PURPOSE: To develop and validate an automated computational tool for calculating a slice-specific volume computed tomography (CT) dose index (CTDIvol), a water-equivalent diameter (Dw), and size-specific dose estimates (SSDEs) from CT images, addressing limitations of conventional console-displayed values that provide only averaged values across scan regions. METHODS: A custom ImageJ macro was developed based on methodologies proposed in American Association of Physicists in Medicine reports 220 and 293. The tool employs threshold-based body contour segmentation [-140 Hounsfield unit (HU)] to extract patient cross-sectional areas and calculates slice-specific Dw using mean CT numbers. Slice-specific CTDIvol values are estimated by normalizing scanner-displayed CTDIvol to individual slice exposure values from Digital Imaging and Communications in Medicine metadata. An SSDE was computed using appropriate correction factors for head and body examinations.
Validation was performed using water phantoms, anthropomorphic phantoms, and clinical datasets from ≥ 30 patients. Two Siemens CT scanners were evaluated: SOMATOM go. Top®, with console-displayed values, and SOMATOM Force®, with Radimetrics software. Agreement was assessed using intraclass correlation coefficients (ICCs) and Bland-Altman analysis. RESULTS: Water phantom validation demonstrated excellent accuracy, with differences of < 2.3% for both Dw and SSDEs. The macro required approximately 30 seconds per examination to complete the analysis.
Bland-Altman plots confirmed clinically acceptable mean differences. Importantly, the slice-specific approach revealed substantial intra-scan dose variations not captured by console-reported averages, particularly in the chest phantom, where SSDEs ranged from 5.77 to 23.68 mGy despite identical average values. For the clinical dataset, ICC (3,1) values for Scanner A indicated good to excellent agreement across both head and chest/abdomen examinations (head CT-CTDI vol: 0.974, Dw: 0.893, SSDE: 0.965; chest/abdomen CT-CTDIvol: 1.000, Dw: 0.994, SSDE: 0.989). By contrast, Scanner B demonstrated near-perfect agreement for head CT in CTDIvol (0.996) and SSDE (0.967) but poor agreement for Dw (0.267). For chest/abdomen CT, however, Scanner B showed consistently high agreement, with ICC values ranging from 0.884 to 1.000.
CONCLUSION: The developed ImageJ macro provides accurate, transparent, and low-cost open-source solution slice-specific CT dose estimation that correlates well with commercial systems while offering superior spatial resolution. This automated method overcomes the limitations of traditional dose reporting by providing detailed slice-by-slice dose variations, which are often overlooked in average summary values, allowing for more accurate and clinically meaningful dose assessments. CLINICAL SIGNIFICANCE: This tool supports detailed dose evaluation across scan regions, helping optimize protocols and enhance radiation safety. Its slice-specific approach is especially useful in anatomically complex areas and research, offering clinicians more precise dose information to guide patient care.