Search Results (13)

Endometriosis, a prevalent gynecological condition affecting 10–15% of reproductive-age women, involves the growth of endometrial-like tissue outside the uterine cavity. This chronic inflammatory disease can significantly impact fertility by disrupting ovulation, tubal transport, and implantation. Clinical manifestations vary widely, ranging from asymptomatic cases to severe pelvic pain, dysmenorrhea, and dyspareunia. Accurate diagnosis remains challenging, often requiring a combination of patient history, clinical examination, and imaging studies. This paper will discuss the clinical approach to endometriosis during a first-line gynecological appointment, focusing on patient history, including detailed assessment of menstrual, pelvic, and bowel symptoms, and clinical examination; thorough gynecological examination, including abdominal and pelvic palpation, speculum examination, and bimanual examination; imaging evaluation (particularly of the role of ultrasound in identifying and characterizing endometriotic lesions, including the use of the #ENZIAN classification for deep infiltrating endometriosis and evaluation of fertility impact); and discussion of the Endometriosis Fertility Index (EFI) as a tool for assessing fertility potential. This comprehensive approach aims to guide clinicians in identifying and managing endometriosis effectively, improving patient outcomes and optimizing fertility management strategies. Methods: A literature search for suitable articles published from January 1974 to 2024 in the English language was performed using PubMed. Results: Endometriosis is associated with infertility rates ranging from 20% to 68%, with mechanisms including pelvic adhesions, chronic inflammation, and immune dysregulation. The revised American Society for Reproductive Medicine (rASRM) classification and #ENZIAN classification were identified as essential tools for staging and characterizing the disease. Transvaginal ultrasound (TVS) demonstrated high diagnostic accuracy for deep infiltrating endometriosis, with a sensitivity of up to 96% and specificity of 99%. EFI emerged as a valuable predictor of natural conception post-surgery. Additionally, the review underscores the frequent co-occurrence of adenomyosis in women with endometriosis, which may further compromise fertility. Despite advancements in imaging techniques and classification systems, the variability in symptom presentation and disease progression continues to challenge early diagnosis and effective management. Conclusions: Endometriosis is a prevalent gynecological condition affecting women of reproductive age and is associated with infertility. This paper describes the diagnostic approach to endometriosis during a first-line gynecological appointment, focusing on clinical history, physical examination, and the role of imaging, particularly ultrasound, in identifying and characterizing endometriosis lesions. The adoption of standardized classification systems such as #ENZIAN and EFI enhances disease staging and fertility prognosis, allowing for tailored treatment strategies. Despite improvements in non-invasive diagnostic methods, challenges persist in correlating symptom severity with disease extent, necessitating continued research into biomarkers and novel imaging techniques. Additionally, the frequent coexistence of adenomyosis further complicates fertility outcomes, underscoring the need for comprehensive management strategies. Further research is needed to enhance early detection strategies and optimize fertility preservation techniques for affected women. Full article

Infrared small target detection is an important and core problem in infrared search and track systems. Many infrared small target detection methods work well under the premise of a static background; however, the detection effect decreases seriously when the background changes dynamically. In addition, the spatiotemporal information of the target and background of the image sequence are not fully developed and utilized, lacking long-term temporal characteristics. To solve these problems, a novel long-term spatial–temporal tensor (LSTT) model is proposed in this paper. The image registration technique is employed to realize the matching between frames. By directly superimposing the aligned images, the spatiotemporal features of the resulting tensor are not damaged or reduced. From the perspective of the horizontal slice of this tensor, it is found that the background component has similarity in the time dimension and correlation in the space dimension, which is more consistent with the prerequisite of low rank, while the target component is sparse. Therefore, we transform the problem of infrared detection of a small moving target into a low-rank sparse decomposition problem of new tensors composed of several continuous horizontal slices of the aligned image tensor. The low rank of the background is constrained by the partial tubal nuclear norm (PTNN), and the tensor decomposition problem is quickly solved using the alternating-direction method of multipliers (ADMM). Our experimental results demonstrate that the proposed LSTT method can effectively detect small moving targets against a dynamic background. Compared with other benchmark methods, the new method has better performance in terms of detection efficiency and accuracy. In particular, the new LSTT method can extract the spatiotemporal information of more frames in a longer time domain and obtain a higher detection rate. Full article

