TOPAS-nBio validation for simulating water radiolysis and DNA damage under low-LET irradiation.

The chemical stage of the Monte Carlo track-structure simulation code Geant4-DNA has been revised and validated. The root-mean-square (RMS) empirical parameter that dictates the displacement of water molecules after an ionization and excitation event in Geant4-DNA has been shortened to better fit experimental data. The pre-defined dissociation channels and branching ratios were not modified, but the reaction rate coefficients for simulating the chemical stage of water radiolysis were updated. The evaluation of Geant4-DNA was accomplished with TOPAS-nBio. For that, we compared predicted time-dependentGvalues in pure liquid water for·OH, e-aq, and H2with published experimental data. For H2O2and H·, simulation of added scavengers at different concentrations resulted in better agreement with measurements. In addition, DNA geometry information was integrated with chemistry simulation in TOPAS-nBio to realize reactions between radiolytic chemical species and DNA. This was used in the estimation of the yield of single-strand breaks (SSB) induced by137Csγ-ray radiolysis of supercoiled pUC18 plasmids dissolved in aerated solutions containing DMSO. The efficiency of SSB induction by reaction between radiolytic species and DNA used in the simulation was chosen to provide the best agreement with published measurements. An RMS displacement of 1.24 nm provided agreement with measured data within experimental uncertainties for time-dependentGvalues and under the presence of scavengers. SSB efficiencies of 24% and 0.5% for·OH and H·, respectively, led to an overall agreement of TOPAS-nBio results within experimental uncertainties. The efficiencies obtained agreed with values obtained with published non-homogeneous kinetic model and step-by-step Monte Carlo simulations but disagreed by 12% with published direct measurements. Improvement of the spatial resolution of the DNA damage model might mitigate such disagreement. In conclusion, with these improvements, Geant4-DNA/TOPAS-nBio provides a fast, accurate, and user-friendly tool for simulating DNA damage under low linear energy transfer irradiation.

TOPAS-nBio: An Extension to the TOPAS Simulation Toolkit for Cellular and Sub-cellular Radiobiology.

The TOPAS Monte Carlo (MC) system is used in radiation therapy and medical imaging research, having played a significant role in making Monte Carlo simulations widely available for proton therapy related research. While TOPAS provides detailed simulations of patient scale properties, the fundamental unit of the biological response to radiation is a cell. Thus, our goal was to develop TOPAS-nBio, an extension of TOPAS dedicated to advance understanding of radiobiological effects at the (sub-)cellular, (i.e., the cellular and sub-cellular) scale. TOPAS-nBio was designed as a set of open source classes that extends TOPAS to model radiobiological experiments. TOPAS-nBio is based on and extends Geant4-DNA, which extends the Geant4 toolkit, the basis of TOPAS, to include very low-energy interactions of particles down to vibrational energies, explicitly simulates every particle interaction (i.e., without using condensed histories) and propagates radiolysis products. To further facilitate the use of TOPAS-nBio, a graphical user interface was developed. TOPAS-nBio offers full track-structure Monte Carlo simulations, integration of chemical reactions within the first millisecond, an extensive catalogue of specialized cell geometries as well as sub-cellular structures such as DNA and mitochondria, and interfaces to mechanistic models of DNA repair kinetics. We compared TOPAS-nBio simulations to measured and published data of energy deposition patterns and chemical reaction rates (G values). Our simulations agreed well within the experimental uncertainties. Additionally, we expanded the chemical reactions and species provided in Geant4-DNA and developed a new method based on independent reaction times (IRT), including a total of 72 reactions classified into 6 types between neutral and charged species. Chemical stage simulations using IRT were a factor of 145 faster than with step-by-step tracking. Finally, we applied the geometric/chemical modeling to obtain initial yields of double-strand breaks (DSBs) in DNA fibers for proton irradiations of 3 and 50 MeV and compared the effect of including chemical reactions on the number and complexity of DSB induction. Over half of the DSBs were found to include chemical reactions with approximately 5% of DSBs caused only by chemical reactions. In conclusion, the TOPAS-nBio extension to the TOPAS MC application offers access to accurate and detailed multiscale simulations, from a macroscopic description of the radiation field to microscopic description of biological outcome for selected cells. TOPAS-nBio offers detailed physics and chemistry simulations of radiobiological experiments on cells simulating the initially induced damage and links to models of DNA repair kinetics.

