Abdominal wall endometriosis (AWE) is a rare condition defined by the presence of endometrial tissue in the subcutaneous fatty layer and the muscles of the abdominal wall. It is usually caused by the dissemination of endometrial tissue in the wound at the time of obstetrical and gynecological surgeries. AWE is rare and difficult to diagnose. The most frequent clinical presentation is that of a palpable subcutaneous mass near surgical scars associated with cyclic pain and swelling during menses. AWE may be an underreported pathology partly because it has scarcely received attention in the radiologic literature. Its frequency is expected to rise along with the increasing rate of cesarean deliveries; thus, it is important that physicians or sonographers are familiar with this pathology. The purpose of our review is to present the latest data regarding risk factors, clinical and imagisticfindings, and management of AWE.
Background and objective: Spontaneous heterotopic pregnancy (SHP) is a rare condition represented by the synchronous coexistence of an intrauterine and an ectopic pregnancy. It rarely occurs with natural conception and is usually a consequence of assisted reproductive techniques. Diagnosis of SHP can be a challenge for the clinician. The evolution of the intrauterine pregnancy is dependent on many factors, such as the location of the heterotopic pregnancy, gestational age at the time of diagnosis, the surgical procedure, the presence of other risk factors, early or delayed management. The aim of this systematic review of the literature was to extract existing evidence on spontaneous heterotopic pregnancy with otherwise unaffected intrauterine pregnancy. Materials and Methods: From a total of 1907 database entries identified in PubMed, EMBASE and Cochrane reviews, we selected 18 papers for narrative synthesis, for which we explored the diagnostic options, treatment, and outcome of these extremely rare epidemiologic occurrences. Manuscripts were assessed using the CARE guidelines for reporting case reports. Results: The main symptom was abdominal pain, and the preferred treatment approach was surgical, more precisely, using a laparoscopic approach. Most cases presented no risk factors, and the diagnosis was mostly made in the first semester. Conclusions: Normal follow-up and evolution of intrauterine pregnancy have been observed regardless of surgical approach (open or laparoscopic). Early diagnosis and treatment are advised, as they impact maternal and fetal outcomes. Evidence on this topic is scarce, predominantly comprised of case reports with variable degrees of adherence to dissemination guidelines. More studies on this topic are required to optimize care protocols for this type of pregnancy.
1 January 2021 in European Journal of Obstetrics & Gynecology and Reproductive Biology
Cervical cancer represents a major health problem among females due to its increased mortality rate. The conventional therapies are very aggressive and unsatisfactory when it comes to survival rate, especially in terminal stages, which requires the development of new treatment alternatives. With the use of nanotechnology, various chemotherapeutic drugs can be transported via nanocarriers directly to cervical cancerous cells, thus skipping the hepatic first-pass effect and decreasing the rate of chemotherapy side effects. This review comprises various drug delivery systems that were applied in cervical cancer, such as lipid-based nanocarriers, polymeric and dendrimeric nanoparticles, carbon-based nanoparticles, metallic nanoparticles, inorganic nanoparticles, micellar nanocarriers, and protein and polysaccharide nanoparticles. Nanoparticles have a great therapeutic potential by increasing the pharmacological activity, drug solubility, and bioavailability. Through their mechanisms, they highly increase the toxicity in the targeted cervical tumor cells or tissues by linking to specific ligands. In addition, a nondifferentiable model is proposed through holographic implementation in the dynamics of drug delivery dynamics. As any hologram functions as a deep learning process, the artificial intelligence can be proposed as a new analyzing method in cervical cancer.