Abstract
Background:
Magnetic resonance–based measurements of signal intensity have been used to track healing of surgically treated anterior cruciate ligaments (ACLs). However, it is unknown how the signal intensity values in different regions of the ligament or graft change during healing.
Hypothesis:
1) Normalized signal intensity of the healing graft or repaired ACL is heterogenous, 2) temporal changes in normalized signal intensity values differ between the tibial, middle and femoral regions, and 3) there are no differences in regional normalized signal intensity values 2 years postoperatively between grafts, repaired ACLs and contralateral native ACLs.
Study Design:
Cohort Study
Methods:
MR images of patients from a trial comparing ACL reconstruction (ACLR; n=35) with bridge-enhanced ACL repair (REPAIR; n=65) were analyzed. The ACLs were segmented from images acquired at 6, 12 and 24 months postoperatively, and were then partitioned into three sections (femoral, middle and tibial) along the longitudinal axis. Linear mixed modeling was used to compare location specific differences in normalized ligament signal intensity between time points (6, 12 and 24 months) and groups (ACLR, REPAIR, and contralateral native ACL).
Results:
For grafts, the middle region had a higher mean normalized signal intensity compared to the femoral region at all time points (p<.01), but was only greater than the tibial region at 6 months (p<.01). For repaired ACLs, the middle region had a higher mean normalized signal intensity compared to the femoral region at all time points (p<.01), but was only greater than the tibial region at 6 and 12 months (p<.04). From 6 to 24 months, the grafts showed the greatest reduction in normalized signal intensity in the femoral and middle regions (p<.01 compared to tibial regions) while there were no regional differences in repaired ACLs. At 2 years after surgery, repaired ACLs had a lower normalized signal intensity in the tibial region compared to reconstructed grafts and contralateral native ACLs (p<.01).
Conclusion:
The results suggest that graft remodeling is location specific, while the repaired ACLs were more homogenous with lower or comparable normalized signal intensity values at 2 years compared to the contralateral native ACL and reconstructed grafts.
Keywords: ACL MRI Signal Intensity, Remodeling, Healing, ACL Reconstruction, ACL Repair
INTRODUCTION
The graft remodeling process after anterior cruciate ligament (ACL) reconstruction surgery has been a hot topic of investigation due to its importance in guiding post-operative care and determining the time for safe return to sports. However, the challenges in direct assessment of healing tissue’s structural properties using conventional techniques (i.e. mechanical testing, histology) in human subjects are major roadblocks, and have been primarily limited to animal models.1–3,5–7,12 However, the biomechanical, biological and functional differences between animal models and human subjects hinders the translation of those findings to the clinical care of ACL injured patients. More importantly, much of the prior research has focused on ACL reconstruction with very little on recently developed alternatives such as biologically augmented suture repair to induce ACL healing.19
Magnetic resonance (MR) imaging can address some of the limitations associated with conventional structural analysis, owing to its non-invasive nature. MR-based assessment of connective tissue, in particular ligaments and tendons, has gained attention. Previous preclinical1–3,5–7,12 and clinical4,13–16,20 studies have used MR imaging to assess surgically treated ligament quality and its associations with a range of clinical, functional and patient-reported outcomes. In addition to the healing ligament size (i.e., length, cross-sectional area and volume), ligament signal intensity has been used as a surrogate for tissue quality (e.g., collagen organization, tensile strength) with lower signal (i.e. a darker appearance) indicative of a more organized and mature ligament.1–3,5–7,12
A systematic review identified 34 studies using a measure of ACL signal (e.g., signal-to-ratio and signal intensity) for tracking graft remodeling after ACL reconstruction.25 While this review highlights the growing interest in using MR imaging to study ACL healing, the results appear to be inconsistent between studies, which the authors attribute to variations in scanner hardware, image acquisition parameters, and signal interpretation methods.25
Another possible reason for such variability could be the location of the regions of interest (ROI) selected to quantify the ACL signal. Previous studies often use 2-dimensional ROIs to measure ACL signal in a single slice or across several slices.14–17,21 Other studies have used the overall ACL signal intensity (i.e. median or mean) across the entire 3-dimensional geometry of the ACL.4,13,20,26 However, little is known about signal variations across the ACL and how they may influence MR-based assessments of ACL healing. Prior experimental reports on regional variations in native ACL mechanical properties (e.g., differences between ACL bundles),8,9,23,24 highlight the possibility of regional differences in MRI signal across the ACL. Such variations could significantly impact the use of MR imaging to assess healing of the surgically treated ACL, and thus deserve thorough investigation.
In this study, a 3-dimensional quantitative MR imaging approach was used to longitudinally evaluate location-dependent variations in ACL signal intensity within 2 years after ACL reconstruction and bridge-enhanced ACL repair.19 We also analyzed the regional differences in the native ACL MR images obtained from the contralateral knees of the recruited subjects. We hypothesized that: 1) the normalized signal intensity of the reconstructed graft or repaired ACL is heterogenous, with different normalized signal intensities between the tibial (bottom third), middle (middle third) and femoral (upper third) regions, 2) there are longitudinal postoperative changes in normalized signal intensity across the tibial, middle and femoral regions, and 3) there are no differences in regional normalized signal intensity values 2 years after surgery between the reconstructed grafts, repaired ACLs, and contralateral native ACLs.
