Filtered Back Projection Images Research Articles

Three-dimensional cascaded system analysis of a 50 µm pixel pitch wafer-scale CMOS active pixel sensor x-ray detector for digital breast tomosynthesis

High-resolution, low-noise x-ray detectors based on the complementary metal-oxide-semiconductor (CMOS) active pixel sensor (APS) technology have been developed and proposed for digital breast tomosynthesis (DBT). In this study, we evaluated the three-dimensional (3D) imaging performance of a 50 µm pixel pitch CMOS APS x-ray detector named DynAMITe (Dynamic Range Adjustable for Medical Imaging Technology). The two-dimensional (2D) angle-dependent modulation transfer function (MTF), normalized noise power spectrum (NNPS), and detective quantum efficiency (DQE) were experimentally characterized and modeled using the cascaded system analysis at oblique incident angles up to 30°. The cascaded system model was extended to the 3D spatial frequency space in combination with the filtered back-projection (FBP) reconstruction method to calculate the 3D and in-plane MTF, NNPS and DQE parameters. The results demonstrate that the beam obliquity blurs the 2D MTF and DQE in the high spatial frequency range. However, this effect can be eliminated after FBP image reconstruction. In addition, impacts of the image acquisition geometry and detector parameters were evaluated using the 3D cascaded system analysis for DBT. The result shows that a wider projection angle range (e.g. ±30°) improves the low spatial frequency (below 5 mm−1) performance of the CMOS APS detector. In addition, to maintain a high spatial resolution for DBT, a focal spot size of smaller than 0.3 mm should be used. Theoretical analysis suggests that a pixelated scintillator in combination with the 50 µm pixel pitch CMOS APS detector could further improve the 3D image resolution. Finally, the 3D imaging performance of the CMOS APS and an indirect amorphous silicon (a-Si:H) thin-film transistor (TFT) passive pixel sensor (PPS) detector was simulated and compared.

Object shape dependency of in-plane resolution for iterative reconstruction of computed tomography

The present study aimed to investigate whether the in-plane resolution property of iterative reconstruction (IR) of computed tomography (CT) data is object shape-dependent by testing columnar shapes with diameters of 3, 7, and 10cm (circular edge method) and a cubic shape with 5-cm side lengths (linear edge method). For each shape, objects were constructed of acrylic (contrast in Hounsfield units [ΔHU]=120) as well as a soft tissue equivalent material (ΔHU=50). For each shape, we measured the modulation transfer functions (MTFs) of IR and filtered back projection (FBP) using two multi-slice CT scanners at scan doses of 5 and 10mGy. In addition, we evaluated a thin metal wire using the conventional method at 10mGy. For FBP images, the MTF results of the tested objects and the wire method showed substantial agreement, thus demonstrating the validity of our analysis technique. For IR images, the MTF results of different shapes were nearly identical for each object contrast and dose combination, and we did not observe shape-dependent effects of the resolution properties of either tested IR. We conclude that both the circular edge method and linear edge method are equally useful for evaluating the resolution properties of IRs.

Introduction of Total Variation Regularization into Filtered Backprojection Algorithm

In this paper we extend the state-of-the-art filtered backprojection (FBP) method with application of the concept of Total Variation regularization. We compare the performance of the new algorithm with the most common form of regularizing in the FBP image reconstruction via apodizing functions. The methods are validated in terms of cross-correlation coefficient between reconstructed and real image of radioactive tracer distribution using standard Derenzo-type phantom. We demonstrate that the proposed approach results in higher cross-correlation values with respect to the standard FBP method.

Impact of hybrid iterative reconstruction on unenhanced liver CT.

