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∗, T1ρ, 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.

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.

IntroductionAlthough 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.MethodsTwenty 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.ResultsThe 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.ConclusionThe 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.

PurposeQuantitative 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 methodsAn 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.ResultsThe 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.ConclusionUltrashort 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.

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-T 1 mapping, UTE-T 2 * mapping, and UTE-based quantitative susceptibility mapping (UTE-QSM)] as well as with a clinical T 2 mapping sequence on a 3T clinical MR system. For T 1 mapping, a variable flip angle (VFA) method based on actual flip angle imaging (AFI) technique was utilized. For T 2 * 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 (R 2 >0.99), while the clinical T 2 parameter showed impaired linearity (R 2 =0.87). In the ex vivo mouse experiment, UTE-T 2 * mapping and UTE-QSM showed feasibility in the detection of injected stem cells with high contrast, whereas UTE-T 1 and UTE-T 2 * 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 T 2 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 T 2 mapping in detecting stem cells with high contrast.