Reconstruction algorithms and arm positioning effects on abdominal CT image quality and radiation dose: a phantom study

Clinical Snapshot

Key Findings

• P Value: Not reported in abstract

• Effect Size: 83% maximum radiation dose increase with arms-down positioning

• Primary Outcome: Radiation dose increased up to 83% in non-arms-up configurations compared to arms-up position

• Nnt Or Sensitivity: Deep learning reconstruction enabled selected non-arms-up configurations to approach near-reference diagnostic quality

• Confidence Interval: Not reported in abstract

Clinical Application

Highly feasible as involves standard CT positioning techniques and available reconstruction algorithms Directly applicable to Australian radiology practice; supports ACPSEM radiation safety guidelines and optimized imaging protocols across public and private sectors All patients undergoing abdominal CT, particularly those unable to maintain arms-up positioning due to mobility limitations, pain, or claustrophobia

Abstract

OBJECTIVE: To evaluate the effects of arm positioning and reconstruction algorithms on radiation dose and image quality of abdominal CT. MATERIALS AND METHODS: Abdominal CT scans were performed using a customized body phantom at 100 kVp with automatic tube current modulation based on noise indices (NI) of 9, 11, and 13 across seven arm positions: arms up (AU), arms down (AD), arms down with one or two-layered air cushions (ADAC, ADAC2), arms on the belly (AB), and arms on the belly with one or two-layered air cushions (ABAC, ABAC2). Images were reconstructed using filtered back projection (FBP), iterative reconstruction, and deep learning-based reconstruction (DLIR). Radiation dose was recorded. Quantitative image quality metrics included image noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), sharpness, and structural similarity. Qualitative assessment of sharpness, noise, artifacts, and overall image quality was performed using fixed-dose AU-FBP images as the reference standard. RESULTS: Compared with the AU position, radiation dose increased by up to 83% in non-AU configurations, with similar trends across all NI settings. In contrast, air cushion use caused only minor, configuration-dependent dose changes. Qualitatively, non-AU FBP images showed marked degradation, whereas DLIR enabled selected non-AU configurations to approach near-reference diagnostic quality. Air cushion-related benefits were modest overall but more apparent in AB than AD configurations. CONCLUSION: Arm positioning is the primary determinant of radiation dose and image quality in abdominal CT. When arm elevation is not feasible, DLIR effectively mitigates image quality degradation, while air cushions provide limited, configuration-dependent benefits. RELEVANCE STATEMENT: When arms cannot be raised during abdominal CT, avoiding arms-on-belly and using air cushions may help maintain image quality without substantially increasing radiation dose, while deep learning image reconstruction further enhances diagnostic performance under restricted positioning conditions. KEY POINTS: Arm positioning is a major determinant of radiation dose and image quality in abdominal CT. Arms-on-belly positioning produces poorer image quality despite increased radiation dose. DLIR improves image quality across arm positions but does not eliminate positioning-related degradation.