Pooyan Sahbaee

Patient‐based estimation of organ dose for a population of 58 adult patients across 13 protocol categories

PURPOSE This study aimed to provide a comprehensive patient-specific organ dose estimation across a multiplicity of computed tomography (CT) examination protocols. METHODS A validated Monte Carlo program was employed to model a common CT system (LightSpeed VCT, GE Healthcare). The organ and effective doses were estimated from 13 commonly used body and neurological CT examination. The dose estimation was performed on 58 adult computational extended cardiac-torso phantoms (35 male, 23 female, mean age 51.5 years, mean weight 80.2 kg). The organ dose normalized by CTDIvol (h factor) and effective dose normalized by the dose length product (DLP) (k factor) were calculated from the results. A mathematical model was derived for the correlation between the h and k factors with the patient size across the protocols. Based on this mathematical model, a dose estimation iPhone operating system application was designed and developed to be used as a tool to estimate dose to the patients for a variety of routinely used CT examinations. RESULTS The organ dose results across all the protocols showed an exponential decrease with patient body size. The correlation was generally strong for the organs which were fully or partially located inside the scan coverage (Pearson sample correlation coefficient (r) of 0.49). The correlation was weaker for organs outside the scan coverage for which distance between the organ and the irradiation area was a stronger predictor of dose to the organ. For body protocols, the effective dose before and after normalization by DLP decreased exponentially with increasing patients body diameter (r > 0.85). The exponential relationship between effective dose and patients body diameter was significantly weaker for neurological protocols (r < 0.41), where the trunk length was a slightly stronger predictor of effective dose (0.15 < r < 0.46). CONCLUSIONS While the most accurate estimation of a patient dose requires specific modeling of the patient anatomy, a first order approximation of organ and effective doses from routine CT scan protocols can be reasonably estimated using size specific factors. Estimation accuracy is generally poor for organ outside the scan range and for neurological protocols. The dose calculator designed in this study can be used to conveniently estimate and report the dose values for a patient across a multiplicity of CT scan protocols.

The Effect of Contrast Material on Radiation Dose at CT: Part II. A Systematic Evaluation across 58 Patient Models

Purpose To estimate the radiation dose as a result of contrast medium administration in a typical abdominal computed tomographic (CT) examination across a library of contrast material-enhanced computational patient models. Materials and Methods In part II of this study, first, the technique described in part I of this study was applied to enhance the extended cardiac-torso models with patient-specific iodine-time profiles reflecting the administration of contrast material. Second, the patient models were deployed to assess the patient-specific organ dose as a function of time in a typical abdominal CT examination using Monte Carlo simulation. In this hypothesis-generating study, organ dose refers to the total energy deposited in the unit mass of the tissue inclusive of iodine. Third, a study was performed as a strategy to anticipate the biologically relevant dose (absorbed dose to tissue) in highly perfused organs such as the liver and kidney. The time-varying organ-dose increment values relative to those for unenhanced CT examinations were reported. Results The results from the patient models subjected to the injection protocol indicated up to a total 53%, 30%, 35%, 54%, 27%, 18%, 17%, and 24% increase in radiation dose delivered to the heart, spleen, liver, kidneys, stomach, colon, small intestine, and pancreas, respectively. The biologically relevant dose increase with respect to the dose at an unenhanced CT examination was in the range of 0%-18% increase for the liver and 27% for the kidney across 58 patient models. Conclusion The administration of contrast medium increases the total radiation dose. However, radiation dose, while relevant to be included in estimating the risk associated with contrast-enhanced CT, may still not fully characterize the total biologic effects. Therefore, given the fact that many CT diagnostic decisions would be impossible without the use of iodine, this study suggests the need to consider the effect of iodinated contrast material on the organ doses to patients undergoing CT studies when designing CT protocols.

Techniques for virtual lung nodule insertion: volumetric and morphometric comparison of projection-based and image-based methods for quantitative CT

Virtual nodule insertion paves the way towards the development of standardized databases of hybrid CT images with known lesions. The purpose of this study was to assess three methods (an established and two newly developed techniques) for inserting virtual lung nodules into CT images. Assessment was done by comparing virtual nodule volume and shape to the CT-derived volume and shape of synthetic nodules. 24 synthetic nodules (three sizes, four morphologies, two repeats) were physically inserted into the lung cavity of an anthropomorphic chest phantom (KYOTO KAGAKU). The phantom was imaged with and without nodules on a commercial CT scanner (SOMATOM Definition Flash, Siemens) using a standard thoracic CT protocol at two dose levels (1.4 and 22 mGy CTDIvol). Raw projection data were saved and reconstructed with filtered back-projection and sinogram affirmed iterative reconstruction (SAFIRE, strength 5) at 0.6 mm slice thickness. Corresponding 3D idealized, virtual nodule models were co-registered with the CT images to determine each nodules location and orientation. Virtual nodules were voxelized, partial volume corrected, and inserted into nodule-free CT data (accounting for system imaging physics) using two methods: projection-based Technique A, and image-based Technique B. Also a third Technique C based on cropping a region of interest from the acquired image of the real nodule and blending it into the nodule-free image was tested. Nodule volumes were measured using a commercial segmentation tool (iNtuition, TeraRecon, Inc.) and deformation was assessed using the Hausdorff distance. Nodule volumes and deformations were compared between the idealized, CT-derived and virtual nodules using a linear mixed effects regression model which utilized the mean, standard deviation, and coefficient of variation ([Formula: see text], [Formula: see text] and [Formula: see text] of the regional Hausdorff distance. Overall, there was a close concordance between the volumes of the CT-derived and virtual nodules. Percent differences between them were less than 3% for all insertion techniques and were not statistically significant in most cases. Correlation coefficient values were greater than 0.97. The deformation according to the Hausdorff distance was also similar between the CT-derived and virtual nodules with minimal statistical significance in the ([Formula: see text]) for Techniques A, B, and C. This study shows that both projection-based and image-based nodule insertion techniques yield realistic nodule renderings with statistical similarity to the synthetic nodules with respect to nodule volume and deformation. These techniques could be used to create a database of hybrid CT images containing nodules of known size, location and morphology.

