Investigation of basic imaging properties in digital radiography. 13. Effect of simple structured noise on the detectability of simulated stenotic lesions

We investigated the effects of structured background noise on the detectability of stenotic lesions. Digital subtraction angiographic (DSA) images of stenotic blood vessels were simulated and superimposed onto uniform noise samples. Eighteen-alternative forced choice (18-AFC) experiments were employed to determine the detectability of the stenotic lesion in the structured-noise background of a blood vessel. In this study, the dependence of detectability on lesion size, vessel size, and incident x-ray exposure was examined. Our results indicate that the presence of structured noise in an image will reduce the detectability of a lesion. However, the relative performance of an observer when the lesion size and incident exposure were varied was the same with and without the presence of the structured background. Thus, conclusions obtained previously with regard to changes in the detectability of a lesion in the presence of uniform background noise can be applied directly to conditions in which simple structured anatomic background is present.     

Dose efficiency and low-contrast detectability of an amorphous silicon x-ray detector for digital radiography

The effect of dose reduction on low-contrast detectability is investigated theoretically and experimentally for a production grade amorphous silicon (a-Si) x-ray detector and compared with a standard thoracic screen-film combination. A non-prewhitening matched filter observer model modified to include a spatial response function and internal noise for the human visual system (HVS) is used to calculate a signal-to-noise ratio (SNR) related to object detectability. Other inputs to the SNR calculation are the detective quantum efficiency (DQE) and the modulation transfer function (MTF) of the imaging system. Besides threshold detectability, the model predicts the equivalent perception dose ratio (EPDR), which is the fraction of the screen film exposure for which the digital detector provides equal detectability. Images of a contrast-detail phantom are obtained with the digital detector at dose levels corresponding to 27%, 41%, 63% and 100% of the dose used for screen-film. The images are used in a four-alternative forced choice (4-AFC) observer perception study in order to measure threshold detectability. A statistically significant improvement in contrast detectability is measured with the digital detector at 100% and 63% of the screen-film dose. There is no statistical difference between screen-film and digital at 41% of the dose. On average, the experimental EPDR is 44%, which agrees well with the model prediction of 40%.     

Investigation of basic imaging properties in digital radiography. 3. Effect of pixel size on SNR and threshold contrast

The effect of pixel size on the signal-to-noise ratio (SNR) and threshold detection of low-contrast radiologic patterns was investigated theoretically for digital radiographic systems. The SNR based on the perceived statistical decision theory model, together with the internal noise of the human eye-brain system, was calculated by using two-dimensional displayed digital signal spectra and noise Wiener spectra. Threshold contrasts were predicted from the calculated SNR for various combinations of object size and shape, pixel size, resolution, and noise. Predicted threshold contrasts agreed well with those determined experimentally in an observer performance study. The threshold contrast of small objects increased substantially as the pixel size increased beyond 0.2 mm. For pixel sizes of 0.1 and 0.2 mm, however, the threshold contrasts were similar. Since a digital system is not shift invariant, a range of threshold contrast results for a small object and a large pixel, depending on the alignment of the object position relative to the sampling coordinates.     

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.     

Influence of x-ray pulse parameters on the image quality for moving objects in digital cardiac imaging

The image quality of a single frame in a modern cardiac imaging x-ray facility can be improved by adjusting the automatic pulse exposure parameters. The effects of acquisition rate on patient dose and the detectability of moving objects have been fully described in scientific literature. However, the influence of automatic pulse exposure parameters is still to be determined. Images of a moving wheel (with lead wires) were acquired using an H5000 Philips Integris cardiac x-ray system. Poly(methylmethacrylate) plastic samples 20 and 30 cm thick were employed as the build-up phantom to simulate a patient. The images were obtained using preset clinical parameters for cardiac imaging procedures. The signal detectability and motion blur of a contrast bar at a transversal speed in the range of 100-150 mm/s were evaluated with a cine pulse width of 3, 5, 7, and 10 ms under automatic mA kV regulation. Two levels of exposure at the image intensifier entrance were included in this study. Signal detectability was analyzed in terms of the signal-to-noise ratio (SNR) and the value of SNR2/entrance surface dose. The blurring was modeled as a Gaussian-shaped blurring function, and the motion blur was expressed in terms of the peak full width at half maximum and amplitude (apparent contrast) of the resolution functions. A contrast bar simulating a vessel in motion at the maximum velocities of typical cardiac structures was exposed. Severe loss of image quality occurred at pulse widths > or =7 ms. It is also shown that below 5 ms static nonlinearities, likely caused by the need to use a large focus for cine acquisition, dominate the blurring process.     

