Endoscopic submucosal dissection for the treatment of a large inflammatory fibroid polyp in the gastric antrum prolapsing into the duodenum: A case report.

RATIONALE: Inflammatory fibroid polyp (IFP), also known as Vanek tumor, is a rare, benign gastrointestinal lesion characterized by its inflammatory and fibroid histological features. IFP is often discovered incidentally during endoscopic examinations. It is exceedingly rare for an IFP to prolapse into the duodenum and results in incomplete obstruction of the pylorus. PATIENT CONCERNS: A 64-year-old male patient was admitted to the hospital with recurrent episodes of melena over a 6-month period, along with complaints of dizziness and fatigue in the past 10 days. DIAGNOSES: Gastroscopy showed a giant polypoid mass on the posterior wall of the gastric antrum, prolapsing into the duodenum. Abdominal computer tomography (CT) confirmed the tumor protruding into the duodenum. Pathologic examination of the resected specimen confirmed the IFP diagnosis. INTERVENTIONS: The giant tumor was completely and successfully excised using endoscopic submucosal dissection (ESD). After the surgery, the patient underwent acid suppression and fluid replenishment therapy. OUTCOMES: The patient responded well to ESD and was discharged in stable condition. As of the submission of the case report, there has been no recurrence of the tumor after a 5-month follow-up, and the patient is still under follow-up. LESSONS: While IFPs have traditionally been managed surgically, ESD demonstrates promising treatment outcomes, avoiding the need for surgical distal gastrectomy, and emerges as a safe and effective treatment option.

SC-Net: Symmetrical conical network for colorectal pathology image segmentation.

BACKGROUND AND OBJECTIVE: Image segmentation of histopathology of colorectal cancer is a core task of computer aided medical image diagnosis system. Existing convolutional neural networks generally extract multi-scale information in linear flow structures by inserting multi-branch modules, which is difficult to extract heterogeneous semantic information under multi-level and different receptive field and tough to establish context dependency among different receptive field features. METHODS: To address these issues, we propose a symmetric spiral progressive feature fusion encoder-decoder network called the Symmetric Conical Network (SC-Net). First, we design a Multi-scale Feature Extraction Block (MFEB) matching with the Symmetric Conical Network to obtain multi-branch heterogeneous semantic information under different receptive fields, so as to enrich the diversity of extracted feature information. The encoder is composed of MFEB through spiral and multi-branch arrangement to enhance context dependence between different information flow. Secondly, the information loss of contour, color and others in high-level semantic information through causally stacking MFEB, the Feature Mapping Layer (FML) is designed to map low-level features to high-level semantic features along the down-sampling branch and solve the problem of insufficient global feature extraction in deep levels. RESULTS: The SC-Net was evaluated on our self-constructed colorectal cancer dataset, a publicly available breast cancer dataset and a polyp dataset. The results revealed that the mDice of segmentation reached 0.8611, 0.7259 and 0.7144. We compare our model with the state-of-art semantic segmentation UNet++, PSPNet, Attention U-Net, R2U-Net and other advanced segmentation networks. The experimental results demonstrate that we achieve the most advanced performance. CONCLUSIONS: The results indicate that the proposed SC-Net excels in segmenting H&E stained pathology images, effectively preserving morphological features and spatial information even in scenarios with weak texture, poor contrast, and variations in appearance.

Transcriptomic Analysis Reveals Intrinsic Abnormalities in Endometrial Polyps.

Endometrial polyps (EPs) are benign overgrowths of the endometrial tissue lining the uterus, often causing abnormal bleeding or infertility. This study analyzed gene expression differences between EPs and adjacent endometrial tissue to elucidate intrinsic abnormalities promoting pathological overgrowth. RNA sequencing of 12 pairs of EPs and the surrounding endometrial tissue from infertile women revealed 322 differentially expressed genes. Protein-protein interaction network analysis revealed significant alterations in specific signaling pathways, notably Wnt signaling and vascular smooth muscle regulation, suggesting these pathways play critical roles in the pathophysiology of EPs. Wnt-related genes DKK1 and DKKL1 were upregulated, while GPC3, GREM1, RSPO3, SFRP5, and WNT10B were downregulated. Relevant genes for vascular smooth muscle contraction were nearly all downregulated in EPs, including ACTA2, ACTG2, KCNMB1, KCNMB2, MYL9, PPP1R12B, and TAGLN. Overall, the results indicate fundamental gene expression changes promote EP formation through unrestrained growth signaling and vascular defects. The intrinsic signaling abnormalities likely contribute to clinical symptoms of abnormal uterine bleeding and infertility common in EP patients. This analysis provides molecular insights into abnormal endometrial overgrowth to guide improved diagnostic and therapeutic approaches for this troublesome women's health condition. Confirmation of expanded cohorts and further investigations into implicated regulatory relationships are warranted.

