Introduction

The anterior cruciate ligament (ACL) is comprised of a predominantly parallel arrangement of collagen fibers. Organized collagen fibers can change significantly with ACL injury and overuse. Age-related overuse injuries can also result in collagen fiber disorganization, disruption, and neovascularization which can impair the normal joint’s performance (1). These changes often can be detected semi-qualitatively using clinical MRI, based on the local signal changes in the tissue (1). Quantitative MRI-based assessment of ACL has been challenging, firstly because clinical MRI is not capable of imaging normal ACL with high signal due to short T2 (1,2), and secondly because the common quantitative MRI measures like T2 and T1ρ are orientation sensitive and affected by magic angle phenomena (3). Ultrashort echo time MRI (UTE-MRI) can be used to image the ACL (at TE<50 μs) for quantitative assessment (2,4,5). We have developed a new T1ρ sequence using an adiabatic inversion recovery spin-lock pulse cluster followed by Cones data acquisition (3D UTE-Ad-T1ρ) (6). Adiabatic pulses provide a robust spin-lock and can achieve a uniform inversion, which is widely used to create image contrast. Recent studies show that adiabatic spin-lock has the potential for orientation-insensitive T1ρ measurement (7–9). This study aims to investigate the correlations between the UTE-Ad-T1ρ biomarker (5) and mechanical properties in human ACL specimens. This study highlights the potential applications of UTE-Ad-T1ρ technique to noninvasively assess the mechanical properties of human ACL.

Methods

ACL specimens were harvested from thirteen fresh-frozen human cadaveric knee joints (50±21 years old, 2 female and 11 male donors). ACL specimens were soaked in phosphate-buffered saline (PBS) for 2 hours before MRI scans to ensure rehydration after potential drying throughout the sample preparation. Specimens were scanned on a 3T MRI (MR750, GE Healthcare Technologies, WI) scanner using a Mayo Clinic BC-10 T/R birdcage coil. ACL specimens were placed perpendicular to B0. A set of 3D UTE-Ad-T1ρ sequences with seven different spin-locking times (TSLs) (TSL= 0, 2, 4, 6, 8, 12 and 16 ms) were performed. Other imaging parameters included: rectangular RF excitation pulse with a duration of 26 µs, repetition time (TR)=500 ms, echo time (TE)=0.032 ms, flip angle (FA)=10˚, field of view (FOV) = 70 mm × 70 mm, matrix=300×300, slice thickness=1 mm, number of slices=46, receiver bandwidth=±62.5 kHz. T1ρ value was calculated for each specimen using a single-component exponential fitting model (MRI signal decay over increasing TSL). After MRI scans, specimens were washed with PBS before running mechanical tests. Specimens were trimmed into 7×5 mm2 approximate cross-sections (one specimen per donor) and fixed into the grippers (distance between grippers was 15mm) of an in-house developed benchtop uniaxial loading device. After initial alignment and preloading, a 1-mm tensile displacement was applied at 2 mm/min rate and the maximum applied force was recorded. Average maximum mechanical stress was calculated by the maximum load divided by ACL cross-section. The average maximum strain was 0.067 (i.e., 1 mm / 15 mm). The average tensile elastic modulus was calculated by average maximum stress divided by average maximum strain. Pearson’s correlation coefficient between UTE-Ad-T1ρ and average tensile elastic modulus was calculated. Data analysis was performed in MATLAB (2017, The Mathworks Inc., MA).

Results

Figure 1a shows the UTE-Ad-T1ρ MRI image of the thirteen ACL specimens in axial plane. Figures 2a and 2b show the T1ρ fitting results for two representative ACL specimens from a 27-year-old-male and a 44-year-old-female donor, respectively. Figures 3 demonstrates the scatter plot and linear regression analysis of the average elastic modulus on UTE-Ad-T1ρ. The correlation between T1ρ and mechanical measures was significant and strong (R=-0.81, p<0.01).

Discussion

Our developed UTE-Ad-T1ρ MRI technique predicted the mechanical properties of the ACL with a significant strong correlation. This study highlighted the UTE-Ad-T1ρ technique as a useful quantitative method to assess ACL mechanical properties. Future studies will be required to investigate the correlations between our MRI biomarkers as measured in vivo compared with arthroscopic measures.

Conclusion

The presented UTE technique can predict mechanical properties of human ACL. Such an MRI technique with low magic angle sensitivity may help diagnose ACL injuries and monitor ACL graft maturation.

Acknowledgements

The authors acknowledge grant support from NIH (R21AR073496, R01AR075825, 2R01AR062581, 1R01 AR068987), VA Clinical Science and Rehabilitation R&D Awards (I01CX001388 and I01RX002604), and JSPS KAKENHI Grant Number JP18KK0104.

References

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