Correlation between CT numbers and tissue parameters needed for Monte Carlo simulations of clinical dose distributions

Abstract

We describe a new method to convert CT numbers into mass density and elemental weights of tissues required as input for dose calculations with Monte Carlo codes such as EGS4. As a first step, we calculate the CT numbers for 71 human tissues. To reduce the effort for the necessary fits of the CT numbers to mass density and elemental weights, we establish four sections on the CT number scale, each confined by selected tissues. Within each section, the mass density and elemental weights of the selected tissues are interpolated. For this purpose, functional relationships between the CT number and each of the tissue parameters, valid for media which are composed of only two components in varying proportions, are derived. Compared with conventional data fits, no loss of accuracy is accepted when using the interpolation functions. Assuming plausible values for the deviations of calculated and measured CT numbers, the mass density can be determined with an accuracy better than 0.04 g cm(-3). The weights of phosphorus and calcium can be determined with maximum uncertainties of 1 or 2.3 percentage points (pp) respectively. Similar values can be achieved for hydrogen (0.8 pp) and nitrogen (3 pp). For carbon and oxygen weights, errors up to 14 pp can occur. The influence of the elemental weights on the results of Monte Carlo dose calculations is investigated and discussed.

Monte Carlo Evaluation of Internal Dose and Distribution Imaging Due to Insoluble Radioactive Cs-Bearing Particles of Water Deposited Inside Lungs via Pulmonary Inhalation Using PHITS Code Combined with Voxel Phantom Data

“…For the present treatment of voxel computational phantoms referred to the adult reference male of ICRP 110 publication [19] we have compiled its CT values [20] formed by the DICOM format to the PHITS input data using the "dicom2phits" package program combined with the PHITS calculation code. This program has involved the data exchange functions based on the relationship between CT values [19,20] and material densities and compositions at each tissue or organ [14].…”

“…This program has involved the data exchange functions based on the relationship between CT values [19,20] and material densities and compositions at each tissue or organ [14]. In the present PHITS input file, we have generated the voxel phantom data with the smallest unit size of 0.98 0.98 10 mm 3 for each compartment of the respiratory tract regions around a human lung.…”

Jaw position uncertainty and adjacent fields in breast cancer radiotherapy

“…Tissue segmentation is performed by the formalism in Schneider et al, (10) as reported earlier (6) . Clinical target volume (CTV) and planning target volume (PTV) are delineated according to clinical routine at our hospital.…”

Application of GEANT4radiation transport toolkit to dose calculations in anthropomorphic phantoms

“…The correspondence between each voxel CT number and its material is established by calibration functions, which are CT scanner dependent. For the used scanner, a Siemens Somatom Plus 4, CT number conversion to elemental weights of tissue and mass density were obtained following the work of Schneider et al [16]. These authors have divided the CT number range, comprehended between −1000 Hounsfield to 1500 Hounsfield, in different regions, each one having a distinct density and elemental weights of tissue parameterization.…”

“…A CT thorax image was acquired and two regions composed of different radiological substitute tissues were identified, Rando-lung and Randotissue [20], and the CT-number distributions obtained. Mean CT values were then used to calculate a mean density value for this tissue using parameterizations described in [16]. Results were compared with manufacturer data and are presented in Table 1.…”