Analysis of Radiographic Image Quality in Computed Radiography with Variations in Subject Thickness and AEC Sensitivity Settings
Keywords:
Computed Radiography, AuAtomatic Exposure Control, Image Quality, Signal-to-Noise Ratio, Exposure IndexAbstract
This study evaluates the influence of subject thickness variations and Automatic Exposure Control (AEC) sensitivity on radiographic image quality in Computed Radiography (CR) systems. A total of 16 radiographic images were analyzed, consisting of 12 images obtained from polymethyl methacrylate (PMMA) phantoms and 4 images from the TOR CDR phantom. Experiments were conducted using phantoms with thicknesses of 10, 15, 20, and 25 cm. Radiographic exposures were performed at a fixed tube voltage of 70 kV, with the AEC system automatically adjusting the tube current-time product (mAs). For each PMMA thickness, exposures were repeated three times to evaluate Signal-to-Noise Ratio (SNR), contrast, and Exposure Index (EI), while TOR CDR images were acquired once per thickness variation. Image quality was assessed through Signal-to-Noise Ratio (SNR), contrast, and Exposure Index (EI) using ImageJ software and One-way ANOVA statistical testing. Results demonstrated that while the AEC effectively maintains contrast (p = 0.202) and EI (p = 0.796) within optimal diagnostic ranges, the SNR decreases significantly as subject thickness increases (p = 0.001). Optimal image quality was achieved at 10 cm for the TOR CDR phantom and 15 cm for the PMMA phantom. The study concludes that although AEC regulates dose consistency, additional protocol optimization is necessary for subjects exceeding 20 cm to mitigate SNR degradation caused by scattered radiation.
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