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From Medical Imaging to the Digital Patient

Nicholas Ayache
p. 20
Cet article est une traduction de :
De l’imagerie médicale à la médecine computationnelle
Autre(s) traduction(s) de cet article :
From Medical Images to Computational Medicine

Notes de la rédaction

Excerpts from the inaugural lecture 10 April 2014
Source: La lettre, no. 39, March 2015

Texte intégral

1In his 2008 Inaugural Lecture, Gérard Berry explained How and Why the World is Turning Digital. Then already, he spoke of the growing impact of informatics on medicine, particularly through the most recent developments in imaging.

2It is an immense honour for me today to be invited to this prestigious place, to the Chair of Informatics and Computational Sciences, to present some of the most advanced research in computational medical imaging. This young research field, at the interface between informatics and medicine, designs software which analyses and simulates medical images that can be used to build a digital model of the patient to support diagnosis, prognosis, and therapeutic practice.

3Let us start by going back a few centuries in time to attend another lecture that Rembrandt immortalized in his 1632 painting, The Anatomy Lesson of Dr Nicolaes Tulp. This painting teaches us a core principle of medical imaging: it is not enough to observe the inside of the human body so as to understand its organization and functioning. It is also necessary to project abstract – geometric and biophysical – models to understand the images of the human body and to move from a description of its structures, anatomy, to an analysis of its functions, physiology. Imaging of the human body has evolved significantly since 1632. Medical imaging is omnipresent in routine and hospital clinical practice. The nature, quantity and resolution of medical images are continuously growing, owing to constant progress in image acquisition technology. In addition to X-ray radiographies, four main imaging modalities are currently used in hospitals: CT scanners (computed tomography), MRI (magnetic resonance imaging), ultrasound imaging, and PET or SPECT scintigraphies (nuclear medicine). The images produced by these four modalities are volumetric: for each point in the human body they provide information measured in a small volume element called voxel (volume element), the volume extension of the pixel (picture element). Medical images contain a lot of information. The anatomical image of an organ, or of the entire body, can contain several hundred million voxels, stored in vast tables of numbers.

4As if all these images were not enough, large databases of images are gradually becoming available on the Web. These images come with anonymized data on the patient’s history and pathology, and can be accessed remotely to confirm a diagnosis or for statistical studies. With this proliferation of medical images, informatics and the computational sciences have become vital to exploit this over-abundance of complex data rigorously and optimally, so as to extract the clinically relevant information. The methodological framework unifying the analysis and simulation of images is the digital patient. It consists in a set of computational models of the human body combining computer data and algorithms to simulate in silico, i.e. with a computer, the anatomy and physiology of tissues and organs. These algorithms themselves rely on mathematical, biological, physical, and chemical models of life forms on different space and time scales.

5As in Rembrandt’s painting, the personalized computational model can be projected in images to facilitate their interpretation, and therefore support diagnosis. The personalized model can also further prognosis by simulating the evolution of a pathology, and then support therapy by planning and simulating an operation, or by controlling it by means of intra-operative images. This is the future of computational medicine, at the service both of physician and patient.

• A video of the Lecture is available at, on the professor’s page.

• Nicholas Ayache also organized a symposium on the same subject (see p. 65).

• The Chair is funded by Inria.

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Référence papier

Nicholas Ayache, « From Medical Imaging to the Digital Patient », La lettre du Collège de France, 9 | -1, 20.

Référence électronique

Nicholas Ayache, « From Medical Imaging to the Digital Patient », La lettre du Collège de France [En ligne], 9 | 2015, mis en ligne le 25 septembre 2015, consulté le 19 novembre 2019. URL : ; DOI : 10.4000/lettre-cdf.2158

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Nicholas Ayache

Senior Researcher, Inria

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