Automatic calculation of patient size metrics in computed tomography: What level of computational accuracy do we need?. (19th December 2017)

• Record Type: Journal Article
• Authors: Sarmento, Sandra; Mendes, Bruno; Gouvêa, Margarida
• Is Part Of: Journal of applied clinical medical physics. Volume 19:Number 1(2018)
• Page Start: 218
• Page End: 227
• Publication Date: 2017-12-19
• Subjects: computed tomography -- examination doses -- patient size metrics -- water equivalent diameter; Medical physics -- Periodicals; Clinical medicine -- Periodicals; Health Physics; Clinical Medicine; Electronic journals; Periodicals; Periodicals; Fulltext; Internet Resources; 610.153
• DOI: 10.1002/acm2.12240
• Languages: English
• ISSNs: 1526-9914

Abstract

Abstract: Objectives: To compare the effectiveness of two different patient size metrics based on water equivalent diameter ( D w ), the mid‐scan water equivalent diameter D w_c, and the mean (average) water equivalent diameter in the imaged region, D w_ave, for automatic detection of accidental changes in computed tomography (CT) acquisition protocols. Methods: Patient biometric data (height and weight) were available from a previous survey for 80 adult chest examinations, and 119 adult single‐acquisition chest–abdomen–pelvis (CAP) examinations for two 16 slice scanners (GE LightSpeed and Toshiba Aquilion RXL) equipped with automatic tube current modulation (ATCM). D w_c and D w_ave were calculated from the archived CT images. Size‐specific dose estimates (SSDE) were obtained from volume CT dose index (CTDIvol ), using the conversion factors for a patient diameter of D w_c . Results: CTDIvol and SSDE correlate better with D w_ave than with D w_c . R ‐squared values of linear fits to CTDIvol of CAP examinations were 0.81–0.89 for D w_c and 0.93–0.94 for D w_ave (SSDE: 0.69–080 for D w_c, 0.87–0.92 for D w_ave ). Percentage differences between D w_c and D w_ave were −4 ± 4% for chest and +5 ± 4% for CAP examinations (in % of D w_ave ). However, small D w variations translated as larger variations in CTDIvol for these ATCM systems (e.g., a 24% increase in D w doubled CTDIvol ). The dependence of CTDIvol on D w_ave was similar for chest and CAP examinations performed with similar ATCM parameters, while use of D w_c resulted in a clear separation of the same data according to examination type. Maximum D w variation in the imaged region was 5.6 ± 1.6 cm for chest and 6.5 ± 1.4 cm for CAP examinations. Conclusions: D w_ave is a better metric than D w_c for binning similar‐sized patients in dose comparison studies, despite the additional computational effort required for its calculation Therefore, when implementing automatic determination of D w for SSDE calculations, automatic calculation of D w_ave should be considered.