Complete labia majora fusion after obliterative surgical procedure: a video case report.

Obliterative surgical procedures have been classically used as a method to reduce pelvic organ prolapse in elderly women who do not wish to preserve the vagina for sexual intercourse. The aim of this video is to demonstrate a surgical technique of repairing complete labia majora fusion in a woman who had previously undergone one of these procedures. We present the case of an 80 year-old woman with a history of progressive difficulty on voiding onset and sensation of incomplete bladder emptying. She reported an obliterative procedure to correct her pelvic organ prolapse (POP) 10 years earlier. On physical examination, complete fusion of labia majora was observed, causing abnormal urinary drainage. Perineal reconstructive surgery was performed without complications and the application of topical Promestriene was prescribed. Optimal genital re-epithelization was observed during follow-up. As observed, patients undergoing obliterative surgery who present with genital atrophy are at increased risk of developing vulvar adherences. Applying vaginal moisturizers or local topical estrogens can prevent this condition. In severe vulvar fusions, early surgical treatment is recommended to prevent potentially serious complications.

Exploiting Ambipolarity in Graphene Field-Effect Transistors for Novel Designs on High-Frequency Analog Electronics.

Exploiting ambipolar electrical conductivity based on graphene field-effect transistors has raised enormous interest for high-frequency (HF) analog electronics. Controlling the device polarity, by biasing the graphene transistor around the vertex of the V-shaped transfer curve, enables to redesign and highly simplify conventional analog circuits, and simultaneously to seek for multifunctionalities, especially in the HF domain. This study presents new insights for the design of different HF applications such as power amplifiers, mixers, frequency multipliers, phase shifters, and modulators that specifically leverage the inherent ambipolarity of graphene-based transistors.

medigan: a Python library of pretrained generative models for medical image synthesis.

Purpose: Deep learning has shown great promise as the backbone of clinical decision support systems. Synthetic data generated by generative models can enhance the performance and capabilities of data-hungry deep learning models. However, there is (1) limited availability of (synthetic) datasets and (2) generative models are complex to train, which hinders their adoption in research and clinical applications. To reduce this entry barrier, we explore generative model sharing to allow more researchers to access, generate, and benefit from synthetic data. Approach: We propose medigan, a one-stop shop for pretrained generative models implemented as an open-source framework-agnostic Python library. After gathering end-user requirements, design decisions based on usability, technical feasibility, and scalability are formulated. Subsequently, we implement medigan based on modular components for generative model (i) execution, (ii) visualization, (iii) search & ranking, and (iv) contribution. We integrate pretrained models with applications across modalities such as mammography, endoscopy, x-ray, and MRI. Results: The scalability and design of the library are demonstrated by its growing number of integrated and readily-usable pretrained generative models, which include 21 models utilizing nine different generative adversarial network architectures trained on 11 different datasets. We further analyze three medigan applications, which include (a) enabling community-wide sharing of restricted data, (b) investigating generative model evaluation metrics, and (c) improving clinical downstream tasks. In (b), we extract Fréchet inception distances (FID) demonstrating FID variability based on image normalization and radiology-specific feature extractors. Conclusion: medigan allows researchers and developers to create, increase, and domain-adapt their training data in just a few lines of code. Capable of enriching and accelerating the development of clinical machine learning models, we show medigan's viability as platform for generative model sharing. Our multimodel synthetic data experiments uncover standards for assessing and reporting metrics, such as FID, in image synthesis studies.

