The purpose of this study was to demonstrate that Monte Carlo treatment planning systems require tissue characterization (density and composition) as a function of CT number. A discrete set of tissue classes with a specific composition is introduced. In the current work we demonstrate that, for megavoltage photon radiotherapy, only the hydrogen content of the different tissues is of interest. This conclusion might have an impact on MRI-based dose calculations and on MVCT calibration using tissue substitutes. A stoichiometric calibration was performed, grouping tissues with similar atomic composition into 15 dosimetrically equivalent subsets. To demonstrate the importance of hydrogen, a new scheme was derived, with correct hydrogen content, complemented by oxygen (all elements differing from hydrogen are replaced by oxygen). Mass attenuation coefficients and mass stopping powers for this scheme were calculated and compared to the original scheme. Twenty-five CyberKnife treatment plans were recalculated by an in-house developed Monte Carlo system using tissue density and hydrogen content derived from the CT images. The results were compared to Monte Carlo simulations using the original stoichiometric calibration. Between 300 keV and 3 MeV, the relative difference of mass attenuation coefficients is under 1% within all subsets. Between 10 keV and 20 MeV, the relative difference of mass stopping powers goes up to 5% in hard bone and remains below 2% for all other tissue subsets. Dose-volume histograms (DVHs) of the treatment plans present no visual difference between the two schemes. Relative differences of dose indexes D98, D95, D50, D05, D02, and Dmean were analyzed and a distribution centered around zero and of standard deviation below 2% (3 σ) was established. On the other hand, once the hydrogen content is slightly modified, important dose differences are obtained. Monte Carlo dose planning in the field of megavoltage photon radiotherapy is fully achievable using only hydrogen content of tissues, a conclusion that might impact MRI dose calculation, but can also help selecting the optimal tissue substitutes when calibrating MVCT devices.
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http://dx.doi.org/10.1120/jacmp.v16i5.5586 | DOI Listing |
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College of Environmental Science and Engineering, Nankai University, 38 Tongyan Road, Jinnan District, 300350 Tianjin, China.
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View Article and Find Full Text PDFStat Med
February 2025
Department of Mathematical Sciences, The University of Texas at Dallas, Richardson, Texas.
Advances in next-generation sequencing technology have enabled the high-throughput profiling of metagenomes and accelerated microbiome studies. Recently, there has been a rise in quantitative studies that aim to decipher the microbiome co-occurrence network and its underlying community structure based on metagenomic sequence data. Uncovering the complex microbiome community structure is essential to understanding the role of the microbiome in disease progression and susceptibility.
View Article and Find Full Text PDFMed Phys
January 2025
Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, Kraków, Poland.
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View Article and Find Full Text PDFBiol Cybern
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Institute for Physics and Astronomy, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476, Potsdam, Germany.
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