Academic Appointments

Honors & Awards

  • K99/R00 Pathway to Independence Award, National Institute of Health (August 2013)
  • Jack Fowler Junior Investigator Award, American Association of Physicists in Medicine (August 2013)
  • AAPM Research Seed Funding Grant Award, American Association of Physicists in Medicine (July 2012)
  • Siemens Excellence Award, Association of Industry and Czech Universities and Siemens (December 2008)
  • Sylvia Fedoruk Prize, Canadian Organization of Medical Physicists (June 2008)
  • Young Investigator's Award - 3rd place, International Conference on the Use of Computers in Radiation Therapy (July 2007)

Professional Education

  • PhD, McGill University (2009)
  • BSc, Czech Technical University (2003)

Research & Scholarship

Current Research and Scholarly Interests

I am interested in ) treatment planning for small animal radiotherapy, 2) x-ray fluorescence CT (XFCT) imaging for high-sensitivity molecular imaging, and 3) novel concept of radiation therapy with very high-energy electron (VHEE) beams.


2014-15 Courses


Journal Articles

  • Proton-induced x-ray fluorescence CT imaging. Medical physics Bazalova-Carter, M., Ahmad, M., Matsuura, T., Takao, S., Matsuo, Y., Fahrig, R., Shirato, H., Umegaki, K., Xing, L. 2015; 42 (2): 900-?


    To demonstrate the feasibility of proton-induced x-ray fluorescence CT (pXFCT) imaging of gold in a small animal sized object by means of experiments and Monte Carlo (MC) simulations.First, proton-induced gold x-ray fluorescence (pXRF) was measured as a function of gold concentration. Vials of 2.2 cm in diameter filled with 0%-5% Au solutions were irradiated with a 220 MeV proton beam and x-ray fluorescence induced by the interaction of protons, and Au was detected with a 3 × 3 mm(2) CdTe detector placed at 90° with respect to the incident proton beam at a distance of 45 cm from the vials. Second, a 7-cm diameter water phantom containing three 2.2-diameter vials with 3%-5% Au solutions was imaged with a 7-mm FWHM 220 MeV proton beam in a first generation CT scanning geometry. X-rays scattered perpendicular to the incident proton beam were acquired with the CdTe detector placed at 45 cm from the phantom positioned on a translation/rotation stage. Twenty one translational steps spaced by 3 mm at each of 36 projection angles spaced by 10° were acquired, and pXFCT images of the phantom were reconstructed with filtered back projection. A simplified geometry of the experimental data acquisition setup was modeled with the MC TOPAS code, and simulation results were compared to the experimental data.A linear relationship between gold pXRF and gold concentration was observed in both experimental and MC simulation data (R(2) > 0.99). All Au vials were apparent in the experimental and simulated pXFCT images. Specifically, the 3% Au vial was detectable in the experimental [contrast-to-noise ratio (CNR) = 5.8] and simulated (CNR = 11.5) pXFCT image. Due to fluorescence x-ray attenuation in the higher concentration vials, the 4% and 5% Au contrast were underestimated by 10% and 15%, respectively, in both the experimental and simulated pXFCT images.Proton-induced x-ray fluorescence CT imaging of 3%-5% gold solutions in a small animal sized water phantom has been demonstrated for the first time by means of experiments and MC simulations.

    View details for DOI 10.1118/1.4906169

    View details for PubMedID 25652502

  • Treatment planning for radiotherapy with very high-energy electron beams and comparison of VHEE and VMAT plans. Medical physics Bazalova-Carter, M., Qu, B., Palma, B., Hårdemark, B., Hynning, E., Jensen, C., Maxim, P. G., Loo, B. W. 2015; 42 (5): 2615


    The aim of this work was to develop a treatment planning workflow for rapid radiotherapy delivered with very high-energy electron (VHEE) scanning pencil beams of 60-120 MeV and to study VHEE plans as a function of VHEE treatment parameters. Additionally, VHEE plans were compared to clinical state-of-the-art volumetric modulated arc therapy (VMAT) photon plans for three cases.VHEE radiotherapy treatment planning was performed by linking EGSnrc Monte Carlo (MC) dose calculations with inverse treatment planning in a research version of RayStation. In order to study the effect of VHEE treatment parameters on VHEE dose distributions, a matlab graphical user interface (GUI) for calculation of VHEE MC pencil beam doses was developed. Through the GUI, pediatric case MC simulations were run for a number of beam energies (60, 80, 100, and 120 MeV), number of beams (13, 17, and 36), pencil beam spot (0.1, 1.0, and 3.0 mm) and grid (2.0, 2.5, and 3.5 mm) sizes, and source-to-axis distance, SAD (40 and 50 cm). VHEE plans for the pediatric case calculated with the different treatment parameters were optimized and compared. Furthermore, 100 MeV VHEE plans for the pediatric case, a lung, and a prostate case were calculated and compared to the clinically delivered VMAT plans. All plans were normalized such that the 100% isodose line covered 95% of the target volume.VHEE beam energy had the largest effect on the quality of dose distributions of the pediatric case. For the same target dose, the mean doses to organs at risk (OARs) decreased by 5%-16% when planned with 100 MeV compared to 60 MeV, but there was no further improvement in the 120 MeV plan. VHEE plans calculated with 36 beams outperformed plans calculated with 13 and 17 beams, but to a more modest degree (<8%). While pencil beam spacing and SAD had a small effect on VHEE dose distributions, 0.1-3 mm pencil beam sizes resulted in identical dose distributions. For the 100 MeV VHEE pediatric plan, OAR doses were up to 70% lower and the integral dose was 33% lower for VHEE compared to 6 MV VMAT. Additionally, VHEE conformity indices (CI100 = 1.09 and CI50 = 4.07) were better than VMAT conformity indices (CI100 = 1.30 and CI50 = 6.81). The 100 MeV VHEE lung plan resulted in mean dose decrease to all OARs by up to 27% for the same target coverage compared to the clinical 6 MV flattening filter-free (FFF) VMAT plan. The 100 MeV prostate plan resulted in 3% mean dose increase to the penile bulb and the urethra, but all other OAR mean doses were lower compared to the 15 MV VMAT plan. The lung case CI100 and CI50 conformity indices were 3% and 8% lower, respectively, in the VHEE plan compared to the VMAT plan. The prostate case CI100 and CI50 conformity indices were 1% higher and 8% lower, respectively, in the VHEE plan compared to the VMAT plan.The authors have developed a treatment planning workflow for MC dose calculation of pencil beams and optimization for treatment planning of VHEE radiotherapy. The authors have demonstrated that VHEE plans resulted in similar or superior dose distributions for pediatric, lung, and prostate cases compared to clinical VMAT plans.

