Nuclear Medicine

Single-photon emission computed tomography/computed tomography-based radiomics of bone metastases for predicting epidermal growth factor receptor mutation status and targeted therapy efficacy in non-small-cell lung cancer.

BACKGROUND: This study aimed to develop a single-photon emission computed tomography/computed tomography (SPECT/CT)-based radiomics model using bone metastases to predict epidermal growth factor receptor (EGFR) mutation status and the efficacy of targeted therapy in patients with non-small-cell lung cancer. METHODS: This retrospective study included 240 patients with non-small-cell lung cancer. Am...

Deep learning-based PET/CT mixture-of-experts model for relapse risk stratification in relapsed/refractory classical hodgkin lymphoma: a multicenter study.

BACKGROUND: Relapsed/refractory classical Hodgkin lymphoma (R/R cHL) remains clinically challenging due to substantial heterogeneity in relapse risk. Reliable, non-invasive tools for improved relapse risk stratification are urgently needed to guide individualized therapeutic strategies. METHODS: In this multicenter retrospective study, 161 patients with R/R cHL from five institutions were included...

An segformer-mix vision transformer-based GIST segmentation in fused CT-PET images.

Accurate segmentation of gastrointestinal stromal tumour (GIST) is always challenging task due to tissues intestines may have similar intensity values...

Tumor spread through air spaces in non-small-cell lung cancer: 18F-fluorodeoxyglucose PET-based tumoral and peritumoral radiomics analysis with machine learning.

OBJECTIVE: To investigate the utility of tumoral and peritumoral [18F]-fluorodeoxyglucose PET-based radiomics models for predicting tumor spread throu...

Deep Learning-Driven Discovery and Engineering of an Efficient PETase for Depolymerization and Detoxification of PET Microplastics Under Physiological Conditions.

Microplastics (MPs) accumulation in ecosystem and human organs poses urgent environmental and health risks, yet few enzymes efficiently degrade polyet...

Self-supervised multimodal swin UNETR for PET/CT segmentation of diffuse large B-cell lymphoma.

Accurate segmentation of diffuse large B-cell lymphoma (DLBCL) is critical for reliable PET/CT-based quantification and total metabolic tumor volume (...

Thyroid Year-in-Review 2025-2026: Precision Medicine and De-escalation in Contemporary Thyroidology.

The 'Thyroid: Year in Review', presented at the AACE 2026 annual meeting, synthesized practice-influencing peer-reviewed clinical research published b...

A Dual-Center, Interpretable Deep Learning-Radiomics Fusion Model for Distinguishing Nasopharyngeal Carcinoma from Nasopharyngeal Lymphoma Using FDG PET/CT.

RATIONALE AND OBJECTIVES: Accurate differentiation between Nasopharyngeal Carcinoma (NPC) and Nasopharyngeal Lymphoma (NPL) is critical for clinical m...

CT-based prediction of hematoma expansion and adverse outcomes after intracerebral hemorrhage: evidence appraisal, artificial intelligence translation, and GeroScience perspectives.

Spontaneous intracerebral hemorrhage (ICH) is a highly lethal and disabling form of stroke, in which hematoma expansion (HE) is a major and potentiall...

A Deep Learning Approach for Noise Suppression in Cardiac-gated SPECT Studies.

BACKGROUND: Cardiac-gated SPECT images are prone to elevated imaging noise in clinical acquisitions. This study investigates the use of a deep learnin...

PET/CT In paediatric lymphoma: Current role and advances.

Fluorine-18 fluorodeoxyglucose ([18F] FDG) PET/CT has become central to the management of paediatric lymphoma, providing critical information for stag...

Development and validation of an amyloid PET dementia of the Alzheimer's type (DAT) score.

BackgroundAlzheimer's disease (AD) can be debilitating if left untreated, but its progression may be altered through early detection.ObjectiveTo devel...

18F-Fluorodeoxyglucose-positron emission tomography/computed tomography in Lymphoma.

FDG-PET/CT is central to Lugano-based staging, Deauville-scored response assessment, and prognostication across Hodgkin and non-Hodgkin lymphoma subty...

Evaluating the age of rib fractures through 99mTc-MDP SPECT strategy based on a machine learning algorithm: a preliminary study.

Rib fractures are among the most common injuries in traffic accidents. Accurate evaluation of rib fracture age is important as it assists forensic exp...

Deep learning for CT-less attenuation correction synthesis in non-small cell lung cancer: A proof-of-concept evaluated for quantitative and physical characteristics.

To develop and rigorously validate a deep learning framework for CT-free positron emission tomography (PET) attenuation correction in non-small cell l...

The impact of data extraction percentage and deep learning-based reconstruction on image quality in gated PET/computed tomography.

BACKGROUND: Respiratory motion artifacts degrade PET/computed tomography (PET/CT) image quality. Data-driven gated (DDG) PET/CT addresses this issue b...

Sex-Related Performance Disparities in Convolutional Neural Networks for Imaging-Based Assessment of Coronary Atherosclerosis and Ischemic Heart Disease: A Systematic Review.

Sex-related disparities persist in the diagnosis and management of ischemic heart disease (IHD), raising concern that convolutional neural networks (C...

Multimodal artificial intelligence for prostate cancer imaging: workflow-relevant fusion of mpMRI, PSMA PET, ultrasound, and clinical data for diagnosis, local staging, and treatment personalization.

BACKGROUND: Prostate cancer imaging is inherently multimodal, yet many AI tools remain single-modality and therefore misaligned with real-world abdomi...

Unsupervised waveform reshaping for enhanced time-of-flight precision in PET detectors.

Objective.To enhance the image quality in time-of-flight positron emission tomography (TOF-PET) reconstruction by improving the accuracy of TOF estima...

Programmable nanoprobes for molecular imaging of cancer: toward adaptive and context-responsive diagnostics.

Molecular imaging has emerged as a powerful tool for early cancer detection and real-time visualization of disease progression; however, conventional ...