Determination of contrast media administration to achieve a targeted contrast enhancement in computed tomography.

Abstract. Contrast enhancement is a key component of computed tomography (CT) imaging and offers opportunities for optimization. The design and optimization of techniques, however, require orchestration with the scan parameters and, further, a methodology to relate contrast enhancement and injection function. We used such a methodology to develop a method, the analytical inverse method, to predict the required injection function to achieve a desired contrast enhancement in a given organ by incorporation of a physiologically based compartmental model. The method was evaluated across 32 different target contrast enhancement functions for aorta, kidney, stomach, small intestine, and liver. The results exhibited that the analytical inverse method offers accurate performance with error in the range of 10% deviation between the predicted and desired organ enhancement curves. However, this method is incapable of predicting the injection function based on the liver enhancement. The findings of this study can be useful in optimizing contrast medium injection function as well as scan timing to provide more consistency in the way contrast-enhanced CT examinations are performed. To our knowledge, this work is one of the first attempts to predict the contrast material injection function for a desired organ enhancement curve.

SU-C-12A-03: The Impact of Contrast Medium On Radiation Dose in CT: A Systematic Evaluation Across 58 Patient Models

PURPOSE To assess the effect of contrast medium on radiation dose as a function of time via Monte Carlo simulation from the liver CT scan across a library of 5D XCAT models METHODS: A validated Monte Carlo simulation package (PENELOPE) was employed to model a CT system (LightSpeed 64 VCT, GE Healthcare). The radiation dose was estimated from a common abdomen CT examination. The dose estimation was performed on a library of adult extended cardiac-torso (5D XCAT) phantoms (35 male, 23 female, mean age 51.5 years, mean weight 80.2 kg). The 5D XCAT models were created based on patient-specific iodine concentration-time results from our computational contrast medium propagation model for different intravenous injection protocols. To enable a dynamic estimation of radiation dose, each organ in the model was assigned to its own time-concentration curve via the PENELOPE package, material.exe. Using the Monte Carlo, for each scan time point after the injection, 80 million photons were initiated and tracked through the phantoms. Finally, the dose to the liver was tallied from the deposited energy. RESULTS Monte Carlo simulation results of radiation dose delivered to the liver from the XCAT models indicated up to 30% increase in dose for different time after the administration of contrast medium. CONCLUSION The contrast enhancement is employed in over 60% of imaging modalities, which not only remarkably affects the CT image quality, but also increases the radiation dose by as much as 70%. The postinjection multiple acquisition in several enhanced CT protocols, makes the radiation dose increment through the use of contrast medium, an inevitable factor in optimization of these protocols. The relationship between radiation dose and injected contrast medium as a function of time studied in this work allows optimization of contrast administration for vulnerable individuals.

Development and comparison of projection and image space 3D nodule insertion techniques

This study aimed to develop and compare two methods of inserting computerized virtual lesions into CT datasets. 24 physical (synthetic) nodules of three sizes and four morphologies were inserted into an anthropomorphic chest phantom (LUNGMAN, KYOTO KAGAKU). The phantom was scanned (Somatom Definition Flash, Siemens Healthcare) with and without nodules present, and images were reconstructed with filtered back projection and iterative reconstruction (SAFIRE) at 0.6 mm slice thickness using a standard thoracic CT protocol at multiple dose settings. Virtual 3D CAD models based on the physical nodules were virtually inserted (accounting for the system MTF) into the nodule-free CT data using two techniques. These techniques include projection-based and image-based insertion. Nodule volumes were estimated using a commercial segmentation tool (iNtuition, TeraRecon, Inc.). Differences were tested using paired t-tests and R2 goodness of fit between the virtually and physically inserted nodules. Both insertion techniques resulted in nodule volumes very similar to the real nodules (<3% difference) and in most cases the differences were not statistically significant. Also, R2 values were all <0.97 for both insertion techniques. These data imply that these techniques can confidently be used as a means of inserting virtual nodules in CT datasets. These techniques can be instrumental in building hybrid CT datasets composed of patient images with virtually inserted nodules.