Conduta de Autolesão não Suicida em Adolescentes

A autolesão não suicida na adolescência tem recebido atenção de pesquisadores em virtudedo aumento de casos relatados nas escolas e mídias sociais, porém, o tema ainda é pouco focalizado na produção científica. Por tanto, este estudo tem objetivo de investigar, quais são as características, nos aspectos modos de conduta, sociodemográficos e psicológicos de pessoas, sem psicopatologia, que apresentam conduta autolesiva não suicida. Trata-se de um estudo qualitativo realizado através de estudos publicados nas bases de dados Scientific Eletronic Library (SciELO), Portal de Periódicos Eletrônicos de Psicologia (PePSIC) e no Catálogo de Teses e Dissertações, utilizando os descritores: autolesão, automutilação, adolescência, em diversas combinações de artigos de pesquisas de campo com o acesso liberado entre os anos de 2014 a 2019. Discute-se que a autolesão em adolescentes precisa ser compreendida como sendo configurada a partir dos condicionantes histórico-sociais que permeiam a experiência do que é ser adolescente na sociedade atual e torna-se importante que o psicólogo escolar atue considerando as conjunturas presentes na atualidade e que sua ação se volte para finalidades transformadoras. A população sem psicopatologia que apresenta autolesão não suicida são pessoas que se cortam na superfície da pele, podendo variar, na fase da adolescência com idades entre dez e dezoito anos, de classe baixa e média, morando com um dos progenitores, vivenciam fortes conflitos e emoções adversas e se lesionam no intuído de se sentirem melhor.

Edema mamario unilateral en contexto de insuficiencia cardíaca: presentación de un caso y revisión de la literatura / Unilateral breast edema in context of heart failure: A case report and literature review

El edema mamario unilateral puede aparecer como sintomatología atípica de la insuficiencia cardíaca. Presenta un amplio diagnóstico diferencial, entre el que se incluyen causas benignas, como la mastitis o las enfermedades sistémicas que cursan con edema generalizado; y causas malignas como el carcinoma inflamatorio de mama. Esta última entidad, aunque poco frecuente, presenta mayor agresividad que otros tipos de tumores mamarios y se deberá sospechar su diagnóstico ante la presencia de cambios mamarios unilaterales. En este artículo se presenta un caso de edema mamario unilateral en una paciente con fallo cardíaco congestivo en el que se sopesaron la mastitis y el carcinoma inflamatorio como diagnósticos iniciales. También se incluye una revisión de la literatura de los pocos casos publicados sobre el tema. (AU)

Unilateral breast edema might appear as an infrequent symptom of congestive heart failure. It has a wide range of diagnostic possibilities including benign causes, such as mastitis or systemic diseases causing general edema, and malign causes such as inflammatory breast cancer. This kind of tumor, although uncommon, is more aggressive than other breast tumors. Therefore, it is mandatory to rule it out whenever changes in breast skin occur. We report a case of unilateral breast edema in a patient with congestive heart failure for whom mastitis and inflammatory breast cancer were considered as first diagnostic possibilities. A literature review of the few articles published on the subject is also included. (AU)

Pelvic inflammatory disease presenting 16 months after vaginal hysterectomy: A case report and literature review.

Pelvic inflammatory disease after hysterectomy is rare and the underlying route of infection is highly heterogeneous. We report the case of a 52-year-old woman with a history of vaginal hysterectomy for uterine prolapse admitted to the emergency department with acute abdominal pain and fever. Vaginal discharge and pelvic tenderness were evident in the clinical examination. Ultrasound and computed tomography scans showed a cystic pelvic mass in contact with the vaginal cuff, suggesting the diagnosis of pelvic inflammatory disease. Laparoscopic examination revealed a bilateral tubo-ovarian abscess firmly attached and fistulized to the vaginal cuff, and after tubal removal and antibiotic coverage the patient had an optimal recovery. We performed a review of the case reports published on this subject, and concluded that pelvic inflammatory disease should not be excluded in patients with a history of hysterectomy when symptoms and findings are compatible.

Deep learning reconstruction of digital breast tomosynthesis images for accurate breast density and patient-specific radiation dose estimation.

