Investigation of basic imaging properties in digital radiography. 8. Detection of simulated low-contrast objects in digital subtraction angiographic images

We investigated the effects of imaging and display conditions on the detectability of low-contrast objects in digital subtraction angiographic (DSA) images. The test images were produced by superimposition of low-contrast objects on a uniform noisy background obtained with a DSA system. We employed 18-alternative forced-choice (18-AFC) experiments and predictions based on statistical decision theory to study the dependence of the threshold contrasts of the test objects on the object size, incident x-ray exposure, display window width, and display medium. The results indicated that the threshold contrast decreased with increasing object size, and that the detectability of an object of a given size increased with increasing incident x-ray exposure and decreasing width of the display window. We found that the signal-to-noise ratio (SNR) obtained from the perceived statistical decision theory model, which includes the observer's internal noise, can accurately predict the detectability of low-contrast objects in DSA images. The threshold SNR corresponding to 50% correct detection in the 18-AFC experiments had a constant value of 3.8, in agreement with results reported previously for screen-film systems. The theoretical model will be useful for prediction of the performance of a DSA system based on its physical characteristics, and for evaluation of the tradeoff between patient exposure and diagnostic accuracy for a given DSA unit.     

A lesion detectability simulation method for digital x-ray imaging

A simulation method is described in this work that aids in quantifying the upper limits of lesion detectability as a function of lesion size, lesion contrast, pixel size, and x-ray exposure for digital x-ray imaging systems. The method entails random lesion placement with subsequent simulated imaging on idealized x-ray detectors with no additive noise and 100% quantum detective efficiency. Lesions of different size and thickness were simulated. Mean (expectation) lesion signal-to-noise ratios (LSNRs) were calculated and receiver operating characteristic (ROC) curves were constructed based on LSNR ensembles. Mean (expectation) values of the areas under the ROC curves were calculated for lesions of varying size on pixel arrays of varying size at different exposures. Analyses were performed across several parameters, including lesion size, pixel size, and exposure levels representative of various areas of radiography. As expected, lesion detectability increased with lesion size, contrast, pixel size, and exposure. The model suggests that lesion detectability is strongly dependent on the relative alignment (phase) of the lesion with the pixel matrix for lesions on the order of the pixel size.     

Image feature analysis and computer-aided diagnosis in digital radiography. 2. Computerized determination of vessel sizes in digital subtraction angiography

We developed an iterative deconvolution technique to determine the size of a "blurred" vessel in a digital subtraction angiographic (DSA) image by taking into account the unsharpness of the DSA system. Initially, a region of interest over a small segment of the contrast-filled vessel was selected in a DSA image, and the center line of the opacified vessel was determined by polynomial curve fitting of the locations of the peak pixel values along the vessel image. The blurred image profile was then obtained from pixel values across the vessel in a direction perpendicular to the center line. This measured profile was compared iteratively with a calculated profile for various size vessels, which was obtained from a cylindrical vessel model and from the line spread function, until the root-mean-square difference between the two profiles was minimized. The size of a cylindrical vessel yielding the matched profile was considered the best estimate of the unknown vessel size. Studies with a blood vessel phantom indicated that vessels larger than 0.5 mm could be measured with an accuracy and precision of approximately 0.1 mm, which is about 1/3 of the pixel size used in our DSA system. Details of our approach and some clinical vessel images with and without simulated stenotic lesions are presented.     

Effects of pulsatile blood flow in large vessels on thermal dose distribution during thermal therapy

The aim of this study is to evaluate the effect of pulsatile blood flow in thermally significant blood vessels on the thermal lesion region during thermal therapy of tumor. A sinusoidally pulsatile velocity profile for blood flow was employed to simulate the cyclic effect of the heart beat on the blood flow. The evolution of temperature field was governed by the energy transport equation for blood flow together with Pennes' bioheat equation for perfused tissue encircling the blood vessel. The governing equations were numerically solved by a novel multi-block Chebyshev pseudospectral method and the accumulated thermal dose in tissue was computed. Numerical results show that pulsatile velocity profile, with various combinations of pulsatile amplitude and frequency, has little difference in effect on the thermal lesion region of tissue compared with uniform or parabolic velocity profile. However, some minor differences on the thermal lesion region of blood vessel is observed for middle-sized blood vessel. This consequence suggests that, in this kind of problem, we may as well do the simulation simply by a steady uniform velocity profile for blood flow.     