Dual ensemble system for polyp segmentation with submodels adaptive selection ensemble.

Colonoscopy is one of the main methods to detect colon polyps, and its detection is widely used to prevent and diagnose colon cancer. With the rapid development of computer vision, deep learning-based semantic segmentation methods for colon polyps have been widely researched. However, the accuracy and stability of some methods in colon polyp segmentation tasks show potential for further improvement. In addition, the issue of selecting appropriate sub-models in ensemble learning for the colon polyp segmentation task still needs to be explored. In order to solve the above problems, we first implement the utilization of multi-complementary high-level semantic features through the Multi-Head Control Ensemble. Then, to solve the sub-model selection problem in training, we propose SDBH-PSO Ensemble for sub-model selection and optimization of ensemble weights for different datasets. The experiments were conducted on the public datasets CVC-ClinicDB, Kvasir, CVC-ColonDB, ETIS-LaribPolypDB and PolypGen. The results show that the DET-Former, constructed based on the Multi-Head Control Ensemble and the SDBH-PSO Ensemble, consistently provides improved accuracy across different datasets. Among them, the Multi-Head Control Ensemble demonstrated superior feature fusion capability in the experiments, and the SDBH-PSO Ensemble demonstrated excellent sub-model selection capability. The sub-model selection capabilities of the SDBH-PSO Ensemble will continue to have significant reference value and practical utility as deep learning networks evolve.

Risk prediction and analysis of gallbladder polyps with deep neural network.

The aim of this study is to analyze the risk factors associated with the development of adenomatous and malignant polyps in the gallbladder. Adenomatous polyps of the gallbladder are considered precancerous and have a high likelihood of progressing into malignancy. Preoperatively, distinguishing between benign gallbladder polyps, adenomatous polyps, and malignant polyps is challenging. Therefore, the objective is to develop a neural network model that utilizes these risk factors to accurately predict the nature of polyps. This predictive model can be employed to differentiate the nature of polyps before surgery, enhancing diagnostic accuracy. A retrospective study was done on patients who had cholecystectomy surgeries at the Department of Hepatobiliary Surgery of the Second People's Hospital of Shenzhen between January 2017 and December 2022. The patients' clinical characteristics, lab results, and ultrasonographic indices were examined. Using risk variables for the growth of adenomatous and malignant polyps in the gallbladder, a neural network model for predicting the kind of polyps will be created. A normalized confusion matrix, PR, and ROC curve were used to evaluate the performance of the model. In this comprehensive study, we meticulously analyzed a total of 287 cases of benign gallbladder polyps, 15 cases of adenomatous polyps, and 27 cases of malignant polyps. The data analysis revealed several significant findings. Specifically, hepatitis B core antibody (95% CI -0.237 to 0.061, p < 0.001), number of polyps (95% CI -0.214 to -0.052, p = 0.001), polyp size (95% CI 0.038 to 0.051, p < 0.001), wall thickness (95% CI 0.042 to 0.081, p < 0.001), and gallbladder size (95% CI 0.185 to 0.367, p < 0.001) emerged as independent predictors for gallbladder adenomatous polyps and malignant polyps. Based on these significant findings, we developed a predictive classification model for gallbladder polyps, represented as follows, Predictive classification model for GBPs = -0.149 * core antibody - 0.033 * number of polyps + 0.045 * polyp size + 0.061 * wall thickness + 0.276 * gallbladder size - 4.313. To assess the predictive efficiency of the model, we employed precision-recall (PR) and receiver operating characteristic (ROC) curves. The area under the curve (AUC) for the prediction model was 0.945 and 0.930, respectively, indicating excellent predictive capability. We determined that a polyp size of 10 mm served as the optimal cutoff value for diagnosing gallbladder adenoma, with a sensitivity of 81.5% and specificity of 60.0%. For the diagnosis of gallbladder cancer, the sensitivity and specificity were 81.5% and 92.5%, respectively. These findings highlight the potential of our predictive model and provide valuable insights into accurate diagnosis and risk assessment for gallbladder polyps. We identified several risk factors associated with the development of adenomatous and malignant polyps in the gallbladder, including hepatitis B core antibodies, polyp number, polyp size, wall thickness, and gallbladder size. To address the need for accurate prediction, we introduced a novel neural network learning algorithm. This algorithm utilizes the aforementioned risk factors to predict the nature of gallbladder polyps. By accurately identifying the nature of these polyps, our model can assist patients in making informed decisions regarding their treatment and management strategies. This innovative approach aims to improve patient outcomes and enhance the overall effectiveness of care.