To clarify the impact of hybrid iterative reconstruction (HIR) and filtered back projection (FBP) on unenhanced liver CT. 30 patients with hepatocellular carcinoma (HCC) underwent unenhanced CT. The images were reconstructed with FBP and weak (Level 1), mild (Level 4) and strong (Level 7) levels of HIR (iDose4; Philips Medical Systems, Cleveland, OH). Quantitatively, attenuations of the HCC (with the largest lesion in each case), hepatic parenchyma (the average of four segments) and image noise (standard deviation of the attenuations in hepatic parenchyma) were compared between the four kinds of reconstruction using the two-tailed paired t-test. Qualitatively, liver lesion conspicuity and characterization were also compared using the Wilcoxon signed-rank test. Attenuation of the liver lesion with the strong level of HIR was significantly higher than that with FBP (p = 0.0005). Attenuations of hepatic parenchyma with all three HIR levels were significantly lower than that with FBP (p ≤ 0.0002 in all comparisons). Image noise with each of the three HIR levels was significantly smaller than that with FBP (p < 0.0001 in any comparison). There was no significant difference in lesion conspicuity and characterization between FBP and each HIR level (p ≥ 0.0819 in all comparisons). Although attenuations of the liver lesion and hepatic parenchyma were significantly different between HIR and FBP, HIR had no significant effect on lesion conspicuity and characterization. Advances in knowledge: Attenuations of liver lesions and hepatic parenchyma differ significantly between HIR and FBP images.

Diagnostic performance of reduced-dose CT with a hybrid iterative reconstruction algorithm for the detection of hypervascular liver lesions: a phantom study.

To investigate the diagnostic performance of reduced-dose CT with a hybrid iterative reconstruction (IR) algorithm for the detection of hypervascular liver lesions. Thirty liver phantoms with or without simulated hypervascular lesions were scanned with a 320-slice CT scanner with control-dose (40 mAs) and reduced-dose (30 and 20 mAs) settings. Control-dose images were reconstructed with filtered back projection (FBP), and reduced-dose images were reconstructed with FBP and a hybrid IR algorithm. Objective image noise and the lesion to liver contrast-to-noise ratio (CNR) were evaluated quantitatively. Images were interpreted independently by 2 blinded radiologists, and jackknife alternative free-response receiver-operating characteristic (JAFROC) analysis was performed. Hybrid IR images with reduced-dose settings (both 30 and 20 mAs) yielded significantly lower objective image noise and higher CNR than control-dose FBP images (P < .05). However, hybrid IR images with reduced-dose settings had lower JAFROC1 figure of merit than control-dose FBP images, although only the difference between 20 mAs images and control-dose FBP images was significant for both readers (P < .01). An aggressive reduction of the radiation dose would impair the detectability of hypervascular liver lesions, although objective image noise and CNR would be preserved by a hybrid IR algorithm. • A half-dose scan with a hybrid iterative reconstruction preserves objective image quality. • A hybrid iterative reconstruction algorithm does not improve diagnostic performance. • An aggressive dose reduction would impair the detectability of low-contrast lesions.

Radiation dose reduction based on CNR index with low-tube voltage scan for pediatric CT scan: experimental study using anthropomorphic phantoms.

BackgroundTo figure out the relationship between image noise and contrast noise ratio (CNR) at different tube voltages, using anthropomorphic new-born and 1-year-old phantoms, and to discuss the feasibility of radiation dose reduction, based on the obtained CNR index from image noise. We performed helical scans of the anthropomorphic new-born and 1-year-old phantoms. The CT numbers of the simulated aorta and image noise of the simulated mediastinum were measured; then CNR was calculated on 80, 100, and 120-kVp images reconstructed with filtered back projection (FBP) and iterative reconstruction (IR). We also measured the center and surface dose in the case of CNR of 14 using radio-photoluminescence glass dosimeters.ResultsThe CT number of the simulated aorta was increased with decreasing tube voltage from 120 to 80 kVp (362.5–535.1 HU for the new-born, 358.9–532.6 HU for the 1-year-old). At CNR of 14, the center dose was 0.4, 0.6 and 0.9 mGy at FBP and 0.5, 0.6 and 0.9 mGy at IR and with the new-born phantom acquired at 80, 100 and 120 kVp, respectively. The center dose for FBP image was reduced by 56% at 80 kVp, 34% at 100 kVp for the new-born and 36% at 80 kVp, 22% at 100 kVp for the 1-year-old compared with that at 120 kVp. We obtained a relationship between image noise and CNR at different tube voltages using the anthropomorphic new-born and 1-year-old phantoms.ConclusionThe use of index of CNR with low-tube voltage may achieve further radiation dose reduction in pediatric CT examination.

