Anatomic nomenclature and 3-dimensional regional model of the human ovary: call for a new paradigm.

The ovaries are the female gonads that are crucial for reproduction, steroid production, and overall health. Historically, the ovary was broadly divided into regions defined as the cortex, medulla, and hilum. This current nomenclature lacks specificity and fails to consider the significant anatomic variations in the ovary. Recent technological advances in imaging modalities and high-resolution omic analyses have brought about the need for revision of the existing definitions, which will facilitate the integration of generated data and enable the characterization of organ subanatomy and function at the cellular level. The creation of these high-resolution multimodal maps of the ovary will enhance collaboration and communication among disciplines and between clinicians and researchers. Beginning in March 2021, the Pediatric and Adolescent Gynecology Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development invited subject-matter experts to participate in a series of workshops and meetings to standardize ovarian nomenclature and define the organ's features. The goal was to develop a spatially defined and semantically consistent terminology of the ovary to support collaborative, team science-based endeavors aimed at generating reference atlases of the human ovary. The group recommended a standardized, 3-dimensional description of the ovary and an ontological approach to the subanatomy of the ovary and definition of follicles. This new greater precision in nomenclature and mapping will better reflect the ovary's heterogeneous composition and function, support the standardization of tissue collection, facilitate functional analyses, and enable clinical and research collaborations. The conceptualization process and outcomes of the effort, which spanned the better part of 2021 and early 2022, are introduced in this article. The institute and the workshop participants encourage researchers and clinicians to adopt the new systems in their everyday work to advance the overarching goal of improving human reproductive health.

Local aortic aneurysm wall expansion measured with automated image analysis.

BACKGROUND: Assessment of regional aortic wall deformation (RAWD) might better predict for abdominal aortic aneurysm (AAA) rupture than the maximal aortic diameter or growth rate. Using sequential computed tomography angiograms (CTAs), we developed a streamlined, semiautomated method of computing RAWD using deformable image registration (dirRAWD). METHODS: Paired sequential CTAs performed 1 to 2 years apart of 15 patients with AAAs of various shapes and sizes were selected. Using each patient's initial CTA, the luminal and aortic wall surfaces were segmented both manually and semiautomatically. Next, the same patient's follow-up CTA was aligned with the first using automated rigid image registration. Deformable image registration was then used to calculate the local aneurysm wall expansion between the sequential scans (dirRAWD). To measure technique accuracy, the deformable registration results were compared with the local displacement of anatomic landmarks (fiducial markers), such as the origin of the inferior mesenteric artery and/or aortic wall calcifications. Additionally, for each patient, the maximal RAWD was manually measured for each aneurysm and was compared with the dirRAWD at the same location. RESULTS: The technique was successful in all patients. The mean landmark displacement error was 0.59 ± 0.93 mm with no difference between true landmark displacement and deformable registration landmark displacement by Wilcoxon rank sum test (P = .39). The absolute difference between the manually measured maximal RAWD and dirRAWD was 0.27 ± 0.23 mm, with a relative difference of 7.9% and no difference using the Wilcoxon rank sum test (P = .69). No differences were found in the maximal dirRAWD when derived using a purely manual AAA segmentation compared with using semiautomated AAA segmentation (P = .55). CONCLUSIONS: We found accurate and automated RAWD measurements were feasible with clinically insignificant errors. Using semiautomated AAA segmentations for deformable image registration methods did not alter maximal dirRAWD accuracy compared with using manual AAA segmentations. Future work will compare dirRAWD with finite element analysis-derived regional wall stress and determine whether dirRAWD might serve as an independent predictor of rupture risk.

Multimodal image analysis and subvalvular dynamics in ischemic mitral regurgitation.

Background: The exact geometric pathogenesis of leaflet tethering in ischemic mitral regurgitation (IMR) and the relative contribution of each component of the mitral valve complex (MVC) remain largely unknown. In this study, we sought to further elucidate mitral valve (MV) leaflet remodeling and papillary muscle dynamics in an ovine model of IMR with magnetic resonance imaging (MRI) and 3-dimensional echocardiography (3DE). Methods: Multimodal imaging combining 3DE and MRI was used to analyze the MVC at baseline, 30 minutes post-myocardial infarction (MI), and 12 weeks post-MI in ovine IMR models. Advanced 3D imaging software was used to trace the MVC from each modality, and the tracings were verified against resected specimens. Results: 3DE MV remodeling was regionally heterogenous and observed primarily in the anterior leaflet, with significant increases in surface area, especially in A2 and A3. The posterior leaflet was significantly shortened in P2 and P3. Mean posteromedial papillary muscle (PMPM) volume was decreased from 1.9 ± 0.2 cm3 at baseline to 0.9 ± 0.3 cm3 at 12 weeks post-MI (P < .05). At 12 weeks post-MI, the PMPM was predominately displaced horizontally and outward along the intercommissural axis with minor apical displacement. The subvalvular contribution to tethering is a combination of unilateral movement, outward displacement, and degeneration of the PMPM. These findings have led to a proposed new framework for characterizing PMPM dynamics in IMR. Conclusions: This study provides new insights into the complex interrelated and regionally heterogenous valvular and subvalvular mechanisms involved in the geometric pathogenesis of IMR tethering.

Validation of semiautomated and locally resolved aortic wall thickness measurements from computed tomography.

OBJECTIVE: Aortic wall thickness (AWT) is important for anatomic description and biomechanical modeling of aneurysmal disease. However, no validated, noninvasive method for measuring AWT exists. We hypothesized that semiautomated image segmentation algorithms applied to computed tomography angiography (CTA) can accurately measure AWT. METHODS: Aortic samples from 10 patients undergoing open thoracoabdominal aneurysm repair were taken from sites of the proximal or distal anastomosis, or both, yielding 13 samples. Aortic specimens were fixed in formalin, embedded in paraffin, and sectioned. After staining with hematoxylin and eosin and Masson's trichrome, sections were digitally scanned and measured. Patients' preoperative CTA Digital Imaging and Communications in Medicine (DICOM; National Electrical Manufacturers Association, Rosslyn, Va) images were segmented into luminal, inner arterial, and outer arterial surfaces with custom algorithms using active contours, isoline contour detection, and texture analysis. AWT values derived from image data were compared with measurements of corresponding pathologic specimens. RESULTS: AWT determined by CTA averaged 2.33 ± 0.66 mm (range, 1.52-3.55 mm), and the AWT of pathologic specimens averaged 2.36 ± 0.75 mm (range, 1.51-4.16 mm). The percentage difference between pathologic specimens and CTA-determined AWT was 9.5% ± 4.1% (range, 1.8%-16.7%). The correlation between image-based measurements and pathologic measurements was high (R = 0.935). The 95% limits of agreement computed by Bland-Altman analysis fell within the range of -0.42 and 0.42 mm. CONCLUSIONS: Semiautomated analysis of CTA images can be used to accurately measure regional and patient-specific AWT, as validated using pathologic ex vivo human aortic specimens. Descriptions and reconstructions of aortic aneurysms that incorporate locally resolved wall thickness are feasible and may improve future attempts at biomechanical analyses.