Optimization of image acquisition techniques for dual-energy imaging of the chest

Experimental and theoretical studies were conducted to determine optimal acquisition techniques for a prototype dual-energy (DE) chest imaging system. Technique factors investigated included the selection of added x-ray filtration, kVp pair, and the allocation of dose between low- and high-energy projections, with total dose equal to or less than that of a conventional chest radiograph. Optima were computed to maximize lung nodule detectability as characterized by the signal-difference-to-noise ratio (SDNR) in DE chest images. Optimal beam filtration was determined by cascaded systems analysis of DE image SDNR for filter selections across the periodic table (Z(filter) = 1-92), demonstrating the importance of differential filtration between low- and high-kVp projections and suggesting optimal high-kVp filters in the range Z(filter) = 25-50. For example, added filtration of approximately 2.1 mm Cu, approximately 1.2 mm Zr, approximately 0.7 mm Mo, and approximately 0.6 mm Ag to the high-kVp beam provided optimal (and nearly equivalent) soft-tissue SDNR. Optimal kVp pair and dose allocation were investigated using a chest phantom presenting simulated lung nodules and ribs for thin, average, and thick body habitus. Low- and high-energy techniques ranged from 60-90 kVp and 120-150 kVp, respectively, with peak soft-tissue SDNR achieved at [60/120] kVp for all patient thicknesses and all levels of imaging dose. A strong dependence on the kVp of the low-energy projection was observed. Optimal allocation of dose between low- and high-energy projections was such that approximately 30% of the total dose was delivered by the low-kVp projection, exhibiting a fairly weak dependence on kVp pair and dose. The results have guided the implementation of a prototype DE imaging system for imaging trials in early-stage lung nodule detection and diagnosis.     

Quantitative evaluation of dual-energy digital mammography for calcification imaging

Dual-energy digital mammography (DEDM), where separate low- and high-energy images are acquired and synthesized to cancel the tissue structures, may improve the ability to detect and visualize microcalcifications. Under ideal imaging conditions, when the mammography image data are free of scatter and other biases, DEDM could be used to determine the thicknesses of the imaged calcifications. We present quantitative evaluation of a DEDM technique for calcification imaging. The phantoms used in the evaluation were constructed by placing aluminium strips of known thicknesses (to simulate calcifications) across breast-tissue-equivalent materials of different glandular-tissue compositions. The images were acquired under narrow-beam geometry and high exposures to suppress the detrimental effects of scatter and random noise. The measured aluminium thicknesses were found to be approximately linear with the true aluminium thicknesses and independent of the underlying glandular-tissue composition. However, the dual-energy images underestimated the true aluminium thickness due to the presence of scatter from adjacent regions. Regions in the DEDM image that contained no aluminium yielded very low aluminium thicknesses (<0.07 mm). The aluminium contrast-to-noise ratio in the dual-energy images increased with the aluminium thickness and decreased with the glandular-tissue composition. The changes to the aluminium contrast-to-noise ratio and the contrast of the tissue structures between the low-energy and DEDM images are also presented.     

Quantitative evaluation of noise reduction strategies in dual-energy imaging

In this paper we describe a quantitative evaluation of the performance of three dual-energy noise reduction algorithms: Kalender's correlated noise reduction (KCNR), noise clipping (NOC), and edge-predictive adaptive smoothing (EPAS). These algorithms were compared to a simple smoothing filter approach, using the variance and noise power spectrum measurements of the residual noise in dual-energy images acquired with an a-Si TFT flat-panel x-ray detector. An estimate of the true noise was made through a new method with subpixel accuracy by subtracting an individual image from an ensemble average image. The results indicate that in the lung regions of the tissue image, all three algorithms reduced the noise by similar percentages at high spatial frequencies (KCNR=88%, NOC=88%, EPAS=84%, NOC/KCNR=88%) and somewhat less at low spatial frequencies (KCNR=45%, NOC=54%, EPAS=52%, NOC/KCNR=55%). At low frequencies, the presence of edge artifacts from KCNR made the performance worse, thus NOC or NOC combined with KCNR performed best. At high frequencies, KCNR performed best in the bone image, yet NOC performed best in the tissue image. Noise reduction strategies in dual-energy imaging can be effective and should focus on blending various algorithms depending on anatomical locations.     

