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Final ID: Poster #: EDU-093

Protecting Our Youngest Patients: Applications of Photon Counting CT Scanners in Reducing Radiation Dose and Improving Imaging Quality

Purpose or Case Report: Photon-counting CT scanners, a recent generational leap in CT technology, offer immense potential in reducing electron noise and elevating image quality. Photon-counting computed tomography (PCCT) stands apart from traditional CT scans through its revolutionary scanning process. Unlike conventional CT scans, which rely on a two-step process to convert X-rays into visible light, photon-counting CT scanners directly transform X-ray photons into electrical signals, effectively minimizing electronic noise. The intrinsic features of PCCT, relying on semiconductor technologies, bring about a significant reduction in electron noise and an enhancement in spatial resolution. This, in turn, yields high-quality images while concurrently lowering radiation doses compared to traditional CT scans. The application of photon-counting detectors in pediatric imaging has been the subject of extensive study, with promising results showcased in initial clinical experiences, especially in pediatric chest imaging. This development is particularly critical given the heightened radiation sensitivity of children when compared to adults. In the United States alone, where over 5 million pediatric CT scans are performed each year, the need to lower radiation exposure is a serious concern. In conclusion, photon-counting CT scanners represent a promising technological advancement with the capacity to improve image quality and reduce radiation exposure in pediatric patients. The ongoing research and development in this field hold the promise of even more substantial enhancements in CT technology, contributing to safer radiation exposure and improved imaging outcomes. This exhibit will review the current PCCT literature and provide case examples of how this technology can implemented in a pediatric setting.
Methods & Materials:
Results:
Conclusions:
  • Khanna, Praneet  ( University of Missouri - Kansas City School of Medicine , Kansas City , Missouri , United States )
  • Park, Brandon  ( University of Missouri - Kansas City School of Medicine , Kansas City , Missouri , United States )
  • Randhawa, Hari  ( University of Missouri - Kansas City School of Medicine , Kansas City , Missouri , United States )
  • Jain, Amit  ( Children's Mercy - Kansas City , Kansas City , Missouri , United States )
  • Lynn, Mitchell  ( Saint Luke's Health System , Kansas City , Missouri , United States )
Session Info:

Posters - Educational

Nuclear Medicine/Molecular Imaging

SPR Posters - Educational

More abstracts on this topic:
CSF Leak in the Pediatric Population: A Case-based Review and Imaging-based Diagnostic Algorithm

Jordan Gregory, Hampton Erica, Stence Nicholas, Milla Sarah, Callen Andrew

Central Nervous System and Temporal Bone Imaging Findings in SOXopathies

Osorio Duque Fernando, Subramanian Subramanian

More abstracts from these authors:
Machine and Deep Learning Models for Identification and Classification of Pediatric Brain Tumors

Randhawa Hari, Park Brandon, Khanna Praneet, Jung Daniel, Das Ayushman, Ginn Kevin, Mitchell Grace

fMRI Early Detection for ADHD in Children

Park Brandon, Khanna Praneet, Randhawa Hari, Lynn Mitchell

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Poster____EDU-093.pdf
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