    View details for DOI 10.1118/1.4918923

    View details for PubMedID 25979053

  • Comparison of film measurements and Monte Carlo simulations of dose delivered with very high-energy electron beams in a polystyrene phantom MEDICAL PHYSICS Bazalova-Carter, M., Liu, M., Palma, B., Dunning, M., McCormick, D., Hemsing, E., Nelson, J., Jobe, K., Colby, E., Koong, A., Tantawi, S., Dolgashev, V., Maxim, P., Loo, B. 2015; 42 (4)
  • Optimized detector angular configuration increases the sensitivity of x-ray fluorescence computed tomography (XFCT) IEEE TRANSACTIONS ON MEDICAL IMAGING Ahmad, M., Bazalova-Carter, M., Fahrig, R., Xing, L. 2015
  • Order of Magnitude Sensitivity Increase in X-ray Fluorescence Computed Tomography (XFCT) Imaging With an Optimized Spectro-Spatial Detector Configuration: Theory and Simulation IEEE TRANSACTIONS ON MEDICAL IMAGING Ahmad, M., Bazalova, M., Xiang, L., Xing, L. 2014; 33 (5): 1119-1128


    The purpose of this study was to increase the sensitivity of XFCT imaging by optimizing the data acquisition geometry for reduced scatter X-rays. The placement of detectors and detector energy window were chosen to minimize scatter X-rays. We performed both theoretical calculations and Monte Carlo simulations of this optimized detector configuration on a mouse-sized phantom containing various gold concentrations. The sensitivity limits were determined for three different X-ray spectra: a monoenergetic source, a Gaussian source, and a conventional X-ray tube source. Scatter X-rays were minimized using a backscatter detector orientation (scatter direction > 110(°) to the primary X-ray beam). The optimized configuration simultaneously reduced the number of detectors and improved the image signal-to-noise ratio. The sensitivity of the optimized configuration was 10 μg/mL (10 pM) at 2 mGy dose with the mono-energetic source, which is an order of magnitude improvement over the unoptimized configuration (102 pM without the optimization). Similar improvements were seen with the Gaussian spectrum source and conventional X-ray tube source. The optimization improvements were predicted in the theoretical model and also demonstrated in simulations. The sensitivity of XFCT imaging can be enhanced by an order of magnitude with the data acquisition optimization, greatly enhancing the potential of this modality for future use in clinical molecular imaging.

    View details for DOI 10.1109/TMI.2014.2305101

    View details for Web of Science ID 000335379500010

    View details for PubMedID 24770916

  • L-shell x-ray fluorescence computed tomography (XFCT) imaging of Cisplatin PHYSICS IN MEDICINE AND BIOLOGY Bazalova, M., Ahmad, M., Pratx, G., Xing, L. 2014; 59 (1): 219-232


    X-ray fluorescence computed tomography (XFCT) imaging has been focused on the detection of K-shell x-rays. The potential utility of L-shell x-ray XFCT is, however, not well studied. Here we report the first Monte Carlo (MC) simulation of preclinical L-shell XFCT imaging of Cisplatin. We built MC models for both L- and K-shell XFCT with different excitation energies (15 and 30 keV for L-shell and 80 keV for K-shell XFCT). Two small-animal sized imaging phantoms of 2 and 4 cm diameter containing a series of objects of 0.6 to 2.7 mm in diameter at 0.7 to 16 mm depths with 10 to 250 µg mL(-1) concentrations of Pt are used in the study. Transmitted and scattered x-rays were collected with photon-integrating transmission detector and photon-counting detector arc, respectively. Collected data were rearranged into XFCT and transmission CT sinograms for image reconstruction. XFCT images were reconstructed with filtered back-projection and with iterative maximum-likelihood expectation maximization without and with attenuation correction. While K-shell XFCT was capable of providing an accurate measurement of Cisplatin concentration, its sensitivity was 4.4 and 3.0 times lower than that of L-shell XFCT with 15 keV excitation beam for the 2 cm and 4 cm diameter phantom, respectively. With the inclusion of excitation and fluorescence beam attenuation correction, we found that L-shell XFCT was capable of providing fairly accurate information of Cisplatin concentration distribution. With a dose of 29 and 58 mGy, clinically relevant Cisplatin Pt concentrations of 10 µg mg(-1) could be imaged with L-shell XFCT inside a 2 cm and 4 cm diameter object, respectively.

    View details for DOI 10.1088/0031-9155/59/1/219

    View details for Web of Science ID 000328549200011

  • Modality comparison for small animal radiotherapy: A simulation study MEDICAL PHYSICS Bazalova, M., Nelson, G., Noll, J. M., Graves, E. E. 2014; 41 (1)

    View details for DOI 10.1118/1.4842415

    View details for Web of Science ID 000329182200015

  • Modality comparison for small animal radiotherapy: a simulation study. Medical physics Bazalova, M., Nelson, G., Noll, J. M., Graves, E. E. 2014; 41 (1): 011710-?


    Small animal radiation therapy has advanced significantly in recent years. Whereas in the past dose was delivered using a single beam and a lead shield for sparing of healthy tissue, conformal doses can be now delivered using more complex dedicated small animal radiotherapy systems with image guidance. The goal of this paper is to investigate dose distributions for three small animal radiation treatment modalities.This paper presents a comparison of dose distributions generated by the three approaches-a single-field irradiator with a 200 kV beam and no image guidance, a small animal image-guided conformal system based on a modified microCT scanner with a 120 kV beam developed at Stanford University, and a dedicated conformal system, SARRP, using a 220 kV beam developed at Johns Hopkins University. The authors present a comparison of treatment plans for the three modalities using two cases: a mouse with a subcutaneous tumor and a mouse with a spontaneous lung tumor. A 5 Gy target dose was calculated using the EGSnrc Monte Carlo codes.All treatment modalities generated similar dose distributions for the subcutaneous tumor case, with the highest mean dose to the ipsilateral lung and bones in the single-field plan (0.4 and 0.4 Gy) compared to the microCT (0.1 and 0.2 Gy) and SARRP (0.1 and 0.3 Gy) plans. The lung case demonstrated that due to the nine-beam arrangements in the conformal plans, the mean doses to the ipsilateral lung, spinal cord, and bones were significantly lower in the microCT plan (2.0, 0.4, and 1.9 Gy) and the SARRP plan (1.5, 0.5, and 1.8 Gy) than in single-field irradiator plan (4.5, 3.8, and 3.3 Gy). Similarly, the mean doses to the contralateral lung and the heart were lowest in the microCT plan (1.5 and 2.0 Gy), followed by the SARRP plan (1.7 and 2.2 Gy), and they were highest in the single-field plan (2.5 and 2.4 Gy). For both cases, dose uniformity was greatest in the single-field irradiator plan followed by the SARRP plan due to the sensitivity of the lower energy microCT beam to target heterogeneities and image noise.The two treatment planning examples demonstrate that modern small animal radiotherapy techniques employing image guidance, variable collimation, and multiple beam angles deliver superior dose distributions to small animal tumors as compared to conventional treatments using a single-field irradiator. For deep-seated mouse tumors, however, higher-energy conformal radiotherapy could result in higher doses to critical organs compared to lower-energy conformal radiotherapy. Treatment planning optimization for small animal radiotherapy should therefore be developed to take full advantage of the novel conformal systems.