Theoretical optimization of a split septaless xenon ionization detector for dual-energy chest radiography

It is proposed that digital scanned projection radiography of the chest be performed by using an energy-sensitive septaless xenon ionization detector (SXID) to obtain dual-energy images. The proposed detector is composed of a front region, sensitive to low-energy x rays, and a rear region, sensitive to high-energy x rays, separated by a suitable filter layer. We have developed a simple, precise theoretical formulation for dual-energy optimization, and applied it to the split SXID. We describe the variation of optimum detector performance with source kilovoltage and filtration (material and thickness), and hence heat loading, under conditions of constant exposure and constant dose. We estimate dose as the average absorbed dose to an equivalent water layer of suitable thickness, assuming slab geometry, so that the calculation is as simple as that for exposure.     

Dynamic dual-energy chest radiography: a potential tool for lung tissue motion monitoring and kinetic study

Dual-energy chest radiography has the potential to provide better diagnosis of lung disease by removing the bone signal from the image. Dynamic dual-energy radiography is now possible with the introduction of digital flat-panel detectors. The purpose of this study is to evaluate the feasibility of using dynamic dual-energy chest radiography for functional lung imaging and tumor motion assessment. The dual-energy system used in this study can acquire up to 15 frames of dual-energy images per second. A swine animal model was mechanically ventilated and imaged using the dual-energy system. Sequences of soft-tissue images were obtained using dual-energy subtraction. Time subtracted soft-tissue images were shown to be able to provide information on regional ventilation. Motion tracking of a lung anatomic feature (a branch of pulmonary artery) was performed based on an image cross-correlation algorithm. The tracking precision was found to be better than 1 mm. An adaptive correlation model was established between the above tracked motion and an external surrogate signal (temperature within the tracheal tube). This model is used to predict lung feature motion using the continuous surrogate signal and low frame rate dual-energy images (0.1-3.0 frames per second). The average RMS error of the prediction was (1.1 ± 0.3) mm. The dynamic dual energy was shown to be potentially useful for lung functional imaging such as regional ventilation and kinetic studies. It can also be used for lung tumor motion assessment and prediction during radiation therapy.     

Optimization of a flat-panel based real time dual-energy system for cardiac imaging

A simulation study was conducted to evaluate the effects of high-energy beam filtration, dual-gain operation and noise reduction on dual-energy images using a digital flat-panel detector. High-energy beam filtration increases image contrast through greater beam separation and tends to reduce total radiation exposure and dose per image pair. It is also possible to reduce dual-energy image noise by acquiring low and high-energy images at two different detector gains. In addition, dual-energy noise reduction algorithms can further reduce image noise. The cumulative effect of these techniques applied in series was investigated in this study. The contrast from a small thickness of calcium was simulated over a step phantom of tissue equivalent material with a CsI phosphor as the image detector. The dual-energy contrast-to-noise ratio was calculated using values of energy absorption and energy variance. A figure-of-merit (FOM) was calculated from dual-energy contrast-to-noise ratio (CNR) and patient effective dose estimated from values of entrance exposure. Filter atomic numbers in the range of 1-100 were considered with thicknesses ranging from 0-2500 mg/cm2. The simulation examined combinations of the above techniques which maximized the FOM. The application of a filter increased image contrast by as much as 45%. Near maximal increases were seen for filter atomic numbers in the range of 40-60 and 85-100 with masses above 750 mg/cm2. Increasing filter thickness beyond 1000 mg/cm2 increased tube loading without further significant contrast enhancement. No additional FOM improvements were seen with dual gain before or after the application of any noise reduction algorithm. Narrow beam experiments were carried out to verify predictions. The measured FOM increased by more than a factor of 3.5 for a silver filter thickness of 800 microm, equal energy weighting and application of a noise clipping algorithm. The main limitation of dynamic high-energy filtration is increased tube loading. The results of this study can be used to help develop an optimal dual-energy imaging system.     

