Regional Differences in Anterior Cruciate Ligament Signal Intensity After Surgical Treatment

LigaNET: A multi-modal deep learning approach to predict the risk of subsequent anterior cruciate ligament injury after surgery

Anterior cruciate ligament (ACL) injuries are a common cause of soft tissue injuries in young active individuals, leading to a significant risk of premature joint degeneration. Postoperative management of such injuries, in particular returning patients to athletic activities, is a challenge with immediate and long-term implications including the risk of subsequent injury. In this study, we present LigaNET, a multi-modal deep learning pipeline that predicts the risk of subsequent ACL injury following surgical treatment. Postoperative MRIs (n=1,762) obtained longitudinally between 3 to 24 months after ACL surgery from a cohort of 159 patients along with 11 non-imaging outcomes were used to train and test: 1) a 3D CNN to predict subsequent ACL injury from segmented ACLs, 2) a 3D CNN to predict injury from the whole MRI, 3) a logistic regression classifier predict injury from non-imaging data, and 4) a multi-modal pipeline by fusing the predictions of each classifier. The CNN using the segmented ACL achieved an accuracy of 77.6% and AUROC of 0.84, which was significantly better than the CNN using the whole knee MRI (accuracy: 66.6%, AUROC: 0.70; P<.001) and the non-imaging classifier (accuracy: 70.1%, AUROC: 0.75; P=.039). The fusion of all three classifiers resulted in highest classification performance (accuracy: 80.6%, AUROC: 0.89), which was significantly better than each individual classifier (P<.001). The developed multi-modal approach had similar performance in predicting the risk of subsequent ACL injury from any of the imaging sequences (P>.10). Our results demonstrate that a deep learning approach can achieve high performance in identifying patients at high risk of subsequent ACL injury after surgery and may be used in clinical decision making to improve postoperative management (e.g., safe return to sports) of ACL injured patients.

Early MRI-based quantitative outcomes are associated with a positive functional performance trajectory from 6 to 24 months post-ACL surgery

PURPOSE

Quantitative magnetic resonance imaging (qMRI) has been used to determine the failure properties of ACL grafts and native ACL repairs and/or restorations. How these properties relate to future clinical, functional, and patient-reported outcomes remain unknown. The study objective was to investigate the relationship between non-contemporaneous qMRI measures and traditional outcome measures following Bridge-Enhanced ACL Restoration (BEAR). It was hypothesized that qMRI parameters at 6 months would be associated with clinical, functional, and/or patient-reported outcomes at 6 months, 24 months, and changes from 6 to 24 months post-surgery.

METHODS

Data of BEAR patients (n = 65) from a randomized control trial of BEAR versus ACL reconstruction (BEAR II Trial; NCT02664545) were utilized retrospectively for the present analysis. Images were acquired using the Constructive Interference in Steady State (CISS) sequence at 6 months post-surgery. Single-leg hop test ratios, arthrometric knee laxity values, and International Knee Documentation Committee (IKDC) subjective scores were determined at 6 and 24 months post-surgery. The associations between traditional outcomes and MRI measures of normalized signal intensity, mean cross-sectional area (CSA), volume, and estimated failure load of the healing ACL were evaluated based on bivariate correlations and multivariable regression analyses, which considered the potential effects of age, sex, and body mass index.

RESULTS

CSA (r = 0.44, p = 0.01), volume (r = 0.44, p = 0.01), and estimated failure load (r = 0.48, p = 0.01) at 6 months were predictive of the change in single-leg hop ratio from 6 to 24 months in bivariate analysis. CSA (βstandardized = 0.42, p = 0.01), volume (βstandardized = 0.42, p = 0.01), and estimated failure load (βstandardized = 0.48, p = 0.01) remained significant predictors when considering the demographic variables. No significant associations were observed between MRI variables and either knee laxity or IKDC when adjusting for demographic variables. Signal intensity was also not significant at any timepoint.

CONCLUSION

The qMRI-based measures of CSA, volume, and estimated failure load were predictive of a positive functional outcome trajectory from 6 to 24 months post-surgery. These variables measured using qMRI at 6 months post-surgery could serve as prospective markers of the functional outcome trajectory from 6 to 24 months post-surgery, aiding in rehabilitation programming and return-to-sport decisions to improve surgical outcomes and reduce the risk of reinjury.

LEVEL OF EVIDENCE

Level II.

