Ultrashort echo time magnetic resonance imaging (UTE-MRI) techniques have been increasingly used to assess cortical bone microstructure. High resolution micro computed tomography (μCT) is routinely employed for validating the MRI-based assessments. However, water protons in cortical bone may reside in micropores smaller than the detectable size ranges by μCT. The goal of this study was to evaluate the upper limit of UTE-MRI and compare its efficacy to μCT at determining bone porosity ex vivo. This study investigated the correlations between UTE-MRI based quantifications and histomorphometric measures of bone porosity that cover all pores larger than 1μm. Anterior tibial midshaft specimens from eleven donors (51±16 years old, 6 males, 5 females) were scanned on a clinical 3T-MRI using UTE magnetization transfer (UTE-MT, three power levels and five frequency offsets) and UTE-T2* sequences. Two-pool MT modeling and bicomponent exponential T2* fitting were performed on the MRI datasets. Specimens were then scanned by μCT at 9μm voxel size. Histomorphometry was performed on hematoxylin and eosin (H&E) stained slides imaged at submicron resolution. Macromolecular fraction from MT modeling, bi-component T2* fractions, and short component T2* showed strong correlations (R>0.7, P<0.01) with histomorphometric total and large-pores (>40μm) porosities as well as with μCT-based porosity. UTE-MRI could also assess small pores variations with moderate correlations (R>0.5, P<0.01). The UTE-MRI techniques can detect variations of bone porosity comprised of pores below the range detectable by μCT. Such fine pore variations can contribute differently to the development of bone diseases or to the bone remodeling process, however, this needs to be investigated. In scanned specimens, major porosity changes were from large pores, therefore the μCT employment was likely adequate to validate UTE-MRI biomarkers.

Bone stress injury (BSI) incidents have been increasing amongst athletes in recent years as a result of more intense sporting activities. Cortical bone in the tibia and fibula is one of the most common BSI sites. Nowadays, clinical magnetic resonance imaging (MRI) is the recommended technique for BSI diagnosis at an early stage. However, clinical MRI focuses on edema observations in surrounding soft tissues, rather than the injured components of the bone. Specifically, both normal and injured bone are invisible in conventional clinical MRI. In contrast, ultrashort echo time (UTE)-MRI is able to detect the rapidly decaying signal from the bone. This study aimed to employ UTE-MRI for fatigue fracture detection in fibula cortical bone through an ex vivo investigation. Fourteen human fibular samples (47 ± 20 years old, four women) were subjected to cyclic loading on a four-point bending setup. The loading was displacement controlled to induce -5000 ± 1500 μ-strain at 4 Hz. Loading was stopped when bone stiffness was reduced by 20%. Fibula samples were imaged twice, using UTE-MRI and micro-computed tomography (μCT), first pre-loading and second post-loading. After loading, the macromolecular fraction (MMF) from UTE-MT modeling demonstrated a significant decrease (12% ± 20%, P = 0.02) on average. Single-component T * also decreased significantly by BSI (12% ± 11%, P = 0.01) on average. MMF reduction is hypothesized to be a result of collagenous matrix rupture and water increase. However, faster T * decay might be a result of water shifts towards newly developed microcracks with higher susceptibility. Despite this good sensitivity level of the UTE-MRI technique, the μCT-based porosity at a voxel size of 9 μm was not affected by loading. UTE-MRI shows promise as a new quantitative technique to detect BSI.

The collagen density is not detected in the patellar tendon (PT), posterior cruciate ligament (PCL), and anterior cruciate ligament (ACL) in clinic. We assess the technical feasibility of three-dimension multiecho fat saturated ultrashort echo time cones (3D FS-UTE-Cones) acquisitions for single- and bicomponent T2⁎ analysis of bound and free water pools in PT, PCL, and ACL in clinic. The knees of five healthy volunteers and six knee joint samples from cadavers were scanned via 3D multiecho FS-UTE-Cones acquisitions on a clinical scanner. Single-component fitting of T2⁎M and bicomponent fitting of short T2⁎ (T2⁎S), long T2⁎ (T2⁎L), short T2⁎ fraction (Frac_S), and long T2⁎ fraction (Frac_L) were performed within tendons and ligaments. Our results showed that biexponential fitting was superior to single-exponential fitting in PT, PCL, and ACL. For knee joint samples, there was no statistical difference among all data in PT, PCL, and ACL. For volunteers, all parameters of bicomponent fitting were statistically different across PT, PCL, and ACL, except for T2⁎S, T2⁎L, and T2⁎M resulting in flawed measurements due to the magic angle effect. 3D multiecho FS-UTE-Cones acquisition allows high resolution T2⁎ mapping in PT, PCL, and ACL of keen joint samples and PT and PCL of volunteers. The T2⁎ values and their fractions can be characterized by bicomponent T2⁎ analysis that is superior to single-component T2⁎ analysis, except for ACL of volunteers.