Performance of high-resolution monitors for digital chest imaging

High-resolution cathode-ray tubes (CRT's) are currently the most viable soft-copy display for digital radiography. We present here methods for measuring large-area contrast ratio and detail contrast ratio. A two-dimensional charge coupled device (ccd) array signal-averaged with a video frame buffer permits linear microradiometric measure of individual beam lines. Results from three different 1000-line monitors demonstrate the shift variance of resolution. The detail contrast ratio (or modulation depth) was found to vary from 100% to less than 10% across the face of one CRT. Dynamic focus in both the horizontal and vertical deflection circuitry proved effective in reducing this shift variance. Comparisons of three phosphors demonstrate the utility of long persistence phosphors (P164) for static display in producing brighter images with less flicker. Recommendations for CRT design and selection for high-resolution digital radiography are included.     

Dual-energy imaging of the chest: optimization of image acquisition techniques for the 'bone-only' image

Experiments were conducted to determine optimal acquisition techniques for bone image decompositions for a prototype dual-energy (DE) imaging system. Technique parameters included kVp pair (denoted [kVp(L)/kVp(H)]) and dose allocation (the proportion of dose in low- and high-energy projections), each optimized to provide maximum signal difference-to-noise ratio in DE images. Experiments involved a chest phantom representing an average patient size and containing simulated ribs and lung nodules. Low- and high-energy kVp were varied from 60-90 and 120-150 kVp, respectively. The optimal kVp pair was determined to be [60/130] kVp, with image quality showing a strong dependence on low-kVp selection. Optimal dose allocation was approximately 0.5-i.e., an equal dose imparted by the low- and high-energy projections. The results complement earlier studies of optimal DE soft-tissue image acquisition, with differences attributed to the specific imaging task. Together, the results help to guide the development and implementation of high-performance DE imaging systems, with applications including lung nodule detection and diagnosis, pneumothorax identification, and musculoskeletal imaging (e.g., discrimination of rib fractures from metastasis).     

Comparison of three different techniques for dual-energy subtraction imaging in digital radiography: A signal-to-noise analysis

Dual-energy subtraction imaging techniques allow the tissue and bone structures in the patient to be visualized and studied in two separate images, thus removing the obscurity associated with overlapping of the two structures. In addition, they allow the subtraction image signals to be used for quantifying the tissue and bone thicknesses. Thus, capability for dual-energy subtraction imaging is often incorporated with new digital radiography systems. There are three different approaches to dual-energy image subtraction imaging techniques. Among them, the dual-kilovolt (peak) [kV(p)] and sandwich detector techniques have been two widely used approaches. A third approach is the single-kV(p) dual-filter technique, which allows some flexible control of the spectra while avoiding the technical complexity of kV(p) value switching in slit-scan imaging. In this report, the noise properties associated with these three techniques are studied and compared by computing the noise variances in the subtraction image signals as a function of the kV(p) values and filter thicknesses. It was found that the dual-kVp technique results in the least noisy subtraction images, whereas the dual-filter technique results in slightly less noisy subtraction images than the sandwich detector technique. Following optimization of the kV(p) value and filter thicknesses, the dual-filter and sandwich detector techniques result in a noise level of approximately three and four times higher than that resulted from the dual-kV(p) technique, respectively.     

On two-parameter models of photon cross sections: application to dual-energy CT imaging

The goal of this study is to evaluate the theoretically achievable accuracy in estimating photon cross sections at low energies (20-1000 keV) from idealized dual-energy x-ray computed tomography (CT) images. Cross-section estimation from dual-energy measurements requires a model that can accurately represent photon cross sections of any biological material as a function of energy by specifying only two characteristic parameters of the underlying material, e.g., effective atomic number and density. This paper evaluates the accuracy of two commonly used two-parameter cross-section models for postprocessing idealized measurements derived from dual-energy CT images. The parametric fit model (PFM) accounts for electron-binding effects and photoelectric absorption by power functions in atomic number and energy and scattering by the Klein-Nishina cross section. The basis-vector model (BVM) assumes that attenuation coefficients of any biological substance can be approximated by a linear combination of mass attenuation coefficients of two dissimilar basis substances. Both PFM and BVM were fit to a modern cross-section library for a range of elements and mixtures representative of naturally occurring biological materials (Z = 2-20). The PFM model, in conjunction with the effective atomic number approximation, yields estimated the total linear cross-section estimates with mean absolute and maximum error ranges of 0.6%-2.2% and 1%-6%, respectively. The corresponding error ranges for BVM estimates were 0.02%-0.15% and 0.1%-0.5%. However, for photoelectric absorption frequency, the PFM absolute mean and maximum errors were 10.8%-22.4% and 29%-50%, compared with corresponding BVM errors of 0.4%-11.3% and 0.5%-17.0%, respectively. Both models were found to exhibit similar sensitivities to image-intensity measurement uncertainties. Of the two models, BVM is the most promising approach for realizing dual-energy CT cross-section measurement.     

