AIMC Topic: Bone Neoplasms

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In Silico Digital Twins of Bone Metastasis Enable Investigation of Tumor Progression and Therapy Response.

Cancer research
UNLABELLED: Bone metastasis (BM) is a leading cause of morbidity and mortality in patients with prostate and renal cancer. The complex and dynamic biological processes driving its progression present significant challenges for both understanding and ...

Microfluidics-based label-free SERS profiling of exosomes with machine learning for osteosarcoma diagnosis.

Talanta
Osteosarcoma (OS) calls for early diagnosis to significantly improve patient survival rates. Exosomes hold significant potential as noninvasive biomarkers for the early diagnosis of cancer. Here, we design a microfluidic device to purify and analyze ...

Metabolic Adaptation Study of Tumor Cells during Lung Cancer Bone Metastasis in Mice Based on Single-Cell Metabolome Analysis.

Journal of the American Society for Mass Spectrometry
Lung cancer metastasis, the leading cause of patient mortality, is driven by circulating tumor cells (CTCs), which act as direct mediators of metastatic spread. To elucidate the metabolic heterogeneity across lung cancer metastatic stages, a panorami...

Impact of environmental pollution on human health: Investigating the role of Polycyclic Aromatic Hydrocarbons in pediatric osteosarcoma.

Ecotoxicology and environmental safety
BACKGROUND: Polycyclic aromatic hydrocarbons (PAHs), widely emitted through industrial processes and vehicular exhaust, are recognized environmental carcinogens. Although PAH exposure has been linked to various malignancies, the specific molecular me...

A Deep Learning Model for Comprehensive Automated Bone Lesion Detection and Classification on Staging Computed Tomography Scans.

Academic radiology
RATIONALE AND OBJECTIVES: A common site of metastases for a variety of cancers is the bone, which is challenging and time consuming to review and important for cancer staging. Here, we developed a deep learning approach for detection and classificati...

A Novel Two-step Classification Approach for Differentiating Bone Metastases From Benign Bone Lesions in SPECT/CT Imaging.

Academic radiology
RATIONALE AND OBJECTIVES: This study aims to develop and validate a novel two-step deep learning framework for the automated detection, segmentation, and classification of bone metastases in SPECT/CT imaging, accurately distinguishing malignant from ...

MRI Radiomics and Automated Habitat Analysis Enhance Machine Learning Prediction of Bone Metastasis and High-Grade Gleason Scores in Prostate Cancer.

Academic radiology
RATIONALE AND OBJECTIVES: To explore the value of machine learning models based on MRI radiomics and automated habitat analysis in predicting bone metastasis and high-grade pathological Gleason scores in prostate cancer.

Exosomal Gene Biomarkers in Osteosarcoma: Mifepristone as a Targeted Therapeutic Revealed by Multi-Omics Analysis.

FASEB journal : official publication of the Federation of American Societies for Experimental Biology
Osteosarcoma (OS) is an aggressive bone cancer that mainly occurs in children and adolescents. OS patients are mainly treated with neoadjuvant chemotherapy and surgical resection. This treatment is effective for early osteosarcoma. However, the effec...

Recent advancements in feature extraction and classification based bone cancer detection - a systematic review.

Biomedical physics & engineering express
Cancer is a deadly disease that occurs due to the uncontrolled growth of abnormal cells. Bone cancer is the third most occurring disease; approximately 10,000 patients suffer from bone cancer in India annually. It can lead to death if not diagnosed i...

Radiomics-based machine learning in prediction of response to neoadjuvant chemotherapy in osteosarcoma: A systematic review and meta-analysis.

Clinical imaging
BACKGROUND AND AIMS: Osteosarcoma (OS) is the most common primary bone malignancy, and neoadjuvant chemotherapy (NAC) improves survival rates. However, OS heterogeneity results in variable treatment responses, highlighting the need for reliable, non-...