The relationship between cancer detection in mammography and image quality measurements

PurposeTo investigate the relationship between image quality measurements and the clinical performance of digital mammographic systems.MethodsMammograms containing subtle malignant non-calcification lesions and simulated malignant calcification clusters were adapted to appear as if acquired by four types of detector. Observers searched for suspicious lesions and gave these a malignancy score. Analysis was undertaken using jackknife alternative free-response receiver operating characteristics weighted figure of merit (FoM). Images of a CDMAM contrast-detail phantom were adapted to appear as if acquired using the same four detectors as the clinical images. The resultant threshold gold thicknesses were compared to the FoMs using a linear regression model and an F-test was used to find if the gradient of the relationship was significantly non-zero.ResultsThe detectors with the best image quality measurement also had the highest FoM values. The gradient of the inverse relationship between FoMs and threshold gold thickness for the 0.25 mm diameter disk was significantly different from zero for calcification clusters (p = 0.027), but not for non-calcification lesions (p = 0.11). Systems performing just above the minimum image quality level set in the European Guidelines for Quality Assurance in Breast Cancer Screening and Diagnosis resulted in reduced cancer detection rates compared to systems performing at the achievable level.ConclusionsThe clinical effectiveness of mammography for the task of detecting calcification clusters was found to be linked to image quality assessment using the CDMAM phantom. The European Guidelines should be reviewed as the current minimum image quality standards may be too low.     

Optimization of the exposure parameters in digital mammography using contrast-detail metrics

PurposeOptimization studies in digital mammography aid to assure the image quality and radiological protection of the patient. The aim of this work is to test effectiveness and applicability of a method based on a Figure of Merit (FOM = (IQF_inv)²/AGD) to improve all the exposure parameters (Target/Filter combination, kVp and mAs) in order to improve the image acquisition technique that will provide the best compromise between image quality and the average glandular dose (AGD).MethodsA contrast-detail analysis, employing the test object CDMAM, was carried out for the digital mammography unit manufactured by Lorad Hologic – model Selenia. We simulated two breast thicknesses using phantoms and a Figure of Merit as optimization tool, which includes an indicator of image quality, the IQF_inv and the average glandular dose. Images of the ACR and TORMAM phantoms were obtained with both, automatic and optimized exposure parameters. In order to compare the image quality, the SNR (Signal to Noise Ratio) was measured in each image.ResultsIn the two phantoms, for both 4.5 and 7.5 cm thicknesses, the AGDs obtained with the optimized parameters show a reduction. In addition, the images obtained with the optimized exposure parameters, had the same or a better image quality when compared to the images obtained using the automatic mode.ConclusionsThe proposed optimization methodology proved to be an effective tool to improve the digital mammography unit, due to the use of objective metrics for evaluation and validation of the results.     

Simulation of images of CDMAM phantom and the estimation of measurement uncertainties of threshold gold thickness

PurposeTo demonstrate a method of simulating mammography images of the CDMAM phantom and to investigate the coefficient of variation (CoV) in the threshold gold thickness (t_T) measurements associated with use of the phantom.MethodsThe noise and sharpness of Hologic Dimensions and GE Essential mammography systems were characterized to provide data for the simulation. The simulation method was validated by comparing the t_T results of real and simulated images of the CDMAM phantom for three different doses and the two systems. The detection matrices produced from each of 64 images using CDCOM software were randomly resampled to create 512 sets of 8, 16 and 32 images to estimate the CoV of t_T. Sets of simulated images for a range of doses were used to estimate the CoVs for a range of diameters and threshold thicknesses.ResultsNo significant differences were found for t_T or the CoV between real and simulated CDMAM images. It was shown that resampling from 256 images was required for estimating the CoV. The CoV was around 4% using 16 images for most of the phantom but is over double that for details near the edge of the phantom.ConclusionsWe have demonstrated a method to simulate images of the CDMAM phantom for different systems at a range of doses. We provide data for calculating uncertainties in t_T. Any future review of the European guidelines should take into consideration the calculated uncertainties for the 0.1 mm detail.     

