Brian Wang

Simulation of organ-specific patient effective dose due to secondary neutrons in proton radiation treatment.

Cancer patients undergoing radiation treatment are exposed to high doses to the target (tumour), intermediate doses to adjacent tissues and low doses from scattered radiation to all parts of the body. In the case of proton therapy, secondary neutrons generated in the accelerator head and inside the patient reach many areas in the patient body. Due to the improved efficacy of management of cancer patients, the number of long term survivors post-radiation treatment is increasing substantially. This results in concern about the risk of radiation-induced cancer appearing at late post-treatment times. This paper presents a case study to determine the effective dose from secondary neutrons in patients undergoing proton treatment. A whole-body patient model, VIP-Man, was employed as the patient model. The geometry dataset generated from studies made on VIP-Man was implemented into the GEANT4 Monte Carlo code. Two proton treatment plans for tumours in the lung and paranasal sinus were simulated. The organ doses and ICRP-60 radiation and tissue weighting factors were used to calculate the effective dose. Results show whole body effective doses for the two proton plans of 0.162 Sv and 0.0266 Sv, respectively, to which the major contributor is due to neutrons from the proton treatment nozzle. There is a substantial difference among organs depending on the treatment site.

Hypofractionated stereotactic radiotherapy for the treatment of brain metastases.

This retrospective review evaluated the efficacy and toxicity profiles of various dose fractionations using hypofractionated stereotactic radiotherapy (HSRT) in the treatment of brain metastases.

Monte Carlo modeling of a High‐Sensitivity MOSFET dosimeter for low‐ and medium‐energy photon sources

Metal-oxide-semiconductor field effect transistor (MOSFET) dosimeters are increasingly utilized in radiation therapy and diagnostic radiology. While it is difficult to characterize the dosimeter responses for monoenergetic sources by experiments, this paper reports a detailed Monte Carlo simulation model of the High-Sensitivity MOSFET dosimeter using Monte Carlo N-Particle (MCNP) 4C. A dose estimator method was used to calculate the dose in the extremely thin sensitive volume. Efforts were made to validate the MCNP model using three experiments: (1) comparison of the simulated dose with the measurement of a Cs-137 source, (2) comparison of the simulated dose with analytical values, and (3) comparison of the simulated energy dependence with theoretical values. Our simulation results show that the MOSFET dosimeter has a maximum response at about 40 keV of photon energy. The energy dependence curve is also found to agree with the predicted value from theory within statistical uncertainties. The angular dependence study shows that the MOSFET dosimeter has a higher response (about 8%) when photons come from the epoxy side, compared with the kapton side for the Cs-137 source.

Apparatus dependence of normal brain tissue dose in stereotactic radiosurgery for multiple brain metastases

OBJECT Technical improvements in commercially available radiosurgery platforms have made it practical to treat a large number of intracranial targets. The goal of this study was to investigate whether the dose to normal brain when planning radiosurgery to multiple targets is apparatus dependent. METHODS The authors selected a single case involving a patient with 12 metastatic lesions widely distributed throughout the brain as visualized on contrast-enhanced CT. Target volumes and critical normal structures were delineated with Leksell Gamma Knife Perfexion software. The imaging studies including the delineated contours were digitally exported into the CyberKnife and Novalis multileaf collimator-based planning systems for treatment planning using identical target dose goals and dose-volume constraints. Subsets of target combinations (3, 6, 9, or 12 targets) were planned separately to investigate the relationship of number of targets and radiosurgery platform to the dose to normal brain. RESULTS Despite similar target dose coverage and dose to normal structures, the dose to normal brain was strongly apparatus dependent. A nonlinear increase in dose to normal brain volumes with increasing number of targets was also noted. CONCLUSIONS The dose delivered to normal brain is strongly dependent on the radiosurgery platform. How general this conclusion is and whether apparatus-dependent differences are related to differences in hardware design or differences in dose-planning algorithms deserve further investigation.