The Influence of Iterative Reconstruction on Coronary Artery Calcium Scoring—Phantom and Clinical Studies

We compared the effect of iterative model reconstruction (IMR), filtered back projection (FBP), and hybrid iterative reconstruction (HIR) on coronary artery calcium (CAC) scoring. CAC scans of 30 consecutive patients (18 men and 12 women, age 70.1 ± 12.2 years) were reconstructed with FBP, HIR, and IMR, and the image noise was measured on all images. Two radiologists independently measured the CAC scores using semiautomated software, and interobserver agreement was evaluated. Statistical analysis included the Spearman correlation coefficient and Bland-Altman analysis. The mean image noise on FBP, HIR, and IMR images was 48.0 ± 7.9, 29.6 ± 4.8, and 9.3 ± 1.3 Hounsfield units, respectively. The difference among all reconstruction combinations was significant (P < .01). The CAC score on HIR and IMR scans was 4.2% and 8.9% lower, respectively, than the CAC score on FBP images. There was no significant difference in the mean CAC score among the three reconstructions. The interobserver correlation was excellent for all three reconstructions (r2 = 0.96 FBP, 0.99 HIR, 0.99 IMR); the best Bland-Altman measure of agreement was with IMR, followed by HIR and FBP. For CAC scoring, IMR can reduce the image noise and blooming artifacts, and consequently lowers the measured CAC score. IMR can lessen measurement variability and yield stable, reproducible measurements.

The Population Effective Dose of Medical Computed Tomography Examinations in Taiwan for 2013.

PurposeTo evaluate the annual effective dose per capita attributed to computed tomography (CT) examinations in 2013 and to predict the population effective dose from 2000 to 2013 in Taiwan.MethodsA CT examination database collected from 30 hospitals was divided into 22 procedures and classified into six regions: head, neck, chest, abdomen, pelvis, and other, respectively. The effective doses in different regions were evaluated by dose-length product (DLP) multiplied by conversion factors.ResultsThe CT scan dose parameters were collected from 4,407 patients. For the six scanned regions, the percentages of patients scanned were: head (39.8%), neck (3.9%), chest (23.3%), abdomen (26.7%), pelvis (4.8%), and other (1.6%), respectively. The DLPs per patient (mGy·cm/patient) were head (1,071±225), neck (1,103±615), chest (724±509), abdomen (1,315±550), pelvis (1,231±620) and other (1,407±937), respectively. The number of CT examinations increased rapidly, with an average annual growth rate of 7.6%. The number of CT examinations in 2013 was 2.6 times that in 2000. The population effective dose was 0.30 mSv per capita in 2000 and increased to 0.74 mSv per capita in 2013, with an annual growth rate of 7.2%. The growth trend indicates that the effective dose will continue to rise in Taiwan.ConclusionSome strategies should be applied to cope with this growth. Defining the CT dose reference level stipulated in official recommendations and encouraging the use of iterative reconstruction imaging instead of filtered back-projection imaging could be a useful method for optimizing the effective dose and image quality.

Submillisievert Radiation Dose Coronary CT Angiography: Clinical Impact of the Knowledge-Based Iterative Model Reconstruction