    View details for DOI 10.1118/1.4842415

    View details for PubMedID 24387502

  • X - ray luminescence and x - ray fluorescence computed tomography : new molecular imaging modalities IEEE Transactions on Medical Imaging Ahmad, M., Pratx, G., Bazalova, M., Xing, L. 2014
  • Development of XFCT imaging strategy for monitoring the spatial distribution of platinum-based chemodrugs: Instrumentation and phantom validation MEDICAL PHYSICS Kuang, Y., Pratx, G., Bazalova, M., Qian, J., Meng, B., Xing, L. 2013; 40 (3)


    Developing an imaging method to directly monitor the spatial distribution of platinum-based (Pt) drugs at the tumor region is of critical importance for early assessment of treatment efficacy and personalized treatment. In this study, the authors investigated the feasibility of imaging platinum (Pt)-based drug distribution using x-ray fluorescence (XRF, a.k.a. characteristic x ray) CT (XFCT).A 5-mm-diameter pencil beam produced by a polychromatic x-ray source equipped with a tungsten anode was used to stimulate emission of XRF photons from Pt drug embedded within a water phantom. The phantom was translated and rotated relative to the stationary pencil beam in a first-generation CT geometry. The x-ray energy spectrum was collected for 18 s at each position using a cadmium telluride detector. The spectra were then used for the K-shell XRF peak isolation and sinogram generation for Pt. The distribution and concentration of Pt were reconstructed with an iterative maximum likelihood expectation maximization algorithm. The capability of XFCT to multiplexed imaging of Pt, gadolinium (Gd), and iodine (I) within a water phantom was also investigated.Measured XRF spectrum showed a sharp peak characteristic of Pt with a narrow full-width at half-maximum (FWHM) (FWHMK?1 = 1.138 keV, FWHMK?2 = 1.052 keV). The distribution of Pt drug in the water phantom was clearly identifiable on the reconstructed XRF images. Our results showed a linear relationship between the XRF intensity of Pt and its concentrations (R(2) = 0.995), suggesting that XFCT is capable of quantitative imaging. A transmission CT image was also obtained to show the potential of the approach for providing attenuation correction and morphological information. Finally, the distribution of Pt, Gd, and I in the water phantom was clearly identifiable in the reconstructed images from XFCT multiplexed imaging.XFCT is a promising modality for monitoring the spatial distribution of Pt drugs. The technique may be useful in tailoring tumor treatment regimen in the future.

    View details for DOI 10.1118/1.4789917

    View details for Web of Science ID 000316369400003

    View details for PubMedID 23464279

  • First Demonstration of Multiplexed X-Ray Fluorescence Computed Tomography (XFCT) Imaging IEEE TRANSACTIONS ON MEDICAL IMAGING Kuang, Y., Pratx, G., Bazalova, M., Meng, B., Qian, J., Xing, L. 2013; 32 (2): 262-267


    Simultaneous imaging of multiple probes or biomarkers represents a critical step toward high specificity molecular imaging. In this work, we propose to utilize the element-specific nature of the X-ray fluorescence (XRF) signal for imaging multiple elements simultaneously (multiplexing) using XRF computed tomography (XFCT). A 5-mm-diameter pencil beam produced by a polychromatic X-ray source (150 kV, 20 mA) was used to stimulate emission of XRF photons from 2% (weight/volume) gold (Au), gadolinium (Gd), and barium (Ba) embedded within a water phantom. The phantom was translated and rotated relative to the stationary pencil beam in a first-generation CT geometry. The X-ray energy spectrum was collected for 18 s at each position using a cadmium telluride detector. The spectra were then used to isolate the K shell XRF peak and to generate sinograms for the three elements of interest. The distribution and concentration of the three elements were reconstructed with the iterative maximum likelihood expectation maximization algorithm. The linearity between the XFCT intensity and the concentrations of elements of interest was investigated. We found that measured XRF spectra showed sharp peaks characteristic of Au, Gd, and Ba. The narrow full-width at half-maximum (FWHM) of the peaks strongly supports the potential of XFCT for multiplexed imaging of Au, Gd, and Ba ( FWHM(Au,Kα1) = 0.619 keV, FWHM(Au,Kα2)=1.371 keV , FWHM(Gd,Kα)=1.297 keV, FWHM(Gd,Kβ)=0.974 keV , FWHM(Ba,Kα)=0.852 keV, and FWHM(Ba,Kβ)=0.594 keV ). The distribution of Au, Gd, and Ba in the water phantom was clearly identifiable in the reconstructed XRF images. Our results showed linear relationships between the XRF intensity of each tested element and their concentrations ( R(2)(Au)=0.944 , R(Gd)(2)=0.986, and R(Ba)(2)=0.999), suggesting that XFCT is capable of quantitative imaging. Finally, a transmission CT image was obtained to show the potential of the approach for providing attenuation correction and morphological information. In conclusion, XFCT is a promising modality for multiplexed imaging of high atomic number probes.

    View details for DOI 10.1109/TMI.2012.2223709

    View details for Web of Science ID 000314367100011

    View details for PubMedID 23076031

  • Monte Carlo model of the scanning beam digital x-ray (SBDX) source PHYSICS IN MEDICINE AND BIOLOGY Bazalova, M., Weil, M. D., Wilfley, B., Graves, E. E. 2012; 57 (22): 7381-7394


    The scanning-beam digital x-ray (SBDX) system has been developed for fluoroscopic imaging using an inverse x-ray imaging geometry. The SBDX system consists of a large-area x-ray source with a multihole collimator and a small detector. The goal of this study was to build a Monte Carlo (MC) model of the SBDX source as a useful tool for optimization of the SBDX imaging system in terms of its hardware components and imaging parameters. The MC model of the source was built in the EGSnrc/BEAMnrc code and validated using the DOSXYZnrc code and Gafchromic film measurements for 80, 100, and 120 kV x-ray source voltages. The MC simulated depth dose curves agreed with measurements to within 5%, and beam profiles at three selected depths generally agreed within 5%. Exposure rates and half-value layers for three voltages were also calculated from the MC simulations. Patient skin-dose per unit detector-dose was quantified as a function of patient size for all three x-ray source voltages. The skin-dose to detector-dose ratio ranged from 5-10 for a 20 cm thick patient to 1 × 10(3)-1 × 10(5) for a 50 cm patient for the 120 and 80 kV beams, respectively. Simulations of imaging dose for a prostate patient using common imaging parameters revealed that skin-dose per frame was as low as 0.2 mGy.

    View details for DOI 10.1088/0031-9155/57/22/7381

    View details for Web of Science ID 000310838700014

    View details for PubMedID 23093305

  • Investigation of X-ray Fluorescence Computed Tomography (XFCT) and K-Edge Imaging IEEE TRANSACTIONS ON MEDICAL IMAGING Bazalova, M., Kuang, Y., Pratx, G., Xing, L. 2012; 31 (8): 1620-1627


    This work provides a comprehensive Monte Carlo study of X-ray fluorescence computed tomography (XFCT) and K-edge imaging system, including the system design, the influence of various imaging components, the sensitivity and resolution under various conditions. We modified the widely used EGSnrc/DOSXYZnrc code to simulate XFCT images of two acrylic phantoms loaded with various concentrations of gold nanoparticles and Cisplatin for a number of XFCT geometries. In particular, reconstructed signal as a function of the width of the detector ring, its angular coverage and energy resolution were studied. We found that XFCT imaging sensitivity of the modeled systems consisting of a conventional X-ray tube and a full 2-cm-wide energy-resolving detector ring was 0.061% and 0.042% for gold nanoparticles and Cisplatin, respectively, for a dose of ? 10 cGy. Contrast-to-noise ratio (CNR) of XFCT images of the simulated acrylic phantoms was higher than that of transmission K-edge images for contrast concentrations below 0.4%.

