Design considerations for a limited angle, dedicated breast, TOF PET scanner

Development of partial ring, dedicated breast positron emission tomography (PET) scanners is an active area of research. Due to the limited angular coverage, generation of distortion and artifact-free, fully 3D tomographic images is not possible without rotation of the detectors. With time-of-flight (TOF) information, it is possible to achieve the 3D tomographic images with limited angular coverage and without detector rotation. We performed simulations for a breast scanner design with a ring diameter and an axial length of 15 cm and comprising a full (180 degrees in-plane angular coverage), 2/3 (120 degrees in-plane angular coverage) or 1/2 (90 degrees in-plane angular coverage) ring detector. Our results show that as the angular coverage decreases, improved timing resolution is needed to achieve distortion-free and artifact-free images with TOF. The contrast recovery coefficient (CRC) value for small hot lesions in a partial ring scanner is similar to a full ring non-TOF scanner. Our results indicate that a timing resolution of 600 ps is needed for a 2/3 ring scanner, while a timing resolution of 300 ps is needed for a 1/2 ring scanner. We also analyzed the ratio of lesion CRC to the background pixel noise (SNR) and concluded that TOF improves the SNR values of the partial ring scanner, and helps to compensate for the loss in sensitivity due to reduced geometric sensitivity in a limited angle coverage PET scanner. In particular, it is possible to maintain similar SNR characteristic in a 2/3 ring scanner with a timing resolution of 300 ps as in a full ring non-TOF scanner.     

Image quality assessment of LaBr3-based whole-body 3D PET scanners: a Monte Carlo evaluation

The main thrust for this work is the investigation and design of a whole-body PET scanner based on new lanthanum bromide scintillators. We use Monte Carlo simulations to generate data for a 3D PET scanner based on LaBr3 detectors, and to assess the count-rate capability and the reconstructed image quality of phantoms with hot and cold spheres using contrast and noise parameters. Previously we have shown that LaBr3 has very high light output, excellent energy resolution and fast timing properties which can lead to the design of a time-of-flight (TOF) whole-body PET camera. The data presented here illustrate the performance of LaBr3 without the additional benefit of TOF information, although our intention is to develop a scanner with TOF measurement capability. The only drawbacks of LaBr3 are the lower stopping power and photo-fraction which affect both sensitivity and spatial resolution. However, in 3D PET imaging where energy resolution is very important for reducing scattered coincidences in the reconstructed image, the image quality attained in a non-TOF LaBr3 scanner can potentially equal or surpass that achieved with other high sensitivity scanners. Our results show that there is a gain in NEC arising from the reduced scatter and random fractions in a LaBr3 scanner. The reconstructed image resolution is slightly worse than a high-Z scintillator, but at increased count-rates, reduced pulse pileup leads to an image resolution similar to that of LSO. Image quality simulations predict reduced contrast for small hot spheres compared to an LSO scanner, but improved noise characteristics at similar clinical activity levels.     

Why is TOF PET reconstruction a more robust method in the presence of inconsistent data?

In order to obtain an accurate and quantitative positron emission tomography (PET) image, emission data need to be corrected for random coincidences, photon attenuation and Compton scattering of photons in the tissue, and detector efficiency response or normalization. The accuracy of these corrections strongly affects the quality of the PET image. There is evidence that time-of-flight (TOF) PET reconstruction is less sensitive than non-TOF reconstruction to inconsistencies between emission data and corrections. The purpose of this study is to analyze and discuss such experimental evidence. In this work, inconsistent correction data (inconsistent normalization, absence of scatter correction and mismatched attenuation correction) are introduced in experimental phantom data. Both TOF and non-TOF reconstructed images are analyzed to examine the effect of flawed data. The behavior of TOF reconstruction in respiratory artifacts, a very common example of inconsistency in the data, is studied in patient images. TOF reconstruction is less sensitive to mismatched attenuation correction, erroneous normalization and poorly estimated scatter correction. Such robustness depends strongly on the time resolution of the TOF PET scanner. In particular, the robustness of TOF in the presence of attenuation correction inconsistencies is discussed, using a simulation of a simple model of respiratory artifacts. We expect new generations of PET scanners, with improved time resolution, to be less and less sensitive to poor quality normalization, scatter and attenuation corrections. This not only reduces artifacts in the PET image, but also opens the way to less stringent requirements for the quality of the CT image (reducing either the equipment cost or the dose to the patient), and for the normalization protocols (simplifying or shortening the normalization procedures). Moreover, TOF reconstruction can be beneficial in multimodalities such as PET/MR, where a direct attenuation measurement is not available and attenuation correction can only be approximated.     