The purpose of this study was to evaluate the noise and image quality of images reconstructed with a knowledge-based iterative model reconstruction (knowledge-based IMR) in ultra-low dose cardiac computed tomography (CT). We performed submillisievert radiation dose coronary CT angiography on 43 patients. We also performed a phantom study to evaluate the influence of object size with the automatic exposure control phantom. We reconstructed clinical and phantom studies with filtered back projection (FBP), hybrid iterative reconstruction (hybrid IR), and knowledge-based IMR. We measured effective dose of patients and compared CT number, image noise, and contrast noise ratio in ascending aorta of each reconstruction technique. We compared the relationship between image noise and body mass index for the clinical study, and object size for phantom study. The mean effective dose was 0.98 ± 0.25 mSv. The image noise of knowledge-based IMR images was significantly lower than those of FBP and hybrid IR images (knowledge-based IMR: 19.4 ± 2.8; FBP: 126.7 ± 35.0; hybrid IR: 48.8 ± 12.8, respectively) (P < .01). The contrast noise ratio of knowledge-based IMR images was significantly higher than those of FBP and hybrid IR images (knowledge-based IMR: 29.1 ± 5.4; FBP: 4.6 ± 1.3; hybrid IR: 13.1 ± 3.5, respectively) (P < .01). There were moderate correlations between image noise and body mass index in FBP (r = 0.57, P < .01) and hybrid IR techniques (r = 0.42, P < .01); however, these correlations were weak in knowledge-based IMR (r = 0.27, P < .01). Compared to FBP and hybrid IR, the knowledge-based IMR offers significant noise reduction and improvement in image quality in submillisievert radiation dose cardiac CT.

Optimization of hybrid iterative reconstruction level and evaluation of image quality and radiation dose for pediatric cardiac computed tomography angiography.

Hybrid iterative reconstruction can reduce image noise and produce better image quality compared with filtered back-projection (FBP), but few reports describe optimization of the iteration level. We optimized the iteration level of iDose4 and evaluated image quality for pediatric cardiac CT angiography. Children (n = 160) with congenital heart disease were enrolled and divided into full-dose (n = 84) and half-dose (n = 76) groups. Four series were reconstructed using FBP, and iDose4 levels 2, 4 and 6; we evaluated subjective quality of the series using a 5-grade scale and compared the series using a Kruskal-Wallis H test. For FBP and iDose4-optimal images, we compared contrast-to-noise ratios (CNR) and size-specific dose estimates (SSDE) using a Student's t-test. We also compared diagnostic-accuracy of each group using a Kruskal-Wallis H test. Mean scores for iDose4 level 4 were the best in both dose groups (all P < 0.05). CNR was improved in both groups with iDose4 level 4 as compared with FBP. Mean decrease in SSDE was 53% in the half-dose group. Diagnostic accuracy for the four datasets were in the range 92.6-96.2% (no statistical difference). iDose4 level 4 was optimal for both the full- and half-dose groups. Protocols with iDose4 level 4 allowed 53% reduction in SSDE without significantly affecting image quality and diagnostic accuracy.

Dual energy CT with one full scan and a second sparse-view scan using structure preserving iterative reconstruction (SPIR)

Conventional dual-energy CT (DECT) reconstruction requires two full-size projection datasets with two different energy spectra. In this study, we propose an iterative algorithm to enable a new data acquisition scheme which requires one full scan and a second sparse-view scan for potential reduction in imaging dose and engineering cost of DECT. A bilateral filter is calculated as a similarity matrix from the first full-scan CT image to quantify the similarity between any two pixels, which is assumed unchanged on a second CT image since DECT scans are performed on the same object. The second CT image from reduced projections is reconstructed by an iterative algorithm which updates the image by minimizing the total variation of the difference between the image and its filtered image by the similarity matrix under data fidelity constraint. As the redundant structural information of the two CT images is contained in the similarity matrix for CT reconstruction, we refer to the algorithm as structure preserving iterative reconstruction (SPIR). The proposed method is evaluated on both digital and physical phantoms, and is compared with the filtered-backprojection (FBP) method, the conventional total-variation-regularization-based algorithm (TVR) and prior-image-constrained-compressed-sensing (PICCS). SPIR with a second 10-view scan reduces the image noise STD by a factor of one order of magnitude with same spatial resolution as full-view FBP image. SPIR substantially improves over TVR on the reconstruction accuracy of a 10-view scan by decreasing the reconstruction error from 6.18% to 1.33%, and outperforms TVR at 50 and 20-view scans on spatial resolution with a higher frequency at the modulation transfer function value of 10% by an average factor of 4. Compared with the 20-view scan PICCS result, the SPIR image has 7 times lower noise STD with similar spatial resolution. The electron density map obtained from the SPIR-based DECT images with a second 10-view scan has an average error of less than 1%.