Investigation of basic imaging properties in digital radiography 10. Structure mottle of II-TV digital imaging systems

Single-frame images obtained with image intensifier (II)-TV digital systems contain a large amount of structure mottle. In the present study, we examined several II-TV digital systems by use of Wiener spectral analysis and noted considerable variation of the structure mottle over the wide spatial frequency range. We found that the structure mottle in these systems may originate in the input phosphor, the output phosphor, and/or the electronic components, and that the Wiener spectra of structure mottle seem to depend on the specific combination of these components. The results of observer performance studies indicated that structure mottle can significantly decrease the detection of low-contrast objects in a single-frame image when the exposure incident on the II is greater than approximately 0.1 mR. In addition, we showed that the structure mottle can be removed by subtraction of a uniformly exposed mask. This simple procedure will improve the quality of radiologic images obtained with II-TV digital systems. Note, however, that the structure mottle is largely eliminated by subtraction in digital subtraction angiography (DSA) images.     

Comparison of an amorphous silicon/cesium iodide flat-panel digital chest radiography system with screen/film and computed radiography systems--a contrast-detail phantom study.

Flat-panel (FP) based digital radiography systems have recently been introduced as a new and improved digital radiography technology; it is important to evaluate and compare this new technology with currently widely used conventional screen/film (SF) and computed radiography (CR) techniques. In this study, the low-contrast performance of an amorphous silicon/cesium iodide (aSi/Csl)-based flat-panel digital chest radiography system is compared to those of a screen/film and a computed radiography system by measuring their contrast-detail curves. Also studied were the effects of image enhancement in printing the digital images and dependence on kVp and incident exposure. It was found that the FP system demonstrated significantly better low-contrast performance than the SF or CR systems. It was estimated that a dose savings of 70%-90% could be achieved to match the low-contrast performance of the FP images to that of the SF images. This dose saving was also found to increase with the object size. No significant difference was observed in low-contrast performances between the SF and CR systems. The use of clinical enhancement protocols for printing digital images was found to be essential and result in better low-contrast performance. No significant effects were observed for different kVps. From the results of this contrast-detail phantom study, the aSi/CsI-based flat-panel digital chest system should perform better under clinical situations for detection of low-contrast objects such as lung nodules. However, proper processing prior to printing would be essential to realizing this better performance.     

Comparison of low contrast detectability between a digital amorphous silicon and a screen-film based imaging system for thoracic radiography.

Low contrast threshold detectability is investigated theoretically and experimentally for an amorphous silicon (a-Si) x-ray detector designed for digital radiography and for a standard thoracic screen-film combination. A theoretical signal-to-noise ratio is described with a human observer signal detection model. It is calculated using the detective quantum efficiency (DQE) and the modulation transfer function of the imaging system, as well as a spatial response function for the human visual system. Using a four-alternative forced choice observer perception study, the threshold contrasts of disk shaped objects ranging in size from 0.3 to 4.0 mm are determined. Significantly better contrast detectability is obtained from the digital detector, which is attributed to its higher DQE. On average, the disk shaped objects can be detected at 45% less contrast than required for screen-film. With no free parameters the experimental data agree well with those predicted by the observer model. Based upon the data, the model predicts that x-ray exposure for the a-Si detector only needs to be 30% of the exposure required to perform equally well on the contrast-detail detectability task using screen-film.     

