Age-related differences in progression patterns, follow-up strategies, and postoperative outcomes in locally advanced rectal cancer: insights from a large-scale validated study.

Background: Locally advanced rectal cancer (LARC) presents significant treatment challenges, particularly as patient age may influence disease progression and treatment response. Understanding the differences in progression patterns and treatment outcomes between older patient (OP) and non-older patient (NOP) is essential for tailoring effective management strategies.

Objectives: We aimed to explore the differences of progression pattern, postoperative treatment, and survival outcome between OP and NOP groups in LARC.

Comprehensive analysis of the prognostic value of pre-treatment nutritional indicators in elderly rectal cancer patients.

Nutritional status assessment has been deemed essential in treating elderly cancer patients. This study aims to investigate and compare the prognostic value and clinical utility of pre-treatment nutritional indicators in elderly rectal cancer (RC) patients. We retrospectively collected data from 361 elderly rectal cancer patients.

Analysis of risk characteristics for early progression and late progression in locally advanced rectal cancer patients: a large population-based and validated study.

Background And Objective: The current study aimed to explore the factors influencing early progression (EP) and late progression (LP) in locally advanced rectal cancer (LARC) patients.

Methods: The patients were classified into EP and LP groups using one year as a cutoff. The random survival forest model was utilized to calculate the probability of time-to-progression.

Prognostic and immunological implications of glutathione metabolism genes in lung adenocarcinoma: A focus on the core gene SMS and its impact on M2 macrophage polarization.

Glutathione metabolism (GM) is a crucial part of various metabolic and pathophysiological processes. However, its role in lung adenocarcinoma (LUAD) has not been comprehensively studied. This study aimed to explore the potential relationship between GM genes, the prognosis, and the immune microenvironment of patients with LUAD.

Prediction of liver metastasis and recommended optimal follow-up nursing in rectal cancer.

We aimed to analyze and investigate the clinical factors that influence the occurrence of liver metastasis in locally advanced rectal cancer patients, with an attempt to assist patients in devising the optimal imaging-based follow-up nursing. Between June 2011 and May 2021, patients with rectal cancer at our hospital were retrospectively analyzed. A random survival forest model was developed to predict the probability of liver metastasis and provide a practical risk-based approach to surveillance.

Superficial vessel-based near infrared-assisted patient position recognition and real-time monitoring system (VIPS) for radiotherapy: A proof-of-concept study.

Background: The accuracy and precision of patient position in radiotherapy process have dramatic impacts on the tumor local control and therapy-related side effects, and there exist demands to explore effective positioning solutions, particularly in the era with great progress in imaging recognition and matching.

Purpose: Superficial vessel-based near infrared-assisted patient position recognition and real-time monitoring system (VIPS) was proposed to develop an automated, operator-independent and skin marker-free imaging system to improve patient setup and intrafractional motion monitoring.

Methods: VIPS includes two components, the imaging module and the image alignment software.

Prognostic and immunological role of cancer-associated fibroblasts-derived exosomal protein in esophageal squamous cell carcinoma.

Background: Cancer-associated fibroblasts (CAFs) are a crucial component of the tumor microenvironment (TME) and play significant roles in tumor initiation, progression, and immune evasion. Despite this, the specific exosomal proteins derived from CAFs and their functions in esophageal squamous cell carcinoma (ESCC) remain unknown. Therefore, this study aims to investigate the impact and prognostic significance of CAFs-derived exosomal proteins in ESCC.

Accuracy Evaluation Trial of Mixed Reality-Guided Spinal Puncture Technology.

Purpose: To evaluate the accuracy of mixed reality (MR)-guided visualization technology for spinal puncture (MRsp).

Methods: MRsp involved the following three steps: 1. Lumbar spine computed tomography (CT) data were obtained to reconstruct virtual 3D images, which were imported into a HoloLens (2nd gen).

The development and validation of a nomogram for predicting brain metastases after chemotherapy and radiotherapy in male small cell lung cancer patients with stage III.

Objective: The purpose of this research was to develop a model for brain metastasis (BM) in limited-stage small cell lung cancer (LS-SCLC) patients and to help in the early identification of high-risk patients and the selection of individualized therapies.

Methods: Univariate and multivariate logic regression was applied to identify the independent risk factors of BM. A receiver operating curve (ROC) and nomogram for predicting the incidence of BM were then conducted based on the independent risk factors.

Prognostic value of pre-therapeutic nutritional risk factors in elderly patients with locally advanced esophageal squamous cell carcinoma receiving definitive chemoradiotherapy or radiotherapy.

Background: The nutritional status of cancer patients is a crucial factor in determining their prognosis. The objective of this study was to investigate and compare the prognostic value of pretreatment nutrition-related indicators in elderly esophageal squamous cell carcinoma (ESCC). Risk stratification was performed according to independent risk factors and a new nutritional prognostic index was constructed.

Systemic Immune-Inflammatory Index, Tumor-Infiltrating Lymphocytes, and Clinical Outcomes in Esophageal Squamous Cell Carcinoma Receiving Concurrent Chemoradiotherapy.

Background: Systemic inflammation may be involved in the entire cancer process as a promoter and is associated with antitumor immunity. The systemic immune-inflammation index (SII) has been shown to be a promising prognostic factor. However, the relationship between SII and tumor-infiltrating lymphocytes (TIL) have not been established in esophageal cancer (EC) patients receiving concurrent chemoradiotherapy (CCRT).

Higher radiation dose on immune cells is associated with radiation-induced lymphopenia and worse prognosis in patients with locally advanced esophageal squamous cell carcinoma.

