PDF(Pubmed)
Abstract：
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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 ).
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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 ).
UNASSIGNED: 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.
摘要：
■传统上描述提上肌间隙（LH）的措施是直接可靠的；但是，它们不是专门设计来捕捉显著差异的.统计形状模型（SSM）用于量化育龄女性的LH形状变化，并确定与LH大小和形状相关的新变量。
■对19名未产者的骨盆MRI进行的回顾性研究，32帕罗斯，执行了12名孕妇。LH在最小LH尺寸的平面中分段。SSM已实施。LH尺寸由横截面积定义，最大横向直径,前后(A-P)直径。新的SSM引导变量由变化最大的区域定义。多变量方差分析(MANOVA)评估了组间差异，和相关性决定了大小和形状变量之间的关系。
■整体形状（p<0.001），SSM模式2(椭圆形至T形,p=0.002),模式3(更圆到更宽的前部形状，p=0.004),最大横径（p=0.003）在组间差异显著。在A-P长度的14％和79％处发现了新的前后横向直径。前横径和最大横径密切相关(r=0.780,p<0.001)，后横径和最大横径弱相关(r=0.398，p=0.001)。
■传统的最大横径通常与SSM发现相对应，但不能独立描述前后变化。新颖的前后横向直径代表了大小和形状的变化，可以很容易地和传统的衡量标准一起计算，并且对细微和局部LH变化更敏感。因此，它们有更强的能力作为预测和诊断参数。
■对19名未产者的骨盆MRI进行的回顾性研究，32帕罗斯，执行了12名孕妇。LH在最小LH尺寸的平面中分段。SSM已实施。LH尺寸由横截面积定义，最大横向直径,前后(A-P)直径。新的SSM引导变量由变化最大的区域定义。多变量方差分析(MANOVA)评估了组间差异，和相关性决定了大小和形状变量之间的关系。
■整体形状（p<0.001），SSM模式2(椭圆形至T形,p=0.002),模式3(更圆到更宽的前部形状，p=0.004),最大横径（p=0.003）在组间差异显著。在A-P长度的14％和79％处发现了新的前后横向直径。前横径和最大横径密切相关(r=0.780,p<0.001)，后横径和最大横径弱相关(r=0.398，p=0.001)。
■传统的最大横径通常与SSM发现相对应，但不能独立描述前后变化。新颖的前后横向直径代表了大小和形状的变化，可以很容易地和传统的衡量标准一起计算，并且对细微和局部LH变化更敏感。因此，它们有更强的能力作为预测和诊断参数。
