Sensitivity of low energy brachytherapy Monte Carlo dose calculations to uncertainties in human tissue composition

Landry, Guillaume; Reniers, Brigitte; Murrer, L.; Lutgens, Ludy; Gurp, Esther J. Bloemen-van; Pignol, Jean-Philippe; Keller, Brian; Beaulieu, Luc; Verhaegen, Frank

doi:10.1118/1.3477161

Cited by 82 publications

(81 citation statements)

References 47 publications

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“…The method allowed the determination of an effective Z and electron density of each voxel; this information was used for a more accurate classification. This principle was extended to BT with low energy photons by Landry et al (2010Landry et al ( , 2011aLandry et al ( , 2011b. The accuracy of effective Z numbers derived from dual-energy computed tomography (DECT) scans was investigated by Goodsitt et al (2011).…”

Section: Introductionmentioning

confidence: 99%

The potential of dual-energy computed tomography for quantitative decomposition of soft tissues to water, protein and lipid in brachytherapy

2013

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Abstract. Dosimetric accuracy of radiation treatment planning in brachytherapy depends on knowledge of tissue composition. It has been speculated that soft tissues can be decomposed to water, lipid and protein. The aim of our work is to evaluate the accuracy of such tissue decomposition. Selected abdominal soft tissues, whose average elemental compositions were taken from literature, were decomposed using dual energy computed tomography to water, lipid, and protein via the three-material decomposition method. The quality of the decomposition was assessed using relative differences between the (i) mass energy absorption and (ii) mass energy attenuation coefficients of the analyzed and approximated tissues. It was found that the relative differences were less than 2% for photon energies larger than 10 keV. The differences were notably smaller than the ones for water as the transport and dose scoring medium. The choice of the water, protein and lipid triplet resulted in negative elemental mass fractions for some analyzed tissues. As negative elemental mass fractions cannot be used in general purpose particle transport computer codes using the Monte Carlo method, other triplets should be used for the decomposition. These triplets may further improve the accuracy of the approximation as the differences were mainly caused by the lack of high-Z materials in the water, protein and lipid triplet.

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Section: Introductionmentioning

confidence: 99%

The potential of dual-energy computed tomography for quantitative decomposition of soft tissues to water, protein and lipid in brachytherapy

2013

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“…For example, neglecting tissue composition differences in low energy Pd-103 and I-125 permanent seed implants of the breast and prostate have been shown to lead to errors in dose-volume histogram (DVH) metrics used for prescription and plan assessment ranging from 8% to 40%. [3][4][5][6] Even higher energy brachytherapy sources, such as Ir-192 and Yb-169, have been shown to suffer from dose calculation errors on the order of 5%-30% when neglecting patient-specific tissue composition and geometry. 7,8 Recommended bulk tissue compositions 9 are derived from a handful of measurements that exhibit large sample-tosample variability.…”

Section: Introductionmentioning

confidence: 99%

Prospects for in vivo estimation of photon linear attenuation coefficients using postprocessing dual‐energy CT imaging on a commercial scanner: Comparison of analytic and polyenergetic statistical reconstruction algorithms

et al. 2013

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Purpose: Accurate patient-specific photon cross-section information is needed to support more accurate model-based dose calculation for low energy photon-emitting modalities in medicine such as brachytherapy and kilovoltage x-ray imaging procedures. A postprocessing dual-energy CT (pDECT) technique for noninvasive in vivo estimation of photon linear attenuation coefficients has been experimentally implemented on a commercial CT scanner and its accuracy assessed in idealized phantom geometries. Methods: Eight test materials of known composition and density were used to compare pDECTestimated linear attenuation coefficients to NIST reference values over an energy range from 10 keV to 1 MeV. As statistical image reconstruction (SIR) has been shown to reconstruct images with less random and systematic error than conventional filtered backprojection (FBP), the pDECT technique was implemented with both an in-house polyenergetic SIR algorithm, alternating minimization (AM), as well as a conventional FBP reconstruction algorithm. Improvement from increased spectral separation was also investigated by filtering the high-energy beam with an additional 0.5 mm of tin. The law of propagated uncertainty was employed to assess the sensitivity of the pDECT process to errors in reconstructed images. Results: Mean pDECT-estimated linear attenuation coefficients for the eight test materials agreed within 1% of NIST reference values for energies from 1 MeV down to 30 keV, with mean errors rising to between 3% and 6% at 10 keV, indicating that the method is unbiased when measurement and calibration phantom geometries are matched. Reconstruction with FBP and AM algorithms conferred similar mean pDECT accuracy. However, single-voxel pDECT estimates reconstructed on a 1 × 1 × 3 mm 3 grid are shown to be highly sensitive to reconstructed image uncertainty; in some cases pDECT attenuation coefficient estimates exhibited standard deviations on the order of 20% around the mean. Reconstruction with the statistical AM algorithm led to standard deviations roughly 40% to 60% less than FBP reconstruction. Additional tin filtration of the high energy beam exhibits similar pDECT estimation accuracy as the unfiltered beam, even when scanning with only 25% of the dose. Using the law of propagated uncertainty, low Z materials are found to be more sensitive to image reconstruction errors than high Z materials. Furthermore, it is estimated that reconstructed CT image uncertainty must be limited to less than 0.25% to achieve a target linear-attenuation coefficient estimation uncertainty of 3% at 28 keV. Conclusions: That pDECT supports mean linear attenuation coefficient measurement accuracies of 1% of reference values for energies greater than 30 keV is encouraging. However, the sensitivity of the pDECT measurements to noise and systematic errors in reconstructed CT images warrants further investigation in more complex phantom geometries. The investigated statistical reconstruction algorithm, AM, reduced random measurement uncertainty relative to FBP ...

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“…Due to the lower energy of the MEBXS, TG-43U1 functions will be strongly affected by tissue heterogeneity. Tissue heterogeneities for different radionuclidebased sources have been considered by many researchers (Meigooni and Nath, 1992;Landry et al, 2010;Yang and Rivard, 2011;Hyer et al, 2012;Chiu-Tsao et al, 2012) however there are not many works in the literature to investigate the influence of tissue heterogeneities for MEBXS (Mille et al, 2010). In MEBXS skin cancer treatment at different anatomical sites (i.e.…”

Section: Introductionmentioning

confidence: 99%

Influences of spherical phantom heterogeneities on dosimetric charactristics of miniature electronic brachytherapy X-ray sources: Monte Carlo study

Jashni

Safigholi

Meigooni

2015

Applied Radiation and Isotopes

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Sensitivity of low energy brachytherapy Monte Carlo dose calculations to uncertainties in human tissue composition

Cited by 82 publications

References 47 publications

The potential of dual-energy computed tomography for quantitative decomposition of soft tissues to water, protein and lipid in brachytherapy

The potential of dual-energy computed tomography for quantitative decomposition of soft tissues to water, protein and lipid in brachytherapy

Prospects for in vivo estimation of photon linear attenuation coefficients using postprocessing dual‐energy CT imaging on a commercial scanner: Comparison of analytic and polyenergetic statistical reconstruction algorithms

Influences of spherical phantom heterogeneities on dosimetric charactristics of miniature electronic brachytherapy X-ray sources: Monte Carlo study

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