G. Olivera

21st Century Oncology, Redding, California, United States

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Publications (245)613.92 Total impact

  • Radiotherapy and Oncology 12/2014; 111:S158-S159. DOI:10.1016/S0167-8140(15)31612-1 · 4.36 Impact Factor
  • X. Mo · Y. Chen · M. Chen · D. Parnell · S. Key · W. Lu · G. Olivera · D. Galmarini
    International journal of radiation oncology, biology, physics 09/2014; 90(1):S741. DOI:10.1016/j.ijrobp.2014.05.2154 · 4.26 Impact Factor
  • Y. Chen · M. Reeher · X. Mo · M. Chen · G. Olivera · S. Key · D.W. Parnell · D. Galmarini · W. Lu
    International journal of radiation oncology, biology, physics 09/2014; 90(1):S740. DOI:10.1016/j.ijrobp.2014.05.2153 · 4.26 Impact Factor
  • International journal of radiation oncology, biology, physics 09/2014; 90(1):S127. DOI:10.1016/j.ijrobp.2014.05.570 · 4.26 Impact Factor
  • W. Lu · X. Mo · M. Chen · Y. Chen · D. Parnell · S. Key · G. Olivera · D. Galmarini
    International journal of radiation oncology, biology, physics 09/2014; 90(1):S820. DOI:10.1016/j.ijrobp.2014.05.2363 · 4.26 Impact Factor
  • M Chen · X Mo · Y Chen · D Parnell · S Key · G Olivera · W Galmarini · W Lu
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    ABSTRACT: Purpose: To efficiently calculate the head scatter fluence for an arbitrary intensity-modulated field with any source distribution using the source occlusion model.
    Medical Physics 06/2014; 41(6):223-223. DOI:10.1118/1.4888337 · 2.64 Impact Factor
  • Y Chen · X Mo · M Chen · G Olivera · M Reeher · D Parnell · S Key · D Galmarini · W Lu
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    ABSTRACT: Purpose: An accurate leaf fluence model can be used in applications such as patient specific delivery QA and in-vivo dosimetry for TomoTherapy systems. It is known that the total fluence is not a linear combination of individual leaf fluence due to leakage-transmission, tongue-and-groove, and source occlusion effect. Here we propose a method to model the nonlinear effects as linear terms thus making the MLC-detector system a linear system.
    Medical Physics 06/2014; 41(6):335-336. DOI:10.1118/1.4888808 · 2.64 Impact Factor
  • M. Chen · X. Mo · D. Parnell · G. Olivera · D. Galmarini · W. Lu
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    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.
    Journal of Physics Conference Series 02/2014; 489(1). DOI:10.1088/1742-6596/489/1/012072
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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.
    Journal of Physics Conference Series 02/2014; 489(1). DOI:10.1088/1742-6596/489/1/012075
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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.
    Journal of Physics Conference Series 02/2014; 489(1). DOI:10.1088/1742-6596/489/1/012016
  • W. Lu · M. Chen · X. Mo · D. Parnell · G. Olivera · D. Galmarini
    International Journal of Radiation OncologyBiologyPhysics 10/2013; 87(2):S137-S138. DOI:10.1016/j.ijrobp.2013.06.354 · 4.26 Impact Factor
  • International Journal of Radiation OncologyBiologyPhysics 10/2013; 87(2):S709-S710. DOI:10.1016/j.ijrobp.2013.06.1880 · 4.26 Impact Factor
  • W Lu · M Chen · X Mo · D Parnell · G Olivera · D Galmarini
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    ABSTRACT: Purpose: To validate a simple portal dose calculator for plan QA and in‐vivo dosimetry. Methods: We model portal dose as a function of the fluence map, patient attenuation, patient scatter and portal response. Fluence maps are reconstructed using control‐point sequence in RTPlan. Patient attenuation is calculated via ray‐tracing through the patient CT. The effect of patient scatter and portal response is modeled by convolution, where the convolution kernel is derived from the commissioning measurements of different beam energies, different field sizes, different phantom thickness, and different source to image distances (SIDs). For various IMRT/3D plan, phantom and patient geometry, both in‐air and in‐transit portals were calculated. The calculations were compared with portal measurements. The Gamma Index of measurements against predicted portals with various dose difference (DD) criteria (1%, 2%, 3%, 4%, 5%, etc) and distance to agreement (DTA) criteria (1 mm, 2 mm, 3 mm, 4 mm, 5 mm, etc) were calculated. The Gamma pass rates of various DD and DTA criteria were evaluated and formed a Gamma table. Results: For various IMRT beams, the head, body and lung phantoms, the in‐air and in‐transit portal calculations matched well with portal measurements. The Gamma pass rates for in‐air portal are above 97% for 2 mm, 2% criteria and above 99% for 3 mm, 3% criteria. The Gamma pass rates for in‐transit portal were above 90% for 2 mm, 2% criteria and above 95% for 3 mm, 3% criteria. Conclusion: The simple portal dose calculation model is validated via phantom measurements. The model could be used in clinic for in‐air and intransit portal prediction.
