Colon Cancer

Impact of image reconstruction algorithms on histogram analysis of iodine concentration for assessing chemotherapy response in pancreatic ductal adenocarcinoma.

PURPOSE: To evaluate the impact of image reconstruction algorithms on histogram analysis of iodine concentration (IC) derived from dual-energy CT (DECT) to assess response to first-line chemotherapy in patients with pancreatic ductal adenocarcinoma (PDAC). METHODS: We retrospectively analyzed 41 patients with PDAC who underwent pancreatic protocol DECT during first-line chemotherapy between Januar...

Artificial intelligence-assisted proteomic signatures for discriminating malignant from benign pulmonary nodules.

Lung cancer remains a major global health burden. Although low-dose CT (LDCT) is effective for early detection, its clinical application is limited by a high false-positive rate and the need for subsequent invasive confirmation, such as biopsy. Meanwhile, the extensive protein-level alterations as observed in lung cancer provide a rationale for developing minimally invasive plasma proteomics-based...

Uncertainty-Aware Risk Stratification in Pediatric Low-Grade Glioma Using Multimodal Data.

BACKGROUND AND PURPOSE: Risk stratification in pediatric low-grade glioma (pLGG) remains challenging due to biological and clinical heterogeneity. We ...

Automated Body Composition from Computed Tomography Scans Improves Survival Prediction in Colorectal Cancer Patients.

Colorectal cancer is one of the most common cancers, but the current staging system is limited by the variability and paradoxical survival outcomes. B...

Histology-derived prediction of a stromal remodeling program in pancreatic ductal adenocarcinoma with transcriptomic and spatial validation.

OBJECTIVE: To develop and validate a histology-based model for predicting a stromal stiffness-related molecular surrogate in pancreatic ductal adenoca...

Haematological pre-staging of colorectal cancer: Longitudinal trends identify high-risk metastatic phenotypes 24 months prior to diagnosis.

BACKGROUND: The latent systemic phase of colorectal cancer (CRC) offers a critical but often missed window for early intervention. This study evaluate...

A machine learning-derived and functionally validated circadian rhythm signature predicts clinical outcomes and in silico drug sensitivity in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) displays considerable heterogeneity in clinical outcomes, highlighting the need for reliable prognostic biomarkers...

AI-Assisted Risk Stratification in Stage II Colorectal Cancer: Multi-Institutional Validation of Semantically-Enhanced Deep Learning.

BACKGROUND AND AIMS: Accurate risk stratification in stage II colorectal cancer is essential for treatment decision-making, as current guidelines reco...

Novel indicator for colonoscopy insertion difficulty and its application in predictive modelling: a multicentre prospective study protocol in China.

BACKGROUND: Colonoscopy is a cornerstone for the screening and diagnosis of colorectal diseases. Colonoscopy insertion difficulty is associated with e...

Identification of Methionine Metabolism-Driven Heterogeneous Subtypes in Colorectal Cancer and Their Associated Immune Microenvironment.

AIM: Tumor heterogeneity, driven by metabolic reprogramming, challenges colorectal cancer (CRC) treatment. Methionine metabolism is crucial for tumor ...

Single-cell and spatial transcriptomic landscapes reveal PIGT as a pivotal regulator of immunometabolic remodeling in colorectal cancer liver metastasis.

Colorectal cancer liver metastasis (CRLM) represents the leading cause of mortality in colorectal cancer (CRC). However, the molecular mechanisms enab...

Bisphenol A exposure in myasthenia gravis: Potential targets and mechanisms revealed by network toxicology and molecular dynamics.

BACKGROUND: Myasthenia gravis (MG) is a B-cell-mediated autoimmune disease characterized by impaired neuromuscular transmission. Although genetic pred...

Developing a Histology-Based Artificial Intelligence Biomarker to Predict Adjuvant Chemotherapy Benefit in Pancreatic Cancer.

PURPOSE: The choice of adjuvant chemotherapy in pancreatic ductal adenocarcinoma (PDAC) is mainly guided by patients' general condition. We hypothesiz...

Predicting which colorectal cancer patients are most likely to improve their functional capacity with pre-surgery prehabilitation: a retrospective study based on the 6-min walk distance.

PURPOSE: Prehabilitation prior to colorectal cancer (CRC) surgery aims to improve functional capacity and postoperative outcomes, although results rem...

Automation dependence in AI-assisted colonoscopy: impact of system reliability and surgeon experience on navigation performance.

BACKGROUND: As artificial intelligence (AI) is increasingly introduced into endoscopic navigation, understanding how operators use and respond to AI s...

Prediction of single cell expression from low-plex immunofluorescence images for guiding precision oncology.

Spatial omics allows for comprehensive investigation of the tumor immune microenvironment (TIME). Stratifying patients by their TIMEs contributes with...

Multi-component radiological model based on intratumoral CT threshold segmentation for predicting visceral pleural invasion in lung adenocarcinoma ≤ 30 mm.

OBJECTIVES: This retrospective study aims to investigate the value of intratumoral computed tomography (CT) threshold segmentation in radiomics, deep ...

Early prediction of anastomotic leakage within 24 h after minimally invasive colorectal cancer surgery using postoperative inflammatory markers: development and temporal validation of a machine learning model.

PURPOSE: Early identification of anastomotic leakage (AL) is critical for safe discharge within enhanced recovery pathways. This study developed and p...

CT-based Intratumoral Heterogeneity Score for Preoperative Prediction of Lymphovascular Invasion and Prognosis in Lung Adenocarcinoma: A Multicenter Validation and Radiogenomic Interpretation.

BACKGROUND: Lymphovascular invasion (LVI) is a key determinant of recurrence and survival in lung adenocarcinoma (LUAD), but preoperative identificati...

Preoperative PET/CT phenotype of gastric-type endocervical adenocarcinoma: integrated morphological, metabolic, serological, and explainable machine-learning analysis.

PURPOSE: Gastric-type endocervical adenocarcinoma (GAS) is an aggressive, non-HPV-associated cervical adenocarcinoma that is often difficult to recogn...