Single-polyp metabolomics for coral health assessment.

Coral reef ecosystems supported by environmentally sensitive reef-building corals face serious threats from human activities. Our understanding of these reef threats is hampered by the lack of sufficiently sensitive coral environmental impact assessment systems. In this study, we established a platform for metabolomic analysis at the single-coral-polyp level using state-of-the-art mass spectrometry (probe electrospray ionization/tandem mass spectrometry; PESI/MS/MS) capable of fine-scale analysis. We analyzed the impact of the organic UV filter, benzophenone (BP), which has a negative impact on corals. We also analyzed ammonium and nitrate samples, which affect the environmental sensitivity of coral-zooxanthella (Symbiodiniaceae) holobionts, to provide new insights into coral biology with a focus on metabolites. The method established in this study breaks new ground by combining PESI/MS/MS with a technique for coral polyps that can control the presence or absence of zooxanthellae in corals, enabling functions of zooxanthellae to be assessed on a polyp-by-polyp basis for the first time. This system will clarify biological mechanisms of corals and will become an important model system for environmental impact assessment using marine organisms.

A colonial serrated polyp classification model using white-light ordinary endoscopy images with an artificial intelligence model and TensorFlow chart.

In this study, we implemented a combination of data augmentation and artificial intelligence (AI) model-Convolutional Neural Network (CNN)-to help physicians classify colonic polyps into traditional adenoma (TA), sessile serrated adenoma (SSA), and hyperplastic polyp (HP). We collected ordinary endoscopy images under both white and NBI lights. Under white light, we collected 257 images of HP, 423 images of SSA, and 60 images of TA. Under NBI light, were collected 238 images of HP, 284 images of SSA, and 71 images of TA. We implemented the CNN-based artificial intelligence model, Inception V4, to build a classification model for the types of colon polyps. Our final AI classification model with data augmentation process is constructed only with white light images. Our classification prediction accuracy of colon polyp type is 94%, and the discriminability of the model (area under the curve) was 98%. Thus, we can conclude that our model can help physicians distinguish between TA, SSA, and HPs and correctly identify precancerous lesions such as TA and SSA.

Peutz-Jeghers syndrome with polyps in the stomach, duodenum, and small and large intestine: a case report.

BACKGROUND: Peutz-Jeghers syndrome is a rare hereditary condition characterized by gastrointestinal polyps and pigmented oral lesions. The case contributes to a deeper understanding of Peutz-Jeghers syndrome and underscores the significance of interdisciplinary collaboration for accurate diagnosis and tailored therapeutic strategies. CASE DESCRIPTION: We present a case of a 15-year-old Afghan female patient with multiple polyps throughout the gastrointestinal tract and mucocutaneous pigmentation. Despite previous medical visits and colonoscopies, her symptoms persisted. A multidisciplinary team discussed the case and recommended further investigations and interventions. A polypectomy was performed, confirming the presence of hamartomatous polyps. The patient was diagnosed with Peutz-Jeghers syndrome, but during the course of treatment she went through complications and was managed surgically as well. CONCLUSION: Timely polyp removal and lifelong surveillance are crucial in managing Peutz-Jeghers syndrome. Further research and genetic analysis are needed to improve understanding and management of this rare disorder.

