Improving radiological quantification of levator hiatus features with measures informed by statistical shape modeling.

Abstract

Purpose: The measures that traditionally describe the levator hiatus (LH) are straightforward and reliable; however, they were not specifically designed to capture significant differences. Statistical shape modeling (SSM) was used to quantify LH shape variation across reproductive-age women and identify novel variables associated with LH size and shape.

Approach: A retrospective study of pelvic MRIs from 19 nulliparous, 32 parous, and 12 pregnant women was performed. The LH was segmented in the plane of minimal LH dimensions. SSM was implemented. LH size was defined by the cross-sectional area, maximal transverse diameter, and anterior-posterior (A-P) diameter. Novel SSM-guided variables were defined by regions of greatest variation. Multivariate analysis of variance (MANOVA) evaluated group differences, and correlations determined relationships between size and shape variables.

Results: Overall shape ( $p<0.001$ ), SSM mode 2 (oval to $T$ -shape, $p=0.002$ ), mode 3 (rounder to broader anterior shape, $p=0.004$ ), and maximal transverse diameter ( $p=0.003$ ) significantly differed between groups. Novel anterior and posterior transverse diameters were identified at 14% and 79% of the A-P length. Anterior transverse diameter and maximal transverse diameter were strongly correlated ( $r=0.780$ , $p<0.001$ ), while posterior transverse diameter and maximal transverse diameter were weakly correlated ( $r=0.398$ , $p=0.001$ ).

Conclusions: The traditional maximal transverse diameter generally corresponded with SSM findings but cannot describe anterior and posterior variation independently. The novel anterior and posterior transverse diameters represent both size and shape variation, can be easily calculated alongside traditional measures, and are more sensitive to subtle and local LH variation. Thus, they have a greater ability to serve as predictive and diagnostic parameters.