Nuclear Medicine

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 by the short acquisition time, which results in significant image noise and poor lesion detectability. Enhancing image quality under such conditions remains a technical challenge. PURPOSE: To improve the image quality of 15-s breath-hold PET scans, w...

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 physicochemical, physiological, and formulation-related barriers. Traditional models for evaluating absorption exhibit limitations in physiological relevance and predictive accuracy. This review critically examines evolving methodologies for oral drug a...

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...

Evaluation of radiomics-based machine learning models for detection of cervical lymph node metastasis from oral cancer on PET images.

PURPOSE: In this study, we hypothesized that radiomics analysis applied to pre-treatment PET images would be more accurate in the detection of lymph n...

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...

Early diagnosis of Alzheimer's Disease: Graph theoretical analysis of cerebellar network features based on 18F-AV45 PET.

Pathological and neuroimaging changes in the cerebellum of Alzheimer's disease (AD) patients have been well documented. However, the changes in cerebe...

Enhancing uncertainty assessment in dynamic PET imaging with residual permutation and clustering.

Quantitative positron emission tomography (PET) is widely used for disease diagnosis and therapy monitoring, yet the reliability of kinetic parameters...

Deep learning cascade networks for segmentation of fluorine-18 sodium fluoride positron emission tomography scans of equine metacarpo- and metatarsophalangeal joints outperform atlas-based method.

OBJECTIVE: To create a labeled dataset and evaluate a convolutional neural network (CNN) for segmentation of fluorine-18 sodium fluoride PET scans of ...

Clinical validation of perfusion imaging with pulmonary function test data using Voronoi-based discretization.

Accurate lung function assessment is essential for diagnosing and managing diseases like COPD, pulmonary emboli, and lung cancer. Single-photon emissi...

Computational analysis of the Lengyel-Epstein system for the chlorite-iodide-malonic acid reaction using radial basis function neural network.

The chlorine dioxide-iodine-malonic acid (CDIMA) reaction governed by the Lengyel-Epstein equations is a canonical reaction-diffusion system known for...