The advantages of using average attenuation metrics to express patient size in computed tomography dose optimization. (September 2016)

• Record Type: Journal Article
• Authors: Sarmento, S.; Mendes, B.; Gouvêa, M.
• Is Part Of: Physica medica. Volume 32(2016)Supplement 3
• Page Start: 314
• Page End: 315
• Publication Date: 2016-09
• Subjects: Medical physics -- Periodicals; Biophysics -- Periodicals; Biophysics -- Periodicals; Imagerie médicale -- Périodiques; Radiothérapie -- Périodiques; Rayons X -- Sécurité -- Mesures -- Périodiques; Physique -- Périodiques; Médecine -- Périodiques; 610.153
• DOI: 10.1016/j.ejmp.2016.07.189
• Languages: English
• ISSNs: 1120-1797

Abstract

Abstract : Introduction: Dose comparisons are essential to the process of dose optimization in computed tomography (CT). Large-scale databases, and size-specific dose estimates (SSDE), made comparisons less dependent on patient size. However, quantification of patient size would still be useful, to allow comparisons between different patient populations and different scanners. Moreover, when optimizing acquisition protocols after installation of a new scanner, dose data will be collected first for a small number of patients, and it is important that this can be compared with an established standard. Purpose: To assess the feasibility of using the water equivalent diameter (Dw) instead of patient weight to quantify patient size. Materials and methods: Existing data from a previous survey was re-analyzed using Dw metrics. Two different values of Dw were obtained for each exam: the midscan or central Dw (Dw_c) used for calculation of SSDE, and the average value of Dw in the scanned region (Dw_a). The data pertained to adult chest and chest-abdomen-pelvis (CAP) exams, in two 16 slice CT scanners (a GE Lightspeed and a Toshiba Aquilion RXL). Results: The volume CT dose index (CTDIvol) and the SSDE were plotted as a function of patient weight, body mass index (BMI), Dw_c and Dw_a. The use of Dw_a was found to reduce the dispersion of the data, relative to all the other metrics used, allowing a clearer visualization. Conclusion: Dw_a proved a robust and useful metric to characterize patient size, which can be used for comparisons of both small and large data sets. Disclosure: The authors have no relevant financial or non-financial relationships to disclose.