The two-dimensional nature of mammography makes estimation of the overall breast density challenging, and estimation of the true patient-specific radiation dose impossible. Digital breast tomosynthesis (DBT), a pseudo-3D technique, is now commonly used in breast cancer screening and diagnostics. Still, the severely limited 3rd dimension information in DBT has not been used, until now, to estimate the true breast density or the patient-specific dose. This study proposes a reconstruction algorithm for DBT based on deep learning specifically optimized for these tasks. The algorithm, which we name DBToR, is based on unrolling a proximal-dual optimization method. The proximal operators are replaced with convolutional neural networks and prior knowledge is included in the model. This extends previous work on a deep learning-based reconstruction model by providing both the primal and the dual blocks with breast thickness information, which is available in DBT. Training and testing of the model were performed using virtual patient phantoms from two different sources. Reconstruction performance, and accuracy in estimation of breast density and radiation dose, were estimated, showing high accuracy (density <±3%; dose <±20%) without bias, significantly improving on the current state-of-the-art. This work also lays the groundwork for developing a deep learning-based reconstruction algorithm for the task of image interpretation by radiologists.

Fibroglandular tissue distribution in the breast during mammography and tomosynthesis based on breast CT data: A patient-based characterization of the breast parenchyma.

PURPOSE: To develop a patient-based breast density model by characterizing the fibroglandular tissue distribution in patient breasts during compression for mammography and digital breast tomosynthesis (DBT) imaging. METHODS: In this prospective study, 88 breast images were acquired using a dedicated breast computed tomography (CT) system. The breasts in the images were classified into their three main tissue components and mechanically compressed to mimic the positioning for mammographic acquisition of the craniocaudal (CC) and mediolateral oblique (MLO) views. The resulting fibroglandular tissue distribution during these compressions was characterized by dividing the compressed breast volume into small regions, for which the median and the 25th and 75th percentile values of local fibroglandular density were obtained in the axial, coronal, and sagittal directions. The best fitting function, based on the likelihood method, for the median distribution was obtained in each direction. RESULTS: The fibroglandular tissue tends to concentrate toward the caudal (about 15% below the midline of the breast) and anterior regions of the breast, in both the CC- and MLO-view compressions. A symmetrical distribution was found in the MLO direction in the case of the CC-view compression, while a shift of about 12% toward the lateral direction was found in the MLO-view case. CONCLUSIONS: The location of the fibroglandular tissue in the breast under compression during mammography and DBT image acquisition is a major factor for determining the actual glandular dose imparted during these examinations. A more realistic model of the parenchyma in the compressed breast, based on patient image data, was developed. This improved model more accurately reflects the fibroglandular tissue spatial distribution that can be found in patient breasts, and therefore might aid in future studies involving radiation dose and/or cancer development risk estimation.

Custom designed radial forearm free flap for reconstruction of nasomaxillary defects: Report of two cases.

Nasal amputation and nasomaxillary defects, need to reconstruct the internal lining, osteochondral structure, and external coating of the nose. Authors report a 70-year-old male and a 65-year-old female treated for nasomaxillary defects (Brown JS, Shaw RJ. The Lancet Oncology 2010;11:1001-1008) due to squamous cell carcinoma (SCC) where the tip of the nose was preserved. A new custom design of the radial forearm free flap (RFFF) consisting on a subcutaneous tissue (SCT) component, a skin paddle for the internal nasal vault lining, and a skin paddle for the external nasal skin coating was raised to treat both total thickness nasal defects. The dimension of each skin paddle corresponds to the defect measurements. The skin incisions of the custom design correspond to those of a conventional RFFF. The SCT component was harvested in a subcutaneous plane continuously with the skin island for the internal nasal lining which is drawn on the ulnar skin of the forearm. The component for the external nasal coating was drawn on the radial skin area of the flap. No postoperative complications and a satisfactory outcome was reported after 1 year of follow-up. This new custom design of the RFFF is described for reconstruction of nasomaxillary defects when the tip of the nose is preserved.

Breast MRI and X-ray mammography registration using gradient values.