First experimental results of time-of-flight reconstruction on an LSO PET scanner

Time-of-flight (TOF) positron emission tomography (PET) was studied and preliminarily developed in the 1980s, but the lack of a scintillator able to deliver at the same time proper time resolution and stopping power has prevented this technique from becoming widespread and commercially available. With the introduction of LSO in PET, TOF is now a feasible option. TOF reconstruction has been implemented in the CPS Hi-Rez PET scanner, both with 2D filtered-back-projection (FBP2D) and 3D ordered subset expectation maximization (OSEM3D). A new procedure has been introduced in the time alignment to compensate for the limited digital time resolution of the present electronics. A preliminary version of scatter correction for TOF has been devised and is presented. The measured time resolution of 1.2 ns (FWHM) allowed for a signal-to-noise ratio increase of about 50% in phantoms of about 40 cm transaxial size, or a gain larger than 2 in noise equivalent counts (NEC). TOF reconstruction has shown the expected improvement in SNR, both in simulation and experimental data. First experimental results show two improvements of TOF reconstruction over conventional (non-TOF) reconstruction: a lower noise level and a better capability to resolve structures deep inside large objects.     

Rapid calculation of detectability in Bayesian single photon emission computed tomography

We consider the calculation of lesion detectability using a mathematical model observer, the channelized Hotelling observer (CHO), in a signal-known-exactly/background-known-exactly detection task for single photon emission computed tomography (SPECT). We focus on SPECT images reconstructed with Bayesian maximum a posteriori methods. While model observers are designed to replace time-consuming studies using human observers, the calculation of CHO detectability is usually accomplished using a large number of sample images, which is still time consuming. We develop theoretical expressions for a measure of detectability, the signal-to-noise-ratio (SNR) of a CHO observer, that can be very rapidly evaluated. Key to our expressions are approximations to the reconstructed image covariance. In these approximations, we use methods developed in the PET literature, but modify them to reflect the different nature of attenuation and distance-dependent blur in SPECT. We validate our expressions with Monte Carlo methods. We show that reasonably accurate estimates of the SNR can be obtained at a computational expense equivalent to approximately two projection operations, and that evaluating SNR for subsequent lesion locations requires negligible additional computation.     

Comparison of yttrium-90 quantitative imaging by TOF and non-TOF PET in a phantom of liver selective internal radiotherapy

The aim of this study is to determine the feasibility of achieving quantitative measurement in (90)Y-microspheres liver selective internal radiotherapy (SIRT) by imaging (90)Y with a conventional non-time of flight (TOF) PET device. Instead of the bremsstrahlung x-rays of the β-decay, the low branch of e(-)-?e(+) pair production in the (90)Y-decay was used. The activity distribution in a phantom-simulated liver SIRT was obtained by direct (90)Y-PET imaging. We tested a LYSO TOF PET and two GSO and BGO non-TOF PET scanners using a 3.6-l cylindrical phantom filled with the (90)Y solution containing two sets of hot and cold spheres. The best hot contrast was obtained with the LYSO TOF. It was close to the expected value and remained constant, even for short acquisition times. The LYSO non-TOF was about 10% lower. The GSO performed similarly but degraded for shorter times whilst the BGO was the worst with 40% loss. For the cold spheres, the LYSO TOF and the GSO provided the best results, while the LYSO non-TOF and the BGO were the worst. (90)Y PET imaging in liver SIRT is achievable with LYSO TOF. Conventional LYSO and GSO show a loss of contrast and require longer acquisition times. BGO imaging is not feasible for dosimetry calculation.     