Ecological and Specific Evidence-Based Safe Return To Play After Anterior Cruciate Ligament Reconstruction In Soccer Players: A New International Paradigm

Existing return to play (RTP) assessments have not demonstrated the ability to decrease risk of subsequent anterior cruciate ligament (ACL) injury after reconstruction (ACLR). RTP criteria are standardized and do not simulate the physical and cognitive activity required by the practice of sport. Most RTP criteria do not include an ecological approach. There are scientific algorithms as the "5 factor maximum model" that can identify risk profiles and help reduce the risk of a second anterior cruciate ligament injury. Nevertheless, these algorithms remain too standardized and do not include the situations experienced in games by soccer players. This is why it is important to integrate ecological situations specific to the environment of soccer players in order to evaluate players under conditions closest to their sporting activity, especially with high cognitive load. One should identify high risk players under two conditions: Clinical analyses commonly include assessments such as isokinetic testing, functional tests (hop tests, vertical force-velocity, profile), running, clinical assessments (range of motion and graft laxity), proprioception and balance (Star Excursion Balance Test modified, Y-Balance, stabilometry) and psychological parameters (kinesophobia, quality of life and fear of re-injury). Field testing usually includes game simulation, evaluation under dual-task conditions, fatigue and workload analysis, deceleration, timed-agility-test and horizontal force-velocity profiles. Although it seems important to evaluate strength, psychological variables and aerobic and anaerobic capacities, evaluation of neuromotor control in standard and ecological situations may be helpful for reducing the risk of injury after ACLR. This proposal for RTP testing after ACLR is supported by the scientific literature and attempts to approximate the physical and cognitive loads during a soccer match. Future scientific investigation will be required to demonstrate the validity of this approach.

Level of Evidence

5.

Three-dimensional magnetic resonance imaging analysis shows sex-specific patterns in changes in anterior cruciate ligament cross-sectional area along its length

Smaller anterior cruciate ligament (ACL) size in females has been hypothesized to be a key contributor to a higher incidence of ACL tears in that population, as a lower cross-sectional area (CSA) directly corresponds to a larger stress on the ligament for a given load. Prior studies have used a mid-length CSA measurement to quantify ACL size. In this study, we used magnetic resonance imaging to quantify the CSA along the entire length of the intact ACL. We hypothesized that changes in the ACL CSA along its length would have different patterns in males and females. We also hypothesized that changes in ACL CSA along its length would be associated with body size or knee size with different associations in females and males. MR images of contralateral ACL-intact knees of 108 patients (62 females, 13-35 years) undergoing ACL surgery were used to measure the CSA along the ACL length, using a custom program. For both females and males, the largest CSA was located at 37%-39% of ACL length from the tibial insertion. Compared to females, males had a significantly larger CSA only within the distal 41% of the ACL (p < 0.001). ACL CSA was associated with patient height and weight in males (r > 0.3; p < 0.05), whereas it was associated with intercondylar notch width in females (r > 0.3; p < 0.05). These findings highlight the importance of standardizing the location of measurement of ACL CSA.

Automated segmentation of the healed anterior cruciate ligament from T2 * relaxometry MRI scans

Collagen organization of the anterior cruciate ligament (ACL) can be evaluated using T2 * relaxometry. However, T2 * mapping requires manual image segmentation, which is a time-consuming process and prone to inter- and intra- segmenter variability. Automating segmentation would address these challenges. A model previously trained using Constructive Interference in Steady State (CISS) scans was applied to T2 * segmentation via transfer learning. It was hypothesized that there would be no significant differences in the model's segmentation performance between T2 * and CISS, structural measures versus ground truth manual segmentation, and reliability versus independent and retest manual segmentation. Transfer learning was conducted using 54 T2 * scans of the ACL. Segmentation performance was assessed with Dice coefficient, precision, and sensitivity, and structurally with T2 * value, volume, subvolume proportions, and cross-sectional area. Model performance relative to independent manual segmentation and repeated segmentation by the ground truth segmenter (retest) were evaluated on a random subset. Segmentation performance was analyzed with Mann-Whitney U tests, structural measures with Wilcoxon signed-rank tests, and performance relative to manual segmentation with repeated-measures analysis of variance/Tukey tests (α = 0.05). T2 * segmentation performance was not significantly different from CISS on all measures (p > 0.35). No significant differences were detected in structural measures (p > 0.50). Automatic segmentation performed as well as the retest on all segmentation measures, whereas independent segmentations were lower than retest and/or automatic segmentation (p < 0.023). Structural measures were not significantly different between segmenters. The automatic segmentation model performed as well on the T2 * sequence as on CISS and outperformed independent manual segmentation while performing as well as retest segmentation.

