Oncology/Hematology

CT Radiomic Features Are Associated with DNA Copy Number Alterations of Head and Neck Squamous Cell Carcinomas.

BACKGROUND AND PURPOSE: While a larger fraction of head and neck squamous cell carcinoma (HNSCC) genomes is characterized by a high prevalence of copy number alterations (CNA-positive), a smaller subset with more favorable oncologic outcome is instead driven by somatic mutations (CNA-negative). We aimed to investigate the radiomic phenotypes of CNA-positive and -negative HNSCCs in contrast CT imag...

Machine learning predicts hepatocellular carcinoma risk from routine clinical data: a large population-based multicentric study.

Hepatocellular carcinoma (HCC) is a highly fatal tumor, for which risk stratification is crucial, yet remains challenging. Here, we develop an interpretable machine-learning framework for HCC risk stratification based on routinely collected clinical data. We utilize prospectively collected multimodal data from over 900,000 individuals and 983 cases of HCC across two population-scale cohorts: the "...

Digitally Assessed Nucleolar Size Compared to Traditional Pathologist WHO Grade Allocation in Clear Cell Renal Cell Carcinoma.

Traditional WHO grading for renal cell carcinoma (RCC), largely based on nucleolar prominence, has well-known intraobserver and interobserver variabil...

Automated acquisition of explainable knowledge from unannotated colposcopic images for predicting the natural course of CIN2.

OBJECTIVE: Cervical intraepithelial neoplasia grade 2 (CIN2) represents a critical turning point in cervical cancer progression. While its natural reg...

Decoding structural fingerprints to elucidate the mechanism of action of anti-apoptotic protein Mcl-1.

Overexpression of myeloid cell leukaemia-1 (Mcl-1) is commonly observed in numerous haematological malignancies and solid tumours, where it contribute...

Development and validation of a highly accurate multigene gene expression biomarker to predict chemotherapy response in primary triple-negative breast cancer.

PURPOSE: Triple-negative breast cancer (TNBC) is an aggressive subtype lacking estrogen and progesterone receptors and HER2 amplification. Representin...

A comparative evaluation of commercial software programs for automatic segmentation in breast cancer radiotherapy planning.

Commercial software tools for automatic segmentation have been adopted in breast cancer radiotherapy planning. In this study, we directly compared com...

Comparison of breast ultrasound image classification accuracy between convolutional neural networks and human experts using multicenter external validation cohort data.

PURPOSE: In recent years, much research has been conducted on ultrasound diagnosis of breast tumors using convolutional neural networks (CNNs). While ...

Contemporary Indications and Technical Limits of Transoral Laser Microsurgery for Laryngeal Squamous Cell Carcinoma.

Transoral laser microsurgery (TOLMS) is an established organ-preserving treatment for early-stage and selected intermediate-stage laryngeal squamous c...

Deconvolving cell-type-specific gene expression profiles from bulk RNA-seq samples.

Bulk RNA sequencing (bulk RNA-seq) and single-cell RNA sequencing (scRNA-seq) are two important high-throughput sequencing platforms that have wide ap...

A Deep Learning-Driven Framework Integrating Organoid-Based Functional Validation Identifies Universal Neoantigens from Recurrent Glioma Mutations.

Glioblastoma (GBM) is the most common malignant intracranial tumor in adults, with a median survival of only 16-20 months. Neoantigen therapy has show...

Prostate cancer tissue mapping and stratification using DRAQ5 and Eosin fluorescent labels integrated with AI classification and segmentation algorithms.

BACKGROUND: Fluorescent microscopy using the DRAQ5 and Eosin probes has been shown in the literature to be capable of producing rapid tissue character...

Path forward: Cryoablation for colorectal liver metastases.

PURPOSE: Colorectal liver metastases (CRLM) are a leading cause of mortality in patients with colorectal cancer. While surgical resection is the stand...

Advanced imaging techniques for tumor intraoperative navigation imaging.

Cancer remains a leading cause of mortality and morbidity, with surgical resection being a fundamental element of treatment. However, early detection ...

Finding the most promising indications for novel treatments in oncology.

Tackling cancer with effective therapies is a major challenge our society faces with significant costs and complexities of designing and validating tr...

Tumor vessel phenotype in colorectal cancer microenvironment according to age at diagnosis.

BACKGROUND: Given the global issue of the rising incidence of early-onset colorectal cancer (CRC), we tested the hypothesis that tumor vasculature phe...

In-silico study of machine learning discovers de novo lipogenesis for predicting prognosis and immunotherapy responses in kidney renal clear cell carcinoma.

Whole-body magnetic resonance imaging for cancer screening in asymptomatic adults: a multicenter study.

OBJECTIVES: Whole-body MRI is increasingly used for preventive health screening; however, the prevalence and distribution of incidental oncologically ...

Bone Metastasis Detection at CT with Deep Learning Models Trained Using Multicenter, Multimodal Reference Standards: Development and Evaluation.

Purpose To develop and validate deep learning models for detecting bone metastases on abdominal and thoracic CT scans, considering lesion visibility, ...

Systems-level integration of machine learning, SHAP explainability, PCA, and network topology reveals multitarget protective actions of tannic acid against doxorubicin toxicity in pentose phosphate pathway.

Doxorubicin (DOX) is an effective chemotherapeutic agent; however, its clinical use is limited due to dose-dependent toxicities. This study aimed to i...