    View details for DOI 10.1109/TMI.2012.2201165

    View details for Web of Science ID 000307120600010

    View details for PubMedID 22692896

  • The importance of tissue segmentation for dose calculations for kilovoltage radiation therapy MEDICAL PHYSICS Bazalova, M., Graves, E. E. 2011; 38 (6): 3039-3049


    The aim of this work was to evaluate the effect of tissue segmentation on the accuracy of Monte Carlo (MC) dose calculations for kilovoltage radiation therapy, which are commonly used in preclinical radiotherapy studies and are also being revisited as a clinical treatment modality. The feasibility of tissue segmentation routinely done on the basis of differences in tissue mass densities was studied and a new segmentation scheme based on differences in effective atomic numbers was developed.MC dose calculations in a cylindrical mouse phantom with small cylindrical inhomogeneities consisting of 34 ICRU-44 tissues were performed using the EGSnrc/BEAMnrc and DOSXYZnrc codes. The dose to tissue was calculated for five different kilovoltage beams currently used in small animal radiotherapy: a microCT 120 kV beam, two 225 kV beams filtered with either 4 mm of Al or 0.5 mm of Cu, a heavily filtered 320 kV beam, and a 192Ir beam. The mean doses to the 34 ICRU-44 tissues as a function of tissue mass density and effective atomic number and beam energy were studied. A treatment plan for an orthotopic lung tumor model was created, and the dose distribution was calculated for three tissue segmentation schemes using 4, 8, and 39 tissue bins to assess the significance of the simulation results for kilovoltage radiotherapy.In our model, incorrect assignment of adipose tissue to muscle caused dose calculation differences of 27%, 13%, and 7% for the 120 kV beam and the 225 kV beams filtered with 4 mm Al and 0.5 mm Cu, respectively. For the heavily filtered 320 kV beam and a 192Ir source, potential dose calculation differences due to tissue mis-assignment were below 4%. There was no clear relationship between the dose to tissue and its mass density for x-ray beams generated by tube potentials equal or less than 225 kV. A second order polynomial fit approximated well the absorbed dose to tissue as a function of effective atomic number for these beams. In the mouse study, the 120 kV beam dose to bone was overestimated by 100% and underestimated by 10% for the 4 and 8-tissue segmentation schemes compared to the 39-tissue segmentation scheme, respectively. Dose to adipose tissue was overestimated by 30% and underestimated by 10%, respectively. In general, organ at risk (OAR) doses were overestimated in the 4-tissue and the 8-tissue segmentation schemes compared to the 39-tissue segmentation.Tissue segmentation was shown to be a key parameter for dose calculations with kilovoltage beams used in small animal radiotherapy when an x-ray tube with a potential < or = 225 kV is used as a source. A new tissue segmentation scheme with 39 tissues based on effective number differences derived from mass density differences has been implemented.

    View details for DOI 10.1118/1.3589138

    View details for Web of Science ID 000291405200022

    View details for PubMedID 21815377

  • Investigation of the effects of treatment planning variables in small animal radiotherapy dose distributions MEDICAL PHYSICS Motomura, A. R., Bazalova, M., Zhou, H., Keall, P. J., Graves, E. E. 2010; 37 (2): 590-599


    Methods used for small animal radiation treatment have yet to achieve the same dose targeting as in clinical radiation therapy. Toward understanding how to better plan small animal radiation using a system recently developed for this purpose, the authors characterized dose distributions produced from conformal radiotherapy of small animals in a microCT scanner equipped with a variable-aperture collimator.Dose distributions delivered to a cylindrical solid water phantom were simulated using a Monte Carlo algorithm. Phase-space files for 120 kVp x-ray beams and collimator widths of 1-10 mm at isocenter were generated using BEAMnrc software, and dose distributions for evenly spaced beams numbered from 5 to 80 were generated in DOSXYZnrc for a variety of targets, including centered spherical targets in a range of sizes, spherical targets offset from centered by various distances, and various ellipsoidal targets. Dose distributions were analyzed using dose volume histograms. The dose delivered to a mouse bearing a spontaneous lung tumor was also simulated, and dose volume histograms were generated for the tumor, heart, left lung, right lung, and spinal cord.Results indicated that for centered, symmetric targets, the number of beams required to achieve a smooth dose volume histogram decreased with increased target size. Dose distributions for noncentered, symmetric targets did not exhibit any significant loss of conformality with increasing offset from the phantom center, indicating sufficient beam penetration through the phantom for targeting superficial targets from all angles. Even with variable collimator widths, targeting of asymmetric targets was found to have less conformality than that of spherical targets. Irradiation of a mouse lung tumor with multiple beam widths was found to effectively deliver dose to the tumor volume while minimizing dose to other critical structures.Overall, this method of generating and analyzing dose distributions provides a quantitative method for developing practical guidelines for small animal radiotherapy treatment planning. Future work should address methods to improve conformality in asymmetric targets.

    View details for DOI 10.1118/1.3276738

    View details for Web of Science ID 000274075600019

    View details for PubMedID 20229867

  • Kilovoltage beam Monte Carlo dose calculations in submillimeter voxels for small animal radiotherapy MEDICAL PHYSICS Bazalova, M., Zhou, H., Keall, P. J., Graves, E. E. 2009; 36 (11): 4991-4999


    Small animal conformal radiotherapy (RT) is essential for preclinical cancer research studies and therefore various microRT systems have been recently designed. The aim of this paper is to efficiently calculate the dose delivered using our microRT system based on a microCT scanner with the Monte Carlo (MC) method and to compare the MC calculations to film measurements.Doses from 2-30 mm diameter 120 kVp photon beams deposited in a solid water phantom with 0.2 x 0.2 x 0.2 mm3 voxels are calculated using the latest versions of the EGSnrc codes BEAMNRC and DOSXYZNRC. Two dose calculation approaches are studied: a two-step approach using phase-space files and direct dose calculation with BEAMNRC simulation sources. Due to the small beam size and submillimeter voxel size resulting in long calculation times, variance reduction techniques are studied. The optimum bremsstrahlung splitting number (NBRSPL in BEAMNRC) and the optimum DOSXYZNRC photon splitting (Nsplit) number are examined for both calculation approaches and various beam sizes. The dose calculation efficiencies and the required number of histories to achieve 1% statistical uncertainty--with no particle recycling--are evaluated for 2-30 mm beams. As a final step, film dose measurements are compared to MC calculated dose distributions.The optimum NBRSPL is approximately 1 x 10(6) for both dose calculation approaches. For the dose calculations with phase-space files, Nsplit varies only slightly for 2-30 mm beams and is established to be 300. Nsplit for the DOSXYZNRC calculation with the BEAMNRC source ranges from 300 for the 30 mm beam to 4000 for the 2 mm beam. The calculation time significantly increases for small beam sizes when the BEAMNRC simulation source is used compared to the simulations with phase-space files. For the 2 and 30 mm beams, the dose calculations with phase-space files are more efficient than the dose calculations with BEAMNRC sources by factors of 54 and 1.6, respectively. The dose calculation efficiencies converge for beams with diameters larger than 30 mm.A very good agreement of MC calculated dose distributions to film measurements is found. The mean difference of percentage depth dose curves between calculated and measured data for 2, 5, 10, and 20 mm beams is 1.8%.

