Abstract
A prospective radiographic analysis of adolescent idiopathic scoliosis (AIS) patients managed with alternate-level pedicle screw fixation was performed. The objective of this study was to characterize segmental curve flexibility and to determine its predictive value in curve correction in AIS patients. Little is known regarding the distinct segmental curve characteristics and their ability to predict curve correction in patients with AIS. The segmental Cobb angle was measured on posteroanterior standing radiographs and on fulcrum bending radiographs. Radiographs were analyzed preoperatively and at 2 years postoperatively and the curve was divided into upper, mid, and lower segments based on predefined criteria. The segmental flexibility and the segmental fulcrum bending correction index (FBCI) were calculated. Eighty patients were included with mean age of 15 years. Preoperative mean segmental Cobb angles were 18, 31, and 17 degrees in the upper, mid, and lower segments, respectively. Segmental bending Cobb angles were 6, 13, and 4 degrees, respectively, corresponding to segmental flexibilities of 50%, 47%, and 83% in the upper, mid, and lower segments, respectively (P < 0.001). At 2-year follow up, the mean segmental FBCI were 155%, 131%, and 100% in the upper, mid, and lower segments, respectively (P < 0.001), which suggested that the lower segment of the curve was more flexible than the other segments and that higher correction was noted in the upper segments. A significant, positive correlation was noted between the segmental bending Cobb angle and the segmental FBCI (P < 0.05), whereby the strength of the correlation varied based on the curve segment. This is the first study to demonstrate the segmental variations in curve flexibility using the fulcrum bending radiograph in AIS patients. Curve flexibility is not uniform throughout the curve and different segments exhibit greater flexibility/correctibility than others. Segmental flexibility should be considered in assessing AIS patients and in the clinical decision-making strategy to optimize curve correction outcomes. 03.
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