MRI Allows Accurate Measurement of Glenoid Bone Loss

Abstract

Background: Bony Bankart lesions larger than a certain size can lead to a high redislocation rate, despite treatment with Bankart repair. Detection and measurement of glenoid bone loss play key roles in selecting the appropriate surgical therapy in patients with shoulder instability. There is controversy about which diagnostic modalities, using different measurement methods, provide the best diagnostic validity.

Questions/purposes: (1) What are the diagnostic accuracies of true AP radiographs, West Point (WP) view radiographs, MRI, and CT to detect glenoid bone loss? (2) Are there differences in the measurements of glenoid bone loss on MRI and CT? (3) What are the intrarater and interrater reliabilities of CT and MRI to measure glenoid bone loss?

Methods: Between August 2012 and February 2017, we treated 80 patients for anterior shoulder instability. Of those, we considered patients with available preoperative true AP radiographs, WP radiographs, CT images, and MR images of the affected shoulder as potentially eligible. Based on that, 63% (50 of 80) of patients were eligible for analysis; 31% (25 of 80) were excluded because not all planes or slices (such as sagittal, axial, or frontal) of each diagnostic imaging modalities were available and 7% (5 of 80) because of the insufficient quality of diagnostic images (for example, setting of the layers did not allow adequate en face view of the glenoid). Preoperative true AP radiographs, WP radiographs, CT images and MR images of the affected shoulders were retrospectively assessed for the presence of glenoid bone loss by two blinded observers at a median (range) 25 months (12 to 66) postoperatively. To evaluate sensitivity, specificity, positive predictive value, negative predictive value, accuracy, diagnostic odds ratio, positive likelihood ratio, negative likelihood ratio, and area under the curve (AUC), we compared the detection of glenoid bone loss at follow-up achieved with the aforementioned imaging modalities with intraoperative arthroscopic detection. In all patients with glenoid bone loss, two blinded observers measured the size of the glenoid bone loss on preoperative CT and MR images using six measuring techniques: depth and length of the glenoid bone loss, Bigliani classification, best-fit circle width loss method, AP distance method, surface area method, and Gerber X ratio. Subsequently, the sizes of the glenoid bone loss determined using CT and MRI were compared. To estimate intraobserver and interobserver reliability, measurements were performed in a blinded fashion by two observers. Their level of experience was equivalent to that of orthopaedic residents, and they completed a training protocol before the measurements.

Results: For the ability to accurately diagnose Bankart lesions, the AUC (accuracy of a diagnostic test; the closer to 1.0, the more accurate the test) was good for MRI (0.83 [95% confidence interval 0.70 to 0.94]; p < 0.01), fair for CT (0.79 [95% CI 0.66 to 0.92]; p < 0.01), poor for WP radiographs (0.69 [95% CI 0.54 to 0.85]; p = 0.02) and failed for true AP radiographs (0.55 [95% CI 0.39 to 0.72]; p = 0.69). In paired comparisons, there were no differences between CT and MRI regarding (median [range]) lesion width (2.33 mm [0.35 to 4.53] versus 2.26 mm [0.90 to 3.47], p = 0.71) and depth (0.42 mm [0.80 to 1.39] versus 0.40 mm [0.06 to 1.17]; p = 0.54), and there were no differences concerning the other measurement methods: best-fit circle width loss method (15.02% [2.48% to 41.59%] versus 13.38% [2.00% to 36.34%]; p = 0.66), AP distances method (15.48% [1.44% to 42.01%] versus 12.88% [1.43% to 36.34%]; p = 0.63), surface area method (14.01% [0.87% to 38.25] versus 11.72% [2.45% to 37.97%]; p = 0.68), and Gerber X ratio (0.75 [0.13 to 1.47] versus 0.76 [0.27 to 1.13]; p = 0.41). Except for the moderate interrater reliability of the Bigliani classification using CT (intraclass correlation coefficient = 0.599 [95% CI 0.246 to 0.834]; p = 0.03) and acceptable interrater reliability of the Gerber X ratio using CT (0.775 [95% CI 0.542 to 0.899]; p < 0.01), all other measurement methods had good or excellent intrarater and interrater reliabilities on MRI and CT.

Conclusion: The results of this study show that CT and MRI can accurately detect glenoid bone loss, whereas WP radiographs can only recognize them poorly, and true AP radiographs do not provide any adequate diagnostic accuracy. In addition, when measuring glenoid bone loss, MRI images of the analyzed measurement methods yielded sizes that were no different from CT measurements. Finally, the use of MRI images to measure Bankart bone lesions gave good-to-excellent reliability in the present study, which was not inferior to CT findings. Considering the advantages including lower radiation exposure and the ability to assess the condition of the labrum using MRI, we believe MRI can help surgeons avoid ordering additional CT imaging in clinical practice for the diagnosis of anterior shoulder instability in patients with glenoid bone loss. Future studies should investigate the reproducibility of our results with a larger number of patients, using other measurement methods that include examination of the opposite side or with three-dimensional reconstructions.

Level of evidence: Level I diagnostic study.

Fig. 1

This figure shows a schematic representation of the method to measure depth and length of a glenoid bone loss. A best-fit circle is placed on the lower two-thirds of the glenoid. A line connecting the anteroinferior and anterosuperior rim of the glenoid bone loss was used to measure the length of the bony defect (blue line). To measure the depth of the glenoid bone loss, a second line (red line) perpendicular to the first line was drawn between the deepest point of the glenoid bone loss and the best-fit circle. A color image accompanies the online version of this article.

Fig. 2

This figure shows a schematic representation of the best-fit circle width loss method. A best-fit circle was drawn on the inferior part of the glenoid on an en face view of the glenoid. The diameter (blue line) of the best-fit circle was measured. Using a parallel line to the diameter of the best fit circle, the width (red line) of the glenoid bone loss was measured [39]. A color image accompanies the online version of this article.

Fig. 3

This figure illustrates the AP distance method. The bare spot was identified and a best-fit circle with the bare spot as the center was drawn over the inferior glenoid. The distance A from the bare-spot area to the anterior rim of the glenoid was measured. In the same manner, the distance between the bare spot and posterior rim of the glenoid was determined. The amount of glenoidal bone loss was then calculated using the following formula: A/B x100 [32]. A color image accompanies the online version of this article.

Fig. 4

This figure shows a schematic representation of the surface area measurement method. A best-fit circle is placed on the lower two-thirds of the glenoid, starting at the 3 o’clock position (yellow circle). The area of the best-fit circle was calculated digitally. The bony fragment (white line) was identified and delineated. The surface area of the bony fragment was determined digitally. The glenoid bone loss was finally calculated by determining the ratio between the two areas [39]. A color image accompanies the online version of this article.

Fig. 5

This figure shows the Gerber X ratio method. Using an en face view of the glenoid, a best-fit circle was drawn over the lower part of the glenoid, and its diameter (red line) was measured. Then, the length of the glenoid bone loss was measured using a line (blue line) connecting the anterocranial and anterocaudal edges of the glenoid bone loss [34]. A color image accompanies the online version of this article.