AIMC Topic: Radiopharmaceuticals
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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...
The Value of Machine Learning-based Radiomics Model Characterized by PET Imaging with Ga-FAPI in Assessing Microvascular Invasion of Hepatocellular Carcinoma.
Academic radiology
Dec 7, 2024
RATIONALE AND OBJECTIVES: This study aimed to develop a radiomics model characterized by Ga-fibroblast activation protein inhibitors (FAPI) positron emission tomography (PET) imaging to predict microvascular invasion (MVI) of hepatocellular carcinoma...
A multi-view learning approach with diffusion model to synthesize FDG PET from MRI T1WI for diagnosis of Alzheimer's disease.
Alzheimer's & dementia : the journal of the Alzheimer's Association
Dec 6, 2024
INTRODUCTION: This study presents a novel multi-view learning approach for machine learning (ML)-based Alzheimer's disease (AD) diagnosis.
MIRD Pamphlet No. 31: MIRDcell V4-Artificial Intelligence Tools to Formulate Optimized Radiopharmaceutical Cocktails for Therapy.
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Dec 3, 2024
Radiopharmaceutical cocktails have been developed over the years to treat cancer. Cocktails of agents are attractive because 1 radiopharmaceutical is unlikely to have the desired therapeutic effect because of nonuniform uptake by the targeted cells. ...
Self-supervised neural network for Patlak-based parametric imaging in dynamic [F]FDG total-body PET.
European journal of nuclear medicine and molecular imaging
Dec 2, 2024
PURPOSE: The objective of this study is to generate reliable K parametric images from a shortened [F]FDG total-body PET for clinical applications using a self-supervised neural network algorithm.
3D full-dose brain-PET volume recovery from low-dose data through deep learning: quantitative assessment and clinical evaluation.
European radiology
Nov 28, 2024
OBJECTIVES: Low-dose (LD) PET imaging would lead to reduced image quality and diagnostic efficacy. We propose a deep learning (DL) method to reduce radiotracer dosage for PET studies while maintaining diagnostic quality.
F-FDG PET/CT-based habitat radiomics combining stacking ensemble learning for predicting prognosis in hepatocellular carcinoma: a multi-center study.
BMC cancer
Nov 27, 2024
BACKGROUND: This study aims to develop habitat radiomic models to predict overall survival (OS) for hepatocellular carcinoma (HCC), based on the characterization of the intratumoral heterogeneity reflected in F-FDG PET/CT images.
Accuracy of deep learning-based attenuation correction in Tc-GSA SPECT/CT hepatic imaging.
Radiography (London, England : 1995)
Nov 15, 2024
INTRODUCTION: Attenuation correction (AC) is necessary for accurate assessment of radioactive distribution in single photon emission computed tomography (SPECT). The method of computed tomography-based AC (CTAC) is widely used because of its accuracy...
A F-FDG PET/CT-based deep learning-radiomics-clinical model for prediction of cervical lymph node metastasis in esophageal squamous cell carcinoma.
Cancer imaging : the official publication of the International Cancer Imaging Society
Nov 12, 2024
BACKGROUND: To develop an artificial intelligence (AI)-based model using Radiomics, deep learning (DL) features extracted from F-fluorodeoxyglucose (F-FDG) Positron emission tomography/Computed Tomography (PET/CT) images of tumor and cervical lymph n...
Human-Artificial Intelligence Symbiotic Reporting for Theranostic Cancer Care.
Cancer biotherapy & radiopharmaceuticals
Nov 5, 2024
Reporting of diagnostic nuclear images in clinical cancer management is generally qualitative. Theranostic treatment with Lu radioligands for prostate cancer and neuroendocrine tumors is routinely given as the same arbitrary fixed administered activi...
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