@article{sahbaee_abadi_sanders_becchetti_zhang_agasthya_segars_samei_2016, title={A technique for multi-dimensional optimization of radiation dose, contrast dose, and image quality in CT imaging}, volume={9783}, ISSN={["1996-756X"]}, DOI={10.1117/12.2216516}, abstractNote={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%).}, journal={MEDICAL IMAGING 2016: PHYSICS OF MEDICAL IMAGING}, author={Sahbaee, Pooyan and Abadi, Ehsan and Sanders, Jeremiah and Becchetti, Marc and Zhang, Yakun and Agasthya, Greeshma and Segars, Paul and Samei, Ehsan}, year={2016} }
 @article{robins_solomon_sahbaee_samei_2016, title={Development and Comparison of Projection and Image Space 3D Nodule Insertion Techniques}, volume={9783}, ISSN={["0277-786X"]}, DOI={10.1117/12.2216930}, abstractNote={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.}, journal={MEDICAL IMAGING 2016: PHYSICS OF MEDICAL IMAGING}, author={Robins, Marthony and Solomon, Justin and Sahbaee, Pooyan and Samei, Ehsan}, year={2016} }
 @article{sahbaee_robins_solomon_samei_2016, title={Development of a Hausdorff Distance based 3D quantification technique to evaluate the CT imaging system impact on depiction of lesion morphology}, volume={9783}, ISSN={["0277-786X"]}, DOI={10.1117/12.2216503}, abstractNote={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.}, journal={MEDICAL IMAGING 2016: PHYSICS OF MEDICAL IMAGING}, author={Sahbaee, Pooyan and Robins, Marthony and Solomon, Justin and Samei, Ehsan}, year={2016} }
 @article{fu_tian_sahbaee_zhang_segars_samei_2016, title={Organ dose conversion coefficients for tube current modulated CT protocols for an adult population}, volume={9783}, ISSN={["1996-756X"]}, DOI={10.1117/12.2217271}, abstractNote={In computed tomography (CT), patient-specific organ dose can be estimated using pre-calculated organ dose conversion coefficients (organ dose normalized by CTDIvol, h factor) database, taking into account patient size and scan coverage. The conversion coefficients have been previously estimated for routine body protocol classes, grouped by scan coverage, across an adult population for fixed tube current modulated CT. The coefficients, however, do not include the widely utilized tube current (mA) modulation scheme, which significantly impacts organ dose. This study aims to extend the h factors and the corresponding dose length product (DLP) to create effective dose conversion coefficients (k factor) database incorporating various tube current modulation strengths. Fifty-eight extended cardiac-torso (XCAT) phantoms were included in this study representing population anatomy variation in clinical practice. Four mA profiles, representing weak to strong mA dependency on body attenuation, were generated for each phantom and protocol class. A validated Monte Carlo program was used to simulate the organ dose. The organ dose and effective dose was further normalized by CTDIvol and DLP to derive the h factors and k factors, respectively. The h factors and k factors were summarized in an exponential regression model as a function of body size. Such a population-based mathematical model can provide a comprehensive organ dose estimation given body size and CTDIvol. The model was integrated into an iPhone app XCATdose version 2, enhancing the 1st version based upon fixed tube current modulation. With the organ dose calculator, physicists, physicians, and patients can conveniently estimate organ dose.}, journal={MEDICAL IMAGING 2016: PHYSICS OF MEDICAL IMAGING}, author={Fu, Wanyi and Tian, Xiaoyu and Sahbaee, Pooyan and Zhang, Yakun and Segars, William Paul and Samei, Ehsan}, year={2016} }
 @article{sahbaee_li_segars_marin_nelson_samei_2015, title={Determination of contrast media administration to achieve a targeted contrast enhancement in CT}, volume={9412}, ISSN={["1996-756X"]}, DOI={10.1117/12.2082261}, abstractNote={Contrast enhancement is a key component of CT imaging and offer opportunities for optimization. The design and optimization of new techniques however requires orchestration with the scan parameters and further a methodology to relate contrast enhancement and injection function. In this study, we used such a methodology to develop a method, 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 the scan timing to provide more consistency in the way that the 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.}, journal={MEDICAL IMAGING 2015: PHYSICS OF MEDICAL IMAGING}, author={Sahbaee, Pooyan and Li, Yuan and Segars, Paul P. and Marin, Daniele and Nelson, Rendon and Samei, Ehsan}, year={2015} }
 @article{lakshmanan_kapadia_sahbaee_wolter_harrawood_brady_samei_2014, title={An X-ray scatter system for material identification in cluttered objects: A Monte Carlo simulation study}, volume={335}, ISSN={["1872-9584"]}, DOI={10.1016/j.nimb.2014.05.021}, abstractNote={The analysis of X-ray scatter patterns has been demonstrated as an effective method of identifying specific materials in mixed object environments, for both biological and non-biological applications. Here we describe an X-ray scatter imaging system for material identification in cluttered objects and investigate its performance using a large-scale Monte Carlo simulation study of one-thousand objects containing a broad array of materials. The Geant4 Monte Carlo source code for Rayleigh scatter physics was modified to model coherent scatter diffraction in bulk materials based on experimentally measured form factors for 33 materials. The simulation was then used to model coherent scatter signals from a variety of targets and clutter (background) materials in one thousand randomized objects. The resulting scatter images were used to characterize four parameters of the imaging system that affected its ability to identify target materials: (a) the arrangement of materials in the object, (b) clutter attenuation, (c) type of target material, and (d) the X-ray tube current. We found that the positioning of target materials within the object did not significantly affect their detectability; however, a strong negative correlation was observed between the target detectability and the clutter attenuation of the object. The imaging signal was also found to be relatively invariant to increases in X-ray tube current above 1 mAs for most materials considered in the study. This work is the first Monte Carlo study to our knowledge of a large population of cluttered object of an X-ray scatter imaging system for material identification and lays the foundation for large-scale studies of the effectiveness of X-ray scatter imaging systems for material identification in complex samples.}, journal={NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION B-BEAM INTERACTIONS WITH MATERIALS AND ATOMS}, author={Lakshmanan, Manu N. and Kapadia, Anuj J. and Sahbaee, Pooyan and Wolter, Scott D. and Harrawood, Brian P. and Brady, David and Samei, Ehsan}, year={2014}, month={Sep}, pages={31–38} }
 @article{sahbaee_segars_samei_2014, title={Patient-based estimation of organ dose for a population of 58 adult patients across 13 protocol categories}, volume={41}, ISSN={["2473-4209"]}, DOI={10.1118/1.4883778}, abstractNote={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 patient's body diameter (r > 0.85). The exponential relationship between effective dose and patient's 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.}, number={7}, journal={MEDICAL PHYSICS}, author={Sahbaee, Pooyan and Segars, W. Paul and Samei, Ehsan}, year={2014}, month={Jul} }