Dose reduction potential of iterative reconstruction algorithms in neck CTA-a simulation study.

This study aimed to determine the degree of radiation dose reduction in neck CT angiography (CTA) achievable with Sinogram-affirmed iterative reconstruction (SAFIRE) algorithms. 10 consecutive patients scheduled for neck CTA were included in this study. CTA images of the external carotid arteries either were reconstructed with filtered back projection (FBP) at full radiation dose level or underwent simulated dose reduction by proprietary reconstruction software. The dose-reduced images were reconstructed using either SAFIRE 3 or SAFIRE 5 and compared with full-dose FBP images in terms of vessel definition. 5 observers performed a total of 3000 pairwise comparisons. SAFIRE allowed substantial radiation dose reductions in neck CTA while maintaining vessel definition. The possible levels of radiation dose reduction ranged from approximately 34 to approximately 90% and depended on the SAFIRE algorithm strength and the size of the vessel of interest. In general, larger vessels permitted higher degrees of radiation dose reduction, especially with higher SAFIRE strength levels. With small vessels, the superiority of SAFIRE 5 over SAFIRE 3 was lost. Neck CTA can be performed with substantially less radiation dose when SAFIRE is applied. The exact degree of radiation dose reduction should be adapted to the clinical question, in particular to the smallest vessel needing excellent definition.

Effect of Low-Dose MDCT and Iterative Reconstruction on Trabecular Bone Microstructure Assessment.

We investigated the effects of low-dose multi detector computed tomography (MDCT) in combination with statistical iterative reconstruction algorithms on trabecular bone microstructure parameters. Twelve donated vertebrae were scanned with the routine radiation exposure used in our department (standard-dose) and a low-dose protocol. Reconstructions were performed with filtered backprojection (FBP) and maximum-likelihood based statistical iterative reconstruction (SIR). Trabecular bone microstructure parameters were assessed and statistically compared for each reconstruction. Moreover, fracture loads of the vertebrae were biomechanically determined and correlated to the assessed microstructure parameters. Trabecular bone microstructure parameters based on low-dose MDCT and SIR significantly correlated with vertebral bone strength. There was no significant difference between microstructure parameters calculated on low-dose SIR and standard-dose FBP images. However, the results revealed a strong dependency on the regularization strength applied during SIR. It was observed that stronger regularization might corrupt the microstructure analysis, because the trabecular structure is a very small detail that might get lost during the regularization process. As a consequence, the introduction of SIR for trabecular bone microstructure analysis requires a specific optimization of the regularization parameters. Moreover, in comparison to other approaches, superior noise-resolution trade-offs can be found with the proposed methods.

Noise Reduction in Abdominal Computed Tomography Applying Iterative Reconstruction (ADMIRE)

The study aimed to compare image quality of filtered back projection (FBP) and iterative reconstruction (advanced modeled iterative reconstruction, ADMIRE) in contrast-enhanced computed tomography (CT) of the abdomen, and to assess the differences of reconstructions according to these methods. It also aimed to investigate the potential for noise reduction of ADMIRE for different reconstructed slice thicknesses. CT data of the abdomen and pelvis were acquired using a 128-slice single-source CT system using automated kV selection and tube current adaption based on patients' anatomy. Raw data sets from patients scanned at 100 kV were selected, and images were reconstructed with slice thicknesses of 1 mm, 3 mm, and 5 mm, both with FBP and ADMIRE. Filter strength F1, F3, and F5 of the ADMIRE algorithm and the corresponding reconstruction kernels were used. In total, 58 raw data sets from 17 patients were used to reconstruct from the same raw data FBP and ADMIRE images, representing identical body regions. Identical regions of interest were placed at the same position of up to four images and image noise was measured. Differences of reconstructed images and detail preservation were tested using an image subtraction technique, and subjective image quality was assessed using a 5-point Likert scale. On average, for 1-mm slice thickness, noise reduction was 9.15% ± 2.4% with filter strength level F1, 30.2% ± 3.4% with F3, and 54.4% ± 7.0% with F5 as compared to FBP. For a slice thickness of 3 mm, noise reduction was 8.5% ± 3.7% with F1, 28.6% ± 3.9% with F3, and 52.2% ± 9.1% with F5. For 5 mm, the corresponding values are 8.9% ± 2.7%, 31.4% ± 2.8%, and 52.7% ± 7.7%. On subtraction images, edge information of tissue classes with a high attenuation gradient was found, but structures with small differences in attenuation were not detectable on subtraction images, confirming that no relevant details were lost in the iterative reconstruction process. ADMIRE is able to reduce image noise considerably (up to 50%) without any obvious negative impact on lesion depiction as assessed visually. Noise reduction of ADMIRE seems to be independent of slice thickness.