A New Standard DNA Damage (SDD) Data Format.

Our understanding of radiation-induced cellular damage has greatly improved over the past few decades. Despite this progress, there are still many obstacles to fully understand how radiation interacts with biologically relevant cellular components, such as DNA, to cause observable end points such as cell killing. Damage in DNA is identified as a major route of cell killing. One hurdle when modeling biological effects is the difficulty in directly comparing results generated by members of different research groups. Multiple Monte Carlo codes have been developed to simulate damage induction at the DNA scale, while at the same time various groups have developed models that describe DNA repair processes with varying levels of detail. These repair models are intrinsically linked to the damage model employed in their development, making it difficult to disentangle systematic effects in either part of the modeling chain. These modeling chains typically consist of track-structure Monte Carlo simulations of the physical interactions creating direct damages to DNA, followed by simulations of the production and initial reactions of chemical species causing so-called "indirect" damages. After the induction of DNA damage, DNA repair models combine the simulated damage patterns with biological models to determine the biological consequences of the damage. To date, the effect of the environment, such as molecular oxygen (normoxic vs. hypoxic), has been poorly considered. We propose a new standard DNA damage (SDD) data format to unify the interface between the simulation of damage induction in DNA and the biological modeling of DNA repair processes, and introduce the effect of the environment (molecular oxygen or other compounds) as a flexible parameter. Such a standard greatly facilitates inter-model comparisons, providing an ideal environment to tease out model assumptions and identify persistent, underlying mechanisms. Through inter-model comparisons, this unified standard has the potential to greatly advance our understanding of the underlying mechanisms of radiation-induced DNA damage and the resulting observable biological effects when radiation parameters and/or environmental conditions change.

Monte Carlo simulation of chemistry following radiolysis with TOPAS-nBio.

Simulation of water radiolysis and the subsequent chemistry provides important information on the effect of ionizing radiation on biological material. The Geant4 Monte Carlo toolkit has added chemical processes via the Geant4-DNA project. The TOPAS tool simplifies the modeling of complex radiotherapy applications with Geant4 without requiring advanced computational skills, extending the pool of users. Thus, a new extension to TOPAS, TOPAS-nBio, is under development to facilitate the configuration of track-structure simulations as well as water radiolysis simulations with Geant4-DNA for radiobiological studies. In this work, radiolysis simulations were implemented in TOPAS-nBio. Users may now easily add chemical species and their reactions, and set parameters including branching ratios, dissociation schemes, diffusion coefficients, and reaction rates. In addition, parameters for the chemical stage were re-evaluated and updated from those used by default in Geant4-DNA to improve the accuracy of chemical yields. Simulation results of time-dependent and LET-dependent primary yields Gx (chemical species per 100 eV deposited) produced at neutral pH and 25 °C by short track-segments of charged particles were compared to published measurements. The LET range was 0.05-230 keV µm-1. The calculated Gx values for electrons satisfied the material balance equation within 0.3%, similar for protons albeit with long calculation time. A smaller geometry was used to speed up proton and alpha simulations, with an acceptable difference in the balance equation of 1.3%. Available experimental data of time-dependent G-values for [Formula: see text] agreed with simulated results within 7% ± 8% over the entire time range; for [Formula: see text] over the full time range within 3% ± 4%; for H2O2 from 49% ± 7% at earliest stages and 3% ± 12% at saturation. For the LET-dependent Gx, the mean ratios to the experimental data were 1.11 ± 0.98, 1.21 ± 1.11, 1.05 ± 0.52, 1.23 ± 0.59 and 1.49 ± 0.63 (1 standard deviation) for [Formula: see text], [Formula: see text], H2, H2O2 and [Formula: see text], respectively. In conclusion, radiolysis and subsequent chemistry with Geant4-DNA has been successfully incorporated in TOPAS-nBio. Results are in reasonable agreement with published measured and simulated data.

