Nuclear Medicine

On the utility of ChatGPT in conducting a literature review on deep learning for dopamine transporter SPECT with [¹²³I]ioflupane.

AIM: This study evaluated ChatGPT (GPT-5.2) for drafting a review paper on deep learning in dopamine transporter (DAT)-SPECT with [¹²³I]ioflupane. METHODS: The review workflow consisted of 3 steps: (i) literature search, (ii) generation of structured summaries with 24 predefined fields for each publication, and (iii) drafting a review paper based on the structured summaries across all publications...

Multimodal PET/CT-based PD-L1 status prediction in lung cancer via semi-supervised and unsupervised deep learning.

Deep learning (DL) techniques have been applied in lung cancer screening, assessing drug effectiveness, and enhancing prognosis prediction. Within this context, the combination of 18FDG PET/CT images with DL has demonstrated promising results, particularly in predicting programmed death ligand-1 (PD-L1) expression in lung cancer, improving overall prediction accuracy and offering a viable non-inva...

Outer nuclear layer thinning as an in vivo biomarker for discriminating probable FTLD-tau from probable FTLD-TDP with PET-supported subtyping.

BACKGROUND AND OBJECTIVES: Outer nuclear layer (ONL) thinning has been identified in frontotemporal lobar degeneration (FTLD); however, its utility fo...

[Current status and progress of prognostic evaluation in marginal zone lymphoma].

Marginal zone lymphoma (MZL) is an indolent B-cell non-Hodgkin lymphoma with marked heterogeneity. Currently, histological subtype, clinical stage, bi...

Unveiling the sensing mechanism of a Nile Red-naphthoquinone H₂S fluorescent probe: theoretical calculation and deep learning prediction.

Hydrogen sulfide (H₂S) is a vital endogenous gasotransmitter implicated in numerous physiological and pathological processes; thus, its precise detect...

Performance of the Techcyte AI-based image analysis system for coproparasitological diagnosis in clinical stool specimens: a retrospective evaluation study.

UNLABELLED: Coproparasitological stool analysis based on microscopic examination is the reference diagnostic technique routinely performed in clinical...

Denoising of ultra-low-dose 15O positron emission tomography images using deep image prior with anatomical information extracted through magnetic resonance segmentation.

PURPOSE: Recent deep-learning methods can recover standard-dose PET images from low-dose images. However, these methods require a large amount of data...

Accelerating the discovery of industrial PET-degrading enzymes: Evolving paradigms from bioprospecting to computational discovery.

Polyethylene terephthalate (PET) waste remains a major environmental and resource challenge, and enzymatic depolymerization offers a promising route f...

Evaluation of PET/CT Artificial Intelligence Image Reconstructions VS Harmonized Clinical Reconstruction.

BACKGROUND: This study focuses on evaluating how SubtlePET™, an artificial intelligence (AI)-based image enhancement algorithm, produced PET/CT images...

Standardizing PSMA PET/CT reporting in prostate cancer: from structured frameworks to AI-assisted interpretation.

PSMA PET/CT is increasingly used for prostate cancer staging, restaging, treatment selection, and therapy response assessment. In parallel, several in...

Automatic metabolic breast cancer staging using [¹⁸F]FDG PET/CT: comparison with nuclear medicine physician-based and clinical staging.

PURPOSE: This study aimed to evaluate a deep-learning (DL)-based framework to automatically perform breast cancer (BC) metabolic staging on [¹⁸F]FDG P...

RDoC-informed explainable AI as a paradigm for multilevel Alzheimer's disease diagnosis and progression prediction: a systematic review.

Explainable Artificial Intelligence (XAI) is gaining popularity in early diagnosis and monitoring of dementia. Herein, we recommend the incorporation ...

Denoising of 4D dynamic PET images using spatiotemporal regularization with integrated temporal restoration (SPRINTER).

PURPOSE: High-quality 4D dynamic PET imaging is often compromised by noise, especially in low-count frames, which limits clinical utility and quantita...

Risk stratification for reoperation outcomes in recurrent or persistent papillary thyroid carcinoma: development and validation of a machine learning model.

BACKGROUNDS: Reoperation is a key therapeutic strategy for recurrent or persistent papillary thyroid carcinoma (PTC), but its outcomes remain highly h...

Radiomics-enhanced 18F-AV45 PET/MRI for integrative assessment and centiloid estimation of amyloid-β burden in Alzheimer's disease.

OBJECTIVE: Reliable assessment of cerebral amyloid-β (Aβ) deposition is essential for the diagnosis and management of Alzheimer's disease (AD). This s...

Evaluation of Baseline and Interim-Therapy PET Features for Prognostication in High-Risk Pediatric Hodgkin Lymphoma: A Retrospective Analysis of the AHOD1331 Trial.

This study aimed to evaluate the prognostic value of conventional and advanced PET metrics for predicting progression-free survival in high-risk pedia...

Revisiting Perfusion in the Forgotten Right Ventricle: Artificial Intelligence-Enhanced Quantification on PET/CT.

Increased right ventricular (RV) radiotracer uptake on perfusion imaging has been recognized as a marker of increased cardiovascular risk. However, th...

End-to-End PET/CT Interpretation and Quantification with an LLM-Orchestrated AI Agent: A Real-World Pilot Study.

Although deep learning models have improved individual PET analysis, image processing, and quantification tasks, end-to-end automation from raw DICOM ...

Deep integration of clinical metadata with [18F]FDG PET/CT imaging for histological subtyping in non-small cell lung cancer: a multi-center study.

PURPOSE: To develop and validate a multimodal deep learning framework that integrates clinical metadata with [18F]FDG PET/CT imaging to resolve overla...

Contrast injection protocols used in oncological CT and opportunities for practice optimisation.

INTRODUCTION: Contrast-enhanced CT is central to oncological imaging, yet no official guidelines exist for contrast injection protocols. As a result, ...