G. Olivera

21st Century Oncology, Redding, California, United States

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Publications (220)393.49 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: Purpose: The Gamma Index defines an asymmetric metric between the evaluated image and the reference image. It provides a quantitative comparison that can be used to indicate sample-wised pass/fail on the agreement of the two images. The Gamma passing/failing rate has become an important clinical evaluation tool. However, the presence of noise in the evaluated and/or reference images may change the Gamma Index, hence the passing/failing rate, and further, clinical decisions. In this work, we systematically studied the impact of the image noise on the Gamma Index calculation. Methods: We used both analytic formulation and numerical calculations in our study. The numerical calculations included simulations and clinical images. Three different noise scenarios were studied in simulations: noise in reference images only, in evaluated images only, and in both. Both white and spatially correlated noises of various magnitudes were simulated. For clinical images of various noise levels, the Gamma Index of measurement against calculation, calculation against measurement, and measurement against measurement, were evaluated. Results: Numerical calculations for both the simulation and clinical data agreed with the analytic formulations, and the clinical data agreed with the simulations. For the Gamma Index of measurement against calculation, its distribution has an increased mean and an increased standard deviation as the noise increases. On the contrary, for the Gamma index of calculation against measurement, its distribution has a decreased mean and stabilized standard deviation as the noise increases. White noise has greater impact on the Gamma Index than spatially correlated noise. Conclusions: The noise has significant impact on the Gamma Index calculation and the impact is asymmetric. The Gamma Index should be reported along with the noise levels in both reference and evaluated images. Reporting of the Gamma Index with switched roles of the images as reference and evaluated images or some composite metrics would be a good practice.
    02/2014; 489(1).
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    ABSTRACT: Purpose: During a typical 5-7 week treatment of external beam radiotherapy, there are potential differences between planned patient's anatomy and positioning, such as patient weight loss, or treatment setup. The discrepancies between planned and delivered doses resulting from these differences could be significant, especially in IMRT where dose distributions tightly conforms to target volumes while avoiding organs-at-risk. We developed an automatic system to monitor delivered dose using daily imaging. Methods: For each treatment, a merged image is generated by registering the daily pre-treatment setup image and planning CT using treatment position information extracted from the Tomotherapy archive. The treatment dose is then computed on this merged image using our in-house convolution-superposition based dose calculator implemented on GPU. The deformation field between merged and planning CT is computed using the Morphon algorithm. The planning structures and treatment doses are subsequently warped for analysis and dose accumulation. All results are saved in DICOM format with private tags and organized in a database. Due to the overwhelming amount of information generated, a customizable tolerance system is used to flag potential treatment errors or significant anatomical changes. A web-based system and a DICOM-RT viewer were developed for reporting and reviewing the results. Results: More than 30 patients were analysed retrospectively. Our in-house dose calculator passed 97% gamma test evaluated with 2% dose difference and 2mm distance-to-agreement compared with Tomotherapy calculated dose, which is considered sufficient for adaptive radiotherapy purposes. Evaluation of the deformable registration through visual inspection showed acceptable and consistent results, except for cases with large or unrealistic deformation. Our automatic flagging system was able to catch significant patient setup errors or anatomical changes. Conclusions: We developed an automatic dose verification system that quantifies treatment doses, and provides necessary information for adaptive planning without impeding clinical workflows.
    02/2014; 489(1).
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    ABSTRACT: Purpose: Accurate on-line reconstruction of in-vivo volume dose that accounts for both machine and patient discrepancy is not clinically available. We present a simple reference-dose-perturbation algorithm that reconstructs in-vivo volume dose fast and accurately. Methods: We modelled the volume dose as a function of the fluence map and density image. Machine (output variation, jaw/leaf position errors, etc.) and patient (setup error, weight loss, etc.) discrepancies between the plan and delivery were modelled as perturbation of the fluence map and density image, respectively. Delivered dose is modelled as perturbation of the reference dose due to change of the fluence map and density image. We used both simulated and clinical data to validate the algorithm. The planned dose was used as the reference. The reconstruction was perturbed from the reference and accounted for output-variations and the registered daily image. The reconstruction was compared with the ground truth via isodose lines and the Gamma Index. Results: For various plans and geometries, the volume doses were reconstructed in few seconds. The reconstruction generally matched well with the ground truth. For the 3%/3mm criteria, the Gamma pass rates were 98% for simulations and 95% for clinical data. The differences mainly appeared on the surface of the phantom/patient. Conclusions: A novel reference-dose-perturbation dose reconstruction model is presented. The model accounts for machine and patient discrepancy from planning. The algorithm is simple, fast, yet accurate, which makes online in-vivo 3D dose reconstruction clinically feasible.
