ArticleIEEE transactions on radiation and plasma medical sciences2021
A Clinically Driven Task-Based Comparison of Photon Counting and Conventional Energy Integrating CT for Soft Tissue, Vascular, and High-Resolution Tasks.
Article in IEEE transactions on radiation and plasma medical sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 19 citations in OpenAlex.
- Article
- Assessment of Image Quality Performance of a Photon-Counting Computed Tomography Scanner Approved for Whole-Body Clinical Applications.Sensors (Basel, Switzerland) · 2025Article
- Voxelwise characterization of noise for a clinical photon-counting CT scanner with a model-based iterative reconstruction algorithm.European radiology experimental · 2025Article
- To Reconstruct or Discard: A Comparison of Additive and Subtractive Charge Sharing Correction Algorithms at High and Low X-ray Fluxes.Sensors (Basel, Switzerland) · 2024Article
- Multivariate signal-to-noise ratio as a metric for characterizing spectral computed tomography.Physics in medicine and biology · 2024Article
- Development of a separability index for task specific characterization of spectral computed tomography.Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) · 2024Article
- A systematic task-based image quality assessment of photon-counting and energy integrating CT as a function of reconstruction kernel and phantom size.Medical physics · 2024Article
- Impact of the confluence of cardiac motion and high spatial resolution on performance of ECG-gated imaging with an investigational photon-counting CT system: A phantom study.Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) · 2023Article
- A methodology for incorporating a photon-counting CT system into routine clinical use.Journal of applied clinical medical physics · 2023Article
- Technology Characterization Through Diverse Evaluation Methodologies: Application to Thoracic Imaging in Photon-Counting Computed Tomography.Journal of computer assisted tomographyArticle
- High Spatial-Resolution Skull Base Imaging With Photon-Counting Computed Tomography and Energy-Integrating Computed Tomography: A Comparative Phantom Study.Journal of computer assisted tomographyArticle
Corrections and comments
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
Abstract
Photon-counting CT detectors are the next step in advancing CT system development and will replace the current energy integrating detectors (EID) in CT systems in the near future. In this context, the performance of PCCT was compared to EID CT for three clinically relevant tasks: abdominal soft tissue imaging, where differentiating low contrast features is important; vascular imaging, where iodine detectability is critical; and, high-resolution skeletal and lung imaging. A multi-tiered phantom was imaged on an investigational clinical PCCT system (Siemens Healthineers) across different doses using three imaging modes: macro and ultra-high resolution (UHR) PCCT modes and EID CT. Images were reconstructed using filtered backprojection and soft tissue (B30f), vascular (B46f), or high-resolution (B70f; U70f for UHR) kernels. Noise power spectra, task transfer functions, and detectability index were evaluated. For a soft tissue task, PCCT modes showed comparable noise and resolution with improved contrast-to-noise ratio. For a vascular task, PCCT modes showed lower noise and improved iodine detectability. For a high resolution task, macro mode showed lower noise and comparable resolution while UHR mode showed higher noise but improved spatial resolution for both air and bone. PCCT offers competitive advantages to EID CT for clinical tasks.
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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.