Improved efficiency in Monte Carlo simulation for passive-scattering proton therapy.

The aim of this work was to improve the computational efficiency of Monte Carlo simulations when tracking protons through a proton therapy treatment head. Two proton therapy facilities were considered, the Francis H Burr Proton Therapy Center (FHBPTC) at the Massachusetts General Hospital and the Crocker Lab eye treatment facility used by University of California at San Francisco (UCSFETF). The computational efficiency was evaluated for phase space files scored at the exit of the treatment head to determine optimal parameters to improve efficiency while maintaining accuracy in the dose calculation. For FHBPTC, particles were split by a factor of 8 upstream of the second scatterer and upstream of the aperture. The radius of the region for Russian roulette was set to 2.5 or 1.5 times the radius of the aperture and a secondary particle production cut (PC) of 50 mm was applied. For UCSFETF, particles were split a factor of 16 upstream of a water absorber column and upstream of the aperture. Here, the radius of the region for Russian roulette was set to 4 times the radius of the aperture and a PC of 0.05 mm was applied. In both setups, the cylindrical symmetry of the proton beam was exploited to position the split particles randomly spaced around the beam axis. When simulating a phase space for subsequent water phantom simulations, efficiency gains between a factor of 19.9 ± 0.1 and 52.21 ± 0.04 for the FHTPC setups and 57.3 ± 0.5 for the UCSFETF setups were obtained. For a phase space used as input for simulations in a patient geometry, the gain was a factor of 78.6 ± 7.5. Lateral-dose curves in water were within the accepted clinical tolerance of 2%, with statistical uncertainties of 0.5% for the two facilities. For the patient geometry and by considering the 2% and 2mm criteria, 98.4% of the voxels showed a gamma index lower than unity. An analysis of the dose distribution resulted in systematic deviations below of 0.88% for 20% of the voxels with dose of 20% of the maximum or more.

A framework for implementation of organ effect models in TOPAS with benchmarks extended to proton therapy.

The aim of this work was to develop a framework for modeling organ effects within TOPAS (TOol for PArticle Simulation), a wrapper of the Geant4 Monte Carlo toolkit that facilitates particle therapy simulation. The DICOM interface for TOPAS was extended to permit contour input, used to assign voxels to organs. The following dose response models were implemented: The Lyman-Kutcher-Burman model, the critical element model, the population based critical volume model, the parallel-serial model, a sigmoid-based model of Niemierko for normal tissue complication probability and tumor control probability (TCP), and a Poisson-based model for TCP. The framework allows easy manipulation of the parameters of these models and the implementation of other models. As part of the verification, results for the parallel-serial and Poisson model for x-ray irradiation of a water phantom were compared to data from the AAPM Task Group 166. When using the task group dose-volume histograms (DVHs), results were found to be sensitive to the number of points in the DVH, with differences up to 2.4%, some of which are attributable to differences between the implemented models. New results are given with the point spacing specified. When using Monte Carlo calculations with TOPAS, despite the relatively good match to the published DVH's, differences up to 9% were found for the parallel-serial model (for a maximum DVH difference of 2%) and up to 0.5% for the Poisson model (for a maximum DVH difference of 0.5%). However, differences of 74.5% (in Rectangle1), 34.8% (in PTV) and 52.1% (in Triangle) for the critical element, critical volume and the sigmoid-based models were found respectively. We propose a new benchmark for verification of organ effect models in proton therapy. The benchmark consists of customized structures in the spread out Bragg peak plateau, normal tissue, tumor, penumbra and in the distal region. The DVH's, DVH point spacing, and results of the organ effect models are provided. The models were used to calculate dose response for a Head and Neck patient to demonstrate functionality of the new framework and indicate the degree of variability between the models in proton therapy.

