AIMC Topic: Lung Neoplasms

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Feasibility of Sub-milliSievert Low-dose Computed Tomography with Deep Learning Image Reconstruction in Evaluating Pulmonary Subsolid Nodules: A Prospective Intra-individual Comparison Study.

Academic radiology Dec 13, 2024
RATIONALE AND OBJECTIVES: To comprehensively assess the feasibility of low-dose computed tomography (LDCT) using deep learning image reconstruction (DLIR) for evaluating pulmonary subsolid nodules, which are challenging due to their susceptibility to...
Feasibility Studies Humans Radiation Dosage Prospective Studies Signal-To-Noise Ratio Tomography, X-Ray Computed Middle Aged Deep Learning Lung Neoplasms Female Multiple Pulmonary Nodules Aged Radiographic Image Interpretation, Computer-Assisted Adult Male
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Real-World and Clinical Trial Validation of a Deep Learning Radiomic Biomarker for PD-(L)1 Immune Checkpoint Inhibitor Response in Advanced Non-Small Cell Lung Cancer.

JCO clinical cancer informatics Dec 13, 2024
PURPOSE: This study developed and validated a novel deep learning radiomic biomarker to estimate response to immune checkpoint inhibitor (ICI) therapy in advanced non-small cell lung cancer (NSCLC) using real-world data (RWD) and clinical trial data.
Adult Radiomics Biomarkers, Tumor Male Immune Checkpoint Inhibitors Retrospective Studies Humans Middle Aged Carcinoma, Non-Small-Cell Lung Female Lung Neoplasms Deep Learning Positron Emission Tomography Computed Tomography Aged B7-H1 Antigen Aged, 80 and over
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Development of a urine-based metabolomics approach for multi-cancer screening and tumor origin prediction.

Frontiers in immunology Dec 13, 2024
BACKGROUND: Cancer remains a leading cause of mortality worldwide. A non-invasive screening solution was required for early diagnosis of cancer. Multi-cancer early detection (MCED) tests have been considered to address the challenge by simultaneously...
Middle Aged Stomach Neoplasms Metabolomics Neoplasms Humans Metabolome Colorectal Neoplasms Lung Neoplasms Female Biomarkers, Tumor Early Detection of Cancer Aged Male Adult
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Comparative Analysis of Generative Pre-Trained Transformer Models in Oncogene-Driven Non-Small Cell Lung Cancer: Introducing the Generative Artificial Intelligence Performance Score.

JCO clinical cancer informatics Dec 11, 2024
PURPOSE: Precision oncology in non-small cell lung cancer (NSCLC) relies on biomarker testing for clinical decision making. Despite its importance, challenges like the lack of genomic oncology training, nonstandardized biomarker reporting, and a rapi...
Humans Artificial Intelligence High-Throughput Nucleotide Sequencing Oncogenes Precision Medicine Biomarkers, Tumor Lung Neoplasms Carcinoma, Non-Small-Cell Lung
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Non-invasive Prediction of Lymph Node Metastasis in NSCLC Using Clinical, Radiomics, and Deep Learning Features From F-FDG PET/CT Based on Interpretable Machine Learning.

Academic radiology Dec 10, 2024
PURPOSE: This study aimed to develop and evaluate a machine learning model combining clinical, radiomics, and deep learning features derived from PET/CT imaging to predict lymph node metastasis (LNM) in patients with non-small cell lung cancer (NSCLC...
Male Middle Aged Deep Learning Lung Neoplasms Positron Emission Tomography Computed Tomography Carcinoma, Non-Small-Cell Lung Aged Radiopharmaceuticals Retrospective Studies Humans Lymphatic Metastasis Adult Fluorodeoxyglucose F18 Female Machine Learning Radiomics
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Spectrum of errors in nodule detection and characterization using machine learning: A pictorial essay.

Current problems in diagnostic radiology Dec 10, 2024
In academic and research settings, computer-aided nodule detection software has been shown to increase accuracy, efficiency, and throughput. However, radiologists need to be familiar with the spectrum of errors that can occur when these algorithms ar...
Radiographic Image Interpretation, Computer-Assisted Humans Machine Learning Tomography, X-Ray Computed Algorithms Diagnostic Errors Lung Neoplasms Solitary Pulmonary Nodule
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Utility of a Large Language Model for Extraction of Clinical Findings from Healthcare Data following Lung Ablation: A Feasibility Study.

Journal of vascular and interventional radiology : JVIR Dec 9, 2024
To assess the feasibility of utilizing a large language model (LLM) in extracting clinically relevant information from healthcare data in patients who have undergone microwave ablation for lung tumors. In this single-center retrospective study, radio...
Pneumothorax Hemoptysis Recurrence Large Language Models Hemothorax Ablation Techniques Time Factors Lung Neoplasms Treatment Outcome Predictive Value of Tests Neoplasm Recurrence, Local Data Mining Reproducibility of Results Microwaves Natural Language Processing Aged Humans Feasibility Studies Male Retrospective Studies Middle Aged Electronic Health Records Female
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Deep learning using histological images for gene mutation prediction in lung cancer: a multicentre retrospective study.

The Lancet. Oncology Dec 6, 2024
BACKGROUND: Accurate detection of driver gene mutations is crucial for treatment planning and predicting prognosis for patients with lung cancer. Conventional genomic testing requires high-quality tissue samples and is time-consuming and resource-con...
Humans Prognosis Retrospective Studies Mutation High-Throughput Nucleotide Sequencing Middle Aged Deep Learning China Female Lung Neoplasms Aged Biomarkers, Tumor Male
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Self-supervised learning improves robustness of deep learning lung tumor segmentation models to CT imaging differences.

Medical physics Dec 5, 2024
BACKGROUND: Self-supervised learning (SSL) is an approach to extract useful feature representations from unlabeled data, and enable fine-tuning on downstream tasks with limited labeled examples. Self-pretraining is a SSL approach that uses curated do...
Deep Learning Image Processing, Computer-Assisted Lung Neoplasms Carcinoma, Non-Small-Cell Lung Humans Supervised Machine Learning Neural Networks, Computer Tomography, X-Ray Computed
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Machine learning-aided discovery of T790M-mutant EGFR inhibitor CDDO-Me effectively suppresses non-small cell lung cancer growth.

Cell communication and signaling : CCS Dec 5, 2024
BACKGROUND: Epidermal growth factor receptor (EGFR) T790M mutation often occurs during long durational erlotinib treatment of non-small cell lung cancer (NSCLC) patients, leading to drug resistance and disease progression. Identification of new selec...
Apoptosis Mutation Xenograft Model Antitumor Assays ErbB Receptors Protein Kinase Inhibitors Humans Cell Proliferation Machine Learning Signal Transduction Cell Line, Tumor Carcinoma, Non-Small-Cell Lung Animals Lung Neoplasms Mice, Nude Oleanolic Acid Antineoplastic Agents Mice
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