    02/2014; 489(1).
  • W Lu, M Chen, G Olivera, D Galmarini
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    ABSTRACT: Purpose: Exit 2D detectors are widely used in clinics as a tool for pre- treatment field verification. It is desired to have accurate modeling of the detector dose for each IMRT plan with patient geometry for in-vivo delivery verification. We propose a novel hybrid of model and measurement based methods to estimate the detector dose using the information from TPS and plan/verification CT. Methods: Our approach is based on the generalized equivalent field size (GEFS) method. It requires two commissioning tables for various square fields (l×l, 2×2, [ellipsis (horizontal)]40×40): the percent depth dose (PDD) table and the detector correction factor (DDCF) table. PDDs are retrieved from the treatment planning system (TPS), and DDCFs are reconstructed from measurement with various field sizes and air gaps (from 5 cm to 50 cm). GEFS models the detector point dose as the superposition of annular contribution of the fluence map, which is retrieved from the TPS. Correction on the radiological path length is calculated through ray-tracing the patient CT. Corrections on the air gap between the couch and detector and detector response are applied via table lookup on PDD and DDCF. Results: We validated the proposed method using TPS with extended geometry and direct clinic measurements for both regular and IMRT fields, various phantom and patient geometry. For all calculations, more than 98% of pixels pass the gamma index with criteria of 3%, 3mm. Each calculation took only a few seconds on a single PC. Conclusions: We proposed a novel detector dose calculation method that can be applied for arbitrary IMRT field and arbitrary patient geometry. The calculation is simple and fast and when compared with detector measurement during IMRT treatment, makes in- vivo delivery verification and dose reconstruction feasible.
    Medical Physics 06/2012; 39(6):3957. · 2.91 Impact Factor
  • Minesh P. Mehta, Wolfgang A. Tomé, Gustavo H. Olivera
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    ABSTRACT: Over the last 2 years, several advances have been made in the field of radiotherapy for brain tumors. Key advances are summarized in this review. Crucial technologic advances, such as radiosurgery, fractionated stereotactic radiotherapy, and intensity-modulated radiotherapy, are discussed. Better understanding of the interaction between the processes of angiogenesis, apoptosis, cell-cycle regulation, and signal transduction and the effects of ionizing radiation has made it clear that many of these ‘new agents’ are, in fact, valuable modulators of the radiation response. Another exciting molecular discovery is the recognition of radiation-induced promoters that can be exploited to cause spatially and temporally configured expression of selected genes; this approach may represent the ideal application of conformal radiation techniques in the future, yielding welldefined genetic changes in specifically targeted tissues. The final ‘frontier’ covered in this review is the newer categories of radiosensitizers, ranging from topoisomerase-I inhibitors, to expanded metalloporphyrins, to oxygendissociating agents.
