Image-Guided Precision Medicine in the Diagnosis and Treatment of Pheochromocytomas and Paragangliomas

In this comprehensive review, we aimed to discuss the current state-of-the-art medical imaging for pheochromocytomas and paragangliomas (PPGLs) diagnosis and treatment. Despite major medical improvements, PPGLs, as with other neuroendocrine tumors (NETs), leave clinicians facing several challenges;...

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Bibliographic Details
Published in:Cancers 2023-09, Vol.15 (18), p.4666
Main Authors: Gabiache, Gildas, Zadro, Charline, Rozenblum, Laura, Vezzosi, Delphine, Mouly, Céline, Thoulouzan, Matthieu, Guimbaud, Rosine, Otal, Philippe, Dierickx, Lawrence, Rousseau, Hervé, Trepanier, Christopher, Dercle, Laurent, Mokrane, Fatima-Zohra
Format: Article
Language:English
Subjects:
Abdomen
Algorithms
Antigens
Artificial intelligence
Biomarkers
Cancer
Care and treatment
Catecholamines
Chemotherapy
Development and progression
Diagnosis
Dopamine
Epidemiology
Hypertension
Immunotherapy
Kinases
Lymphatic system
Medical imaging
Medical imaging equipment
Medical prognosis
Medical research
Medicine, Experimental
Metastases
Metastasis
Mutation
Neuroendocrine tumors
Paraganglioma
Pathology
Phenotypes
Precision medicine
Radiomics
Review
Tomography
Tumors
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Summary:In this comprehensive review, we aimed to discuss the current state-of-the-art medical imaging for pheochromocytomas and paragangliomas (PPGLs) diagnosis and treatment. Despite major medical improvements, PPGLs, as with other neuroendocrine tumors (NETs), leave clinicians facing several challenges; their inherent particularities and their diagnosis and treatment pose several challenges for clinicians due to their inherent complexity, and they require management by multidisciplinary teams. The conventional concepts of medical imaging are currently undergoing a paradigm shift, thanks to developments in radiomic and metabolic imaging. However, despite active research, clinical relevance of these new parameters remains unclear, and further multicentric studies are needed in order to validate and increase widespread use and integration in clinical routine. Use of AI in PPGLs may detect changes in tumor phenotype that precede classical medical imaging biomarkers, such as shape, texture, and size. Since PPGLs are rare, slow-growing, and heterogeneous, multicentric collaboration will be necessary to have enough data in order to develop new PPGL biomarkers. In this nonsystematic review, our aim is to present an exhaustive pedagogical tool based on real-world cases, dedicated to physicians dealing with PPGLs, augmented by perspectives of artificial intelligence and big data.
ISSN:2072-6694
2072-6694
DOI:10.3390/cancers15184666