Purpose: Uterine sarcomas are rare tumours characterized by clinical and histopathological diversity and poor prognosis. We analyzed diagnostic, prognostic and therapeutic difficulties encountered with these tumors by insisting on the importance of early diagnosis.
Patients And Methods: From 1997 to 2004 ten patients with uterine sarcoma who underwent surgery in the obstetrics and gynecology unit at the Tunis maternity center were included in this retrospective study. The tumors were classified at the time of diagnosis using the FIGO staging system. The histological diagnosis was based on the WHO classification.
Results: There were 5 cases of leiomyosarcoma, 2 cases of carcinosarcoma, 2 cases of endometrial stromal sarcoma and 1 adenosarcoma. There were four cases of stage I, two cases of stage II, two cases of stage III and two of stage IV tumors. The diagnosis of uterine sarcoma was strongly suspected and proved before the initial operation in 20% of cases and during this operation in 60% of cases. Diagnosis was only established at the histological exam in two cases. Total hysterectomy with bilateral salpingo-oophorectomy was performed in 90% of patients. Radiation therapy was performed in four. Chemotherapy was delivered in two patients. After an average of four years five patients were in remission, three had died and two were lost to follow-up.
Conclusion: Early preoperative or intra-operative diagnosis is essential while awaiting for more effective chemotherapy protocols or therapeutic strategies.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/s0368-2315(06)76407-9 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Viral Oncogenesis: Synergistic Role of Genome Integration and Persistence.
Viruses
December 2024
Laboratory of Virology, National Institute for Infectious Diseases "Lazzaro Spallanzani" (IRCCS), 00149 Rome, Italy.
Persistence is a strategy used by many viruses to evade eradication by the immune system, ensuring their permanence and transmission within the host and optimizing viral fitness. During persistence, viruses can trigger various phenomena, including target organ damage, mainly due to an inflammatory state induced by infection, as well as cell proliferation and/or immortalization. In addition to immune evasion and chronic inflammation, factors contributing to viral persistence include low-level viral replication, the accumulation of viral mutants, and, most importantly, maintenance of the viral genome and reliance on viral oncoprotein production.
View Article and Find Full Text PDFIntegrating Interpretability in Machine Learning and Deep Neural Networks: A Novel Approach to Feature Importance and Outlier Detection in COVID-19 Symptomatology and Vaccine Efficacy.
Viruses
November 2024
Faculty of Medical and Health Sciences, Tel Aviv University, Tel Aviv 6997801, Israel.
In this study, we introduce a novel approach that integrates interpretability techniques from both traditional machine learning (ML) and deep neural networks (DNN) to quantify feature importance using global and local interpretation methods. Our method bridges the gap between interpretable ML models and powerful deep learning (DL) architectures, providing comprehensive insights into the key drivers behind model predictions, especially in detecting outliers within medical data. We applied this method to analyze COVID-19 pandemic data from 2020, yielding intriguing insights.
View Article and Find Full Text PDFReaching Forest Workers with Yellow Fever Vaccine Through Engagement of the Private Sector in Central African Republic.
Vaccines (Basel)
December 2024
World Health Organization, 20 Avenue Appia, 1211 Geneva, Switzerland.
: Yellow fever (YF) outbreaks continue to affect populations that are not reached by routine immunization services, such as workers at a high risk of occupational exposure to YF. In the Central African Republic (CAR), YF cases were detected in districts characterized by the presence of workers in forest areas. We developed an innovative approach based on a local partnership with private companies of the extractive industry to administer YF vaccine to workers in remote areas during the response to an outbreak.
View Article and Find Full Text PDFMambaPose: A Human Pose Estimation Based on Gated Feedforward Network and Mamba.
Sensors (Basel)
December 2024
School of Electronic Information Engineering, Taiyuan University of Science and Technology, Taiyuan 030024, China.
Human pose estimation is an important research direction in the field of computer vision, which aims to accurately identify the position and posture of keypoints of the human body through images or videos. However, multi-person pose estimation yields false detection or missed detection in dense crowds, and it is still difficult to detect small targets. In this paper, we propose a Mamba-based human pose estimation.
View Article and Find Full Text PDFMachine Learning Recognizes Stages of Parkinson's Disease Using Magnetic Resonance Imaging.
Sensors (Basel)
December 2024
Faculty of Computer Science, Polish-Japanese Academy of Information Technology, 86 Koszykowa Street, 02-008 Warsaw, Poland.
Neurodegenerative diseases (NDs), such as Alzheimer's disease (AD) and Parkinson's disease (PD), are debilitating conditions that affect millions worldwide, and the number of cases is expected to rise significantly in the coming years. Because early detection is crucial for effective intervention strategies, this study investigates whether the structural analysis of selected brain regions, including volumes and their spatial relationships obtained from regular T1-weighted MRI scans ( = 168, PPMI database), can model stages of PD using standard machine learning (ML) techniques. Thus, diverse ML models, including Logistic Regression, Random Forest, Support Vector Classifier, and Rough Sets, were trained and evaluated.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!