Iterative reconstruction reduces abdominal CT dose

doi:10.1016/j.ejrad.2011.04.021

European Journal of Radiology

Volume 81, Issue 7, July 2012, Pages 1483-1487

https://doi.org/10.1016/j.ejrad.2011.04.021 Get rights and content

Abstract

Objective

In medical imaging, lowering radiation dose from computed tomography scanning, without reducing diagnostic performance is a desired achievement. Iterative image reconstruction may be one tool to achieve dose reduction. This study reports the diagnostic performance using a blending of 50% statistical iterative reconstruction (ASIR) and filtered back projection reconstruction (FBP) compared to standard FBP image reconstruction at different dose levels for liver phantom examinations.

Methods

An anthropomorphic liver phantom was scanned at 250, 185, 155, 140, 120 and 100 mA s, on a 64-slice GE Lightspeed VCT scanner. All scans were reconstructed with ASIR and FBP. Four readers evaluated independently on a 5-point scale 21 images, each containing 32 test sectors. In total 672 areas were assessed. ROC analysis was used to evaluate the differences.

Results

There was a difference in AUC between the 250 mA s FBP images and the 120 and 100 mA s FBP images. ASIR reconstruction gave a significantly higher diagnostic performance compared to standard reconstruction at 100 mA s.

Conclusion

A blending of 50–90% ASIR and FBP may improve image quality of low dose CT examinations of the liver, and thus give a potential for reducing radiation dose.

Section snippets

An anthropomorphic liver phantom

A custom made anthropomorphic upper abdomen phantom already designed for ROC studies of the detectability of liver lesions was used in this study [8], [9]. There are 4 liver tissue equivalent inserts in the phantom. Each of these inserts is divided into eight sectors. Half of the sectors contain cavities with diameters ranging from 2 mm to 7 mm. Theses cavities were filled with water to simulate low density liver lesions (Fig. 1). A total of 32 test sectors were evaluated in each phantom image.

Diagnostic performance at different dose levels

In Table 1 diagnostic performance for FBP reconstruction and with blending of ASIR reconstruction for all readers at all dose levels is presented. Comparison of AUC between different dose levels and different reconstruction methods are presented in Table 2.

For the 50% ASIR reconstructed images at different dose levels, no difference in AUC was detected compared to the full dose FBP reconstructed, except for 100 mA s (Fig. 2). This may indicate that the diagnostic performance is the same up to a

Discussion

In order to improve image quality and reduce the doses from CT examinations, all CT manufacturers recently introduced a version of iterative reconstruction algorithms. The results from this study indicate that it may be possible reducing the CT doses up to 50% and still maintain the diagnostic performance in the images using ASIR reconstruction.

Our results are corresponding to results reported in other studies [4], [5], [6], [7]. Singh et al. indicated that ASIR both lowered image noise and

