Philippe Després

Dynamic 18F-FET PET in Newly Diagnosed Astrocytic Low-Grade Glioma Identifies High-Risk Patients

Because the clinical course of low-grade gliomas in the individual adult patient varies considerably and is unpredictable, we investigated the prognostic value of dynamic 18F-fluorethyltyrosine (18F-FET) PET in the early diagnosis of astrocytic low-grade glioma (World Health Organization grade II). Methods: Fifty-nine patients with newly diagnosed low-grade glioma and dynamic 18F-FET PET before histopathologic assessment were retrospectively investigated. 18F-FET PET analysis comprised a qualitative visual classification of lesions; assessment of the semiquantitative parameters maximal, mean, and total standardized uptake value as ratio to background and biologic tumor volume; and dynamic analysis of intratumoral 18F-FET uptake over time (increasing vs. decreasing time–activity curves). The correlation between PET parameters and progression-free survival, overall survival, and time to malignant transformation was investigated. Results: 18F-FET uptake greater than the background level was found in 34 of 59 tumors. Dynamic 18F-FET uptake analysis was available for 30 of these 34 patients. Increasing and decreasing time–activity curves were found in 18 and 12 patients, respectively. Neither the qualitative factor presence or absence of 18F-FET uptake nor any of the semiquantitative uptake parameters significantly influenced clinical outcome. In contrast, decreasing time–activity curves in the kinetic analysis were highly prognostic for shorter progression-free survival and time to malignant transformation (P < 0.001). Conclusion: Absence of 18F-FET uptake in newly diagnosed astrocytic low-grade glioma does not generally indicate an indolent disease course. Among the 18F-FET–positive gliomas, decreasing time–activity curves in dynamic 18F-FET PET constitute an unfavorable prognostic factor in astrocytic low-grade glioma and, by identifying high-risk patients, may ease treatment decisions.

Validating plastic scintillation detectors for photon dosimetry in the radiologic energy range.

PURPOSE Photon dosimetry in the kilovolt (kV) energy range represents a major challenge for diagnostic and interventional radiology and superficial therapy. Plastic scintillation detectors (PSDs) are potentially good candidates for this task. This study proposes a simple way to obtain accurate correction factors to compensate for the response of PSDs to photon energies between 80 and 150 kVp. The performance of PSDs is also investigated to determine their potential usefulness in the diagnostic energy range. METHODS A 1-mm-diameter, 10-mm-long PSD was irradiated by a Therapax SXT 150 unit using five different beam qualities made of tube potentials ranging from 80 to 150 kVp and filtration thickness ranging from 0.8 to 0.2 mmAl + 1.0 mmCu. The light emitted by the detector was collected using an 8-m-long optical fiber and a polychromatic photodiode, which converted the scintillation photons to an electrical current. The PSD response was compared with the reference free air dose rate measured with a calibrated Farmer NE2571 ionization chamber. PSD measurements were corrected using spectra-weighted corrections, accounting for mass energy-absorption coefficient differences between the sensitive volumes of the ionization chamber and the PSD, as suggested by large cavity theory (LCT). Beam spectra were obtained from x-ray simulation software and validated experimentally using a CdTe spectrometer. Correction factors were also obtained using Monte Carlo (MC) simulations. Percent depth dose (PDD) measurements were compensated for beam hardening using the LCT correction method. These PDD measurements were compared with uncorrected PSD data, PDD measurements obtained using Gafchromic films, Monte Carlo simulations, and previous data. RESULTS For each beam quality used, the authors observed an increase of the energy response with effective energy when no correction was applied to the PSD response. Using the LCT correction, the PSD response was almost energy independent, with a residual 2.1% coefficient of variation (COV) over the 80-150-kVp energy range. Monte Carlo corrections reduced the COV to 1.4% over this energy range. All PDD measurements were in good agreement with one another except for the uncorrected PSD data, in which an over-response was observed with depth (13% at 10 cm with a 100 kVp beam), showing that beam hardening had a non-negligible effect on the PSD response. A correction based on LCT compensated very well for this effect, reducing the over-response to 3%. CONCLUSION In the diagnostic energy range, PSDs show high-energy dependence, which can be corrected using spectra-weighted mass energy-absorption coefficients, showing no considerable sign of quenching between these energies. Correction factors obtained by Monte Carlo simulations confirm that the approximations made by LCT corrections are valid. Thus, PSDs could be useful for real-time dosimetry in radiology applications.

