Calculation of organ doses in x-ray examinations of premature babies.

Lung disease represents one of the most life-threatening conditions in prematurely born children. In the evaluation of the neonatal chest, the primary and most important diagnostic study is the chest radiograph. Since prematurely born children are very sensitive to radiation, those radiographs may lead to a significant radiation detriment. Knowledge of the radiation dose is therefore necessary to justify the exposures. To calculate doses in the entire body and in specific organs, computational models of the human anatomy are needed. Using medical imaging techniques, voxel phantoms have been developed to achieve a representation as close as possible to the anatomical properties. In this study two voxel phantoms, representing prematurely born babies, were created from computed tomography- and magnetic resonance images: Phantom 1 (1910 g) and Phantom 2 (590 g). The two voxel phantoms were used in Monte Carlo calculations (MCNPX) to assess organ doses. The results were compared with the commercially available software package PCXMC in which the available mathematical phantoms can be downsized toward the prematurely born baby. The simple phantom-scaling method used in PCXMC seems to be sufficient to calculate doses for organs within the radiation field. However, one should be careful in specifying the irradiation geometry. Doses in organs that are wholly or partially outside the primary radiation field depend critically on the irradiation conditions and the phantom model.

Determination of conversion factors from air kerma to operational dose equivalent quantities for low-energy X-ray spectra.

The conversion coefficients from air kerma to ICRU operational dose equivalent quantities for STUK's realisation of the X-radiation qualities N-15 to N-60 of the ISO narrow (N) spectrum series were determined by utilising X-ray spectrum measurements. The pulse-height spectra were measured using a planar high-purity germanium spectrometer and unfolded to fluence spectra using Monte Carlo generated data of the spectrometer response. To verify the measuring and unfolding method, the first and second half-value layers and the air kerma rate were calculated from the fluence spectra and compared with the values measured using an ionisation chamber. For each radiation quality, the spectrum was characterised by the parameters given in ISO 4037-1. The conversion coefficients from the air kerma to the ICRU operational quantities Hp(10), Hp(0.07), H'(0.07) and H*(10) were calculated using monoenergetic conversion coefficients at zero angle of incidence. The results are discussed with respect to ISO 4037-4, and compared with published results for low-energy X-ray spectra.

How should low-contrast detail detectability be measured in fluoroscopy?

The relationship and precision of four methods for measuring the low-contrast detail detectability in fluoroscopic imaging were studied. These included the physical measurement of the accumulation rate of the square of the signal-to-noise ratio (SNR(rate)2), two-alternative forced-choice (2-AFC) experiments, sixteen-alternative forced-choice (16-AFC) experiments and subjective determination of the threshold contrast. The precision and sensitivity of the threshold contrast measurement were seen to be modest in the constancy testing of fluoroscopic equipment: only large changes in system performance could be reliably detected by that method. The measurement of the SNR(rate)2 is suggested instead. The relationship between the results of the various methods were studied, and it was found that human performance can be related to SNR(rate)2 by introducing the concept of the effective image information integration time (t(eff)). When measured for an unlimited observation time, it depicts the saturation of human performance in detecting a static low-contrast detail in dynamic image noise. Here, t(eff) was found to be about 0.6 s in 2-AFC tests and 0.3 s in 16-AFC tests.