    View details for DOI 10.1118/1.3238465

    View details for Web of Science ID 000271217900018

    View details for PubMedID 19994508

  • The ATLAS Experiment at the CERN Large Hadron Collider JOURNAL OF INSTRUMENTATION Aad, G., ABAT, E., Abdallah, J., ABDELALIM, A. A., Abdesselam, A., Abdinov, O., Abi, B. A., Abolins, M., Abramowicz, H., Acerbi, E., Acharya, B. S., Achenbach, R., Ackers, M., Adams, D. L., Adamyan, F., Addy, T. N., Aderholz, M., Adorisio, C., Adragna, P., Aharrouche, M., Ahlen, S. P., Ahles, F., Ahmad, A., Ahmed, H., Aielli, G., Akesson, P. F., Akesson, T. P., Alam, S. M., Albert, J., Albrand, S., Aleksa, M., Aleksandrov, I. N., Aleppo, M., Alessandria, F., Alexa, C., Alexander, G., Alexopoulos, T., Alimonti, G., Aliyev, M., Allport, P. P., Allwood-Spiers, S. E., Aloisio, A., Alonso, J., Alves, R., Alviggi, M. G., Amako, K., Amaral, P., Amaral, S. P., Ambrosini, G., Ambrosio, G., Amelung, C., Ammosov, V. V., Amorim, A., Amram, N., Anastopoulos, C., Anderson, B., Anderson, K. J., Anderssen, E. C., Andreazza, A., Andrei, V., Andricek, L., Andrieux, M., Anduaga, X. S., Anghinolfi, F., Antonaki, A., Antonelli, M., Antonelli, S., Apsimon, R., Arabidze, G., Aracena, I., Arai, Y., Arce, A. T., Archambault, J. P., Arguin, J., Arik, E., Arik, M., Arms, K. E., Armstrong, S. R., Arnaud, M., Arnault, C., Artamonov, A., Asai, S., Ask, S., Asman, B., Asner, D., Asquith, L., Assamagan, K., Astbury, A., Athar, B., Atkinson, T., Aubert, B., Auerbach, B., Auge, E., Augsten, K., Aulchenko, V. M., Austin, N., Avolio, G., Avramidou, R., Axen, A., Ay, C., Azuelos, G., Baccaglioni, G., Bacci, C., Bachacou, H., Bachas, K., BACHY, G., Badescu, E., Bagnaia, P., Bailey, D. C., Baines, J. T., Baker, O. K., Ballester, F., Pedrosa, F. B., Banas, E., Banfi, D., Bangert, A., Bansal, V., Baranov, S. P., Baranov, S., Barashkou, A., Barberio, E. L., Barberis, D., Barbier, G., Barclay, P., Bardin, D. Y., Bargassa, P., Barillari, T., Barisonzi, M., Barnett, B. M., Barnett, R. M., Baron, S., Baroncelli, A., Barone, M., Barr, A. J., Barreiro, F., da Costa, J. 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W., Schuler, G., Schultes, J., Schultz-Coulon, H., Schumacher, J., Schumacher, M., Schune, P., Schwartzman, A., Schweiger, D., Schwemling, P., Schwick, C., Schwienhorst, R., Schwierz, R., Schwindling, J., Scott, W. G., Secker, H., Sedykh, E., Seguin-Moreau, N., Segura, E., Seidel, S. C., Seiden, A., Seixas, J. M., Sekhniaidze, G., Seliverstov, D. M., Sellden, B., Seman, M., Semprini-Cesari, N., Serfon, C., Serin, L., Seuster, R., Severini, H., Sevior, M. E., Sexton, K. A., Sfyrla, A., Shah, T. P., Shan, L., Shank, J. T., Shapiro, M., SHATALOV, P. B., Shaver, L., Shaw, C., Shears, T. G., Sherwood, P., Shibata, A., Shield, P., Shilov, S., Shimojima, M., Shin, T., Shiyakova, M., Shmeleva, A., Shoa, M., SHOCHET, M. J., Shupe, M. A., Sicho, P., Sidoti, A., Siebel, A., Siebe, M., Siegrist, J., Sijacki, D., Silva, J., Silverstein, S. B., Simak, V., Simic, L., Simion, S., Simmons, B., Simonyan, M., Sinervo, P., Sipica, V., Siragusa, G., Sisakyan, A. N., Sivoklokov, S., Sjoelin, J., Skubic, P., Skvorodnev, N., Slattery, P., Slavicek, T., Sliwa, K., Sloan, T. J., Sloper, J., Smakhtin, V., Small, A., Smirnov, S. Y., Smirnov, Y., Smirnova, L., Smirnova, O., Smith, N. A., Smith, B. C., Smith, D. S., Smith, J., Smith, K. M., Smith, B., Smizanska, M., Smolek, K., SNESAREV, A. A., Snow, S. W., Snow, J., Snuverink, J., Snyder, S., SOARES, M., Soares, S., Sobie, R., Sodomka, J., Soderberg, M., Soffer, A., Solans, C. A., Solar, M., Sole, D., Camillocci, E. S., Solodkov, A. A., Solov'yanov, O. V., Soloviev, I., Soluk, R., Sondericker, J., Sopko, V., Sopko, B., Sorbi, M., Medel, J. S., Sosebee, M., Sosnovtsev, V. V., Suay, L. S., Soukharev, A., Soukup, J., Spagnolo, S., Spano, F., Speckmayer, P., Spegel, M., SPENCER, E., Spighi, R., Spigo, G., Spila, F., Spiriti, E., Spiwoks, R., Spogli, L., Spousta, M., Sprachmann, G., Spurlock, B., Denis, R. D., Stahl, T., Staley, R. J., Stamen, R., Stancu, S. N., Stanecka, E., Stanek, R. W., Stanescu, C., Stapnes, S., Starchenko, E. A., Staroba, P., Stastny, J., Staude, A., Stavina, P., Stavrianakou, M., Stavropoulos, G., Stefanidis, E., STEFFENS, J. L., Stekl, I., STELZER, H. J., Stenzel, H., Stewart, G., Stewart, T. D., Stiller, W., Stockmanns, T., Stodulski, M., Stonjek, S., Stradling, A., Straessner, A., Strandberg, J., Strandlie, A., Strauss, M., Strickland, V., Striegel, D., Strizenec, P., Stroehmer, R., Strom, D. M., Strong, J. A., Stroynowski, R., Stugu, B., Stumer, I., Su, D., Subramania, S., Suchkov, S. I., Sugaya, Y., Sugimoto, T., Suk, M., SULIN, V. V., SULTANOV, S., Sun, Z., Sundal, B., Sushkov, S., Susinno, G., Sutcliffe, P., Sutton, M. R., Sviridov, Y. M., Sykora, I., Szczygiel, R. R., Szeless, B., Szymocha, T., Sanchez, J., Ta, D., Gameiro, S. T., Tadel, M., Tafirout, R., Taga, A., Takai, H., Takashima, R., Takeda, H., Takeshita, T., Talby, M., Talyshev, A., Tamsett, M. C., Tanaka, J., Tanaka, K., Tanaka, R., Tanaka, S., Tanaka, S., Tanaka, Y., Tappern, G. P., Tapprogge, S., Tarem, S., Tarrade, F., Tarrant, J., Tartarelli, G., Tas, P., Tasevsky, M., Tayalati, Y., Taylor, F. E., Taylor, G., Taylor, G. N., Taylor, R. P., Tcherniatine, V., Tegenfeldt, F., Teixeira-Dias, P., ten Kate, H., Teng, P. K., Ter-Antonyan, R., TERADA, S., Terron, J., Terwort, M., Teuscher, R. J., Tevlin, C. M., Thadome, J., Thion, J., Thioye, M., Thomas, A., Thomas, J. P., Thomas, T. L., Thomas, E., Thompson, R. J., Thompson, A. S., Thun, R. P., Tic, T., Tikhomirov, V. O., Tikhonov, Y. A., Timm, S., Timmermans, C. J., Tipton, P., Viegas, F. J., Tisserant, S., Titov, M., Tobias, J., Tocut, V. M., Toczek, B., Todorova-Nova, S., Tojo, J., Tokar, S., Tokushuku, K., Tomasek, L., Tomasek, M., Tomasz, F., Tomoto, M., Tompkins, D., Tompkins, L., Toms, K., Tonazzo, A., Tong, G., Tonoyan, A., Topfel, C., Topilin, N. D., Torrence, E., Pais, J. G., TOTH, J., Touchard, F., Tovey, D. R., Tovey, S. N., Towndrow, E. F., Trefzger, T., Treichel, M., Treis, J., Tremblet, L., Tribanek, W., Tricoli, A., Trigger, I. M., Trilling, G., Trincaz-Duvoid, S., Tripiana, M. F., Trischuk, W., Trka, Z., Trocme, B., Troncon, C., Tseng, J., Tsiafis, I., Tsiareshka, P. V., Tsipolitis, G., Tskhadadze, E. G., Tsukerman, I. I., Tsulaia, V., Tsuno, S., Turala, M., Cakir, I. T., Turlay, E., Tuts, P. M., Twomey, M. S., Tynde, M., Typaldos, D., Tyrvainen, H., Tzamarioudaki, E., Tzanakos, G., Ueda, I., Uhrmacher, M., Ukegawa, F., Comes, M. U., Unal, G., Underwood, D. G., Undrus, A., Unel, G., Unno, Y., Urkovsky, E., Usai, G., Usov, Y., Vacavant, L., Vacek, V., Vachon, B., Vahsen, S., Valderanis, C., Valenta, J., Valente, P., Valero, A., Valkar, S., Ferrer, J. A., van der Bij, H., van der Graaf, H., Van der Kraaij, E., van Eijk, B., van Eldik, N., van Gemmeren, P., van Kesteren, Z., Van