Small nodule detectability evaluation using a generalized scan-statistic model

In this paper is investigated the use of the scan statistic for evaluating the detectability of small nodules in medical images. The scan-statistic method is often used in applications in which random fields must be searched for abnormal local features. Several results of the detection with localization theory are reviewed and a generalization is presented using the noise nodule distribution obtained by scanning arbitrary areas. One benefit of the noise nodule model is that it enables determination of the scan-statistic distribution by using only a few image samples in a way suitable both for simulation and experimental setups. Also, based on the noise nodule model, the case of multiple targets per image is addressed and an image abnormality test using the likelihood ratio and an alternative test using multiple decision thresholds are derived. The results obtained reveal that in the case of low contrast nodules or multiple nodules the usual test strategy based on a single decision threshold underperforms compared with the alternative tests. That is a consequence of the fact that not only the contrast or the size, but also the number of suspicious nodules is a clue indicating the image abnormality. In the case of the likelihood ratio test, the multiple clues are unified in a single decision variable. Other tests that process multiple clues differently do not necessarily produce a unique ROC curve, as shown in examples using a test involving two decision thresholds. We present examples with two-dimensional time-of-flight (TOF) and non-TOF PET image sets analysed using the scan statistic for different search areas, as well as the fixed position observer.     

Design study of an in situ PET scanner for use in proton beam therapy

Proton beam therapy can deliver a high radiation dose to a tumor without significant damage to surrounding healthy tissue or organs. One way of verifying the delivered dose distribution is to image the short-lived positron emitters produced by the proton beam as it travels through the patient. A potential solution to the limitations of PET imaging in proton beam therapy is the development of a high sensitivity, in situ PET scanner that starts PET imaging almost immediately after patient irradiation while the patient is still lying on the treatment bed. A partial ring PET design is needed for this application in order to avoid interference between the PET detectors and the proton beam, as well as restrictions on patient positioning on the couch. A partial ring also allows us to optimize the detector separation (and hence the sensitivity) for different patient sizes. Our goal in this investigation is to evaluate an in situ PET scanner design for use in proton therapy that provides tomographic imaging in a partial ring scanner design using time-of-flight (TOF) information and an iterative reconstruction algorithm. GEANT4 simulation of an incident proton beam was used to produce a positron emitter distribution, which was parameterized and then used as the source distribution inside a water-filled cylinder for EGS4 simulations of a PET system. Design optimization studies were performed as a function of crystal type and size, system timing resolution, scanner angular coverage and number of positron emitter decays. Data analysis was performed to measure the accuracy of the reconstructed positron emitter distribution as well as the range of the positron emitter distribution. We simulated scanners with varying crystal sizes (2-4 mm) and type (LYSO and LaBr(3)) and our results indicate that 4 mm wide LYSO or LaBr(3) crystals (resulting in 4-5 mm spatial resolution) are adequate; for a full-ring, non-TOF scanner we predict a low bias (<0.6 mm) and a good precision (<1 mm) in the estimated range relative to the simulated positron distribution. We then varied the angular acceptance of the scanner ranging from 1/2 to 2/3 of 2π; a partial ring TOF imaging with good timing resolution (≤600 ps) is necessary to produce accurate tomographic images. A two-third ring scanner with 300 ps timing resolution leads to a bias of 1.0 mm and a precision of 1.4 mm in the range estimate. With a timing resolution of 600 ps, the bias increases to 2.0 mm while the precision in the range estimate is similar. For a half-ring scanner design, more distortions are present in the image, which is characterized by the increased error in the profile difference estimate. We varied the number of positron decays imaged by the PET scanner by an order of magnitude and we observe some decrease in the precision of the range estimate for lower number of decays, but all partial ring scanner designs studied have a precision ≤1.5 mm. The largest number tested, 150 M total positron decays, is considered realistic for a clinical fraction of delivered dose, while the range of positron decays investigated in this work covers a variable number of situations corresponding to delays in scan start time and the total scan time. Thus, we conclude that for partial ring systems, an angular acceptance of at least 1/2 (of 2π) together with timing resolution of 300 ps is needed to achieve accurate and precise range estimates. With 600 ps timing resolution an angular acceptance of 2/3 (of 2π) is required to achieve satisfactory range estimates. These results indicate that it would be feasible to develop a partial-ring dedicated PET scanner based on either LaBr(3) or LYSO to accurately characterize the proton dose for therapy planning.     