[Gastric hamartomatous inverted polyps: a clinicopathological analysis of five cases].

Objective: To investigate the endoscopic and histopathological features, diagnosis and differential diagnosis of gastric hamartomatous inverted polyp (GHIP). Methods: Five cases of GHIP were collected at the University Town Hospital of Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China, from May 2021 to May 2023. The endoscopic, pathological and immunohistochemical features of the 5 GHIP cases were analyzed. The relevant literature was reviewed. Results: There were 3 males and 2 females, aged from 49 to 60 years, with a mean age of 56 years. The lesions were located in the fundus and body of the stomach, and presented as polyps or masses under endoscopy. Microscopically, the lesions were mainly in the submucosa and consisted of lobulated or clustered gastric glandular epithelium surrounded by hyperplastic smooth muscle. In some areas, there were differentiated glandular elements mimicking the normal gastric mucosa. The irregularly dilated glandular elements in the center were lined by hyperplastic foveolar epithelium, while the glands in the periphery were fundic or pyloric glands. In addition, in some areas, the glands showed cystic expansion, disordered arrangement and lack of differentiation. The hyperplastic glandular epithelium included foveolar epithelium, fundic gland and pyloric gland. There were scattered neuroendocrine cells and smooth muscle bundles in the stroma. Immunohistochemically, the tumor cells were positive for MUC5AC, MUC6, Pepsinogen Ⅰ and H+/K+ ATPase ß, but negative for MUC2. The scattered neuroendocrine cells were positive for synaptophysin, and the desmin stain highlighted hyperplastic smooth muscle bundles. One case was classified as type 2 gastric inverted polyp, and 4 cases were classified as type 3. Conclusions: GHIP is a rare gastric polyp with unique histological features. It should be distinguished from inverted hyperplastic polyp, gastritis cystica profunda, adenomyoma, hyperplastic polyps and well-differentiated gastric tubular adenocarcinoma, etc. Improving the understanding of its pathogenesis and diagnostic features can help avoid misdiagnoses.

Manually driven versus motor driven hysteroscopic tissue removal system for polypectomy: Long-term results.

OBJECTIVE: The aim of this follow-up study is to compare a manually driven hysteroscopic tissue removal system (ResectrTM 9 Fr) with a motor driven system (TruclearTM) in terms of long-term clinical outcomes such as abnormal uterine bleeding and polyp recurrence. STUDY DESIGN: This is a follow-up of a multicenter randomized controlled trial comparing a manually and motor driven hysteroscopic tissue removal system for polypectomy. This prospective cohort study was performed at Ghent University Hospital (Ghent, Belgium) and Catharina Hospital Eindhoven (Eindhoven, the Netherlands). The trial was registered at Clinicaltrials.gov (Trial ID = NCT05337605, April 2022). Seventy-five women with abnormal uterine bleeding who participated in the randomized controlled trial and had pathological confirmation of the diagnosis of an endometrial polyp, were contacted. Fifty-five women (70.67 %) were willing to participate in this follow-up study. The primary outcome was the recurrence and/or persistence of abnormal uterine bleeding and the time to the recurrence of abnormal uterine bleeding. Secondary outcomes were polyp recurrence and time to polyp recurrence, symptom relief, satisfaction score regarding symptom relief and general satisfaction score regarding the surgical procedure. RESULTS: In the manually driven group, the mean time to the recurrence or persistence of abnormal uterine bleeding was 26 months (95 % CI 20 - 32). In the motor driven group, the mean time to the recurrence or persistence of abnormal uterine bleeding was 29 months (95 % CI 23- 34). A log-rank test showed a non-significant difference between both groups (P =.77). There was no significant difference in polyp recurrence (P =.22) or symptom relief between the two groups (P =.67). Additionally, the groups did not differ in satisfaction scores regarding symptoms or polypectomy (P =.16 and P =.61, respectively). CONCLUSION: This long-term follow-up study showed no statistically significant difference in the recurrence and persistence of abnormal uterine bleeding between a manually and motor driven hysteroscopic tissue removal system for polypectomy.