METHODS
Participants
The imaging data were obtained from the “BEAR II” trial (IDE G150268, IRB P00021470, NCT 02664545).19 All patients granted their informed consent prior to participating. One hundred patients, ages 13 to 35, who presented with a complete ACL tear, were less than 45 days from injury, had closed physes, and had at least 50% of the length of the ACL attached to the tibia (as determined from a pre-operative MR image) were randomized in an approximate 2:1 ratio to undergo either the scaffold-enhanced ACL repair procedure (REPAIR group, n=65, 57% female, age: 17 [16 – 20] years), or autograft ACL reconstruction (ACLR group, n=35, 54% female, age: 17 [15 – 23] years). The 2:1 enrollment ratio was utilized to maximize the chances of the trial picking up relatively rare adverse events after the bridge-enhanced ACL repair procedure, while maintaining sufficient a priori power to detect clinically significant differences between treatment groups in the primary outcome measures. Prior to randomization, the surgeons reported which graft type they would select for the patient if they were randomized to the ACL reconstruction group. Randomization was stratified by the surgeon’s preference for autograft source (hamstring or bone-patellar tendon-bone) and administered by the research coordinators using sealed envelopes from the statistician. Patients were excluded from enrollment if they had a history of prior ipsilateral knee surgery, history of prior knee infection, or had risk factors that could adversely affect ligament healing (nicotine/tobacco use, corticosteroids in the past six months, chemotherapy, diabetes, inflammatory arthritis). Patients were also excluded if they had a displaced bucket handle tear of the medial meniscus requiring repair. All other meniscal injuries were included. Patients were also excluded if they had a full thickness chondral injury, a grade III MCL injury, a concurrent complete patellar dislocation, or an operative posterolateral corner injury. A detailed description of the trial along with clinical and functional outcomes have been previously reported.19
Surgical Procedures
ACL reconstruction with autograft tendon (ACLR):
A standard hamstring autograft procedure was performed using a quadruple semitendinosus-gracilis graft (n=33) or central third bone-patellar tendon-bone autograft (n=2) using a continuous-loop cortical button (Endobutton; Smith & Nephew, Andover, MA) for proximal fixation and a bioabsorbable interference screw (BioRCI HA; Smith & Nephew) for tibial fixation. A minimal notchplasty was performed at the surgeon’s discretion if needed for adequate visualization of the posterior notch for placement of the femoral tunnel starting point within the prior ACL footprint. The intra-articular locations of the tibial and femoral tunnels were through the tibial and femoral footprints respectively. The femoral tunnel was drilled using various techniques including an anteromedial portal technique and a flexible drill system technique (Clancy Anatomic Cruciate Guide, Smith & Nephew).
Bridge-Enhanced ACL Repair (REPAIR):
A knee arthroscopy was performed, and any meniscal injuries were treated if present. A tibial aimer (ACUFEX Director Drill Guide; Smith and Nephew, Andover, MA) was used to place a 2.4 mm guide pin through the tibia and the tibial footprint of the ACL. The pin was over-drilled with a 4.5 mm reamer (Endoscopic Drill; Smith & Nephew, Andover, MA). A notchplasty was performed using a combination of a shaver and a curette to facilitate visualization of the femoral footprint. A guide pin was then placed in the femoral ACL footprint, drilled through the femur and then over-drilled with the 4.5 mm reamer. A 4 cm arthrotomy was made at the medial border of the patellar tendon and a whip stitch of #2 absorbable braided suture (Vicryl; Ethicon, Cincinnati, OH) was placed into the tibial stump of the torn ACL. Two #2 non-absorbable braided sutures (Ethibond; Ethicon, Cincinnati OH) were looped through the two center holes of a cortical button (Endobutton; Smith & Nephew, Andover, MA). The free ends of a #2 absorbable braided suture from the tibial stump were passed through the cortical button, which was then passed through the femoral tunnel and engaged on the lateral femoral cortex. Both looped sutures of #2 non-absorbable braided (four matched ends) were passed through the scaffold, and 10 cc of autologous blood obtained from the antecubital vein was added to the scaffold. The scaffold was then passed up along the sutures into the femoral notch and the non-absorbable braided sutures were passed through the tibial tunnel and tied over a second cortical button on the anterior tibial cortex with the knee in full extension. The remaining pair of suture ends coming through the femur were tied over the femoral cortical button to bring the ACL stump into the scaffold using an arthroscopic surgeon’s knot and knot pusher.19
Post-operative rehabilitation
An identical physical therapy protocol, adapted from that of the Multicenter Orthopaedics Outcomes Network (MOON)27,28 was provided to all patients. For all patients, a locking hinged brace (TScope; Breg, Carlsbad, CA) was applied post-operatively to limit joint range of motion between 0 to 50 degrees of knee flexion for 2 weeks, and from 0 to 90 degrees for the next four weeks, unless they had a concomitant meniscal repair, in which case the brace range was restricted to 0 to 40 degrees for the first 4 weeks post-operatively before increasing to 0 to 90 degrees of flexion. Use of a locking hinge brace to restrict range of motion for the first six weeks after surgery is the standard of care for ACL reconstruction at our institution. All patients were provided with a cold therapy unit (Iceman, DJO Global, Vista CA). Both groups were partial weight bearing for 2 weeks, then weight bearing as tolerated with crutches until 4 weeks. Use of a functional ACL brace (CTi brace; OSSUR, Orange County, CA) was recommended from 6 to 12 weeks and then for cutting and pivoting sports for 2 years after surgery. Patients were cleared for return to sport at the operating surgeon’s discretion after completing an IKDC Subjective Score, hamstring and quadriceps strength measurement and bilateral hop testing at the 6-month visit.