Fourier rebinning of time-of-flight PET data

This paper explores fast reconstruction strategies for 3D time-of-flight (TOF) positron emission tomography (PET), based on 2D data rebinning. Starting from pre-corrected 3D TOF data, a rebinning algorithm estimates for each transaxial slice the 2D TOF sinogram that would have been acquired by a single-ring scanner. The rebinned sinograms can then be reconstructed using any algorithm for 2D TOF reconstruction. We introduce TOF-FORE, an approximate rebinning algorithm obtained by extending the Fourier rebinning method for non-TOF data. In addition, we identify two partial differential equations that must be satisfied by consistent 3D TOF data, and use them to derive exact rebinning algorithms and to characterize the degree of the approximation in TOF-FORE. Numerical simulations demonstrate that TOF-FORE is more accurate than two different TOF extensions of the single-slice rebinning method, and suggest that TOF-FORE will be a valuable tool for practical TOF PET in the range of axial apertures and time resolutions typical of current scanners.     

A new timing model for calculating the intrinsic timing resolution of a scintillator detector

The coincidence timing resolution is a critical parameter which to a large extent determines the system performance of positron emission tomography (PET). This is particularly true for time-of-flight (TOF) PET that requires an excellent coincidence timing resolution (<1 ns) in order to significantly improve the image quality. The intrinsic timing resolution is conventionally calculated with a single-exponential timing model that includes two parameters of a scintillator detector: scintillation decay time and total photoelectron yield from the photon-electron conversion. However, this calculation has led to significant errors when the coincidence timing resolution reaches 1 ns or less. In this paper, a bi-exponential timing model is derived and evaluated. The new timing model includes an additional parameter of a scintillator detector: scintillation rise time. The effect of rise time on the timing resolution has been investigated analytically, and the results reveal that the rise time can significantly change the timing resolution of fast scintillators that have short decay time constants. Compared with measured data, the calculations have shown that the new timing model significantly improves the accuracy in the calculation of timing resolutions.     

Physical and clinical performance of the mCT time-of-flight PET/CT scanner

Time-of-flight (TOF) measurement capability promises to improve PET image quality. We characterized the physical and clinical PET performance of the first Biograph mCT TOF PET/CT scanner (Siemens Medical Solutions USA, Inc.) in comparison with its predecessor, the Biograph TruePoint TrueV. In particular, we defined the improvements with TOF. The physical performance was evaluated according to the National Electrical Manufacturers Association (NEMA) NU 2-2007 standard with additional measurements to specifically address the TOF capability. Patient data were analyzed to obtain the clinical performance of the scanner. As expected for the same size crystal detectors, a similar spatial resolution was measured on the mCT as on the TruePoint TrueV. The mCT demonstrated modestly higher sensitivity (increase by 19.7 ± 2.8%) and peak noise equivalent count rate (NECR) (increase by 15.5 ± 5.7%) with similar scatter fractions. The energy, time and spatial resolutions for a varying single count rate of up to 55 Mcps resulted in 11.5 ± 0.2% (FWHM), 527.5 ± 4.9 ps (FWHM) and 4.1 ± 0.0 mm (FWHM), respectively. With the addition of TOF, the mCT also produced substantially higher image contrast recovery and signal-to-noise ratios in a clinically-relevant phantom geometry. The benefits of TOF were clearly demonstrated in representative patient images.     