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In early stages of tendon disease, mechanical properties may become altered prior to changes in morphological anatomy. Ultrashort echo time (UTE) magnetic resonance imaging (MRI) can be used to directly detect signal from tissues with very short T2 values, including unique viscoelastic tissues such as tendons. The purpose of this study was to use UTE sequences to measure T2*, T1 and magnetization transfer ratio (MTR) variations of tendon samples under static tensile loads. Six human peroneal tendons were imaged before and under static loading using UTE sequences on a clinical 3T MRI scanner. Tendons were divided into two static tensile loading groups: group A that underwent one-step loading (15 N) and group B that underwent two-step loading (15 and 30 N). The T2*, T1 and MTR variations were investigated in two selected ROIs, including whole and core sections. Mean T2* values for the first step of loading (groups A and B) in both whole section and core section regions of interest (ROIs) were significantly decreased by 13 ± 7% (P=0.028) and 16 ± 5% (P=0.017), respectively. For the second loading step (group B), there was a consistent, but non-significant reduction in T2* value by 9 ±2% (P=0.059) and 7 ± 5% (P=0.121) for whole and core sections, respectively. Mean T1 did not show any consistent changes for either loading steps (P>0.05). Mean MTR increased slightly, but not significantly for both loading steps (P>0.05). Significant differences were found only in T2* values of tendons by static tensile load application. Therefore, T2* monitoring during loading is suggested for quantitative investigation of the tendons biomechanics.

Objective To utilize the 3D Inversion Recovery prepared Ultrashort-Echo-Time with Cones Readout (IR-UTE-Cones) MRI technique for direct imaging of lamellar bone with comparison to the gold standard of computed tomography (CT). Materials and Methods CT and MRI was performed on 11 shoulder specimens and 3 patients. Five specimens had imaging performed before and after glenoid fracture (osteotomy). 2D and 3D volume-rendered CT images were reconstructed and conventional T1-weighted and 3D IR-UTE-Cones MRI techniques were performed. Glenoid widths and defects were independently measured by two readers using the circle method. Measurements were compared with those made from 3D CT datasets. Paired-sample Student’s t tests and intraclass correlation coefficients were performed. In addition, 2D CT and 3D IR-UTE-Cones MRI datasets were linearly registered, digitally overlaid, and compared in consensus by these two readers. Results Compared with the reference standard (3D CT), glenoid bone diameter measurements made on 2D CT and 3D IR-UTE-Cones were not significantly different for either reader whereas T1-weighted images underestimated the diameter (mean difference of 0.18 cm, p=0.003 and 0.16 cm, p=0.022 for readers 1 and 2, respectively). However, mean margin of error for measuring glenoid bone loss was small for all modalities (range 1.46-3.92%). All measured ICCs were near perfect. Digitally registered 2D CT and 3D IR-UTE-Cones MRI datasets yielded essentially perfect congruity between the two modalities. Conclusion The 3D IR-UTE-Cones MRI technique selectively visualizes lamellar bone, produces similar contrast to 2D CT imaging, and compares favorably to measurements made using 2D and 3D CT.

Ultrashort TE (UTE) sequences have the capability to image tissues with very short T2s that typically appear as low signal in clinical sequences. UTE sequences can also be used in multi-echo acquisitions which allow assessment of the T2s of these tissues. Here we study the accuracy of such T2 measurements when combined with fat saturation (FS).

Background The gold standard for mapping nerve fiber orientation in white matter of the human brain is histological analysis through biopsy. Such mappings are a crucial step in validating non-invasive techniques for assessing nerve fiber orientation in the human brain by using diffusion MRI. However, the manual extraction of nerve fiber directions of histological slices is tedious, time consuming, and prone to human error. New Method The presented semi-automated algorithm first creates a binary-segmented mask of the nerve fibers in the histological image, and then extracts an estimate of average directionality of nerve fibers through a Fourier-domain analysis of the masked image. It also generates an uncertainty level for its estimate of average directionality. Results and Comparison with Existing Methods The average orientations of the semi-automatic method were first compared to a qualitative expert opinion based on visual inspection of nerve fibers. A weighted RMS difference between the expert estimate and the algorithmically-determined angle (weighted by expert's confidence in his estimate) was 15.4 degrees, dropping to 9.9 degrees when only cases with an expert confidence level of greater than 50% were included. The algorithmically-determined angles were then compared with angles extracted using a manual segmentation technique, yielding an RMS difference of 11.2 degrees. Conclusion The presented semi-automated method is in good agreement with both qualitative and quantitative manual expert-based approaches for estimating directionality of nerve fibers in white matter from images of stained histological slices of the human brain.