Vulpen, I., VanBerg, R., Vandelli, W., Vandoni, G., Vaniachine, A., Vannucci, F., Varanda, M., Rodriguez, F. V., Vari, R., Varnes, E. W., Varouchas, D., Vartapetian, A., Varve, K. E., Vassilakopoulos, V. I., Vassilieva, L., Vataga, E., Vaz, L., Vazeille, F., Vedrine, P., Vegni, G., Veillet, J. J., Vellidis, C., Veloso, F., Veness, R., Veneziano, S., Ventura, A., Ventura, S., VERCESI, V., Verducci, M., Verkerke, W., Vermeulen, J. C., Vertogardov, L., Vetterli, M. C., Vichou, I., Vickey, T., Viehhauser, G. H., Vigeolas, E., Villa, M., Villani, E. G., VILLATE, J., Villella, I., Vilucchi, E., Vincent, P., Vincke, H., Vincter, M. G., Vinogradov, V. B., VIRCHAUX, M., Viret, S., Virzi, J., Vitale, A., Vivarelli, I., Vives, R., Vaques, F. V., Vlachos, S., Vogt, H., Vokac, P., Vollmer, C. F., Volpi, M., Volpini, G., von Boehn-Buchholz, R., von der Schmitt, H., Von Toerne, E., Vorobel, V., Vorobiev, A. P., Vorozhtsov, A. S., VOROZHTSOV, S. B., Vos, M., Voss, K. C., Voss, R., Vossebeld, J. H., Vovenko, A. S., Vranjes, N., Vrba, V., Vreeswijk, M., Anh, T. V., Vuaridel, B., Vudragovic, M., Vuillemin, V., Vuillermet, R., Waenanen, A., Wahlen, H., Walbersloh, J., Walker, R., Walkowiak, W., Wall, R., Wallny, R. S., Walsh, S., Wang, C., Wang, J. C., Wappler, F., Warburton, A., Ward, C. P., Warner, G. P., Warren, M., Warsinsky, M., Wastie, R., Watkins, P. M., Watson, A. T., Watts, G., Waugh, A. T., Waugh, B. M., Weaverdyck, C., Webel, M., Weber, G., Weber, J., Weber, M., Weber, P., Weidberg, A. R., Weilhammer, P. M., Weingarten, J., Weiser, C., Wellenstein, H., Wellisch, H. P., Wells, P., Wemans, A., Wen, M., Wenaus, T., Wendler, S., Wengler, T., Wenig, S., Wermes, N., Werneke, P., Werner, P., Werthenbach, U., Wheeler-Ellis, S. J., Whitaker, S. P., White, A., White, M. J., White, S., Whittington, D., Wicek, F., Wicke, D., Wickens, F. J., Wiedenmann, W., Wielers, M., Wienemann, P., Wiesmann, M., Wiesmann, M., Wijnen, T., Wildauer, A., Wilhelm, I., Wilkens, H. G., Williams, H. H., Willis, W., Willocq, S., Wilmut, I., Wilson, J. A., Wilson, A., Wingerter-Seez, I., Winton, L., WITZELING, W., Wlodek, T., Woehrling, E., Wolter, M. W., Wolters, H., Wosiek, B., Wotschack, J., WOUDSTRA, M. J., Wright, C., Wu, S. L., Wu, X., Wuestenfeld, J., Wunstorf, R., Xella-Hansen, S., Xiang, A., Xie, S., Xie, Y., Xu, G., Xu, N., Yamamoto, A., Yamamoto, S., Yamaoka, H., Yamazaki, Y., Yan, Z., Yang, H., Yang, J. C., Yang, S., Yang, U. K., Yang, Y., Yang, Z., Yao, W., Yao, Y., Yarradoddi, K., Yasu, Y., Ye, J., Yilmaz, M., Yoosoofmiya, R., Yorita, K., Yoshida, H., Yoshida, R., Young, C., Youssef, S. P., Yu, D., Yu, J., Yu, M., Yu, X., Yuan, J., Yurkewicz, A., Zaets, V. G., Zaidan, R., Zaitsev, A. M., Zajac, J., Zajacova, Z., Zalite, A. Y., Zalite, Y. K., Zaneo, L., Zarzhitsky, P., Zaytsev, A., Zdrazil, M., Zeitnitz, C., Zeller, M., Zema, P. F., Zendler, C., Zenin, A. V., Zenis, T., Zenonos, Z., Zenz, S., Zerwas, D., Zhang, H., Zhang, J., Zheng, W., Zhang, X., Zhao, L., Zhao, T., Zhao, X., Zhao, Z., Zhelezko, A., Zhemchugov, A., Zheng, S., Zhichao, L., Zhou, B., Zhou, N., Zhou, S., Zhou, Y., Zhu, C. G., Zhu, H. Z., Zhuang, X. A., Zhuravlov, V., Zilka, B., Zimin, N. I., Zimmermann, S., Ziolkowski, M., Zitoun, R., Zivkovic, L., Zmouchko, V. V., Zobernig, G., Zoccoli, A., Zoeller, M. M., Zolnierowski, Y., Zsenei, A., zur Nedden, M., Zychacek, V. 2008; 3
  • ATLAS pixel detector electronics and sensors JOURNAL OF INSTRUMENTATION Aad, G., Ackers, M., Alberti, F. A., Aleppo, M., Alimonti, G., Alonso, J., Anderssen, E. C., Andreani, A., Andreazza, A., Arguin, J., Arms, K. E., Barberis, D., Barbero, M. B., Bazalova, M., Beccherle, R. B., Becks, K. H., Behera, P. K., Bellina, F., Beringer, J., Bernardet, K., Biesiada, J. B., Blanquart, L., Boek, J., Boyd, G. R., Breugnon, P., Buchholz, P., Butler, B., Caccia, M., Capsoni, A. C., Caso, C., Cauz, D., Cepeda, M., Cereseto, R., Cervetto, M., Chu, M. L., Citterio, M., Clemens, J. C., Coadou, Y. C., Cobal, M., Coccaro, A., Coelli, S., Correard, S., Cristinziani, M., Cuneo, S., D'Auria, S., DAMERI, M., Darbo, G., Dardin, S., De Lotto, B., De Sanctis, U., De Regie, J. B., del Papa, C., Delpierre, P., Di Girolamo, B., Dietsche, W., Djama, F., Dobos, D., Donega, M., DOPKE, J., Einsweiler, K., EYRING, A., Fasching, D., Feligioni, L., Ferguson, D., Fernando, W., Fischer, P., Fisher, M. J., Flick, T., Gagliardi, G., Galyaev, E., Gan, K. K., Garcia-Sciveres, M., GARELLI, N., Gariano, G. G., Gaycken, G. G., Gemme, C., Gerlach, P., Gilchriese, M., Giordani, M. P., Giugni, D., Glitza, K. W., Goessling, C., Golling, T., Goozen, F., Gorelov, I., Gorfine, G., Grah, C., Gray, H. M., Gregor, I. M., Grosse-Knetter, J., Grybel, K., Gutierrez, P., Hallewell, G. D., Hartman, N., Havranek, M., Heinemann, B., Henss, T., HOEFERKAMP, M. R., Hoffmann, D., Holder, M., Honerbach, W., Horn, C., Hou, S., Huang, G. S., Huegging, F., Hughes, E. W., Ibragimov, I., Ilyashenko, I., Imhaeuser, M., Izen, J. M., Jackson, J., Jana, D., Jared, R. C., Jez, P., Johnson, T., Joseph, J., Kagan, H., Karagounis, M., Kass, R. D., Keil, M., Kersten, S., Kind, P., Klaiber-Lodewigs, J., Klingbeil, L., Klingenberg, R., Korn, A., Kostyukhin, V. V., Kostyukhina, I., Krasel, O., Krueger, H., Krueger, K., Kudlaty, J., Kuhl, T., Kvasnicka, O., Lantzsch, K., Lari, T., Latorre, S. L., Lee, S. C., Lenz, T., Lenzen, G., Lepidis, J., Leveque, J., Leyton, M., Mateos, D. L., Loureiro, K. F., Lueke, D., Luisa, L., Lys, J., Madaras, R. J., Maettig, P., Manca, F. M., Mandelli, E., Marcisovsky, M., Marshall, Z., Martinez, G., Masetti, L., Mass, M., Mathes, M., McKay, R., Meddeler, G., Meera-Lebbai, R., Meroni, C., Metcalfe, J., Meyer, W. T., Miller, D. W., Miller, W., Montesano, S., Monti, M. M., Morettini, P., Moss, J. M., Mouthuy, T., Nechaeva, P., Ockenfels, W., Odino, G. A., Olcese, M., OSCULATI, B., Parodi, F., Pekedis, A., Perez, K., Peric, I., Pizzorno, C., Popule, J., Post, R., Ragusa, F., Rahimi, A. M., Raith, B., Rajek, S., Reeves, K., Reisinger, I., Richardson, J. D., Rosenberg, E. I., Rossi, L. P., Rottlaender, I., Rovani, A. R., Rozanov, A., Runolfsson, O., Ruscino, E. R., Saavedra, A. F., Sabatini, F. S., Saleem, M., Sandvoss, S., Sanny, B., Santi, L., Scherzer, M. I., Schiavi, C., Schreiner, A., Schultes, J., Schwartzman, A., Seibert, R., Seidel, S. C., Severini, H., Shanava, S., Sicho, P., Skubic, P., Smith, A. C., Smith, D. S., Snow, J., Stahl, T., Stockmanns, T., Strandberg, S., Strauss, M., Ta, D., Tegenfeldt, F., Teng, P. K., Ter-Antonyan, R., Thadome, J., Tic, T., Tomasek, L., Tomasek, M., Tomasi, F., Toms, K., Tran, C., Treis, J., Triplett, N., Troncon, C., Vacavant, L., Vahsen, S., Valenta, J., Vegni, G., Vernocchi, F., Vigeolas, E., Virzi, J., Viscione, E., Vrba, V., Walbersloh, J., Walkowiak, W., Weber, J., Weber, T. F., Weingarten, J., Weldon, C., Wermes, N., Werthenbach, U., Wirth, J. S., Witharm, R., Witt, B., Wittgen, M., Wuestenfeld, J., Wunstorf, R., Wyckoff, J., Yao, W., Young, C., Zaidan, R., Zdrazil, M., Zetti, F., Zhong, J., Ziolkowski, M., Zizkaa, G., Zoeller, M. M. 2008; 3
  • Dual-energy CT-based material extraction for tissue segmentation in Monte Carlo dose calculations PHYSICS IN MEDICINE AND BIOLOGY Bazalova, M., Carrier, J., Beaulieu, L., Verhaegen, F. 2008; 53 (9): 2439-2456


