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Updated: Aug 5, 2026

X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging
Published on: September 11, 2011
Obese patient imaging: Potential dose reduction with photon-counting CT
Leening P Liu1, Kai Mei1, Shobhit Sharma2
1Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Background:
Photon-counting CT (PCCT) offers key advantages over energy integrating detector CT (EID-CT), especially in low-dose scans and imaging larger patients. As obesity rates rise, minimizing image noise is critical for diagnostic accuracy.
Purpose:
To evaluate the dose efficiency of cadmium-zinc-telluride (CZT) based PCCT compared to EID-CT across phantom sizes.
Methods:
A patient-specific 3D-printed pancreas phantom and a phantom with tissue mimicking inserts were placed in extension rings corresponding to the 50th, 75th, 85th, and 95th percentile adult waist circumferences. Phantoms were scanned on both PCCT and EID-CT with CTDIvol ranging from 0.5 to 19.4 mGy. Noise was measured in both phantoms to evaluate dose efficiency. Non-Poisson noise at low doses (<2 mGy) was quantified using root mean square error from linear fits of the noise-dose relationship. Potential dose reduction was then assessed by matching noise levels between scanners across phantom sizes.
Results:
PCCT demonstrated reduced noise compared to EID-CT across all phantom sizes and doses with average noise reductions of 22%, 23%, 25%, and 28% for the 50th, 75th, 85th, and 95th percentile phantoms, respectively. Noise reduction was greater at lower doses and larger phantom sizes, reaching 88 HU at 1 mGy for the 95th percentile phantom. Non-Poisson noise decreased significantly with PCCT compared to EID-CT for all phantom sizes (p < 0.013). At matched noise levels, PCCT enabled potential dose reductions of 33% and 44% for the 50th and 95th percentile phantoms, respectively.
Conclusions:
PCCT exhibited superior dose efficiency compared to EID-CT across a range of phantom sizes. The enhanced dose efficiency enables both noise reduction and potential dose reduction for the imaging of obese patients and low-dose imaging applications. Further evaluation with task-based image quality metrics remains necessary before clinical implementation of dose reduction.
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