Effect of radiographic techniques (kVp and mAs) on image quality and patient doses in digital subtraction angiography

We investigated how varying the x-ray tube voltage and image receptor input exposure affected image quality and patient radiation doses in interventional neuroradiologic imaging. Digital subtraction angiography (DSA) images were obtained of a phantom with 1 mm diameter vessels containing iodine at concentrations between 4.5 and 50 mg/cc. The detection threshold concentration of iodine was determined by inspecting DSA images obtained at a range of x-ray tube voltages and input exposure levels. Surface doses were obtained from measured x-ray tube output data, and corresponding values of energy imparted were determined using the exposure-area product incident on the phantom. In one series of experiments, the air kerma at the image intensifier (X) was varied between 0.44 microGy per frame and 8.8 microGy per frame at a constant x-ray tube voltage of 70 kVp. In a second series of experiments, the tube voltage was varied between 50 and 100 kVp, and the mAs adjusted to maintain a constant exposure level at the input of the image intensifier. At a constant x-ray tube voltage, the surface dose and energy imparted were directly proportional to the input exposure per frame used to acquire the DSA images. On our DSA system operated below 2.2 microGy per frame, the threshold iodine concentration was found to be proportional to X(-0.57), which is in reasonable agreement with the theoretical prediction for a quantum noise limited imaging system. Above 2.2 microGy per frame, however, the threshold iodine concentration was proportional to X(-0.26), indicating that increasing the input exposure above this value will only achieve modest improvements in image quality. At a constant image intensifier input exposure level, increasing the x-ray tube voltage from 50 kVp to 100 kVp reduced the surface dose by a factor of 6.1, and the energy imparted by a factor of 3.5. The detection threshold iodine concentration was found to be proportional to kVp(n), where n was 2.1 at 1.1 microGy per frame, and 1.6 at 3.9 microGy per frame. For clinical situations that can be modeled by a uniform phantom, reducing the x-ray tube voltage rather than increasing the exposure level would best achieve improvements on our DSA imaging system performance.     

A correlated noise reduction algorithm for dual-energy digital subtraction angiography

It has long been recognized that the problems of motion artifacts in conventional time subtraction digital subtraction angiography (DSA) may be overcome using energy subtraction techniques. Of the variety of energy subtraction techniques investigated, non-k-edge dual-energy subtraction offers the best signal-to-noise ratio (SNR). However, this technique achieves only 55% of the temporal DSA SNR. Noise reduction techniques that average the noisier high-energy image produce various degrees of noise improvement while minimally affecting iodine contrast and resolution. A more significant improvement in dual-energy DSA iodine SNR, however, results when the correlated noise that exists in material specific images is appropriately cancelled. The correlated noise reduction (CNR) algorithm presented here follows directly from the dual-energy computed tomography work of Kalender who made explicit use of noise correlations in material specific images to reduce noise. The results are identical to those achieved using a linear version of the two-stage filtering process described by Macovski in which the selective image is filtered to reduce high-frequency noise and added to a weighted, high SNR, nonselective image which has been processed with a high-frequency bandpass filter. The dual-energy DSA CNR algorithm presented here combines selective tissue and iodine images to produce a significant increase in the iodine SNR while fully preserving iodine spatial resolution. Theoretical calculations predict a factor of 2-4 improvement in SNR compared to conventional dual-energy images. The improvement factor achieved is dependent upon the x-ray beam spectra and the size of blurring kernel used in the algorithm.(ABSTRACT TRUNCATED AT 250 WORDS)     

Image quality assessment in digital mammography: part II. NPWE as a validated alternative for contrast detail analysis

Assessment of image quality for digital x-ray mammography systems used in European screening programs relies mainly on contrast-detail CDMAM phantom scoring and requires the acquisition and analysis of many images in order to reduce variability in threshold detectability. Part II of this study proposes an alternative method based on the detectability index (d') calculated for a non-prewhitened model observer with an eye filter (NPWE). The detectability index was calculated from the normalized noise power spectrum and image contrast, both measured from an image of a 5 cm poly(methyl methacrylate) phantom containing a 0.2 mm thick aluminium square, and the pre-sampling modulation transfer function. This was performed as a function of air kerma at the detector for 11 different digital mammography systems. These calculated d' values were compared against threshold gold thickness (T) results measured with the CDMAM test object and against derived theoretical relationships. A simple relationship was found between T and d', as a function of detector air kerma; a linear relationship was found between d' and contrast-to-noise ratio. The values of threshold thickness used to specify acceptable performance in the European Guidelines for 0.10 and 0.25 mm diameter discs were equivalent to threshold calculated detectability indices of 1.05 and 6.30, respectively. The NPWE method is a validated alternative to CDMAM scoring for use in the image quality specification, quality control and optimization of digital x-ray systems for screening mammography.     