4D MAP Image Reconstruction Incorporating Organ Motion

Four-dimensional respiratory correlated computed tomography (4D RCCT) has been widely used for studying organ motion. Most current algorithms use binning techniques which introduce artifacts that can seriously hamper quantitative motion analysis. In this paper, we develop an algorithm for tracking organ motion which uses raw time-stamped data and simultaneously reconstructs images and estimates deformations in anatomy. This results in a reduction of artifacts and an increase in signal-to-noise ratio (SNR). In the case of CT, the increased SNR enables a reduction in dose to the patient during scanning. This framework also facilitates the incorporation of fundamental physical properties of organ motion, such as the conservation of local tissue volume. We show in this paper that this approach is accurate and robust against noise and irregular breathing for tracking organ motion. A detailed phantom study is presented, demonstrating accuracy and robustness of the algorithm. An example of applying this algorithm to real patient image data is also presented, demonstrating the utility of the algorithm in reducing artifacts.

4D CT image reconstruction with diffeomorphic motion model.

Four-dimensional (4D) respiratory correlated computed tomography (RCCT) has been widely used for studying organ motion. Most current RCCT imaging algorithms use binning techniques that are susceptible to artifacts and challenge the quantitative analysis of organ motion. In this paper, we develop an algorithm for analyzing organ motion which uses the raw, time-stamped imaging data to reconstruct images while simultaneously estimating deformation in the subjects anatomy. This results in reduction of artifacts and facilitates a reduction in dose to the patient during scanning while providing equivalent or better image quality as compared to RCCT. The framework also incorporates fundamental physical properties of organ motion, such as the conservation of local tissue volume. We demonstrate that this approach is accurate and robust against noise and irregular breathing patterns. We present results for a simulated cone beam CT phantom, as well as a detailed real porcine liver phantom study demonstrating accuracy and robustness of the algorithm. An example of applying this algorithm to real patient image data is also presented.

Dose reconstruction for intensity-modulated radiation therapy using a non-iterative method and portal dose image

A straightforward and accurate method was developed to verify the delivery of intensity-modulated radiation therapy (IMRT) and to reconstruct the dose in a patient. The method is based on a computational algorithm that linearly describes the physical relationship between beamlets and dose-scoring voxels in a patient and the dose image from an electronic portal imaging device (EPID). The relationship is expressed in the form of dose response functions (responses) that are quantified using Monte Carlo (MC) particle transport techniques. From the dose information measured by the EPID the received patient dose is reconstructed by inversely solving the algorithm. The unique and novel non-iterative feature of this algorithm sets it apart from many existing dose reconstruction methods in the literature. This study presents the algorithm in detail and validates it experimentally for open and IMRT fields. Responses were first calculated for each beamlet of the selected fields by MC simulation. In-phantom and exit film dosimetry were performed on a flat phantom. Using the calculated responses and the algorithm, the exit film dose was used to inversely reconstruct the in-phantom dose, which was then compared with the measured in-phantom dose. The dose comparison in the phantom for all irradiated fields showed a pass rate of higher than 90% dose points given the criteria of dose difference of 3% and distance to agreement of 3 mm.

Revealing CD38 cellular localization using a cell permeable, mechanism-based fluorescent small-molecule probe.

Nicotinamide adenine dinucleotide (NAD) is increasingly recognized as an important signaling molecule that affects numerous biological pathways. Thus, enzymes that metabolize NAD can have important biological functions. One NAD-metabolizing enzyme in mammals is CD38, a type II transmembrane protein that converts NAD primarily to adenosine diphosphate ribose (ADPR) and a small amount of cyclic adenosine diphosphate ribose (cADPR). Localization of CD38 was originally thought to be only on the plasma membrane, but later reports showed either significant or solely, intracellular CD38. With the efficient NAD-hydrolysis activity, the intracellular CD38 may lead to depletion of cellular NAD, thus producing harmful effects. Therefore, the intracellular localization of CD38 needs to be carefully validated. Here, we report the synthesis and application of a cell permeable, fluorescent small molecule (SR101–F-araNMN) that can covalently label enzymatically active CD38 with minimal perturbation of live cells. Using this fluorescent probe, we revealed that CD38 is predominately on the plasma membrane of Raji and retinoic acid (RA)-treated HL-60 cells. Additionally, the probe revealed no CD38 expression in K562 cells, which was previously reported to have solely intracellular CD38. The finding that very little intracellular CD38 exists in these cell lines suggests that the major enzymatic function of CD38 is to hydrolyze extracellular rather than intracellular NAD. The fluorescent activity-based probes that we developed allow the localization of CD38 in different cells to be determined, thus enabling a better understanding of the physiological function.

