http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Ye Rongping,Weng Shuping,Li Yueming,Yan Chuan,Chen Jianwei,Zhu Yuemin,Wen Liting 대한영상의학회 2021 Korean Journal of Radiology Vol.22 No.1
Objective: To explore the value of magnetic resonance imaging (MRI)-based whole tumor texture analysis in differentiating borderline epithelial ovarian tumors (BEOTs) from FIGO stage I/II malignant epithelial ovarian tumors (MEOTs). Materials and Methods: A total of 88 patients with histopathologically confirmed ovarian epithelial tumors after surgical resection, including 30 BEOT and 58 MEOT patients, were divided into a training group (n = 62) and a test group (n = 26). The clinical and conventional MRI features were retrospectively reviewed. The texture features of tumors, based on T2- weighted imaging, diffusion-weighted imaging, and contrast-enhanced T1-weighted imaging, were extracted using MaZda software and the three top weighted texture features were selected by using the Random Forest algorithm. A non-texture logistic regression model in the training group was built to include those clinical and conventional MRI variables with p value < 0.10. Subsequently, a combined model integrating non-texture information and texture features was built for the training group. The model, evaluated using patients in the training group, was then applied to patients in the test group. Finally, receiver operating characteristic (ROC) curves were used to assess the diagnostic performance of the models. Results: The combined model showed superior performance in categorizing BEOTs and MEOTs (sensitivity, 92.5%; specificity, 86.4%; accuracy, 90.3%; area under the ROC curve [AUC], 0.962) than the non-texture model (sensitivity, 78.3%; specificity, 84.6%; accuracy, 82.3%; AUC, 0.818). The AUCs were statistically different (p value = 0.038). In the test group, the AUCs, sensitivity, specificity, and accuracy were 0.840, 73.3%, 90.1%, and 80.8% when the non-texture model was used and 0.896, 75.0%, 94.0%, and 88.5% when the combined model was used. Conclusion: MRI-based texture features combined with clinical and conventional MRI features may assist in differentitating between BEOT and FIGO stage I/II MEOT patients.
( Jie Li ),( Biyao Zou ),( Hideki Fujii ),( Yee Hui Yeo ),( Fanpu Ji ),( Dong Hyun Lee ),( Yuemin Feng ),( Xiaoyu Xie ),( Wanhua Ren ),( Qiang Zhu ),( Mindie H. Nguyen ) 대한간학회 2018 춘·추계 학술대회 (KASL) Vol.2018 No.1
Aims: NAFLD is generally correlated with the obesity epidemic. Asia is a heterogeneous region with varying socioeconomic levels and obesity prevalence; therefore, our goal was to estimate the prevalence of NAFLD in Asia through a meta-analytic approach. Methods: PubMed and EMBASE databases were searched from 1989 to 2017 for relevant studies reporting NAFLD prevalence in Asia. All studies were reviewed by three independent investigators. We used random-effects models to provide point estimates with 95% confidence interval (CI) of prevalence. Publication bias was assessed by Egger weighted regression Methods. Results: From the 2700 titles and abstracts reviewed, 195 papers from 13 countries met the inclusion criteria and included 1,753,168 subjects. The overall pooled prevalence for NAFLD in Asia was 31% (95% CI: 29-32). Individual country prevalence was shown in Table 1. In countries with more than 3 studies, the lowest prevalence was seen in Japan (24%, 95% CI: 21-28) and the highest in Iran (36%, 95%CI 31-41). Notably, pooled prevalence from studies with sample <1,000 subjects was much higher (34%, 95% CI: 31-38, 45 studies, n=23,857) than estimate from larger studies (≥1,000 subjects) (30%, 95% CI: 28- 31, 150 studies, n=172,9311). By sub-regions within Asia (Table 2), there was significant regional differences (P<0.01) with the highest NAFLD prevalence seen in West Asia (33%, 95% CI: 28-39, 13 studies, n=32,142) and the lowest in Southeast Asia (24%, 95% CI: 15-33, 5 studies, n=3457). By country income levels, NAFLD prevalence was 30% (95% CI: 29-32, 89 studies, n=1,005,409) for high-income countries and 31% (95% CI: 29-33, 106 studies, n=747,759) for middle-income countries (P<0.63). Conclusions: Overall NAFLD prevalence in Asia is 31% similar to Western countries and by country-income levels within Asia but varies by some sub-regions or Asia with the highest prevalence in West Asia (33%).