Radiomics Analysis of Intratumoral and Various Peritumoral Regions From Automated Breast Volume Scanning for Accurate Ki-67 Prediction in Breast Cancer Using Machine Learning.

Rationale And Objectives: Current radiomics research primarily focuses on intratumoral regions and fixed peritumoral areas, lacking optimization for accurate Ki-67 prediction. This study aimed to develop machine learning (ML) models to analyze radiomic features from Automated Breast Volume Scanning (ABVS) images of different peritumoral region sizes to identify the optimal size for accurate preoperative Ki-67 prediction.

Materials And Methods: A total of 668 breast cancer patients were enrolled and divided into training (486) and testing (182) cohorts.

Probing the Atomic Erosion Wear Characteristics of TiC-Coated Fe in Oil and Gas Drilling Environments.

The titanium carbide (TiC) coating is considered one of the key coating materials to resist erosion wear in oil and gas drilling environments due to its excellent impact and wear resistance. Based on molecular dynamics, the erosion wear resistance of TiC coatings and the pure Fe system in the simulation of nanoindentation, scratch, and particle impact was studied at the microscale. The results indicate that TiC coatings can effectively enhance the load-bearing capacity of the Fe substrate within the critical load range and exhibit low friction characteristics and erosion resistance.

Thyroid imaging reporting and data system with MRI morphological features for thyroid nodules: diagnostic performance and unnecessary biopsy rate.

Background: To assess MRI-based morphological features in improving the American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS) for categorizing thyroid nodules.

Methods: A retrospective analysis was performed on 728 thyroid nodules (453 benign and 275 malignant) that postoperative pathology confirmed. Univariate and multivariate logistic regression analyses were used to find independent predictors of MRI morphological features in benign and malignant thyroid nodules.

Prediction of Follicular Thyroid Neoplasm and Malignancy of Follicular Thyroid Neoplasm Using Multiparametric MRI.

The study aims to evaluate multiparametric magnetic resonance imaging (MRI) for differentiating Follicular thyroid neoplasm (FTN) from non-FTN and malignant FTN (MFTN) from benign FTN (BFTN). We retrospectively analyzed 702 postoperatively confirmed thyroid nodules, and divided them into training (n = 482) and validation (n = 220) cohorts. The 133 FTNs were further split into BFTN (n = 116) and MFTN (n = 17) groups.

Prediction model based on MRI morphological features for distinguishing benign and malignant thyroid nodules.

Background: The low specificity of Thyroid Imaging Reporting and Data System (TI-RADS) for preoperative benign-malignant diagnosis leads to a large number of unnecessary biopsies. This study developed and validated a predictive model based on MRI morphological features to improve the specificity.

Methods: A retrospective analysis was conducted on 825 thyroid nodules pathologically confirmed postoperatively.

Nomogram Utilizing ABVS Radiomics and Clinical Factors for Predicting ≤ 3 Positive Axillary Lymph Nodes in HR+ /HER2- Breast Cancer with 1-2 Positive Sentinel Nodes.

Background: In HR+ /HER2- breast cancer patients with ≤ 3 positive axillary lymph nodes (ALNs), genomic tests can streamline chemotherapy decisions. Current studies, centered on tumor metrics, miss broader patient insights. Automated Breast Volume Scanning (ABVS) provides advanced 3D imaging, and its potential synergy with radiomics for ALN evaluation is untapped.

Quantitative evaluation of diffusion-weighted MRI for differentiating benign and malignant thyroid nodules larger than 4 cm.

Purpose: Our study aimed to diagnose benign or malignant thyroid nodules larger than 4 cm using quantitative diffusion-weighted imaging (DWI) analysis.

Methods: Eighty-two thyroid nodules were investigated retrospectively and divided them into benign (n = 62) and malignant groups (n = 20). We calculated quantitative features DWI and apparent diffusion coefficient (ADC) signal intensity standard deviation (DWI and ADC), DWI and ADC signal intensity ratio (DWI and ADC), mean ADC and minimum ADC value (ADC and ADC) and ADC value standard deviation (ADC).