    Monte Carlo (MC) dose calculations are performed on patient geometries derived from computed tomography (CT) images. For most available MC codes, the Hounsfield units (HU) in each voxel of a CT image have to be converted into mass density (rho) and material type. This is typically done with a (HU; rho) calibration curve which may lead to mis-assignment of media. In this work, an improved material segmentation using dual-energy CT-based material extraction is presented. For this purpose, the differences in extracted effective atomic numbers Z and the relative electron densities rho(e) of each voxel are used. Dual-energy CT material extraction based on parametrization of the linear attenuation coefficient for 17 tissue-equivalent inserts inside a solid water phantom was done. Scans of the phantom were acquired at 100 kVp and 140 kVp from which Z and rho(e) values of each insert were derived. The mean errors on Z and rho(e) extraction were 2.8% and 1.8%, respectively. Phantom dose calculations were performed for 250 kVp and 18 MV photon beams and an 18 MeV electron beam in the EGSnrc/DOSXYZnrc code. Two material assignments were used: the conventional (HU; rho) and the novel (HU; rho, Z) dual-energy CT tissue segmentation. The dose calculation errors using the conventional tissue segmentation were as high as 17% in a mis-assigned soft bone tissue-equivalent material for the 250 kVp photon beam. Similarly, the errors for the 18 MeV electron beam and the 18 MV photon beam were up to 6% and 3% in some mis-assigned media. The assignment of all tissue-equivalent inserts was accurate using the novel dual-energy CT material assignment. As a result, the dose calculation errors were below 1% in all beam arrangements. Comparable improvement in dose calculation accuracy is expected for human tissues. The dual-energy tissue segmentation offers a significantly higher accuracy compared to the conventional single-energy segmentation.