Evaluation of automatic image quality assessment in chest CT – A human cadaver study

PurposeThe evaluation of clinical image quality (IQ) is important to optimize CT protocols and to keep patient doses as low as reasonably achievable. Considering the significant amount of effort needed for human observer studies, automatic IQ tools are a promising alternative. The purpose of this study was to evaluate automatic IQ assessment in chest CT using Thiel embalmed cadavers.MethodsChest CT’s of Thiel embalmed cadavers were acquired at different exposures. Clinical IQ was determined by performing a visual grading analysis. Physical-technical IQ (noise, contrast-to-noise and contrast-detail) was assessed in a Catphan phantom. Soft and sharp reconstructions were made with filtered back projection and two strengths of iterative reconstruction. In addition to the classical IQ metrics, an automatic algorithm was used to calculate image quality scores (IQs). To be able to compare datasets reconstructed with different kernels, the IQs values were normalized.ResultsGood correlations were found between IQs and the measured physical-technical image quality: noise (ρ = −1.00), contrast-to-noise (ρ = 1.00) and contrast-detail (ρ = 0.96). The correlation coefficients between IQs and the observed clinical image quality of soft and sharp reconstructions were 0.88 and 0.93, respectively.ConclusionsThe automatic scoring algorithm is a promising tool for the evaluation of thoracic CT scans in daily clinical practice. It allows monitoring of the image quality of a chest protocol over time, without human intervention. Different reconstruction kernels can be compared after normalization of the IQs.     

Toward standardized quantitative image quality (IQ) assessment in computed tomography (CT): A comprehensive framework for automated and comparative IQ analysis based on ICRU Report 87

PurposeBased on the guidelines from “Report 87: Radiation Dose and Image-quality Assessment in Computed Tomography” of the International Commission on Radiation Units and Measurements (ICRU), a software framework for automated quantitative image quality analysis was developed and its usability for a variety of scientific questions demonstrated.MethodsThe extendable framework currently implements the calculation of the recommended Fourier image quality (IQ) metrics modulation transfer function (MTF) and noise-power spectrum (NPS), and additional IQ quantities such as noise magnitude, CT number accuracy, uniformity across the field-of-view, contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) of simulated lesions for a commercially available cone-beam phantom. Sample image data were acquired with different scan and reconstruction settings on CT systems from different manufacturers.ResultsSpatial resolution is analyzed in terms of edge-spread function, line-spread-function, and MTF. 3D NPS is calculated according to ICRU Report 87, and condensed to 2D and radially averaged 1D representations. Noise magnitude, CT numbers, and uniformity of these quantities are assessed on large samples of ROIs. Low-contrast resolution (CNR, SNR) is quantitatively evaluated as a function of lesion contrast and diameter. Simultaneous automated processing of several image datasets allows for straightforward comparative assessment.ConclusionsThe presented framework enables systematic, reproducible, automated and time-efficient quantitative IQ analysis. Consistent application of the ICRU guidelines facilitates standardization of quantitative assessment not only for routine quality assurance, but for a number of research questions, e.g. the comparison of different scanner models or acquisition protocols, and the evaluation of new technology or reconstruction methods.     

Novel phantom for performance evaluation of contrast-enhanced 3D rotational angiography

PurposeThis technical note presents an in-house phantom with a specially designed contrast-object module constructed to address the need for three-dimensional rotational angiography (3DRA) testing.MethodsThe initial part of the study was a brief evaluation on the commercially available phantom used for 3DRA and computed tomography angiography (CTA) to confirm the need for a special phantom for 3D angiography. Once confirmed, an in-house phantom was constructed. The novel phantom was tested to evaluate the basic image performance metrics, i.e., unsharpness (MTF) and noise characterization (NPS), as well as to show its capability for vessel contrast visibility study.ResultsThe low contrast objects in the commercially available tools dedicated for CT is found to yield significantly lower signal difference to noise ratio (SDNR) when used for 3DRA, therefore deemed inadequate for 3DRA contrast evaluation. The constructed in-house phantom demonstrates a capability to serve for basic imaging performance check (MTF, NPS, and low contrast evaluation) for 3DRA and CTA. With higher and potentially adjustable visibility of contrast objects as artificial vessels, the in-house phantom also makes more clinically relevant tests, e.g., human- or model observer study and task-based optimization, possible.ConclusionThe novel phantom with special contrast object module shows higher visibility in 3DRA compared to the currently available commercial phantom and, therefore, is recommended for use in 3D angiography.     

