OBJECTIVE: To perform a calibration study to provide data to help improve consistency in the pressure that is applied during mammography. METHODS: Automatic readouts of breast thickness accuracy vary between mammography machines; therefore, one machine was selected for calibration. 250 randomly selected patients were invited to participate; 235 agreed, and 940 compression data sets were recorded (breast thickness, breast density and pressure). Pressure (measured in decanewtons) was increased from 5 daN through 1-daN intervals until the practitioner felt that the pressure was appropriate for imaging; at each pressure increment, breast thickness was recorded. RESULTS: Graphs were generated and equations derived; second-order polynomial trend lines were applied using the method of least squares. No difference existed between breast densities, but a difference did exist between "small" (15×29 cm) and "medium/large" (18×24/24×30 cm) paddles. Accordingly, data were combined. Graphs show changes in thickness from 5-daN pressure for craniocaudal and mediolateral oblique views for the small and medium/large paddles combined. Graphs were colour coded into three segments indicating high, intermediate and low gradients [≤-2 (light grey); -1.99 to -1 (mid-grey); and ≥-0.99 (dark grey)]. We propose that 13 daN could be an appropriate termination pressure on this mammography machine. CONCLUSION: Using patient compression data we have calibrated a mammography machine to determine its breast compression characteristics. This calibration data could be used to guide practice to minimise pressure variations between practitioners, thereby improving patient experience and reducing potential variation in image quality. ADVANCES IN KNOWLEDGE: For the first time, pressure-thickness graphs are now available to help guide mammographers in the application of pressure.
OBJECTIVE: To perform a calibration study to provide data to help improve consistency in the pressure that is applied during mammography. METHODS: Automatic readouts of breast thickness accuracy vary between mammography machines; therefore, one machine was selected for calibration. 250 randomly selected patients were invited to participate; 235 agreed, and 940 compression data sets were recorded (breast thickness, breast density and pressure). Pressure (measured in decanewtons) was increased from 5 daN through 1-daN intervals until the practitioner felt that the pressure was appropriate for imaging; at each pressure increment, breast thickness was recorded. RESULTS: Graphs were generated and equations derived; second-order polynomial trend lines were applied using the method of least squares. No difference existed between breast densities, but a difference did exist between "small" (15×29 cm) and "medium/large" (18×24/24×30 cm) paddles. Accordingly, data were combined. Graphs show changes in thickness from 5-daN pressure for craniocaudal and mediolateral oblique views for the small and medium/large paddles combined. Graphs were colour coded into three segments indicating high, intermediate and low gradients [≤-2 (light grey); -1.99 to -1 (mid-grey); and ≥-0.99 (dark grey)]. We propose that 13 daN could be an appropriate termination pressure on this mammography machine. CONCLUSION: Using patient compression data we have calibrated a mammography machine to determine its breast compression characteristics. This calibration data could be used to guide practice to minimise pressure variations between practitioners, thereby improving patient experience and reducing potential variation in image quality. ADVANCES IN KNOWLEDGE: For the first time, pressure-thickness graphs are now available to help guide mammographers in the application of pressure.
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