Utilizing adaptive deformable convolution and position embedding for colon polyp segmentation with a visual transformer.

Polyp detection is a challenging task in the diagnosis of Colorectal Cancer (CRC), and it demands clinical expertise due to the diverse nature of polyps. The recent years have witnessed the development of automated polyp detection systems to assist the experts in early diagnosis, considerably reducing the time consumption and diagnostic errors. In automated CRC diagnosis, polyp segmentation is an important step which is carried out with deep learning segmentation models. Recently, Vision Transformers (ViT) are slowly replacing these models due to their ability to capture long range dependencies among image patches. However, the existing ViTs for polyp do not harness the inherent self-attention abilities and incorporate complex attention mechanisms. This paper presents Polyp-Vision Transformer (Polyp-ViT), a novel Transformer model based on the conventional Transformer architecture, which is enhanced with adaptive mechanisms for feature extraction and positional embedding. Polyp-ViT is tested on the Kvasir-seg and CVC-Clinic DB Datasets achieving segmentation accuracies of 0.9891 ± 0.01 and 0.9875 ± 0.71 respectively, outperforming state-of-the-art models. Polyp-ViT is a prospective tool for polyp segmentation which can be adapted to other medical image segmentation tasks as well due to its ability to generalize well.

Investigation of Clinical, Laboratory, Imaging Findings and Histopathological Features of Patients with Gastric Neuroendocrine Cell Hyperplasia.

BACKGROUND/AIMS: Neuroendocrine cell hyperplasia is a non-neoplastic proliferation of enterochromaffin-like cells and is considered a premalignant lesion because of their potential to progress to neuroendocrine tumor. In this study, we aimed to evaluate the demographic and clinical features, laboratory, radiological and endoscopic findings, gastric biopsy histopathological features, follow-up frequency, and histopathological findings of patients diagnosed with gastric neuroendocrine cell hyperplasia as well as to investigate the factors that play a role in the development of neuroendocrine tumors on the basis of neuroendocrine cell hyperplasia. MATERIALS AND METHODS: The study has been conducted in 2 centers with 282 patients that were grouped as those with and without neuroendocrine tumor. Individuals with control endoscopy were separated as those with regression of neuroendocrine cell hyperplasia and those without regression, and the determined parameters were evaluated between the groups. RESULTS: The most common histological subtype of neuroendocrine cell hyperplasia was linear+micronodular (50.4%). Neuroendocrine tumor developed in 4.3% (12/282) of the patients with neuroendocrine cell hyperplasia after a mean of 36 months. The presence of polyps as confirmed via endoscopy and dysplasia as confirmed via histopathological examination was significantly higher in favor of the group with neuroendocrine tumor (P = .01). In patients with neuroendocrine cell hyperplasia regressed and patients in whom it did not regress were examined, the rate of asymptomatic patients and increased sedimentation rate were found in favor of the group that did not regress (P = .02 and P = .02), but no difference was found in other parameters. CONCLUSION: Neuroendocrine tumor development rate was found to be 4.3% in the background of neuroendocrine cell hyperplasia. Two factors predicting progression from neuroendocrine cell hyperplasia to neuroendocrine tumor can be elaborated as the presence of polypoid appearance due to neuroendocrine cell hyperplasia as confirmed via endoscopy and dysplasia as confirmed via histopathological examination.

Systematic review and meta-analysis of the etiology of heavy menstrual bleeding in 2,770 adolescent females.