GPU‐accelerated regularized iterative reconstruction for few‐view cone beam CT

PURPOSE The present work proposes an iterative reconstruction technique designed for x-ray transmission computed tomography (CT). The main objective is to provide a model-based solution to the cone-beam CT reconstruction problem, yielding accurate low-dose images via few-views acquisitions in clinically acceptable time frames. METHODS The proposed technique combines a modified ordered subsets convex (OSC) algorithm and the total variation minimization (TV) regularization technique and is called OSC-TV. The number of subsets of each OSC iteration follows a reduction pattern in order to ensure the best performance of the regularization method. Considering the high computational cost of the algorithm, it is implemented on a graphics processing unit, using parallelization to accelerate computations. RESULTS The reconstructions were performed on computer-simulated as well as human pelvic cone-beam CT projection data and image quality was assessed. In terms of convergence and image quality, OSC-TV performs well in reconstruction of low-dose cone-beam CT data obtained via a few-view acquisition protocol. It compares favorably to the few-view TV-regularized projections onto convex sets (POCS-TV) algorithm. It also appears to be a viable alternative to full-dataset filtered backprojection. Execution times are of 1-2 min and are compatible with the typical clinical workflow for nonreal-time applications. CONCLUSIONS Considering the image quality and execution times, this method may be useful for reconstruction of low-dose clinical acquisitions. It may be of particular benefit to patients who undergo multiple acquisitions by reducing the overall imaging radiation dose and associated risks.

Fast dose calculation in magnetic fields with GPUMCD.

A new hybrid imaging-treatment modality, the MRI-Linac, involves the irradiation of the patient in the presence of a strong magnetic field. This field acts on the charged particles, responsible for depositing dose, through the Lorentz force. These conditions require a dose calculation engine capable of taking into consideration the effect of the magnetic field on the dose distribution during the planning stage. Also in the case of a change in anatomy at the time of treatment, a fast online replanning tool is desirable. It is improbable that analytical solutions such as pencil beam calculations can be efficiently adapted for dose calculations within a magnetic field. Monte Carlo simulations have therefore been used for the computations but the calculation speed is generally too slow to allow online replanning. In this work, GPUMCD, a fast graphics processing unit (GPU)-based Monte Carlo dose calculation platform, was benchmarked with a new feature that allows dose calculations within a magnetic field. As a proof of concept, this new feature is validated against experimental measurements. GPUMCD was found to accurately reproduce experimental dose distributions according to a 2%-2 mm gamma analysis in two cases with large magnetic field-induced dose effects: a depth-dose phantom with an air cavity and a lateral-dose phantom surrounded by air. Furthermore, execution times of less than 15 s were achieved for one beam in a prostate case phantom for a 2% statistical uncertainty while less than 20 s were required for a seven-beam plan. These results indicate that GPUMCD is an interesting candidate, being fast and accurate, for dose calculations for the hybrid MRI-Linac modality.

Sub-second high dose rate brachytherapy Monte Carlo dose calculations with bGPUMCD.

