trend, particularly with a negligible error (<3%) for FF < 20%. Around 5% MMF reduction occurred for FF > 30%. However, MMF estimation using a constant T1 was robust only for regions with FF < 10%. The MTR and T1 values were also robust for only FF < 10%. This study highlights the potential of the UTE-MT modeling with accurate T1 measurement for robust muscle assessment while remaining insensitive to fat infiltration up to moderate levels.

Correction of B0 and linear eddy currents: Impact on morphological and quantitative ultrashort echo time double echo steady state (UTE-DESS) imaging.

The purpose of the current study was to investigate the effects of B0 and linear eddy currents on ultrashort echo time double echo steady state (UTE-DESS) imaging and to determine whether eddy current correction (ECC) effectively resolves imaging artifacts caused by eddy currents. 3D UTE-DESS sequences based on either projection radial or spiral cones trajectories were implemented on a 3-T clinical MR scanner. An off-isocentered thin-slice excitation approach was used to measure eddy currents. The measurements were repeated four times using two sets of tested gradient waveforms with opposite polarities and two different slice locations to measure B0 and linear eddy currents simultaneously. Computer simulation was performed to investigate the eddy current effect. Finally, a phantom experiment, an ex vivo experiment with human synovium and ankle samples, and an in vivo experiment with human knee joints, were performed to demonstrate the effects of eddy currents and ECC in UTE-DESS imaging. In a computer simulation, the two echoes (S+ and S-) in UTE-DESS imaging exhibited strong distortion at different orientations in the presence of B0 and linear eddy currents, resulting in both image degradation as well as misalignment of pixel location between the two echoes. The same phenomenon was observed in the phantom, ex vivo, and in vivo experiments, where the presence of eddy currents degraded S+, S-, echo subtraction images, and T2 maps. The implementation of ECC dramatically improved both the image quality and image registration between the S+ and S- echoes. It was concluded that ECC is crucial for reliable morphological and quantitative UTE-DESS imaging.

Detection of iron oxide nanoparticle (IONP)-labeled stem cells using quantitative ultrashort echo time imaging: a feasibility study.

Background: In this study, we investigated the feasibility of quantitative ultrashort echo time (qUTE) magnetic resonance (MR) imaging techniques in the detection and quantification of iron oxide nanoparticle (IONP)-labeled stem cells. Methods: A stem cell phantom containing multiple layers of unlabeled or labeled stem cells with different densities was prepared. The phantom was imaged with quantitative UTE (qUTE) MR techniques [i.e., UTE-T1 mapping, UTE-T2* mapping, and UTE-based quantitative susceptibility mapping (UTE-QSM)] as well as with a clinical T2 mapping sequence on a 3T clinical MR system. For T1 mapping, a variable flip angle (VFA) method based on actual flip angle imaging (AFI) technique was utilized. For T2* mapping and UTE-QSM, multiple images with variable, interleaved echo times including UTE images and gradient recalled echo (GRE) images were used. For UTE-QSM, the phase information from the multi-echo images was utilized and processed using a QSM framework based on the morphology-enabled dipole inversion (MEDI) algorithm. The qUTE techniques were also evaluated in an ex vivo experiment with a mouse injected with IONP-labeled stem cells. Results: In the phantom experiment, the parameters estimated with qUTE techniques showed high linearity with respect to the density of IONP-labeled stem cells (R2>0.99), while the clinical T2 parameter showed impaired linearity (R2=0.87). In the ex vivo mouse experiment, UTE-T2* mapping and UTE-QSM showed feasibility in the detection of injected stem cells with high contrast, whereas UTE-T1 and UTE-T2* showed limited detection. Overall, UTE-QSM demonstrated the best contrast of all, with other methods being subjected more to a confounding factor due to different magnetic susceptibilities of various types of neighboring tissues, which creates inhomogeneous contrast that behaves similar to IONP. Conclusions: In this study, we evaluated the feasibility of a series of qUTE imaging techniques as well as conventional T2 mapping for the detection of IONP-labeled stem cells in vitro and ex vivo. UTE-QSM performed superior amongst other qUTE techniques as well as conventional T2 mapping in detecting stem cells with high contrast.