The signal intensity of preoperative magnetic resonance imaging has predictive value for determining the arthroscopic reparability of the anterior talofibular ligament

Abstract

PurposeArthroscopic all‐inside anterior talofibular ligament (ATFL) repair is a common surgical technique for chronic ankle instability (CAI), and the condition of the ATFL remnants is associated with its reparability. ATFL reparability can affect the clinical course, but the relationship between magnetic resonance imaging (MRI) findings and the intraoperative ATFL reparability is still unclear. The purpose of this study was to investigate the relationship between ATFL signal intensities according to MRI and intraoperative ATFL reparability. MethodsThis study included 55 cases of CAI (n = 37) and osteochondral lesion of the talus (n = 18) that underwent MRI followed by subsequent arthroscopy. MRI signal intensity was measured preoperatively to calculate the signal to noise ratio (SNR). During arthroscopy, the presence of an ATFL tear was checked and the ATFL tension was classified as taut, mild laxity, or laxity; ATFL quality was classified as excellent (normal), moderate (abnormal but reparable), or poor (irreparable). It was then analyzed whether there was a relationship between the intraoperative findings and the SNR. ResultsThe mean SNR was 23.4 ± 21.6. The SNR was significantly different according to the presence of an ATFL tear and ATFL tension and quality (all P = 0.001). The SNR was better correlated with ATFL quality (r = 0.708) than the presence of a tear (r = 0.545) or degree of tension (r = 0.653). The diagnostic SNR cutoff point to distinguish a normal ATFL from an abnormal but reparable ATFL was 11.2, and that to distinguish between an irreparable and reparable ATFL, was 32.3. ConclusionThe SNR, representing MRI signal intensities, is highly correlated with the intraoperative measures of the ATFL. Therefore, the SNR had predictive value for determining the arthroscopic reparability of the ATFL. Level of evidenceLevel III.

Platelet-rich plasma, a biomaterial, for the treatment of anterior talofibular ligament in lateral ankle sprain

“…For each case, two slices were typically chosen for SNR measurements, which were then averaged to determine the final SNR value. The diagnostic SNR cutoff point for distinguishing between normal and abnormal but reparable ATFL was 11.2, and it took 32.3 to distinguish between an irreparable and reparable ATFL (Ahn et al, 2021).…”

“…The results revealed that the good ATFL condition group had a higher rate of return to sports than the poor ATFL condition group did, who had higher SNR values. According to ATFL tension and quality, Ahn et al also demonstrated that a low SNR evaluated by preoperative MRI predicted better ATFL reparability and that the SNR had predictive value to assess the ATFL reparability utilizing the arthroscopic all-inside ATFL repair procedure (Ahn et al, 2021). They confirmed that the diagnostic SNR cutoff point for differentiating between an aberrant but repairable ATFL and a normal ATFL was 11.2, and that it was 32.3 for differentiating between an irreparable ATFL and a repairable ATFL.…”

“…They discovered that ankles with chronic instability had a higher ATFL SNR than healthy stable ankles, and that the mean ATFL SNR value decreased after repair surgery, implying that the ATFL SNR could be used to assess ligament tissue quality Li et al, 2019). Ahn et al also demonstrated that the SNR was more closely connected to ATFL quality than the presence of a tear or the degree of strain (Ahn et al, 2021).…”

Imaging Modalities to Diagnose, Follow, and Assess Treatment of Chronic Ankle Instability

“…9). Ahn et al56 reviewed the signal intensity of the ATFL in 55 patients with ankle instability and correlated findings to the degree of tension found during arthroscopy and discovered that the lower signal intensity of the ligament predicted better ATFL repairability with respect to tension and quality. Animal models have shown that the signal intensity of a ligament correlates to the vascularity and tensile strength 57,58.…”

Computer-Aided Ankle Ligament Injury Diagnosis from Magnetic Resonance Images Using Machine Learning Techniques

“…Moreover, low accuracy is also observed in many studies [ 12 , 13 , 14 ] which could be due to the fact that it is a static exam used to study a structure that performs dynamic joint control. Further, it can potentially produce false negatives for ligament lesions, which would occur if the ligament was subjected to a yo-yo effect [ 11 , 13 , 15 , 16 , 17 , 18 ]. While staying at rest, it would exhibit a normal morphological structure, but leads to increased fiber elasticity, caused by a bad local collagen quality or quantity [ 19 ].…”