ESTRO 2025 - Abstract Book

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Invited Speaker

ESTRO 2025

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Speaker Abstracts Photon-counting CT technology Marc Kachelriess Division of X-Ray Imaging and CT, German Cancer Research Center (DKFZ), Heidelberg, Germany

Abstract:

Photon-counting CT (PCCT) refers to novel CT systems that are equipped with photon-counting detectors. In contrast to energy-integrating CT (EICT), where the scintillator-based detectors are indirectly converting x-rays to visible light which is then measured by photo diodes, PCCT is a direct converter comprising a semiconductor such as CdTe or CZT, as the sensor material. The direct conversion of x-ray photons into electron charge clouds has several advantages that shall be discussed in this talk: the abscence of electronic noise, a Swank factor of 1, the assessment of each photon's energy and the thus resulting spectral information that can be used in various ways. The lecture also highlights the so-called "iodine effect" which means a higher iodine contrast in PCCT than in EICT as well as the so-called "small pixel effect" that significantly improves the contrast-to-noise ratio of PCCT.

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Speaker Abstracts Critical view: Cost-benefit ratio and impact on outcome in radiotherapy Hugo Bouchard Department of Physics, Universite de Montreal, Montreal, Canada. Imaging and Engineering Axis, CRCHUM, Montreal, Canada. Department of Radiation Oncology, CHUM, Montreal, Canada Abstract: Computed tomography (CT) is a cornerstone of modern medicine, with around 95 scans per 1,000 people annually in Europe. Though only 6 to 10% of these scans are used for radiotherapy planning, CT is indispensable for tumor localization, organ-at-risk delineation, and radiation dose calculation. Photon-counting CT (PCCT) is a cutting-edge technology that provides low-noise, high-resolution images at multiple energies, enabling quantitative information beyond conventional CT. Despite clinical PCCT prototypes in use for over a decade, ongoing innovations in diagnostic radiology and radiation oncology motivate a thorough review of its benefits for radiotherapy and the factors limiting full clinical advantages. First, current evidence on the advantages of PCCT over conventional and dual-energy CT is summarized, alongside relevant radiology applications that inform cancer treatment. Known radiotherapy benefits — enhanced spatial resolution, improved noise performance, and advanced quantitative capabilities — are compared with standard techniques. Next, the technology’s capacity for quantitative measurement, tumor localization, and functional imaging is examined, including its potential to complement or substitute other modalities. A critical assessment follows on modeling in PCCT, especially the role of accurate photon cross-section data and its implications for quantitative imaging. The information content of spectral CT data is explored, along with AI– and machine learning–based approaches, such as Bayesian quantitative estimation and deep learning organ segmentation. Finally, prospects and future applications of spectral PCCT in radiotherapy are discussed, including the possibility of an “all-in-one” modality. By addressing both opportunities and challenges, this review clarifies how PCCT might reshape clinical workflows in radiation oncology.