Low contrast detectability and spatial resolution with model-based Iterative reconstructions of MDCT images: a phantom and cadaveric study.

To compare image quality [low contrast (LC) detectability, noise, contrast-to-noise (CNR) and spatial resolution (SR)] of MDCT images reconstructed with an iterative reconstruction (IR) algorithm and a filtered back projection (FBP) algorithm. The experimental study was performed on a 256-slice MDCT. LC detectability, noise, CNR and SR were measured on a Catphan phantom scanned with decreasing doses (48.8 down to 0.7mGy) and parameters typical of a chest CT examination. Images were reconstructed with FBP and a model-based IR algorithm. Additionally, human chest cadavers were scanned and reconstructed using the same technical parameters. Images were analyzed to illustrate the phantom results. LC detectability and noise were statistically significantly different between the techniques, supporting model-based IR algorithm (p < 0.0001). At low doses, the noise in FBP images only enabled SR measurements of high contrast objects. The superior CNR of model-based IR algorithm enabled lower dose measurements, which showed that SR was dose and contrast dependent. Cadaver images reconstructed with model-based IR illustrated that visibility and delineation of anatomical structure edges could be deteriorated at low doses. Model-based IR improved LC detectability and enabled dose reduction. At low dose, SR became dose and contrast dependent. • Model- based Iterative Reconstruction improves detectability of low contrast object. • With model- based Iterative Reconstruction, spatial resolution is dose and contrast dependent. • Model-based Iterative Reconstruction algorithms enable improved IQ combined with dose-reduction possibilities. • Improvement of SR and LC detectability on the same IMR data set would reduce reconstructions.

SU‐G‐206‐10: Low‐Contrast Detectability Vs. Dose for CT Images Reconstructed Using Filtered Backprojection and Iterative Reconstruction: Assessment with a Model Observer

Purpose:To evaluate CT low‐contrast detectability at different dose levels in images reconstructed using filtered backprojection (FBP) and iterative reconstruction (IR).Methods:A validated channelized Hotelling observer (CHO) model was used to detect low contrast objects in images of a helical CT phantom (Model 061, CIRS) using an Aquilion Prime 160 scanner (Toshiba Medical Systems). Twenty‐one different objects of 7 diameters (2.4, 3.2, 4.6, 6.3, 9.5, and 10 mm) and 3 contrast levels (∼10, 15, and 25 HU) were evaluated. Images were acquired using 5 different tube current settings (45, 60, 90, 140, and 180 mA) and reconstructed using both FBP and IR (Adaptive Iterative Dose Reduction (AIDR) 3D). For each tube current, the phantom was scanned 100 times, yielding sets of 100 object‐present and object‐absent images at the same x‐y locations. All images were evaluated using the CHO and detectability indices (d’) for each object were calculated at all dose levels.Results:For the same tube current setting, images formed using IR yielded d’ values on average 8% higher than images reconstructed using FBP. When dose was reduced by more than 25% of the full dose, however, results showed reduced low‐contrast detectability in AIDR‐3D images compared to 100% dose, FBP images. With the vendordefault settings, dose is automatically reduced by 70‐75% when AIDR 3D reconstructions are selected, which our data indicate would significantly reduce low contrast detectability.Conclusion:At higher dose levels (minimal dose reduction), AIDR‐3D improved object detectability as compared to full‐dose FBP images. However, when dose was reduced by more than 25%, object detectability was substantially reduced for images reconstructed with AIDR‐3D compared to full‐dose FBP images.CH McCollough is supported by industry funding from Siemens Healthcare

Impact of the Adaptive Statistical Iterative Reconstruction Technique on Radiation Dose and Image Quality in Bone SPECT/CT.