MR Imaging and Outcomes
MR images were acquired from surgically treated knees at 6, 12 and 24 months postoperatively. The native ACLs from the contralateral knees were also scanned at least once during the follow-up visits (6, 12, or 24 months), depending on MR magnet availability. We used the first available contralateral knee MRI to analyze the contralateral native ACL. A 3T scanner (Tim Trio, Siemens, Erlangen, Germany) and a 15-channel knee coil were used to scan the knees using a 3D Constructive Interference in Steady State (CISS) sequence (TR/TE=14/7 msec, FA=35, 16cm FOV, 80x512x512 (slice x frequency x phase)) in the sagittal plane. The surgically treated ligaments and the contralateral native ACLs were manually segmented (Figure 1) using image processing software (Mimics v17.0; Materialize, Belgium). Segmentation was performed by outlining the ACL from the sagittal slices due to the better spatial resolution of the image in that plane. The coronal and axial views were used to adjust the segmented masks when required. The segmentation was done by an experienced investigator (AMK) with a high intra-rater reliability (ICC>0.9 for segmenting intact and surgically treated ACL).10,11,13 The segmented masks of the ACLs and grafts from each knee were exported as 3D point clouds along with their corresponding grayscale values. The exported data were then processed with a custom written program (Matlab R2019a; Mathworks, Natick, MA) to partition the segmented ligaments into three equal regions (femoral, middle and tibial), along the ligament’s longitudinal axis (Figure 1). The average grayscale value of each region was then normalized to the subject-specific grayscale value of the femoral cortical bone to normalize the signal intensity for each ligament or graft.13,20
Figure 1.
3D segmentation of the ACL from MR image stacks and partitioning ACL into three equal regions across its length, each covering a third of ACL length.
Statistical Analysis
Linear mixed modeling (LMM) was used to study location (tibial, middle, and femoral) specific differences in the normalized ligament signal intensity at 6, 12 and 24 months after surgery and in contralateral native ACLs. Separate analyses were done for each group (i.e., ACLR, REPAIR and native). For the surgically treated ligaments, the changes in normalized signal intensity of each region from 6 months to 24 months postoperatively were also calculated and compared across regions using LMM analysis. The normalized signal intensity across each region (tibial, middle and femoral) at 24 months after surgery were compared between the groups (ACLR, REPAIR and native) using LMM analysis. Tukey Multiple Comparison Tests were used when performing post-hoc analyses. The unavailable MR images (i.e., due to loss to follow up, noisy images or revised ACLR) were handled as missing data by the LMM. Data are presented as Mean±Standard Deviation. Two-sided p-values are reported and considered significant when p<.05. Analyses were performed using statistical software (Prism v9.0, GraphPad Software Inc).
RESULTS
Most patients (98% 6 months, 97% 12 months, 93% 24 months) successfully completed their MR visits. A total of 43 MR images were not included in the analyses due to loss to follow-up (n=14), revision surgery prior to the MRI visit (n=11), noisy MR image precluding accurate assessment of signal intensity (n=10), and patients who had a surgically treated contralateral ACL (n=8). The final analyses included 96 image sets at 6 months (32 ACLR, 64 REPAIR), 91 image sets at 12 months (30 ACLR, 61 REPAIR), 80 image sets at 24 months (25 ACLR, 55 REPAIR), and 90 image sets from contralateral native ACLs (6 months = 78, 12 months = 15, 24 months = 3). Representative MR images of the native ACL, ACLR and REPAIR are presented in Figure 2.
Figure 2.
Representative sagittal MR images of (Left) native ACL, (Middle) ACLR, and (Right) REPAIR obtained from the CISS sequence.