Quantifying variability in radiation dose due to respiratory-induced tumor motion

State of the art radiation treatment methods such as hypo-fractionated stereotactic body radiation therapy (SBRT) can successfully destroy tumor cells and avoid damaging healthy tissue by delivering high-level radiation dose that precisely conforms to the tumor shape. Though these methods work well for stationary tumors, SBRT dose delivery is particularly susceptible to organ motion, and few techniques capable of resolving and compensating for respiratory-induced organ motion have reached clinical practice. The current treatment pipeline cannot accurately predict nor account for respiratory-induced motion in the abdomen that may result in significant displacement of target lesions during the breathing cycle. Sensitivity of dose deposition to respiratory-induced organ motion represents a significant challenge and may account for observed discrepancies between predictive treatment plan indicators and clinical patient outcomes. Improved treatment-planning and delivery of SBRT requires an accurate prediction of dose deposition uncertainties resulting from respiratory motion. To accomplish this goal, we developed a framework that models both organ displacement in response to respiration and the underlying random variations in patient-specific breathing patterns. Our organ deformation model is a four-dimensional maximum a posteriori (MAP) estimation of tissue deformation as a function of chest wall amplitudes computed from clinically obtained respiratory-correlated computed tomography (RCCT) images. We characterize patient-specific respiration as the probability density function (PDF) of chest wall amplitudes and model patient breathing patterns as a random process. We then combine the patient-specific organ motion and stochastic breathing models to calculate the resulting variability in radiation dose accumulation. This process allows us to predict uncertainties in dose delivery in the presence of organ motion and identify tissues at risk of receiving insufficient or harmful levels of radiation.

Adjoint Monte Carlo method for prostate external photon beam treatment planning: an application to 3D patient anatomy

Recently, the theoretical framework of the adjoint Monte Carlo (AMC) method has been developed using a simplified patient geometry. In this study, we extended our previous work by applying the AMC framework to a 3D anatomical model called VIP-Man constructed from the Visible Human images. First, the adjoint fluxes for the prostate (PTV) and rectum and bladder (organs at risk (OARs)) were calculated on a spherical surface of 1 m radius, centred at the centre of gravity of PTV. An importance ratio, defined as the PTV dose divided by the weighted OAR doses, was calculated for each of the available beamlets to select the beam angles. Finally, the detailed doses in PTV and OAR were calculated using a forward Monte Carlo simulation to include the electron transport. The dose information was then used to generate dose volume histograms (DVHs). The Pinnacle treatment planning system was also used to generate DVHs for the 3D plans with beam angles obtained from the AMC (3D-AMC) and a standard six-field conformal radiation therapy plan (3D-CRT). Results show that the DVHs for prostate from 3D-AMC and the standard 3D-CRT are very similar, showing that both methods can deliver prescribed dose to the PTV. A substantial improvement in the DVHs for bladder and rectum was found for the 3D-AMC method in comparison to those obtained from 3D-CRT. However, the 3D-AMC plan is less conformal than the 3D-CRT plan because only bladder, rectum and PTV are considered for calculating the importance ratios. Nevertheless, this study clearly demonstrated the feasibility of the AMC in selecting the beam directions as a part of a treatment planning based on the anatomical information in a 3D and realistic patient anatomy.