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Adaptive Statistical Iterative Reconstruction Technique for Pulmonary CT

Posted Sep 30, 2010 Updated Apr 7, 2023
By Masahiro Yanagawa MD PhD , Osamu Honda MD PhD , Shigeyuki Yoshida MD , Ayano Kikuyama MD , Atsuo Inoue MD PhD , Hiromitsu Sumikawa MD PhD , Mitsuhiro Koyama MD PhD , Noriyuki Tomiyama MD PhD
11 min read

Rationale and Objectives

To evaluate thin-section computed tomography (CT) images of the lung reconstructed using adaptive statistical iterative reconstruction (ASIR) on standard- and reduced-dose CT.

Materials and Methods

Eleven cadaveric lungs were scanned by multidetector-row CT with two different tube currents (standard dose, 400 mA; reduced dose, 10 mA). The degree of ASIR was classified into six different levels: 0% (non-ASIR), 20%, 40%, 60%, 80%, and 100% (maximum-ASIR). The ASIR (20%, 60%, and 100%) images were compared with the ASIR (0%) images and assessed visually by three independent observers for image quality using a 7-point scale. The evaluation items included abnormal CT findings, normal lung structures, and subjective visual noise. The median scores assigned by the three observers were analyzed statistically. Quantitative noise was calculated by measuring the standard deviation in a circular region of interest on each selected image of ASIR (0%–100%).

Results

On standard-dose CT, the overall image quality significantly improved with increasing degree of ASIR ( P ≤ .009, Wilcoxon signed-ranks test with Bonferroni correction). As ASIR increased, however, intralobular reticular opacities and peripheral vessels tended to be obscure. On reduced-dose CT, the overall image quality of ASIR (100%) was significantly better than that of ASIR (20%) ( P ≤ .009). As ASIR increased, however, intralobular reticular opacities tended to be obscure. Using ASIR significantly reduced subjective and quantitative image noise on both standard- and reduced-dose CT ( P < .001, Bonferroni/Dunn’s method).

Conclusion

ASIR improves the image quality by decreasing image noise. Maximum-ASIR may be needed for improving image quality on highly reduced-dose CT. However, excessive ASIR may obscure subtle shadows.

Multidetector row computed tomography (MDCT), which is now incorporated into daily clinical practice, is a valuable tool for the evaluation of lung disease . It enables simultaneous reconstruction of thin and thick slices from the same raw data acquired from a single series, as well as the rapid scanning of a large longitudinal volume with high z-axis resolution . MDCT equipped with more rapid gantry rotation and more detector arrays has resulted in enhanced image quality by improving temporal resolution. The most recent development in the next generation of MDCT scanners is the introduction of garnet detectors. Garnet gemstone scintillators are configured to emit fluorescence when irradiated with x-rays, and have a primary decay time of only 30 nanoseconds, which is 100 times faster than that of conventional scintillator material. Such scintillators have afterglow levels that are only 25% of those of conventional scintillator materials. The most advantageous feature of MDCT with garnet detectors is its vastly improved spatial resolution, which allows smaller items or features to be distinguished in a transverse CT image and enables high image quality to be obtained even for lower radiation exposure .

Although improvements in temporal or spatial resolution will enhance CT image quality, the choice of reconstruction algorithm also affects image quality. MDCT with garnet detectors can employ adaptive statistical iterative reconstruction (ASIR). Iterative reconstruction, which is already used for image reconstruction in positron emission tomography and single photon emission CT, is a reconstruction algorithm whereby image data are corrected with an assortment of models . ASIR is a newly developed reconstruction algorithm for CT based on the iterative reconstruction algorithm. ASIR was developed in which only one corrective model is used to address image noise. This technique is used to solve one of the primary problems of dose reduction for CT with the conventional filtered back-projection algorithm. By partially correcting for the fluctuations in projection measurement because of limited photon statistics, ASIR algorithm enables a time-efficient reduction in the pixel variance that is statistically unlikely to be representative of anatomic features, with essentially no tradeoff in spatial resolution . It is expected that ASIR will provide higher CT image quality with lower noise, and will enable reconstruction of precise and clear images from reduced-dose raw data . It is thought that the use of ASIR will further improve image quality; however, to the best of our knowledge, no previous study has evaluated image quality of MDCT of the lung using ASIR. The aim of the present study was to evaluate thin-section CT images reconstructed using ASIR on standard- and reduced-dose CT, and to compare ASIR and non-ASIR images.

