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Journal of Nuclear Medicine : Official... Apr 2021
Topics: Fluorodeoxyglucose F18; Magnetic Resonance Imaging; Positron Emission Tomography Computed Tomography; Tomography, X-Ray Computed
PubMed: 33037093
DOI: 10.2967/jnumed.120.256453 -
Journal of Nuclear Medicine : Official... Dec 2023We evaluated whether the artificial intelligence chatbot ChatGPT can adequately answer patient questions related to [F]FDG PET/CT in common clinical indications before...
We evaluated whether the artificial intelligence chatbot ChatGPT can adequately answer patient questions related to [F]FDG PET/CT in common clinical indications before and after scanning. Thirteen questions regarding [F]FDG PET/CT were submitted to ChatGPT. ChatGPT was also asked to explain 6 PET/CT reports (lung cancer, Hodgkin lymphoma) and answer 6 follow-up questions (e.g., on tumor stage or recommended treatment). To be rated "useful" or "appropriate," a response had to be adequate by the standards of the nuclear medicine staff. Inconsistency was assessed by regenerating responses. Responses were rated "appropriate" for 92% of 25 tasks and "useful" for 96%. Considerable inconsistencies were found between regenerated responses for 16% of tasks. Responses to 83% of sensitive questions (e.g., staging/treatment options) were rated "empathetic." ChatGPT might adequately substitute for advice given to patients by nuclear medicine staff in the investigated settings. Improving the consistency of ChatGPT would further increase reliability.
Topics: Humans; Positron Emission Tomography Computed Tomography; Fluorodeoxyglucose F18; Radiopharmaceuticals; Artificial Intelligence; Reproducibility of Results
PubMed: 37709536
DOI: 10.2967/jnumed.123.266114 -
BMC Cancer Aug 2022New-generation silicon-photomultiplier (SiPM)-based PET/CT systems exhibit an improved lesion detectability and image quality due to a higher detector sensitivity....
BACKGROUND
New-generation silicon-photomultiplier (SiPM)-based PET/CT systems exhibit an improved lesion detectability and image quality due to a higher detector sensitivity. Consequently, the acquisition time can be reduced while maintaining diagnostic quality. The aim of this study was to determine the lowest F-FDG PET acquisition time without loss of diagnostic information and to optimise image reconstruction parameters (image reconstruction algorithm, number of iterations, voxel size, Gaussian filter) by phantom imaging. Moreover, patient data are evaluated to confirm the phantom results.
METHODS
Three phantoms were used: a soft-tissue tumour phantom, a bone-lung tumour phantom, and a resolution phantom. Phantom conditions (lesion sizes from 6.5 mm to 28.8 mm in diameter, lesion activity concentration of 15 kBq/mL, and signal-to-background ratio of 5:1) were derived from patient data. PET data were acquired on an SiPM-based Biograph Vision PET/CT system for 10 min in list-mode format and resampled into time frames from 30 to 300 s in 30-s increments to simulate different acquisition times. Different image reconstructions with varying iterations, voxel sizes, and Gaussian filters were probed. Contrast-to-noise-ratio (CNR), maximum, and peak signal were evaluated using the 10-min acquisition time image as reference. A threshold CNR value ≥ 5 and a maximum (peak) deviation of ± 20% were considered acceptable. 20 patient data sets were evaluated regarding lesion quantification as well as agreement and correlation between reduced and full acquisition time standard uptake values (assessed by Pearson correlation coefficient, intraclass correlation coefficient, Bland-Altman analyses, and Krippendorff's alpha).
RESULTS
An acquisition time of 60 s per bed position yielded acceptable detectability and quantification results for clinically relevant phantom lesions ≥ 9.7 mm in diameter using OSEM-TOF or OSEM-TOF+PSF image reconstruction, a 4-mm Gaussian filter, and a 1.65 × 1.65 x 2.00-mm or 3.30 × 3.30 x 3.00-mm voxel size. Correlation and agreement of patient lesion quantification between full and reduced acquisition times were excellent.
CONCLUSION
A threefold reduction in acquisition time is possible. Patients might benefit from more comfortable examinations or reduced radiation exposure, if instead of the acquisition time the applied activity is reduced.
Topics: Fluorodeoxyglucose F18; Humans; Image Processing, Computer-Assisted; Phantoms, Imaging; Positron Emission Tomography Computed Tomography; Positron-Emission Tomography
PubMed: 35978274
DOI: 10.1186/s12885-022-09993-4 -
Medicina (Kaunas, Lithuania) May 2021: Primary gastric diffuse large-B cell lymphoma (DLBCL) is an aggressive lymphoma subtype with high F-FDG avidity but unclear criteria for 2-[F]-FDG PET/CT in the...
