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. 2020 Jul;28(7):2124-2138.
doi: 10.1007/s00167-019-05685-y. Epub 2019 Sep 13.

Anterior cruciate ligament grafts display differential maturation patterns on magnetic resonance imaging following reconstruction: a systematic review

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Anterior cruciate ligament grafts display differential maturation patterns on magnetic resonance imaging following reconstruction: a systematic review

Joseph A Panos et al. Knee Surg Sports Traumatol Arthrosc. 2020 Jul.

Abstract

Purpose: The appearance of anterior cruciate ligament (ACL) grafts on magnetic resonance imaging (MRI) is related to graft maturity and mechanical strength after ACL reconstruction (ACLR). Accordingly, the purpose of this review was to quantitatively analyze reports of serial MRI of the ACL graft during the first year following ACLR; the hypothesis tested was that normalized MRI signal intensity would differ significantly by ACL graft type, graft source, and postoperative time.

Methods: PubMed, Scopus, and CINAHL were searched for all studies published prior to June 2018 reporting MRI signal intensity of the ACL graft at multiple time points during the first postoperative year after ACLR. Signal intensity values at 6 and 12 months post-ACLR were normalized to initial measurements and analyzed using a least-squares regression model to study the independent variables of postoperative time, graft type, and graft source on the normalized MRI signal intensity.

Results: An effect of graft type (P = 0.001) with interactions of graft type * time (P = 0.012) and graft source * time (P = 0.001) were observed. Post hoc analyses revealed greater predicted normalized MRI signal intensity of patellar tendon autografts than both hamstring (P = 0.008) and hamstring with remnant preservation (P = 0.001) autografts at postoperative month 12.

Conclusion: MRI signal varies with graft type, graft source, and time after ACLR. Enhanced graft maturity during the first postoperative year was associated with hamstring autografts, with and without remnant preservation. Serial MRI imaging during the first postoperative year may be clinically useful to identify biologically or mechanically deficient ACL grafts at risk for failure.

Level of evidence: IV.

Keywords: Anterior cruciate ligament; Ligamentization; Magnetic resonance imaging; Signal–noise-quotient.

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Conflict of interest statement

Conflict of Interest The authors declare that they have no conflict of interest.

Figures

Fig. 1
Fig. 1
Literature search results. The most common reason for final exclusion from the quantitative analysis during tertiary review was the lack of serial imaging studies during the first postoperative year (descriptive synthesis; N = 20). Accordingly, all studies included in the quantitative analysis (N = 12) reported imaging studies at multiple time points during the first postoperative year
Fig. 2
Fig. 2
Validation of the weighted least-squares regression model. A significant effect of graft type (P = 0.001) and a significant interaction between time point*graft type (P = 0.016) and time point*graft source (P = 0.001) were observed on the normalized MRI signal intensity. As such, the model is supported by the strong correlation between observed versus predicted values of normalized MRI signal intensity (R2 = 0.697; P < 0.001). The coefficients for each level of the independent variables in the predicted normalized MRI signal intensity model are shown above
Fig. 3
Fig. 3
Predicted normalized MRI signal intensity by graft type and time point: autografts. HS-RP grafts were associated with decreased predicted normalized MRI signal intensity, an increased graft maturity, at all time points. Furthermore by 12 months postoperatively, predicted normalized MRI signal intensity was significantly greater in BPTB grafts compared to HS grafts without differences in HS versus HS-RP grafts (n.s.). These results suggest increasing graft maturation at 12 months in HS and HS-RP grafts compared to BPTB
Fig. 4
Fig. 4
Predicted normalized MRI graft signal intensity by graft type and time point: allografts. Allograft source increased predicted normalized MRI signal intensity at 12 months postoperatively (Fig. 2). In contrast to HS and BPTB autografts, there was not a significant difference between HS and BPTB allografts at 12 months; both graft types at this time point were significantly increased above the normalized ratio of 1, indicating a decrease in maturity. Furthermore, between 6 and 12 months BPTB predicted normalized MRI signal intensity significantly increased, suggesting a decrease in graft maturation during this time
Fig. 5
Fig. 5
Normalized MRI Signal Intensity Effect Sizes: Changes from baseline 2 and between 6 and 12 Months. The trends in the effects of normalized MRI signal intensity parallel those predicted by the experimental model. In Panel E, the effect for the change between 12 months and baseline is not significant, while the model predicts a significant decrease in normalized MRI signal intensity for HS autografts from the ratio of 1 at 12 months (Fig. 3). The observed difference between the model and effect size calculation in this trend could be due to variability in the normalized MRI signal, accounted for in the effect size calculation, but not the 1-sample T-test used to assess predicted normalized MRI signal intensity change from baseline

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