PURPOSE: To develop software to automatically calculate size-specific dose estimates (SSDEs) and to assess the effect of variations in water-equivalent diameter (Dw) along the z-axis on SSDE for computed tomographic (CT) examinations of the torso. MATERIALS AND METHODS: In this institutional review board-approved, HIPAA-compliant, retrospective study, a software program was used to calculate Dw at each image position in 102 consecutive CT examinations of the combined chest, abdomen, and pelvis. SSDE was calculated by multiplying the size-dependent conversion factor and volume CT dose index (CTDIvol) at each image position. The variations in Dw along the z-axis were determined for six hypothetical scanning ranges: chest alone; abdomen alone; pelvis alone; chest and abdomen; abdomen and pelvis; and chest, abdomen, and pelvis. Mean SSDE was calculated in two ways: (a) from the SSDE at each position and (b) from the mean CTDIvol over each scan range and the conversion factor corresponding to Dw at the middle of the scan range. Linear regression analysis was performed to determine the correlation between SSDE values calculated in these two ways. RESULTS: Across patients, for scan ranges 1-6, the mean of the difference between maximal and minimal Dw within a given patient was 5.2, 4.9, 2.5, 6.0, 5.6, and 6.5 cm, respectively. The mean SSDE values calculated by using the two methods were in close agreement, with root mean square differences of 0.9, 0.5, 0.5, 1.4, 1.0, and 1.1 mGy or 6%, 3%, 2%, 9%, 4%, and 6%, for the scan ranges of chest; abdomen; pelvis; chest and abdomen; abdomen and pelvis; and chest, abdomen, and pelvis, respectively. CONCLUSION: Using the mean CTDIvol from the whole scan range and Dw from the image at the center of the scan range provided an easily obtained estimate of SSDE for the whole scan range that agreed well with values from an image-by-image approach, with a root mean square difference less than 1.4 mGy (9%).
PURPOSE: To develop software to automatically calculate size-specific dose estimates (SSDEs) and to assess the effect of variations in water-equivalent diameter (Dw) along the z-axis on SSDE for computed tomographic (CT) examinations of the torso. MATERIALS AND METHODS: In this institutional review board-approved, HIPAA-compliant, retrospective study, a software program was used to calculate Dw at each image position in 102 consecutive CT examinations of the combined chest, abdomen, and pelvis. SSDE was calculated by multiplying the size-dependent conversion factor and volume CT dose index (CTDIvol) at each image position. The variations in Dw along the z-axis were determined for six hypothetical scanning ranges: chest alone; abdomen alone; pelvis alone; chest and abdomen; abdomen and pelvis; and chest, abdomen, and pelvis. Mean SSDE was calculated in two ways: (a) from the SSDE at each position and (b) from the mean CTDIvol over each scan range and the conversion factor corresponding to Dw at the middle of the scan range. Linear regression analysis was performed to determine the correlation between SSDE values calculated in these two ways. RESULTS: Across patients, for scan ranges 1-6, the mean of the difference between maximal and minimal Dw within a given patient was 5.2, 4.9, 2.5, 6.0, 5.6, and 6.5 cm, respectively. The mean SSDE values calculated by using the two methods were in close agreement, with root mean square differences of 0.9, 0.5, 0.5, 1.4, 1.0, and 1.1 mGy or 6%, 3%, 2%, 9%, 4%, and 6%, for the scan ranges of chest; abdomen; pelvis; chest and abdomen; abdomen and pelvis; and chest, abdomen, and pelvis, respectively. CONCLUSION: Using the mean CTDIvol from the whole scan range and Dw from the image at the center of the scan range provided an easily obtained estimate of SSDE for the whole scan range that agreed well with values from an image-by-image approach, with a root mean square difference less than 1.4 mGy (9%).
Authors: Jodie A Christner; Natalie N Braun; Megan C Jacobsen; Rickey E Carter; James M Kofler; Cynthia H McCollough Journal: Radiology Date: 2012-10-22 Impact factor: 11.105
Authors: Maryam Bostani; Kyle McMillan; Peiyun Lu; Grace Hyun J Kim; Dianna Cody; Gary Arbique; S Bruce Greenberg; John J DeMarco; Chris H Cagnon; Michael F McNitt-Gray Journal: Med Phys Date: 2017-04 Impact factor: 4.071
Authors: Monika Uhrig; David Simons; Marc Kachelrieß; Francesco Pisana; Stefan Kuchenbecker; Heinz-Peter Schlemmer Journal: Cancer Imaging Date: 2016-06-21 Impact factor: 3.909