High contrast cartilaginous endplate imaging in spine using three dimensional dual-inversion recovery prepared ultrashort echo time (3D DIR-UTE) sequence

PURPOSE

To investigate the feasibility and application of a novel imaging technique, a three-dimensional dual adiabatic inversion recovery prepared ultrashort echo time (3D DIR-UTE) sequence, for high contrast assessment of cartilaginous endplate (CEP) imaging with head-to-head comparisons between other UTE imaging techniques.

METHOD

The DIR-UTE sequence employs two narrow-band adiabatic full passage (AFP) pulses to suppress signals from long T2 water (e.g., nucleus pulposus (NP)) and bone marrow fat (BMF) independently, followed by multispoke UTE acquisition to detect signals from the CEP with short T2 relaxation times. The DIR-UTE sequence, in addition to three other UTE sequences namely, an IR-prepared and fat-saturated UTE (IR-FS-UTE), a T1-weighted and fat-saturated UTE sequence (T1w-FS-UTE), and a fat-saturated UTE (FS-UTE) was used for MR imaging on a 3 T scanner to image six asymptomatic volunteers, six patients with low back pain, as well as a human cadaveric specimen. The contrast-to-noise ratio of the CEP relative to the adjacent structures-specifically the NP and BMF-was then compared from the acquired images across the different UTE sequences.

RESULTS

For asymptomatic volunteers, the DIR-UTE sequence showed significantly higher contrast-to-noise ratio values between the CEP and BMF (CNRCEP-BMF) (19.9 ± 3.0) and between the CEP and NP (CNRCEP-NP) (23.1 ± 1.7) compared to IR-FS-UTE (CNRCEP-BMF: 17.3 ± 1.2 and CNRCEP-NP: 19.1 ± 1.8), T1w-FS-UTE (CNRCEP-BMF: 9.0 ± 2.7 and CNRCEP-NP: 10.4 ± 3.5), and FS-UTE (CNRCEP-BMF: 7.7 ± 2.2 and CNRCEP-NP: 5.8 ± 2.4) for asymptomatic volunteers (all P-values < 0.001). For the spine sample and patients with low back pain, the DIR-UTE technique detected abnormalities such as irregularities and focal defects in the CEP regions.

CONCLUSION

The 3D DIR-UTE sequence is able to provide high-contrast volumetric CEP imaging for human spines on a clinical 3 T scanner.

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.

Myelin water quantification in multiple sclerosis using short repetition time adiabatic inversion recovery prepared-fast spin echo (STAIR-FSE) imaging

Background

Myelin water imaging (MWI) is a myelin-specific technique, which has great potential for the assessment of demyelination and remyelination. This study develops a new MWI method, which employs a short repetition time adiabatic inversion recovery (STAIR) technique in combination with a commonly used fast spin echo (FSE) sequence and provides quantification of myelin water (MW) fractions.

Method

Whole-brain MWI was performed using the short repetition time adiabatic inversion recovery prepared-fast spin echo (STAIR-FSE) technique on eight healthy volunteers (mean age: 38±14 years, four-males) and seven patients with multiple sclerosis (MS) (mean age: 53.7±8.7 years, two-males) on a 3T clinical magnetic resonance imaging scanner. To facilitate the quantification of apparent myelin water fraction (aMWF), a proton density-weighted FSE was also used during the scans to allow total water imaging. The aMWF measurements of MS lesions and normal-appearing white matter (NAWM) regions in MS patients were compared with those measured in normal white matter (NWM) regions in healthy volunteers. Both the analysis of variance (ANOVA) test and paired comparison were performed for the comparison.

Results

The MW in the whole-brain was selectively imaged and quantified using the STAIR-FSE technique in all participants. MS lesions showed much lower signal intensities than NAWM in the STAIR-FSE images. ANOVA analysis revealed a significant difference in the aMWF measurements between the three groups. Moreover, the aMWF measurements in MS lesions were significantly lower than those in both NWM of healthy volunteers and NAWM of MS patients. Lower aMWF measurements in NAWM were also found in comparison with those in NWM.

Conclusions

The STAIR-FSE technique is capable of measuring aMWF values for the indirect detection of myelin loss in MS, thus facilitating clinical translation of whole brain MWI and quantification, which show great potential for the detection and evaluation of changes in myelin in the brain of patients with MS for future larger cohort studies.