    Current Oncology Reports 04/2012; 2(5):438-444. · 3.33 Impact Factor
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    ABSTRACT: Every year, new radiotherapy techniques including stereotactic radiosurgery using linear accelerators give rise to new applications of Monte Carlo (MC) modeling. Accurate modeling requires knowing the size of the electron spot, one of the few parameters to tune in MC models. The resolution of integrated megavoltage imaging systems, such as the tomotherapy system, strongly depends on the photon spot size which is closely related to the electron spot. The aim of this article is to clarify the relationship between the electron spot size and the photon spot size (i.e., the focal spot size) for typical incident electron beam energies and target thicknesses. Three electron energies (3, 5.5, and 18 MeV), four electron spot sizes (FWHM = 0, 0.5, 1, and 1.5 mm), and two tungsten target thicknesses (0.15 and 1 cm) were considered. The formation of the photon beam within the target was analyzed through electron energy deposition with depth, as well as photon production at several phase-space planes placed perpendicular to the beam axis, where only photons recorded for the first time were accounted for. Photon production was considered for "newborn" photons intersecting a 45 x 45 cm2 plane at the isocenter (85 cm from source). Finally, virtual source position and "effective" focal spot size were computed by back-projecting all the photons from the bottom of the target intersecting a 45 x 45 cm2 plane. The virtual source position and focal spot size were estimated at the plane position where the latter is minimal. In the relevant case of considering only photons intersecting the 45 x 45 cm2 plane, the results unambiguously showed that the effective photon spot is created within the first 0.25 mm of the target and that electron and focal spots may be assumed to be equal within 3-4%. In a good approximation photon spot size equals electron spot size for high energy X-ray treatments delivered by linear accelerators.
    Medical Physics 03/2011; 38(3):1579-86. · 2.91 Impact Factor
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    ABSTRACT: To evaluate a three-dimensional dose verification method based on the exit dose using the onboard detector of tomotherapy. The study included 347 treatment fractions from 24 patients, including 10 prostate, 5 head and neck (HN), and 9 spinal stereotactic body radiation therapy (SBRT) cases. Detector sonograms were retrieved and back-projected to calculate entrance fluence, which was then forward-projected on the CT images to calculate the verification dose, which was compared with ion chamber and film measurement in the QA plans and with the planning dose in patient plans. Root mean square (RMS) errors of 2.0%, 2.2%, and 2.0% were observed comparing the dose verification (DV) and the ion chamber measured point dose in the phantom plans for HN, prostate, and spinal SBRT patients, respectively. When cumulative dose in the entire treatment is considered, for HN patients, the error of the mean dose to the planning target volume (PTV) varied from 1.47% to 5.62% with a RMS error of 3.55%. For prostate patients, the error of the mean dose to the prostate target volume varied from -5.11% to 3.29%, with a RMS error of 2.49%. The RMS error of maximum doses to the bladder and the rectum were 2.34% (-4.17% to 2.61%) and 2.64% (-4.54% to 3.94%), respectively. For the nine spinal SBRT patients, the RMS error of the minimum dose to the PTV was 2.43% (-5.39% to 2.48%). The RMS error of maximum dose to the spinal cord was 1.05% (-2.86% to 0.89%). An excellent agreement was observed between the measurement and the verification dose. In the patient treatments, the agreement in doses to the majority of PTVs and organs at risk is within 5% for the cumulative treatment course doses. The dosimetric error strongly depends on the error in multileaf collimator leaf opening time with a sensitivity correlating to the gantry rotation period.
    International journal of radiation oncology, biology, physics 02/2011; 82(2):1013-20. · 4.59 Impact Factor
  • W. Lu, D. Parnell, G. Olivera, D. Galmarini
    Medical Physics 01/2011; 38(6):3499-. · 2.91 Impact Factor
  • Medical Physics 01/2011; 38(6):3799-. · 2.91 Impact Factor
  • Source
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    ABSTRACT: Helical tomotherapy is a relatively new modality with integrated treatment planning and delivery hardware for radiation therapy treatments. In view of the uniqueness of the hardware design of the helical tomotherapy unit and its implications in routine quality assurance, the Therapy Physics Committee of the American Association of Physicists in Medicine commissioned Task Group 148 to review this modality and make recommendations for quality assurance related methodologies. The specific objectives of this Task Group are: (a) To discuss quality assurance techniques, frequencies, and tolerances and (b) discuss dosimetric verification techniques applicable to this unit. This report summarizes the findings of the Task Group and aims to provide the practicing clinical medical physicist with the insight into the technology that is necessary to establish an independent and comprehensive quality assurance program for a helical tomotherapy unit. The emphasis of the report is to describe the rationale for the proposed QA program and to provide example tests that can be performed, drawing from the collective experience of the task group members and the published literature. It is expected that as technology continues to evolve, so will the test procedures that may be used in the future to perform comprehensive quality assurance for helical tomotherapy units.