Background: To explore the effective dose to immune cells (EDIC) for better prognosis while avoiding radiation-induced lymphopenia (RIL) in patients with locally advanced esophageal squamous cell carcinoma (ESCC).

Materials And Methods: Overall, 381 patients with locally advanced ESCC receiving definitive radiotherapy with or without chemotherapy (dRT ± CT) between 2014 and 2020 were included in this study. The EDIC model was calculated by radiation fraction number and mean doses to the heart, lung, and integral body.

Clinical outcomes and toxicities of locally advanced esophageal squamous cell carcinoma patients treated with early thoracic radiation therapy after induction chemotherapy.

Objective: The purpose of this study was to compare the clinical outcomes and toxicities between induction chemotherapy (IC) + chemo-radiotherapy (CRT) and CRT alone in patients with locally advanced esophageal squamous cell carcinoma (ESCC), to explore the appropriate thoracic radiotherapy (TRT) timing after IC and to identify prognostic factors.

Methods: 450 ESCC patients were included from September 2011 to December 2020, 238 of whom received IC/CRT. Propensity score matching was performed to balance potential confounders between the two groups.

Using inflammatory indexes and clinical parameters to predict radiation esophagitis in patients with small-cell lung cancer undergoing chemoradiotherapy.

Objective: Radiation esophagitis (RE) is a common adverse effect in small cell lung cancer (SCLC) patients undergoing thoracic radiotherapy. We aim to develop a novel nomogram to predict the acute severe RE (grade≥2) receiving chemoradiation in SCLC patients.

Materials And Methods: the risk factors were analyzed by logistic regression, and a nomogram was constructed based on multivariate analysis results.

A Nutrition-Related Factor-Based Risk Stratification for Exploring the Clinical Benefits in the Treatment of Patients With Locally Advanced Esophageal Squamous Cell Carcinoma Receiving Definitive Chemoradiotherapy: A Retrospective Cohort Study.

Objective: No study has reported the risk stratification of BMI and PNI in patients with locally advanced esophageal squamous cell carcinoma (ESCC) undergoing definitive chemoradiotherapy (dCRT). This study aimed to construct a risk stratification to guide the treatment of ESCC following dCRT.

Methods: A total of 1,068 patients with locally advanced ESCC who received dCRT were retrospectively analyzed.

A New Nomogram and Risk Stratification of Brain Metastasis by Clinical and Inflammatory Parameters in Stage III Small Cell Lung Cancer Without Prophylactic Cranial Irradiation.

Background: This study was conducted to determine risk factors for developing brain metastasis (BM) and to predict brain metastasis free survival (BMFS) and overall survival (OS) by combining several clinical parameters and inflammatory indexes.

Materials And Methods: A nomogram and risk stratification were developed based on multivariate analysis results. The prognostic index (PI) predicting the high risk of BM was calculated by multiplying the weighted factor (β coefficient) with each variable.

A Novel Model Combining Tumor Length, Tumor Thickness, TNM_Stage, Nutritional Index, and Inflammatory Index Might Be Superior to the 8th TNM Staging Criteria in Predicting the Prognosis of Esophageal Squamous Cell Carcinoma Patients Treated With Definitive Chemoradiotherapy.

Background: We aimed to determine whether the tumor length and tumor thickness should be used as prognostic factors for esophageal squamous cell carcinoma (ESCC) patients treated with definitive chemoradiotherapy (dCRT).

Methods: A retrospective analysis consists of 902 non-operative ESCC patients received dCRT. The nomogram was used to predict the survival.

The novel pretreatment immune prognostic index discriminates survival outcomes in locally advanced non-operative esophageal squamous cell carcinoma patients treated with definitive chemoradiotherapy: a 6-year retrospective study.

Objective: We aimed to construct risk stratification to help set individualized treatment strategies and intensities for different subgroups of patients.

Methods: The Esophagus Immune Prognostic Index (EIPI) scores were constructed according to the levels of derived neutrophil-to-lymphocyte ratio (dNLR) and lactate dehydrogenase (LDH) before treatment, and the patients were divided into low-, medium-, and high-risk groups. Finally, restricted cubic splines (RCS) were used to explore the relationship between dNLR, LDH, and survival outcomes.

Dosimetric Study of Deep Learning-Guided ITV Prediction in Cone-beam CT for Lung Stereotactic Body Radiotherapy.

Purpose: The purpose of this study was to evaluate the accuracy of a lung stereotactic body radiotherapy (SBRT) treatment plan with the target of a newly predicted internal target volume (ITV) and the feasibility of its clinical application. ITV was automatically generated by our in-house deep learning model according to the cone-beam CT (CBCT) image database.

Method: A retrospective study of 45 patients who underwent SBRT was involved, and Mask R-CNN based algorithm model helped to predict the internal target volume (ITV) using the CBCT image database.

Deep Learning-Based Internal Target Volume (ITV) Prediction Using Cone-Beam CT Images in Lung Stereotactic Body Radiotherapy.

This study aims to develop a deep learning (DL)-based (Mask R-CNN) method to predict the internal target volume (ITV) in cone beam computed tomography (CBCT) images for lung stereotactic body radiotherapy (SBRT) patients and to evaluate the prediction accuracy of the model using 4DCT as ground truth. This study enrolled 78 phantom cases and 156 patient cases who received SBRT treatment. We used a novel DL model (Mask R-CNN) to identify and delineate lung tumor ITV in CBCT images.

Nucleosides and amino acids, isolated from protected against cyclophosphamide-induced myelosuppression in mice.

The material basis of (Berk.) Sacc has not yet been well understood and natural resources are very rare. The present study aimed to clarify the substance basis and compare the protective effect of natural and artificially-cultivated against cyclophosphamide (CTX)-induced myelosuppression.