Uterine leiomyomas (ULs) can be considered as the most common benign monoclonal tumors of the smooth muscle cells in the myometrium (Flynn et al., 2006). Evidence suggests that 70% of women may develop uterine fibroids. Although this disorder may be without signs and symptoms, in 40 to 50 percent of women over age 35 it may present as menorrhagia, infertility, pain, and recurrent pregnancy loss (RPL) (Marino et al., 2004; Wang et al., 2015). There are different risk factors influencing the growth of UL, including: ethnicity, smoking, family history, obesity, diet rich in meat, oral contraceptive pills, age, and biological biomarkers (Faerstein et al., 2001; Keshavarzi et al., 2017). Despite the various studies conducted to understand UL etiology, the exact mechanism of UL pathogenesis is not yet known clearly (Strawn et al., 1995). Several mechanisms have been suggested that have the effects on growth of UL, including ovarian angiogenesis, steroid hormones, growth factors, and
The aim of this study was to investigate the magnetic resonance imaging (MRI) findings for the diagnose uremic encephalopathy and describe the usefulness of MRI findings in the ultimate diagnosis of uremic encephalopathy (UE). A total of 20 patients with uremic encephalopathy admitted to the hospital were evaluated in this prospective study. The clinical manifestations, laboratory and MRI imaging findings, demographic information, and clinical outcome were analyzed for each patient. We observed that the 20 prospectively reviewed patients with UE had no involvement of the basal ganglia or the lentiform fork sign (LFS). However, two-thirds of the patients had white matter involvement, and 80% of the subjects had cerebral or cortical atrophy. The arterial blood gas (ABG) analysis revealed that 50% of the patients suffered from metabolic acidosis (n=10). The results of the present study demonstrated that although the observation of Lentiform Fork Sign and Basal Ganglia involvement in MRI of UE patients is a specific finding the absence of which does not rule out UE. Thus, simultaneous examination of clinical manifestation and laboratory test analyses, along with imaging findings, should also be taken into account.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.