High-grade serous ovarian cancer (HGSOC) is the most lethal tumor of the female genital tract. Despite extensive studies and the identification of some precursor lesions like serous tubal intraepithelial cancer (STIC) or the deviated mutational status of the patients (BRCA germinal mutation), the pathophysiology of HGSOC and the existence of particular risk factors is still a puzzle. Moreover, a lack of screening programs results in delayed diagnosis, which is accompanied by a secondary chemo-resistance of the tumor and usually results in a high recurrence rate after the primary therapy. Therefore, there is an urgent need to identify the substantial risk factors for both predisposed and low-risk populations of women, as well as to create an economically and clinically justified screening program. This paper reviews the classic and novel risk factors for HGSOC and methods of diagnosis and prediction, including serum biomarkers, the liquid biopsy of circulating tumor cells or circulating tumor DNA, epigenetic markers, exosomes, and genomic and proteomic biomarkers. The novel future complex approach to ovarian cancer diagnosis should be devised based on these findings, and the general outcome of such an approach is proposed and discussed in the paper. Full article

Purpose: This study aims to share the experience of minimally invasive ultrasound-guided methotrexate intervention in the treatment of heterotopic interstitial pregnancy (HIP) with good pregnancy outcomes, and to review the treatment, pregnancy outcomes, and impact on the future fertility of HIP patients. Methods: The paper describes the medical history, clinical manifestations, treatment history, and clinical prognosis of a 31-year-old woman with HIP, and reviews cases of HIP from 1992 to 2021 published in the PubMed database. Results: The patient was diagnosed with HIP by transvaginal ultrasound (TVUS) at 8 weeks after assisted reproductive technology. The interstitial gestational sac was inactivated by ultrasound-guided methotrexate injection. The intrauterine pregnancy was successfully delivered at 38 weeks of gestation. Twenty-five HIP cases in 24 studies published on PubMed from 1992 to 2021 were reviewed. Combined with our case, there were 26 cases in total. According to these studies, 84.6% (22/26) of these cases were conceived by in vitro fertilization embryo transfer, 57.7% (15/26) had tubal disorders, and 23.1% (6/26) had a history of ectopic pregnancy; 53.8% (14/26) of the patients presented with abdominal pain and 19.2% (5/26) had vaginal bleeding. All cases were confirmed by TVUS. In total, 76.9% (20/26) of intrauterine pregnancies had a good prognosis (surgery vs. ultrasound interventional therapy 1:1). All fetuses were born without abnormalities. Conclusions: The diagnosis and treatment of HIP remain challenging. Diagnosis mainly relies on TVUS. Interventional ultrasound therapy and surgery are equally safe and effective. Early treatment of concomitant heterotopic pregnancy is associated with high survival of the intrauterine pregnancy. Full article

The human microbiome plays a crucial role in determining the health status of every human being, and the microbiome of the genital tract can affect the fertility potential before and during assisted reproductive treatments (ARTs). This review aims to identify and appraise studies investigating the correlation of genital microbiome to infertility. Publications up to February 2021 were identified by searching the electronic databases PubMed/MEDLINE, Scopus and Embase and bibliographies. Only full-text original research articles written in English were considered eligible for analysis, whereas reviews, editorials, opinions or letters, case studies, conference papers, and abstracts were excluded. Twenty-six articles were identified. The oldest studies adopted the exclusive culture-based technique, while in recent years PCR and RNA sequencing based on 16S rRNA were the most used technique. Regardless of the anatomical site under investigation, the Lactobacillus-dominated flora seems to play a pivotal role in determining fertility, and in particular Lactobacillus crispatus showed a central role. Nonetheless, the presence of pathogens in the genital tract, such as Chlamydia trachomatis, Gardnerella vaginalis, Ureaplasma species, and Gram-negative stains microorganism, affected fertility also in case of asymptomatic bacterial vaginosis (BV). We failed to identify descriptive or comparative studies regarding tubal microbiome. The microbiome of the genital tract plays a pivotal role in fertility, also in case of ARTs. The standardization of the sampling methods and investigations approaches is warranted to stratify the fertility potential and its subsequent treatment. Prospective tubal microbiome studies are warranted. Full article