Materials and methods

Cadaveric Lungs and Imaging

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Subjective Image Analysis

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Objective Image Analysis

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Statistical Analysis

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Results

Image Quality for Abnormal Findings on Standard- and Reduced-dose CT Images

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Table 1

The Statistical Results of Image Quality for Overall Abnormal CT Findings and GGO on Standard- and Reduced-dose CT Images

Abnormal CT Findings Score Value Standard-dose (400 mA) Overall GGO Degree of ASIR (%) Mean ± SD (a) ASIR (20%) 4.02 ± 0.07 4.05 ± 0.13 (b) ASIR (60%) 4.88 ± 0.65 4.95 ± 0.23 (c) ASIR (100%) 5.61 ± 1.23 6.00 ± 0.43 Differences between two groups † P value (c) - (b) .009 ∗ .001 ∗ (c) - (a) <.001 ∗ .001 ∗ (b) - (a) .001 ∗ .009 ∗ Reduced-dose (10 mA) Overall GGO Degree of ASIR (%) Mean ± SD (a) ASIR (20%) 4.14 ± 0.26 4.19 ± 0.32 (b) ASIR (60%) 4.65 ± 0.84 5.33 ± 0.38 (c) ASIR (100%) 4.77 ± 0.69 5.33 ± 0.74 Differences between two groups † P value (c) - (b) .047 >.999 (c) - (a) .009 ∗ .012 ∗ (b) - (a) .028 .011 ∗

CT, computed tomography; ASIR, adaptive statistical iterative reconstruction; GGO, ground-glass opacity.

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Figure 1, Cadaveric lung with nonspecific interstitial pneumonia. Standard-dose CT images of 0.625-mm thickness are shown: ASIR (20%) (a) and ASIR (100%) (b) . The margins of GGO are clearer in (b) than in (a) . Visual image noise is lowest in (b) . In terms of conspicuity and detection of CT findings, the best overall image quality (for abnormal and normal CT findings) is seen in (b) . CT, computed tomography; ASIR, adaptive statistical iterative reconstruction; GGO, ground-glass opacity.

Figure 2, Cadaveric lung with pulmonary hemorrhage. Standard-dose CT images of 0.625-mm thickness are shown: ASIR (20%) (a) and ASIR (100%) (b) . Intralobular reticular opacities appear more obscure in (b) than in (a) . CT, computed tomography; ASIR, adaptive statistical iterative reconstruction.

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Figure 3, Cadaveric lung with nonspecific interstitial pneumonia: the same case as in Figure 1 . Reduced-dose CT images of 0.625-mm thickness are shown: ASIR (20%) (a) and ASIR (100%) (b) . The margins of GGO and bronchioles are clearer in (b) than in (a) . Visual image noise is lowest in (b) . In terms of the conspicuity and detection of CT findings, the best image quality is seen in (b) . CT, computed tomography; ASIR, adaptive statistical iterative reconstruction; GGO, ground-glass opacity.

Figure 4, Cadaveric lung with pulmonary hemorrhage: the same case as in Figure 2 . Reduced-dose CT images of 0.625-mm thickness are shown: ASIR (20%) (a) and ASIR (100%) (b) . Intralobular reticular opacities in (b) appear more obscure than in (a) . CT, computed tomography; ASIR, adaptive statistical iterative reconstruction.