Experimental validation of the TOPAS Monte Carlo system for passive scattering proton therapy.

PURPOSE: TOPAS (TOol for PArticle Simulation) is a particle simulation code recently developed with the specific aim of making Monte Carlo simulations user-friendly for research and clinical physicists in the particle therapy community. The authors present a thorough and extensive experimental validation of Monte Carlo simulations performed with TOPAS in a variety of setups relevant for proton therapy applications. The set of validation measurements performed in this work represents an overall end-to-end testing strategy recommended for all clinical centers planning to rely on TOPAS for quality assurance or patient dose calculation and, more generally, for all the institutions using passive-scattering proton therapy systems. METHODS: The authors systematically compared TOPAS simulations with measurements that are performed routinely within the quality assurance (QA) program in our institution as well as experiments specifically designed for this validation study. First, the authors compared TOPAS simulations with measurements of depth-dose curves for spread-out Bragg peak (SOBP) fields. Second, absolute dosimetry simulations were benchmarked against measured machine output factors (OFs). Third, the authors simulated and measured 2D dose profiles and analyzed the differences in terms of field flatness and symmetry and usable field size. Fourth, the authors designed a simple experiment using a half-beam shifter to assess the effects of multiple Coulomb scattering, beam divergence, and inverse square attenuation on lateral and longitudinal dose profiles measured and simulated in a water phantom. Fifth, TOPAS' capabilities to simulate time dependent beam delivery was benchmarked against dose rate functions (i.e., dose per unit time vs time) measured at different depths inside an SOBP field. Sixth, simulations of the charge deposited by protons fully stopping in two different types of multilayer Faraday cups (MLFCs) were compared with measurements to benchmark the nuclear interaction models used in the simulations. RESULTS: SOBPs' range and modulation width were reproduced, on average, with an accuracy of +1, -2 and ±3 mm, respectively. OF simulations reproduced measured data within ±3%. Simulated 2D dose-profiles show field flatness and average field radius within ±3% of measured profiles. The field symmetry resulted, on average in ±3% agreement with commissioned profiles. TOPAS accuracy in reproducing measured dose profiles downstream the half beam shifter is better than 2%. Dose rate function simulation reproduced the measurements within ∼2% showing that the four-dimensional modeling of the passively modulation system was implement correctly and millimeter accuracy can be achieved in reproducing measured data. For MLFCs simulations, 2% agreement was found between TOPAS and both sets of experimental measurements. The overall results show that TOPAS simulations are within the clinical accepted tolerances for all QA measurements performed at our institution. CONCLUSIONS: Our Monte Carlo simulations reproduced accurately the experimental data acquired through all the measurements performed in this study. Thus, TOPAS can reliably be applied to quality assurance for proton therapy and also as an input for commissioning of commercial treatment planning systems. This work also provides the basis for routine clinical dose calculations in patients for all passive scattering proton therapy centers using TOPAS.

TOPAS: an innovative proton Monte Carlo platform for research and clinical applications.

