Other Cancers

Dual-energy x-ray imaging for AI-based lung tumor localization using foundation models: a phantom study.

Objectives.This study assessed the performance of artificial intelligence (AI)-based tumor tracking using foundation models in planar dual-energy (DE) x-ray compared with the corresponding high-energy (HE) images from the same DE acquisition.Approach.An in-house phantom with pork ribs and artificial tumors was scanned using fast kVp-switching DE planar imaging using two kVp pairs (60/120 kVp and 8...

Multiscale Spatial Fusion Feature-Driven Characterization of Gastric Cancer Invasive Margins: A Multicenter Cohort Study for Preoperative Accurate Differentiation Between T4a and T4b Subtypes.

Accurate preoperative differentiation of gastric cancer T4a/b stages is crucial for surgical planning and prognosis. However, conventional CT assessments often yield suboptimal staging accuracy due to visual limitations and inadequate peritumoral microinvasion quantification. This study developed a multi-scale spatial feature fusion model based on extended regions of interest (eROI) for precise pr...

Multimodal prediction of metachronous liver metastasis in stage I-III colorectal cancer patients: multicenter cohort study employing machine learning.

OBJECTIVE: Postoperative metachronous liver metastasis (MLM) in colorectal cancer (CRC) patients is often difficult to predict using conventional clin...

Artificial intelligence (AI) uses in stereotactic radiosurgery (SRS): diagnosis with brain metastasis (BM) - A systematic review.

BACKGROUND: Brain metastases (BM) are the most common intracranial tumors in adults, and stereotactic radiosurgery (SRS) has become a mainstay of mana...

Machine Learning Prediction of Liver Fibrosis in Patients with Metabolic Dysfunction Associated Steatotic Liver Disease (MASLD).

BACKGROUND: Accurate staging of liver fibrosis is crucial for risk stratification in patients with metabolic dysfunction-associated steatotic liver di...

AI-driven tumor heterogeneity quantification and survival prediction in pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies worldwide, and accurate prognostic prediction remains highly challengin...

ABUS-ResMask-Net: ABUS Lesion Classification Network Design with ResMask Module and BI-RADS Content-Awareness Auxiliary Tasks.

This study aims to develop a 2.5D deep learning model with shape and margin as auxiliary tasks to improve the diagnostic performance of benign-maligna...

Interpretable multimodal deep learning for time-resolved survival prediction after hepatocellular carcinoma resection.

Hepatocellular carcinoma (HCC) exhibits substantial interpatient heterogeneity, leading to markedly variable outcomes and survival even among patients...

Multi-task deep learning model for predicting EGFR mutation status in NSCLC.

Multi-task DL for predicting EGFR mutation status Epidermal growth factor receptor (EGFR) mutation status is a critical biomarker in the management of...

Exploratory clinical-CT machine learning characterization of CK7 expression in clear cell renal cell carcinoma.

BACKGROUND: Cytokeratin 7 (CK7) expression in clear cell renal cell carcinoma (ccRCC) may reflect tumor phenotype and biological heterogeneity, but it...

Screening of shared molecular markers between cervical cancer and major depressive disorder and the mechanism of CRAT/CLIC4 regulating EMT in cervical cancer cells.

BACKGROUND: Cervical cancer (CC) ranks among the most prevalent malignant neoplasms affecting women worldwide. Tumor recurrence, distant metastases, a...

Exosomes in cancer drug resistance: dual roles in therapy failure and emerging precision therapeutics.

Exosomes play a key role in cancer, functioning both as drivers of drug resistance and as tools for therapy. Tumor-derived exosomes facilitate interce...

An evidence informed framework for artificial intelligence in rare breast cancers using small cohort validation synthetic data practices and clinical governance.

Rare breast cancers represent a clinically important but underrepresented group of malignancies. In this Perspective, rare breast cancers are consider...

Comprehensive evaluation of angiogenesis-associated genes in papillary thyroid cancer using bulk RNA and single-cell sequencing data.

OBJECTIVE: The objective of this study is to explore the expression patterns of angiogenesis-related genes in papillary thyroid cancer (PTC) to enhanc...

Multi-omics and network toxicology prioritize ADAMTS13 as a candidate gene computationally linked to TDCPP targets in hepatocellular carcinoma.

BACKGROUND: Tris(1,3-dichloro-2-propyl) phosphate (TDCPP), a widely used organophosphate flame retardant, has been increasingly recognized as a potent...

Integration of network toxicology, machine learning and single-cell sequencing identifies candidate molecular links between air pollutants and hepatocellular carcinoma.

BACKGROUND: Epidemiological studies link long-term air pollution to an increased risk of hepatocellular carcinoma (HCC), but the underlying toxicologi...

Investigating the mechanisms of malignant progression in colorectal cancer using weighted gene co-expression network analysis and machine learning.

Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide. Understanding the complex molecular networks that underlie this...

Machine learning-guided dose-time optimization and experimental validation enhance coumarin therapeutics in oncology.

Coumarins are a group of naturally occurring compounds that have garnered significant interest for their potential anticancer properties, characterize...

FKBP10 may affect the malignant phenotype of oral squamous cell carcinoma cells through the ECM/WNT signaling pathway.

Oral squamous cell carcinoma (OSCC) is a common malignant tumor in the oral and maxillofacial region with a poor prognosis, and its pathophysiology ha...

Predicting local control of brain metastases after Gamma Knife radiosurgery: a multimodal deep learning-radiomics approach.

BACKGROUND: Accurate prediction of local control (LC) following Gamma Knife radiosurgery (GKRS) remains clinically challenging for patients with brain...