AIMC Topic: Bone Neoplasms

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Machine learning for synchronous bone metastasis risk prediction in high grade lung neuroendocrine carcinoma.

Scientific reports
Bone metastasis (BM) is common in high-grade lung neuroendocrine tumors (NETs). This study aimed to use multiple machine learning algorithms to exploring the significant factors associated with synchronous BM in these patients. Patients diagnosed wit...

Whole‑exome evolutionary profiling of osteosarcoma uncovers metastasis‑related driver mutations and generates an independently validated predictive classifier.

Journal of translational medicine
BACKGROUND: Osteosarcoma is the most common primary malignant bone tumor, with high invasiveness and metastatic potential and a poor prognosis in patients with metastatic cancer. Despite the rapid advancements in genomics in recent years that provide...

Interpretable machine learning models for survival prediction in prostate cancer bone metastases.

Scientific reports
Prostate cancer bone metastasis (PCBM) is a highly lethal condition with limited survival. Accurate survival prediction is essential for managing these typically incurable patients. However, existing clinical models lack precision. This study seeks t...

LncRNAs regulates cell death in osteosarcoma.

Scientific reports
Despite improvements, prognosis in osteosarcoma patients remains poor, making it essential to identify additional and more robust therapeutic targets. Non-apoptotic receptor-mediated cell death (RCD), which plays a crucial role in the pathogenesis of...

Automated classification of chondroid tumor using 3D U-Net and radiomics with deep features.

Scientific reports
Classifying chondroid tumors is an essential step for effective treatment planning. Recently, with the advances in computer-aided diagnosis and the increasing availability of medical imaging data, automated tumor classification using deep learning sh...

Artificial intelligence in bone metastasis analysis: Current advancements, opportunities and challenges.

Computers in biology and medicine
BACKGROUND: Artificial Intelligence is transforming medical imaging, particularly in the analysis of bone metastases (BM), a serious complication of advanced cancers. Machine learning and deep learning techniques offer new opportunities to improve de...

Synthesizing [F]PSMA-1007 PET bone images from CT images with GAN for early detection of prostate cancer bone metastases: a pilot validation study.

BMC cancer
BACKGROUND: [F]FDG PET/CT scan combined with [F]PSMA-1007 PET/CT scan is commonly conducted for detecting bone metastases in prostate cancer (PCa). However, it is expensive and may expose patients to more radiation hazards. This study explores deep l...

PET image nonuniformity texture features for metastasis risk prediction in osteosarcoma.

Nuclear medicine communications
OBJECTIVE: PET image analysis provides tumor heterogeneity data related to neoadjuvant chemotherapy response (NACR) and metastatic risk in osteosarcoma. Ki-67 expression is used to predict metastasis. The accuracy of prediction models with image quan...

Surgical and radiological outcomes of giant cell tumor of the bone: prognostic value of Campanacci grading and selective use of denosumab.

Journal of orthopaedics and traumatology : official journal of the Italian Society of Orthopaedics and Traumatology
BACKGROUND: Advancements in diagnostic and therapeutic modalities for giant cell tumors of bone (GCTB) have introduced molecular and radiological tools that refine clinical decision-making. H3.3 G34W immunohistochemical staining has become a routine ...

Prediction of High-Dose Methotrexate Blood Concentration in Osteosarcoma Patients Using Machine Learning.

Drug design, development and therapy
INTRODUCTION: High-dose methotrexate is a typical chemotherapy that is widely used in the treatment of osteosarcoma. However, the unique dose-response relationship of methotrexate makes its treatment window relatively narrow, and its clinical use is ...