[Establishment of 14-Color Panel for Determining Leukocyte Subsets in Human Peripheral Blood with Flow Cytometry].

Objective: To establish a 14-color flow cytometry protocol for the examination of leukocyte subsets in human peripheral blood.

Methods: We used cell membrane surface antibodies CD45, CD3, CD4, CD8, CD19, CD56, CD16, CD14, CD25, CD127, HLA-DR, CD123, CD11c and nucleus staining dye DAPI to establish a 14-color flow cytometry assay to determine the major cell subsets in human peripheral blood. We collected peripheral blood specimens from healthy volunteers to test for antibody titers and optimal photomultiplier tube (PMT) voltage, and to conduct single-color staining and fluorescence minus one control staining.

[Prediction of Response to Neoadjuvant Chemotherapy for Breast Cancer Based on Histomorphology Analysis of Needle Biopsy Images].

Objective: The deep learning method was used to automatically segment the tumor area and the cell nucleus based on needle biopsy images of breast cancer patients prior to receiving neoadjuvant chemotherapy (NAC), and then, the features of the cell clusters in the tumor area were identified to predict the level of pathological remission of breast cancer after NAC.

Methods: 68 breast cancer patients who were to receive NAC at Jiangsu Province Hospital were recruited and the hematoxylin-eosin (HE) stained preoperative biopsy sections of these patients were collected. Unet++ was used to establish a segmentation model and the tumor area and nucleus of the needle biopsy images were automatically segmented accordingly.

Added value of histogram analysis of apparent diffusion coefficient maps for differentiating triple-negative breast cancer from other subtypes of breast cancer on standard MRI.

Background: Triple-negative breast cancers generally occur in young women with remarkable potential to be aggressive. It will be of great help to detect this subtype of tumor early. To retrospectively evaluate the performance of histogram analysis of apparent diffusion coefficient (ADC) maps in distinguishing triple-negative breast cancer (TNBC) from other subtypes of breast cancer (non-TNBC), when combined with magnetic resonance imaging (MRI) features.

Preoperative predicting malignancy in breast mass-like lesions: value of adding histogram analysis of apparent diffusion coefficient maps to dynamic contrast-enhanced magnetic resonance imaging for improving confidence level.

Objective: This study aims to find out the benefits of adding histogram analysis of apparent diffusion coefficient (ADC) maps onto dynamic contrast-enhanced MRI (DCE-MRI) in predicting breast malignancy.

Methods: This study included 95 patients who were found with breast mass-like lesions from January 2014 to March 2016 (47 benign and 48 malignant). These patients were estimated by both DCE-MRI and diffusion-weighted imaging (DWI) and classified into two groups, namely, the benign and the malignant.

Assessing sequence and relationship of regional maturation in corpus callosum and internal capsule in preterm and term newborns by diffusion-tensor imaging.

Background: Diffusion-tensor imaging (DTI) can be used to investigate water diffusion in living tissue.

Objective: To investigate sequence and relationship of regional maturation in corpus callosum (CC) and internal capsule (IC) in preterm and term.

Methods: DTI was performed on 11 preterm infants at less than 37 weeks of corrected gestational age (group I), 21 preterm infants at equivalent-term (group II), 11 term infants during neonatal period (group III).