ROC analysis for assessment of lesion detection performance in 3D PET: influence of reconstruction algorithms

Image quality in positron emission tomography (PET) can be assessed with physical parameters, as spatial resolution and signal-to-noise ratio, or using psychophysical approaches, which include the observer performance and the considered task (ROC analysis). For PET in oncology, such a task is the detection of hot lesions. The aim of the present study was to assess the lesion detection performance due to adequate modeling of the scanner and the measurement process in the image reconstruction process. We compared the standard OSEM software of the manufacturer with a sophisticated fully 3D iterative reconstruction technique (USC MAP). A rectangular phantom with 6 oblique line sources in a homogeneous background (2.6 kBq/ml 18F) was imaged dynamically with an ECAT EXACT HR+ scanner in 3D mode. Reconstructed activity contrasts varied between 15 and 0, as the line sources were filled with 11C (3.2 MBq/ml). Measured attenuation and standard randoms, dead time, and scatter corrections of the manufacturer were employed. For the ROC analysis, a software tool presented a cut-out of the phantom (15 x 15 pixels) to two observers. These cut-outs were rated (5 classes) and the area Az under the ROC curve was determined as a measure of detection performance. The improvement for Az with USC MAP compared to the OSEM reconstructions ranged between 0.02 and 0.23 for signal-to-noise ratios of the background between 2.8 and 3.1 and lesion contrast between 2.1 and 4.2. This study demonstrates that adequate modeling of the measurement process in the reconstruction algorithm improves the detection of small hot lesions markedly.     

Signal and noise properties of position-sensitive avalanche photodiodes

After many years of development, position-sensitive avalanche photodiodes (PSAPDs) are now being incorporated into a range of scintillation detector systems, including those used in high-resolution small-animal PET and PET/MR scanners. In this work, the signal, noise, signal-to-noise ratio (SNR), flood histogram and timing resolution were measured for lutetium oxyorthosilicate (LSO) scintillator arrays coupled to PSAPDs ranging in size from 10 to 20 mm, and the optimum bias voltage and working temperature were determined. Variations in the SNR performance of PSAPDs with the same dimensions were small, but the SNR decreased significantly with increasing PSAPD size and increasing temperature. Smaller PSAPDs (10 mm and 15 mm in width) produced acceptable flood histograms at 24 °C, and cooling lower than 16 °C produced little improvement. The optimum bias voltage was about 25 V below the break down voltage. The larger 20 mm PSAPDs have lower SNR and require cooling to 0-7 °C for acceptable performance. The optimum bias voltage is also lower (35 V or more below the break down voltage depending on the temperature). Significant changes in the timing resolution were observed as the bias voltage and temperature varied. Higher bias voltages provided better timing resolution. The best timing resolution obtained for individual crystals was 2.8 ns and 3.3 ns for the 10 mm and 15 mm PSAPDs, respectively. The results of this work provide useful guidance for selecting the bias voltage and working temperature for scintillation detectors that incorporate PSAPDs as the photodetector.     