Breast magnetic resonance imaging (MRI) and X-ray mammography are two image modalities widely used for early detection and diagnosis of breast diseases in women. The combination of these modalities, traditionally done using intensity-based registration algorithms, leads to a more accurate diagnosis and treatment, due to the capability of co-localizing lesions and susceptibles areas between the two image modalities. In this work, we present the first attempt to register breast MRI and X-ray mammographic images using intensity gradients as the similarity measure. Specifically, a patient-specific biomechanical model of the breast, extracted from the MRI image, is used to mimic the mammographic acquisition. The intensity gradients of the glandular tissue are directly projected from the 3D MRI volume to the 2D mammographic space, and two different gradient-based metrics are tested to lead the registration, the normalized cross-correlation of the scalar gradient values and the gradient correlation of the vectoral gradients. We compare these two approaches to an intensity-based algorithm, where the MRI volume is transformed to a synthetic computed tomography (pseudo-CT) image using the partial volume effect obtained by the glandular tissue segmentation performed by means of an Expectation-Maximization algorithm. This allows us to obtain the digitally reconstructed radiographies by a direct intensity projection. The best results are obtained using the scalar gradient approach along with a transversal isotropic material model, obtaining a target registration error (TRE), in millimeters, of 5.65 ±â€¯2.76 for CC- and of 7.83 ±â€¯3.04 for MLO-mammograms, while the TRE is 7.33 ±â€¯3.62 in the 3D MRI. We also evaluate the effect of the glandularity of the breast as well as the landmark position on the TRE, obtaining moderated correlation values (0.65 and 0.77 respectively), concluding that these aspects need to be considered to increase the accuracy in further approaches.

Monte Carlo study on optimal breast voxel resolution for dosimetry estimates in digital breast tomosynthesis.

Digital breast tomosynthesis (DBT) is currently used as an adjunct technique to digital mammography (DM) for breast cancer imaging. Being a quasi-3D image, DBT is capable of providing depth information on the internal breast glandular tissue distribution, which may be enough to obtain an accurate patient-specific radiation dose estimate. However, for this, information regarding the location of the glandular tissue, especially in the vertical direction (i.e. x-ray source to detector), is needed. Therefore, a dedicated reconstruction algorithm designed to localize the amount of glandular tissue, rather than for optimal diagnostic value, could be desirable. Such a reconstruction algorithm, or, alternatively, a reconstructed DBT image classification algorithm, could benefit from the use of larger voxels, rather than the small sizes typically used for the diagnostic task. In addition, the Monte Carlo (MC) based dose estimates would be accelerated by the representation of the breast tissue with fewer and larger voxels. Therefore, in this study we investigate the optimal DBT reconstructed voxel size that allows accurate dose evaluations (i.e. within 5%) using a validated Geant4-based MC code. For this, sixty patient-based breast models, previously acquired using dedicated breast computed tomography (BCT) images, were deformed to reproduce the breast during compression under a given DBT scenario. Two re-binning approaches were applied to the compressed phantoms, leading to isotropic and anisotropic voxels of different volumes. MC DBT simulations were performed reproducing the acquisition geometry of a SIEMENS Mammomat Inspiration system. Results show that isotropic cubic voxels of 2.73 mm size provide a dose estimate accurate to within 5% for 51/60 patients, while a comparable accuracy is obtained with anisotropic voxels of dimension 5.46 × 5.46 × 2.73 mm3. In addition, the MC simulation time is reduced by more than half in respect to the original voxel dimension of 0.273 × 0.273 × 0.273 mm3 when either of the proposed re-binning approaches is used. No significant differences in the effect of binning on the dose estimates are observed (Wilcoxon-Mann-Whitney test, p-value > 0.4) between the 0° the 23° (i.e. the widest angular range) exposure.

Human trophoblast stem cell self-renewal and differentiation: Role of decorin.

