“Photon-counting CT will become the new standard in chest imaging”
In pulmonology, photon-counting computed tomography (CT) enables physicians to precisely evaluate function thanks to highly detailed spectral maps.
Published on February 6, 2023
Professor Frank Wacker, MD1, and Professor Jens Vogel-Claussen, MD1, report their experiences in clinical practice.
When did you start using photon-counting CT and what were your expectations?
We were very excited about the dose efficiency of the new system.
Professor Frank Wacker, MD, Chairman of Radiology, Hannover Medical School, Germany
Looking at pulmonology specifically, what were the limitations of traditional CT scanners?
Where and how has photon-counting been able to overcome these limitations?
How do improved image contrast and higher spatial resolution affect your diagnoses?
Photon-counting CT has huge potential for future CT lung cancer screening programs.
Professor Jens Vogel-Claussen, MD, Vice Chair, Department of Radiology, Hannover Medical School, Germany
Which patients benefit in particular, also with regard to lower radiation dose and less use of contrast media?
How and in which cases are you using the spectral information now available from a single scan?
How does the availability of monoenergetic images for every scan assist physicians in making a diagnosis or follow-up?
How are you using photon-counting for standard examinations? How does the technology perform in these cases?
Could you please describe one or two patient cases where photon-counting has been particularly helpful?
How do you see the role of CT evolving in your specialty with photon-counting technology?
1 Professor Frank Wacker, MD, and Professor Jens Vogel-Claussen, MD, are employed by an institution that receives financial support from Siemens Healthineers for collaborations.
2 NAEOTOM Alpha is not commercially available in all countries. Its future availability cannot be guaranteed.
The statements by Siemens Healthineers’ customers described herein are based on results that were achieved in the customer's unique setting. Because there is no “typical” hospital or laboratory and many variables exist (e.g., hospital size, samples mix, case mix, level of IT and/or automation adoption) there can be no guarantee that other customers will achieve the same results.