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THIS MONTH’S HIGHLIGHT

Artificial intelligence in MDCT: The next revolution

Dear readers,

Artificial intelligence (AI) is introducing remarkable advances and innovations in the field of radiology, as widely emphasized during the last annual meeting ofthe Radiological Society of North America (see the MDCT.net Newsletter – December 2018). Recent and continuously evolving data have already shown how feasible it is to apply AI to radiological practice, while many studies are exploring new strategies to incorporate AI technologies into existing imaging systems. The objective is to provide a supportive instrument for radiologists and to achieve more precise and individualized diagnoses for patients.

On the wave of this revolutionary progress, we propose Dr. Anzidei’s review, which examines the most relevant applications of AI to MDCT and highlights the unique clinical role played by radiologists. The background and characteristics of AI methods combined with MDCT, as well as some experiences with this application, are illustratedin the selected literature.

Finally, we propose two new clinical cases covering different body regions and pathologies.

We remind you that suggestions for topics to be covered in future issues of this newsletter are welcome as usual. Please send your proposals to us at editorial@mdct.net.

From the MDCT.net team

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ANALYSIS & OPINION

Artificial intelligence in radiology
Analysis by M. Anzidei

The use of artificial intelligence in radiology is promising to be one of the biggest changes in the field since the introduction of cross-sectional imaging with computed tomography and magnetic resonance imaging 40 years ago.
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SELECTED LITERATURE

Nakajima J. Advances in techniques for identifying small pulmonary nodules. Surg Today. 2018 Nov 24. doi: 10.1007/s00595-018-1742-8. [Epub ahead of print]

Selvarajah A, Bennamoun M, Playford D et al. Application of artificial intelligence in coronary computed tomography angiography. Curr Cardiovasc Imaging Rep. 2018;11:12

Pesapane F, Codari M, Sardanelli F. Artificial intelligence in medical imaging: threat or opportunity? Radiologists again at the forefront of innovation in medicine. Eur Radiol Exp. 2018 Oct 24;2(1):35

Yasaka K, Akai H, Kunimatsu Aesserli M et al. Deep learning for staging liver fibrosis on CT: a pilot study. Eur Radiol. 2018 May 14. doi: 10.1007/s00330-018-5499-7. [Epub ahead of print]

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CLINICAL CASES

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