AIMC Topic: Fluorodeoxyglucose F18

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A PET/CT-based 3D deep learning model for predicting spread through air spaces in stage I lung adenocarcinoma.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico Feb 24, 2025
PURPOSE: This study evaluates a three-dimensional (3D) deep learning (DL) model based on fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) for predicting the preoperative status of spread through air spa...
Female Aged Aged, 80 and over Sensitivity and Specificity Male Positron Emission Tomography Computed Tomography Humans Retrospective Studies Neoplasm Staging Radiopharmaceuticals Fluorodeoxyglucose F18 Adenocarcinoma of Lung Middle Aged Deep Learning Imaging, Three-Dimensional Lung Neoplasms
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Artificial intelligence algorithm for preoperative prediction of FIGO stage in ovarian cancer based on clinical features integrated 18F-FDG PET/CT metabolic and radiomics features.

Journal of cancer research and clinical oncology Feb 20, 2025
PURPOSE: The International Federation of Gynecology and Obstetric (FIGO) stage is critical to guiding the treatments of ovarian cancer (OC). We tried to develop a model to predict the FIGO stage of OC through machine learning algorithms with patients...
Retrospective Studies Female Middle Aged Aged Humans Radiopharmaceuticals Adult Ovarian Neoplasms Artificial Intelligence Fluorodeoxyglucose F18 Radiomics Positron Emission Tomography Computed Tomography Machine Learning Neoplasm Staging Algorithms
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IRMA: Machine learning-based harmonization of F-FDG PET brain scans in multi-center studies.

European journal of nuclear medicine and molecular imaging Feb 18, 2025
PURPOSE: Center-specific effects in PET brain scans arise due to differences in technical and procedural aspects. This restricts the merging of data between centers and introduces source-specific bias.
Humans Positron-Emission Tomography Machine Learning Fluorodeoxyglucose F18 Aged Brain Male Female Image Processing, Computer-Assisted Parkinson Disease Alzheimer Disease
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Predicting malignant risk of ground-glass nodules using convolutional neural networks based on dual-time-point F-FDG PET/CT.

Cancer imaging : the official publication of the International Cancer Imaging Society Feb 18, 2025
BACKGROUND: Accurately predicting the malignant risk of ground-glass nodules (GGOs) is crucial for precise treatment planning. This study aims to utilize convolutional neural networks based on dual-time-point F-FDG PET/CT to predict the malignant ris...
Positron Emission Tomography Computed Tomography Radiopharmaceuticals Fluorodeoxyglucose F18 Middle Aged Humans Convolutional Neural Networks Neural Networks, Computer Female Lung Neoplasms Retrospective Studies Aged Solitary Pulmonary Nodule Adult Male
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Comparative analysis of intestinal tumor segmentation in PET CT scans using organ based and whole body deep learning.

BMC medical imaging Feb 17, 2025
BACKGROUND: 18-Fluoro-deoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) is a valuable imaging tool widely used in the management of cancer patients. Deep learning models excel at segmenting highly metabolic tumors but face ch...
Intestinal Neoplasms Positron Emission Tomography Computed Tomography Radiopharmaceuticals Fluorodeoxyglucose F18 Whole Body Imaging Humans Female Aged Male Middle Aged Deep Learning
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Reducing inference cost of Alzheimer's disease identification using an uncertainty-aware ensemble of uni-modal and multi-modal learners.

Scientific reports Feb 14, 2025
While multi-modal deep learning approaches trained using magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG PET) data have shown promise in the accurate identification of Alzheimer's disease, their clinical appl...
Humans Brain Deep Learning Magnetic Resonance Imaging Alzheimer Disease Positron-Emission Tomography Fluorodeoxyglucose F18 Uncertainty
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Optimizing MR-based attenuation correction in hybrid PET/MR using deep learning: validation with a flatbed insert and consistent patient positioning.

European journal of nuclear medicine and molecular imaging Feb 6, 2025
PURPOSE: To address the challenges of verifying MR-based attenuation correction (MRAC) in PET/MR due to CT positional mismatches and alignment issues, this study utilized a flatbed insert and arms-down positioning during PET/CT scans to achieve preci...
Humans Female Reproducibility of Results Aged Adult Magnetic Resonance Imaging Multimodal Imaging Positron Emission Tomography Computed Tomography Fluorodeoxyglucose F18 Male Patient Positioning Middle Aged Deep Learning Image Processing, Computer-Assisted
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A machine learning-based 18F-FDG PET/CT multi-modality fusion radiomics model to predict Mediastinal-Hilar lymph node metastasis in NSCLC: a multi-centre study.

Clinical radiology Jan 29, 2025
AIM: To develop and validate a machine learning (ML) model based on positron emission tomography/computed tomography (PET/CT) multi-modality fusion radiomics to improve the prediction efficiency of mediastinal-hilar lymph node metastasis (LNM).
Middle Aged Aged Lung Neoplasms Lymphatic Metastasis Humans Adult Lymph Nodes Positron Emission Tomography Computed Tomography Machine Learning Radiomics Carcinoma, Non-Small-Cell Lung Radiopharmaceuticals Retrospective Studies Male Fluorodeoxyglucose F18 Female Mediastinum
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F-FDG PET/CT radiomic analysis and artificial intelligence to predict pathological complete response after neoadjuvant chemotherapy in breast cancer patients.

La Radiologia medica Jan 28, 2025
PURPOSE: Build machine learning (ML) models able to predict pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer (BC) patients based on conventional and radiomic signatures extracted from baseline [F]FDG PET/CT.
Female Aged Adult Predictive Value of Tests Breast Neoplasms Humans Middle Aged Positron Emission Tomography Computed Tomography Radiomics Artificial Intelligence Treatment Outcome Radiopharmaceuticals Machine Learning Neoadjuvant Therapy Fluorodeoxyglucose F18 Retrospective Studies Chemotherapy, Adjuvant Lymphatic Metastasis
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F-18 FDG PET/CT based Preoperative Machine Learning Prediction Models for Evaluating Regional Lymph Node Metastasis Status of Patients with Colon Cancer.

Asian Pacific journal of cancer prevention : APJCP Jan 1, 2025
OBJECTIVE: This study aimed to develop a simple machine-learning model incorporating lymph node metastasis status with F-18 Fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) and clinical information for predicting regio...
Middle Aged ROC Curve Lymph Nodes Follow-Up Studies Lymphatic Metastasis Positron Emission Tomography Computed Tomography Colonic Neoplasms Radiopharmaceuticals Fluorodeoxyglucose F18 Female Aged Humans Aged, 80 and over Machine Learning Adult Prognosis Male Retrospective Studies
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