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

IF 1.9 Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Journal of Medical Imaging Pub Date : 2024-07-01 Epub Date: 2024-08-10 DOI:10.1117/1.JMI.11.4.045001
Vincenzia S Vargo, Megan R Routzong, Pamela A Moalli, Ghazaleh Rostaminia, Steven D Abramowitch
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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.

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利用统计形状建模方法改进左肌裂孔特征的放射学量化。
目的:传统上描述提上睑肌间隙(LH)的测量方法简单可靠,但这些方法并非专门为捕捉显著差异而设计。统计形状建模(SSM)被用来量化育龄妇女LH形状的变化,并确定与LH大小和形状相关的新变量:方法:对 19 名非孕期妇女、32 名准孕期妇女和 12 名孕妇的盆腔 MRI 进行回顾性研究。在 LH 最小尺寸平面上对 LH 进行分割。实施了 SSM。LH 的大小由横截面积、最大横径和前后(A-P)径定义。新的 SSM 指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,相关性分析确定了尺寸和形状变量之间的关系:结果:总体形状(p 0.001)、SSM 模式 2(从椭圆形到 T 形,p = 0.002)、模式 3(从较圆到较宽的前部形状,p = 0.004)和最大横径(p = 0.003)在组间存在显著差异。新的前横径和后横径分别占 A-P 长度的 14% 和 79%。前横径和最大横径呈强相关(r = 0.780,p 0.001),而后横径和最大横径呈弱相关(r = 0.398,p = 0.001):结论:传统的最大横径与 SSM 结果基本一致,但不能独立描述前后变异。新型的前后横径同时代表了大小和形状的变化,可以很容易地与传统的测量方法一起计算,而且对细微和局部的 LH 变化更敏感。因此,它们作为预测和诊断参数的能力更强。
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来源期刊
Journal of Medical Imaging
Journal of Medical Imaging RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-
CiteScore
4.10
自引率
4.20%
发文量
0
期刊介绍: JMI covers fundamental and translational research, as well as applications, focused on medical imaging, which continue to yield physical and biomedical advancements in the early detection, diagnostics, and therapy of disease as well as in the understanding of normal. The scope of JMI includes: Imaging physics, Tomographic reconstruction algorithms (such as those in CT and MRI), Image processing and deep learning, Computer-aided diagnosis and quantitative image analysis, Visualization and modeling, Picture archiving and communications systems (PACS), Image perception and observer performance, Technology assessment, Ultrasonic imaging, Image-guided procedures, Digital pathology, Biomedical applications of biomedical imaging. JMI allows for the peer-reviewed communication and archiving of scientific developments, translational and clinical applications, reviews, and recommendations for the field.
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