PURPOSE: While Monte Carlo particle transport has proven useful in many areas (treatment head design, dose calculation, shielding design, and imaging studies) and has been particularly important for proton therapy (due to the conformal dose distributions and a finite beam range in the patient), the available general purpose Monte Carlo codes in proton therapy have been overly complex for most clinical medical physicists. The learning process has large costs not only in time but also in reliability. To address this issue, we developed an innovative proton Monte Carlo platform and tested the tool in a variety of proton therapy applications. METHODS: Our approach was to take one of the already-established general purpose Monte Carlo codes and wrap and extend it to create a specialized user-friendly tool for proton therapy. The resulting tool, TOol for PArticle Simulation (TOPAS), should make Monte Carlo simulation more readily available for research and clinical physicists. TOPAS can model a passive scattering or scanning beam treatment head, model a patient geometry based on computed tomography (CT) images, score dose, fluence, etc., save and restart a phase space, provides advanced graphics, and is fully four-dimensional (4D) to handle variations in beam delivery and patient geometry during treatment. A custom-designed TOPAS parameter control system was placed at the heart of the code to meet requirements for ease of use, reliability, and repeatability without sacrificing flexibility. RESULTS: We built and tested the TOPAS code. We have shown that the TOPAS parameter system provides easy yet flexible control over all key simulation areas such as geometry setup, particle source setup, scoring setup, etc. Through design consistency, we have insured that user experience gained in configuring one component, scorer or filter applies equally well to configuring any other component, scorer or filter. We have incorporated key lessons from safety management, proactively removing possible sources of user error such as line-ordering mistakes. We have modeled proton therapy treatment examples including the UCSF eye treatment head, the MGH stereotactic alignment in radiosurgery treatment head and the MGH gantry treatment heads in passive scattering and scanning modes, and we have demonstrated dose calculation based on patient-specific CT data. Initial validation results show agreement with measured data and demonstrate the capabilities of TOPAS in simulating beam delivery in 3D and 4D. CONCLUSIONS: We have demonstrated TOPAS accuracy and usability in a variety of proton therapy setups. As we are preparing to make this tool freely available for researchers in medical physics, we anticipate widespread use of this tool in the growing proton therapy community.

Efficient voxel navigation for proton therapy dose calculation in TOPAS and Geant4.

A key task within all Monte Carlo particle transport codes is 'navigation', the calculation to determine at each particle step what volume the particle may be leaving and what volume the particle may be entering. Navigation should be optimized to the specific geometry at hand. For patient dose calculation, this geometry generally involves voxelized computed tomography (CT) data. We investigated the efficiency of navigation algorithms on currently available voxel geometry parameterizations in the Monte Carlo simulation package Geant4: G4VPVParameterisation, G4VNestedParameterisation and G4PhantomParameterisation, the last with and without boundary skipping, a method where neighboring voxels with the same Hounsfield unit are combined into one larger voxel. A fourth parameterization approach (MGHParameterization), developed in-house before the latter two parameterizations became available in Geant4, was also included in this study. All simulations were performed using TOPAS, a tool for particle simulations layered on top of Geant4. Runtime comparisons were made on three distinct patient CT data sets: a head and neck, a liver and a prostate patient. We included an additional version of these three patients where all voxels, including the air voxels outside of the patient, were uniformly set to water in the runtime study. The G4VPVParameterisation offers two optimization options. One option has a 60-150 times slower simulation speed. The other is compatible in speed but requires 15-19 times more memory compared to the other parameterizations. We found the average CPU time used for the simulation relative to G4VNestedParameterisation to be 1.014 for G4PhantomParameterisation without boundary skipping and 1.015 for MGHParameterization. The average runtime ratio for G4PhantomParameterisation with and without boundary skipping for our heterogeneous data was equal to 0.97: 1. The calculated dose distributions agreed with the reference distribution for all but the G4PhantomParameterisation with boundary skipping for the head and neck patient. The maximum memory usage ranged from 0.8 to 1.8 GB depending on the CT volume independent of parameterizations, except for the 15-19 times greater memory usage with the G4VPVParameterisation when using the option with a higher simulation speed. The G4VNestedParameterisation was selected as the preferred choice for the patient geometries and treatment plans studied.

A modular method to handle multiple time-dependent quantities in Monte Carlo simulations.

