Zbyněk Tüdös (Associate Professor in Radiology) , Lucia Veverková (Consultant in Radiology) , Jan Baxa (Professor in Radiology) , Igor Hartmann (Consultant in Urology) , Filip Čtvrtlík (Associate Professor in Radiology)
{"title":"The current and upcoming era of radiomics in phaeochromocytoma and paraganglioma","authors":"Zbyněk Tüdös (Associate Professor in Radiology) , Lucia Veverková (Consultant in Radiology) , Jan Baxa (Professor in Radiology) , Igor Hartmann (Consultant in Urology) , Filip Čtvrtlík (Associate Professor in Radiology)","doi":"10.1016/j.beem.2024.101923","DOIUrl":null,"url":null,"abstract":"<div><div>The topic of the diagnosis of phaeochromocytomas remains highly relevant because of advances in laboratory diagnostics, genetics, and therapeutic options and also the development of imaging methods. Computed tomography still represents an essential tool in clinical practice, especially in incidentally discovered adrenal masses; it allows morphological evaluation, including size, shape, necrosis, and unenhanced attenuation. More advanced post-processing tools to analyse digital images, such as texture analysis and radiomics, are currently being studied. Radiomic features utilise digital image pixels to calculate parameters and relations undetectable by the human eye. On the other hand, the amount of radiomic data requires massive computer capacity. Radiomics, together with machine learning and artificial intelligence in general, has the potential to improve not only the differential diagnosis but also the prediction of complications and therapy outcomes of phaeochromocytomas in the future. Currently, the potential of radiomics and machine learning does not match expectations and awaits its fulfilment.</div></div>","PeriodicalId":8810,"journal":{"name":"Best practice & research. Clinical endocrinology & metabolism","volume":"39 1","pages":"Article 101923"},"PeriodicalIF":6.1000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Best practice & research. Clinical endocrinology & metabolism","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1521690X24000770","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
引用次数: 0
Abstract
The topic of the diagnosis of phaeochromocytomas remains highly relevant because of advances in laboratory diagnostics, genetics, and therapeutic options and also the development of imaging methods. Computed tomography still represents an essential tool in clinical practice, especially in incidentally discovered adrenal masses; it allows morphological evaluation, including size, shape, necrosis, and unenhanced attenuation. More advanced post-processing tools to analyse digital images, such as texture analysis and radiomics, are currently being studied. Radiomic features utilise digital image pixels to calculate parameters and relations undetectable by the human eye. On the other hand, the amount of radiomic data requires massive computer capacity. Radiomics, together with machine learning and artificial intelligence in general, has the potential to improve not only the differential diagnosis but also the prediction of complications and therapy outcomes of phaeochromocytomas in the future. Currently, the potential of radiomics and machine learning does not match expectations and awaits its fulfilment.
期刊介绍:
Best Practice & Research Clinical Endocrinology & Metabolism is a serial publication that integrates the latest original research findings into evidence-based review articles. These articles aim to address key clinical issues related to diagnosis, treatment, and patient management.
Each issue adopts a problem-oriented approach, focusing on key questions and clearly outlining what is known while identifying areas for future research. Practical management strategies are described to facilitate application to individual patients. The series targets physicians in practice or training.