The purpose of this study was to compare a routine bone SPECT/CT protocol using CT reconstructed with filtered backprojection (FBP) with an optimized protocol using low-dose CT images reconstructed with adaptive statistical iterative reconstruction (ASiR). In this prospective study, enrolled patients underwent bone SPECT/CT, with 1 SPECT acquisition followed by 2 randomized CT acquisitions: FBP CT (FBP; noise index, 25) and ASiR CT (70% ASiR; noise index, 40). The image quality of both attenuation-corrected SPECT and CT images was visually (5-point Likert scale, 2 interpreters) and quantitatively (contrast ratio [CR] and signal-to-noise ratio [SNR]) estimated. The CT dose index volume, dose-length product, and effective dose were compared. Seventy-five patients were enrolled in the study. Quantitative attenuation-corrected SPECT evaluation showed no inferiority for contrast ratio and SNR issued from FBP CT or ASiR CT (respectively, 13.41 ± 7.83 vs. 13.45 ± 7.99 and 2.33 ± 0.83 vs. 2.32 ± 0.84). Qualitative image analysis showed no difference between attenuation-corrected SPECT images issued from FBP CT or ASiR CT for both interpreters (respectively, 3.5 ± 0.6 vs. 3.5 ± 0.6 and 3.6 ± 0.5 vs. 3.6 ± 0.5). Quantitative CT evaluation showed no inferiority for SNR between FBP and ASiR CT images (respectively, 0.93 ± 0.16 and 1.07 ± 0.17). Qualitative image analysis showed no quality difference between FBP and ASiR CT images for both interpreters (respectively, 3.8 ± 0.5 vs. 3.6 ± 0.5 and 4.0 ± 0.1 vs. 4.0 ± 0.2). Mean CT dose index volume, dose-length product, and effective dose for ASiR CT (3.0 ± 2.0 mGy, 148 ± 85 mGy⋅cm, and 2.2 ± 1.3 mSv) were significantly lower than for FBP CT (8.5 ± 3.7 mGy, 365 ± 160 mGy⋅cm, and 5.5 ± 2.4 mSv). The use of 70% ASiR blending in bone SPECT/CT can reduce the CT radiation dose by 60%, with no sacrifice in attenuation-corrected SPECT and CT image quality, compared with the conventional protocol using FBP CT reconstruction technique.

A limit on dose reduction possible with CT reconstruction algorithms without prior knowledge of the scan subject.

To find an upper bound on the maximum dose reduction possible for any reconstruction algorithm, analytic or iterative, that result from the inclusion of the data statistics. The authors do not analyze noise reduction possible from prior knowledge or assumptions about the object. The authors examined the task of estimating the density of a circular lesion in a cross section. Raw data were simulated by forward projection of existing images and numerical phantoms. To assess an upper bound on the achievable dose reduction by any algorithm, the authors assume that both the background and the shape of the lesion are completely known. Under these conditions, the best possible estimate of the density can be determined by solving a weighted least squares problem directly in the raw data domain. Any possible reconstruction algorithm that does not use prior knowledge or make assumptions about the object, including filtered backprojection (FBP) or iterative reconstruction methods with this constraint, must be no better than this least squares solution. The authors simulated 10,000 sets of noisy data and compared the variance in density from the least squares solution with those from FBP. Density was estimated from FBP images using either averaging within a ROI, or streak-adaptive averaging with better noise performance. The bound on the possible dose reduction depends on the degree to which the observer can read through the possibly streaky noise. For the described low contrast detection task with the signal shape and background known exactly, the average dose reduction possible compared to FBP with streak-adaptive averaging was 42% and it was 64% if only the ROI average is used with FBP. The exact amount of dose reduction also depends on the background anatomy, with statistically inhomogeneous backgrounds showing greater benefits. The dose reductions from new, statistical reconstruction methods can be bounded. Larger dose reductions in the density estimation task studied here are only possible with the introduction of prior knowledge, which can introduce bias.

