AIMC Topic: Lung Neoplasms

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Multimodal treatment of colorectal liver metastases: Where are we? Current strategies and future perspectives.

Bioscience trends Mar 18, 2025
Despite the continued high prevalence of colorectal cancer in the Western world, recent years have witnessed a decline in its mortality rate, largely attributable to the sustained advancement of multimodal treatment modalities for metastatic patients...
Liver Neoplasms Lung Neoplasms Immunotherapy Humans Liver Transplantation Artificial Intelligence Combined Modality Therapy Colorectal Neoplasms Hepatectomy
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Leveraging Artificial Intelligence as a Safety Net for Incidentally Identified Lung Nodules at a Tertiary Center.

Journal of the American College of Surgeons Mar 17, 2025
BACKGROUND: Artificial intelligence (AI)-powered platforms may be used to ensure that clinically significant lung nodules receive appropriate management. We studied the impact of a commercially available AI natural language processing tool on the det...
Multiple Pulmonary Nodules Solitary Pulmonary Nodule Natural Language Processing Tertiary Care Centers Male Middle Aged Lung Neoplasms Humans Artificial Intelligence Retrospective Studies Incidental Findings Tomography, X-Ray Computed Safety-net Providers Electronic Health Records Female Aged
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DPI-MoCo: Deep Prior Image Constrained Motion Compensation Reconstruction for 4D CBCT.

IEEE transactions on medical imaging Mar 17, 2025
4D cone-beam computed tomography (CBCT) plays a critical role in adaptive radiation therapy for lung cancer. However, extremely sparse sampling projection data will cause severe streak artifacts in 4D CBCT images. Existing deep learning (DL) methods ...
Lung Deep Learning Cone-Beam Computed Tomography Image Processing, Computer-Assisted Humans Four-Dimensional Computed Tomography Algorithms Lung Neoplasms Artifacts Phantoms, Imaging
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Establishing a Deep Learning Model That Integrates Pretreatment and Midtreatment Computed Tomography to Predict Treatment Response in Non-Small Cell Lung Cancer.

International journal of radiation oncology, biology, physics Mar 13, 2025
PURPOSE: Patients with identical stages or similar tumor volumes can vary significantly in their responses to radiation therapy (RT) due to individual characteristics, making personalized RT for non-small cell lung cancer (NSCLC) challenging. This st...
Aged, 80 and over Adult Male Middle Aged Tomography, X-Ray Computed Humans Female Retrospective Studies Aged Carcinoma, Non-Small-Cell Lung Area Under Curve Tumor Burden Deep Learning Radiotherapy Dosage ROC Curve Lung Neoplasms Treatment Outcome
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Integration of intratumoral and peritumoral CT radiomic features with machine learning algorithms for predicting induction therapy response in locally advanced non-small cell lung cancer.

BMC cancer Mar 13, 2025
OBJECTIVES: To extract intratumoral, peritumoral, and integrated intratumoral-peritumoral CT radiomic features, develop multi-source radiomic models using various machine learning algorithms to identify the optimal model, and integrate clinical facto...
Adult Carcinoma, Non-Small-Cell Lung Radiomics Tumor Burden Male Induction Chemotherapy Middle Aged Lung Neoplasms Nomograms Retrospective Studies Treatment Outcome Humans Tomography, X-Ray Computed Support Vector Machine Machine Learning Female Algorithms Aged
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Robust vs. Non-robust radiomic features: the quest for optimal machine learning models using phantom and clinical studies.

Cancer imaging : the official publication of the International Cancer Imaging Society Mar 12, 2025
PURPOSE: This study aimed to select robust features against lung motion in a phantom study and use them as input to feature selection algorithms and machine learning classifiers in a clinical study to predict the lymphovascular invasion (LVI) of non-...
Humans Machine Learning Algorithms Tomography, X-Ray Computed Carcinoma, Non-Small-Cell Lung Neoplasm Invasiveness Phantoms, Imaging Female Radiomics Male Lung Neoplasms
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Deep learning radiomics for the prediction of epidermal growth factor receptor mutation status based on MRI in brain metastasis from lung adenocarcinoma patients.

BMC cancer Mar 12, 2025
BACKGROUND: Early and accurate identification of epidermal growth factor receptor (EGFR) mutation status in non-small cell lung cancer (NSCLC) patients with brain metastases is critical for guiding targeted therapy. This study aimed to develop a deep...
Middle Aged Deep Learning ROC Curve Lung Neoplasms Magnetic Resonance Imaging Mutation ErbB Receptors Adenocarcinoma of Lung Adult Radiomics Brain Neoplasms Male Retrospective Studies Female Humans Aged
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Lung cancer detection with machine learning classifiers with multi-attribute decision-making system and deep learning model.

Scientific reports Mar 12, 2025
Diseases of the airways and the other parts of the lung cause chronic respiratory diseases. The major cause of lung disease is tobacco smoke, along with risk factors such as dust, air pollution, chemicals, and frequent lower respiratory infections du...
Lung Neoplasms Humans Decision Making Machine Learning Deep Learning
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Validation of patient-specific deep learning markerless lung tumor tracking aided by 4DCBCT.

Physics in medicine and biology Mar 10, 2025
. Tracking tumors with multi-leaf collimators and x-ray imaging can be a cost-effective motion management method to reduce internal target volume margins for lung cancer patients, sparing normal tissues while ensuring target coverage. To realize that...
Four-Dimensional Computed Tomography Deep Learning Cone-Beam Computed Tomography Image Processing, Computer-Assisted Lung Neoplasms Humans
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Prediction of tumor spread through air spaces with an automatic segmentation deep learning model in peripheral stage I lung adenocarcinoma.

Respiratory research Mar 8, 2025
BACKGROUND: To evaluate the clinical applicability of deep learning (DL) models based on automatic segmentation in preoperatively predicting tumor spread through air spaces (STAS) in peripheral stage I lung adenocarcinoma (LUAD).
Neoplasm Staging Adenocarcinoma of Lung Tomography, X-Ray Computed Humans Female Middle Aged Retrospective Studies Aged Deep Learning Male Lung Neoplasms Predictive Value of Tests
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