: Primary gastric diffuse large-B cell lymphoma (DLBCL) is an aggressive lymphoma subtype with high F-FDG avidity but unclear criteria for 2-[F]-FDG PET/CT in the evaluation of treatment response and prognostication. Our aim was to investigate whether the pretreatment 2-[F]-FDG PET/CT variables may predict treatment response (at end of first-line therapy) and prognosis in primary gastric DLBCL. : we included 57 patients with a diagnosis of primary gastric DLBCL and a baseline 2-[F]-FDG PET/CT and an end of treatment PET/CT after 6 cycles of R-CHOP chemotherapy. We analyzed PET images qualitatively and semi-quantitatively by deriving the maximum standardized uptake value body weight (SUVbw), the maximum standardized uptake value lean body mass (SUVlbm), the maximum standardized uptake value body surface area (SUVbsa), lesion to liver SUVmax ratio (L-L SUV R), lesion to blood-pool SUVmax ratio (L-BP SUV R), metabolic tumor volume and total lesion glycolysis of gastric lesion (gMTV and gTLG), and total MTV (tMTV) and TLG. Survival curves were plotted according to the Kaplan-Meier analysis. at a median follow up of 80 months, the median PFS and OS were 69 and 80 months. Baseline gMTV, gTLG, tMTV, and TLG were significantly higher in patients with incomplete response (partial response and progression) compared to complete response group. tMTV and TLG were confirmed to be independent prognostic factors both for PFS ( = 0.023 and = 0.038) and OS ( = 0.038 and = 0.026); instead, the other metabolic parameters were not related to outcome survival. : high tMTV and TLG were significantly correlated with shorter survival (PFS and OS) and may predict incomplete response after therapy.
Topics: Fluorodeoxyglucose F18; Humans; Positron Emission Tomography Computed Tomography; Positron-Emission Tomography; Prognosis; Retrospective Studies
PubMed: 34069203
DOI: 10.3390/medicina57050498 -
Molecular Imaging and Biology Oct 2021To investigate the possibility of reducing the injected activity for whole-body [18F]FDG-PET/CT studies of paediatric oncology patients and to assess the usefulness of...
PURPOSE
To investigate the possibility of reducing the injected activity for whole-body [18F]FDG-PET/CT studies of paediatric oncology patients and to assess the usefulness of time-of-flight (TOF) acquisition on PET image quality at reduced count levels.
PROCEDURES
Twenty-nine paediatric oncology patients (12F/17M, 3-18 years old (median age 13y), weight 45±20 kg, BMI 19±4 kg/m), who underwent routine whole-body PET/CT examinations on a Siemens Biograph mCT TrueV system with TOF capability (555ps) were included in this study. The mean injected activity was 156 ± 45 MBq (3.8 ± 0.8 kg/MBq) and scaled to patient weight. The raw data was collected in listmode (LM) format and pre-processed to simulate reduced levels of [18F]FDG activity (75, 50, 35, 20 and 10% of the original counts) by randomly removing events from the original LM data. All data were reconstructed using the vendor-specific e7-tools with standard OSEM only, with OSEM plus resolution recovery (PSF). The reconstructions were repeated with added TOF (TOF) and PSF+TOF. The benefit of TOF together with the reduced count levels was evaluated by calculating the gains in signal-to-noise ratio (SNR) in the liver and contrast-to-noise ratio (CNR) in all PET-positive lesions before and after TOF employed at every simulated reduced count level. Finally, the PSF+TOF images at 50, 75 and 100% of counts were evaluated clinically on a 5-point scale by three nuclear medicine physicians.
RESULTS
The visual inspection of the reconstructed images did not reveal significant differences in image quality between 75 and 100% count levels for PSF+TOF. The improvements in SNR and CNR were the greatest for TOF reconstruction and PSF combined. Both SNR and CNR gains did increase linearly with the patients BMI for both OSEM only and PSF reconstruction. These benefits were observed until reducing the counts to 50 and 35% for SNR and CNR, respectively.
CONCLUSIONS
The benefit of using TOF was noticeable when using 50% or greater of the counts when evaluating the CNR and SNR. For [18F]FDG-PET/CT, whole-body paediatric imaging the injected activity can be reduced to 75% of the original dose without compromising PET image quality.
Topics: Adolescent; Child, Preschool; Female; Fluorodeoxyglucose F18; Humans; Image Processing, Computer-Assisted; Male; Neoplasms; Positron Emission Tomography Computed Tomography; Radiation Dosage; Signal-To-Noise Ratio
PubMed: 33846898
DOI: 10.1007/s11307-021-01601-4 -
Nihon Hoshasen Gijutsu Gakkai Zasshi 2023
Topics: Positron-Emission Tomography; Fluorodeoxyglucose F18
PubMed: 36682784
DOI: 10.6009/jjrt.2023-2144 -
Brain : a Journal of Neurology Mar 2024Given the prevalence of dementia and the development of pathology-specific disease-modifying therapies, high-value biomarker strategies to inform medical decision-making...