A general method for handling time-dependent quantities in Monte Carlo simulations was developed to make such simulations more accessible to the medical community for a wide range of applications in radiotherapy, including fluence and dose calculation. To describe time-dependent changes in the most general way, we developed a grammar of functions that we call 'Time Features'. When a simulation quantity, such as the position of a geometrical object, an angle, a magnetic field, a current, etc, takes its value from a Time Feature, that quantity varies over time. The operation of time-dependent simulation was separated into distinct parts: the Sequence samples time values either sequentially at equal increments or randomly from a uniform distribution (allowing quantities to vary continuously in time), and then each time-dependent quantity is calculated according to its Time Feature. Due to this modular structure, time-dependent simulations, even in the presence of multiple time-dependent quantities, can be efficiently performed in a single simulation with any given time resolution. This approach has been implemented in TOPAS (TOol for PArticle Simulation), designed to make Monte Carlo simulations with Geant4 more accessible to both clinical and research physicists. To demonstrate the method, three clinical situations were simulated: a variable water column used to verify constancy of the Bragg peak of the Crocker Lab eye treatment facility of the University of California, the double-scattering treatment mode of the passive beam scattering system at Massachusetts General Hospital (MGH), where a spinning range modulator wheel accompanied by beam current modulation produces a spread-out Bragg peak, and the scanning mode at MGH, where time-dependent pulse shape, energy distribution and magnetic fields control Bragg peak positions. Results confirm the clinical applicability of the method.

SU-E-T-478: Geometrical Splitting Technique to Improve the Computational Efficiency in Monte Carlo Calculations for Proton Therapy.

PURPOSE: To implement a geometry based particle splitting technique in order to reduce the computation time when generating treatment head phase space files for proton therapy dose calculations using Monte Carlo (MC) calculations and to validate the doses generated from these phase spaces with respect to reference simulations. METHODS: The treatment nozzles at the Francis H Burr Proton Therapy Center (FHBPTC) were modeled with a new MC tool ('TOPAS' based on Geant4). For variance reduction purposes, two particle-splitting planes were implemented, one downstream of the second ionization chamber the other upstream of the aperture of the nozzle and phase spaces in IAEA format were recovered. The symmetry of the proton beam was considered to split the particles by a factor of 4 per plane. Split particles were randomly positioned at different locations rotated around the beam axis. The computational efficiency was calculated and dose profiles compared for a voxelized water phantom for different treatment fields for both the reference and optimized simulations. Depth-dose curves and beam profiles were analyzed. Dose calculation in patients was simulated to compare the performance. RESULTS: Normalized computational efficiency between 10 and 14.5 were reached. Percentage difference between dose profiles in water for simulations done with and without particle splitting is within the statistical precision of 2%, 1 standard deviation. Dose distributions for the realistic patient treatment show differences up to 4% in the regions of interest, within 2 standard deviations. CONCLUSIONS: By considering the cylindrically symmetric region of the nozzle and the splitting planes separated at strategic distance, considerable time reduction can be achieved without compromising the precision. This approach will reduce the time for phase space simulations for clinical MC dose calculation at FHBPTC by more than a factor of 10.

SU-E-T-473: Performance Assessment of the TOPAS Tool for Particle Simulation for Proton Therapy Applications.

