### Introduction

### Materials and Methods

### 1. Patient selection

### 2. Patient evaluation

### 3. Back surface topography method

### 4. Statistical analyses

*p*-value <0.01, and in some cases <0.05, was considered statistically significant.

### Results

### 1. Descriptive statistics for radiographic variables

### 2. Descriptive statistics for topographic variables

### 3. Correlation between topographic and radiographic variables

*p*≤0.01) were found between the Cobb angle of the main curve with DHOPI (

*r*=0.810,

*p*<0.001) and POTSI (

*r*=0.629,

*p*<0.001). Furthermore, a significant correlation (

*p*≤0.01) was found between two topographic variables: DHOPI and POTSI (

*r*=0.610,

*p*<0.001), and between PC and thoracic kyphosis angle (

*r*=0.453,

*p*<0.001). The vertebral rotation angle was significantly correlated with DHOPI (

*r*=0.312,

*p*=0.003) and POTSI (

*r*=0.321,

*p*=0.002). Fig. 4 displays the most significant correlations between topographic and radiographic variables.

*F*=92.52,

*p*<0.001) and POTSI (

*F*=32.36,

*p*<0.001), but not for PC (

*F*=2.77,

*p*=0.068). The Bonferroni correction for DHOPI and POTSI variables indicated that there were statistically significant differences between the three groups (

*p*<0.05 for all). No statistically significant differences were observed between groups for the PC variable (Table 4).

### Discussion

*r*=0.758 in lumbar zone and

*r*=0.872 in thoracic zone). Fortin et al. [19] also found a “good to excellent” correlation with shoulder and pelvic asymmetry for thoracic scoliosis (

*r*=0.81–0.97), but “stable to moderate” for thoracic kyphosis, lumbar lordosis, and thoracolumbar or lumbar scoliosis (

*r*=0.30–0.56). Berryman et al. [6], by means of ISIS2, found good correlation (

*r*=0.84) between a topographic variable called the Lateral Asymmetry Index and the Cobb angle. Berryman suggests that the topographic method contributes additional information to radiograph studies and notes that although there is no direct linear correlation between the Cobb angle and topographic parameters, the more severe the Cobb angle is, the greater the deformity in the back surface [6].

*r*=0.810) and POTSI (

*r*=0.629) variables. A positive statistically significant correlation between these two topographic variables (

*r*=0.610) has also been found. This is explained by the asymmetry of the frontal and axial plane that occurs in scoliosis. Furthermore, a statistically significant correlation between the degree of rotation of the apical vertebra with DHOPI (

*r*=0.312) and POTSI (

*r*=0.321) variables was observed herein.

*r*=-0.291). This means that there were patients with severe scoliosis associated with a flattening of the thoracic kyphosis and with increased risk of progression. The same occurs between PC and DHOPI (

*r*=-0.225) and between PC and POTSI (

*r*=-0.244). In these cases, the higher the asymmetry in the coronal and axial planes, the lower the sagittal plane. Furthermore, the PC variable is positively correlated with the thoracic kyphosis angle (

*r*=0.453) and lordosis lumbar angle (

*r*=0.275). In the case of the lumbar lordosis angle, the lower correlation could be due to the fact that the morphology of the back at the lumbar level is dependent on not only the lumbar spine but also on the influence of other structures, such as the gluteus. Studies that focused specifically on the PC variable in other pathologies (e.g., Scheuermann's disease or hyperlordosis lumbar) would be required to demonstrate its clinical effectiveness. Three groups of subjects would be required to demonstrate whether this variable could discriminate between groups: one with thoracic hyperkyphosis/hyperlordosis lumbar; another with normal values for thoracic kyphosis angle and lordosis lumbar angle; and a third with thoracic hypokyphosis/lumbar hypolordosis. We believe that in the case of scoliosis, although DHOPI and POTSI variables seem more effective, the PC variable could serve as a complementary parameter to DHOPI and POTSI in the 3D quantification of the back and trunk asymmetry caused by scoliosis. Table 1 shows that although the difference does not reach statistical significance (

*p*=0.068), the mean value of PC is lower in the more severe than in the milder scoliosis group. This indicates that the PC variable could also contribute to determining the severity and/or progression of scoliosis, since a low value can indicate increased risk of curve progression, and a high value may indicate an association between thoracic hyperkyphosis and scoliosis.Various researchers have attempted to determine which topographic parameters best correlate to vertebral deformity. According to Stokes et al. [20], axial rotation (DHOPI in our study), is the variable that best correlates with skeletal deformity. Oxborrow [21] suggests that the best deformity measure is a combination of topographic indices, combining the Suzuki Hump Sum (SHS) that quantifies asymmetry in the axial plane with POTSI in the coronal plane. Stokes suggests that the best manner to quantify vertebral deformity is the combination of three topographic variables, given that each variable represents a different plane in a 3D deformity [20]. Similarly, we believe that the best way to quantify the back deformity secondary to scoliosis is to consider the three topographical variables (DHOPI, POTSI, and PC), since each one quantifies a different plane of space.