Optimal feature selection for the assessment of vocal fold disorders

Unilateral vocal fold paralysis, vocal fold polyp, and vocal fold nodules are the most common types of neurogenic and organic vocal disorders. This article aims to distinguish these types of vocal diseases into four different classes for the purpose of automatic screening. Firstly, the reconstructed signal at each wavelet packet decomposition sub-band in five levels of decomposition with mother wavelet of (db10) is used to extract the nonlinear features of self-similarity and approximate entropy. Also, wavelet packet coefficients are used to measure energy and Shannon entropy features at different spectral sub-bands. Consequently, to find a discriminant feature vector, three different methods have been applied: Davies-Bouldin (DB) criteria, genetic algorithm (GA) with the fitness functions of support vector machine's (SVM) and k-nearest neighbor's (KNN) recognition rates. Finally, obtained feature vectors have been passed on to SVM and KNN classifiers. The results show that a feature vector of length 12 obtained by the optimization method of GA with the fitness function of SVM's recognition rate fed to SVM classifier achieves the highest classification accuracy of 91%. Furthermore, nonlinear features play an important role in pathological voice classification by participating rate of approximately 67% in the optimal feature vector.     

Psychological treatment for atypical non-cardiac chest pain: a controlled evaluation

Thirty-one patients with atypical non-cardiac chest pain which had persisted despite negative medical investigation were treated in a controlled trial of cognitive-behavioural therapy. The average duration of pain was 4.7 years. Patients were randomized to either immediate treatment or as a control to assessment only. Treatment involved teaching patients how to anticipate and control symptoms, and modification of inappropriate health beliefs. The average number of sessions given was 7.2. There were significant reductions in chest pain. limitations and disruption of daily life, autonomic symptoms, distress and psychological morbidity in the treated group as compared with the control group who were unchanged. The assessment-only group were treated subsequently and showed comparable changes. Improvements were fully maintained by both treated groups at four- to six-months follow-up.     

Efficient selection of tests for bacteriological typing schemes.

To simplify the selection of tests for bacteriological typing methods, such as bacteriophage, bacteriocin, and biotyping, a computerised method was assessed. This uses a numerical index of discrimination (D) to facilitate the selection of an efficient typing set. The computer programs take the most discriminatory test as the initial test in the partial typing set, and then select the next test by combining each of the remaining candidates with the partial set and choosing the test which maximises D. This cycle is repeated until the remaining candidates do not increase the discriminatory power of the typing set. Options are provided for the investigator to pre-select certain tests for inclusion or exclusion from the typing set. It is concluded that the numerical index D is a simple means of test selection, but it must be emphasised that it is important to combine its use with data on the incidence of reaction in each test, on reproducibility, and on the similarity among tests.     

Zygote evaluation: an efficient tool for embryo selection

One of the main problems concerning IVF units is the need to decrease the occurrence of multiple pregnancies in their practice without affecting the overall success rate. Different embryological parameters concerning every step of the early embryo development are known to have some predictive value for implantation potential. In this prospective study, a pronuclear scoring system was used to classify zygotes into six patterns from 0 to 5. Cleaved, day 3 embryos developed from pattern 0 zygotes, which was described as the normal pattern, were transferred when available. For each zygote pattern, the subsequent embryological development was analysed. Pattern 0 zygotes led to significantly more 'good quality' embryos with higher implantation potential than embryos developing from the other zygote patterns (P < 0.01). Embryo transfers including at least one pattern 0 resulted in significantly more pregnancies than transfers without any pattern 0 zygotes (39.3 versus 19.7%, P < 0. 01). No relationship between clinical parameters (age of female partner, infertility cause) and zygote pattern distribution was demonstrated.     