    Medical Physics 09/2010; 37(9):4817-53. · 2.91 Impact Factor
  • W Lu, M Chen, Q Chen, G Olivera
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    ABSTRACT: Purpose: IMRT treatment plan optimization requires a fast yet accurate algorithm to calculate intermediate dose in each iteration. Conventional finite size pencil beam (FSPB) approaches have limitations such as: limited resolution, significant pre‐calculation time, huge memory demand, and limited accuracy in the presence of heterogeneity. In this work, we present a fast dose calculation algorithm that overcomes the limitations of FSPB approaches. Material and Methods: By decomposing the infinitesimal beam dose kernel into the central axis (CAX) and lateral (LSF) components and taking the beam eye view (BEV), we established a Fluence‐map‐Convolution‐Broad‐Beam (FCBB) dose calculation formula. The Collapsed‐cone convolution/superposition (CCCS) doses on water phantom with standard setups and various field sizes are used to derive LSF and CAX, the commissioning data for FCBB. The proposed dose calculation involves a 2D fluence map convolution with LSF followed by table‐lookup with inverse square correction of CAX based on radiological distance calculated via ray‐tracing the density volume. The complexity of FCBB is O(N3) both spatially and temporally, which is orders of magnitude smaller than FSPB in spatial complexity and orders of magnitude faster than CCCS. We implemented FCBB algorithm in C++ language and compared it with CCCS using both simulated and clinical cases. The clinical cases include prostate, H&N and lung patients that were optimized with TomoTherapy TPS. Results: For all tested cases, simulated or clinical, the dose calculation time for CCCS varied from hundreds to thousands of seconds when run on a single PC. It was reduced to sub‐seconds to seconds for FCBB on the same PC. As for the dose differences between FCBB and CCCS, about 90–95% of voxels have Gamma indexes less than 1 for the 3mm/3% criteria. Conclusions: The FCBB algorithm has low memory demand, is ultra‐fast and accurate enough for intermediate dose calculation during IMRT optimization.
    Medical Physics 05/2010; 37(6):3339-3339. · 2.91 Impact Factor
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    ABSTRACT: Purpose: Design an accurate and efficient Monte Carlo (MC)‐based model for the future dynamic jaws feature of TomoTherapy which involves very small fields (< 1cm). In a previous study it was shown that one can simulate any field size from the 5 cm phase‐space file (PSF) using pre‐calculated intensity and angular longitudinal distributions. The present work extends TomoPen a MC model of TomoTherapy based on Penelope to dynamic jaw motion through two steps: (1) design a simplified and efficient MC model to calculate longitudinal and angular distributions and (2) interpolate and incorporate those distributions during an actual dynamic delivery. Material and methods: In the simplified MC model a full‐MC PSF is stored just above the jaws keeping future changes in target position accountable. The particles are duplicated according to cylindrical symmetry and only photon interactions are simulated through the jaws. Longitudinal intensity and angular distributions are then computed and stored for future interpolation and dynamic simulation. The integration over other dimensions (energy transverse direction…) ensures good statistics. Results: Using simple analytical modifiers of the 5 cm PSF it is straightforward to extend TomoPen to dynamic jaw simulation with similar accuracy as compared to full MC generated PSFs. Distributions computed with full MC or the simplified model showed no significant difference the quality of the interpolation being the only remaining potential source of discrepancies. Conclusions: A fast and comprehensive approach for efficient dynamic jaw simulation was devised. After building a database of intensity and angular distributions one can simulate dynamic jaws motion for all the field sizes with a single PSF keeping the same speed of TomoPen i.e. around 6 hours per treatment plan on a single CPU. Research sponsored by TomoTherapy Corporation