Reconstructed ACL Grafts (ACLR)
For the reconstructed grafts, the middle region had the highest average normalized signal intensity 6 months after surgery (Figure 3A). On average, the normalized signal intensity of the middle region was higher than that of the tibial (by 21.3%; p<.01) and femoral (by 12.2%; p<.01) regions. The average normalized signal intensity in the femoral region was higher than that of the tibial region (by 9.8%; p=.04). At 12 months, the average normalized signal intensity of the middle region remained higher than that of the femoral region (by 24.7%; p<.01). There was no difference in the average normalized signal intensity of the reconstructed grafts between the middle and tibial regions (p=.10; Figure 3B). The average normalized signal intensity of the tibial region was higher than that of the femoral region (by 16.7%; p<.01). At 24 months, the regional differences approached those of the native contralateral ACL with the highest average normalized signal intensity value in the tibial region (Figure 3C). On average, the normalized signal intensity of the tibial region was higher than that of the femoral region (by 33.5%; p<.01). While there was no detectable difference between tibial and middle regions (p=.21), the normalized signal intensity of the middle region was higher than that of the femoral region (by 24.8%; p<.01). Compared to the tibial region, the longitudinal changes in normalized signal intensity from 6 to 24 months was higher (more negative) in the middle (p<.01) and femoral (p<.01) regions (Figure 3D). There was no difference in longitudinal changes in normalized signal intensity from 6 to 24 months between the middle and femoral regions (p=.56).
Figure 3.
Regional differences in average normalized signal intensity of the reconstructed ligament at 6 months (A), 12 months (B) and 24 months (C) as well as 6 to 24 months change (D) after ACL reconstruction. Mean ± standard deviation. SI, normalized signal intensity.
Repaired ACL (REPAIR)
Six months after bridge-enhanced ACL repair, the middle region had the highest average normalized signal intensity (Figure 4A). On average, the normalized signal intensity of the middle region was higher than those of the tibial (by 10.3%; p<.01) and femoral (by 16.4%; p<.001) regions. There was no difference in the average normalized signal intensity between the tibial and femoral regions at 6 months (p=.08; Figure 4A). At 12 months, the average normalized signal intensity of the middle region was higher than those of the tibial (by 7.8%; p=.03) and femoral regions (by 18.2%; p<.01; Figure 4B). The average normalized signal intensity of the tibial region was higher than that of the femoral region at 12 months (by 9.6%; p=.01). At 24 months, the only significant difference was the higher average normalized signal intensity value in the middle region compared to that of the femoral region (by 16.4%; p<.01). There were no differences in the average normalized signal intensity between the tibial and middle regions and between the tibial and femoral regions of the repaired ACLs at 24 months (p>.05; Figure 4C). There were no regional differences in the longitudinal changes in average normalized signal intensity from 6 months to 24 months (p>0.3 for all comparisons; Figure 4D).
Figure 4.
Regional differences in average normalized signal intensity of the repaired ACL at 6 months (A), 12 months (B) and 24 months (C) as well as 6 to 24 months change (D) after bridge-enhanced ACL repair procedure. Mean ± standard deviation. SI, normalized signal intensity.
Native ACL
For the contralateral native ACLs, there was a gradual reduction in average normalized signal intensity from tibial region to femoral region (Figure 5). On average, normalized signal intensity of the tibial regions was significantly higher than the middle region (by 16.0%; p<.01) and femoral region (by 38.7%; p<.01). The average normalized signal intensity of the middle region was higher than that of the femoral region (by 19.5%; p<.01).
Figure 5.
Regional differences in average normalized signal intensity of the native ACL. Mean ± standard deviation. SI, normalized signal intensity.
Group Differences at 24 Months
At 24 months after surgery, the repaired ACLs had a lower normalized signal intensity in the tibial region compared to the reconstructed grafts and contralateral native ACLs (p<.01 for all comparisons; Figure 6A). There were no differences in mean normalized signal intensity of the tibial region between the reconstructed grafts and contralateral native intact ACLs (p=.17). There were no group differences in the mean normalized signal intensity of the middle and femoral regions (p>.6 for all comparisons; Figure 6B–C).
Figure 6.
Group differences in regional average normalized signal intensity of the native ACL, reconstructed graft and repaired ACLs at 24 months after surgery. Mean ± standard deviation. SI, normalized signal intensity.
