What the radiologist should know about artificial intelligence – an ESR white paper

Abstract

This paper aims to provide a review of the basis for application of AI in radiology, to discuss the immediate ethical and professional impact in radiology, and to consider possible future evolution. Even if AI does add significant value to image interpretation, there are implications outside the traditional radiology activities of lesion detection and characterisation. In radiomics, AI can foster the analysis of the features and help in the correlation with other omics data. Imaging biobanks would become a necessary infrastructure to organise and share the image data from which AI models can be trained. AI can be used as an optimising tool to assist the technologist and radiologist in choosing a personalised patient’s protocol, tracking the patient’s dose parameters, providing an estimate of the radiation risks. AI can also aid the reporting workflow and help the linking between words, images, and quantitative data. Finally, AI coupled with CDS can improve the decision process and thereby optimise clinical and radiological workflow.

Artificial intelligence: Who is responsible for the diagnosis?

“…Artificial intelligence is entering the radiological discipline very quickly and will soon be in clinical use. The European Society of Radiology stated that the most likely and immediate impact of AI will be on the management of radiology workflows, improving and automating acquisition protocols, appropriateness (with clinical decision support systems), structured reporting, up to the ability to interpret the big data of image biobanks connected to tissue biobanks, with the development of radiogenomics [22].…”

“…Much discussion has been raised in the media about the introduction of artificial intelligence in radiological practice, suggesting that radiologists could become useless or even disappear as a specialty [19][20][21]. This could lead to a lack of motivation for young doctors to pursue a career in radiology, with a real imminent risk of not having enough radiologist specialists.…”

Use of CT and artificial intelligence in suspected or COVID-19 positive patients: statement of the Italian Society of Medical and Interventional Radiology

“…As diagnostic imaging is an ecosystem of digital data, which is collected for each patient who undergoes any radiographic, computed tomography, magnetic resonance, ultrasound, and all nuclear medicine investigation, so much data, or big data, need an accurate interpretation related to the clinical problem for which the patient undergoes the investigation; this is the task of the radiologist, through the radiological medical act, that is summarized in the radiological report. In this context, artificial intelligence is a promising technology that allows to process so big data and extract meaningful information [12][13][14].…”

Artificial Intelligence in Radiology—Ethical Considerations

“…Ideally, this data should be annotated (labelled), and have an assigned "ground truth" (i.e., the answer the algorithm should be expected to arrive at if functioning as expected). This annotation and assignment of ground truth can be a very labour-intensive task [11], but first, the data must be available. In effect, the data are usually patient imaging studies.…”