# 120 Years of Accelerators that Heal

- Institution: CERN
- Department: John Adams Lecture
- Speaker: Ugo AMALDI
- Year: 2013
- Language: English
- Source: [CERN](https://videos.cern.ch/record/3003447)
- Licence: [CERN](http://copyright.web.cern.ch)
- Who can watch: Teens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

The discovery of X rays was made possible by the intelligent use of the best accelerator of the time. Since then, the development of particle accelerators has been at the root of both fundamental discoveries in physics and unforeseeable medical applications. The lecture will describe the major steps in this 120-year history of diagnostics and tumour therapy.

The first attempts to heal tumours with X rays were made only one month after Röntgen's discovery, but the understanding of the mechanisms by which the radiation kills the cells and the introduction of dose fractionation took much longer. The use of X rays in diagnostics developed much faster and its benefits were very visible during the First World War. Today no tumour could be treated and no patient could be operated without a CT scan, which employs an X ray tube that is not very different from the one introduced by William Coolidge in 1912.

On the particle therapy frontier, more sophisticated and larger particle accelerators have contributed to the continuous increase of the tumour control rate. The initial betatrons were substituted, at the end of the 1950s, by radiofrequency electron linacs. More recently proton and carbon ion accelerators have become important tools in the fight against tumours, in particular "radio-resistant" tumours. After a review of the rationale for all forms of radiotherapy and of the accelerators used in proton therapy, the European centres for carbon ion therapy will be discussed and the challenges facing the physicists and the engineers developing the accelerators will be described. .

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## Lectures

1. [120 Years of Accelerators that Heal](https://invisiblenetwork.ai/learn/cern/3003447/05840720a93b), 1 h 23 min (CERN's player)