DISCUSSION
The current findings support our first hypothesis as we found differences in the mean ACL or graft normalized signal intensity values across the tibial, middle, and femoral regions after surgical treatment. The findings partially support our second hypothesis showing no regional differences in the changes in normalized signal intensity of the repaired ACLs, in contrast to regional differences seen in the reconstructed grafts. The findings also partially support our third hypothesis as there were no group differences in normalized signal intensity of the middle and femoral regions 2 years postoperatively in contrast to lower tibial normalized signal intensity in the repaired ACLs compared to the reconstructed grafts and contralateral native ACLs. We also observed significant regional differences in normalized signal intensity of native ACL. Considering prior associations between MR-based normalized signal intensity and experimentally measured mechanical and histological properties of the ACL,1–3,5–7,12 our current observations suggest location-specific ACL graft healing and remodeling occur within the first 2 years after ACL reconstruction and repair. Our findings also highlight the importance of location and ROI selection for more accurate and consistent assessments of ACL structural properties based on its MR-based signal intensity
Among studies investigating ACL graft structure and remodeling using MR imaging, some have reported signal measurements from different locations of the ACL graft.14–16,18,21 Studies by Li and colleagues reported the signal-to-noise quotient (SNQ), another method to normalize graft signal intensity, at the femoral, middle and tibial regions from a single mid-sagittal slice.14–16 While their results showed regional differences in SNQ,14–16 none of the studies reported statistical comparisons of average SNQ between the three regions. Using a similar approach, Ma et al showed significant variations in graft SNQ at the proximal, middle and distal region of the graft at 6 months after ACL reconstruction and found the highest SNQ in the middle region compared to the distal and proximal regions.18 A recent study by Warth et al used ultrashort-T2 MR imaging and 3D analysis to map the longitudinal changes in ACL graft within the first year after surgery in 10 patients.26 Their results suggested differences in average T2* measurements between the proximal half and distal half of the grafts, which were not statistically compared. Most recently, Putnis and colleagues used discrete 2-dimensional measurements to investigate regional differences in relative ACL graft to posterior cruciate ligament signal ratio (SIR) in reconstructed knees 1 year after surgery.21 They showed significant differences in graft SIR with highest signal in the middle region and lowest signal in the femoral aperture.21 Our current findings confirms those prior observations and provide additional insights into how regional differences in normalized signal intensity can change differently within the first two year after ACL reconstruction or bridge-enhanced ACL repair.
In the current study, we used MR images of 100 subjects to assess regional differences in the surgically treated ACL and the native ACL using a 3-dimensional approach. Our findings found the highest normalized signal intensity (inferior tissue quality) values in the middle region in the graft at 6 months with similar normalized signal intensity values between femoral and tibial regions. However, the minimal changes (10%) in normalized signal intensity of the tibial region in contrast to those of the middle (45%) and femoral (49%) regions resulted in a different signal profile at 24 months with highest normalized signal intensity at tibial region, which then gradually decreased towards middle and femoral regions. The observed signal distribution at 24 months after ACL reconstruction resembled the pattern seen in the native ACL, which also has a consistent signal drop from the tibial to femoral regions. Similar to grafts, the repaired ACLs also had a heterogenous signal distribution at 6 months with the highest normalized signal intensity seen in the middle region, which corresponded to the location of the injury and wound healing after surgical repair. However, this pattern remained relatively unchanged until 24 months, owing to comparable reductions in normalized signal intensity (remodeling) across all three regions (35% - 38%). Interestingly, at 2 years after surgery, the repaired ACLs had a lower normalized signal intensity (i.e., more organized tissue) compared to the reconstructed grafts and native ACLs. These observations highlight the potential of the bridge-enhanced ACL repair to restore the MR-based ACL signal intensity across the length of the ACL. However, further studies are needed to investigate the biomechanical and functional implications of such homogeneity compared to heterogenous reconstructed grafts.
Our current observations agree with prior reports of regional differences in intact ACL mechanical properties measured ex vivo8,9,23,24 and differences in intact ACL T2 and T2* relaxation times measured from MR imaging.22 Our findings are also in line with prior studies showing significant changes in ACL signal following surgical treatment, with overall reductions in normalized signal intensity from 6 to 24 months after surgery, which is indicative of substantial tissue remodeling (i.e., ligamentization for reconstructed grafts and wound healing for repaired ACLs). However, these findings offer new insight into heterogeneity of the structural properties of the surgically treated ACL and how these regional differences vary within 2 years after surgery. These observed regional differences in normalized signal intensity highlights the importance of measurement of regional signal intensity across the whole ligament in contrast to limited ROI assessment (e.g., from the middle of the ligament in a single MRI slice). Such consideration could help with improved measurement reliability and may lead to lower variations between studies.25 The observed regional differences in graft remodeling in contrast to homogenous remodeling seen in the repaired ACLs warrants further investigation. These observations cumulatively suggest that in addition to the quantified signal intensity, the pattern of signal distribution may play an important role in capturing postoperative changes in surgically treated ACLs.