BACKGROUND: Adolescent heavy menstrual bleeding(HMB), menorrhagia or abnormal uterine bleeding commonly occur in adolescent women. The differential diagnosis can be challenging. The pneumonic: PALM-COEIN (polyp, adenomyosis, leiomyoma, malignancy and hyperplasia, coagulopathy, ovulatory dysfunction, endometrial, iatrogenic, and not yet classified), is commonly used but it does not stratify as to the likelihood of a disorder. We have sought to develop a probability-based differential diagnosis for Adolescent HMB, menorrhagia or abnormal uterine bleeding. METHODS: A comprehensive literature search was conducted using PubMed, EMBASE, and SCOPUS databases. Case series describing adolescents from 10-19 years of age with HMB, menorrhagia or abnormal uterine bleeding was acceptable if: more than 10 patients were included; editorials, case reports, and secondary sources such as review articles, or book chapters were excluded. No language filter was used, but an English abstract was required. The etiology of HMB, menorrhagia or abnormal uterine bleeding, and the country of origin was extracted from articles that met inclusion criteria. Cumulative rate estimates were determined by Bayesian probability modeling. RESULTS: Seventeen full text articles were reviewed in detail; 2,770 patients were included. The most frequent causes of HMB were Ovarian Uterine Disorders (23.7%; 95% CredI 22-25.5%), Coagulation Disorders (19.4%; 95% CredI 17.8-21.1%), and Platelet Disorders (6.23%; 95% CredI 5.27-7.27%) with 45.9% (95% CredI 43.8-47.%9) of the cases of indeterminate origin. CONCLUSIONS: The leading causes of HMB in healthy adolescent females were varied. The sub-analysis identified distinct etiologies, suggesting that multiple factors must be considered in the evaluation of HMB. While PALM-COEIN (polyp, adenomyosis, leiomyoma, malignancy and hyperplasia, coagulopathy, ovulatory dysfunction, endometrial, iatrogenic, and not yet classified) provides us with a comprehensive picture of the possible causes of HMB in females, this systematic review assigns probabilities to the etiologies of HMB in adolescent females, providing physicians with a more focused and efficient pathway to diagnosis.

Cáncer incidental de vesícula: incidencia y factores asociados en pacientes de una institución de la ciudad de Medellín / Incidental gallbladder cancer: Incidence and associated factors in patients from an institution in the city of Medellín

Introducción. El cáncer de vesícula biliar es una de las neoplasias más frecuentes de la vía biliar y la mayoría de los casos se diagnostican de forma incidental o en estadios avanzados. En Colombia existen pocas publicaciones acerca de la prevalencia y características clínicas de pacientes con cáncer insospechado de vesícula biliar. El objetivo de este trabajo fue actualizar la información existente. Métodos. Estudio de tipo transversal basado en registros médicos. Como variable de resultado se definió el hallazgo incidental de patología maligna reportado por un patólogo y el subtipo histológico. Se midieron variables demográficas, clínicas y quirúrgicas. Se calcularon OR con sus respectivos intervalos de confianza (IC95%). Resultados. De los 2630 casos analizados, en cuatro se hizo diagnóstico de cáncer incidental de vesícula, con una prevalencia del 0,15 %. Se encontraron como características asociadas al cáncer incidental de vesícula, la edad, el antecedente de cáncer y la presencia de pólipos. Conclusiones. Esta es una patología poco frecuente en la población evaluada, lo que permite afirmar que no es necesario realizar estudios prequirúrgicos más amplios de forma rutinaria, a menos que el paciente presente alguno de los factores asociados.

Introduction. Gallbladder cancer is one of the most common neoplasms of the bile duct and most cases are diagnosed incidentally or in advanced stages. In Colombia, there are few publications about the prevalence and clinical characteristics of patients with unsuspected gallbladder cancer. The objective of this work was to update the existing information. Methods. Cross-sectional study based on medical records. The incidental finding of malignant pathology reported and the histological subtype were defined as the outcome variable. Demographic, clinical and surgical variables were measured. ORs were calculated with their respective 95% CI. Results. Of the 2630 cases analyzed, four were diagnosed with incidental gallbladder cancer, with a prevalence of 0.15%. Characteristics associated with incidental gallbladder cancer were age, history of cancer and the presence of polyps. Conclusions. This is a rare pathology in the population evaluated, which allows us to recommend that it is not necessary to routinely perform more extensive presurgical studies, unless the patient presents any of the associated factors.

Gastric fundic gland polyposis and cancer development after eradication of Helicobacter pylori in patient with gastric adenocarcinoma and proximal polyposis of the stomach (GAPPS).