The origin and regulation of stem cells sustaining trophoblast renewal in the human placenta remain unclear. Decorin, a leucine-rich proteoglycan restrains trophoblast proliferation, migration/invasiveness and endovascular differentiation, and local decorin overproduction is associated with preeclampsia (PE). Here, we tested the role of decorin in human trophoblast stem cell self-renewal and differentiation, using two models: an immortalized first trimester trophoblast cell line HTR-8/SVneo (HTR) and freshly isolated primary trophoblast (p-trophoblast) from early first trimester (6-9 weeks) placentas. Self-renewal capacity was measured by spheroid forming ability of single cells on ultra-low attachment plates for multiple generations. Markers of embryonic stem (ES) cells, trophoblast stem (TS) cells and trophoblast were used to identify stem cell hierarchy. Differentiation markers for syncytial and extravillous (EVT) pathways were employed to identify differentiated cells. Bewo cells were additionally used to explore DCN effects on syncytialization. Results reveal that the incidence of spheroid forming stem-like cells was 13-15% in HTR and 0.1-0.4%, in early first trimester p-trophoblast, including a stem cell hierarchy of two populations of ES and TS-like cells. DCN restrained ES cell self-renewal, promoted ES to TS transition and maintenance of TS cell stem-ness, but inhibited TS cell differentiation into both syncytial and EVT pathways.

Multimodal Breast Parenchymal Patterns Correlation Using a Patient-Specific Biomechanical Model.

In this paper, we aim to produce a realistic 2-D projection of the breast parenchymal distribution from a 3-D breast magnetic resonance image (MRI). To evaluate the accuracy of our simulation, we compare our results with the local breast density (i.e., density map) obtained from the complementary full-field digital mammogram. To achieve this goal, we have developed a fully automatic framework, which registers MRI volumes to X-ray mammograms using a subject-specific biomechanical model of the breast. The optimization step modifies the position, orientation, and elastic parameters of the breast model to perform the alignment between the images. When the model reaches an optimal solution, the MRI glandular tissue is projected and compared with the one obtained from the corresponding mammograms. To reduce the loss of information during the ray-casting, we introduce a new approach that avoids resampling the MRI volume. In the results, we focus our efforts on evaluating the agreement of the distributions of glandular tissue, the degree of structural similarity, and the correlation between the real and synthetic density maps. Our approach obtained a high-structural agreement regardless the glandularity of the breast, whilst the similarity of the glandular tissue distributions and correlation between both images increase in denser breasts. Furthermore, the synthetic images show continuity with respect to large structures in the density maps.

A step-by-step review on patient-specific biomechanical finite element models for breast MRI to x-ray mammography registration.

Breast magnetic resonance imaging (MRI) and x-ray mammography are two image modalities widely used for the early detection and diagnosis of breast diseases in women. The combination of these modalities leads to a more accurate diagnosis and treatment of breast diseases. The aim of this paper is to review the registration between breast MRI and x-ray mammographic images using patient-specific finite element-based biomechanical models. Specifically, a biomechanical model is obtained from the patient's MRI volume and is subsequently used to mimic the mammographic acquisition. Due to the different patient positioning and movement restrictions applied in each image modality, the finite element analysis provides a realistic physics-based approach to perform the breast deformation. In contrast with other reviews, we do not only expose the overall process of compression and registration but we also include main ideas, describe challenges, and provide an overview of the used software in each step of the process. Extracting an accurate description from the MR images and preserving the stability during the finite element analysis require an accurate knowledge about the algorithms used, as well as the software and underlying physics. The wide perspective offered makes the paper suitable not only for expert researchers but also for graduate students and clinicians. We also include several medical applications in the paper, with the aim to fill the gap between the engineering and clinical performance.

Local breast density assessment using reacquired mammographic images.