There were several limitations to this study. First, the majority of the ACLR patients were treated with a four-stranded hamstring autografts except for the two that received bone-patellar tendon-bone autografts. The low number of bone-patellar tendon-bone grafts limits the generalizability of the reported findings to graft types other than autograft hamstring and highlights the need for future studies to assess regional differences in signal intensity between graft types. Moreover, we only evaluated patients undergoing ACL reconstruction with a single bundle graft; thus, the results cannot be extrapolated to patients who have had a double bundle ACL reconstruction. Second, the contralateral knee images were obtained at one of three time points after the study, rather than at all three time points to minimize imaging time. The subjects that had more than one contralateral scan had relatively consistent MRI values; however, we did not rigorously evaluate this and a more systematic, dedicated acquisition of the contralateral knee images may be required to detect temporal changes in the contralateral knee. Third, signal intensity magnitude depends on the hardware, sequence, image acquisition parameters and normalization process, which were varied between prior studies, and thus hampered our ability to directly compare the results between the prior studies and our own. Work is currently underway to optimize imaging sequences and normalization techniques to minimize differences between hardware and sequences. Nonetheless, normalized signal intensity measures obtained using the same hardware and sequence within a study provides insight into the integrity of the healing ligament or graft. Fourth, the current study is a secondary analysis of the available imaging data from BEAR Trial with no a priori power analysis to evaluate regional changes in signal intensity. 19 However post-hoc power analysis indicates that we had 80% power to detect 0.15 unit differences in normalized signal intensity. Finally, our findings indicate the existence of regional signal differences but do not offer insight into mechanisms responsible for such differences. Further studies are required to confirm these observations and to identify factors contributing to observed signal heterogeneity. Follow up studies are also required to investigate the effect of signal heterogeneity in outcomes of ACL surgery, and potentially risk of re-injury.
Conclusion
The MRI-based assessment of ACL structure and its changes after surgical treatment are location specific. At early stages of healing after surgery, the middle section of the ACL was the least organized (highest signal) in both surgical groups. The grafts presented the least organized tissue in the tibial region and the most organized in the femoral region at 2 years after surgery. Grafts also undergo significant remodeling in the femoral and middle regions, compared to the tibial region, where as the remodeling of the repaired ACLs are mostly homogenous with comparable degree of signal reduction (tissue organization) across all three regions.
ACKNOWLEDGEMENTS:
We would like to acknowledge the significant contributions of the clinical trial team including Bethany Trainor. We would also like to acknowledge the contributions of our medical safety monitoring team of Joseph DeAngelis, Peter Nigrovic, and Carolyn Hettrich, our data monitors Maggie Malsch, Meghan Fitzgerald, and Erica Denhoff, as well as the clinical care team for the trial patients, including Kathryn Ackerman, Alyssa Aguiar, Judd Allen, Michael Beasley, Jennifer Beck, Dennis Borg, Jeff Brodeur, Stephanie Burgess, Melissa Christino, Sarah Collins, Gianmichel Corrado, Sara Carpenito, Corey Dawkins, Pierre D’Hemecourt, Jon Ferguson, Michele Flannery, Casey Gavin, Ellen Geminiani, Stacey Gigante, Annie Griffin, Emily Hanson, Elspeth Hart, Jackie Hastings, Pamela Horne-Goffigan, Christine Gonzalez, Meghan Keating, Elizabeth KillKelly, Elizabeth Kramer, Pamela Lang, Hayley Lough, Chaimae Martin, Michael McClincy, William Meehan, Ariana Moccia, Jen Morse, Mariah Mullen, Stacey Murphy, Emily Niu, Michael O’Brien, Nikolas Paschos, Katrina Plavetsky, Bridget Quinn, Shannon Savage, Edward Schleyer, Benjamin Shore, Cynthia Stein, Andrea Stracciolini, Dai Sugimoto, Dylan Taylor, Ashleigh Thorogood, Kevin Wenner, Brianna Quintiliani, and Natasha Trentacosta. We would also like to thank the perioperative and operating room staff and the members of the Department of Anesthesia who were extremely helpful in developing the perioperative and intraoperative protocols. We would also like to acknowledge the efforts of other scaffold manufacturing team members, including Gabe Perrone, Gordon Roberts, Doris Peterkin, and Jakob Sieker. We are also grateful for the study design guidance provided by the Division of Orthopedic Devices at the Center for Devices and Radiological Health at the U.S. Food and Drug Administration under the guidance of Laurence Coyne and Mark Melkerson, particularly the efforts of Casey Hanley, Peter Hudson, Jemin Dedania, Pooja Panigrahi, and Neil Barkin. Lastly, we would like to acknowledge funding support from the Translational Research Program at Boston Children’s Hospital, the Children’s Hospital Orthopaedic Surgery Foundation, the Children’s Hospital Sports Medicine Foundation and the National Institutes of Health and the National Institute of Arthritis and Musculoskeletal and Skin Diseases through grant numbers R01-AR065462 and R01-AR056834. This research was also conducted with support from the Football Players Health Study at Harvard University. The Football Players Health Study is funded by a grant from the National Football League Players Association. The content is solely the responsibility of the authors and does not necessarily represent the official views of Harvard Medical School, Harvard University or its affiliated academic health care centers, the National Football League Players Association, Boston Children’s Hospital or the National Institutes of Health. We are also especially grateful to the patients and their families who participated in this study, their willingness to participate in research that may help others in the future inspires all of us.