    View details for DOI 10.1088/0031-9155/53/9/015

    View details for Web of Science ID 000255120100016

    View details for PubMedID 18421124

  • Spectroscopic characterization of a novel electronic brachytherapy system PHYSICS IN MEDICINE AND BIOLOGY Liu, D., Poon, E., Bazalova, M., Reniers, B., Evans, M., Rusch, T., Verhaegen, F. 2008; 53 (1): 61-75


    The Axxent developed by Xoft Inc. is a novel electronic brachytherapy system capable of generating x-rays up to 50 keV. These low energy photon-emitting sources merit attention not only because of their ability to vary the dosimetric properties of the radiation, but also because of the radiobiological effects of low energy x-rays. The objective of this study is to characterize the x-ray source and to model it using the Geant4 Monte Carlo code. Spectral and attenuation curve measurements are performed at various peak voltages and angles and the source is characterized in terms of spectrum and half-value layers (HVLs). Also, the effects of source variation and source aging are quantified. Bremsstrahlung splitting, phase-space scoring and particle-tagging features are implemented in the Geant4 code, which is bench-marked against BEAMnrc simulations. HVLs from spectral measurements, attenuation curve measurements and Geant4 simulations mostly agree within uncertainty. However, there are discrepancies between measurements and simulations for photons emitted on the source transverse plane (90 degrees).

    View details for DOI 10.1088/0031-9155/53/1/004

    View details for Web of Science ID 000252792400004

    View details for PubMedID 18182687

  • Tissue segmentation in Monte Carlo treatment planning: A simulation study using dual-energy CT images RADIOTHERAPY AND ONCOLOGY Bazatova, M., Carrier, J., Beautieu, L., Verhaegen, F. 2008; 86 (1): 93-98


    Tissue segmentation is an important step in Monte Carlo (MC) dose calculation and is often done uncritically. A new approach to tissue segmentation using dual-energy CT images is studied in this work.A simple MC model of a CT scanner was built and CT images of phantoms with ten tissue-equivalent cylinders were simulated using soft and hard X-ray spectra. The Z and rho(e) of the cylinders were extracted using a formalism based on a parameterization of the linear attenuation coefficient.It was shown that in order to extract Z and rho(e) with a reasonable accuracy, hard X-ray beams have to be used for scanning. When an additional filtration of 9 mm of aluminium in the CT X-ray beam is used, beam hardening in high density materials is suppressed and the mean errors of the extraction of Z and rho(e) for 10 tissue-equivalent materials in a small tissue-equivalent phantom are 3.7% and 3.1%, respectively.MC simulations were used to show that the extraction of Z and rho(e) for a number of tissue-equivalent materials using dual-energy CT images is possible which improves tissue segmentation for Monte Carlo dose calculations, as demonstrated with a 250 kVp photon beam dose calculation.

    View details for DOI 10.1016/j.radonc.2007.11.008

    View details for Web of Science ID 000253303000015

    View details for PubMedID 18068841

  • Monte Carlo dose calculations for phantoms with hip prostheses INTERNATIONAL WORKSHOP ON MONTE CARLO TECHNIQUES IN RADIOTHERAPY DELIVERY AND VERIFICATION - THIRD MCGILL INTERNATIONAL WORKSHOP Bazalova, M., Coolens, C., Cury, F., Childs, P., Beaulieu, L., Verhaegen, F. 2008; 102
  • Monte Carlo simulation of a computed tomography x-ray tube PHYSICS IN MEDICINE AND BIOLOGY Bazalova, M., Verhaegen, F. 2007; 52 (19): 5945-5955


    The dose delivered to patients during computed tomography (CT) exams has increased in the past decade. With the increasing complexity of CT examinations, measurement of the dose becomes more difficult and more important. In some cases, the standard methods, such as measurement of the computed tomography dose index (CTDI), are currently under question. One approach to determine the dose from CT exams is to use Monte Carlo (MC) methods. Since the patient geometry can be included in the model, Monte Carlo simulations are potentially the most accurate method of determining the dose delivered to patients. In this work, we developed a MC model of a CT x-ray tube. The model was validated with half-value layer (HVL) measurements and spectral measurements with a high resolution Schottky CdTe spectrometer. First and second HVL for beams without additional filtration calculated from the MC modelled spectra and determined from attenuation measurements differ by less than 2.5%. The differences between the first and second HVL for both filtered and non-filtered beams calculated from the MC modelled spectra and spectral measurements with the CdTe detector were less than 1.8%. The MC modelled spectra match the directly measured spectra. This works presents a first step towards an accurate MC model of a CT scanner.

    View details for DOI 10.1088/0031-9155/52/19/015

    View details for Web of Science ID 000250443200015

    View details for PubMedID 17881811

  • Correction of CT artifacts and its influence on Monte Carlo dose calculations MEDICAL PHYSICS Bazalova, M., Beaulieu, L., Palefsky, S., Verhaegen, F. 2007; 34 (6): 2119-2132


    Computed tomography (CT) images of patients having metallic implants or dental fillings exhibit severe streaking artifacts. These artifacts may disallow tumor and organ delineation and compromise dose calculation outcomes in radiotherapy. We used a sinogram interpolation metal streaking artifact correction algorithm on several phantoms of exact-known compositions and on a prostate patient with two hip prostheses. We compared original CT images and artifact-corrected images of both. To evaluate the effect of the artifact correction on dose calculations, we performed Monte Carlo dose calculation in the EGSnrc/DOSXYZnrc code. For the phantoms, we performed calculations in the exact geometry, in the original CT geometry and in the artifact-corrected geometry for photon and electron beams. The maximum errors in 6 MV photon beam dose calculation were found to exceed 25% in original CT images when the standard DOSXYZnrc/CTCREATE calibration is used but less than 2% in artifact-corrected images when an extended calibration is used. The extended calibration includes an extra calibration point for a metal. The patient dose volume histograms of a hypothetical target irradiated by five 18 MV photon beams in a hypothetical treatment differ significantly in the original CT geometry and in the artifact-corrected geometry. This was found to be mostly due to miss-assignment of tissue voxels to air due to metal artifacts. We also developed a simple Monte Carlo model for a CT scanner and we simulated the contribution of scatter and beam hardening to metal streaking artifacts. We found that whereas beam hardening has a minor effect on metal artifacts, scatter is an important cause of these artifacts.

    View details for DOI 10.1118/1.2736777

    View details for Web of Science ID 000247479600029

    View details for PubMedID 17654915

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