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It is assumed that this correlation is diminished due to IR not being available. This would have had an impact on image noise as seen in many previous studies on different reconstructing methods.41–43 This is an extremely useful finding especially when having to justify the procurement of a new scanner.
The need to continually optimise CT protocols is essential to ensure the lowest possible radiation dose for the clinical task and individual patient. The aim of this study was to explore the effect of reducing effective mAs on nodule detection and radiation dose across six scanners.
An anthropomorphic chest phantom was scanned using a low-dose chest CT protocol, with the effective mAs lowered to the lowest permissible level. All other acquisition parameters remained consistent. Images were evaluated by five radiologists to determine their sensitivity in detecting six simulated nodules within the phantom. Image noise was calculated together with DLP.
The lowest possible mAs achievable ranged from 7 to 19 mAs. The two highest mAs setting (17 mAs + 19 mAs) had kV modulation enabled (100 kV instead of 120 kV) which consequently resulted in a higher nodule detection rate. Overall nodule detection averaged at 91% (range 80–97%). Out of a possible 180 nodules, 16 were missed, with 12 of those 16 being the same nodule. Noise was double for the Somatom Sensation scanner when compared to the others; however, this scanner did not have iterative reconstruction and it was installed over 10 years ago. There was a strong correlation between image noise and scanner age.
This study highlighted that nodules can be detected at very low effective mAs (<20 mAs) but only when other acquisition parameters are optimised i.e. iterative reconstruction and kV modulation. Nodule detection rates were affected by nodule location and image noise.
This study consolidates previous findings on how to successfully optimise low-dose chest CT. It also highlights the difficulty with standardisation owing to factors such as scanner age and different vendor attributes.
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Image-based noise reduction techniques are useful because they can be applied across various computed tomography (CT) scanner models from different vendors, regardless of the iterative reconstruction availability. The purpose of this study was to propose a 3-dimensional cross-directional bilateral filter (3D-CDBF) and compare the edge-preserving noise reduction on low-dose CT images to a model-based iterative reconstruction (MBIR).
The 3D-CDBF comprises a bilateral filter and a smoothing filter applied in range filtering. The filtering process was applied with four iterations using empirically determined parameters that yielded the best tradeoff between noise reduction and edge preservation for a very low radiation dose of 2.5 mGy. In-plane and z-directional edge preservation performances for low-contrast rod phantoms (60 Hounsfield units) were compared to a clinically available MBIR and a conventional 3D bilateral filter (3D-BF), using task-based spatial resolution (task-based transfer function: TTF) and slice thickness. Moreover, the noise power spectra (NPS) were compared. Furthermore, performance was compared on abdominal CT images acquired from volunteers at 2.5 mGy (approved by our institutional review board).
In phantom tests, 3D-CDBF provided 28.5% higher spatial resolution at 50%TTF compared to MBIR. Moreover, total NPS was lower, while the slice thickness (z-axis resolution) was slightly broader than that achieved by MBIR (0.99 mm vs. 0.92 mm). 3D-BF was inferior to both 3D-CDBF and MBIR in all measurements. Consistent with phantom results, 3D-CDBF significantly reduced noise on abdominal images compared to MBIR (P < 0.001), exhibiting better preservation of organ edges.
This 3D-CDBF may provide superior edge preserving noise reduction of low-dose CT images compared to currently available MBIR.
Correlation of size-dependent conversion factor and body-mass-index using size-specific dose estimates formalism in CT examinations
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The aim of this investigation is to establish the relationship between the size-dependent conversion factor (f_size) and the body-mass-index (BMI) and to test whether BMI can be substituted for the conventionally used patients’ anterior-posterior (AP) and lateral (LAT) dimensions for calculation of f_size. By calculating f_size on the basis of BMI instead of the AP and LAT measurements, size-specific dose estimates (SSDE) could be determined prior to image acquisition.
Our institute utilizes a dose monitoring software to record radiation exposure during CT examinations. The datasets gathered during each examination contain information regarding the scan protocol, the volumetric computed tomography dose index (CTDI_vol), SSDE and BMI. f_size is traditionally calculated through measurement of AP and LAT dimensions. In this work, the dose monitoring system calculates AP and LAT diameters at the middle of scout views. For purpose of this investigation, we used data from 13544 patients who underwent CT examinations of the torso, head or knee (both) to compare f_size as calculated from the AP and LAT dimensions to f_size calculated as a function of BMI.