Upper-Bound on Dose Reduction in CT Reconstruction for Nodule Detection

The success of X-ray computed tomography (CT) as a widespread medical diagnosis tool has led to concerns about possible harm due to the increased average radiation dose to the population. A highly effective way to reduce CT radiation dose is to use iterative image reconstruction. All major CT vendors now offer iterative reconstruction solutions and claim that they can achieve the desired image quality at only a fraction of the dose level needed with conventional filtered backprojection (FBP) reconstruction. In this paper, we empirically estimate the upper bound on the achievable dose reduction in CT reconstruction in the context of a clinical detection task. We do this based on a series of patient lung CT data sets, with and without nodules, for a large number of random noise realizations. We analyze lesion detectability in the FBP images, in which case performance is lost due to the sub-optimal reconstruction. We compare this to lesion detectability directly in the raw data domain, where by definition, all information is still available with specific location information. This, therefore, represents the best scenario any reconstruction algorithm could achieve from raw data without additional prior information. The results indicate that a threefold dose reduction is feasible relative to FBP reconstruction: specifically, the upper bound on dose reduction was estimated at 62.5% for 90% detection accuracy and 66.2% for 80% detection accuracy. Statistical weighting is responsible for approximately half of that benefit.

A robust noise reduction technique for time resolved CT.

To develop a noise reduction method for time resolved CT data, especially those with significant patient motion. PArtial TEmporal Nonlocal (PATEN) means is a technique that uses the redundant information in time-resolved CT data to achieve noise reduction. In this method, partial temporal profiles are used to determine the similarity (or weight) between pixels, and the similarity search makes use of both spatial and temporal information, providing robustness to patient motion. The performance of the PATEN filter was qualitatively and quantitatively evaluated with nine cardiac CT patient data sets and five CT brain perfusion patient data sets. In cardiac CT, PATEN was applied to reduce noise primarily in the reduced-dose phases created with electrocardiographic (ECG) pulsing. CT number accuracy and noise reduction were evaluated in both full-dose phases and reduced-dose phases between filtered backprojection images and PATEN filtered images. In CT brain perfusion, simulated quarter dose data were obtained by adding noise to the raw data of a routine dose scan. PATEN was applied to the simulated low-dose images. Image noise, time-intensity profile accuracy, and perfusion parameter maps were compared among low-dose, low-dose+PATEN filter, and full-dose images. The noise reduction performance of PATEN was compared to a previously proposed noise reduction method, time-intensity profile similarity (TIPS) bilateral filtering. In 4D cardiac CT, after PATEN filtering, the image noise in the reduced-dose phases was greatly reduced, making anatomical structures easier to identify. The mean decreases in noise values between the original and PATEN images were 11.0% and 53.8% for the full and reduced-dose phases of the cardiac cycle, respectively. TIPS could not achieve effective noise reduction. In CT brain perfusion, PATEN achieved a 55.8%-66.3% decrease in image noise in the low-dose images. The contrast to noise ratio in the axial images was increased and was comparable to the full-dose images. Differentiation of anatomical structure in the PATEN images and corresponding quantitative perfusion parameter maps were preferred by two neuroradiologists compared to the simulated low-dose and TIPS results. The mean perfusion parameters calculated from the PATEN images agreed with those determined from full-dose data to within 12% and 20% for normal and diseased regions. In ECG-gated cardiac CT, where the dose had already been reduced by a factor of 5 in the reduced-dose phases, PATEN achieved a 53.8% noise reduction, which decreased the noise level in the reduced-dose phases close to that of the full-dose phases. In CT brain perfusion, a fourfold dose reduction was demonstrated to be achievable by PATEN filtering, which improved quantitative perfusion analysis. PATEN can be used to effectively reduce image noise to improve image quality, even when significant motion occurred between temporal samples.