Appendix B: Interaction Data for Body Tissues

White, D. R.; Griffith, R. V.; Wilson, I. J.

doi:10.1093/jicru_os24.1.14

Cited by 11 publications

(6 citation statements)

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“…Therefore, an explicit comparison with our results (also shown in figure 4) was obtained by recovering the linear attenuation coefficient of the skin from its composition making use of the XMuDat database. For the sake of completeness, an equivalent recovery was also performed from the skin composition provided by the ICRU Report 46 (White et al 1992), also represented in figure 4. It can be seen that the overlap between the two recovered attenuations is not complete, meaning that the original chemical compositions are slightly different.…”

Section: Offline Onlinementioning

confidence: 99%

Quantitative characterization of breast tissues with dedicated CT imaging

et al. 2019

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A quantitative characterization of the soft tissues composing the human breast is achieved by means of a monochromatic CT phase-contrast imaging system, through accurate measurements of their attenuation coefficients within the energy range of interest for breast CT clinical examinations. Quantitative measurements of linear attenuation coefficients are performed on tomographic reconstructions of surgical samples, using monochromatic X-ray beams from a synchrotron source and a free space propagation setup. An online calibration is performed on the obtained reconstructions, in order to reassess the validity of the standard calibration procedure of the CT scanner. Three types of healthy tissues (adipose, glandular, and skin) and malignant tumors, when present, are considered from each sample. The measured attenuation coefficients are in very good agreement with the outcomes of similar studies available in the literature, although they span an energy range that was mostly neglected in the previous studies. No globally significant differences are observed between healthy and malignant dense tissues, although the number of considered samples does not appear sufficient to address the issue of a quantitative differentiation of tumors. The study assesses the viability of the proposed methodology for the measurement of linear attenuation coefficients, and provides a denser sampling of attenuation data in the energy range useful to breast CT.

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Section: Offline Onlinementioning

confidence: 99%

Quantitative characterization of breast tissues with dedicated CT imaging

et al. 2019

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“…Although Catphan materials should not be considered tissue-equivalent (Verhaegen and Devic 2005), in what follows we will refer to them as 'tissuesubstitutes' for the sake of simplicity. As reference biological tissues, we chose the 50 adult biological tissues reported in ICRU 46 (White et al 1992).…”

Section: Theoretical Evaluation Of Tissue-substitutesmentioning

confidence: 99%

Revisiting the single-energy CT calibration for proton therapy treatment planning: a critical look at the stoichiometric method

2018

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Despite extensive research in dual-energy computed tomography (CT), single-energy CT (SECT) is still the standard imaging modality in proton therapy treatment planning and, in this context, the stoichiometric calibration method is considered to be the most accurate to establish a relationship between CT numbers and proton stopping power. This work revisits the SECT calibration for proton therapy treatment planning, with special emphasis on the stoichiometric method. Three different sets of tissue-substitutes of known elemental composition (Gammex, CIRS and Catphan) were scanned with the same scanning protocol. A stoichiometric fit was performed for each set of tissue-substitutes. Based on that, the CT number, relative electron density and relative proton stopping power were calculated for ICRU 46 biological tissues and the different sets of tissue-substitutes. Despite common belief, it was found that the stoichiometric fit depends on the elemental composition of the tissue-substitutes used in the calibration, leading to differences in relative stopping power up to 3.5% for cortical bone. In addition, according to Rutherford et al (1976 Neuroradiology 11 15-21) parametrization of the atomic cross-section, CT numbers of Gammex tissue-substitutes and ICRU 46 biological tissues were found to be similar within the whole energy range relevant to computed tomography. Consequently, it was found that, for Gammex tissue-substitutes, the CT calibration curve resulting from the stoichiometric method agrees with that obtained by simple interpolation of experimental data. In conclusion, the stoichiometric method for SECT calibration seems to depend on the tissue-substitutes used for calibration-which could be regarded as an additional source of uncertainty in proton range for bone tissues. Furthermore, Gammex tissue-substitutes appear to be a good representative of biological tissues within the energy range relevant to computed tomography-making the stoichiometric method unnecessary.

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“…Another technique to overcome the lack of ED in MRI involves assigning a bulk rED to manually contoured targets and OARs. Some authors derive their rED values from the international commission on radiation units and measurements (ICRU) Report 46 (White and Wilson 1992). For example, Jonsson et al considered ICRU Report 46 rED values for cranium, femoral bone, lung, and soft tissue.…”

Section: Introductionmentioning

confidence: 99%

MRI-based IMRT planning for MR-linac: comparison between CT- and MRI-based plans for pancreatic and prostate cancers

et al. 2016

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The treatment planning in radiation therapy (RT) can be arranged to combine benefits of computed tomography (CT) and magnetic resonance imaging (MRI) together to maintain dose calculation accuracy and improved target delineation. Our aim is study the dosimetric impact of uniform relative electron density assignment on IMRT treatment planning with additional consideration given to the effect of a 1.5 T transverse magnetic field (TMF) in MR-Linac. A series of intensity modulated RT (IMRT) plans were generated for two representative tumor sites, pancreas and prostate, using CT and MRI datasets. Representative CT-based IMRT plans were generated to assess the impact of different electron density (ED) assignment on plan quality using CT without the presence of a 1.5 T TMF. The relative ED (rED) values used were taken from the ICRU report 46. Four types of rED assignment in the organs at risk (OARs), the planning target volumes (PTV) and in the non-specified tissue (NST) were considered. Dose was recalculated (no optimization) using a Monaco 5.09.07a research planning system employing Monte Carlo calculations with an option to include TMF. To investigate the dosimetric effect of different rED assignment, the dose-volume parameters (DVPs) obtained from these specific rED plans were compared to those obtained from the original plans based on CT. Overall, we found that uniform rED assignment results in differences in DVPs within 3% for the PTV and 5% for OAR. The presence of 1.5 T TMF on IMRT DVPs resulted in differences that were generally within 3% of the Gold St for both the pancreas and prostate. The combination of uniform rED assignment and TMF produced differences in DVPs that were within 4-5% of the Gold St. Larger differences in DVPs were observed for OARs on T2-based plans. The effects of using different rED assignments and the presence of 1.5 T TMF for pancreas and prostate IMRT plans are generally within 3% and 5% of PTV and OAR Gold St values. There are noticeable dosimetric differences between the CT- and MRI-based IMRT plans caused by a combination of anatomical changes between the two image acquisition times, uniform rED assignment and 1.5 T TMF.

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Appendix B: Interaction Data for Body Tissues

Cited by 11 publications

References 0 publications

Quantitative characterization of breast tissues with dedicated CT imaging

Quantitative characterization of breast tissues with dedicated CT imaging

Revisiting the single-energy CT calibration for proton therapy treatment planning: a critical look at the stoichiometric method

MRI-based IMRT planning for MR-linac: comparison between CT- and MRI-based plans for pancreatic and prostate cancers

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