Given the prevalence of dementia and the development of pathology-specific disease-modifying therapies, high-value biomarker strategies to inform medical decision-making are critical. In vivo tau-PET is an ideal target as a biomarker for Alzheimer's disease diagnosis and treatment outcome measure. However, tau-PET is not currently widely accessible to patients compared to other neuroimaging methods. In this study, we present a convolutional neural network (CNN) model that imputes tau-PET images from more widely available cross-modality imaging inputs. Participants (n = 1192) with brain T1-weighted MRI (T1w), fluorodeoxyglucose (FDG)-PET, amyloid-PET and tau-PET were included. We found that a CNN model can impute tau-PET images with high accuracy, the highest being for the FDG-based model followed by amyloid-PET and T1w. In testing implications of artificial intelligence-imputed tau-PET, only the FDG-based model showed a significant improvement of performance in classifying tau positivity and diagnostic groups compared to the original input data, suggesting that application of the model could enhance the utility of the metabolic images. The interpretability experiment revealed that the FDG- and T1w-based models utilized the non-local input from physically remote regions of interest to estimate the tau-PET, but this was not the case for the Pittsburgh compound B-based model. This implies that the model can learn the distinct biological relationship between FDG-PET, T1w and tau-PET from the relationship between amyloid-PET and tau-PET. Our study suggests that extending neuroimaging's use with artificial intelligence to predict protein specific pathologies has great potential to inform emerging care models.
Topics: Humans; Amyloidogenic Proteins; Artificial Intelligence; Biomarkers; Deep Learning; Fluorodeoxyglucose F18; Neuroimaging; Tauopathies
PubMed: 37804318
DOI: 10.1093/brain/awad346 -
BMJ Open Diabetes Research & Care Jun 2021Saliva collection is a non-invasive test and is convenient. 1,5-anhydroglucitol (1,5-AG) is a new indicator reflecting short-term blood glucose levels. This study aimed...
INTRODUCTION
Saliva collection is a non-invasive test and is convenient. 1,5-anhydroglucitol (1,5-AG) is a new indicator reflecting short-term blood glucose levels. This study aimed to explore the relationship between saliva 1,5-AG and insulin secretion function and insulin sensitivity.
RESEARCH DESIGN AND METHODS
Adult patients with type 2 diabetes who were hospitalized were enrolled. Based on blood glucose and C-peptide, homeostasis model assessment 2 for β cell secretion function, C-peptidogenic index (CGI), △2-hour C-peptide (2hCP)/△2-hour postprandial glucose (2hPG), ratio of 0-30 min area under the curve for C-peptide and area under the curve for glucose (AUC/AUC), and AUC/AUC were calculated to evaluate insulin secretion function, while indicators such as homeostasis model assessment 2 for insulin resistance were used to assess insulin sensitivity.
RESULTS
We included 284 subjects (178 men and 106 women) with type 2 diabetes aged 20-70 years. The saliva 1,5-AG level was 0.133 (0.089-0.204) µg/mL. Spearman's correlation analysis revealed a significantly negative correlation between saliva 1,5-AG and 0, 30, and 120 min blood glucose, glycated hemoglobin A, and glycated albumin (all p<0.05), and a significantly positive association between saliva 1,5-AG and CGI (=0.171, p=0.004) and AUC /AUC (=0.174, p=0.003). The above correlations still existed after adjusting for age, sex, body mass index, and diabetes duration. In multiple linear regression, saliva 1,5-AG was an independent factor of CGI (standardized =0.135, p=0.015) and AUC /AUC (standardized =0.110, p=0.020).
CONCLUSIONS
Saliva 1,5-AG was related to CGI and AUC/AUC in patients with type 2 diabetes.
TRIAL REGISTRATION NUMBER
ChiCTR-SOC-17011356.
Topics: Adult; China; Deoxyglucose; Diabetes Mellitus, Type 2; Female; Glucose Tolerance Test; Humans; Insulin; Insulin Secretion; Male; Saliva
PubMed: 34167955
DOI: 10.1136/bmjdrc-2021-002199 -
Cancer Radiotherapie : Journal de La... Sep 2023Over the last decades, the refinement of radiation therapy techniques has been associated with an increasing interest for individualized radiation therapy with the aim... (Review)
Review
Over the last decades, the refinement of radiation therapy techniques has been associated with an increasing interest for individualized radiation therapy with the aim of increasing or maintaining tumor control and reducing radiation toxicity. Developments in artificial intelligence (AI), particularly machine learning and deep learning, in imaging sciences, including nuclear medecine, have led to significant enthusiasm for the concept of "rapid learning health system". AI combined with radiomics applied to (F)-fluorodeoxyglucose positron emission tomography/computed tomography ([F]-FDG PET/CT) offers a unique opportunity for the development of predictive models that can help stratify each patient's risk and guide treatment decisions for optimal outcomes and quality of life of patients treated with radiation therapy. Here we present an overview of the current contribution of AI and radiomics-based machine learning models applied to (F)-FDG PET/CT in the management of cancer treated by radiation therapy.
Topics: Humans; Positron Emission Tomography Computed Tomography; Fluorodeoxyglucose F18; Artificial Intelligence; Quality of Life; Radiation Oncology
PubMed: 37481344
DOI: 10.1016/j.canrad.2023.06.001 -
Journal of Nuclear Cardiology :... Oct 2020
Topics: Fatty Acids; Fluorodeoxyglucose F18; Glucose; Humans; Liver; Non-alcoholic Fatty Liver Disease; Positron-Emission Tomography
PubMed: 30547298
DOI: 10.1007/s12350-018-01532-8