Disclosures:
This study received funding support from the Translational Research Program at Boston Children’s Hospital, the Children’s Hospital Orthopaedic Surgery Foundation, the Children’s Hospital Sports Medicine Foundation, the Football Players Health Study at Harvard University, and the National Institutes of Health and the National Institute of Arthritis and Musculoskeletal and Skin Diseases through grants R01-AR065462 and R01-AR056834. M.M.M. is a founder, paid consultant, and equity holder in Miach Orthopaedics, Inc, which was formed to work on upscaling production of the BEAR scaffold. M.M.M. maintained a conflict-of-interest management plan that was approved by Boston Children’s Hospital and Harvard Medical School during the conduct of the trial, with oversight by both conflict-of-interest committees and the institutional review board of Boston Children’s Hospital, as well as the US Food and Drug Administration. B.C.F. is an assistant editor for The American Journal of Sports Medicine, the spouse of M.M.M. with the inherently same conflicts. A.M.K. is a paid consultant for Miach Orthopaedics, Inc, maintained a conflict-of-interest management plan that was approved by Boston Children’s Hospital and Harvard Medical School during the conduct of the trial, with oversight by both conflict-of-interest committees and the institutional review board of Boston Children’s Hospital. For the BEAR Trial Team, D.E.K., L.J.M., and Y.-M.Y. all have disclosures as listed in the American Academy of Orthopaedic Surgeons database, none of which are related to this current project or technology. These include educational payments from Kairos Surgical (D.E.K., Y.-M.Y.) and food, beverage, and travell reimbursements from 5 companies (each <$500). L.J.M. also has received multiple payments for food and beverage from various companies. B.P. has manufactured the scaffolds used in the trials at Boston Children’s Hospital and is a paid consultant and equity holder in Miach Orthopaedics at this time, as he assists with transfer of the manufacturing process to the contract manufacturing organization that Miach has engaged to do the manufacturing. N.S. has manufactured scaffolds used in the trials at Boston Children’s Hospital and is a paid consultant for Miach Orthopaedics. B.P. and N.S. maintain a conflict-of-interest management plan that was approved by Boston Children’s Hospital and Harvard Medical School during the conduct of the trial, with oversight by both conflict-of-interest committees and the institutional review board of Boston Children’s Hospital
REFERENCES
- 1.Beveridge JE, Machan JT, Walsh EG, et al. Magnetic resonance measurements of tissue quantity and quality using T2 * relaxometry predict temporal changes in the biomechanical properties of the healing ACL. J Orthop Res. 2018;36(6):1701–1709. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Beveridge JE, Proffen BL, Karamchedu NP, et al. Cartilage Damage Is Related to ACL Stiffness in a Porcine Model of ACL Repair. J Orthop Res. 2019;37(10):2249–2257. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Beveridge JE, Walsh EG, Murray MM, Fleming BC. Sensitivity of ACL volume and T2( *) relaxation time to magnetic resonance imaging scan conditions. J Biomech. 2017;56:117–121. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Biercevicz AM, Akelman MR, Fadale PD, et al. MRI volume and signal intensity of ACL graft predict clinical, functional, and patient-oriented outcome measures after ACL reconstruction. Am J Sports Med. 2015;43(3):693–699. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Biercevicz AM, Miranda DL, Machan JT, Murray MM, Fleming BC. In Situ, noninvasive, T2*-weighted MRI-derived parameters predict ex vivo structural properties of an anterior cruciate ligament reconstruction or bioenhanced primary repair in a porcine model. Am J Sports Med. 2013;41(3):560–566. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Biercevicz AM, Murray MM, Walsh EG, et al. T2 * MR relaxometry and ligament volume are associated with the structural properties of the healing ACL. J Orthop Res. 2014;32(4):492–499. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Biercevicz AM, Proffen BL, Murray MM, Walsh EG, Fleming BC. T2* relaxometry and volume predict semi-quantitative histological scoring of an ACL bridge-enhanced primary repair in a porcine model. J Orthop Res. 2015;33(8):1180–1187. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Butler DL, Guan Y, Kay MD, et al. Location-dependent variations in the material properties of the anterior cruciate ligament. J Biomech. 1992;25(5):511–518. [DOI] [PubMed] [Google Scholar]
- 9.Castile RM, Skelley NW, Babaei B, Brophy RH, Lake SP. Microstructural properties and mechanics vary between bundles of the human anterior cruciate ligament during stress-relaxation. J Biomech. 2016;49(1):87–93. [DOI] [PubMed] [Google Scholar]