MO-E-17A-02: Incorporation of Contrast Medium Dynamics in Anthropomorphic Phantoms: The Advent of 5D XCAT Models

PURPOSE To develop a unique method to incorporate the dynamics of contrast-medium propagation into the anthropomorphic phantom, to generate a five-dimensional (5D) patient model for multimodality imaging studies. METHODS A compartmental model of blood circulation network within the body was embodied into an extended cardiac-torso (4D-XCAT) patient model. To do so, a computational physiologic model of the human cardiovascular system was developed which includes a series of compartments representing heart, vessels, and organs. Patient-specific cardiac output and blood volume were used as inputs influenced by the weight, height, age, and gender of the patients model. For a given injection protocol and given XCAT model, the contrast-medium transmission within the body was described by a series of mass balance differential equations, the solutions to which provided the contrast enhancement-time curves for each organ; thereby defining the tissue materials including the contrastmedium within the XCAT model. A library of time-dependent organ materials was then defined. Each organ in each voxelized 4D-XCAT phantom was assigned to a corresponding time-varying material to create the 5D-XCAT phantom in which the fifth dimension is blood/contrast-medium within the temporal domain. RESULTS The model effectively predicts the time-varying concentration behavior of various contrast-medium administration in each organ for different patient models as function of patient size (weight/height) and different injection protocol factors (injection rate and pattern, iodine concentration or volume). The contrast enhanced XCAT patient models was developed based on the concentration of iodine as a function of time after injection. CONCLUSION Majority of medical imaging systems take advantage of contrast-medium administration in terms of better image quality, the effect of which was ignored in previous optimization studies. The study enables a comprehensive optimization of contrast administration both in terms of image quality and radiation dose, and can be used in different modalities such as CT, MRI, and ultrasound.

Effect of Iodine-based Contrast Material on Radiation Dose at CT

From Shivani Pahwa, MD,* Nicholas K. Schiltz, PhD,† Lee E. Ponsky, MD,‡ Ziang Lu, BA,§ Mark A. Griswold, PhD,*|| Vikas Gulani, MD, PhD*‡|| Departments of Radiology* and Urology,‡ University Hospitals Cleveland Medical Center, Cleveland, Ohio Departments of Population & Quantitative Health Sciences† and Biomedical Engineering,|| Case Western Reserve University, 10900 Euclid Ave, Bolwell B120, Cleveland, OH 44106-0500 e-mail: vikas@case.edu Case Western Reserve University School of Medicine, Cleveland, Ohio§

A technique for multi-dimensional optimization of radiation dose, contrast dose, and image quality in CT imaging

The purpose of this study was to substantiate the interdependency of image quality, radiation dose, and contrast material dose in CT towards the patient-specific optimization of the imaging protocols. The study deployed two phantom platforms. First, a variable sized phantom containing an iodinated insert was imaged on a representative CT scanner at multiple CTDI values. The contrast and noise were measured from the reconstructed images for each phantom diameter. Linearly related to iodine-concentration, contrast to noise ratio (CNR), was calculated for different iodine-concentration levels. Second, the analysis was extended to a recently developed suit of 58 virtual human models (5D-XCAT) with added contrast dynamics. Emulating a contrast-enhanced abdominal image procedure and targeting a peak-enhancement in aorta, each XCAT phantom was “imaged” using a CT simulation platform. 3D surfaces for each patient/size established the relationship between iodine-concentration, dose, and CNR. The Sensitivity of Ratio (SR), defined as ratio of change in iodine-concentration versus dose to yield a constant change in CNR was calculated and compared at high and low radiation dose for both phantom platforms. The results show that sensitivity of CNR to iodine concentration is larger at high radiation dose (up to 73%). The SR results were highly affected by radiation dose metric; CTDI or organ dose. Furthermore, results showed that the presence of contrast material could have a profound impact on optimization results (up to 45%).

Development of a Hausdorff distance based 3D quantification technique to evaluate the CT imaging system impact on depiction of lesion morphology

The purpose of this study was to develop a 3D quantification technique to assess the impact of imaging system on depiction of lesion morphology. Regional Hausdorff Distance (RHD) was computed from two 3D volumes: virtual mesh models of synthetic nodules or “virtual nodules” and CT images of physical nodules or “physical nodules”. The method can be described in following steps. First, the synthetic nodule was inserted into anthropomorphic Kyoto thorax phantom and scanned in a Siemens scanner (Flash). Then, nodule was segmented from the image. Second, in order to match the orientation of the nodule, the digital models of the “virtual” and “physical” nodules were both geometrically translated to the origin. Then, the “physical” was gradually rotated at incremental 10 degrees. Third, the Hausdorff Distance was calculated from each pair of “virtual” and “physical” nodules. The minimum HD value represented the most matching pair. Finally, the 3D RHD map and the distribution of RHD were computed for the matched pair. The technique was scalarized using the FWHM of the RHD distribution. The analysis was conducted for various shapes (spherical, lobular, elliptical, and speculated) of nodules. The calculated FWHM values of RHD distribution for the 8-mm spherical, lobular, elliptical, and speculated “virtual” and “physical” nodules were 0.23, 0.42, 0.33, and 0.49, respectively.