Multisphere phantom and analysis algorithm for PET image quality assessment

PET image quality measurements of lesion detectability frequently use a small, radioactive sphere in a larger phantom. The typical analysis of a small single sphere in background has several shortcomings as a measure for detectability and quantitation: the measurement has low statistical power; the region of interest (ROI) is susceptible to large pixel-to-pixel fluctuations; only a single point in the axial and transaxial field of view is analyzed; background noise measurements in regions away from the signal sphere may bias the detectability measurement and user-placed ROIs can cause inconsistent measurements. For a more robust measurement and repeatable analysis of small lesion detectability in PET images, a multisphere phantom and analysis algorithm were developed. The multisphere phantom consists of a collection of 50 1.0-cm spheres, mounting rods and a gridded plate. A PET/CT study is presented where 29 spheres with a 4:1 sphere-to-background radioactivity ratio were acquired for multiple frame durations and reconstructed. An analysis algorithm was implemented and applied to the acquired PET/CT that detects the contrast-enhanced spheres in a CT, places ROIs on the spheres and their respective proximal background, applies the ROIs to the PET and performs quantitation. Results are presented that show the impact of increasing number of signal spheres and of different background ROI placement methods on the image quality measurement. Increasing the number of spheres reduced the variability in the image quality measurements, but only up to a point, beyond which increasing the number of spheres did not considerably reduce the variability. A phantom with numerous spherical inserts increases several measurement aspects: the flexibility of sphere placement during setup, the number of radioactivity concentrations that can be used during a single study and the statistical power of measurements. Additionally, an automated algorithm that localizes spheres, places ROIs and performs quantitation will increase reliability and reproducibility of image quality assessment, in addition to simplifying the analysis.     

Impact of resolution and noise characteristics of digital radiographic detectors on the detectability of lung nodules

One of the unanswered questions in digital radiography is the connection between physical image quality metrics and clinical detection performance. In this paper, we examine the impact of two physical metrics, resolution and noise, on the detectability of nodules in a pulmonary background for specific digital radiographic detectors. A detection experiment was performed on a simulated image set using anatomical backgrounds from a high-quality lung radiograph and three different simulated nodule sizes (2-3.5 mm). The resolution and noise of the resulting images were modified using existing routines to simulate a selenium-based and a cesium iodide-based flat-panel detector at comparable exposures. A location-known-exactly (LKE) observer performance experiment was performed in which four experienced chest radiologists and three physicists specializing in chest radiology scored the images. The data from the observer experiment were analyzed by receiver operating characteristic (ROC) methodology. The detectability, as measured by the parameter Az, was higher for the selenium detector than the cesium iodide detector for all nodule sizes by an average of 8.5%. For one nodule size (2.75 mm), the difference between detectors was statistically significant (p < 0.01). The findings indicate that for the particular task studied, the superior resolution performance of the selenium-based detector provided better detectability of subtle lung nodules even though the images had greater noise than images obtained with the cesium iodide detector.     

Computation of realistic virtual phantom images for an objective lesion detectability assessment in digital mammography

Image quality assessment is required for an optimal use of mammographic units. On the one hand, there are objective image quality assessment methods based on the measurement of technical parameters such as modulation transfer function (MTF), noise power spectrum (NPS) or detection quantum efficiency (DQE) describing performances of digital detectors. These parameters are, however, without direct relationship with lesion detectability in clinical practice. On the other hand, there are image quality assessment methods involving time consuming procedures, but presenting a direct relationship with lesion detectability. This contribution describes an X-ray source/digital detector model leading to the simulation of virtual contrast-detail phantom (CDMAM) images. The virtual image computation method requires the acquisition of only few real images and allows for an objective image quality assessment presenting a direct relationship with lesion detectability. The transfer function of the proposed model takes as input physical parameters (MTF* and noise) measured under clinical conditions on mammographic units. As presented in this contribution, MTF* is a modified MTF taking into account the effects due to X-ray scatter in the breast and magnification. Results obtained with the structural similarity index prove that the simulated images are quite realistic in terms of contrast and noise. Tests using contrast detail curves highlight the fact that the simulated and real images lead to very similar data quality in terms of lesion detectability. Finally, various statistical tests show that quality factors computed for both the simulated images and the real images are very close for the two data sets.     

