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The Relationship between Organ Dose and Patients Size in Multidetector Computed Tomography (MDCT) Scans Utilizing Tube Current Modulation (TCM)


Computed Tomography (CT) has been one of the leading imaging modalities in today's practice of Radiology. Since its introduction in 1970s, its unique tomographic capability has not only prevented countless number of unnecessary surgeries but also saved lives by early detection of disease. Radiation dose from CT has been estimated to contribute to almost 50% of all medical radiation exposures. Concerns about radiation-induced carcinogenesis have resulted in efforts that encourage monitoring and reporting radiation dose from CT examinations. It has been suggested that the most appropriate quantity for assessing risk of carcinogenesis from x-ray imaging procedures is the radiation dose to individual patients. Currently employed dose metrics used to report patient dose are CTDIvol and DLP, neither of which is patient-specific dose, let alone dose to individual organs.

CTDIvol is dose to a homogenous cylindrical phantom, which is defined for fixed tube current CT exams. With the implementation of Tube Current Modulation (TCM) feature in almost all clinical CT protocols as an intended means for dose reduction, while maintaining an appropriate diagnostic image quality, CTDIvol definition was standardized across scanners to reflect dose to CTDI phantom based on the average tube current across the entire scan length. Depending on the type of CT exam, the average tube current used to report a CTDIvol value may or may not represent the actual tube current at a specific table location. In addition to not taking into account variation of the tube current across a single exam, CTDIvol is size-independent, i.e. patients with different sizes have the same CTDIvol value if scanned using the same imaging parameters.

To adjust CTDIvol for size, AAPM Task Group 204 was established and subsequently published a report containing conversions as a function of effective diameter which can be applied to scanner-reported CTDIvolto adjust for patient size. However, the generated conversion factors were based on fixe tube current measurements and Monte Carlo simulations and failed to take into account TCM. Additionally, the size metric used in TG 204 was entirely based on patients' physical dimensions and does not take into account variations in composition and density among patients, let alone within a single patient; i.e. differences between chest and abdomen in terms of attenuation properties could not be explained with a simple measure of dimension such as effective diameter. Instead attenuation-based metrics need to be implemented to explain these differences.

The overall purpose of this dissertation was to improve organ dose estimation from Computed Tomography exams by: (a) taking into account the commonly used feature in CT protocols, Tube Current Modulation (TCM), (b) employing a more appropriate way of reporting CTDI for TCM exams and (c) using a patient size descriptor capable of describing the attenuation properties of individual patients.

For this dissertation a validated Monte Carlo based MDCT model capable of simulating organ dose was utilized to estimate organ dose to voxelized patient models undergoing tube current modulated CT examinations. Both detailed TCM and z-axis-only modulation information were used in the simulations in case raw projection data was not accessible. In addition to simulated organ doses different CTDIvol values based on the type of patient model, abdomen versus chest, were calculated. These CTDIvol values included regional CTDIvol,regional and organ-specific CTDIvol,organ along with scanner-reported CTDIvol, referred to as global CTDIvol,global. Furthermore different size metrics, such as effective diameter and attenuation-based metrics, were calculated for every axial CT image within a series and averaged corresponding to the same regions and images used to calculated the above mentioned regional and organ-specific CTDIvol values.

Using an approach similar to previous efforts and AAPM Task Group 204, the estimated organ doses were normalized by CT Dose Index (CTDIvol) values. However, for TCM scans normalized organ doses by CTDIvol,globalwere observed to not have a strong correlation with patient size. This result was quite different from that observed previously for fixed tube current exams. In contrast, when regional descriptors of scanner output (CTDIvol,regional and CTDIvol,organ) were used as a modified normalization factor, the results demonstrated significantly improved correlations with patient size.

Additionally, an attenuation-based patient size metric, the water equivalent diameter (WED), was investigated in terms of its ability to describe the effects of patient size on organ dose. WED was compared to the size metric introduced in TG204, effective diameter, which is based only on patient morphology (e.g. perimeter) and not on attenuation. Results of the comparisons demonstrated no statistically significant improvements of correlation between normalized organ doses and size metric once WED was utilized, except for normalized lung dose. Although there were no statistically significant improvements, the correlation of determination, R2, increased for almost all organs once WED was employed. Similarly, there was no statistically significant difference between differently averaged size metrics, i.e. global average of size metrics versus regional average of size metrics, except for normalized lung dose, which showed a statistically significant improvement in R2 once a regional WED was employed as a size metric compared to global WED.

Using improved normalization quantity and patient size metric for tube current modulated CT examinations, Generalized Linear Models were used to generate a predictive model capable of estimating dose from TCM exams using regional CTDIvol) and WED. Different models based on scanners and organs were generated to establish the level of accuracy of each model and to determine the level of specification needed to achieve best organ dose estimates. Additionally, models with different response variables, normalized organ dose versus actual organ dose, were explored and compared.

When tested using a separate test set, investigated models with regional CTDIvol) either as a predictor or normalization factor resulted in very similar results while models created with global CTDIvol) as a predictor resulted in underestimation of organ dose across all organs. Additionally, it was shown that a model based on pooled data was not significantly different than scanner and organ-specific models since the pooled-data model resulted in employing significant categorical predictors such as scanners and organs. This observation confirms the fact that TCM algorithms are different across scanners and regional CTDIvol) is not capable of eliminating these differences, but it can eliminate differences among TCM functions across a single CT scanner. Predictive organ dose estimates using generated models resulted in a mean percent difference of less than 10% when compared to actual Monte Carlo simulated organ doses.

The improvement of the newly generated model was also compared against currently used dose metrics, CTDIvol) , SSDE, and ImPACT. While comparisons with actual Monte Carlo simulated organ doses resulted in statistically significant differences between conventional dose metrics and simulated organ doses, comparisons with organ estimates from the newly developed model resulted in no difference from Monte Carlo simulated organ doses.

This work demonstrated the feasibility of estimating organ dose from tube current modulated scans from three major CT manufacturers using an improved descriptor of tube current modulated scans as normalization quantity or predictor and a patient size metric based on patients attenuation properties.

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