A computer-aided diagnosis scheme of breast lesion classification using GLGLM and shape features: Combined-view and multi-classifiers

PurposeTo address high false-positive results of FFDM issue, we make the first effort to develop a computer-aided diagnosis (CAD) scheme to analyze and distinguish breast lesions.MethodThe breast lesion regions were first segmented and depicted on FFDM images from 106 patients. In this work, 11 gray-level gap-length matrix texture features and 12 shape features were extracted form craniocaudal view and mediolateral oblique view, and then Student’s t-test, Fisher-score and Relief-F were introduced to select features. We also investigated the effect of three factors, i.e., discretisation, selection methods and classifier methods, of the classification performance via analysis of variance. Finally, a classification model was constructed. Spearman’s correlation coefficient analysis was conducted to assess the internal relevance of features.ResultsThe proposed scheme using Student’s t-test achieved an area under the receiver operating characteristic curve (AUC) value of 0.923 at 512 bins. The AUC values are 0.884, 0.867, 0.874 and 0.901 for the low gray-level gaps emphasis (LGGE), solidity, extent, and the combined set, respectively. Solidity and extent depicts the correlation coefficient of 0.86 (P < 0.05).ConclusionsWe present a new CAD scheme based on the contribution of the significant factors. The experimental results demonstrate that the presented scheme can be used to successfully distinguish breast carcinoma lesions and benign fibroadenoma lesions in our FFDM dataset and the MIAS dataset, which may provide a CAD method to assist radiologists in diagnosing and interpreting screening mammograms. Moreover, we found that LGGE, solidity and extent features show great potential for breast lesion classification.     

Performance comparison of two resolution modeling PET reconstruction algorithms in terms of physical figures of merit used in quantitative imaging

PurposeResolution modeling (RM) of PET systems has been introduced in iterative reconstruction algorithms for oncologic PET. The RM recovers the loss of resolution and reduces the associated partial volume effect. While these methods improved the observer performance, particularly in the detection of small and faint lesions, their impact on quantification accuracy still requires thorough investigation. The aim of this study was to characterize the performances of the RM algorithms under controlled conditions simulating a typical ¹⁸F-FDG oncologic study, using an anthropomorphic phantom and selected physical figures of merit, used for image quantification.MethodsMeasurements were performed on Biograph HiREZ (B_HiREZ) and Discovery 710 (D_710) PET/CT scanners and reconstructions were performed using the standard iterative reconstructions and the RM algorithms associated to each scanner: TrueX and SharpIR, respectively.ResultsRM determined a significant improvement in contrast recovery for small targets (≤17 mm diameter) only for the D_710 scanner. The maximum standardized uptake value (SUV_max) increased when RM was applied using both scanners. The SUV_max of small targets was on average lower with the B_HiREZ than with the D_710. Sharp IR improved the accuracy of SUV_max determination, whilst TrueX showed an overestimation of SUV_max for sphere dimensions greater than 22 mm. The goodness of fit of adaptive threshold algorithms worsened significantly when RM algorithms were employed for both scanners.ConclusionsDifferences in general quantitative performance were observed for the PET scanners analyzed. Segmentation of PET images using adaptive threshold algorithms should not be undertaken in conjunction with RM reconstructions.     

