ReviewRadiology. Imaging cancer2026
Spectral CT and Photon-counting Detector CT: Principles and Applications in Neuroradiology.
Review in Radiology. Imaging cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Spectral CT and photon-counting detector (PCD) CT are recent innovations in imaging that have gained increasing use as diagnostic tools. Both modalities leverage advanced detector technologies-PCD CT uses detectors that count individual x-ray photons and measure their energies, while spectral CT separates x-ray energies at dual or multiple levels. These approaches provide higher spatial resolution, improved contrast-to-noise ratio, and reduced noise and enable multienergy imaging from a single acquisition. These techniques enhance visualization of tissue characteristics and reduce artifacts compared with conventional energy-integrating detector CT. This review article introduces the fundamental principles of spectral CT and PCD CT, their advantages in neuro-oncologic applications, and their potential to improve diagnostic imaging through enhanced image quality and quantitative accuracy.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.