Nuclear Medicine

Application of Total-Body PET in Pediatric Patients.

This article highlights the advancements in total-body PET (TB PET) imaging, emphasizing its benefits for pediatric patients, including low-dose protocols, rapid acquisition, and dynamic imaging capabilities. It discusses technological innovations like silicon photomultiplier detectors, artificial intelligence-enhanced reconstruction, and ultralong axial fields of view, which improve image quality...

Artificial intelligence for TNM staging in NSCLC: a critical appraisal of segmentation utility in [1⁸F]FDG PET/CT.

PURPOSE: This study aims to investigate whether a diagnostic AI model can effectively support lesion detection and staging in non-small cell lung cancer (NSCLC) [1⁸F]FDG PET/CT studies, focusing on the distinction between technical segmentation accuracy and clinically meaningful performance. METHODS: In this retrospective single-centre study, [1⁸F]FDG PET/CT scans from 306 treatment-naïve NSCLC pa...

Prognostic value of a combined model integrating clinical and PET radiomics parameters in metastatic melanoma: A dual-center retrospective study.

OBJECTIVES: To develop and evaluate the predictive efficacy of a combined model incorporating clinical parameters and PET-based radiomics signature (R...

Low-count whole-body PET denoising with deep learning in a multicenter, multi-tracer and externally validated study.

BACKGROUND: Positron Emission Tomography (PET) is a powerful diagnostic tool, but its availability, high cost and radiation burden limit its accessibi...

Dynamic frame-by-frame motion correction for 18F-flurpiridaz PET-MPI using convolution neural network.

PURPOSE: Precise quantification of myocardial blood flow (MBF) and flow reserve (MFR) in 18F-flurpiridaz PET significantly relies on motion correction...

An integrated machine learning framework for predicting anthropogenic and natural iodine isotopes in the South China Sea with uncertainty quantification.

Anthropogenic Iodine-129 (129I) is a critical long-lived radionuclide for tracing ocean circulation and environmental contamination. However, its meas...

Accuracy of Photon Dose Calculation on Photon-Counting Computed Tomography-A Comparison Study Based on Virtual Monoenergetic and Electron Density (Rho) Images for Pancreatic Cases.

PURPOSE: Photon-counting computed tomography (PCCT) offers versatile anatomic information because of better energy discrimination and higher spatial r...

Total-body [18F]FDG-PET/CT imaging of healthy volunteers with minimal effective dose.

PURPOSE: High-sensitivity, total-body (TB) positron emission tomography (PET) and computed tomography (CT) imaging systems enable substantial reductio...

Deep learning-based obstructive coronary artery disease prediction from myocardial perfusion SPECT.

PURPOSE: We aim to apply the deep learning (DL) technique to predict the gold-standard invasive coronary angiography (ICA) for coronary artery disease...

Resolution and quality enhancement of SPECT cerebral blood flow images using Pix2pix deep learning.

BACKGROUND: Cerebral blood flow (CBF) imaging can be performed using SPECT with 123I-IMP; however, its spatial resolution and image quality are inferi...

18F-FDG PET-based ensemble deep learning model for the prediction of lymphovascular invasion in colorectal cancer patients.

OBJECTIVE: The aim of this study was to investigate the diagnostic performance of the 2.5-dimensional (2.5D) ensemble deep learning (DL) model based o...

Mapping systemic inter-organ metabolic networks across glycemic continuum using whole-body [18F]FDG PET/CT and machine learning.

PURPOSE: Glucose homeostasis relies on coordinated interactions among multiple organs, and its disruption relates to diabetes development. This study ...

AI-Quantified ¹¹C-MET PET/CT bone marrow metabolic activity for prognostic assessment in newly diagnosed multiple myeloma.

PURPOSE: To develop and validate an AI method for automated quantification of whole-skeleton bone marrow (BM) metabolic activity using Carbon 11 (11C)...

Preventing exotic pet beetle invasion with an improved lightweight and efficient pest detection model deployed on mobile devices.

BACKGROUND: The illegal smuggling of exotic pet beetles presents a growing threat to global ecosystems. Customs authorities play a critical role in pr...

NHOC/NHOP as novel biomarkers for predicting lymph node metastasis in NSCLC using PET/CT radiomics and machine learning: a two-center retrospective study.

PURPOSE: NHOC and NHOP, defined as the normalized distances from peak uptake to tumour centroid and perimeter, are novel PET/CT metrics of tumour aggr...

coPERCIST: AI-assisted PET-CT response assessment.

PURPOSE: The PET Response Criteria in Solid Tumours (PERCIST) 1.0 provides a standardized framework for evaluating treatment response using [18F]fluor...

Fully automated volumetric assessment of tumor burden using artificial intelligence on 68Ga-PSMA-11 PET predicts survival after 177Lu-PSMA therapy in metastatic Castration-resistant prostate cancer.

PURPOSE: Despite the rapid development of artificial intelligence (AI)-powered automated segmentation tools for PET/CT imaging, their prognostic value...

Clinical evaluation of deep learning-based CT-free PET reconstruction image: a dual-center study.

PURPOSE: Efforts to reduce the radiation burden of PET/CT have driven the increasing development of AI-based CT-less PET imaging techniques. However, ...

Brain metabolic imaging with 18 F-PET-CT and machine-learning clustering analysis reveal divergent metabolic phenotypes in patients with amyotrophic lateral sclerosis.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by significant clinicopathologic heterogeneity. Th...

Validation of novel low-dose CT methods for quantifying bone marrow in the appendicular skeleton of patients with multiple myeloma: initial results from the [18F]FDG PET/CT sub-study of the Phase 3 GMMG-HD7 Trial.

PURPOSE: The clinical significance of medullary abnormalities in the appendicular skeleton detected by computed tomography (CT) in patients with multi...