Preoperative Cervical Lymph Node Metastasis Prediction in Papillary Thyroid Carcinoma: A Noninvasive Clinical Multimodal Radiomics (CMR) Nomogram Analysis.

This study aimed to evaluate the feasibility of applying a clinical multimodal radiomics nomogram based on ultrasonography (US) and multiparametric magnetic resonance imaging (MRI) for the prediction of cervical lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) preoperatively. We performed retrospective evaluations of 133 patients with pathologically confirmed PTC, who were assigned to the training cohort and validation cohort (7 : 3), and extracted radiomics features from the preoperative US, T2-weighted (T2WI),diffusion-weighted (DWI), and contrast-enhanced T1-weighted (CE-T1WI) images. Optimal subsets were selected using minimum redundancy, maximum relevance, and recursive feature elimination in the support vector machine (SVM).

MRI-Based Texture Analysis for Preoperative Prediction of BRAF V600E Mutation in Papillary Thyroid Carcinoma.

Purpose: BRAF V600E mutation can compensate for the low detection rate by fine-needle aspiration (FNA) and is related to aggressiveness and lymph node metastasis. This study aimed to investigate the relationship between texture analysis features based on magnetic resonance imaging (MRI) and mutations.

Methods: Retrospective analysis was performed on patients with postoperative pathology confirmed papillary thyroid carcinoma (PTC) from 2017 to 2021.

Downregulation of PDGF-D Inhibits Proliferation and Invasion in Breast Cancer MDA-MB-231 Cells.

Background: The platelet derived growth factor-D (PDGF-D) plays an important role in breast tumor aggressiveness. However, limited study has investigated the effect of silencing PDGF-D on the biological function of breast cancer. The purpose of this study is to clarify the potential value of PDGF-D as a target for breast cancer treatment.

Evolving Fully Automated Machine Learning via Life-Long Knowledge Anchors.

Automated machine learning (AutoML) has achieved remarkable progress on various tasks, which is attributed to its minimal involvement of manual feature and model designs. However, most of existing AutoML pipelines only touch parts of the full machine learning pipeline, e.g.

microRNA-377 acts as a suppressor in esophageal squamous cell carcinoma through CBX3-dependent P53/P21 pathway.

Stem cells play pivotal roles in esophageal squamous cell carcinoma (ESCC) recurrence and metastasis. The self-renewal ability of stem cells was associated with specific microRNAs (miRs). Herein, we identified the effects of miR-377 on ESCC stem cell activities.

Hypoxic bone marrow mesenchymal cell-extracellular vesicles containing miR-328-3p promote lung cancer progression via the NF2-mediated Hippo axis.

Lung cancer is the most aggressive tumour afflicting patients on a global scale. Extracellular vesicle (EV)-delivered microRNAs (miRs) have been reported to play critical roles in cancer development. The current study aimed to investigate the role of hypoxic bone marrow mesenchymal cell (BMSC)-derived EVs containing miR-328-3p in lung cancer.

Effects of Blast Wave-induced Biomechanical Changes on Lung Injury in Rats.

Objective: To observe the dynamic impacts of shock waves on the severity of lung injury in rats with different injury distances.

Methods: Simulate open-field shock waves; detect the biomechanical effects of explosion sources at distances of 40, 44, and 48 cm from rats; and examine the changes in the gross anatomy of the lungs, lung wet/dry weight ratio, hemoglobin concentration, blood gas analysis, and pathology.

Results: Biomechanical parameters such as the overpressure peak and impulse were gradually attenuated with an increase in the injury distance.

Thoracic tumor resection combined with SVC replacement using autologous pericardium.

Background: Invasion of the superior vena cava (SVC) by thoracic tumors and occurrence of SVC syndrome are often encountered in clinical practice; but the prognosis in these cases is poor. Replacement of the SVC with autologous pericardial tissue is rarely performed. In this study, we sought to investigate the postoperative outcomes of this rare procedure.