AIMC Topic: Lung Neoplasms

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Identification of Origin for Spinal Metastases from MR Images: Comparison Between Radiomics and Deep Learning Methods.

World neurosurgery Apr 13, 2023
OBJECTIVE: To determine whether spinal metastatic lesions originated from lung cancer or from other cancers based on spinal contrast-enhanced T1 (CET1) magnetic resonance (MR) images analyzed using radiomics (RAD) and deep learning (DL) methods.
Retrospective Studies Deep Learning Magnetic Resonance Imaging Spinal Neoplasms Lung Neoplasms Humans
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Day surgery unit robotics thoracic surgery: feasibility and management.

Journal of cancer research and clinical oncology Apr 10, 2023
BACKGROUND: Day surgery has been widely carried out in medical developed countries such as Europe and the United States with high efficiency, safety and economy. The development of thoracic day surgery started late, and currently only a few top three...
Male Postoperative Complications Lung Neoplasms Humans Retrospective Studies Thoracic Surgery, Video-Assisted Ambulatory Surgical Procedures Thoracic Surgery Robotics Feasibility Studies
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Deep Learning With an Attention Mechanism for Differentiating the Origin of Brain Metastasis Using MR images.

Journal of magnetic resonance imaging : JMRI Mar 25, 2023
BACKGROUND: Brain metastasis (BM) is a serious neurological complication of cancer of different origins. The value of deep learning (DL) to identify multiple types of primary origins remains unclear.
Deep Learning Lung Neoplasms Magnetic Resonance Imaging Diffusion Magnetic Resonance Imaging Humans Carcinoma, Non-Small-Cell Lung Retrospective Studies Brain Neoplasms Female Middle Aged Breast Neoplasms
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Deep learning-based fast volumetric imaging using kV and MV projection images for lung cancer radiotherapy: A feasibility study.

Medical physics Mar 24, 2023
PURPOSE: The long acquisition time of CBCT discourages repeat verification imaging, therefore increasing treatment uncertainty. In this study, we present a fast volumetric imaging method for lung cancer radiation therapy using an orthogonal 2D kV/MV ...
Phantoms, Imaging Lung Neoplasms Feasibility Studies Deep Learning Cone-Beam Computed Tomography Humans Lung
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The value of artificial intelligence in the diagnosis of lung cancer: A systematic review and meta-analysis.

PloS one Mar 23, 2023
Lung cancer is a common malignant tumor disease with high clinical disability and death rates. Currently, lung cancer diagnosis mainly relies on manual pathology section analysis, but the low efficiency and subjective nature of manual film reading ca...
Sensitivity and Specificity Humans Lung Neoplasms Artificial Intelligence
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Robot-assisted thoracic surgery for stages IIB-IVA non-small cell lung cancer: retrospective study of feasibility and outcome.

Journal of robotic surgery Mar 16, 2023
Robot-assisted thoracic surgery (RATS) for higher stages non-small cell lung carcinoma (NSCLC) remains controversial. This study reports the feasibility of RATS in patients with stages IIB-IVA NSCLC. A single-institute, retrospective study was conduc...
Neoplasm Staging Robotic Surgical Procedures Feasibility Studies Carcinoma, Non-Small-Cell Lung Robotics Thoracic Surgery Humans Lung Neoplasms Treatment Outcome Retrospective Studies
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Validation of a Fully Automated Hybrid Deep Learning Cardiac Substructure Segmentation Tool for Contouring and Dose Evaluation in Lung Cancer Radiotherapy.

Clinical oncology (Royal College of Radiologists (Great Britain)) Mar 11, 2023
BACKGROUND AND PURPOSE: Accurate and consistent delineation of cardiac substructures is challenging. The aim of this work was to validate a novel segmentation tool for automatic delineation of cardiac structures and subsequent dose evaluation, with p...
Heart Deep Learning Organs at Risk Image Processing, Computer-Assisted Humans Lung Neoplasms Radiotherapy Planning, Computer-Assisted Tomography, X-Ray Computed
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Incidentally found resectable lung cancer with the usage of artificial intelligence on chest radiographs.

PloS one Mar 10, 2023
PURPOSE: Detection of early lung cancer using chest radiograph remains challenging. We aimed to highlight the benefit of using artificial intelligence (AI) in chest radiograph with regard to its role in the unexpected detection of resectable early lu...
Radiography, Thoracic Humans Lung Neoplasms Retrospective Studies Artificial Intelligence Radiography
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A Novel IoT-Enabled Healthcare Monitoring Framework and Improved Grey Wolf Optimization Algorithm-Based Deep Convolution Neural Network Model for Early Diagnosis of Lung Cancer.

Sensors (Basel, Switzerland) Mar 8, 2023
Lung cancer is a high-risk disease that causes mortality worldwide; nevertheless, lung nodules are the main manifestation that can help to diagnose lung cancer at an early stage, lowering the workload of radiologists and boosting the rate of diagnosi...
Early Detection of Cancer Neural Networks, Computer Humans Delivery of Health Care Artificial Intelligence Lung Neoplasms Algorithms
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Predicting survival after radiosurgery in patients with lung cancer brain metastases using deep learning of radiomics and EGFR status.

Physical and engineering sciences in medicine Mar 1, 2023
The early prediction of overall survival (OS) in patients with lung cancer brain metastases (BMs) after Gamma Knife radiosurgery (GKRS) can facilitate patient management and outcome improvement. However, the disease progression is influenced by multi...
Retrospective Studies Brain Neoplasms Deep Learning Humans ErbB Receptors Lung Neoplasms Radiosurgery
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