Reporting and analyzing statistical uncertainties in Monte Carlo–based treatment planning

Chetty, Indrin J.; Roşu, Mihaela; Kessler, Marc L.; Fraass, Benedick A.; Haken, Randall K. Ten; Kong, Feng-Ming; McShan, Daniel L.

doi:10.1016/j.ijrobp.2006.03.039

Cited by 82 publications

(66 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…1.5ϫ 10 9 histories were simulated per plan, resulting in 1statistics of better than 0.5% on average within the target. 41 The plans calculated using the exhale homogeneous dataset were normalized to 100% at the isocenter. All the other plans were normalized to the isocenter dose from the reference exhale homogeneous dose distribution to illustrate dose changes for the same number of monitor units per beam as in the reference exhale plan.…”

Section: B Treatment Planningmentioning

confidence: 99%

The impact of breathing motion versus heterogeneity effects in lung cancer treatment planning

et al. 2007

Self Cite

View full text Add to dashboard Cite

The purpose of this study is to investigate the effects of tissue heterogeneity and breathing-induced motion/deformation on conformal treatment planning for pulmonary tumors and to compare the magnitude and the clinical importance of changes induced by these effects. Treatment planning scans were acquired at normal exhale/inhale breathing states for fifteen patients. The internal target volume (ITV) was defined as the union of exhale and inhale gross tumor volumes uniformly expanded by 5 mm. Anterior/posterior opposed beams (AP/PA) and three-dimensional (3D)-conformal plans were designed using the unit-density exhale ("static") dataset. These plans were further used to calculate (a) density-corrected ("heterogeneous") static dose and (b) heterogeneous cumulative dose, including breathing deformations. The DPM Monte Carlo code was used for dose computations. For larger than coin-sized tumors, relative to unit-density plans, tumor and lung doses increased in the heterogeneity-corrected plans. In comparing cumulative and static plans, larger normal tissue complication probability changes were observed for tumors with larger motion amplitudes and uncompensated breathing-induced hot/cold spots in lung. Accounting for tissue heterogeneity resulted in average increases of 9% and 7% in mean lung dose (MLD) for the 6 MV and 15 MV photon beams, respectively. Breathing-induced effects resulted in approximately 1% and 2% average decreases in MLD from the static value, for the 6 and 15 MV photon beams, respectively. The magnitude of these effects was not found to correlate with the treatment plan technique, i.e., AP/PA versus 3D-CRT. Given a properly designed ITV, tissue heterogeneity effects are likely to have a larger clinical significance on tumor and normal lung treatment evaluation metrics than four-dimensional respiratory-induced changes.

show abstract

Section: B Treatment Planningmentioning

confidence: 99%

The impact of breathing motion versus heterogeneity effects in lung cancer treatment planning

et al. 2007

Self Cite

View full text Add to dashboard Cite

show abstract

“…The photon cutoff energy (PCUT) and electron cutoff energy (ECUT) were set to 0.01 and 0.7 MeV, respectively, and the electron range rejection was set to 2 MeV for all Monte Carlo simulations. Dose calculations were performed with 300,000,000 histories to achieve a mean relative statistical uncertainty of 0.4% over all voxels with doses greater than 50% of the maximum dose.…”

Section: Methodsmentioning

confidence: 99%

Experimental verification of 4D Monte Carlo simulations of dose delivery to a moving anatomy

et al. 2017

View full text Add to dashboard Cite

show abstract

“…The unknown dose received by the patient TLDs was calculated using the individual calibration factor of the TLD rods relating their reading to the IC reading which received a known dose. In this study, the reference dosimeter is the IC described in deposition), and the local statistical uncertainty according to [10]. The squared sum of Edep and D are also provided and can be used to compute the statistical uncertainty when the simulation is split into multiple runs to improve computational efficiency.…”

Section: Clinical Studymentioning

confidence: 99%

“…The squared sum of Edep and D are also provided and can be used to compute the statistical uncertainty when the simulation is split into multiple runs to improve computational efficiency. Equation 1 defines the statistical uncertainty e k at pixel k, with N being the number of primary events, d kt the deposited energy in pixel k at primary event t [10][11][12]. S k is an estimate of the standard error of the mean dose in voxel k.…”

Section: Clinical Studymentioning

confidence: 99%

Monte-Carlo dosimetry for intraoperative radiotherapy using a low energy x-ray source

et al. 2015

View full text Add to dashboard Cite

Reporting and analyzing statistical uncertainties in Monte Carlo–based treatment planning

Cited by 82 publications

References 21 publications

The impact of breathing motion versus heterogeneity effects in lung cancer treatment planning

The impact of breathing motion versus heterogeneity effects in lung cancer treatment planning

Experimental verification of 4D Monte Carlo simulations of dose delivery to a moving anatomy

Monte-Carlo dosimetry for intraoperative radiotherapy using a low energy x-ray source

Contact Info

Product

Resources

About