Umeå universitets logga

Background/Introduction: The concept of Size-Specific Dose Estimates (SSDE) for refining computed tomography (CT) dosimetry has been proposed in the Report of the American Association of Physicists in Medicine (AAPM) Task Group 204.[1] The present conventional metrics for patient exposure in CT applications are the Computed Tomography Dose Index (CTDI) and Dose Length Product (DLP), which do not take patient size into account. Due to Tube Current Modulation (TCM) functionality being used in most CT examinations to achieve consistent clinical image quality independent of patient size, follow-up of radiation exposure and optimization is not straightforward with the CTDI and DLP metrics.

Estimation of the SSDE is done in two steps, first determination of patient size from the actual CT images, either the localizer radiograph(s) or axial images. When patient size is known, the Report of AAPM Task Group 204 supplies conversion factors per patient size to determine a correction factor, f, which is used together with the CTDI to determine the SSDE, i.e. SSDE = f x CTDI_vol (mGy).

The physical patient size, in cm, is easily determined manually from a patient image, e.g. by a measurement tool in PACS. However, this is not feasible in large-scale optimization and clinical audit projects. Furthermore, as detailed in the Report of AAPM Task Group 220,[2] a more robust metric for estimating patient exposure via the SSDE is the Water Equivalent Diameter (WED), which determines patient size as equivalent thickness of X-ray beam attenuation in water. The WED is particularly suited for the for making the SSDE robust for comparisons of patient exposure between different anatomical regions, e.g. thorax and abdomen, where physical patient size make be very similar but the attenuation properties will vary considerably due to tissue density.

The WED cannot be determined manually from patient images, nor is it feasible to use the less robust metric given by patient physical size in large-scale projects. In this work we therefore present results from a software solution, which is part of the REMbox framework (Dicom Port AB, Umeå, Sweden), for determining the SSDE via automated image segmentation. Furthermore, when working in the image domain other quality assurance related metrics can be determined, e.g. evaluation of patient centering in CT examinations. Patient centering is something that has been discussed for a long time in optimization of CT examinations, due to complex relations between bow-tie filter X-ray beam shaping and TCM, which have optimal functionality with regard to both clinical image quality and patient exposure if the patient is perfectly centered in the CT gantry.