Improving Early Identification of Significant Weight Loss Using Clinical Decision Support System in Lung Cancer Radiation Therapy.

Purpose: Early identification of patients who may be at high risk of significant weight loss (SWL) is important for timely clinical intervention in lung cancer radiotherapy (RT). A clinical decision support system (CDSS) for SWL prediction was implemented within the routine clinical workflow and assessed on a prospective cohort of patients.

Materials And Methods: CDSS incorporated a machine learning prediction model on the basis of radiomics and dosiomics image features and was connected to a web-based dashboard for streamlined patient enrollment, feature extraction, SWL prediction, and physicians' evaluation processes.

Multi-view radiomics and dosiomics analysis with machine learning for predicting acute-phase weight loss in lung cancer patients treated with radiotherapy.

We propose a multi-view data analysis approach using radiomics and dosiomics (R&D) texture features for predicting acute-phase weight loss (WL) in lung cancer radiotherapy. Baseline weight of 388 patients who underwent intensity modulated radiation therapy (IMRT) was measured between one month prior to and one week after the start of IMRT. Weight change between one week and two months after the commencement of IMRT was analyzed, and dichotomized at 5% WL.

The Needs and Benefits of Continuous Model Updates on the Accuracy of RT-Induced Toxicity Prediction Models Within a Learning Health System.

Purpose: Clinical data collection and development of outcome prediction models by machine learning can form the foundation for a learning health system offering precision radiation therapy. However, changes in clinical practice over time can affect the measures and patient outcomes and, hence, the collected data. We hypothesize that regular prediction model updates and continuous prospective data collection are important to prevent the degradation of a model's predication accuracy.

Evaluation of classification and regression tree (CART) model in weight loss prediction following head and neck cancer radiation therapy.

Objective: We explore whether a knowledge-discovery approach building a Classification and Regression Tree (CART) prediction model for weight loss (WL) in head and neck cancer (HNC) patients treated with radiation therapy (RT) is feasible.

Methods And Materials: HNC patients from 2007 to 2015 were identified from a prospectively collected database Oncospace. Two prediction models at different time points were developed to predict weight loss ≥5 kg at 3 months post-RT by CART algorithm: (1) during RT planning using patient demographic, delineated dose data, planning target volume-organs at risk shape relationships data and (2) at the end of treatment (EOT) using additional on-treatment toxicities and quality of life data.

Preventive effects of a fermented dairy product against Alzheimer's disease and identification of a novel oleamide with enhanced microglial phagocytosis and anti-inflammatory activity.

Despite the ever-increasing number of patients with dementia worldwide, fundamental therapeutic approaches to this condition have not been established. Epidemiological studies suggest that intake of fermented dairy products prevents cognitive decline in the elderly. However, the active compounds responsible for the effect remain to be elucidated.

Histological types and localizations of lung cancers in patients with combined pulmonary fibrosis and emphysema.

Background: Most patients with combined pulmonary fibrosis and emphysema (CPFE) are males, and heavy smokers. CPFE is more prevalent than fibrosis in patients with lung cancer, and patients with CPFE usually have a poor prognosis. This study reviewed the differences in the prevalence of lung cancer among patients with normal, fibrosis, emphysema and CPFE via chest computed tomography (CT), and the relationship between histopathology and the localizations of lung cancer.

The utility of galactomannan antigen in the bronchial washing and serum for diagnosing pulmonary aspergillosis.

Background: The diagnosis of pulmonary aspergillosis is difficult because the sensitivity of the conventional methods for the detection of Aspergillus such as culture and cytology, is poor. To improve the sensitivity for Aspergillus detection, the detection of galactomannan antigen has been investigated. The serum galactomannan (GM) antigen has been recognized to be a useful tool for the diagnosis of invasive pulmonary aspergillosis.

The relationship between the clinical course and cytokine in a patient with cigarette smoking-induced acute eosinophilic pneumonia - A case report.

A 19-year-old female was admitted to our hospital because of a sudden onset fever and cough, and she was diagnosed to have acute eosinophilic pneumonia (AEP). The cause was thought to be cigarette smoking, because she had started smoking just before the development of AEP and her condition improved after cigarette smoking cessation, without corticosteroid treatment. The cytokines which are thought to be involved in eosinophilic accumulation in the lungs were analyzed using bronchoalveolar lavage fluid (BALF) and serum.

Effects of inhaled tiotropium plus transdermal tulobuterol versus tiotropium alone on impulse oscillation system (IOS)-assessed measures of peripheral airway resistance and reactance, lung function and quality of life in patients with COPD: a randomized crossover study.

Background: The addition of transdermal tulobuterol (Tulo) to inhaled tiotropium bromide (Tio) produced beneficial effects on spirometry-assessed parameters of respiratory function, disease-related symptoms and quality of life in patients with chronic obstructive pulmonary disease (COPD).

Aim: To compare the effects of Tio plus Tulo versus Tio alone on peripheral airway obstruction and quality of life in Japanese patients with COPD using impulse oscillation system (IOS)-assessed measures.

Patients And Methods: Patients aged 50-80 years with clinically stable COPD and a forced expiratory volume in 1 s (FEV(1)) that was 30-80% of the predicted value were randomized to receive Tio 18 μg once daily, or combination therapy with Tio 18 μg once daily plus Tulo 2 mg once daily for 4 weeks.