A channelized Hotelling observer study of lesion detection in SPECT MAP reconstruction using anatomical priors

In emission tomography, anatomical side information, in the form of organ and lesion boundaries, derived from intra-patient coregistered CT or MR scans can be incorporated into the reconstruction. Our interest is in exploring the efficacy of such side information for lesion detectability. To assess detectability we used the SNR of a channelized Hotelling observer and a signal-known exactly/background-known exactly detection task. In simulation studies, we incorporated anatomical side information into a SPECT MAP (maximum a posteriori) reconstruction by smoothing within but not across organ or lesion boundaries. A non-anatomical prior was applied by uniform smoothing across the entire image. We investigated whether the use of anatomical priors with organ boundaries alone or with perfect lesion boundaries alone would change lesion detectability relative to the case of a prior with no anatomical information. Furthermore, we investigated whether any such detectability changes for the organ-boundary case would be a function of the distance of the lesion to the organ boundary. We also investigated whether any detectability changes for the lesion-boundary case would be a function of the degree of proximity, i.e. a difference in the radius of the true functional lesion and the radius of the anatomical lesion boundary. Our results showed almost no detectability difference with versus without organ boundaries at any lesion-to-organ boundary distance. Our results also showed no difference in lesion detectability with and without lesion boundaries, and no variation of lesion detectability with degree of proximity.     

Amorphous selenium flat panel detectors for digital mammography: validation of a NPWE model observer with CDMAM observer performance experiments

Model observers have been developed which incorporate a specific imaging task, system performance, and human observer characteristics and can potentially overcome some of the limitations in using detective quantum efficiency for optimization and comparison of detectors. In this paper, a modified nonprewhitening matched filter (NPWE) model observer was developed and validated to predict object detectability for an amorphous selenium (a-Se) direct flat-panel imager (FPI) where aliasing is severe. A preclinical a-Se digital mammography FPI with 85 microm pixel size was used in this investigation. Its physical imaging properties including modulation transfer function (MTF), noise power spectrum, and DQE were fully characterized. An observer performance study was conducted by imaging the CDMAM 3.4 contrast-detail phantom designed specifically for digital mammography and presenting these images to a panel of seven observers. X-ray attenuation and scatter due to the phantom were determined experimentally for use in development of the model observer. The observer study results were analyzed via threshold averaging and signal detection theory (SDT) based techniques to produce contrast-detail curves where threshold contrast is plotted as a function of disk diameter. Validity of the model was established using SDT analysis of the experimental data. The effect of aliasing on the detectability of small diameter disks was determined using the NPWE model observer. The signal spectrum was calculated using the presampling MTF of the detector with and without including the aliased terms. Our results indicate that the NPWE model based on Fourier domain parameters provides reasonable prediction of object detectability for the signal-known-exactly task in uniform image noise for a-Se direct FPI.     

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.     

Penalized maximum-likelihood image reconstruction for lesion detection

Detecting cancerous lesions is one major application in emission tomography. In this paper, we study penalized maximum-likelihood image reconstruction for this important clinical task. Compared to analytical reconstruction methods, statistical approaches can improve the image quality by accurately modelling the photon detection process and measurement noise in imaging systems. To explore the full potential of penalized maximum-likelihood image reconstruction for lesion detection, we derived simplified theoretical expressions that allow fast evaluation of the detectability of a random lesion. The theoretical results are used to design the regularization parameters to improve lesion detectability. We conducted computer-based Monte Carlo simulations to compare the proposed penalty function, conventional penalty function, and a penalty function for isotropic point spread function. The lesion detectability is measured by a channelized Hotelling observer. The results show that the proposed penalty function outperforms the other penalty functions for lesion detection. The relative improvement is dependent on the size of the lesion. However, we found that the penalty function optimized for a 5 mm lesion still outperforms the other two penalty functions for detecting a 14 mm lesion. Therefore, it is feasible to use the penalty function designed for small lesions in image reconstruction, because detection of large lesions is relatively easy.     

