Quantitative Evaluation of Vertical Off-Centering Effects on Dose Output and Image Quality across Modern CT Systems
Abstract
Purpose
Vertical patient off-centering is a common positioning error known to alter automatic exposure control (AEC) behavior and increase variability in both radiation output and image quality. The purpose of this study is to systematically quantify the impact of vertical mis-centering across five CT systems, including both energy integrating and photon counting detector technologies. By simulating standard and a larger patient habitus, we aim to characterize vendor specific differences in, tube current (mA) modulation, and diagnostic image quality metrics as a function of table height.
Methods
An anthropomorphic chest phantom (LUNGMAN PH-1, Kyoto Kagaku) with solid nodule inserts was scanned on five systems: GE Revolution, GE Discovery 750 HD, Philips Brilliance iCT 256, Siemens SOMATOM Force, and Siemens NAEOTOM Alpha. Soft-tissue-equivalent (~1.06 ) chest plates were added to mimic a larger patient habitus. A consistent clinical chest protocol was used across scanners, and vertical offsets of +/- 2.5, +/- 5.0, and +/- 7.5 cm from isocenter were introduced. For each acquisition, CTDIvol and vendor specific mA modulation curves were collected from DICOM metadata and scanner dose reports. Image quality evaluation includes ROI-based noise, Hounsfield unit (HU) accuracy, and nodule contrast-to-noise ratio (CNR). Multiple repeated acquisitions are performed to ensure statistical reliability.
Results
Data collection and Results will quantify the degree to which off centering alters radiation output and image quality on each scanner platform, with particular attention to differences in mA modulation response, variability, and nodule CNR degradation.
Conclusion
This multi-vendor evaluation, including the assessment of vertical mis-centering effects on a photon counting CT system, will provide quantitative evidence on how patient positioning influences radiation output and image quality performance across contemporary CT platforms. Findings will support improved centering related quality control (QC) procedures, technologist training, and protocol optimization, offering actionable guidance for reducing AEC related variability in clinical practice.