Investigation of basic imaging properties in digital radiography. 4. Effect of unsharp masking on the detectability of simple patterns

The signal-to-noise ratios (SNRs) of simple radiologic patterns processed by the unsharp-masking technique were calculated on the basis of a statistical decision theory model that includes both the observer's visual transfer function and a noise component internal to his eye-brain system. For a variety of processing parameters, the contrast-detail diagrams predicted from this SNR agreed qualitatively with experimental results obtained in observer performance studies. Unsharp masking with a large mask and a large weighting factor improved the detection of square objects to a level comparable with that achieved by the overall contrast enhancement technique using a factor of 4. However, unsharp masking with a small mask and a large weighting factor can substantially degrade the detectability of these objects. The potential practical utility of the unsharp-masking technique is discussed.     

Detectability in computed tomographic images.

The detection limitations inherent in statistically limited computed tomographic (CT) images are described through the application of signal detection theory. The detectability of large-area, low-contrast objects is shown to be chiefly dependent upon the low-frequency content of the noise power spectral density. For projection data containg uncorrelated noise, the resulting ramplike, low-frequency behavior of the noise power spectrum of CT reconstructions may be conveniently characterized by the number of noise-equivalent x-ray quanta (NEQ) detected in the projection measurements. The NEQ for a given image may be determined either from a measurement of the noise power spectrum or from the noise granularity computed with an appropriate weighting function. A measure of the efficiency of scanner dose utilization is proposed which compares the average dose to that required by an ideal scanner to obtain the same NEQ.     

Scanned-projection digital mammography

The effectiveness of film-screen mammography is limited by tradeoffs between latitude and contrast, film granularity, and the need to increase dose when antiscatter methods are used. We are currently developing a scanned-projection digital mammography (SPDM) system to overcome these limitations. The system consists of a pair of scanning slits, a high-resolution x-ray image intensifier tube, a linear photodiode array, and a digital display. The detective quantum efficiency of the SPDM system at spatial frequencies up to 3 cycles/mm is similar to that of mammographic film-screen combinations, but is lower at high frequencies. For low-contrast objects as small as 0.1 mm in diameter, the signal-to-noise ratio is currently equal to that of optimally exposed mammographic film-screen images for equal dose to the breast and superior for regions which would be underexposed or overexposed on film. This is achieved by the use of a low-noise detector system, geometric magnification, and scatter elimination. Images of a contrast-detail phantom and excised breast tissue illustrate the superior contrast sensitivity of SPDM.     

Automated assessment of low contrast sensitivity for CT systems using a model observer

Purpose: Low contrast sensitivity of CT scanners is regularly assessed by subjective scoring of low contrast detectability within phantom CT images. Since in these phantoms low contrast objects are arranged in known fixed patterns, subjective rating of low contrast visibility might be biased. The purpose of this study was to develop and validate a software for automated objective low contrast detectability based on a model observer.Methods: Images of the low contrast module of the Catphan 600 phantom were used for the evaluation of the software. This module contains two subregions: the supraslice region with three groups of low contrast objects (each consisting of nine circular objects with diameter 2-15 mm and contrast 0.3, 0.5, and 1.0%, respectively) and the subslice region with three groups of four circular objects each (diameter 3-9 mm; contrast 1.0%). The software method offered automated determination of low contrast detectability using a NPWE (nonprewhitening matched filter with an eye filter) model observer for the supraslice region. The model observer correlated templates of the low contrast objects with the acquired images of the Catphan phantom and a discrimination index d' was calculated. This index was transformed into a proportion correct (PC) value. In the two-alternative forced choice (2-AFC) experiments used in this study, a PC ≥ 75% was proposed as a threshold to decide whether objects were visible. As a proof of concept, influence of kVp (between 80 and 135 kV), mAs (25-200 mAs range) and reconstruction filter (four filters, two soft and two sharp) on low contrast detectability was investigated. To validate the outcome of the software in a qualitative way, a human observer study was performed.Results: The expected influence of kV, mAs and reconstruction filter on image quality are consistent with the results of the proposed automated model. Higher values for d' (or PC) are found with increasing mAs or kV values and for the soft reconstruction filters. For the highest contrast group (1%), PC values were fairly above 75% for all object diameters >2 mm, for all conditions. For the 0.5% contrast group, the same behavior was observed for object diameters >3 mm for all conditions. For the 0.3% contrast group, PC values were higher than 75% for object diameters >6 mm except for the series acquired at the lowest dose (25 mAs), which gave lower PC values. In the human observer study similar trends were found.Conclusions: We have developed an automated method to objectively investigate image quality using the NPWE model in combination with images of the Catphan phantom low contrast module. As a first step, low contrast detectability as a function of both acquisition and reconstruction parameter settings was successfully investigated with the software. In future work, this method could play a role in image reconstruction algorithms evaluation, dose reduction strategies or novel CT technologies, and other model observers may be implemented as well.     