PURPOSE: The TOPAS Tool for Particle Simulation was developed to make Geant4 Monte Carlo simulation more readily available for research and clinical physicists. Before releasing this new tool to the proton therapy community, several test have been performed to ensure accurate simulations in a variety of proton therapy setups. METHODS: TOPAS can model a passive scattering or scanning beam treatment head, model a patient geometry based on CT images, score dose, fluence, etc., save and replay a phase space, provides advanced graphics, and is fully four-dimensional (4D) to handle variations in beam delivery and patient geometry during treatment. An innovative control system meets requirements for ease of use, reliability and repeatability without sacrificing flexibility. To test the TOPAS code, we modeled proton therapy treatment examples including the UCSF eye treatment beamline (UCSFETB), the MGH STAR radiosurgery beamline and the MGH gantry treatment head in passive scattering and scanning modes. The simulations included time-dependent geometry and time- dependent beam current delivery. RESULTS: At the UCSFETB, time- dependent depth dose distributions were accurately simulated with time- varying energy modulation from a rotating propeller. At the MGH STAR beamline, distal and proximal ranges agreed within measurement uncertainty and the shape of the simulated SOBP followed measured data. For the MGH gantry treatment head in passive scattering mode, SOBPs were simulated for the full set of range modulator wheel and second scatterer combinations. TOPAS simulation was within clinical required accuracy. For the MGH nozzle in scanning mode, a variety of scan patterns were simulated with fluence maps generated for cases including beam current modulation, energy modulation and target tracking. CONCLUSIONS: Our results demonstrate the functionality of TOPAS. They show agreement with measured data and demonstrate the capabilities of TOPAS in simulating beam delivery in 3D and 4D. This work was supported by IH/NCI under R01 CA 140735-01.

SU-E-T-500: Pencil-Beam versus Monte Carlo Based Dose Calculation for Proton Therapy Patients with Complex Geometries. Clinical Use of the TOPAS Monte Carlo System.

PURPOSE: To investigate the necessity of the verification of dose distributions using Monte Carlo (MC) simulations for proton therapy of head and neck patients and other complex patient geometries. METHODS: TOPAS, a TOol for PArticle Simulations that makes MC simulations easy-to-use for research and clinical use and is layered on top of Geant4, has been used to simulate the treatments of head and neck patients at the Massachusetts General Hospital (MGH). The resulting dose distributions have been compared to pencil beam calculations based on the XiO treatment planning system. Dose difference distributions were used to highlight areas where the two algorithms did not agree. Dose volume histograms are utilized to investigate the overall agreement of the planned doses in target structures. RESULTS: 21 head and neck patients, both nasopharynx and spinal cord, were investigated. The field complexity ranges from a single field up to 13 fields. For all patients, the dose in the clinical target volume agrees well. Nevertheless, differences in critical structures around the targets have been observed mostly due to range differences between the two algorithms. CONCLUSIONS: Pencil beam algorithms provide an accurate description of dose in the target volume. However, we conclude that the differences between MC simulations and pencil beam algorithms in regions outside the target for complex geometries, such as present in head and neck patients, support the necessity of routine use of MC simulations for treatment verifications before treatment. TOPAS is aiming to make such routine simulations available to all researchers and clinics. An automated interface utilizing TOPAS to enable such simulations has been developed at MGH and should become routinely used in the near future for patients with complex geometries. NIH/NCI R01 CA140735.

Sleep disorders in end-stage renal disease: 'Markers of inadequate dialysis'?

Excessive daytime sleepiness and sleep disorders, including sleep apnea syndrome, restless legs syndrome, and periodic limb movement disorder, occur with increased frequency in patients with end-stage renal disease (ESRD). The detection and management of sleep disorders in ESRD patients is often challenging but may have significant clinical benefits. Some of the poor quality of life in ESRD may be attributed to the presence of concomitant sleep disorders, yet the classical symptoms of sleep disorders (poor concentration, daytime sleepiness, and insomnia) are often ascribed to the uremic syndrome itself. Conventional risk factors and screening tools used in the diagnosis of sleep disorders seem to have limited applicability in dialysis patients implicating the unique pathophysiology of sleep disorders in ESRD. Emerging evidence suggests that sleep apnea may contribute to the augmented cardiovascular event rates and to the accelerated development of atherosclerosis in ESRD. Whether treatment of sleep disorders in ESRD patients can affect the high morbidity and mortality of ESRD patients has yet to be elucidated. To date, conventional renal replacement therapies do not appear to have a significant impact on the treatment of sleep disorders in ESRD. The promising therapeutic effects of optimal uremia control in the forms of nocturnal hemodialysis and renal transplantation on sleep disorders require further mechanistic and clinical studies.

