Feasibility of isodose-shaped scintillation detectors for the measurement of gamma knife output factors.

PURPOSE: Scintillation detectors were 3D printed based on a gamma knife (GK) dose distribution to calculate the volume averaging effect. The collimator output factors were measured using isodose-shaped scintillators (ISSs) and compared with those of a micro-diamond detector and previous reports. METHODS: An absorbed dose distribution in a spherical dosimetry phantom with a radius of 8 cm was obtained from GK treatment planning software (Leksell GammaPlan [LGP], Elekta AB, Stockholm, Sweden). Two types of ISSs were fabricated to fit the 97.2% (ISS-1) and 95.6% (ISS-2) isodose surfaces. The volume averaging correction factors were obtained by dividing the absorbed dose to water in the central voxel (CV) by that in the ISS. The correction effect due to the difference between the ISS and water was calculated by Monte Carlo simulations. Ten ISS detectors, five of each type, were used to measure the output factors of the 4- and 8-mm collimators of a GK Icon to assess system consistency. The output factors of seven GKs were measured using two ISS detectors, one of each type, and a PTW T60019 (PTW, Freiburg, Germany) micro-diamond detector. RESULTS: The detector output ratios (DORs) measured using the five ISSs of each type were consistent, with standard uncertainties less than 0.2%. In the 4-mm field, the volume averaging correction factor ratios were 1.018 and 1.026, and the output factors after all corrections were 0.827 (0.006) and 0.825 (0.006) for ISS-1 and ISS-2, respectively. In the 8-mm field, the volume averaging correction factor ratios were 1.000 for both ISS types, and the output factors were 0.898 (0.003) and 0.900 (0.003) for ISS-1 and ISS-2, respectively. The ISS detectors could measure the output factors of a GK with uncertainties comparable to that of the PTW 60019 detector. The output factors of all detectors decreased with the dose rate. CONCLUSION: The volume averaging effect of an ISS developed in-house could be calculated using known dose distributions. The collimator output factors of the GK Perfexion/Icon models measured using ISS detectors were consistent with those of a commercial synthetic micro-diamond detector and recent studies.

A multivariate approach to determine electron beam parameters for a Monte Carlo 6 MV Linac model: Statistical and machine learning methods.

PURPOSE: This study aimed to determine the optimal initial electron beam parameters of a Linac for radiotherapy with a multivariate approach using statistical and machine-learning tools. METHODS: For MC beam commissioning, a 6 MV Varian Clinac was simulated using the Geant4 toolkit. The authors investigated the relations between simulated dose distribution and initial electron beam parameters, namely, mean energy (E), energy spread (ES), and radial beam size (RS). The goodness of simulation was evaluated by the slope of differences between the simulated and the golden beam data. The best-fit combination of the electron beam parameters that minimized the slope of dose difference was searched through multivariate methods using conventional statistical methods and machine-learning tools of the scikit-learn library. RESULTS: Simulation results with 87 combinations of the electron beam parameters were analyzed. Regardless of being univariate or multivariate, traditional statistical models did not recommend a single parameter set simultaneously minimizing slope of dose differences for percent depth dose (PDD) and lateral dose profile (LDP). Two machine learning classification modules, RandomForestClassifier and BaggingClassifier, agreed in recommending (E = 6.3 MeV, ES = ±5.0%, RS = 1.0 mm) for predicting simultaneous acceptance of PDD and LDP. CONCLUSIONS: The machine learning with random-forest and bagging classifier modules recommended a consistent result. It was possible to draw an optimal electron beam parameter set using multivariate methods for MC simulation of a radiotherapy 6 MV Linac.

Development of an IAEA phase-space dataset for the Leksell Gamma Knife® Perfexion™ using multi-threaded Geant4 simulations.

This study was conducted to develop a phase-space dataset in the International Atomic Energy Agency (IAEA) format for Monte Carlo (MC) simulations of the Leksell Gamma Knife® (LGK, Elekta Instrument AB, Stockholm, Sweden) Perfexion™ (PFX). An open-source MC code, namely, the Geant4 toolkit with a recently updated multi-threaded mode, was used to maximize the efficiency of the developed IAEA phase-space dataset. The absorbed dose profiles for single shots of the LGK PFX were calculated using the developed dataset and compared with those from radiochromic film measurements and Leksell GammaPlan® version 11.0.3 (LGP, Elekta Instruments) for verification. The mean relative absorbed dose differences in all single shots were less than 3.6% compared with the films and less than 4.0% compared with LGP. The collimator output factors were also calculated for all single shots and compared with the LGP results. The simulated collimator output factor was 0.816 ±â€¯0.003 for a 4-mm shot and 0.903 ±â€¯0.001 for an 8-mm shot in a spherical water phantom. The efficiency of the developed dataset was evaluated by comparing the times required for various simulations. Simulations with the phase-space dataset ran 25, 8.2 and 3.2 times faster than simulations without the phase-space dataset for 4-, 8-, and 16-mm shots, respectively. Using the dataset developed in this study, MC simulations of the LGK PFX can be performed more efficiently for various purposes, such as treatment plan verification and beam quality factor calculations.

Expression of multidrug resistance proteins in rat and human chronic pancreatitis.

BACKGROUND AND AIMS: The expression of the ABC-transporters MDR-1, MRP1, and MRP-2 was investigated in healthy pancreas and in chronic pancreatitis tissue samples in rats and humans to evaluate their possible involvement in a multidrug resistance of the pancreas with consequences for the pharmacologic treatment of pancreatic diseases. METHODS: Human pancreatic tissue samples of healthy tissue and chronic pancreatitis were collected during pancreas surgery. In rats, the time-course of the expression of transporter proteins was studied 14, 28, and 56 days after experimental induction of chronic pancreatitis. The expression of MDR-1, MRP-1, MRP-2, and furthermore, LRP and PAP was investigated by RT-PCR, Real Time TaqManPCR, and immunohistochemistry. RESULTS: In rat pancreas, MDR-1 (P-gp) and MRP-1 but in human pancreas MDR-1 (P-gp), MRP-1 and MRP-2 were found to be expressed. Chronic pancreatitis lead to an increased transcription of mRNA of MDR-1 (rat and human) and much lower, MRP-2 (human). CONCLUSIONS: The expression of P-gp and related transporters could have impact on the metabolism, distribution, and availability of various compounds, including drugs, in the pancreas. The results indicate that this could be more pronounced in chronic pancreatitis.