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Rofo 2020; 192(09): 847-853
DOI: 10.1055/a-1167-8402
Review

AI in Radiology: Where are we today in Multiple Sclerosis Imaging?

Article in several languages: English | deutsch
Paul Eichinger
1   Department of Radiology, Klinikum rechts der Isar der Technischen Universität München, München, Germany
,
Claus Zimmer
2   Department of Neuroradiology, Klinikum rechts der Isar der Technischen Universität München, München, Germany
,
Benedikt Wiestler
2   Department of Neuroradiology, Klinikum rechts der Isar der Technischen Universität München, München, Germany
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Abstract

Background MR imaging is an essential component in managing patients with Multiple sclerosis (MS). This holds true for the initial diagnosis as well as for assessing the clinical course of MS. In recent years, a growing number of computer tools were developed to analyze imaging data in MS. This review gives an overview of the most important applications with special emphasis on artificial intelligence (AI).

Methods Relevant studies were identified through a literature search in recognized databases, and through parsing the references in studies found this way. Literature published as of November 2019 was included with a special focus on recent studies from 2018 and 2019.

Results There are a number of studies which focus on optimizing lesion visualization and lesion segmentation. Some of these studies accomplished these tasks with high accuracy, enabling a reproducible quantitative analysis of lesion loads. Some studies took a radiomics approach and aimed at predicting clinical endpoints such as the conversion from a clinically isolated syndrome to definite MS. Moreover, recent studies investigated synthetic imaging, i. e. imaging data that is not measured during an MR scan but generated by a computer algorithm to optimize the contrast between MS lesions and brain parenchyma.

Conclusion Computer-based image analysis and AI are hot topics in imaging MS. Some applications are ready for use in clinical routine. A major challenge for the future is to improve prediction of expected disease courses and thereby helping to find optimal treatment decisions on an individual level. With technical improvements, more questions arise about the integration of new tools into the radiological workflow.

Key Points: 

  • Computer algorithms have a growing impact on analyzing MR imaging in MS.

  • Artificial intelligence is more and more commonly employed in such computer tools.

  • Applications include lesion segmentation, prediction of clinical parameters and image synthesizing.

Citation Format

  • Eichinger P, Zimmer C, Wiestler B. AI in Radiology: Where are we today in Multiple Sclerosis Imaging?. Fortschr Röntgenstr 2020; 192: 847 – 853

Key words

multiple sclerosis - artificial intelligence - MR-imaging - radiomics - segmentation


Publication History

Received: 30 December 2019

Accepted: 17 April 2020

Article published online:
08 July 2020

© Georg Thieme Verlag KG
Stuttgart · New York

 

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