Nuclear Medicine

Cascaded Deep Learning enables multimodal brain PET spatial normalization and quantification for Alzheimer's disease.

Semi-quantitative positron emission tomography (PET) analysis, particularly Centiloid and CenTauRz scaling, is essential for Alzheimer's disease (AD) research and diagnosis. However, standard quantification workflows often depend on structural MRI for spatial normalization (SN) or rely on computationally intensive software, limiting clinical accessibility. In this retrospective, multi-center study...

Virtual photon-counting micro-CT platform for simulation of head and neck cancer imaging in mice.

OBJECTIVE: Our goal was to develop a simulation platform for photon-counting CT (PCCT) imaging in mouse models of head and neck squamous cell carcinoma (HNSCC). APPROACH: High-resolution vasculature from an energy-integrating detector micro-CT scan of a barium-enhanced mouse was transferred to the mouse whole-body (MOBY) digital phantom using affine warps. To generate tumors with contrast agent di...

Development of LRRC15-binding disulfide-constrained peptides for PET imaging of cancer-associated fibroblasts.

Leucine-rich-repeat-containing protein 15 (LRRC15) is selectively expressed on cancer-associated fibroblasts (CAFs) and constitutes a promising biomar...

Optimizing acquisition time and injected dose in 18F-FDG PET/CT imaging using deep learning: enhancing image protocol efficiency and safety.

BACKGROUND: This study aims to evaluate the effectiveness of deep learning algorithms in simulating standard acquisition time images from shortened ac...

Deep learning models built from PSMA PET of the primary tumor can predict synchronous and metachronous prostate cancer metastases.

OBJECTIVE: The objective was to develop prognostic models that included convolutional neural networks (CNN) derived from 18F-DCFPyL (PSMA) PET imaging...

Automated FDG uptake/PET-CT fused scan diagnosis of various lymph node tumors using object detection AI techniques.

Lymph nodes (LN) constitute a vital component of the lymphatic system, serving a pivotal role in immune functioning and maintaining fluid balance in t...

Profiling cognition and brain metabolism in amyotrophic lateral sclerosis and frontotemporal dementia.

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are described as a disease continuum, given their shared clinical, genetic and p...

Synthesis of Amyloid Images Using a Generative Adversarial Network from 2-Dimensional 18F-FDG Images and Evaluation for Clinical Use.

The use of amyloid PET to assess patient suitability of disease-modifying drugs for Alzheimer disease is increasing. This study aimed to synthesize am...

The impact of scan time on dynamic [Formula: see text]-FAPI-04 total-body PET parametric imaging generated by deep learning models.

PURPOSE: To date, some studies have employed deep learning techniques to directly generate dynamic positron emission tomography (PET) parametric image...

GPDM: generation-prior diffusion model for accelerated direct attenuation and scatter correction of whole-body 18F-FDG PET.

Accurate attenuation and scatter correction is essential in positron emission tomography (PET) for reliable visual interpretation and quantitative ana...

At the Decision Point Before Scintigraphy: AI-Echo in Suspected ATTR Cardiac Amyloidosis.

Mechanistic Insights into PET-MPs-Aggravated Ischemic Stroke via Integrated Computational-Experimental Approaches.

Microplastics, especially the environmentally pervasive polyethylene terephthalate microplastics (PET-MPs), are important environmental pollutants, an...

Assessing Image Quality and Diagnostic Performance of Quadruple-Low Coronary CT Angiography with Deep Learning in High-BMI Patients.

RATIONALE AND OBJECTIVES: To examine the feasibility of a quadruple-low protocol in coronary computed tomography angiography (CCTA) assisted by the de...

MSML-DenseXmer: harnessing vision transformers through integration with novel dense networks for medical image fusion.

The integration of multiple modalities in medical imaging allows a thorough representation of structural and functional details, resulting in improved...

Fully automatic left ventricle segmentation in [Formula: see text]Rb PET/CT Using a semi-supervised nnU-net.

BACKGROUND: Quantification of myocardial blood flow (MBF) with [Formula: see text]Rb PET/CT requires accurate delineation of the left ventricle (LV). ...

MMTC-Net: Multimodal Temporal Cervical Network for HSIL+ Recognition in Precancer Screening.

Cervical precancer screening is essential for reducing disease-related mortality. In colposcopic practice, clinicians jointly assess dynamic acetic-ac...

Beyond target lesions: Prognostic value of longitudinal AI-derived whole-body [1⁸F]FDG PET/CT metrics in metastatic melanoma.

PURPOSE: To investigate the prognostic value of an artificial intelligence (AI)-based semi-automated tool for longitudinal whole-body quantification o...

Leveraging the non-contrast CT component of PET/CT: an AI-driven delta-radiomics approach to monitor treatment response in metastatic breast cancer.

PURPOSE: 18 F-FDG PET/CT is the standard modality for monitoring treatment response in metastatic breast cancer. This study aims to evaluate the predi...

Unsupervised anomaly detection for longitudinal comparison in whole-body PET/CT images.

PURPOSE: This study investigates the utility of unsupervised anomaly detection for longitudinal comparison of whole-body 18F-fluorodeoxyglucose (FDG)-...

An interpretable 1⁸F-PSMA PET/CT-MRI model for optimizing prostate biopsy decisions.

PURPOSE: Distinguishing indolent from clinically significant prostate cancer (csPCa) in biopsy-naïve men remains a diagnostic challenge, often leading...