A 44-year-old woman with gastric cancer (GC) and fundic gland polyposis (FGPs) was referred to our hospital for further diagnosis and treatment. She successfully underwent eradication therapy for Helicobacter pylori (HP) 6 years ago, but did not exhibit FGPs at that time. When she underwent an esophagogastroduodenoscopy 2, 4, and 5 years after the eradication of HP, her imaging results revealed the existence of FGPs which gradually increased in her gastric fundus and body. Gastric adenocarcinoma and proximal polyposis of the stomach (GAPPS) was suspected and a mutational analysis was performed, revealing an APC promoter 1B variant c.-191T > C. A robotic total gastrectomy with lymphadenectomy was performed. Histopathological analysis of the surgical specimens revealed GC with no lymph node metastasis. GAPPS is characterized by GC and FGPs. However, our case shows different gastric phenotypes that are dependent on the status of HP infection.

Expression levels of ADAMTS 5, 9, and 12 in endometrial polyps and their predictive value for the diagnosis and recurrence of endometrial polyps.

PURPOSE: Endometrial polyps (EPs) are common gynecological disorders for which no clear etiology has been found. ADAMTS have been associated with a variety of diseases. This study aimed to investigate the potential correlation between serologic levels of ADAMTS 5, 9, and 12 in patients with EPs. METHODS: A total of 88 patients were categorized into two groups: the EPs group, consisting of recurrent EPs and first occurrence EPs, and a control group. The study compared the general information and serum levels of ADAMTS 5, 9, and 12 between the groups. RESULTS: Regarding the general data, a statistically significant age difference (p < 0.05) was observed, while no significant differences were found in the other variables. After considering age as a confounding factor, the previously observed statistical significance in the differences of ADAMTS5 and 9 between the groups diminished. However, it was found that the concentrations of ADAMTS12 in both the EPs group and the recurrent EPs group were significantly higher compared to the control group and the first occurrence EPs group (p < 0.05). ROC curves were generated to determine the critical values of ADAMTS12 for predicting EPs and recurrent EPs, which were found to be 0.6962 ng/ml (sensitivity: 100 %, specificity: 39.5 %) and 0.8768 ng/ml (sensitivity: 75.0 %, specificity: 76.3 %), respectively. CONCLUSION: Our findings revealed elevated serologic levels of ADAMTS12 in the EPs group, particularly in the recurrent EPs group. Furthermore, ADAMTS-12 was identified as a valuable biomarker for assisting in the diagnosis and prediction of EPs recurrence.

The risk factors for premalignant and malignant endometrial polyps in premenopausal and postmenopausal women and trends over the past decade: A retrospective study in a single center, South Korea.

OBJECTIVES: To assess the prevalence and risk factors for premalignancy and malignancy in endometrial polyps and to evaluate trends over the past decade. STUDY DESIGN: This was a retrospective study of patients who underwent hysteroscopic polypectomy at Inha University Hospital, South Korea between January 2013 and June 2023. The demographic and clinical characteristics of the patients reviewed to identify risk factors for premalignancy and malignancy in endometrial polyps included the following: age, parity, body mass index, menopausal status, abnormal uterine bleeding symptoms, diabetes mellitus, hypertension, polycystic ovarian syndrome, use of menopausal hormonal therapy or oral contraceptives, tamoxifen treatment in patients with breast cancer, and the number of polyps. RESULTS: In total, 725 patients were enrolled, among whom 52 (7.2 %) had premalignant and malignant lesions. In logistic regression analysis, menopause (OR: 8.37, 95 % CI [3.33-21.04]), abnormal uterine bleeding (OR: 7.42, 95 % CI [2.13-25.86]), obesity (OR: 3.22, 95 % CI [1.53-6.77]), multiple polyps (OR: 2.86, 95 % CI [1.39-5.88]) and nulliparity (OR: 2.64, 95 % CI [1.13-6.19]) were significantly associated with premalignancy and malignancy in polyps. Annual trends during the study period showed an increase in the number of patients with three of the five risk factors (obesity, multiple polyps, and nulliparity) and an increase in the prevalence of premalignancy and malignancy in polyps. CONCLUSIONS: Menopause, abnormal uterine bleeding, obesity, multiple polyps, and nulliparity increase the risk of premalignancy and malignancy in endometrial polyps. The prevalence of premalignant and malignant polyps has been increasing over the past decade. The risk factors that have contributed to this trend were obesity, nulliparity, and multiple polyps.