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Applications of artificial intelligence in oncologic 18F-FDG PET/CT imaging: a systematic review

Mohammad Salehi Sadaghiani, Steven P. Rowe, Sara Sheikhbahaei

2021Annals of Translational Medicine68 citationsDOIOpen Access PDF

Abstract

Artificial intelligence (AI) is a growing field of research that is emerging as a promising adjunct to assist physicians in detection and management of patients with cancer. 18 F-FDG PET imaging helps physicians in detection and management of patients with cancer. In this study we discuss the possible applications of AI in 18 F-FDG PET imaging based on the published studies. A systematic literature review was performed in PubMed on early August 2020 to find the relevant studies. A total of 65 studies were available for review against the inclusion criteria which included studies that developed an AI model based on 18F-FDG PET data in cancer to diagnose, differentiate, delineate, stage, assess response to therapy, determine prognosis, or improve image quality. Thirty-two studies met the inclusion criteria and are discussed in this review. The majority of studies are related to lung cancer. Other studied cancers included breast cancer, cervical cancer, head and neck cancer, lymphoma, pancreatic cancer, and sarcoma.

Topics & Concepts

MedicineRadiomicsPositron emission tomographyCancerPancreatic cancerHead and neck cancerLung cancerBreast cancerPet imagingMedical physicsRadiologyOncologyInternal medicineRadiomics and Machine Learning in Medical ImagingMedical Imaging Techniques and ApplicationsLung Cancer Diagnosis and Treatment
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