PURPOSE To establish the accuracy and speed ofbGPUMCD, a GPU-oriented Monte Carlo code used for high dose rate brachytherapy dose calculations. The first objective is to evaluate the time required for dose calculation when full Monte Carlo generated dose distribution kernels are used for plan optimization. The second objective is to assess the accuracy and speed when recalculating pre-optimized plans, consisting of many dwell positions. METHODS bGPUMCD is tested with three clinical treatment plans : one prostate case, one breast case, and one rectum case with a shielded applicator. Reference distributions, generated with GEANT4, are used as a basis of comparison. Calculations of full dose distributions of pre-optimized treatment plans as well as single dwell dosimetry are performed. Single source dosimetry, based on TG-43 parameters reproduction, is also presented for the microSelectron V2 (Nucletron, Veenendaal, The Netherlands). RESULTS In timing experiments, the computation of single dwell position dose kernels takes between 0.25 and 0.5 s.bGPUMCD can compute full dose distributions of previously optimized plans in ∼2 s. bGPUMCD is capable of computing pre-optimized brachytherapy plans within 1% for the prostate case and 2% for the breast and shielded applicator cases, when comparing the dosimetric parameters D90 and V100 of the reference (GEANT4) and bGPUMCD distributions. For all voxels within the target, an absolute average difference of approximately 1% is found for the prostate case, less than 2% for the breast case and less than 2% for the rectum case with shielded applicator. Larger point differences (>5%) are found within bony regions in the prostate case, where bGPUMCD underdoses compared to GEANT4. Single source dosimetry results are mostly within 2% for the radial function and within 1%-4% for the anisotropic function. CONCLUSIONS bGPUMCD has the potential to allow for fast MC dose calculation in a clinical setting for all phases of HDR treatment planning, from dose kernel calculations for plan optimization to plan recalculation.PURPOSE To establish the accuracy and speed of bGPUMCD, a GPU-oriented Monte Carlo code used for high dose rate brachytherapy dose calculations. The first objective is to evaluate the time required for dose calculation when full Monte Carlo generated dose distribution kernels are used for plan optimization. The second objective is to assess the accuracy and speed when recalculating pre-optimized plans, consisting of many dwell positions. METHODS bGPUMCD is tested with three clinical treatment plans : one prostate case, one breast case, and one rectum case with a shielded applicator. Reference distributions, generated with GEANT4, are used as a basis of comparison. Calculations of full dose distributions of pre-optimized treatment plans as well as single dwell dosimetry are performed. Single source dosimetry, based on TG-43 parameters reproduction, is also presented for the microSelectron V2 (Nucletron, Veenendaal, The Netherlands). RESULTS In timing experiments, the computation of single dwell position dose kernels takes between 0.25 and 0.5 s. bGPUMCD can compute full dose distributions of previously optimized plans in ∼2 s. bGPUMCD is capable of computing pre-optimized brachytherapy plans within 1% for the prostate case and 2% for the breast and shielded applicator cases, when comparing the dosimetric parameters D90 and V100 of the reference (GEANT4) and bGPUMCD distributions. For all voxels within the target, an absolute average difference of approximately 1% is found for the prostate case, less than 2% for the breast case and less than 2% for the rectum case with shielded applicator. Larger point differences (>5%) are found within bony regions in the prostate case, where bGPUMCD underdoses compared to GEANT4. Single source dosimetry results are mostly within 2% for the radial function and within 1%-4% for the anisotropic function. CONCLUSIONS bGPUMCD has the potential to allow for fast MC dose calculation in a clinical setting for all phases of HDR treatment planning, from dose kernel calculations for plan optimization to plan recalculation.

Validation of GPUMCD for low-energy brachytherapy seed dosimetry.

PURPOSE To validate GPUMCD, a new package for fast Monte Carlo dose calculations based on the GPU (graphics processing unit), as a tool for low-energy single seed brachytherapy dosimetry for specific seed models. As the currently accepted method of dose calculation in low-energy brachytherapy computations relies on severe approximations, a Monte Carlo based approach would result in more accurate dose calculations, taking in to consideration the patient anatomy as well as interseed attenuation. The first step is to evaluate the capability of GPUMCD to reproduce low-energy, single source, brachytherapy calculations which could ultimately result in fast and accurate, Monte Carlo based, brachytherapy dose calculations for routine planning. METHODS A mixed geometry engine was integrated to GPUMCD capable of handling parametric as well as voxelized geometries. In order to evaluate GPUMCD for brachytherapy calculations, several dosimetry parameters were computed and compared to values found in the literature. These parameters, defined by the AAPM Task-Group No. 43, are the radial dose function, the 2D anisotropy function, and the dose rate constant. These three parameters were computed for two different brachytherapy sources: the Amersham OncoSeed 6711 and the Imagyn IsoStar IS-12501. RESULTS GPUMCD was shown to yield dosimetric parameters similar to those found in the literature. It reproduces radial dose functions to within 1.25% for both sources in the 0.5< r <10 cm range. The 2D anisotropy function was found to be within 3% at r =5 cm and within 4% at r = 1 cm. The dose rate constants obtained were within the range of other values reported in the literature. CONCLUSION GPUMCD was shown to be able to reproduce various TG-43 parameters for two different low-energy brachytherapy sources found in the literature. The next step is to test GPUMCD as a fast clinical Monte Carlo brachytherapy dose calculations with multiple seeds and patient geometry, potentially providing more accurate results than the TG-43 formalism while being much faster than calculations using general purpose Monte Carlo codes.

