Dual biomarkers CT-based deep learning model incorporating intrathoracic fat for discriminating benign and malignant pulmonary nodules in multi-center cohorts.

Background: Recent studies in the field of lung cancer have emphasized the important role of body composition, particularly fatty tissue, as a prognostic factor. However, there is still a lack of practice in combining fatty tissue to discriminate benign and malignant pulmonary nodules.

Purpose: This study proposes a deep learning (DL) approach to explore the potential predictive value of dual imaging markers, including intrathoracic fat (ITF), in patients with pulmonary nodules.

Preoperative glucose-to-lymphocyte ratio predicts survival in cancer.

Background: Systemic inflammation and glucose metabolism have been closely related to the survival of cancer patients. Therefore, we aimed to evaluate whether preoperative glucose-to-lymphocyte ratio (GLR) can be used to predict the survival of cancer patients.

Methods: We retrospectively examined 2172 cancer patients who underwent surgery from January 1, 2014, to December 31, 2016.

Red blood cell distribution width is associated with sarcopenia risk in early-stage non-small cell lung cancer.

Background: Sarcopenia has received increasing attention in non-small cell lung cancer (NSCLC). Red blood cell distribution width (RDW) is a significant component of the complete blood count and indicates the heterogeneity of erythrocyte volume. Little information is known about RDW in relation to sarcopenia in early-stage (IA-IIIA) NSCLC.

Subcutaneous fat predicts bone metastasis in breast cancer: A novel multimodality-based deep learning model.

Objectives: This study explores a deep learning (DL) approach to predicting bone metastases in breast cancer (BC) patients using clinical information, such as the fat index, and features like Computed Tomography (CT) images.

Methods: CT imaging data and clinical information were collected from 431 BC patients who underwent radical surgical resection at Harbin Medical University Cancer Hospital. The area of muscle and adipose tissue was obtained from CT images at the level of the eleventh thoracic vertebra.

Albumin-bilirubin score predicts trastuzumab resistance in HER2-positive breast cancer.

The albumin-bilirubin (ALBI) score is a novel indicator of liver function. Some studies showed that the ALBI score was a predictive marker for the prognosis and efficacy of drug therapy in malignancies. We aimed to assess the predicted role of ALBI score in the sensitivity to therapy with trastuzumab in patients with human epidermal growth factor receptor 2 (HER2) positive breast cancer (BC).

Preoperative small airway dysfunction is associated with skeletal muscle loss in early-stage non-small cell lung cancer.

Background: Postoperative skeletal muscle loss (SM loss) was reported to be associated with a poor prognosis in early-stage non-small cell lung cancer (NSCLC). Small airway dysfunction (SAD) is a common but neglected respiratory abnormality. Little information is known about the association between preoperative SAD and postoperative SM loss in early-stage NSCLC.

Pectoralis muscle predicts distant metastases in breast cancer by deep learning radiomics.

Background: Sarcopenia is associated with a poor prognosis in patients with breast cancer (BC). Currently, there are few quantitative assessments carried out between muscle biomarkers and distant metastasis using existing methods.

Purpose: To assess the predictive value of the pectoralis muscle for BC distant metastasis, we developed a deep learning radiomics nomogram model (DLR-N) in this study.

Deep learning radiomics under multimodality explore association between muscle/fat and metastasis and survival in breast cancer patients.

Sarcopenia is correlated with poor clinical outcomes in breast cancer (BC) patients. However, there is no precise quantitative study on the correlation between body composition changes and BC metastasis and survival. The present study proposed a deep learning radiomics (DLR) approach to investigate the effects of muscle and fat on distant metastasis and death outcomes in BC patients.

Preoperative Pectoralis Muscle Index Predicts Distant Metastasis-Free Survival in Breast Cancer Patients.

Background: Breast cancer is one of the most commonly diagnosed cancers, and the fourth leading cause of cancer deaths in females worldwide. Sarcopenia is related to adverse clinical outcomes in patients with malignancies. Muscle index is a key parameter in evaluating sarcopenia.

System dynamics research of remanufacturing closed-loop supply chain dominated by the third party.

With the rapid development of the electronic information industry in recent years, electronic products are being updated faster and faster, and e-waste recycling has become a common problem around the world. Firstly, this article contrasts recycling at home and abroad using the predicament of Midea Corp. Based on a closed-loop supply chain with the system dynamics method, a model is constructed and simulated.