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Mechanobiology in the Reproductive Tract
Published in Jiro Nagatomi, Eno Essien Ebong, Mechanobiology Handbook, 2018
Julie Anne MacDonald, Dori C. Woods
Previous sections have described the roles for mechanotransduction in guiding sperm transit, uterine function, and ovarian function, as well as how dysregulated mechanotransduction might negatively impact the reproductive tract. Several pathologies linked to premature ovarian failure, such as PCOS, discussed previously, show significant defects in the ovarian microenvironment (Lewandowski et al. 2006), with potential roles for dysregulated mechanotransduction in disease progression. Uterine fibroids are noncancerous growths within the uterus that occur at very high frequencies in the population of reproductive aged women, with some estimates as high as 70%–80% of American women (Stewart 2015). At present, the mechanism of formation remains unclear; however, mounting evidence suggests the cause could be aberrant mechanotransduction within the uterus. Additionally, the mechanical properties of breast tissue have been implicated in both cancer diagnoses and progression (reviewed in Weaver et al. 1996).
Normal Anatomy of the Female Pelvis and Sonographic Demonstration of Pelvic Abnormalities
Published in Asim Kurjak, Ultrasound and Infertility, 2020
Ultrasonic visualization of a uterine fibroid provides in a number of cases a fast and simple diagnosis of the cause of infertility. Infertility is the only symptom in a considerable amount of patients with a uterine fibroid. Large nodes in the posterior uterine wall dislocate the tubes and diminish their motility, so that acceptance and transport of fertilized ova are impossible. Nodes situated close to the sotia tubae uterine can cause mechanical obstruction of the tubes, and submucosal fibromas interfere with nidation.39
Anatomically constrained deformable 3D reconstruction of intraoperative uterus from preoperative MRI data on uterine fibroid treatment
Published in Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 2021
Hee Guan Khor, Guochen Ning, Ting Wang, Yingang Wen, Xinran Zhang, Hongen Liao
Treatment of uterine fibroids using High-Intensity Focused Ultrasound (HIFU) is an emerging non-invasive and thermoablative treatment applied transcutaneously. In this procedure, HIFU relies on preoperative Magnetic Resonance Imaging (MRI) data for intraoperative navigation. To address the problem of the interposition of bowel loops in the acoustic pathway, the bladder-and-rectum-filling (BRF) technique is implemented which includes sequential urinary bladder and rectal filling during HIFU therapy to achieve the optimal position of the targeted uterine fibroids (Verpalen et al. 2020). However, because of the deformation of the uterus under BRF, the preoperative MRI data cannot be directly used for soft tissue navigation during HIFU treatment to perfectly reflect the uterus current structure. The conventional workflow includes the use of intraoperative sensor data, such as ultrasound to capture intraoperative organ structures, which can then be used for deformable corrections (Dickinson et al. 2013). However, the low quality of ultrasound images and unknown parameters (i.e. unseen uterus surfaces, tissue parameters) limits the accuracy of the deformable model, resulting in unsafety treatment and fibroid remnants. Previous research (Yoo et al. 2020) synthesise postoperative appearance using a conditional generative adversarial network (cGAN). The unsupervised CNN-based image registration method (Mansilla et al. 2020) uses segmentation masks to learn global non-linear representations of anatomical structures and uses them to constrain the registration process. Studies using finite element analysis and tissue parameters as training data to determine the statistical deformable model for prostate interventions (Wang et al. 2016). However, it can be practically infeasible to obtain such data for each new patient. Therefore, the modelling of intraoperative uterus structure between empty and full bladder anatomy deems to be a crucial image processing step to provide accurate HIFU navigation.