Signal-to-noise ratio and spatial resolution in x-ray electronic imagers: is the MTF a relevant parameter?

In most imaging detectors, the modulation transfer function (MTF) is regarded as a good parameter to describe spatial resolution. This is undoubtedly valid for visual observation. However, the detectability of a detail is essentially a matter of signal-to-noise ratio, which is not accounted for by the MTF. In x-ray imaging, signal-to-noise ratio in the image is generally limited by incident photons statistics, often larger than readout noises. Therefore, the MTF of the detector applies to both signal and noise, and does not impair the image content. Contrast can easily be restored by image processing without altering the signal-to-noise ratio. However, a number of effects may alter very differently noise and signal: (i) If the MTF significantly extends beyond half the sampling frequency, the aliasing introduced by spatial sampling can severely enhance the noise and cancel the benefit of the good signal transfer. This is illustrated by synthetic images which simulate the response of imagers with different MTFs to the same test pattern in the presence of quantum noise. (ii) Parallax and blurring by the x-ray spot size or motion are shown to degrade the transfer properties of signal, but do not affect the quantum noise; they must be treated separately. Contrary to the x-ray converter MTF, parallax directly impacts the detective quantum efficiency (DQE). Finally, it is shown that only the detective quantum efficiency can reliably describe the spatial resolution of an x-ray imaging detector in the presence of noise, parallax and blurring.     

The role of the lateral suprasylvian visual cortex of the cat in object-background interactions: Permanent deficits following lesions

The contribution of the lateral suprasylvian cortex to pattern recognition was studied by behavioural detection experiments in combination with bilateral lesions of different parts of the lateral suprasylvian areas (LSA) and area 7 in seven cats. In a two-alternatives forced choice task the cats had to discriminate simple outline patterns which were additively superimposed on a structured visual background made up of broadband Gaussian noise. For various stimulus conditions (moving or stationary patterns and/or background) the detection probability (P _D) of the cats was measured as a function of the signal to noise ratio (S/N). Each cat was tested before and after the lesion. Four different types of lesion could be distinguished depending on their extent: (1) lesion of parts of the (LSA); (2) lesion of parts of the LSA with undercutting of areas 17, 18 and 19; (3) lesion of area 7; (4) lesion of area 7 and parts of the LSA.

Patient size and x-ray technique factors in head computed tomography examinations. II. Image quality

We investigated how patient head characteristics, as well as the choice of x-ray technique factors, affect lesion contrast and noise values in computed tomography (CT) images. Head sizes and mean Hounsfield unit (HU) values were obtained from head CT images for five classes of patients ranging from the newborn to adults. X-ray spectra with tube voltages ranging from 80 to 140 kV were used to compute the average photon energy, and energy fluence, transmitted through the heads of patients of varying size. Image contrast, and the corresponding contrast to noise ratios (CNRs), were determined for lesions of fat, muscle, and iodine relative to a uniform water background. Maintaining a constant image CNR for each lesion, the patient energy imparted was also computed to identify the x-ray tube voltage that minimized the radiation dose. For adults, increasing the tube voltage from 80 to 140 kV changed the iodine HU from 2.62 x 10(5) to 1.27 x 10(5), the fat HU from -138 to -108, and the muscle HU from 37.1 to 33.0. Increasing the x-ray tube voltage from 80 to 140 kV increased the percentage energy fluence transmission by up to a factor of 2. For a fixed x-ray tube voltage, the percentage transmitted energy fluence in adults was more than a factor of 4 lower than for newborns. For adults, increasing the x-ray tube voltage from 80 to 140 kV improved the CNR for muscle lesions by 130%, for fat lesions by a factor of 2, and for iodine lesions by 25%. As the size of the patient increased from newborn to adults, lesion CNR was reduced by about a factor of 2. The mAs value can be reduced by 80% when scanning newborns while maintaining the same lesion CNR as for adults. Maintaining the CNR of an iodine lesion at a constant level, use of 140 kV increases the energy imparted to an adult patient by nearly a factor of 3.5 in comparison to 80 kV. For fat and muscle lesions, raising the x-ray tube voltage from 80 to 140 kV at a constant CNR increased the patient dose by 37% and 7%, respectively. Our two key findings are that for head CT examinations performed at a constant CNR, the mAs can be substantially reduced when scanning infants, and that use of the lowest x-ray tube voltage will generally reduce patient doses.     

