ArticlePhysics in medicine and biology2020
Multi-energy CT imaging for large patients using dual-source photon-counting detector CT.
Article in Physics in medicine and biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed, 22 citations in OpenAlex.
- Spectral performance for iodine quantification of a dual-source, dual-kV photon counting detector CT.Medical physics · 2025Article
- Impact of patient habitus and acquisition protocol on iodine quantification in dual-source photon-counting computed tomography.Journal of medical imaging (Bellingham, Wash.) · 2024Article
- An introduction to photon-counting detector CT (PCD CT) for radiologists.Japanese journal of radiology · 2023Review
- Pros and Cons of Dual-Energy CT Systems: "One Does Not Fit All".Tomography (Ann Arbor, Mich.) · 2023Review
- First-generation clinical dual-source photon-counting CT: ultra-low-dose quantitative spectral imaging.European radiology · 2022Article
- A multienergy computed tomography method without image segmentation or prior knowledge of X-ray spectra or materials.Heliyon · 2022Article
- Photon-Counting Detector CT: Key Points Radiologists Should Know.Korean journal of radiology · 2022Review
- CdTe Based Energy Resolving, X-ray Photon Counting Detector Performance Assessment: The Effects of Charge Sharing Correction Algorithm Choice.Sensors (Basel, Switzerland) · 2020Article
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7 authors at 1 institution in 1 country.
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Abstract
Multi-energy CT imaging of large patients with conventional dual-energy (DE)-CT using an energy-integrating-detector (EID) is challenging due to photon starvation-induced image artifacts, especially in lower tube potential (80-100 kV) images. Here, we performed phantom experiments to investigate the performance of DECT for morbidly obese patients, using an iodine and water material decomposition task as an example, on an emulated dual-source (DS)-photon-counting-detector (PCD)-CT, and compared its performance with a clinical DS-EID-CT. An abdominal CT phantom with iodine inserts of different concentrations was wrapped with tissue-equivalent gel layers to emulate a large patient (50 cm lateral size). The phantom was scanned on a research whole-body single-source (SS)-PCD-CT (140 kV tube potential), a DS-PCD-CT (100/Sn140 kV; Sn140 indicates 140 kV with Sn filter), and a clinical DS-EID-CT (100/Sn140 kV) with the same radiation dose. Phantom scans were repeated five times on each system. The DS-PCD-CT acquisition was emulated by scanning twice on the SS-PCD-CT using different tube potentials. The multi-energy CT images acquired on each system were then reconstructed, and iodine- and water-specific images were generated using material decomposition. The root-mean-square-error (RMSE) between true and measured iodine concentrations were calculated for each system and compared. The images acquired on the DS-EID-CT showed severe artifacts, including ringing, reduced uniformity, and photon starvation artifacts, especially for low-energy images. These were largely reduced in DS-PCD-CT images. The CT number difference that was measured using regions-of-interest across field-of-view were reduced from 20.3 ± 0.9 (DS-EID-CT) to 2.5 ± 0.4 HU on DS-PCD-CT, showing improved image uniformity using DS-PCD-CT. Iodine RMSE was reduced from 3.42 ± 0.03 mg ml
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