Other Cancers

Advancing CNS tumor diagnostics with expanded DNA methylation-based classification.

DNA methylation-based classification is now central to contemporary neuro-oncology, as highlighted by the World Health Organization (WHO) classification of central nervous system (CNS) tumors. We present the Heidelberg CNS Tumor Methylation Classifier version 12.8 (v12.8), trained on 7,495 methylation profiles, which expands recognized entities from 91 classes in version 11 (v11) to 184 subclasses...

Machine learning models for predicting response to epidermal growth factor receptor tyrosine kinase inhibitors in non-small cell lung cancer brain metastases: a systematic review and meta-analysis.

BACKGROUND: Predicting clinical and radiological outcomes of epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) in patients with non-small cell lung cancer (NSCLC) and brain metastases (BMs) is crucial for effective patient management. Machine learning (ML)-based models have increasingly been utilized to predict EGFR-TKI response in patients with lung cancer brain metastasis (...

Raman imaging uncovers Ebracteolatain A's subtype-selective metabolic reprogramming in luminal versus triple-negative breast cancer cells.

Ebracteolatain A (EA), a potential anti-cancer agent, has demonstrated efficacy against breast cancer through protein kinase D1 inhibition. However, i...

Cross-modality fusion of hematology-based digital and molecular biomarkers for intelligent epidemiological screening and surveillance of hepatocellular carcinoma.

Early detection of hepatocellular carcinoma (HCC) remains a critical challenge due to the disease's complexity and the limitations of current screenin...

Artificial intelligence diagnostics for bladder tumor identification and grade prediction depend on narrow band imaging cystoscopy.

The effective treatment of bladder cancer depends on early evaluation through cystoscopy. Given the clinical importance of distinguishing the tumor gr...

Multi-omic biomarker detection in ovarian cancer.

Ovarian cancer remains one of the most lethal gynecologic malignancies, largely because of late-stage diagnosis and the absence of reliable biomarkers...

From macroscopic clearance to molecular eradication: paradigm shift and future perspectives in the detecting of residual lesions after transurethral resection of bladder tumors.

INTRODUCTION: Residual lesions after transurethral resection of bladder tumor (TURBT) are a major contributor to recurrence in bladder cancer. Advance...

Biological multi-omics approaches to next-generation biomarkers in immune-related disorders and malignancies: An overview.

Cancer and autoimmune diseases are major global health challenges characterized by molecular and clinical heterogeneity. Traditional single-analyte bi...

Automated Segmentation of Liver and Liver Tumors with SwinUNETR and UNET Neural Networks on 18F-FDG PET/CT.

OBJECTIVES: To develop and evaluate automated segmentation models for the liver and hepatic tumors on 18F-fluorodeoxyglucose positron emission tomogra...

Integrating lesser omentum adipose CT in dual-phase tumor imaging: A multi-label deep learning framework for preoperative microvascular invasion prediction and survival analysis in hepatocellular carcinoma.

BACKGROUND AND OBJECTIVE: Accurate preoperative prediction of microvascular invasion (MVI) and survival risk is essential for personalized treatment i...

Using machine learning to predict clinical remission with exclusive enteral nutrition in pediatric Crohn disease.

OBJECTIVES: Exclusive enteral nutrition (EEN) is a first-line treatment for induction of remission in luminal pediatric Crohn disease (pCD). However, ...

Anomaly changes in the functional connectome of post-operative neurosurgical patients: A case series.

PURPOSE: The use of neuronavigation with superimposed mapping tools has enabled visualization of key fiber tracts and improved peri-operative planning...

Prediction of Lung Metastasis in Breast Cancer Patients Using Machine Learning Classifiers.

Breast cancer is the most common cancer among women, and metastasis to the lung is associated with poor prognosis. Reliable biomarkers for predicting ...

Digital pathology-based prognostic model for hepatocellular carcinoma: Integrating pathomics signatures with clinical parameters for recurrence prediction and biological interpretation.

BACKGROUND: Hepatocellular carcinoma (HCC) remains a therapeutic challenge due to high post-resection recurrence rates and heterogeneous outcomes. We ...

Turmeric extracellular vesicles-derived "all-in-one" nanoagent enables full-cycle synergistic immunomodulation of lung cancer.

Lung cancer's metastatic propensity and recurrence prevalence necessitate innovative immunotherapy strategies beyond conventional single-mode regulati...

Diagnosis of head and neck cancer by AI-based tumor-educated platelet RNA profiling of liquid biopsies.

Over 95% of head and neck cancers are squamous cell carcinoma (HNSCC). HNSCC is mostly diagnosed late, causing a poor prognosis despite the applicatio...

Clinical Efficacy of Real-Time Artificial Intelligence-Assisted Colonoscopy in Colorectal Polyp Detection: A Prospective Multicenter Randomized Controlled Trial.

BACKGROUND/AIMS: Early detection and removal of colon polyps are critical for preventing colorectal cancer. Computer-aided detection (CADe) systems ha...

Feasibility of transperineal prostate biopsy guided by fusion of [18F]F-PSMA-1007 PET/MRI with real-time transrectal ultrasound. Prostate cancer classification using imaging biomarkers and radiomics in PIRADS 3 lesions.

OBJECTIVE: To assess the diagnostic feasibility of transperineal biopsy guided by fusion of PET/MRI with [18F]F-PSMA-1007 and real-time transrectal ul...

Trajectories of affective disorders-the central structures of CRC/TRR 393.

The recurrent and often unpredictable course of affective disorders poses a critical challenge for long-term patient care. The CRC/TRR 393 consortium ...

Deep Learning Model for Differentiating Between Neoplastic Pathologic Fracture and Nonpathologic Fracture Using Hip Radiographs.

BACKGROUND: Although radiographs are the first-line imaging modality, differentiating between neoplastic pathologic fractures and nonpathologic fractu...