Sperm binding within the oviductal sperm reservoir plays an important role for reproductive success by enabling sperm survival and maintaining fertilizing capacity. To date, numerous in vitro technologies have been established to measure sperm binding capacity to cultured oviductal cells or oviductal explants. However, these methods do not accurately represent the microenvironment and complex multi-molecular nature of the oviduct. In this paper, we describe a novel protocol for assessing sperm binding capacity in the tubal sperm reservoir using an ex vivo oviduct culture in the bovine model. This protocol includes the staining of frozen-thawed bovine spermatozoa with the DNA-binding dye Hoechst 33342, the co-incubation of stained sperm in closed segments of the oviduct and the visualization and quantification of bound spermatozoa by fluorescence microscopy. By generating overlays of multiple Z-stacks of randomly selected regions of interest (ROIs), spermatozoa bound in the sperm reservoir can be visualized and quantified within the 3D arrangement of the oviductal folds. This method, which is applicable to multiple species, can be used to assess individual sperm binding capacity in males for prognostic purposes as well as to assess the impact of diseases and medications on the formation of the sperm reservoir in the oviduct in humans and animals. Full article

This paper conducts a rigorous analysis for the problem of robust tensor completion, which aims at recovering an unknown three-way tensor from incomplete observations corrupted by gross sparse outliers and small dense noises simultaneously due to various reasons such as sensor dead pixels, communication loss, electromagnetic interferences, cloud shadows, etc. To estimate the underlying tensor, a new penalized least squares estimator is first formulated by exploiting the low rankness of the signal tensor within the framework of tensor ${\ast }_L$-Singular Value Decomposition (${\ast }_L$-SVD) and leveraging the sparse structure of the outlier tensor. Then, an algorithm based on the Alternating Direction Method of Multipliers (ADMM) is designed to compute the estimator in an efficient way. Statistically, the non-asymptotic upper bound on the estimation error is established and further proved to be optimal (up to a log factor) in a minimax sense. Simulation studies on synthetic data demonstrate that the proposed error bound can predict the scaling behavior of the estimation error with problem parameters (i.e., tubal rank of the underlying tensor, sparsity of the outliers, and the number of uncorrupted observations). Both the effectiveness and efficiency of the proposed algorithm are evaluated through experiments for robust completion on seven different types of remote sensing data. Full article

The main aim of this work was the investigation of the possibility of replacing the heavy metallic meshes applied onto the composite structure in airplanes for lightning strike protection with a thin film of Tuball single-wall carbon nanotubes in the form of ultra-light, conductive paper. The Tuball paper studied contained 75 wt.% or 90 wt.% of carbon nanotubes and was applied on the top of carbon fibre reinforced polymer before fabrication of flat panels. First, the electrical conductivity, impact resistance and thermo-mechanical properties of modified laminates were measured and compared with the reference values. Then, flat panels with selected Tuball paper, expanded copper foil and reference panels were fabricated for lightning strike tests. The effectiveness of lightning strike protection was evaluated by using the ultrasonic phased-array technique. It was found that the introduction of Tuball paper on the laminates surface improved both the surface and the volume electrical conductivity by 8800% and 300%, respectively. The impact resistance was tested in two directions, perpendicular and parallel to the carbon fibres, and the values increased by 9.8% and 44%, respectively. The dynamic thermo-mechanical analysis showed higher stiffness and a slight increase in glass transition temperature of the modified laminates. Ultrasonic investigation after lightning strike tests showed that the effectiveness of Tuball paper is comparable to expanded copper foil. Full article

Face recognition and identification are very important applications in machine learning. Due to the increasing amount of available data, traditional approaches based on matricization and matrix PCA methods can be difficult to implement. Moreover, the tensorial approaches are a natural choice, due to the mere structure of the databases, for example in the case of color images. Nevertheless, even though various authors proposed factorization strategies for tensors, the size of the considered tensors can pose some serious issues. Indeed, the most demanding part of the computational effort in recognition or identification problems resides in the training process. When only a few features are needed to construct the projection space, there is no need to compute a SVD on the whole data. Two versions of the tensor Golub–Kahan algorithm are considered in this manuscript, as an alternative to the classical use of the tensor SVD which is based on truncated strategies. In this paper, we consider the Tensor Tubal Golub–Kahan Principal Component Analysis method which purpose it to extract the main features of images using the tensor singular value decomposition (SVD) based on the tensor cosine product that uses the discrete cosine transform. This approach is applied for classification and face recognition and numerical tests show its effectiveness. Full article

