Attention-guided context asymmetric fusion networks for the liver tumor segmentation of computed tomography images.

Background: Liver tumor segmentation based on medical imaging is playing an increasingly important role in liver tumor research and individualized therapeutic decision-making. However, it remains a challenging in terms of the accuracy of automatic segmentation of liver tumors. Therefore, we aimed to develop a novel deep neural network for improving the results from the automatic segmentation of liver tumors.

Nomogram based on clinical and preoperative CT features for predicting the early recurrence of combined hepatocellular-cholangiocarcinoma: a multicenter study.

Purpose: To establish and validate a multiparameter prediction model for early recurrence after radical resection in patients diagnosed with combined hepatocellular-cholangiocarcinoma (cHCC-CC).

Materials And Methods: This study reviewed the clinical characteristics and preoperative CT images of 143 cHCC-CC patients who underwent radical resection from three institutions. A total of 110 patients from institution 1 were randomly divided into training set (n = 78) and testing set (n = 32) in the ratio of 7-3.

Peritumoral edema in preoperative magnetic resonance imaging is an independent prognostic factor for hepatocellular carcinoma.

Background: Peritumoral edema is an independent prognostic risk factor for malignant tumors. Therefore, assessment of peritumoral edema in preoperative magnetic resonance imaging (MRI) may provide better prognostic information in patients with hepatocellular carcinoma (HCC).

Aim: To determine whether peritumoral edema in preoperative MRI is a prognostic factor for HCC.

GSTT1 and GSTM1 polymorphisms predict treatment outcome for breast cancer: a systematic review and meta-analysis.

Observational studies have reported controversial results on the association between GSTT1 and GSTM1 genotypes and treatment outcome of breast cancer. The purpose of this study is to evaluate the association between GSTT1 and GSTM1 and treatment outcome in breast cancer patients. Eligible studies were searched in PubMed, EMBASE, Cochrane Library, and China National Knowledge Infrastructure databases.

Diagnostic performance of ADCs in different ROIs for breast lesions.

Objective: The purpose of this study was to explore the diagnostic performance of apparent diffusion coefficient (ADC) values for breast lesions by different measuring methods and find out the optimum measuring method.

Methods: ADCW-mean and ADCW-min were obtained by whole-measurement method, while ADCmean and ADCmin were extracted by spot-measurement method. Four ADCs were analyzed by One-way ANOVA and Independent T-test.

Meta-analysis of diffusion-weighted magnetic resonance imaging in detecting prostate cancer.

Purpose: The objective of this study was to determine the diagnostic performance of quantitative diffusion-weighted magnetic resonance imaging in detection of prostate cancer.

Methods: A comprehensive search was performed for English articles published before May 2012 that fulfilled the following criteria: patients had histopathologically proved prostate cancer; diffusion-weighted imaging (DWI) was performed for the detection of prostate cancer, and data for calculating sensitivity and specificity were included. Methodological quality was assessed by using the quality assessment of diagnostic studies instrument.