Velocity profile distribution along an arterial vessel: way to improve detection of stenotic sites

The influence of an arterial stenosis on the pattern of blood velocity spatial distribution is investigated. The blood velocity field in a human femoral artery in a stenotic state is computed by means of numerical simulation. Four distributions of velocity profiles along the vessel are shown, corresponding to four different instants of the cardiac cycle. The shape of the spatial pattern of the velocity profile is strongly perturbed by the stenosis: disturbances are so clear that an easy, precise localisation of the stenotic site is always possible, whatever instant of the cardiac cycle is considered. The reported results prove that a three-dimensional view of the velocity profile distribution along the vessel best emphasises the relevant haemodynamic information from a diagnostic point of view.     

Prognostic factors in cutaneous malignant melanoma. A comparative study of long term and short term survivors

The clinical presentation and histologic characteristics of primary melanomas of a consecutive series of 100 short term (fatal within five years) and 100 long term survivors (disease-free for ten years or longer) were studied. The clinical parameters analyzed included the history of pre-existent mole, duration of changes before diagnosis, site, elevation, ulceration, extent of pigmentation, and satellitosis around the primary lesion. Study of histologic features included analysis of exact measurements of the primary melanoma, depth of dermal invasion, tumor cell morphology, mitotic rate, intracellular pigmentation, presence or absence of giant tumor cells, blood vessel or lymphatic invasion, lateral junctional activity, and presence and extent of lymphoid response to the primary lesion.Statistically significant differences were found between the long term and short term survivors with respect to several variables. It is one of the conclusions of this study that an elective node dissection would seem to be indicated in all patients with stage I melanoma who present with poor prognostic signs, that is, patients who belong to any combination of the following categories: male, primary lesions>1 cm., which has ulcerated, with a deeper level of dermal penetration, with dermal lymphatic or blood vessel invasion, and a lack of lymphoid reaction around the primary lesion.     

应用连续小波变换检测和增强DSA血管影像的研究

数字血管减影的影像中的血管像具有对比度低的特点。本文用一种全新的思想实现DSA影像中血管像的增强,即先应用小波变换技术检测血管边缘,使其从背景中分离出来,再应用对比度拉伸的方法进一步增强血管同背景的对比度,由于本文使用的连续小波变换可从不同方向上检测影像灰度变化情况,所以检测到的影像边缘更准确全面,而且由于噪声的小波变换的模较小,较好地抑制了减影像中的背景噪音,处理后的血管影像具有三维实体的视觉效果。     

Optimisation of density and contrast yielded by multiformat photographic imagers used for scintigraphy

The maximum optical density (MOD) and contrast (characterised by an effective gamma, gamma eff) yielded by multiformat photographic imagers used for scintigraphy, was determined by densitometry of a computer image, which consisted of a pattern of uniform squares containing known counts. A series of clinical scintigrams were photographed using various MOD and gamma eff values, and were graded by three experienced clinicians. It was found that a MOD of 1.6 and a gamma eff of 2.9 yielded optimal images for general use if bone scintigrams are also to be photographed. Lesion detectability in phantom images using extreme MOD and gamma eff values that were still clinically acceptable was determined. At very low false-positive rates (less than or equal to 1%) the higher gamma eff yielded a significantly greater lesion detectability (p = 0.02) at an information density of 2200 counts cm-2 in accordance with White-head's theory. It is concluded that quantification and optimisation of density and contrast factors are important and that the technique described enables quality control of multiformat imagers with respect to these factors.