    Medical Physics 05/2010; 37(6):3467-3467. · 2.91 Impact Factor
  • M Chen, Q Chen, G Olivera, W Lu
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    ABSTRACT: Purpose: To generalize the equivalent field size (EFS) for non‐uniform fluence maps, to propose and verify a dose calculation method based on the generalized equivalent field size (GEFS). Method and Materials: A parallel‐beam dose table PDT(s,d) that consists of central axis dose (CAD) at various depths d of a water phantom for circular fields of various diameters s and can be obtained by the collapsed cone convolution/superposition (CCCS) method is used to define the phantom scatter Sp, Sp(s)=PDT(s,dref)/PDT(sref,dref), where sref and dref are the reference depth and reference diameter, respectively. Sp can be extended for arbitrary fluence maps by integrating fluence with respect to the phantom scatter with proper normalization. More precisely, the phantom scatter at a point c on the reference plane is Żf(x)/f∗(c)dSp(x‐c), where f∗(c) is the closest non‐zero fluence to f (c). For any given fluence map, GEFS of a point is defined to be the diameter of a circular field that has the same phantom scatter at the reference depth. Once GEFS is determined, we use PDT again to look up dose. Results: GEFS is consistent with EFS for square fields. We tested the proposed dose calculation on various field shapes with uniform or non‐uniform intensity. The resulting dose distributions are within 3%/3mm from those calculated by the CCCS approach except near the fluence edges in the buildup regions. Conclusion: EFS is a useful tool for estimating dose of non‐standard fields. However, its application is limited to uniform fluence maps. In this work, we extend the application to non‐uniform fluence maps and propose a dose calculation method based on GEFS. The agreement between dose calculations based on GEFS and CCCS indicates that dose can be well approximated by scaling CAD along the radiation beam when the phantom scatter is estimated through GEFS.
    Medical Physics 05/2010; 37(6):3326-3326. · 2.91 Impact Factor
  • Q Chen, M Chen, G Olivera, W Lu
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    ABSTRACT: Purpose: Dose calculation is essential in treatment planning in radiation therapy. Collapsed Cone Convolution/superposition (CCCS) based dose calculation is regarded as clinical standard in terms of accuracy. It is essential to run a CCCS based dose calculation before accept the plan. Our main objective is to develop an ultrafast GPU‐based CCCS dose calculation engine capable of performing near real‐time dose calculation with a single PC. Method and Materials: The dose calculation engine in commercial TomoTherapy® system is re‐implemented using NVIDIA'S CUDA language. In order to fully unleash the power of GPU, algorithms are modified to better suit the GPU architecture. A non‐voxel based ray‐tracing algorithm is used for TERMA calculation to avoid write‐conflicts and utilize GPU's free texture interpolation. An exponential dose kernel model is used for CCCS calculation that reduces the computation by over 100. Efforts are made to ensure the coalesced memory access throughout calculation. Results: The GPU dose engine running on a single NVIDIA GTX‐295 card is compared with the original commercial version running on a CPU cluster for both performance and accuracy. Extensive tests were run that includes different delivery modes (TomoHelicalSM, TomoDirectSM) and different disease sites on either patient CT or Tomo® cheese‐phantom. The GPU algorithm on one GTX‐295 is 8–16 times faster than original dose engine running on a 14‐blade (consists of 28 dual‐core Xeon5148 2.33GHz CPUs) TomoTherapy® high‐performance cluster. This translates to a speedup of 200‐400 over a single Xeon5148 CPU. The new GPU dose engine produces doses that are within 1%, 1 mm of original dose engine. It is also within 3% of the ion chamber and film measurement, passing all verification tests. Conclusion: We developed an ultrafast GPU‐based CCCS dose engine. Compared with the current cluster based commercial product, performance gains and accuracy verification are demonstrated.
