Nuclear Medicine

18F-FDG PET/CT and receptor-positive circulating tumor cells-based machine learning model for predicting poorly differentiated lung adenocarcinoma.

INTRODUCTION: This study aimed to develop and validate a machine learning model that integrates radiomic features from 2-[18F]fluoro-2-deoxy-D-glucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) with folate receptor-positive circulating tumor cells (FR+-CTCs) for the preoperative prediction of tumor differentiation grade, as defined by the International Association for the ...

Vessel-specific perivascular fat attenuation index derived from AI-CCTA and its association with impaired coronary flow reserve in patients with INOCA.

OBJECTIVES: To investigate the association between artificial intelligence (AI)-derived coronary computed tomography angiography (CCTA) features and impaired coronary flow reserve (CFR) in patients with ischemia and non-obstructive coronary arteries (INOCA). METHODS: Retrospective analysis of 101 suspected coronary artery disease (CAD) patients with non-obstructive stenosis (<50%) on CCTA who unde...

Advances and challenges of PET imaging in bladder cancer-An update and future trends.

Molecular imaging with positron emission tomography (PET) is a powerful tool in the clinical management of bladder cancer, providing functional inform...

AutoPET Challenge on Fully Automated Lesion Segmentation in Oncologic PET/CT Imaging, Part 2: Domain Generalization.

This article reports the results of the second iteration of the autoPET challenge on automated lesion segmentation in whole-body PET/CT, held in conju...

Simultaneous synthesis of perfusion and ventilation images from CT using a dual-decoder residual attention network for lung disease diagnosis.

BACKGROUND: Deep learning algorithms can synthesize pulmonary functional images from CT images. However, previous studies have only been able to predi...

Filling of incomplete sinograms from sparse PET detector configurations using a residual U-Net.

BACKGROUND: Long axial field-of-view PET scanners are becoming increasingly available worldwide for clinical and research nuclear medicine examination...

Image quality restoration in 15-s breath-hold PET using a diffusion-based neural network.

BACKGROUND: Breath-hold PET imaging helps reduce respiratory motion artifacts in thoracoabdominal scans. However, its clinical application is limited ...

From permeability to prediction: evolving strategies for evaluating oral drug absorption.

Oral drug administration, preferred for patient compliance and convenience, encounters significant bioavailability challenges arising from complex phy...

Radiopharmaceuticals: Status, Regulatory Landscape and Future Perspective.

Radiopharmaceuticals are biologically active molecules labeled with radionuclides that have advanced the possibility of the nuclear medicine. They sup...

Attenuation correction of cardiac 82Rb pet using deep learning generated synthetic CT.

Ischemic heart disease remains a leading cause of mortality worldwide. Myocardial perfusion imaging (MPI) using Rubidium-82 (82Rb) positron emission t...

Environmental PET-microplastic exposure and risk of non-alcoholic fatty liver disease: An integrated computational toxicology and multi-omics study.

The escalating severity of global microplastic pollution has triggered significant public health concerns. Polyethylene terephthalate (PET), a ubiquit...

TASNet: A tri-modal attentive scale robust adaptive fusion framework for progressive mild cognitive impairment classification.

BACKGROUND: Accurate prediction of progressive Mild Cognitive Impairment (pMCI) versus stable MCI (sMCI) is crucial for early Alzheimer's disease (AD)...

Evaluation of GPT-5 for Esophageal Cancer Staging Using Fluorodeoxyglucose Positron Emission Tomography Maximum-Intensity Projection Images: Comparative Pilot Study.

BACKGROUND: Accurate esophageal cancer staging relies on 18F fluorodeoxyglucose positron emission tomography (18F FDG-PET), but its interpretation is ...

Deep learning-based attenuation and scatter correction in myocardial SPECT without using X-ray CT images.

Subregional limbic radiomics on FDG-PET provides accurate early detection of Alzheimer's disease.

BACKGROUND: To investigate the radiomics features of the hippocampus and the amygdala subregions in FDG-PET images that can best differentiate Mild Co...

Determinants of intracranial microcalcification assessed by 18F-sodium fluoride PET.

PURPOSE: Intracranial calcifications are commonly found in adults and may represent either benign or pathological lesions. Conventional imaging modali...

Lesion-level dual-tracer PET biomarkers predict prognosis in multiple myeloma treated with CXCR4-directed radiopharmaceutical therapy.

BACKGROUND: C-X-C motif chemokine receptor 4 (CXCR4)-directed radiopharmaceutical therapy (RPT) represents a promising option for hematologic malignan...

Artificial Intelligence for radiation dose reduction in computed tomography: a narrative synthesis of clinical evidence from 2020 to 2025.

Computed tomography (CT) is essential to modern clinical practice but contributes substantially to population radiation exposure, particularly in onco...

Clinical value of artificial intelligence in reducing PET image acquisition time: routine clinical validation using qualitative, quantitative, and radiomic analysis on a cohort of 282 patients undergoing [18F]FDG and [68Ga]Ga-PSMA-11 PET/CT.

BACKGROUND: Reducing acquisition time in PET/CT imaging can degrade image quality and may compromise both diagnostic reliability and the robustness of...

Nuclear medicine in predicting hepatocellular carcinoma response.

Immune checkpoint inhibitors and anti-angiogenic targeted therapies have improved outcomes in hepatocellular carcinoma (HCC), but responses remain het...