Developing a Machine Learning-Based Clinical Decision Support Tool for Uterine Tumor Imaging

Uterine leiomyosarcoma (LMS) is a rare but aggressive malignancy. On imaging, it is difficult to differentiate LMS from, for example, degenerated leiomyoma (LM), a prevalent but benign condition. We curated a data set of 115 axial T2-weighted MRI images from 110 patients (mean [range] age=45 [17-81] years) with UTs that included five different tumor types. These data were randomly split stratifying on tumor volume into training (n=85) and test sets (n=30). An independent second reader (reader 2) provided manual segmentations for all test set images. To automate segmentation, we applied nnU-Net and explored the effect of training set size on performance by randomly generating subsets with 25, 45, 65 and 85 training set images. We evaluated the ability of radiomic features to distinguish between types of UT individually and when combined through feature selection and machine learning. Using the entire training set the mean [95% CI] fibroid DSC was measured as 0.87 [0.59-1.00] and the agreement between the two readers was 0.89 [0.77-1.0] on the test set. When classifying degenerated LM from LMS we achieve a test set F1-score of 0.80. Classifying UTs based on radiomic features we identify classifiers achieving F1-scores of 0.53 [0.45, 0.61] and 0.80 [0.80, 0.80] on the test set for the benign versus malignant, and degenerated LM versus LMS tasks. We show that it is possible to develop an automated method for 3D segmentation of the uterus and UT that is close to human-level performance with fewer than 150 annotated images. For distinguishing UT types, while we train models that merit further investigation with additional data, reliable automatic differentiation of UTs remains a challenge

Insatisfação corporal em gestantes: uma revisão integrativa da literatura

Resumo A imagem corporal de gestantes deve ser alvo de atenção por parte dos profissionais, tendo em vista a promoção da saúde materna infantil. O objetivo da presente revisão integrativa foi analisar a literatura sobre imagem e insatisfação corporal em gestantes. Foram buscados artigos nas bases de dados Scopus, PubMed, BVS e PsycINFO utilizando o cruzamento de “pregnancy” com as palavras-chave: “body image” e “body dissatisfaction”. Após a adoção dos critérios de inclusão e exclusão foram analisados 40 estudos. Estes apontam dados inconclusivos quanto à insatisfação corporal durante a gestação. Presença de sintomas depressivos, baixa autoestima, atitude alimentar inadequada e ganho de peso fora dos limites recomendados têm sido associados a uma imagem corporal negativa. Contradições nos achados podem estar relacionados às diferenças nos instrumentos utilizados para mensurar a imagem corporal. Pelo possível impacto de uma imagem corporal negativa durante a gestação na saúde materna e infantil, são recomendadas novas investigações, em especial o desenvolvimento de um instrumento avaliativo de imagem corporal específico para gestantes

Morbidity Pattern among Under-five Children of Market Women in Ibadan

Background: The study was carried out in two large markets in Ibadan, namely: Bodija, a predominantly food market with poor environmental sanitation, and Gbagi, a textile market with a cleaner environment. Objectives: To compare the morbidity patterns among under-five children of traders in both markets. Design: A cross sectional study design was utilized. Patients and Participants: Mothers with under-five children in the two markets. Method: A structured questionnaire was administered to mothers of under-five children in both markets to obtain information about immunization and childhood illnesses among their children. A physical examination was also carried out on each index child. Results: A total of 232 and 219 children were seen in Bodija and Gbagi markets, respectively. Mothers in Gbagi had higher educational attainment than those in Bodija. Mothers' reports of fever, cough and diarrhoea affecting their children indicated a similarity in the prevalence of these symptoms among children in both markets. However, physical examination revealed that the children in Bodija had more signs of morbidity compared to those in Gbagi. The prevalences of anaemia, malaria parasitaemia and ascariasis were 28 percent, 20 percent and eight percent in Bodija, while the corresponding figures for Gbagi were eight percent, 17 percent and two percent (

Hematologic and Vitamin Status of African American Women and Their Relationships to Pregnancy Outcome

A prospective observational study was conducted to investigate the effects of nutrition and related factors on the outcome of pregnancy in nulliparous African American women 16-35 years of age. Blood samples from a subset of these subjects were taken during the first (1st), second (2nd) and third (3rd) trimesters of pregnancy and at delivery. Cord blood samples were also collected at delivery. Levels of selected biochemical variables including serum ferritin, vitamin B12 and folate as well as whole blood folate, and selected hematologic indices were determined and correlated with pregnancy outcome variables. During the second trimester of pregnancy, values for hematocrit and hemoglobin were less than 30% and 11 g/dL, respectively, in 16% and 30% of the participants, respectively. Serum and whole blood (WB) folate increased sequentially during pregnancy. Cord concentrations of serum folate were significantly higher than maternal concentrations at delivery (P\u3c0.05). Serum ferritin declined significantly from 36±5.6 ng/ml in the first trimester to 17±1.5 ng/ml during the 3rd trimester (P\u3c0.05), and returned to the 2nd trimester level (26±2.0 ng/ml) at delivery. Second trimester WB folate was positively related to birth weight (R2=0.21), while gestational age was inversely correlated with 3rd trimester vitamin B12 (R2=0.34). These data suggest that vitamin B12 and folate play an important role in the outcome of pregnancy in this population