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.

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.

Quantitative myelin water imaging using short TR adiabatic inversion recovery prepared echo-planar imaging (STAIR-EPI) sequence

Introduction

Numerous techniques for myelin water imaging (MWI) have been devised to specifically assess alterations in myelin. The biomarker employed to measure changes in myelin content is known as the myelin water fraction (MWF). The short TR adiabatic inversion recovery (STAIR) sequence has recently been identified as a highly effective method for calculating MWF. The purpose of this study is to develop a new clinical transitional myelin water imaging (MWI) technique that combines STAIR preparation and echo-planar imaging (EPI) (STAIR-EPI) sequence for data acquisition.

Methods

Myelin water (MW) in the brain has shorter T1 and T2 relaxation times than intracellular and extracellular water. In the proposed STAIR-EPI sequence, a short TR (e.g., ≤300 ms) together with an optimized inversion time enable robust long T1 water suppression with a wide range of T1 values [i.e., (600, 2,000) ms]. The EPI allows fast data acquisition of the remaining MW signals. Seven healthy volunteers and seven patients with multiple sclerosis (MS) were recruited and scanned in this study. The apparent myelin water fraction (aMWF), defined as the signal ratio of MW to total water, was measured in the lesions and normal-appearing white matter (NAWM) in MS patients and compared with those measured in the normal white matter (NWM) in healthy volunteers.

Results

As seen in the STAIR-EPI images acquired from MS patients, the MS lesions show lower signal intensities than NAWM do. The aMWF measurements for both MS lesions (3.6 ± 1.3%) and NAWM (8.6 ± 1.2%) in MS patients are significantly lower than NWM (10 ± 1.3%) in healthy volunteers (P < 0.001).

Discussion

The proposed STAIR-EPI technique, which can be implemented in MRI scanners from all vendors, is able to detect myelin loss in both MS lesions and NAWM in MS patients.

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.

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.

Feasibility of ultrashort echo time quantitative susceptibility mapping with a 3D cones trajectory in the human brain

Purpose

Quantitative susceptibility mapping (QSM) has surfaced as a promising non-invasive quantitative biomarker that provides information about tissue composition and microenvironment. Recently, ultrashort echo time quantitative susceptibility mapping (UTE-QSM) has been investigated to achieve QSM of short T2 tissues. As the feasibility of UTE-QSM has not been demonstrated in the brain, the goal of this study was to develop a UTE-QSM with an efficient 3D cones trajectory and validate it in the human brain.

Materials and methods

An ultrashort echo time (UTE) cones sequence was implemented in a 3T clinical MRI scanner. Six images were acquired within a single acquisition, including UTE and gradient recalled echo (GRE) images. To achieve QSM, a morphology-enabled dipole inversion (MEDI) algorithm was incorporated, which utilizes both magnitude and phase images. Three fresh cadaveric human brains were scanned using the 3D cones trajectory with eight stretching factors (SFs) ranging from 1.0 to 1.7. In addition, five healthy volunteers were recruited and underwent UTE-QSM to demonstrate the feasibility in vivo. The acquired data were processed with the MEDI-QSM pipeline.

Results

The susceptibility maps estimated by UTE-QSM showed reliable tissue contrast. In the ex vivo experiment, high correlations were found between the baseline (SF of 1.0) and SFs from 1.1 to 1.7 with Pearson's correlations of 0.9983, 0.9968, 0.9959, 0.9960, 0.9954, 0.9943, and 0.9879, respectively (all p-values < 0.05). In the in vivo experiment, the measured QSM values in cortical gray matter, juxtacortical white matter, corpus callosum, caudate, and putamen were 25.4 ± 4.0, -21.8 ± 3.2, -22.6 ± 10.0, 77.5 ± 18.8, and 53.8 ± 7.1 ppb, consistent with the values reported in the literature.

Conclusion

Ultrashort echo time quantitative susceptibility mapping enables direct estimation of the magnetic susceptibility in the brain with a dramatically reduced total scan time by use of a stretched 3D cones trajectory. This technique provides a new biomarker for susceptibility mapping in the in vivo brain.