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Image Quality for Normal Findings on Standard- and Reduced-dose CT images

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Table 2

The Statistical Results of Image Quality for Normal Findings on Standard- and Reduced-dose CT Images

Normal Findings Score value Standard-dose (400 mA) Overall Bronchi Central V Bronchiole Peripheral V Visual Noise Degree of ASIR (%) Mean ± SD (a) ASIR (20%) 4.07 ± 0.26 4.00 ± 0.00 4.00 ± 0.00 4.09 ± 0.30 4.09 ± 0.30 4.18 ± 0.40 (b) ASIR (60%) 4.85 ± 0.95 4.54 ± 0.52 4.63 ± 0.50 5.63 ± 0.67 3.73 ± 0.78 5.73 ± 0.46 (c) ASIR (100%) 5.33 ± 1.73 5.55 ± 0.68 5.45 ± 0.82 6.45 ± 0.82 2.36 ± 0.80 6.82 ± 0.40 Differences between two groups † P value (c) and (b) .006 ∗ .015 ∗ .049 .016 ∗ .009 ∗ .014 ∗ (c) and (a) <.001 ∗ .009 ∗ .012 ∗ .006 ∗ .008 ∗ .006 ∗ (b) and (a) <.001 ∗ .142 .091 .009 ∗ .207 .007 ∗ Reduced-dose (10 mA) Overall Bronchi Central V Bronchiole Peripheral V Visual Noise Degree of ASIR (%) Mean ± SD (a) ASIR (20%) 4.00 ± 0.00 4.00 ± 0.00 4.00 ± 0.00 4.00 ± 0.00 4.00 ± 0.00 4.00 ± 0.00 (b) ASIR (60%) 4.84 ± 0.73 4.55 ± 0.52 4.45 ± 0.52 5.00 ± 0.77 4.63 ± 0.80 5.55 ± 0.52 (c) ASIR (100%) 5.07 ± 1.21 4.73 ± 0.78 4.64 ± 0.67 5.09 ± 0.94 4.18 ± 1.25 6.73 ± 0.46 Differences between two groups † P value (c) and (b) .158 .463 .361 .753 .262 .016 ∗ (c) and (a) <.001 ∗ .093 .115 .014 ∗ .610 .005 ∗ (b) and (a) <.001 ∗ .142 .224 .012 ∗ .049 .007 ∗

ASIR, adaptive statistical iterative reconstruction; central V, central vessels; peripheral V, peripheral vessels.

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Figure 5, Cadaveric lung with nonspecific interstitial pneumonia: a different CT image slice of the case same as in Figure 1 . Standard-dose CT images of 0.625-mm thickness are shown: ASIR (20%) (a) and ASIR (100%) (b) . Peripheral vessels (arrows) in (b) appear more obscure than in (a) . CT, computed tomography; ASIR, adaptive statistical iterative reconstruction.

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Quantitative Noise Measurements

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Figure 6, (a) Quantitative noise measurements (mean ± SD) on standard-dose CT images. ASIR (0%) is a non-ASIR image reconstructed using a filtered back-projection algorithm, while ASIR (100%) is an image reconstructed using ASIR to the maximum: ASIR (0%) (11.04 ± 2.89), ASIR (20%) (9.22 ± 2.66), ASIR (40%) (7.75 ± 2.19), ASIR (60%) (5.90 ± 1.74), ASIR (80%) (4.46 ± 1.58), and ASIR (100%) (3.12 ± 1.09). There are significant differences with respect to quantitative noise among all groups ( P < .001). (Ref. SD = standard deviation, ASIR = adaptive statistical iterative reconstruction). (b) Quantitative noise measurements (mean ± SD) on reduced-dose CT images: ASIR (0%) (43.53 ± 3.93), ASIR (20%) (40.29 ± 3.84), ASIR (40%) (36.93 ± 3.92), ASIR (60%) (33.98 ± 4.79), ASIR (80%) (31.02 ± 4.49), and ASIR (100%) (28.05 ± 5.47). There are significant differences with respect to quantitative noise among all groups ( P < .001). CT, computed tomography; ASIR, adaptive statistical iterative reconstruction; SD, standard deviation.

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Discussion

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Academic Radiology, Volume 17, Issue 10
Journals General Radiology
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