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Background: Quantifying radiation burden is necessary for optimizing imaging protocols. The normalized dose coefficient (NDC) is determined from the water‐equivalent diameter (WED) and is used to scale the CTDIvol based on body habitus to determine the size specific dose estimate (SSDE). In this study we determine the SSDE prior to the CT scan and how sensitive the SSDE from WED is to the lifetime attributable risk (LAR) from BEIR VII. Method: For calibration, phantom images are used to relate the mean pixel values along a profile (PPV¯$\overline {{\rm{PPV}}} $) of the CT localizer to the water‐equivalent area (AW) of the CT axial scan at the same z‐location. Images of the CTDIvol phantoms (32 cm, 16 cm, and ∼1 cm) and ACR phantom (Gammex 464) were acquired on four scanners. The relationship between the AW and PPV¯$\overline {{\rm{PPV}}} $ was used to calculate the WED from the CT localizer for patient scans. A total of 790 CT examinations of the chest and abdominopelvic regions were used in this study. The effective diameter (ED) was calculated from the CT localizer. The LAR was calculated based on the patient chest and abdomen using the National Cancer Institute Dosimetry System for Computed Tomography (NCICT). The radiation sensitivity index (RSI) and risk differentiability index (RDI) were calculated for SSDE and CTDIvol. Results: The WED from CT localizers and CT axials scans show good correlation (R2 = 0.96) with the maximum percentage difference being 13.45%. The NDC from WED correlates poorly with LAR for lungs (R2 = 0.18) and stomach (R2 = 0.19), however that is the best correlation. Conclusion: The SSDE can be determined within 20% as recommended by the report of AAPM TG 220. The CTDIvol and SSDE are not good surrogates for radiation risk, however the sensitivity for SSDE improves when using WED instead of ED. [ABSTRACT FROM AUTHOR]

Purpose: Patient size‐specific dose estimate (SSDE) calculations require knowledge of a patient's size. Errors in patient size propagate through SSDE calculations. AAPM Reports 204 and 220 recommend that a magnification correction be applied to patient size surrogates extracted from CT localizer radiographs. This technical note presents a novel approach for such a magnification correction. Methods: In our model‐based magnification correction, we assume that the patient's cross sections are elliptical with minor and major axes defined using the anterior–posterior (AP) and lateral (LAT) patient dimensions. We parameterize the problem by modeling a line emanating from the source, grazing the patient (i.e., the ellipse), and then terminating onto the detector plane. We model tangent lines on each side of the ellipse on both the LAT and AP CT localizer radiographs. We also account for vertical mispositioning with table offset. We compared our correction model to the actual AP and LAT dimensions to the vendor‐supplied CT localizer images that only received a geometric magnification correction, and to other methods described in the literature. We compare our model to the others using direct size to size comparisons as well as SSDE conversion factor. Results: Our model‐based method provides consistent accurate results (less than 1.8% error for absolute size and 1.2% error for SSDE for all measurement conditions) for all positions and patient sizes. Existing literature‐based methods had maximum errors for absolute size and SSDE of 7.5% and 5.2%, and for the vendor, they were 30.9% and 17.0%, respectively. Conclusion: We presented a new model‐based geometric size correction method that outperforms a simple geometric correction as well as other methods presented in the literature. By modeling the patient cross section and beam geometry using information all derived from the DICOM header and CT localizer views, we demonstrated SSDE correction factor improvements from 17.0% (vendor correction) to 1.2% (model base). These changes correspond directly into changes in SSDE itself and also represent clinically realistic patient sizes and mispositioning amounts. [ABSTRACT FROM AUTHOR]