CT dose reduction using Automatic Exposure Control and iterative reconstruction: A chest paediatric phantoms study

PurposeTo evaluate the impact of Automatic Exposure Control (AEC) on radiation dose and image quality in paediatric chest scans (MDCT), with or without iterative reconstruction (IR).MethodsThree anthropomorphic phantoms representing children aged one, five and 10-year-old were explored using AEC system (CARE Dose 4D) with five modulation strength options. For each phantom, six acquisitions were carried out: one with fixed mAs (without AEC) and five each with different modulation strength. Raw data were reconstructed with Filtered Back Projection (FBP) and with two distinct levels of IR using soft and strong kernels. Dose reduction and image quality indices (Noise, SNR, CNR) were measured in lung and soft tissues. Noise Power Spectrum (NPS) was evaluated with a Catphan 600 phantom.ResultsThe use of AEC produced a significant dose reduction (p < 0.01) for all anthropomorphic sizes employed. According to the modulation strength applied, dose delivered was reduced from 43% to 91%. This pattern led to significantly increased noise (p < 0.01) and reduced SNR and CNR (p < 0.01). However, IR was able to improve these indices. The use of AEC/IR preserved image quality indices with a lower dose delivered. Doses were reduced from 39% to 58% for the one-year-old phantom, from 46% to 63% for the five-year-old phantom, and from 58% to 74% for the 10-year-old phantom. In addition, AEC/IR changed the patterns of NPS curves in amplitude and in spatial frequency.ConclusionsIn chest paediatric MDCT, the use of AEC with IR allows one to obtain a significant dose reduction while maintaining constant image quality indices.     

Correcting observer effect bias in estimates of nesting success of a coastal bird,the White-fronted Plover Charadrius marginatus

Capsule A recently developed observer-effects model gives better estimates than the survival model.

Aims To compare the performance of the traditional survival model with that of an observer-effects model in estimating nesting success.

Methods We used survival data from 654 nests in a covariate-dependent extension of a maximum-likelihood estimator model to simultaneously estimate daily survival rate and observer effect on nesting success in four different sectors of a study site. Standard likelihood-ratio tests and Akaike's information criterion differences were used to compare model performances.

Results A significant (negative) observer effect was detected in one of four sectors of the study area, and was probably attributable to small mammal predators. Despite significantly higher predation risk during the laying period, there was a significant positive observer effect during the laying period, contrasting with a weak negative effect during the incubation period, suggesting that an observer's tracks around unattended nests reduced predation risk. Likelihood-ratio tests indicated a significantly better fit using the observer effects model versus the Mayfield survival model in four of six scenarios.

Conclusion The observer-effects model accounts for bias in estimates of nest survival rates, and is preferred over the survival model because the inclusion of observer effect as a variable does not over-parameterize the model.     

Survey of chest radiography systems: Any link between contrast detail measurements and visual grading analysis?

PurposeTo evaluate image quality of chest radiography for a number of systems in Belgium, using a contrast-detail (c-d) test object and Visual Grading Analysis (VGA) of an anthropomorphic phantom.MethodsThe study comprised 22 chest imaging systems in Belgium. C-d data were measured using Leeds TO20 test object, imaged using poly(methyl methacrylate) (PMMA) thicknesses of 9, 13 and 16 cm. Images of the Lungman phantom, with additional tissue-equivalent chest plates to represent different patient sizes, were then acquired. Perceived image quality was evaluated using VGA by three radiologists. Images were acquired at a patient equivalent position with system-specific exposure settings for Posterior-Anterior chest protocol. Incident air kerma (IAK) was measured using a solid-state dosemeter.ResultsC-d results showed large differences between the systems. Total number of visible discs ranged from 38 to 83 (for 9 cm PMMA) with a consistent average drop of 10% as PMMA thickness was systematically increased. However, no correlation was found between number of visible discs and IAK. Perceived image quality scored by the readers from the Lungman images decreased with increasing phantom thickness, however no correlation of VGA score with IAK was seen. Moderate correlation was found between the VGA score of one of the readers and the TO20 results, and no correlation for the rest.ConclusionsThe spread in dose and image quality measures was high and no correlation was seen between either image quality measure and IAK, suggesting the need for optimization. A more powerful tool is required for task-based optimization in chest radiography.     

