Nuclear Medicine

Acanthamoeba Keratitis: Recent Advances in Diagnosis and Management.

PURPOSE: To review recent advances in the diagnosis and management of acanthamoeba keratitis (AK), emphasizing clinically relevant developments from the past 5 years. METHODS: A scoping review of PubMed and ClinicalTrials.gov was conducted for studies published between July 2020 and December 2025 using the terms "acanthamoeba AND (diag* OR test* OR treatment)." Clinical studies and studies of huma...

Scan-wise generalized PET denoising with contrastive adversarial learning.

Objective.Deep learning has significantly advanced low-count positron emission tomography (PET) denoising. However, models trained on specific distributions often yield biased outputs when applied to scans with different activity distributions caused by anatomical and physiological variations (distribution shifts). Existing methods fail to generalize well across these scan-wise variations. Our goa...

Beyond 0.29±0.02 mm intrinsic spatial resolution based on monolithic crystals using convolutional neural network: a simulation study.

High spatial resolution is important for a Positron Emission Tomography (PET) system. Monolithic crystal based detectors are promising to deliver ...

The impact of a novel deep learning reconstruction algorithm on image quality in ultralow-dose CT: a quantitative phantom study.

OBJECTIVE: The aim of this study is to evaluate the performance of a novel deep learning image reconstruction (DLIR) algorithm in noise reduction, con...

A tissue-informed deep learning-based method for positron range correction in preclinical [Formula: see text]Ga PET imaging.

PURPOSE: Positron range (PR) limits spatial resolution and quantitative accuracy in PET imaging, particularly for high-energy positron-emitting radion...

Integrated CT-PET radiogenomics and graph-based multi-task learning for preoperative prediction of key glioma molecular markers.

BACKGROUND: The clinical management of glioma is increasingly dependent on the tumor's molecular profile, particularly the mutation status of Isocitra...

[18F] PSMA-3Q PET/CT radiomics at 45% SUVmax threshold: predicting post-surgical ISUP grade ≥ 4 and extraprostatic extension for noninvasive stratification in prostate cancer management.

OBJECTIVE: To systematically evaluate radiomic features extracted from [18F] PSMA-3Q PET/CT using 40%, 45%, and 50% SUVmax thresholds for their abilit...

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) ...

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 carcinom...

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.

Deep learning reconstruction dual-energy computed tomography for gastrointestinal system tumors: low-kiloelectron volt imaging vs routine imaging.

AIM: To qualitatively and quantitatively compare dual-energy computed tomography (DECT)-derived 55 keV virtual monochromatic images (VMIs) using deep ...

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...