Reconstruction of 3D objects in various tomographic measurements is an important problem which can be naturally addressed within the mathematical framework of 3D tensors. In Optical Coherence Tomography, the reconstruction problem can be recast as a tensor completion problem. Following the seminal work of Candès et al., the approach followed in the present work is based on the assumption that the rank of the object to be reconstructed is naturally small, and we leverage this property by using a nuclear norm-type penalisation. In this paper, a detailed study of nuclear norm penalised reconstruction using the tubal Singular Value Decomposition of Kilmer et al. is proposed. In particular, we introduce a new, efficiently computable definition of the nuclear norm in the Kilmer et al. framework. We then present a theoretical analysis, which extends previous results by Koltchinskii Lounici and Tsybakov. Finally, this nuclear norm penalised reconstruction method is applied to real data reconstruction experiments in Optical Coherence Tomography (OCT). In particular, our numerical experiments illustrate the importance of penalisation for OCT reconstruction. Full article

The rapid development of sensor technology gives rise to the emergence of huge amounts of tensor (i.e., multi-dimensional array) data. For various reasons such as sensor failures and communication loss, the tensor data may be corrupted by not only small noises but also gross corruptions. This paper studies the Stable Tensor Principal Component Pursuit (STPCP) which aims to recover a tensor from its corrupted observations. Specifically, we propose a STPCP model based on the recently proposed tubal nuclear norm (TNN) which has shown superior performance in comparison with other tensor nuclear norms. Theoretically, we rigorously prove that under tensor incoherence conditions, the underlying tensor and the sparse corruption tensor can be stably recovered. Algorithmically, we first develop an ADMM algorithm and then accelerate it by designing a new algorithm based on orthogonal tensor factorization. The superiority and efficiency of the proposed algorithms is demonstrated through experiments on both synthetic and real data sets. Full article

Many tasks in computer vision suffer from missing values in tensor data, i.e., multi-way data array. The recently proposed tensor tubal nuclear norm (TNN) has shown superiority in imputing missing values in 3D visual data, like color images and videos. However, by interpreting in a circulant way, TNN only exploits tube (often carrying temporal/channel information) redundancy in a circulant way while preserving the row and column (often carrying spatial information) relationship. In this paper, a new tensor norm named the triple tubal nuclear norm (TriTNN) is proposed to simultaneously exploit tube, row and column redundancy in a circulant way by using a weighted sum of three TNNs. Thus, more spatial-temporal information can be mined. Further, a TriTNN-based tensor completion model with an ADMM solver is developed. Experiments on color images, videos and LiDAR datasets show the superiority of the proposed TriTNN against state-of-the-art nuclear norm-based tensor norms. Full article

Ovarian cancer is the foremost cause of gynecological cancer death in the developed world, as it is usually diagnosed at an advanced stage. In this paper we discuss current issues, the efficacy and problems associated with ovarian cancer screening, and compare the characteristics of ovarian cancer subtypes. There are two types of ovarian cancer: Type I carcinomas, which are slow-growing, indolent neoplasms thought to arise from a precursor lesion, which are relatively common in Asia; and Type II carcinomas, which are clinically aggressive neoplasms that can develop de novo from serous tubal intraepithelial carcinomas (STIC) and/or ovarian surface epithelium and are common in Europe and the USA. One of the most famous studies on the subject reported that annual screening using CA125/transvaginal sonography (TVS) did not reduce the ovarian cancer mortality rate in the USA. In contrast, a recent study in the UK showed an overall average mortality reduction of 20% in the screening group. Another two studies further reported that the screening was associated with decreased stage at detection. Theoretically, annual screening using CA125/TVS could easily detect precursor lesions and could be more effective in Asia than in Europe and the USA. The detection of Type II ovarian carcinoma at an early stage remains an unresolved issue. The resolving power of CA125 or TVS screening alone is unlikely to be successful at resolving STICs. Biomarkers for the early detection of Type II carcinomas such as STICs need to be developed. Full article