Bone SPECT image reconstruction using deconvolution and wavelet transformation: Development,performance assessment and comparison in phantom and patient study with standard OSEM and resolution recovery algorithm

PurposeThe aim of this work was to introduce a new algorithm for image reconstruction in bone SPECT and to compare its performances with a commercially available standard OSEM and resolution recovery (RR) reconstruction.Materials and methodsThe algorithm was built applying the Lucy-Richardson deconvolution adn logarithmic image processing to the projections. A modification of the coefficients of wavelet decomposition was used to suppress the noise. The comparison with vendor software was performed both in a phantom study, using Signal-to-Noise ratio (SNR), Signal-to-Background ratio (SBR), spatial resolution and in clinical studies, by visual assessment of changes in contrast, spatial resolution and lesion detectability.ResultsA change in the SNR (from −4 to 40%), an increase in the SBR (from 19 to 40%), a minor improvement in spatial resolution and a similar noise level were observed in the phantom study in comparison to the standard OSEM. A decrease in the SNR, a worse spatial resolution, but only a 3 to 13 % lower SBR were achieved in comparison with the vendor supplied RR algorithm. The proposed algorithm creates patient images with better contrast and lesion detectability compared to clinically used OSEM. Compared to RR, more than half of obtained images showed better contrast and nearly half of them have better lesion detectability.ConclusionThe proposed algorithm compares favorably with the standard OSEM. Although less favorable, the comparison with RR and noise suppression algorithms, suggests that it can be used with only a slight decrease in the SBR.     

Reduction of Metal Artifact in Single Photon-Counting Computed Tomography by Spectral-Driven Iterative Reconstruction Technique

PurposeThe exciting prospect of Spectral CT (SCT) using photon-counting detectors (PCD) will lead to new techniques in computed tomography (CT) that take advantage of the additional spectral information provided. We introduce a method to reduce metal artifact in X-ray tomography by incorporating knowledge obtained from SCT into a statistical iterative reconstruction scheme. We call our method Spectral-driven Iterative Reconstruction (SPIR).MethodThe proposed algorithm consists of two main components: material decomposition and penalized maximum likelihood iterative reconstruction. In this study, the spectral data acquisitions with an energy-resolving PCD were simulated using a Monte-Carlo simulator based on EGSnrc C++ class library. A jaw phantom with a dental implant made of gold was used as an object in this study. A total of three dental implant shapes were simulated separately to test the influence of prior knowledge on the overall performance of the algorithm. The generated projection data was first decomposed into three basis functions: photoelectric absorption, Compton scattering and attenuation of gold. A pseudo-monochromatic sinogram was calculated and used as input in the reconstruction, while the spatial information of the gold implant was used as a prior. The results from the algorithm were assessed and benchmarked with state-of-the-art reconstruction methods.ResultsDecomposition results illustrate that gold implant of any shape can be distinguished from other components of the phantom. Additionally, the result from the penalized maximum likelihood iterative reconstruction shows that artifacts are significantly reduced in SPIR reconstructed slices in comparison to other known techniques, while at the same time details around the implant are preserved. Quantitatively, the SPIR algorithm best reflects the true attenuation value in comparison to other algorithms.ConclusionIt is demonstrated that the combination of the additional information from Spectral CT and statistical reconstruction can significantly improve image quality, especially streaking artifacts caused by the presence of materials with high atomic numbers.     

X-Ray Induced Formation of γ-H2AX Foci after Full-Field Digital Mammography and Digital Breast-Tomosynthesis

Purpose

To determine in-vivo formation of x-ray induced γ-H2AX foci in systemic blood lymphocytes of patients undergoing full-field digital mammography (FFDM) and to estimate foci after FFDM and digital breast-tomosynthesis (DBT) using a biological phantom model.