    Medical Physics 05/2010; 37(6):3383-3383. · 2.91 Impact Factor
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    ABSTRACT: Extend to very small fields the validity of a Monte Carlo (MC) based model of TomoTherapy called TomoPen for future implementation of the dynamic jaws feature for helical TomoTherapy. First, the modelling of the electron source was revisited using a new method to measure source obscuration for very small fields (<1cm). The method consisted in MC simulations simulations and measurements of the central dose in a water phantom for a 10 cm x FW field scanned to deliver a 10 x 10 cm(2) fluence. FW, the longitudinal field width, was varied from 0.4 to 5 cm. The second part of the work consisted of adapting TomoPen to account for any configuration of the jaws in a fast and efficient way by using routinely only the phase-space file of the largest field (5 cm) and interpolated analytical information of phase-space files of smaller field widths. For the electron source fine tuning, it was shown that the best results were obtained for a 1.1mm wide spot. Our single phase-space method showed no significant differences compared to MC simulations of various field widths even though only longitudinal intensity and angular analytical functions were applied to the 5 cm phase-space. The designed model is able to simulate all jaw openings from the 5 cm field phase-space file by applying a bi-dimensional analytical function accounting for the fluence and the angular distribution in the longitudinal direction.
    Radiotherapy and Oncology 02/2010; 94(2):229-34. · 4.52 Impact Factor
  • E. Chao, D. Lucas, K. Ruchala, G. Olivera
    Medical Physics 01/2010; 37(6). · 2.91 Impact Factor
  • M. Chen, Q. Chen, G. Olivera, W. Lu
    Fuel and Energy Abstracts 01/2010; 78(3).
  • Medical Physics 01/2010; 37(6). · 2.91 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: History: Helical tomotherapy is a relatively new modality with integrated imaging, planning and delivery hardware for radiation therapy treatments. In view of the unique hardware design and its implications for routine quality assurance, the Therapy Physics Committee (TPC) of the AAPM commissioned Task Group 148 to review this modality and to make quality assurance recommendations. General Outline: Initial chapters provided a brief overview of the technology and describe unique aspects of the technology. These chapters are followed by three chapters that are dedicated to the delivery, imaging, and planning aspects. A final chapter summarizes the QA recommendations and details daily, monthly, quarterly, and annual procedures. Major Highlights: This report is designed to provide guidance to the physicist that is charged with establishing a routine QA program for helical tomotherapy. Since the imaging and treatment planning aspects are intimately connected to the physical machine hardware, each of these aspects is covered in this report such that TG‐148 provides comprehensive guidelines. Implementation Plan: The summary chapter list daily, monthly, quarterly, and annual tests. This chapter is designed to facilitate the implementation of the recommended QA procedures. Timeline for the Report Release: This task group was submitted in February 2010 to the Medical Physics Journal for review. Conflict of Interest: Gustavo Olivera is an employee of TomoTherapy, Inc.; John Balog owns TomoTherapy stock; Katja Langen hold a research agreement with TomoTherapy, Inc.Learning Objectives:1. Understand the unique aspects of helical tomotherapy2. Understand QA aspects of the delivery, imaging, and planning components of helical tomotherapy3. Implement a routine QA program for helical tomotherapy
    Medical Physics 01/2010; 37(6). · 2.91 Impact Factor
  • Medical Physics 01/2010; 37(6). · 2.91 Impact Factor

Publication Stats

3k Citations
393.49 Total Impact Points

Institutions

  • 2012–2014
    • 21st Century Oncology
      Redding, California, United States
  • 1998–2012
    • University of Wisconsin, Madison
      • • Department of Human Oncology
      • • Department of Medical Physics
      Mississippi, United States
  • 2008–2011
    • Catholic University of Louvain
      • Institute of Experimental and Clinical Research (IREC)
      Walloon Region, Belgium
  • 2005–2009
    • University of Texas MD Anderson Cancer Center
      • Division of Radiation Oncology
      Houston, TX, United States
  • 2007
    • Instituto de Física Rosario
      Rosario, Santa Fe, Argentina
  • 2003
    • University of Arkansas at Little Rock
      Little Rock, Arkansas, United States
  • 1995–1997
    • Rosario National University
      • Institute of Physics (IFIR)
      Rosario, Santa Fe, Argentina
  • 1996
    • National Scientific and Technical Research Council
      • IFIR Instituto de Física Rosario
      Buenos Aires, Buenos Aires F.D., Argentina