Development of a dosimeter prototype with machine learning based 3-D dose reconstruction capabilities

A 3-D dosimeter fills the need for treatment plan and delivery verification required by every modern radiation-therapy method used today. This report summarizes a proof-of-concept study to develop a water-equivalent solid 3-D dosimeter that is based on novel radiation-hard scintillating material. The active material of the prototype dosimeter is a blend of radiation-hard peroxide-cured polysiloxane plastic doped with scintillating agent P-Terphenyl and wavelength-shifter BisMSB. The prototype detector was tested with 6 MV and 10 MV X-ray beams at Ohio State University’s Comprehensive Cancer Center. A 3-D dose distribution was successfully reconstructed by a neural network specifically trained for this prototype. This report summarizes the material production procedure, the material’s water equivalency investigation, the design of the prototype dosimeter and its beam tests, as well as the details of the utilized machine learning approach and the reconstructed 3-D dose distributions.

Prototyping a Smart Contract Based Public Procurement to Fight Corruption

Corruption in public procurement is a worldwide appearance that causes immense financial and reputational damages. Especially in developing countries, corruption is a widespread issue due to secrecy and lack of transparency. An important instrument for transparency and accountability assurance is the record which is managed and controlled by recordkeeping systems. Blockchain technology and more precisely blockchain-based smart contracts are emerging technological tools that can be used as recordkeeping systems and a tool to mitigate some of the fraud involving public procurement records. Immutability, transparency, distribution and automation are some of the features of smart contracts already implemented in several applications to avoid malicious human interference. In this paper, we discuss some of the frauds in public procurement, and we propose smart contracts to automatize different stages of the public procurement procedure attempting to fix their biggest current weaknesses. The processes we have focused on include the bidding process, supplier habilitation and delivery verification. In the three subprocesses, common irregularities include human fallibility, improper information disclosure and hidden agreements which concern not only governments but also civil society. To show the feasibility and usability of our proposal, we have implemented a prototype that demonstrates the process using sample data.

Feasibility study of a verification method for proton and carbon ion radiotherapy plan delivery accuracy check

Background All plan verification systems available for particle therapy are designed for pre-treatment verification. The plan delivery accuracy during treatment are unknown. The purpose of this study is to introduce a verification method and develop a software for proton and carbon ion plan delivery accuracy check. Methods A program was developed using Matlab to reconstruct dose from beam parameters recorded in log files and compare the dose reconstructed with the dose calculated by treatment planning system (TPS). Ten carbon ion plans and ten proton plans were enrolled in this study for algorithm validation, sensitivity analysis and plan delivery verification. The dose reconstruction algorithm was validated by comparing the dose calculated by TPS with reconstructed dose using the same beam parameters. The sensitivity of gamma pass rate to spot size deviation, position deviation and particle number deviation were analyzed by comparing dose reconstructed from pseudo plans which have manually added errors with original plan dose. Then plan delivery verification using homemade software were done for the 20 actual treated plans. Results A program for plan delivery verification was developed. For the validation of dose reconstruction algorithm, the mean dose difference between reconstructed dose and plan dose were 0.70% ± 0.24% and 0.51% ± 0.25% for carbon ion and proton plans, respectively. According to our simulation, the Gamma pass rate of carbon ion beam is more sensitive to spot position deviation and particle number deviation, and the Gamma pass rate of proton beam is more sensitive to spot size deviation. For the actual plan delivery verification using homemade software, the mean gamma pass rate were 99.47% ± 0.48%, 99.36% ± 0.50% and 99.48% ± 0.50% for carbon ion beams and 99.92% ± 0.13%, 99.96% ±0.06% and 99.89% ±0.13% for proton beams at three different depth of high dose region using 3mm/3% criteria. Conclusions A software was programed and the algorithm was verified. The method we introduced and the software we made for plan delivery verification is feasible and reliable. The verification method presented in this study can be easily repeated in other hospital.