Materials and Methods

The study complies with the Declaration of Helsinki and was performed following approval by the ethic committee of the University of Erlangen-Nuremberg. Written informed consent was obtained from every patient. For in-vivo tests, systemic blood lymphocytes were obtained from 20 patients before and after FFDM. In order to compare in-vivo post-exposure with pre-exposure foci levels, the Wilcoxon matched pairs test was used. For in-vitro experiments, isolated blood lymphocytes from healthy volunteers were irradiated at skin and glandular level of a porcine breast using FFDM and DBT. Cells were stained against the phosphorylated histone variant γ-H2AX, and foci representing distinct DNA damages were quantified.

Results

Median in-vivo foci level/cell was 0.086 (range 0.067–0.116) before and 0.094 (0.076–0.126) after FFDM (p = 0.0004). In the in-vitro model, the median x-ray induced foci level/cell after FFDM was 0.120 (range 0.086–0.140) at skin level and 0.035 (range 0.030–0.050) at glandular level. After DBT, the median x-ray induced foci level/cell was 0.061 (range 0.040–0.081) at skin level and 0.015 (range 0.006–0.020) at glandular level.

Conclusion

In patients, mammography induces a slight but significant increase of γ-H2AX foci in systemic blood lymphocytes. The introduced biological phantom model is suitable for the estimation of x-ray induced DNA damages in breast tissue in different breast imaging techniques.     

Phantom study quantifying the depth performance of a handheld magnetometer for sentinel lymph node biopsy

PurposeThe use of a magnetic nanoparticle tracer and handheld magnetometer for sentinel lymph node biopsy (SLNB) was recently introduced to overcome drawbacks associated with the use of radioisotope tracers. Unlike the gamma probe, the used magnetometers are not only sensitive to the tracer, but also the diamagnetic human body. This potentially limits the performance of the magnetometer when used clinically.MethodsA phantom, mimicking the magnetic and mechanical properties of the human axilla, was constructed. The depth performance of two current generation magnetometers was evaluated in this phantom. LN-phantoms with tracer uptake ranging from 5 to 500 μg iron were placed at clinically relevant depths of 2.5, 4 and 5.5 cm. Distance-response curves were obtained to quantify the depth performance of the probes.ResultsThe depth performance of both probes was limited. In the absence of diamagnetic material and forces on the probe (ideal conditions) a LN-phantom with high uptake (500 μg iron) could first be detected at 3.75 cm distance. In the phantom, only superficially placed LNs (2.5 cm) with high uptake (500 μg iron) could be detected from the surface. The penetration depth was insufficient to detect LNs with lower uptake, or which were located deeper.ConclusionThe detection distance of the current generation magnetometers is limited, and does not meet the demands formulated by the European Association for Nuclear Medicine for successful transcutaneous SLN localization. Future clinical trials should evaluate whether the limited depth sensitivity is of influence to the clinical outcome of the SLNB procedure.     

Combination system in advanced image processing for improving image contrast and a conventional row-ratio grid for an indirect flat-panel detector system: An experimental study

Conventional grids with high grid ratios are not ideal for use in bedside radiography because of the difficulty in maintaining the required alignment. To address this issue, the potential usefulness of a combination system that employs removal processing software for scattered radiation and a conventional grid with a low grid ratio (3:1) for an indirect-conversion-type flat-panel detector system was evaluated by measuring image quality and observer performance. The hypothetical grid ratios for the software were 2:1, 3:1, 6:1, 8:1, and 10:1. The scatter fraction of the combination system was lower than that of the software alone. Significant improvement was observed in the effect of scattered radiation removal up to a hypothetical software grid ratio of 6:1. However, the Wiener spectrum increased (radiographic noise degraded) with an increase in the hypothetical grid ratio. The contrast ratios of the combination system were improved compared to those of the software alone for anthropomorphic chest radiographs. An observer test was also conducted using the contrast-detail phantom. The combination system indicated higher low-contrast detectability compared to the software alone, although there were no statistical differences between the hypothetical grid ratios of 6:1, 8:1, and 10:1 in all combinations of the software alone and the combination system. We concluded that a combination system with software that uses a hypothetical grid ratio of 6:1 or more and a 3:1 conventional grid would be more useful for reducing the scattered radiation component compared to the software alone with a hypothetical higher grid ratio for thicker objects.     