- 10.Flannery SW, Kiapour AM, Edgar DJ, et al. A transfer learning approach for automatic segmentation of the surgically treated anterior cruciate ligament. J Orthop Res. 2021. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Flannery SW, Kiapour AM, Edgar DJ, Murray MM, Fleming BC. Automated magnetic resonance image segmentation of the anterior cruciate ligament. J Orthop Res. 2020. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Fleming BC, Vajapeyam S, Connolly SA, Magarian EM, Murray MM. The use of magnetic resonance imaging to predict ACL graft structural properties. J Biomech. 2011;44(16):2843–2846. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Kiapour AM, Ecklund K, Murray MM, et al. Changes in Cross-sectional Area and Signal Intensity of Healing Anterior Cruciate Ligaments and Grafts in the First 2 Years After Surgery. Am J Sports Med. 2019;47(8):1831–1843. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Li H, Chen J, Li H, Wu Z, Chen S. MRI-based ACL graft maturity does not predict clinical and functional outcomes during the first year after ACL reconstruction. Knee Surg Sports Traumatol Arthrosc. 2017;25(10):3171–3178. [DOI] [PubMed] [Google Scholar]
- 15.Li H, Chen S, Tao H, Li H, Chen S. Correlation Analysis of Potential Factors Influencing Graft Maturity After Anterior Cruciate Ligament Reconstruction. Orthop J Sports Med. 2014;2(10):2325967114553552. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Li H, Tao H, Cho S, et al. Difference in graft maturity of the reconstructed anterior cruciate ligament 2 years postoperatively: a comparison between autografts and allografts in young men using clinical and 3.0-T magnetic resonance imaging evaluation. Am J Sports Med. 2012;40(7):1519–1526. [DOI] [PubMed] [Google Scholar]
- 17.Ma Y, Murawski CD, Rahnemai-Azar AA, et al. Graft maturity of the reconstructed anterior cruciate ligament 6 months postoperatively: a magnetic resonance imaging evaluation of quadriceps tendon with bone block and hamstring tendon autografts. Knee Surg Sports Traumatol Arthrosc. 2015;23(3):661–668. [DOI] [PubMed] [Google Scholar]
- 18.Matringe M, Camadro JM, Labbe P, Scalla R. Protoporphyrinogen oxidase inhibition by three peroxidizing herbicides: oxadiazon, LS 82-556 and M&B 39279. FEBS Lett. 1989;245(1-2):35–38. [DOI] [PubMed] [Google Scholar]
- 19.Murray MM, Fleming BC, Badger GJ, et al. Bridge-Enhanced Anterior Cruciate Ligament Repair Is Not Inferior to Autograft Anterior Cruciate Ligament Reconstruction at 2 Years: Results of a Prospective Randomized Clinical Trial. Am J Sports Med. 2020;48(6):1305–1315. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Murray MM, Kiapour AM, Kalish LA, et al. Predictors of Healing Ligament Size and Magnetic Resonance Signal Intensity at 6 Months After Bridge-Enhanced Anterior Cruciate Ligament Repair. Am J Sports Med. 2019;47(6):1361–1369. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Putnis SE, Oshima T, Klasan A, et al. Magnetic Resonance Imaging 1 Year After Hamstring Autograft Anterior Cruciate Ligament Reconstruction Can Identify Those at Higher Risk of Graft Failure: An Analysis of 250 Cases. Am J Sports Med. 2021:363546521995512. [DOI] [PubMed] [Google Scholar]
- 22.Schmitz RJ, Wang H-M, Kraft RA, et al. Regional differences in anterior cruciate ligament imaging biomarkers: T2 and T2* values. Muscles, Ligaments & Tendons Journal (MLTJ). 2018;8(2). [Google Scholar]
- 23.Skelley NW, Castile RM, Cannon PC, et al. Regional Variation in the Mechanical and Microstructural Properties of the Human Anterior Cruciate Ligament. Am J Sports Med. 2016;44(11):2892–2899. [DOI] [PubMed] [Google Scholar]
- 24.Skelley NW, Castile RM, York TE, et al. Differences in the microstructural properties of the anteromedial and posterolateral bundles of the anterior cruciate ligament. Am J Sports Med. 2015;43(4):928–936. [DOI] [PubMed] [Google Scholar]
- 25.Van Dyck P, Zazulia K, Smekens C, et al. Assessment of Anterior Cruciate Ligament Graft Maturity With Conventional Magnetic Resonance Imaging: A Systematic Literature Review. Orthop J Sports Med. 2019;7(6):2325967119849012. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Warth RJ, Zandiyeh P, Rao M, et al. Quantitative Assessment of In Vivo Human Anterior Cruciate Ligament Autograft Remodeling: A 3-Dimensional UTE-T2* Imaging Study. Am J Sports Med. 2020;48(12):2939–2947. [DOI] [PubMed] [Google Scholar]
- 27.Wright RW, Preston E, Fleming BC, et al. A systematic review of anterior cruciate ligament reconstruction rehabilitation: part I: continuous passive motion, early weight bearing, postoperative bracing, and home-based rehabilitation. J Knee Surg. 2008;21(3):217–224. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Wright RW, Preston E, Fleming BC, et al. A systematic review of anterior cruciate ligament reconstruction rehabilitation: part II: open versus closed kinetic chain exercises, neuromuscular electrical stimulation, accelerated rehabilitation, and miscellaneous topics. J Knee Surg. 2008;21(3):225–234. [DOI] [PMC free article] [PubMed] [Google Scholar]