Development of a randomised contrast detail digital phantom for observer detectability study

The accuracy and the efficacy of radiological diagnosis depend, to a large extent, on the conditions under which radiographs and images are viewed. This mainly involves the luminance of the display devices and the ambient room illumination. We report a perceptual study to investigate the relationship between detectability and monitor luminance as well as ambient illuminance. A statistical test pattern was used in this study, and the test pattern was developed using Microsoft® Visual Basic 6. The test pattern contained a set of randomised contrast detail objects, that is, disks of different diameters (0.7, 1.0, 1.4, and 2.0 mm) and contrasts against a black background (2.7, 3.9, 5.5, and 7.8%), simulating lesions in digital images. The receiver operating characteristic (ROC) analysis was used in this study. The results indicated that a set of optimal viewing conditions exists and that it has a significant effect on detectability performance.     

Detection performance analysis for time-of-flight PET

In this paper, we investigate the performance of time-of-flight (TOF) positron emission tomography (PET) in improving lesion detectability. We present a theoretical approach to compare lesion detectability of TOF versus non-TOF systems and perform computer simulations to validate the theoretical prediction. A single-ring TOF PET tomograph is simulated using SimSET software, and images are reconstructed in 2D from list-mode data using a maximum a posteriori method. We use a channelized Hotelling observer to assess the detection performance. Both the receiver operating characteristic (ROC) and localization ROC curves are compared for the TOF and non-TOF PET systems. We first studied the SNR gains for TOF PET with different scatter and random fractions, system timing resolutions and object sizes. We found that the TOF information improves the lesion detectability and the improvement is greater with larger fractions of randoms, better timing resolution and bigger objects. The scatters by themselves have little impact on the SNR gain after correction. Since the true system timing resolution may not be known precisely in practice, we investigated the effect of mismatched timing kernels and showed that using a mismatched kernel during reconstruction always degrades the detection performance, no matter whether it is narrower or wider than the real value. Using the proposed theoretical framework, we also studied the effect of lumpy backgrounds on the detection performance. Our results indicated that with lumpy backgrounds, the TOF PET still outperforms the non-TOF PET, but the improvement is smaller compared with the uniform background case. More specifically, with the same correlation length, the SNR gain reduces with bigger number of lumpy patches and greater lumpy amplitudes. With the same variance, the SNR gain reaches the minimum when the width of the Gaussian lumps is close to the size of the tumor.     

