AIMC Topic: Lutetium

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Prognostic Value of AI-Assisted Lesion Tracking on End-of-Treatment PSMA PET in mCRPC Patients Treated with Lu-PSMA: A Retrospective, Single-Center Study.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine Nov 3, 2025
This study aimed to explore the prognostic value of the artificial intelligence-assisted lesion tracking applied to prostate-specific membrane antigen (PSMA) PET in patients with metastatic castration-resistant prostate cancer (mCRPC) treated with PS...
Male Middle Aged Treatment Outcome Prostate-Specific Antigen Prognosis Retrospective Studies Aged Aged, 80 and over Radioisotopes Antigens, Surface Humans Glutamate Carboxypeptidase II Artificial Intelligence Lutetium Radiopharmaceuticals Heterocyclic Compounds, 1-Ring Positron-Emission Tomography Dipeptides Prostatic Neoplasms, Castration-Resistant
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Deep Learning for Automated Measures of SUV and Molecular Tumor Volume in [Ga]PSMA-11 or [F]DCFPyL, [F]FDG, and [Lu]Lu-PSMA-617 Imaging with Global Threshold Regional Consensus Network.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine Nov 3, 2025
Metastatic castration-resistant prostate cancer has a high rate of mortality with a limited number of effective treatments after hormone therapy. Radiopharmaceutical therapy with [Lu]Lu-prostate-specific membrane antigen-617 (LuPSMA) is one treatment...
Humans Aged Male Deep Learning Consensus Urea Lysine Radioisotopes Tumor Burden Gallium Radioisotopes Image Processing, Computer-Assisted Heterocyclic Compounds, 1-Ring Gallium Isotopes Automation Fluorodeoxyglucose F18 Positron Emission Tomography Computed Tomography Lutetium Oligopeptides Prostate-Specific Antigen Dipeptides
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Prediction of Lesion-Based Treatment Response after Two Cycles of Lu-177 Prostate Specific Membrane Antigen Treatment in Metastatic Castration-Resistant Prostate Cancer Using Machine Learning.

Urologia internationalis Sep 30, 2024
INTRODUCTION: Lutetium-177 (Lu-177) prostate-specific membrane antigen (PSMA) therapy is a radionuclide treatment that prolongs overall survival in metastatic castration-resistant prostate cancer (MCRPC). We aimed to predict lesion-based treatment re...
Gallium Radioisotopes Glutamate Carboxypeptidase II Lutetium Neoplasm Metastasis Prostatic Neoplasms, Castration-Resistant Radioisotopes Antigens, Surface Machine Learning Retrospective Studies Aged Aged, 80 and over Treatment Outcome Positron Emission Tomography Computed Tomography Radiopharmaceuticals Male Middle Aged Humans
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Precise positioning of gamma ray interactions in multiplexed pixelated scintillators using artificial neural networks.

Biomedical physics & engineering express Jun 5, 2024
. The positioning ofray interactions in positron emission tomography (PET) detectors is commonly made through the evaluation of the Anger logic flood histograms. machine learning techniques, leveraging features extracted from signal waveform, have de...
Algorithms Equipment Design Positron-Emission Tomography Cerium Lutetium Scintillation Counting Silicon Gamma Rays Neural Networks, Computer
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A Deep-Learning-Based Partial-Volume Correction Method for Quantitative Lu SPECT/CT Imaging.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine Jun 3, 2024
With the development of new radiopharmaceutical therapies, quantitative SPECT/CT has progressively emerged as a crucial tool for dosimetry. One major obstacle of SPECT is its poor resolution, which results in blurring of the activity distribution. Es...
Humans Phantoms, Imaging Single Photon Emission Computed Tomography Computed Tomography Deep Learning Lutetium Image Processing, Computer-Assisted Monte Carlo Method Radioisotopes
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Quantitative evaluation of a deep learning-based framework to generate whole-body attenuation maps using LSO background radiation in long axial FOV PET scanners.

European journal of nuclear medicine and molecular imaging Jul 19, 2022
PURPOSE: Attenuation correction is a critically important step in data correction in positron emission tomography (PET) image formation. The current standard method involves conversion of Hounsfield units from a computed tomography (CT) image to cons...
Fluorodeoxyglucose F18 Lutetium Background Radiation Image Processing, Computer-Assisted Magnetic Resonance Imaging Radiopharmaceuticals Positron-Emission Tomography Humans Deep Learning Water
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Deep-Learning Generation of Synthetic Intermediate Projections Improves Lu SPECT Images Reconstructed with Sparsely Acquired Projections.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine Aug 28, 2020
The aims of this study were to decrease the Lu-SPECT acquisition time by reducing the number of projections and to circumvent image degradation by adding deep-learning-generated synthesized projections. We constructed a deep convolutional U-net-shap...
Humans Deep Learning Time Factors Tomography, Emission-Computed, Single-Photon Image Processing, Computer-Assisted Lutetium Radioisotopes
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A deep learning approach to radiation dose estimation.

Physics in medicine and biology Feb 4, 2020
Currently methods for predicting absorbed dose after administering a radiopharmaceutical are rather crude in daily clinical practice. Most importantly, individual tissue density distributions as well as local variations of the concentration of the ra...
Tissue Distribution Glutamate Carboxypeptidase II Lutetium Organs at Risk Radiation Dosage Humans Monte Carlo Method Neural Networks, Computer Radioisotopes Algorithms Reproducibility of Results Tomography, X-Ray Computed Neoplasms Deep Learning Radiopharmaceuticals
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GTM-Based QSAR Models and Their Applicability Domains.

Molecular informatics Feb 3, 2015
In this paper we demonstrate that Generative Topographic Mapping (GTM), a machine learning method traditionally used for data visualisation, can be efficiently applied to QSAR modelling using probability distribution functions (PDF) computed in the l...
Databases, Chemical Humans Gadolinium Thrombin Machine Learning Lutetium Models, Chemical Calcium
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Machine Learning-based Dose Prediction in [Lu]Lu-PSMA-617 Therapy by Integrating Biomarkers and Radiomic Features from [Ga]Ga-PSMA-11 Positron Emission Tomography/Computed Tomography.

International journal of radiation oncology, biology, physics Nov 1, 2025
PURPOSE: The study aimed to develop machine learning (ML) models for pretherapy prediction of absorbed doses (ADs) in kidneys and tumoral lesions for patients with metastatic castration-resistant prostate cancer (mCRPC) undergoing [Lu]Lu-PSMA-617 (Lu...
Radiotherapy Dosage Monte Carlo Method Radioisotopes Organometallic Compounds Prostate-Specific Antigen Radiopharmaceuticals Dipeptides Prostatic Neoplasms, Castration-Resistant Gallium Radioisotopes Gallium Isotopes Lutetium Heterocyclic Compounds, 1-Ring Machine Learning Aged Radiomics Biomarkers, Tumor Male Middle Aged Kidney Positron Emission Tomography Computed Tomography Humans
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