CHO数字观察器在PET图像滤波方法评估中的应用

在临床应用中需要限制扫描时间和药物剂量,这往往会使正电子发射断层扫描(PET)的图像的分辨率变低,噪声变多。为提供可供临床诊断的图像,去噪是一个必须的手段,而在重建后增加一个滤波器是目前最常用的去噪方法。因此对不同滤波器滤波效果的比较是PET图像重建中的重要环节,其中最关键的是滤波参数的选取。目前采用的信噪比(SNR)以及恢复系数(RC)等评估方法可以用来非定量地选取参数,研究者们只能凭经验选取最优参数。而通道化霍特林观察器(CHO)作为一个比较通用的数字观察器,已被用于与PET图像质量相关的各种参数的选择,如重建算法参数、系统设计参数、临床协议参数等,然而其在评估不同滤波方法对图像重建质量的影响中的应用研究还比较少。通过比较CHO计算得到的ROC(receiver operating characteristic)曲线下面积(area under the ROC curve,AUC),选择两种常用的滤波器(即高斯滤波器和非局部均值(Non-Local Mean, NLM)滤波器)的最优参数,并评估它们在PET中的滤波效果。结果表明,对于13 mm球体,σ为1.1~1.4的高斯滤波器和f为0.5~0.9的NLM滤波器可以达到最大的检测能力值,而对于10 mm球体,σ为1.4~2.0的高斯滤波器和f为0.5~0.9的NLM滤波器可以达到最大的检测能力值。虽然两个滤波器所对应的AUC值都能高达0.9,但是NLM滤波器的AUC值高于高斯滤波器。通过IEC图像和病人图像也能发现,NLM滤波后的PET图像中的亮点比高斯滤波的更加清晰,噪声更少。该结论和传统滤波器评估方法得到的结论一致,这说明在PET的病灶检测任务中,CHO能够准确地比较这两种滤波器的性能。     

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.     

Fast reconstruction of 3D time-of-flight PET data by axial rebinning and transverse mashing

Faster scintillators like LaBr(3) and LSO have sparked renewed interest in PET scanners with time-of-flight (TOF) information. The TOF information adds another dimension to the data set compared to conventional three-dimensional (3D) PET with the size of the projection data being multiplied by the number of TOF bins. Here we show by simulations and analytical reconstruction that angular sampling for two-dimensional (2D) TOF PET can be reduced significantly compared to what is required for conventional 2D PET. Fully 3D TOF PET data, however, have a wide range of oblique and transverse angles. To make use of the smaller necessary angular sampling we reduce the 3D data to a set of 2D histoprojections. This is done by rebinning the 3D data to 2D data and by mashing these 2D data into a limited number of angles. Both methods are based on the most likely point given by the TOF measurement. It is shown that the axial resolution loss associated with rebinning reduces with improved timing resolution and becomes less than 1 mm for a TOF resolution below 300 ps. The amount of angular mashing that can be applied without tangential resolution loss increases with improved TOF resolution. Even quite coarse angular mashing (18 angles out of 324 measured angles for 424 ps) does not significantly reduce image quality in terms of the contrast or noise. The advantages of the proposed methods are threefold. Data storage is reduced to a limited number of 2D histoprojections with TOF information. Compared to listmode format we have the advantage of a predetermined storage space and faster reconstruction. The method does not require the normalization of projections prior to rebinning and can be applied directly to measured listmode data.     

Accelerated EM reconstruction in total-body PET: potential for improving tumour detectability

Total-body positron emission tomography (PET) is a useful diagnostic tool for evaluating malignant disease. However, tumour detection is limited by image artefacts due to the lack of attenuation correction and noise. Attenuation correction may be possible using transmission data acquired after or simultaneously with emission data. Despite the elimination of attenuation artefacts, however, tumour detection is still hampered by noise, which is amplified during image reconstruction by filtered backprojection (FBP). We have investigated, as an alternative to FBP, an accelerated expectation maximization (EM) algorithm for its potential to improve tumour detectability in total-body PET. Signal to noise ratio (SNR), calculated for a tumour with respect to the surrounding background, is used as a figure of merit. A software tumour phantom, with conditions typical of those encountered in a total-body PET study using simultaneous acquisition, is used to optimize and compare various reconstruction approaches. Accelerated EM reconstruction followed by two-dimensional filtering is shown to yield significantly higher SNR than FBP for a range of tumour sizes, concentrations and counting statistics (deltaSNR = 6.3 +/- 3.9, p < 0.001). The methods developed are illustrated by examples derived from physical phantom and patient data.     

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.     

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.     

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.