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The mean and median kappa values were “good” for both techniques at 50% dose, whereas the values were “poor” for both techniques at 20% dose, without any significant difference between the two techniques. As previously reported (6–9,13,14,16,18,19,21–23,26–29), IR algorithms enable a lower radiation dose for body CT acquisitions while preserving image quality. An evaluation of the 50% dose CT protocol by our four readers confirmed these findings, as diagnostic confidence was maintained and the subjective image quality of the reduced-dose images was still above average when compared to the reference, 100% dose images.
To compare adaptive statistical iterative reconstruction (ASIR) and model-based iterative reconstruction (MBIR) algorithms for reduced-dose computed tomography (CT).
Forty-four young oncology patients (mean age 30 ± 9 years) were included. After routine thoraco-abdominal CT (dose 100%, average CTDI_vol 9.1 ± 2.4 mGy, range 4.4–16.9 mGy), follow-up CT was acquired at 50% (average CTDI_vol 4.5 ± 1.2 mGy, range 2.2–8.4 mGy) in 29 patients additionally at 20% dose (average CTDI_vol 1.9 ± 0.5 mGy, range 0.9–3.4 mGy). Each reduced-dose CT was reconstructed using both ASIR and MBIR. Four radiologists (two juniors and two seniors) blinded to dose and technique read each set of CT images regarding objective and subjective image qualities (high- or low-contrast structures), subjective noise or pixilated appearance, diagnostic confidence, and lesion detection.
At all dose levels, objective image noise was significantly lower with MBIR than with ASIR (P < 0.001). The subjective image quality for low-contrast structures was significantly higher with MBIR than with ASIR (P < 0.001).
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Studies on iterative reconstruction techniques on computed tomographic (CT) scanners show reduced noise and changed image texture. The purpose of this study was to address the possibility of dose reduction and improved conspicuity of lesions in a liver phantom for different iterative reconstruction algorithms. An anthropomorphic upper abdomen phantom, specially designed for receiver operating characteristic analysis was scanned with 2 different CT models from the same vendor, GE CT750 HD and GE Lightspeed VCT. Images were obtained at 3 dose levels, 5, 10, and 15 mGy, and reconstructed with filtered back projection (FBP), and 2 different iterative reconstruction algorithms; adaptive statistical iterative reconstruction and Veo. Overall, 5 interpreters evaluated the images and receiver operating characteristic analysis was performed. Standard deviation and the contrast to noise ratio were measured. Veo image reconstruction resulted in larger area under curves compared with those adaptive statistical iterative reconstruction and FBP image reconstruction for given dose levels. For the CT750 HD, iterative reconstruction at the 10 mGy dose level resulted in larger or similar area under curves compared with FBP at the 15 mGy dose level (0.88-0.95 vs 0.90). This was not shown for the Lightspeed VCT (0.83-0.85 vs 0.92). The results in this study indicate that the possibility for radiation dose reduction using iterative reconstruction techniques depends on both reconstruction technique and the CT scanner model used.
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To investigate whether dose reduction via adaptive statistical iterative reconstruction (ASIR) affects image quality and diagnostic accuracy in neuroendocrine tumor (NET) staging.
A total of 28 NET patients were enrolled in the study. Inclusion criteria were histologically proven NET and visible tumor in abdominal computed tomography (CT). In an intraindividual study design, the patients underwent a baseline CT (filtered back projection, FBP) and follow-up CT (ASIR 40%) using matched scan parameters. Image quality was assessed subjectively using a 5-grade scoring system and objectively by determining signal-to-noise ratio (SNR) and contrast-to-noise ratios (CNRs). Applied volume computed tomography dose index (CTDI_vol) of each scan was taken from the dose report.
ASIR 40% significantly reduced CTDI_vol (10.17 ± 3.06 mGy [FBP], 6.34 ± 2.25 mGy [ASIR] (p < 0.001) by 37.6% and significantly increased CNRs (complete tumor-to-liver, 2.76 ± 1.87 [FBP], 3.2 ± 2.32 [ASIR]) (p < 0.05) (complete tumor-to-muscle, 2.74 ± 2.67 [FBP], 4.31 ± 4.61 [ASIR]) (p < 0.05) compared to FBP. Subjective scoring revealed no significant changes for diagnostic confidence (5.0 ± 0 [FBP], 5.0 ± 0 [ASIR]), visibility of suspicious lesion (4.8 ± 0.5 [FBP], 4.8 ± 0.5 [ASIR]) and artifacts (5.0 ± 0 [FBP], 5.0 ± 0 [ASIR]). ASIR 40% significantly decreased scores for noise (4.3 ± 0.6 [FBP], 4.0 ± 0.8 [ASIR]) (p < 0.05), contrast (4.4 ± 0.6 [FBP], 4.1 ± 0.8 [ASIR]) (p < 0.001) and visibility of small structures (4.5 ± 0.7 [FBP], 4.3 ± 0.8 [ASIR]) (p < 0.001).
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View full text

Iterative reconstruction reduces abdominal CT dose

Abstract

Objective

Methods

Results

Conclusion

Section snippets

An anthropomorphic liver phantom

Diagnostic performance at different dose levels

Discussion

Radiol Clin N Am

Acad Radiol

Computed tomography – an increasing source of radiation exposure

N Engl J Med

Low-tube-voltage, high-tube-current multi-detector abdominal CT: improved image quality and decreased radiation dose with adaptive statistical iterative reconstruction algorithm – initial clinical experience

Radiology

Abdominal CT: comparison of adaptive statistical iterative and filtered back projection reconstruction techniques

Radiology

Diffuse lung disease: CT of the chest with adaptive statistical iterative reconstruction technique

Radiology

Reducing abdominal CT radiation dose with adaptive statistical iterative reconstruction technique

Invest Radiol