Accelerated Quantitative 3D UTE-Cones Imaging Using Compressed Sensing

In this study, the feasibility of accelerated quantitative Ultrashort Echo Time Cones (qUTE-Cones) imaging with compressed sensing (CS) reconstruction is investigated. qUTE-Cones sequences for variable flip angle-based UTE T1 mapping, UTE adiabatic T1ρ mapping, and UTE quantitative magnetization transfer modeling of macromolecular fraction (MMF) were implemented on a clinical 3T MR system. Twenty healthy volunteers were recruited and underwent whole-knee MRI using qUTE-Cones sequences. The k-space data were retrospectively undersampled with different undersampling rates. The undersampled qUTE-Cones data were reconstructed using both zero-filling and CS reconstruction. Using CS-reconstructed UTE images, various parameters were estimated in 10 different regions of interests (ROIs) in tendons, ligaments, menisci, and cartilage. Structural similarity, percentage error, and Pearson’s correlation were calculated to assess the performance. Dramatically reduced streaking artifacts and improved SSIM were observed in UTE images from CS reconstruction. A mean SSIM of ~0.90 was achieved for all CS-reconstructed images. Percentage errors between fully sampled and undersampled CS-reconstructed images were below 5% for up to 50% undersampling (i.e., 2× acceleration). High linear correlation was observed (>0.95) for all qUTE parameters estimated in all subjects. CS-based reconstruction combined with efficient Cones trajectory is expected to achieve a clinically feasible scan time for qUTE imaging.

Articular Cartilage Assessment Using Ultrashort Echo Time MRI: A Review

Articular cartilage is a major component of the human knee joint which may be affected by a variety of degenerative mechanisms associated with joint pathologies and/or the aging process. Ultrashort echo time (UTE) sequences with a TE less than 100 µs are capable of detecting signals from both fast- and slow-relaxing water protons in cartilage. This allows comprehensive evaluation of all the cartilage layers, especially for the short T₂ layers which include the deep and calcified zones. Several ultrashort echo time (UTE) techniques have recently been developed for both morphological imaging and quantitative cartilage assessment. This review article summarizes the current catalog techniques based on UTE Magnetic Resonance Imaging (MRI) that have been utilized for such purposes in the human knee joint, such as T₁, T2∗ , T_1ρ, magnetization transfer (MT), double echo steady state (DESS), quantitative susceptibility mapping (QSM) and inversion recovery (IR). The contrast mechanisms as well as the advantages and disadvantages of these techniques are discussed.

Classification of certain vertebral degenerations using MRI image features

BACKGROUND AND OBJECTIVE

This article describes a fully automatic system for classifying various spinal degenerative phenotypes namely Modic changes, endplate defects and focal changes which are associated with lower back pain. These are obtained from T1/T2 Magnetic Resonance Imaging (MRI) scans. Lower back pain is a predominantly occurring ailment, which is prone to have various roots including the anatomical and pathophysciological aspects. Clinicians and radiologist use MRI to assess and evaluate the extent of damage, cause, and to decide on the future course of treatment. In large healthcare systems, to circumvent the manual reading of various image slices, we describe a system to automate the classification of various vertebral degeneracies that cause lower back pain.

METHODS

We implement a combination of feature extraction, image analysis based on geometry and classification using machine learning techniques for identifying vertebral degeneracies. Image features like local binary pattern, Hu's moments and gray level co-occurrence matrix (GLCM) based features are extracted to identify Modic changes, endplate defects, and presence of any focal changes. A combination of feature set is used for describing the extent of Modic change on the end plate. Feature sensitivity studies towards efficient classification is presented. A STIR based acute/chronic classification is also attempted in the current work.

RESULTS

The implemented method is tested and validated over a dataset containing 100 patients. The proposed framework for detecting the extent of Modic change achieves an accuracy of 85.91%. From the feature sensitivity analysis, it is revealed that entropy based measure obtained from gray level co-occurrence matrix alone is sufficient for detection of focal changes. The classification performance for detecting endplate defect is highly sensitive to the first 2 Hu's moments.

CONCLUSION

A novel approach to identify the allied vertebral degenerations and extent of Modic changes in vertebrae by exploiting image features and classification through machine learning is proposed. This shall assist radiologists in detecting abnormalities and in treatment planning.