WE‐A‐218‐07: Linear Relationship between Average (global) and Regional Average Tube Current (mA) in Tube Current Modulated CT Scans
Purpose: Previously we have shown the importance of implementing region and/or organ‐specific CTDIvol values for tube current modulated (TCM) scans to better quantify scanner's output at a specific table location in TCM CT scans. Extracting and averaging organ‐specific mA values from the DICOM header is a tedious task. Therefore, the purpose of this study was to investigate the relationship between average mA over the entire scan and regional and organ‐specific average mA. Methods: Within a scanner the TCM algorithm performs equally across patients and similar TCM trend is usually been observed among patients, unless there are certain improper positioning of the patient, e. g. arms within the scan FOV in thoracic scans. This suggests a possible high correlation between global and regional average mA. A MatLab code was written to extract tube current values and table location for all of our voxelized patient modes. For specific organs and regions table locations were looked up and average mA values were calculated. For five organs these organ‐specific mA values were compared to the global, scanner‐reported average mA by conduction regression analyses. Results: Regional average mA is linearly proportional to the global average and can be estimated using regression equations instead of extracting every single value from the image and averaging them. The R2 values of the linear regressionequations are 0.80, 0.85, 0.90, 0.90, 0.92, and 0.99 for spleen, kidneys,liver, abdomen, breasts, and lungs, respectively. Conclusion: We have shown that region‐ and organ‐specific average mA calculations, from which a region‐ and organ‐specific CTDIvol can also be calculated, can be estimated using the global average mA. Furthermore, the calculated correlations can be increased if the organ‐specific average mA are calculated using detail TCM function, which includes the angular modulation of tube current as well, rather than utilizing the image data.