Fast GPU-based Monte Carlo simulations for LDR prostate brachytherapy

The aim of this study was to evaluate the potential of bGPUMCD, a Monte Carlo algorithm executed on Graphics Processing Units (GPUs), for fast dose calculations in permanent prostate implant dosimetry. It also aimed to validate a low dose rate brachytherapy source in terms of TG-43 metrics and to use this source to compute dose distributions for permanent prostate implant in very short times. The physics of bGPUMCD was reviewed and extended to include Rayleigh scattering and fluorescence from photoelectric interactions for all materials involved. The radial and anisotropy functions were obtained for the Nucletron SelectSeed in TG-43 conditions. These functions were compared to those found in the MD Anderson Imaging and Radiation Oncology Core brachytherapy source registry which are considered the TG-43 reference values. After appropriate calibration of the source, permanent prostate implant dose distributions were calculated for four patients and compared to an already validated Geant4 algorithm. The radial function calculated from bGPUMCD showed excellent agreement (differences within 1.3%) with TG-43 accepted values. The anisotropy functions at r = 1 cm and r = 4 cm were within 2% of TG-43 values for angles over 17.5°. For permanent prostate implants, Monte Carlo-based dose distributions with a statistical uncertainty of 1% or less for the target volume were obtained in 30 s or less for 1 × 1 × 1 mm(3) calculation grids. Dosimetric indices were very similar (within 2.7%) to those obtained with a validated, independent Monte Carlo code (Geant4) performing the calculations for the same cases in a much longer time (tens of minutes to more than a hour). bGPUMCD is a promising code that lets envision the use of Monte Carlo techniques in a clinical environment, with sub-minute execution times on a standard workstation. Future work will explore the use of this code with an inverse planning method to provide a complete Monte Carlo-based planning solution.

GGEMS-Brachy: GPU GEant4-based Monte Carlo simulation for brachytherapy applications.

In brachytherapy, plans are routinely calculated using the AAPM TG43 formalism which considers the patient as a simple water object. An accurate modeling of the physical processes considering patient heterogeneity using Monte Carlo simulation (MCS) methods is currently too time-consuming and computationally demanding to be routinely used. In this work we implemented and evaluated an accurate and fast MCS on Graphics Processing Units (GPU) for brachytherapy low dose rate (LDR) applications. A previously proposed Geant4 based MCS framework implemented on GPU (GGEMS) was extended to include a hybrid GPU navigator, allowing navigation within voxelized patient specific images and analytically modeled (125)I seeds used in LDR brachytherapy. In addition, dose scoring based on track length estimator including uncertainty calculations was incorporated. The implemented GGEMS-brachy platform was validated using a comparison with Geant4 simulations and reference datasets. Finally, a comparative dosimetry study based on the current clinical standard (TG43) and the proposed platform was performed on twelve prostate cancer patients undergoing LDR brachytherapy. Considering patient 3D CT volumes of 400  × 250  × 65 voxels and an average of 58 implanted seeds, the mean patient dosimetry study run time for a 2% dose uncertainty was 9.35 s (≈500 ms 10(-6) simulated particles) and 2.5 s when using one and four GPUs, respectively. The performance of the proposed GGEMS-brachy platform allows envisaging the use of Monte Carlo simulation based dosimetry studies in brachytherapy compatible with clinical practice. Although the proposed platform was evaluated for prostate cancer, it is equally applicable to other LDR brachytherapy clinical applications. Future extensions will allow its application in high dose rate brachytherapy applications.

A study of potential numerical pitfalls in GPU-based Monte Carlo dose calculation

The purpose of this study was to evaluate the impact of numerical errors caused by the floating point representation of real numbers in a GPU-based Monte Carlo code used for dose calculation in radiation oncology, and to identify situations where this type of error arises. The program used as a benchmark was bGPUMCD. Three tests were performed on the code, which was divided into three functional components: energy accumulation, particle tracking and physical interactions. First, the impact of single-precision calculations was assessed for each functional component. Second, a GPU-specific compilation option that reduces execution time as well as precision was examined. Third, a specific function used for tracking and potentially more sensitive to precision errors was tested by comparing it to a very high-precision implementation. Numerical errors were found in two components of the program. Because of the energy accumulation process, a few voxels surrounding a radiation source end up with a lower computed dose than they should. The tracking system contained a series of operations that abnormally amplify rounding errors in some situations. This resulted in some rare instances (less than 0.1%) of computed distances that are exceedingly far from what they should have been. Most errors detected had no significant effects on the result of a simulation due to its random nature, either because they cancel each other out or because they only affect a small fraction of particles. The results of this work can be extended to other types of GPU-based programs and be used as guidelines to avoid numerical errors on the GPU computing platform.

The control of dynamical systems—recovering order from chaos—

Following a brief historical introduction of the notions of chaos in dynamical systems, we will present recent developments that attempt to profit from the rich structure and complexity of the chaotic dynamics. In particular, we will demonstrate the ability to control chaos in realistic complex environments. Several applications will serve to illustrate the theory and to highlight its advantages and weaknesses. The presentation will end with a survey of possible generalizations and extensions of the basic formalism as well as a discussion of applications outside the field of the physical sciences. Future research avenues in this rapidly growing field will also be addressed.