Signal detectability in digital radiography: spatial domain figures of merit

The usefulness of Fourier-based measures of imaging performance has come into question for the evaluation of digital imaging systems. Figures of merit such as detective quantum efficiency (DQE) based on Fourier domain parameters are relevant for linear, shift-invariant systems with stationary noise. However, no digital imaging system is shift invariant, and realistic images do not satisfy the stationarity condition. Our methods for the task-based evaluation of imaging systems, based on signal detectability in the spatial domain, do not require such assumptions. We have computed the performance of ideal and quasi-ideal observers for the task of signal detection in digital radiography. Signal detectability in terms of an observer signal-to-noise-ratio (SNR) has been compared to results obtained from a Monte Carlo simulation of the digital image-acquisition process. The simulation incorporates the effects of random amplification and secondary quantum blur, integration over pixel area, and electronic noise. The observer figures of merit that have been previously shown to bracket human performance directly specify the usefulness of the images for the stated diagnostic task. In addition, the observer figures of merit give a task-dependent measure of imaging system efficiency in terms of the ratio of an output SNR2 to an input SNR2. Thus, the concept of "detective quantum efficiency" reappears in a natural way but based in the spatial domain and not dependent on shift invariance and stationarity assumptions. With respect to the optimum amount of system blur, our simulations indicate that under certain task-dependent conditions, large signals are fairly insensitive to blur in the x-ray transducer, while an optimum blur is found for small signals.     

Analysis of spectral blur effects in x-ray scatter imaging.

Previous analysis in our research program investigating the potential use of scattered photons for medical x-ray imaging has been for monoenergetic beams. In practice, polyenergetic beams are almost always used due to their higher photon fluence rate. The effects of beam polychromaticity on x-ray scatter imaging are determined with the aid of our semianalytic model that images a target object against a background material of the same dimensions when both are situated within a water phantom. Our analysis involves four different photon beams with constant incident energy fluence: (1) a monoenergetic beam with photon energy E0, (2) a dual peak beam with two separate monoenergetic peaks of energies E1 and E2, (3) a clinical x-ray beam, and (4) a rectangular beam with uniform energy fluence between energies Emin and Emax. A comparison between the polyenergetic spectra is accomplished by matching the centroids and standard deviations of the dual peak and rectangular spectra to those of the clinical x-ray spectrum. For the task of imaging liver versus fat structures 1 cm thick in a 25-cm-diam spherical water phantom with the scattered photons between 2 degrees and 12 degrees, the predicted signal-to-noise ratio (SNR) obtained with a 100 kV beam is 87.5% of the SNR acquired with the optimum monoenergetic beam (SNRopt). The SNR for the corresponding dual peak beam is 84.4% of SNRopt and for the rectangular beam is 86.3%. Our analysis shows that monoenergetic x-ray beams are not necessary for x-ray scatter imaging.     

A search for improved technique factors in paediatric fluoroscopy

A Monte Carlo computational model of a fluoroscopic imaging chain was used for deriving optimal technique factors for paediatric fluoroscopy. The optimal technique was defined as the one that minimizes the absorbed dose (or dose rate) in the patient with a constraint of constant image quality. Image quality was assessed for the task of detecting a detail in the image of a patient-simulating phantom, and was expressed in terms of the ideal observer's signal-to-noise ratio (SNR) for static images and in terms of the accumulating rate of the square of SNR for dynamic imaging. The entrance air kerma (or air kerma rate) and the mean absorbed dose (or dose rate) in the phantom quantified radiation detriment. The calculations were made for homogeneous phantoms simulating newborn, 3-, 10- and 15-year-old patients, barium and iodine contrast material details, several x-ray spectra, and for imaging with or without an antiscatter grid. The image receptor was modelled as a CsI x-ray image intensifier (XRII). For the task of detecting low- or moderate-contrast iodine details, the optimal spectrum can be obtained by using an x-ray tube potential near 50 kV and filtering the x-ray beam heavily. The optimal tube potential is near 60 kV for low- or moderate-contrast barium details, and 80-100 kV for high-contrast details. The low-potential spectra above require a high tube load, but this should be acceptable in paediatric fluoroscopy. A reasonable choice of filtration is the use of an additional 0.25 mm Cu, or a suitable K-edge filter. No increase in the optimal tube potential was found as phantom thickness increased. With the constraint of constant low-contrast detail detectability, the mean absorbed doses obtained with the above spectra are approximately 50% lower than those obtained with the reference conditions of 70 kV and 2.7 mm Al filter. For the smallest patient and x-ray field size, not using a grid was slightly more dose-efficient than using a grid, but when the patient size and field size were increased a fibre interspaced grid resulted in lower doses than imaging without a grid. For a 15-year-old patient the mean absorbed doses were up to 40% lower with this grid than without the grid.