Positron autoradiography for intravascular imaging: feasibility evaluation

Approximately 70% of acute coronary artery disease is caused by unstable (vulnerable) plaques with an inflammation of the overlying cap and high lipid content. A rupturing of the inflamed cap of the plaque results in propagation of the thrombus into the lumen, blockage of the artery and acute ischaemic syndrome or sudden death. Morphological imaging such as angiography or intravascular ultrasound cannot determine inflammation status of the plaque. A radiotracer such as 18F-FDG is accumulated in vulnerable plaques due to higher metabolic activity of the inflamed cap and could be used to detect a vulnerable plaque. However, positron emission tomography (PET) cannot detect the FDG-labelled plaques because of respiratory and heart motions, small size and low activity of the plaques. Plaques can be detected using a miniature particle (positron) detector inserted into the artery. In this work, a new detector concept is investigated for intravascular imaging of the plaques. The detector consists of a storage phosphor tip bound to the end of an intravascular catheter. It can be inserted into an artery, absorb the 18F-FDG positrons from the plaques, withdrawn from the artery and read out. Length and diameter of the storage phosphor tip can be matched to the length and the diameter of the artery. Monte Carlo simulations and experimental evaluations of coronary plaque imaging with the proposed detector were performed. It was shown that the sensitivity of the storage phosphor detector to the positrons of 18F-FDG is sufficient to detect coronary plaques with 1 mm and 2 mm sizes and 590 Bq and 1180 Bq activities in the arteries with 2 mm and 3 mm diameters, respectively. An experimental study was performed using plastic tubes with 2 mm diameter filled with an FDG solution, which simulates blood. FDG spots simulating plaques were placed over the surface of the tube. A phosphor tip was inserted into the tube and imaged the plaques. Exposure time was 1 min in all simulations and experiments. Experiments showed that detecting the coronary plaques using the proposed technique is possible. The proposed technique has the potential for fast and accurate detection of vulnerable coronary and other intravascular plaques.     

Effects of scattered radiation and veiling glare in dual-energy tissue-bone imaging: a theoretical analysis

Dual-energy subtraction imaging allows tissue and bone structures to be separated from each other and attenuating thicknesses measured. Potential applications include chest imaging, bone mineral measurement, angiography, and mammography. However, intrinsic to most x-ray detectors is the acceptance of scattered radiation as part of the image signal. Added to that is the veiling glare component when an image intensifier is used. Together, they result in erroneous transmission measurement and degrade the accuracy of energy subtraction processing. In this paper, the effects of scattered radiation and veiling glare on energy subtraction images are examined theoretically. A model is derived and used to compute the effects on the thickness signals, image contrast, and image noise as a function of the scatter glare to primary ratios. The ratios were measured on a point-by-point basis for a Rando chest phantom. For 96% of the image field studied, the thickness signals may be subject to an error ranging from 0 to -22.5 cm for tissue and 0 to 5.2 cm for bone. The image contrast in the tissue image may be reduced by a factor ranging from 1 to 59. The percentage of the uncanceled bone signals ranges from -52% to 52%. The contrast-to-noise ratio may be reduced by a factor ranging from 1 to 18.     

Clinical evaluation of irreversible data compression for computed radiography of the chest

Efficient data compression is essential for practical daily operation of computed radiography (CR) systems. In this study the clinical applicability of type III irreversible high data compression using an FCR 9501 chest unit (Fuji Photo Film, Tokyo, Japan) was evaluated. Sixty-eight normal and 93 various abnormal cases, with an additional 15 cases of lung cancers with solitary lung nodules, were selected from the file. A pair of hard copies of original images and images reconstructed using type III compression was made for each case. Six radiologists evaluated the image quality by visual rating and receiver operating characteristic (ROC) curve analysis. For all five anatomic regions of normal cases, “original equal to compressed” was the most common response, followed by “original significantly better than compressed.” When abnormal cases were evaluated for diagnostic information, there was no significant difference between the compressed and original images. ROC curve analysis on lung nodules with lung cancer showed no significant difference between the two. Compressed CR images using the type III irreversible technique are clinically applicable and acceptable despite slight degradation of image quality.     

An evaluation of the Technicon AutoAnalyzer for automating complement-fixation tests

Obviously there is need for a reliable means of automating complement-fixation tests. This paper offers an account of experience with an AutoAnalyzer adapted for this purpose. Results of syphilis screening tests done by the AutoAnalyzer compared with those of tests performed manually showed satisfactory agreement, the automated method being slightly less specific in our hands. There were no false negative results with the AutoAnalyzer if both Maltaner and Reiter protein antigens were used.