Central venous catheter outcomes in nocturnal hemodialysis.

Central venous catheter (CVC) as hemodialysis (HD) access is associated with great morbidity and mortality in the end-stage renal disease population. Quotidian, nocturnal HD (NHD) is a novel dialysis modality associated with cardiovascular and quality of life benefits, yet there is a concern of a potential increase in vascular access-related complications through patient-directed access cannulation. We aimed to determine catheter incidence and prevalence in the NHD population and to compare rates of catheter-related: infection, thrombolytic administration, hospitalization, survival, and reasons for their loss before and after conversion to NHD. This observational cohort consisted of incident and prevalent NHD patients between 1 November 1993 and 31 May 2005. Rate comparisons were determined by Poisson analysis and catheter survival by Kaplan-Meier curves. Eighty-one CVCs in 33 patients accounted for 17 150 CVC days (CVCD); 40 CVCs were exclusively used for conventional three times weekly HD (CHD) and 25 CVCs were exclusively used during NHD. The incidence and prevalence of CVC use in our NHD population was 35 and 25%, respectively. Comparing CHD to NHD, no significant differences were seen in total rates of infection, thrombolytic administration, or access-related hospitalization. Catheter survival was superior in NHD vs CHD (P=0.03). Adverse terminal catheter events were higher during CHD than NHD (5.84 vs 2.92/1000 CVCD; P=0.03). CVC use and complications in NHD is comparable to that in CHD with the benefit of longer cumulative survival. More frequent CVC use should not be a deterrent to NHD.

Serum S-100beta as a possible marker of blood-brain barrier disruption.

Two brain-specific proteins, S-100beta and neuron-specific enolase (NSE), are released systemically after cerebral lesions, but S-100beta levels sometimes rise in the absence of neuronal damage. We hypothesized that S-100beta is a marker of blood-brain barrier (BBB) leakage rather than of neuronal damage. We measured both proteins in the plasma of patients undergoing iatrogenic BBB disruption with mannitol, followed by chemotherapy. Serum S-100beta increased significantly after mannitol infusion (P<0.05) while NSE did not. This suggests that S-100beta is an early marker of BBB opening that is not necessarily related to neuronal damage.

Effect of 131 iodine therapy on the course of Graves' ophthalmopathy: a quantitative analysis of extraocular muscle volumes using orbital magnetic resonance imaging.

There remains uncertainty as to the effect of radioactive iodine (131I) therapy on the associated ophthalmopathy (GO). Twenty newly diagnosed patients with Graves' hyperthyroidism treated with 131I (median dose, 15.5 mCi) were followed with ophthalmologic evaluations (OE) and magnetic resonance imaging (MRI) at baseline, 2, and 6 months, and with OE alone at 3 years. For MRI, the superior, inferior, and medial rectus muscle volumes and total muscle volumes (TMV) were measured. Replacement levothyroxine was initiated as low thyroxine (T4) levels were noted. At baseline, 10 patients (50%) showed evidence of mild GO by OE and/or MRI. There was a significant difference in TMV between the 20 patients with Graves' hyperthyroidism and 10 controls (mean +/- standard error [SE]; 2,652 +/- 118 vs. 2,046 +/- 96 mm3; P = 0.002) and between the 10 patients with and 10 without GO (3,006 +/- 96 vs. 2,298 +/- 61 mm3; P = 0.001). TMV correlated with the Hertel score (r = 0.56, P = 0.01). TMV showed no significant change at 2 or 6 months posttreatment. The inferior rectus volume increased slightly at 2 months posttreatment (P = 0.03) but remained stable at 6 months. Furthermore, no significant changes occurred in Hertel scores or in clinical assessments up to 3 years posttreatment and none showed worsening or new development of GO. In conclusion, our results show no significant risk for radioiodine-induced initiation or progression of mild GO.