Quantitative MRI Biomarkers to Predict Risk of Reinjury Within 2 Years After Bridge-Enhanced ACL Restoration

BACKGROUND

Quantitative magnetic resonance imaging (qMRI) methods were developed to establish the integrity of healing anterior cruciate ligaments (ACLs) and grafts. Whether qMRI variables predict risk of reinjury is unknown.

PURPOSE

To determine if qMRI measures at 6 to 9 months after bridge-enhanced ACL restoration (BEAR) can predict the risk of revision surgery within 2 years of the index procedure.

STUDY DESIGN

Cohort study; Level of evidence, 2.

METHODS

Originally, 124 patients underwent ACL restoration as part of the BEAR I, BEAR II, and BEAR III prospective trials and had consented to undergo an MRI of the surgical knee 6 to 9 months after surgery. Only 1 participant was lost to follow-up, and 4 did not undergo MRI, leaving a total of 119 patients for this study. qMRI techniques were used to determine the mean cross-sectional area; normalized signal intensity; and a qMRI-based predicted failure load, which was calculated using a prespecified equation based on cross-sectional area and normalized signal intensity. Patient-reported outcomes (International Knee Documentation Committee subjective score), clinical measures (hamstring strength, quadriceps strength, and side-to-side knee laxity), and functional outcomes (single-leg hop) were also measured at 6 to 9 months after surgery. Univariate and multivariable analyses were performed to determine the odds ratios (ORs) for revision surgery based on the qMRI and non-imaging variables. Patient age and medial posterior tibial slope values were included as covariates.

RESULTS

In total, 119 patients (97%), with a median age of 17.6 years, underwent MRI between 6 and 9 months postoperatively. Sixteen of 119 patients (13%) required revision ACL surgery. In univariate analyses, higher International Knee Documentation Committee subjective score at 6 to 9 months postoperatively (OR = 1.66 per 10-point increase; P = .035) and lower qMRI-based predicted failure load (OR = 0.66 per 100-N increase; P = .014) were associated with increased risk of revision surgery. In the multivariable model, when adjusted for age and posterior tibial slope, the qMRI-based predicted failure load was the only significant predictor of revision surgery (OR = 0.71 per 100 N; P = .044).

CONCLUSION

Quantitative MRI-based predicted failure load of the healing ACL was a significant predictor of the risk of revision within 2 years after BEAR surgery. The current findings highlight the potential utility of early qMRI in the postoperative management of patients undergoing the BEAR procedure.

Changes in the Cross-Sectional Profile of Treated Anterior Cruciate Ligament Within 2 Years After Surgery

Background:

The cross-sectional area (CSA) of the anterior cruciate ligament (ACL) and reconstructed graft has direct implications on its strength and knee function. Little is known regarding how the CSA changes along the ligament length and how those changes vary between treated and native ligaments over time.

Hypothesis:

It was hypothesized that (1) the CSA of reconstructed ACLs and restored ACLs via bridge-enhanced ACL restoration (BEAR) is heterogeneous along the length. (2) Differences in CSA between treated and native ACLs decrease over time. (3) CSA of the surgically treated ACLs is correlated significantly with body size (ie, height, weight, body mass index) and knee size (ie, bicondylar and notch width).

Study Design:

Cohort study; Level of evidence, 2.

Methods:

Magnetic resonance imaging scans of treated and contralateral knees of 98 patients (n = 33 ACL reconstruction, 65 BEAR) at 6, 12, and 24 months post-operation were used to measure the ligament CSA at 1% increments along the ACL length (tibial insertion, 0%; femoral insertion, 100%). Statistical parametric mapping was used to evaluate the differences in CSA between 6 and 24 months. Correlations between body and knee size and treated ligament CSA along its length were also assessed.

Results:

Hamstring autografts had larger CSAs than native ACLs at all time points (P < .001), with region of difference decreasing from proximal 95% of length (6 months) to proximal 77% of length (24 months). Restored ACLs had larger CSAs than native ACLs at 6 and 12 months, with larger than native CSA only along a small midsubstance region at 24 months (P < .001). Graft CSA was correlated significantly with weight (6 and 12 months), bicondylar width (all time points), and notch width (24 months). Restored ACL CSA was significantly correlated with bicondylar width (6 months) and notch width (6 and 12 months).

Conclusion:

Surgically treated ACLs remodel continuously within the first 2 years after surgery, leading to ligaments/grafts with heterogeneous CSAs along the length, similar to the native ACL. While reconstructed ACLs remained significantly larger, the restored ACL had a CSA profile comparable with that of the contralateral native ACL. In addition to size and morphology differences, there were fundamental differences in factors contributing to CSA profile between the ACL reconstruction and BEAR procedures.

Registration:

NCT 02664545 (ClinicalTrials.gov identifier).