Estimating Specific Patient Organ Dose for Chest CT Examinations with Monte Carlo Method

Comparison of average Water Equivalent diameter values between CTContour and vendor-specific estimates in CT dosimetry

PURPOSE

This study aimed to compare the average Water Equivalent Diameter (WED) values obtained from CTContour, an open-source program for Size-Specific Dose Estimate (SSDE) and WED calculation, and vendor-specific values provided by Philips scanners.

METHODS

A random sample of 50 adult and 50 paediatric abdomen-pelvis protocol CT images from Philips scanners were chosen at our Hospital and analysed using CTContour, and extracting average WED values from Philips from the images DICOM headers. The average WED values from the two methods were compared via Bland-Altman analysis to assess their agreement and reliability.

RESULTS

The average WED values obtained from CTContour were found to be slightly lower than those obtained from the vendor-specific calculations, with mean disagreements of -5.62% and -2.88% for the adult and paediatric datasets, respectively, with both methods providing clinically acceptable estimations of average WED. There was no statistically significant correlation between body habitus and the level of disagreement between methods.

CONCLUSIONS

This study demonstrates that CTContour can provide average WED measurements comparable to the vendor-specific calculations for SSDE and WED in CT dosimetry. Differences between programs are likely due to inherent differences in the methods employed to estimate WED automatically. Further research is warranted to validate these results for additional CT protocols beyond abdomen-pelvis studies.

Patient-specific fetal radiation dosimetry for pregnant patients undergoing abdominal and pelvic CT imaging

BACKGROUND

Accurate estimation of fetal radiation dose is crucial for risk-benefit analysis of radiological imaging, while the radiation dosimetry studies based on individual pregnant patient are highly desired.

PURPOSE

To use Monte Carlo calculations for estimation of fetal radiation dose from abdominal and pelvic computed tomography (CT) examinations for a population of patients with a range of variations in patients' anatomy, abdominal circumference, gestational age (GA), fetal depth (FD), and fetal development.

METHODS

Forty-four patient-specific pregnant female models were constructed based on CT imaging data of pregnant patients, with gestational ages ranging from 8 to 35 weeks. The simulation of abdominal and pelvic helical CT examinations was performed on three validated commercial scanner systems to calculate organ-level fetal radiation dose.

RESULTS

The absorbed radiation dose to the fetus ranged between 0.97 and 2.24 mGy, with an average of 1.63 ± 0.33 mGy. The CTDI_vol -normalized fetal dose ranged between 0.56 and 1.30, with an average of 0.94 ± 0.25. The normalized fetal organ dose showed significant correlations with gestational age, maternal abdominal circumference (MAC), and fetal depth. The use of ATCM technique increased the fetal radiation dose in some patients.

CONCLUSION

A technique enabling the calculation of organ-level radiation dose to the fetus was developed from models of actual anatomy representing a range of gestational age, maternal size, and fetal position. The developed maternal and fetal models provide a basis for reliable and accurate radiation dose estimation to fetal organs.

Model for Sustainable Financial Planning and Investment Financing Using Monte Carlo Method

The article deals with current issues of finance and investment planning with a selective focus on financial decision-making processes using sophisticated software tools. The article has a special significance in this period when it is necessary to re-evaluate and consider ways of appropriate and effective investment and financial policy in view of the restrictions in enterprises in Slovakia, which brings with it the global pandemic COVID-19 or another crisis in enterprises. The aim of the article is to propose a methodology as a tool for streamlining the investment activities of companies. The proposed methodology combines the usability of traditional and modern economic methods, making it an important tool for the sustainability and competitiveness of enterprises. Three variants of investment decisions in the enterprise were simulated using simulation in terms of two approaches. The first approach focuses on mathematical–economic calculations of deterministic modeling through traditional software tools. The second stochastic modeling uses the simulation of financial risks using a modern software tool using the Monte Carlo method. The output is the creation of a graphical management model in the form of an algorithm.