MO-E-17A-05: Individualized Patient Dosimetry in CT Using the Patient Dose (PATDOSE) Algorithm




Radiation dose to the patient undergoing a CT examination has been the focus of many recent studies. While CTDIvol and SSDE-based methods are important tools for patient dose management, the CT image data provides important information with respect to CT dose and its distribution. Coupled with the known geometry and output factors (kV, mAs, pitch, etc.) of the CT scanner, the CT dataset can be used directly for computing absorbed dose.


The HU numbers in a patient's CT data set can be converted to linear attenuation coefficients (LACs) with some assumptions. With this (PAT-DOSE) method, which is not Monte Carlo-based, the primary and scatter dose are computed separately. The primary dose is computed directly from the geometry of the scanner, x-ray spectrum, and the known patient LACs. Once the primary dose has been computed to all voxels in the patient, the scatter dose algorithm redistributes a fraction of the absorbed primary dose (based on the HU number of each source voxel), and the methods here invoke both tissue attenuation and absorption and solid angle geometry. The scatter dose algorithm can be run N times to include Nth-scatter redistribution. PAT-DOSE was deployed using simple PMMA phantoms, to validate its performance against Monte Carlo-derived dose distributions.


Comparison between PAT-DOSE and MCNPX primary dose distributions showed excellent agreement for several scan lengths. The 1st-scatter dose distributions showed relatively higher-amplitude, long-range scatter tails for the PAT-DOSE algorithm then for MCNPX simulations.


The PAT-DOSE algorithm provides a fast, deterministic assessment of the 3-D dose distribution in CT, making use of scanner geometry and the patient image data set. The preliminary implementation of the algorithm produces accurate primary dose distributions however achieving scatter distribution agreement is more challenging. Addressing the polyenergetic x-ray spectrum and spatially dependent scatter fractions will improve algorithm accuracy.

Funding Support: UC Davis Clinical and Translational Science Center (CTSC) Award; NIH IMSD Student Fellowship; Saxon Student Fellowship

Disclosure: PATENT Royalties from Samsung for dosimetry algorithm