An iterative deconvolution algorithm for image recovery in clinical CT: A phantom study

PurposeTo study the feasibility of using an iterative reconstruction algorithm to improve previously reconstructed CT images which are judged to be non-diagnostic on clinical review. A novel rapidly converging, iterative algorithm (RSEMD) to reduce noise as compared with standard filtered back-projection algorithm has been developed.Materials and methodsThe RSEMD method was tested on in-silico, Catphan^®500, and anthropomorphic 4D XCAT phantoms. The method was applied to noisy CT images previously reconstructed with FBP to determine improvements in SNR and CNR. To test the potential improvement in clinically relevant CT images, 4D XCAT phantom images were used to simulate a small, low contrast lesion placed in the liver.ResultsIn all of the phantom studies the images proved to have higher resolution and lower noise as compared with images reconstructed by conventional FBP. In general, the values of SNR and CNR reached a plateau at around 20 iterations with an improvement factor of about 1.5 for in noisy CT images. Improvements in lesion conspicuity after the application of RSEMD have also been demonstrated. The results obtained with the RSEMD method are in agreement with other iterative algorithms employed either in image space or with hybrid reconstruction algorithms.ConclusionsIn this proof of concept work, a rapidly converging, iterative deconvolution algorithm with a novel resolution subsets-based approach that operates on DICOM CT images has been demonstrated. The RSEMD method can be applied to sub-optimal routine-dose clinical CT images to improve image quality to potentially diagnostically acceptable levels.     

Objective assessment of low-contrast computed tomography images with iterative reconstruction

ObjectiveThis study aims to assess low-contrast image quality using a low-contrast object specific contrast-to-noise ratio (CNR_LO) analysis for iterative reconstruction (IR) computed tomography (CT) images.MethodsA phantom composed of low-contrast rods placed in a uniform material was used in this study. Images were reconstructed using filtered back projection (FBP) and IR (Adaptive Iterative Dose Reduction 3D). Scans were performed at six dose levels: 1.0, 1.8, 3.1, 4.6, 7.1 and 13.3 mGy. Objective image quality was assessed by comparing CNR_LO with CNR using a human observer test.ResultsCompared with FBP, IR yielded increased CNR at the same dose levels. The results of CNR_LO and observer tests showed similarities or only marginal differences between FBP and IR at the same dose levels. The coefficient of determination for CNR_LO was significantly better (R² = 0.86) than that of CNR (R² = 0.47).ConclusionFor IR, CNR_LO could potentially serve as an objective index reflective of a human observer assessment. The results of CNR_LO test indicated that the IR algorithm was not superior to FBP in terms of low-contrast detectability at the same radiation doses.     

Image quality for radiotherapy CT simulators with different scanner bore size

PurposeWe compare image quality parameters derived from phantom images taken on three commercially available radiotherapy CT simulators. To make an unbiased evaluation, we assured images were obtained with the same surface dose measured using XR-QA2 model GafChromic™ film placed at the imaging phantom surface for all three CT-simulators.MethodsRadiotherapy CT simulators GE LS 16, Philips Brilliance Big Bore, and Toshiba Aquilion LB were compared in terms of spatial resolution, low contrast detectability, image uniformity, and contrast to noise ratio using CATPHAN-504 phantom, scanned with Head and Pelvis protocols. Dose was measured at phantom surface, with CT scans repeated until doses on all scanners were within 2%.ResultsIn terms of spatial resolution, the GE simulator appears slightly better, while Philips CT images are superior in terms of SNR for both scanning protocols. The CNR results show that Philips CT images appear to be better, except for high Z material, while Toshiba appears to fit in between the two simulators.ConclusionsWhile the image quality parameters for three RT CT simulators show comparable results, the scanner bore size is of vital importance in various radiotherapy applications. Since the image quality is a function of a large number of confounding parameters, any loss in image quality due to scanner bore size could be compensated by the appropriate choice of scanning parameters, including the exposure and by balancing between the additional imaging dose to the patient and high image quality required in highly conformal RT techniques.