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Positron Emission Tomography Computed Tomography

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Artificial Intelligence for Response Evaluation With PET/CT.

Seminars in nuclear medicine
Positron emission tomography (PET)/computed tomography (CT) are nuclear diagnostic imaging modalities that are routinely deployed for cancer staging and monitoring. They hold the advantage of detecting disease related biochemical and physiologic abno...

Artificial Intelligence for Optimization and Interpretation of PET/CT and PET/MR Images.

Seminars in nuclear medicine
Artificial intelligence (AI) has recently attracted much attention for its potential use in healthcare applications. The use of AI to improve and extract more information out of medical images, given their parallels with natural images and the immens...

Obtaining PET/CT images from non-attenuation corrected PET images in a single PET system using Wasserstein generative adversarial networks.

Physics in medicine and biology
Positron emission tomography (PET) imaging plays an indispensable role in early disease detection and postoperative patient staging diagnosis. However, PET imaging requires not only additional computed tomography (CT) imaging to provide detailed anat...

Radiomics in PET/CT: Current Status and Future AI-Based Evolutions.

Seminars in nuclear medicine
This short review aims at providing the readers with an update on the current status, as well as future perspectives in the quickly evolving field of radiomics applied to the field of PET/CT imaging. Numerous pitfalls have been identified in study de...

Artificial intelligence-based detection of lymph node metastases by PET/CT predicts prostate cancer-specific survival.

Clinical physiology and functional imaging
INTRODUCTION: Lymph node metastases are a key prognostic factor in prostate cancer (PCa), but detecting lymph node lesions from PET/CT images is a subjective process resulting in inter-reader variability. Artificial intelligence (AI)-based methods ca...

Non-invasive decision support for NSCLC treatment using PET/CT radiomics.

Nature communications
Two major treatment strategies employed in non-small cell lung cancer, NSCLC, are tyrosine kinase inhibitors, TKIs, and immune checkpoint inhibitors, ICIs. The choice of strategy is based on heterogeneous biomarkers that can dynamically change during...

Prognostic value of FDG-PET radiomics with machine learning in pancreatic cancer.

Scientific reports
Patients with pancreatic cancer have a poor prognosis, therefore identifying particular tumor characteristics associated with prognosis is important. This study aims to investigate the utility of radiomics with machine learning using F-fluorodeoxyglu...

Machine learning-based FDG PET-CT radiomics for outcome prediction in larynx and hypopharynx squamous cell carcinoma.

Clinical radiology
AIM: To determine whether machine learning-based radiomic feature analysis of baseline integrated 2-[F]-fluoro-2-deoxy-d-glucose (FDG) positron-emission tomography (PET) computed tomography (CT) predicts disease progression in patients with locally a...

Thyroid Incidentalomas: Practice Considerations for Radiologists in the Age of Incidental Findings.

Radiologic clinics of North America
Radiologists very frequently encounter incidental findings related to the thyroid gland. Given increases in imaging use over the past several decades, thyroid incidentalomas are increasingly encountered in clinical practice, and it is important for r...