    Medical Physics 06/2013; 40(6):396. DOI:10.1118/1.4815238 · 2.64 Impact Factor
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    ABSTRACT: Purpose: Portal measurement is becoming an important tool for in vivo dosimetric verification, and Calypso provides real‐time tracking capability; however, when both work simultaneously, large interference arises for portal measurement. The purpose of this study is to investigate the interference of Calypso on portal measurement and mitigation of the interference by applying aluminum shielding over portal panels. Methods: For the same IMRT field and phantom setup, we acquired portal measurements at every 15 degree gantry angle, without and with Calypso, and for those measurements with Calypso, we also acquired portal measurements without and with aluminum shielding over the portal panels. The aluminum shielding consists of a layer of aluminum foil of 0.1 mm thickness covering the portal panel. The measurements without Calypso and without aluminum shielding were regarded as the reference images. All other measurements were regarded as the test images. We measured the deviation of the test images from the reference images by the amplitude difference and using the Gamma Index (3%, 3 mm). Results: With Calypso interference and without aluminum shielding, the signals are larger than the reference, and in some unfavorable gantry angles, the signals can be as much as 15% larger. With aluminum shielding, the interference was much reduced to ∼3% for those unfavorable angles, and the Gamma passing rate achieves 95% for most of the angles. Conclusion: The Calypso interference on portal measurements is gantry angle dependent due to panel orientation and proximity with respect to the Calypso transducer. Shielding on the portal panel can largely reduce electronic interference, and it is anticipated that with an improved complete shielding over the entire portal panel, the interference could be further reduced.
    Medical Physics 06/2013; 40(6):228. DOI:10.1118/1.4814544 · 2.64 Impact Factor
  • Practical Radiation Oncology 04/2013; 3(2 Suppl 1):S2-3. DOI:10.1016/j.prro.2013.01.011
  • 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. DOI:10.1118/1.4736147 · 2.64 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. DOI:10.1007/s11912-000-0064-2 · 2.89 Impact Factor
  • E Sterpin · Y Chen · W Lu · T R Mackie · G H Olivera · S Vynckier
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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. DOI:10.1118/1.3556560 · 2.64 Impact Factor
  • Source
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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. DOI:10.1016/j.ijrobp.2010.12.043 · 4.26 Impact Factor
  • W. Lu · D. Parnell · G. Olivera · D. Galmarini
    Medical Physics 01/2011; 38(6):3499-. DOI:10.1118/1.3612010 · 2.64 Impact Factor

Publication Stats

4k Citations
613.92 Total Impact Points


  • 2012–2014
    • 21st Century Oncology
      Redding, California, United States
  • 1999–2012
    • University of Wisconsin–Madison
      • • Department of Human Oncology
      • • Department of Medical Physics
      Madison, Wisconsin, United States
  • 2009
    • Catholic University of Louvain
      • Institute of Experimental and Clinical Research (IREC)
      Walloon Region, Belgium
  • 2007
    • Baylor College of Medicine
      Houston, Texas, United States
  • 1993–2007
    • Instituto de Física Rosario
      Rosario, Santa Fe, Argentina
  • 2006
    • University of Virginia
      Charlottesville, Virginia, United States
  • 2005
    • University of Texas MD Anderson Cancer Center
      Houston, Texas, United States
  • 1996–1997
    • Rosario National University
      • Institute of Physics (IFIR)
      Rosario, Santa Fe, Argentina
    • National Scientific and Technical Research Council
      • IFIR Instituto de Física Rosario
      Buenos Aires, Buenos Aires F.D., Argentina