PURPOSE: The aim of this paper is to evaluate the spatial glandular volumetric tissue distribution as well as the density measures provided by Volpara™ using a dataset composed of repeated pairs of mammograms, where each pair was acquired in a short time frame and in a slightly changed position of the breast. MATERIALS AND METHODS: We conducted a retrospective analysis of 99 pairs of repeatedly acquired full-field digital mammograms from 99 different patients. The commercial software Volpara™ Density Maps (Volpara Solutions, Wellington, New Zealand) is used to estimate both the global and the local glandular tissue distribution in each image. The global measures provided by Volpara™, such as breast volume, volume of glandular tissue, and volumetric breast density are compared between the two acquisitions. The evaluation of the local glandular information is performed using histogram similarity metrics, such as intersection and correlation, and local measures, such as statistics from the difference image and local gradient correlation measures. RESULTS: Global measures showed a high correlation (breast volume R=0.99, volume of glandular tissue R=0.94, and volumetric breast density R=0.96) regardless the anode/filter material. Similarly, histogram intersection and correlation metric showed that, for each pair, the images share a high degree of information. Regarding the local distribution of glandular tissue, small changes in the angle of view do not yield significant differences in the glandular pattern, whilst changes in the breast thickness between both acquisition affect the spatial parenchymal distribution. CONCLUSIONS: This study indicates that Volpara™ Density Maps is reliable in estimating the local glandular tissue distribution and can be used for its assessment and follow-up. Volpara™ Density Maps is robust to small variations of the acquisition angle and to the beam energy, although divergences arise due to different breast compression conditions.

Characterization of an outbreak of emerging bovine besnoitiosis in southwestern Spain.

Bovine besnoitiosis is an emerging disease in Europe, presenting quick spread toward central and southern Spain. Characterization of an outbreak in a free-ranging Limousin and Avileña beef cattle herd from southwestern Spain territories is attempted. Serological survey in the herd revealed increase of number of infected animals, from 34.3 % on first diagnoses/exams on December 2013 to 42.5 % in the second on April 2014. Blood analysis and serum biochemistry showed important alterations like leukocytosis (+33.2 % of mean value), with lymphocytosis (+205.3 %) and increase of LDH (+25.1 %), associated with tissue damage. Clinical cases were only observed in Limousin animals. Along with typical lesions of acute and chronic besnoitiosis, inflammatory and degenerative processes and parasitic cysts were present in the corpus cavernosum and the corpus spongiosum of penis. By using polymerase chain reaction (PCR) sequencing of 18S rDNA, Besnoitia besnoiti was confirmed as causative agent; microsatellite sequence analyses showed the homology of isolates with previously studied strains.

Angiomiolipoma nasal / Nasal angiomyolipoma

No disponible

Reoperative midface reconstruction.

Reoperative reconstruction of the midface is a challenging issue because of the complexity of this region and the severity of the aesthetic and functional sequela related to the absence or failure of a primary reconstruction. The different situations that can lead to the indication of a reoperative reconstructive procedure after previous oncologic ablative procedures in the midface are reviewed. Surgical techniques, anatomic problems, and limitations affecting the reoperative reconstruction in this region of the head and neck are discussed.

Implementation of a national metrology network of radionuclides used in nuclear medicine.

The Nuclear Medicine Services (NMS) in Brazil routinely use dose calibrators to measure the activity of solutions containing radiopharmaceuticals. These solutions are administered to patients with the intention to diagnose or treat illnesses. However, for optimal results, the activity of these radiopharmaceuticals must be determined as accurately as possible. The National Laboratory for Ionizing Radiation Metrology (LNMRI) led, since 1998, a comparison program for activity measurements of radiopharmaceuticals administered to patients in the NMS with the purpose promoting quality control. This program has been carried out successfully in Rio de Janeiro, but there is a need to implement it around the country. This can be resolved through the implementation of a network of regional laboratories at various locations throughout the national territory. Currently, such a network is active at a second site, located in Brasília, covering the needs of the Center-West Region, and at a third site, located in Porto Alegre, in the South Region. This work presents the results of comparisons for the radiopharmaceuticals nuclides 131I and 99Tcm and proves that the implementation of a radionuclide metrology network is feasible and viable.